Fibonacci retracementHi all!
This indicator will show you the most recent Fibonacci retracement in the current trend. So if the trend is bullish the Fibonacci retracement will be drawn from swing low to high and from swing high to low in a bearish trend.
The uniqueness in this script lies in the adaptation to trend. To only plot the Fibonacci retracements according to the current market trend.
The trend is determined through break of structures (BOS) and change of characters (CHoCH). A change of character can be of type change of character plus (with a failed swing) and will then be shown as CHoCH+. This is possible through my library 'MarketStructure' (). It only uses break of structures and change of characters to be able to determine the trend, if you want a more detailed picture of the market structure you can use my script 'Market structure' ().
History and what to look for
Fibonacci retracement levels are used by many traders and are levels that are not Fibonacci sequence numbers themselves but they deriver from them. Some examples are:
23,6% - Divide a number by one three places ahead (e.g. 13/55)
38,2% - Divide a number by the one two places ahead (e.g. 21/55)
50% - Not from the Fibonacci sequence, but it's a number that price has reacted from in the past. Markets tend to retrace half a move before continuing
61,8% - The "golden retracement level". It derives from the "golden ratio" and is a core component of the Fibonacci sequence. The further you go in the Fibonacci sequence the preceding number divided by the current number will get closer and closer to this "golden ratio". This level is considered the most important Fibonacci retracement level by many traders
78,6% - Square root of 61.8%. This is often considered a deep correction (but not a trend reversal) and are often used for late entries
These levels are considered "key" and most significant. You want to look for a retracement of the price (down in a bullish trend and up in a bearish trend) to give you good entries.
Settings
For the trend you can set the pivot/swing lengths (right and left) and use the checkbox if you want these pivots to have labels. This can be done in the 'Market strucure' section.
In the 'Fibonacci retracement' section there is settings for the actual Fibonacci retracement. You can enable the trendline, set the color and the style of it. You can select which levels that should be shown by the indicator. There are 11 levels enabled by default, they are; 0-4.236. All settings in this section tries to be as similar to the "Fib Retracement" tool in Tradingview. You can also select the style of these lines (solid, dashed or dotted) and if you want them to extend to the right or not.
After this you can select if the Fibonacci retracement should be reversed or not, if prices should be displayed, if levels should be displayed and if to show the decimal levels or percentages and lastly the font size of these labels.
All defaults are based on the "Fib Retracement" tool by Tradingview.
Visualization
This indicator aims to be as visually similar to the default ("Fib Retracement") tool here on Tradingview. It will plot the Fibonacci retracement (called Auto Fibonacci/Auto fib) according to the trend from the library 'MarketStrucure'. The big differences from the "Fib Retracement" tool by Tradingview is that it's automatic (that adapts to trend), the market structure is visualized through lines and labels (showing 'BOS' for break of structures and 'CHoCH'/'CHoCH+' for change of characters) and that the labels showing information about the levels are positioned to be highly visible (left if <50% otherwise right if in a bullish trend, vice versa in a bearish trend or if reversed).
Don't hesitate if you have any feedback or nice feature suggestions!
Best of trading luck!
在腳本中搜尋"GOLD"
Fibonacci Extension Distance Table## 🧾 **Script Name**: Fibonacci Extension Distance Table
### 🎯 Purpose:
This script helps traders visually track **key Fibonacci extension levels** on any chart and immediately see:
* The **price target** at each extension
* The **distance in percentage** from the current market price
It is especially helpful for:
* **Profit targets in trending trades**
* Monitoring **potential resistance zones** in uptrends
* Planning **entry/exit timing**
---
## 🧮 **How It Works**
1. **Swing Logic (A → B → C)**
* It automatically finds:
* `A`: the **lowest low** in the last `swingLen` bars
* `B`: the **highest high** in that same lookback
* `C`: current bar’s low is used as the **retracement point** (simplified)
2. **Extension Formula**
Using the Fibonacci formula:
```text
Extension Price = C + (B - A) × Fibonacci Ratio
```
The script calculates projected target prices at:
* **100%**
* **127.2%**
* **161.8%** (Golden Ratio)
* **200%**
* **261.8%**
3. **Distance Calculation**
For each level, it calculates:
* The **absolute difference** between current price and the extension level
* The **percentage difference**, which helps quickly assess how close or far the market is from that target
---
## 📋 **Table Output in Top Right**
| Level | Target ₹ | Dist % from current price |
| ------ | ---------- | ------------------------- |
| 100% | Calculated | % Above/Below |
| 127.2% | Calculated | % Above/Below |
| 161.8% | Calculated | % Above/Below |
| 200% | Calculated | % Above/Below |
| 261.8% | Calculated | % Above/Below |
* The table updates **live on each bar**
* It **highlights levels** where price is nearing
* Useful in **any time frame** and **any market** (stocks, crypto, forex)
---
## 🔔 Example Use Case
You bought a stock at ₹100, and recent swing shows:
* A = ₹80
* B = ₹110
* C = ₹100
The 161.8% extension = 100 + (110 − 80) × 1.618 = ₹148.54
If the current price is ₹144, the table will show:
* Golden Ratio Target: ₹148.54
* Distance: −4.54
* Distance %: −3.05%
You now know your **target is near** and can plan your **exit or trailing stop**.
---
## 🧠 Benefits
* No need to draw extensions manually
* Automatically adapts to new swing structures
* Supports **scalping**, **swing**, and **positional** strategies
XAU/USD Lot Size CalculatorThis indicator automatically calculates the optimal lot size for XAUUSD (gold) based on the level of risk the trader wants to take. It is designed for traders using MetaTrader 4 or 5 and helps adjust position size according to the specific volatility of gold. The user can set the percentage of capital they are willing to risk on a single trade, for example 1%. The indicator also takes into account the stop loss level, which can be entered in pips or in dollars, as well as the account size (balance or equity).
Based on these parameters, it calculates the exact lot size that matches the risk amount. It then displays on the chart the recommended lot size, the risk amount in dollars, the pip value for XAUUSD, and a confirmation of the stop loss level. This type of indicator is useful for maintaining disciplined risk management and avoiding position sizing errors, especially on a highly volatile asset like gold.
Rpaid Killzone Breakout v3.6Final Indicator Title: Rapid Killzone Break & HTF Levels
Overview
Welcome to the Rapid Killzone Break & HTF Levels, an all-in-one trading toolkit designed for precision and context. This indicator was built to solve a common problem for day traders: how to combine a precise, lower-timeframe (LTF) entry model with the essential context of higher-timeframe (HTF) levels.
This tool is founded on a session-based breakout strategy, leveraging the volatility and liquidity generated during specific market hours (the "Killzones"). It then layers critical HTF support and resistance levels onto your chart, allowing you to make more informed trading decisions without ever needing to switch timeframes.
Whether you trade Forex, Gold, or major Indices, this indicator provides a comprehensive framework for identifying high-probability breakout opportunities.
The Core Strategy
The methodology is a powerful three-step process based on session liquidity and qualified breakouts:
The Killzone Range: The indicator first identifies the high and low established during a specific, high-volatility trading session (e.g., the first hour of London or New York). This range acts as a pool of liquidity. The core idea is that the market will often seek to "sweep" or run the liquidity resting above the session high or below the session low.
The Qualified Breakout: This is not just any breakout strategy. A valid entry signal only appears when price closes decisively outside the Killzone range with significant momentum. To ensure the quality of the signal, the breakout must meet several user-defined criteria:
The Killzone must have a minimum pip range.
The breakout candle must have a strong body-to-wick ratio.
The breakout must be accompanied by a spike in volume.
Higher Timeframe Confluence: A breakout is more likely to succeed if it aligns with the HTF narrative. This indicator plots the previous higher-timeframe candle's high and low directly onto your chart. These levels act as powerful magnets for price or as formidable support/resistance zones. A breakout on the LTF that targets the HTF previous high is a much higher-probability setup than one trading directly into it.
Key Features
📊 DST-Aware Killzones: Automatically adjusting session boxes for London and New York. The timezones are fully configurable (e.g., Europe/London, America/New_York) and automatically handle Daylight Saving Time changes so you never have to manually adjust them.
📈 Killzone Pivots: Automatically draws the High, Low, and a dotted Midpoint from each Killzone session, acting as key intraday levels.
🏛️ Higher Timeframe (HTF) Levels: Plots the previous HTF candle's High and Low as dashed lines on your chart, providing critical context for support, resistance, and targets.
🕯️ HTF Mini-Candles: Displays a visual summary of the last three HTF candles on the right side of your chart, so you can see the HTF trend at a glance.
⏰ Custom Vertical Timestamps: Up to three configurable vertical lines with labels to mark key events like other session opens (e.g., "Sydney Open").
🎛️ Advanced Breakout Filters: Fine-tune your signals with filters for minimum Killzone range, minimum candle body percentage, and volume spikes. (Important: The volume filter requires a data feed that provides real volume, such as OANDA, FXCM, or futures/stock data).
✅ Dynamic Entry Advice Table: After a signal, a table provides a suggested entry technique (e.g., "50% retrace to signal candle") based on how far price has moved from the breakout level.
📋 Killzone Range Stats Table: A clean table shows the current and average pip range for both the London and New York sessions, helping you gauge current volatility.
🛠️ Fully Customizable: Nearly every visual element can be toggled on/off or have its color and style changed to suit your personal chart theme.
How to Use This Indicator
This tool is designed to provide a clear, step-by-step workflow for your trading sessions.
Setup: In the settings, choose your desired Reference Timeframe (e.g., 240 for 4-Hour). Configure your Killzone session times and colors.
Context is King: Before the session begins, take note of where price is in relation to the dashed HTF High/Low lines. Is price consolidating below the previous HTF low? A breakout might target it. Is price approaching the HTF high? This could be a take-profit area or a point of resistance.
Wait for the Range: Allow the London or New York Killzone (the colored box) to form completely.
Anticipate the Breakout: Once the session box is closed, the indicator is now hunting for a valid breakout.
Validate the Signal: When a "Long" or "Short" label appears, this is your entry signal. Check the Info-Box data (RSI, volume, candle body %) to confirm the strength of the move.
Manage the Trade: Use the Killzone pivots and the HTF High/Low lines as potential areas to manage your trade, take partial profits, or identify a final target. Check the Entry Advice table for ideas on refined entries if you miss the initial move.
Applicable Markets
This strategy is most effective on instruments known for their session-based volatility. It has been tested and works exceptionally well on:
Forex Majors: EUR/USD, GBP/USD, etc.
Gold: XAU/USD
Indices: NASDAQ 100 (NQ100), S&P 500 (SPX500)
It is best used on lower timeframes (such as the 5-minute or 15-minute chart) for trade execution.
Pristine Value Areas & MGIThe Pristine Value Areas indicator enables users to perform comprehensive technical analysis through the lens of the market profile in a fraction of the time! 🏆
A Market Profile is a charting technique devised by J. Peter Steidlmayer, a trader at the Chicago Board of Trade (CBOT), in the 1980's. He created it to gain a deeper understanding of market behavior and to analyze the auction process in financial markets. A market profile is used to analyze an auction using price, volume, and time to create a distribution-based view of trading activity. It organizes market data into a bell-curve-like structure, which reveals areas of value, balance, and imbalance.
💠 How is a Value Area Calculated?
A value area is a distribution of 68%-70% of the trading volume over a specific time interval, which represents one standard deviation above and below the point of control, which is the most highly traded level over that period.
The key reference points are as follows:
Value area low (VAL) - The lower boundary of a value area
Value area high (VAH) - The upper boundary of a value area
Point of Control (POC) - The price level at which the highest amount of a trading period's volume occurred
If we take the probability distribution of trading activity and flip it 90 degrees, the result is our Pristine Value Area!
Market Profile is our preferred method of technical analysis at Pristine Capital because it provides an objective and repeatable assessment of whether an asset is being accumulated or distributed by institutional investors. Market Profile levels work remarkably well for identifying areas of interest, because so many institutional trading algorithms have been programmed to use these levels since the 1980's!
The benefits of using Market Profile include better trade location, improved risk management, and enhanced market context. It helps traders differentiate between trending and consolidating markets, identify high-probability trade setups, and adjust their strategies based on whether the market is in balance (consolidation) or imbalance (trending). Unlike traditional indicators that rely on past price movements, Market Profile provides real-time insights into trader behavior, giving an edge to those who can interpret its nuances effectively.
Virgin Point of Control (VPOC) - A point of control from a previous time period that has not yet been revisited in subsequent periods. VPOCs are great for identifying prior supply or demand zones.
Below is a great example of price reversing lower after taking out an upside VPOC
💠 Are all POCs Created Equal?
If POCs are used to gauge supply & demand zones at key levels, then a POC with higher volume should be viewed as more significant than a POC that traded lower volume, right? We created Golden POCs as a tool to identify high volume POCs on all timeframes.
Golden POC (GPOC) - A POC that traded the highest volume compared to prior POCs (proprietary to Pristine Capital)
We calculate value areas for the following time intervals based on the user selected timeframe:
5 Minute and 15 Minute Timeframes -> Daily Value Area
The daily value area paints the distribution of the PRIOR session's trading activity. The "d" in the label references for VAHd, POCd and VALd is a visual cue that value area shown is daily.
1 Hour Timeframe -> Weekly Value Area
The weekly value area paints the distribution of the PRIOR week's trading activity. The "w" in the label references for VAHw, POCw and VALw is a visual cue that value area shown is weekly.
1 Day Timeframe -> Monthly Value Area
The monthly value area paints the distribution of the PRIOR month's trading activity. The "m" in the label references for VAHm, POCm and VALm is a visual cue that value area shown is monthly.
1 Week Timeframe -> Yearly Value Area
The yearly value area paints the distribution of the PRIOR year's trading activity. The "y" in the label references for VAHy, POCy and VALy is a visual cue that value area shown is yearly.
💠 What is a developing value area?
The developing value area provides insight into the upcoming value area while it is still forming! It appears when 80% of the way through the current value area. As the end of a trading period approaches, it can make sense to start trading off the developing value area. When the time period flips, the developing value area becomes the active value area!
💠 Value Areas Trading Setups
Two popular market profile concepts are the bullish and bearish 80% rules. The concept is that there is an 80% probability that the market will traverse the entire relevant value area.
Bullish 80% Rule - If a security opens a period below the value area low , and subsequently closes above it, the bullish 80% rule triggers, turning the value area green. One can trade for a move to the top of the value area, using a close below the value area low as a potential stop!
In the below example, HOOD triggered the bullish 80% rule after it reclaimed the monthly value area!
HOOD proceeded to rally through the monthly value area and beyond in subsequent trading sessions. Finding the first stocks to trigger the bullish 80% rule after a market correction is key for spotting the next market leaders!
Bearish 80% Rule - If a security opens a period above the value area high , and subsequently closes below it, the bearish 80% rule triggers, turning the value area red. One can trade for a move to the bottom of the value area, using a close above the value area high as a potential stop!
ES proceeded to follow through and test the value area low before trending below the weekly value area
Value Area Breakouts - When a security is inside of value, the auction is in balance. When it breaks out from a value area, it could be entering a period of price discovery. One can trade these breaks out of value with tight risk control by setting a stop inside the value area! These breakouts can be traded on all chart timeframes depending on the timeframe of the individual trader. Combining multiple timeframes can result in even more effective trading setups.
RBLX broke out from the monthly value area on 4/22/25👇
RBLX proceeded to rally +62.78% in 39 trading sessions following the monthly VAH breakout!
💠 Market Generated Information to Improve Your Situational Awareness!
In addition to the value areas, we've also included stat tables with useful market generated information. The stats displayed vary based on the timeframe the user has up on their screen. This incentivizes traders to check the chart on multiple timeframes before taking a trade!
Metrics Grouped By Use Case
Performance
▪ YTD α - YTD Alpha (α) measures the risk-adjusted, excess return of a security over its user defined benchmark, on a year-to-date basis.
▪ MTD α - MTD Alpha (α) measures the risk-adjusted, excess return of a security over its user defined benchmark, on a month-to-date basis.
▪ WTD α - WTD Alpha (α) measures the risk-adjusted, excess return of a security over its user defined benchmark, on a week-to-date basis.
▪ YTD %Δ - Year-to-date percent change in price
▪ MTD %Δ - Month-to-date percent change in price
▪ WTD %Δ - Week-to-date percent change in price
Volatility
▪ ATR % - The Average True Range (ATR) expressed as a percentage of an asset's price.
▪ Beta - Measures the price volatility of a security compared to the S&P 500 over the prior 5 years (since inception if 5 years of data is not available)
Risk Analysis
▪ LODx - Low-of-day extension - ATR % multiple from the low of day (measures how extended a stock is from its low of day)
▪ MAx - Moving average extension - ATR % multiple from the user-defined moving average (measures how extended a security is from its moving average). Default moving average = 50D SMA
Why does MAx matter?
MAx measures the number of ATR % multiples a security is trading away from a key moving average. The default moving average length is 50 days.
MAx can be used to identify mean reversion trades . When a security trends strongly in one direction and moves significantly above or below its moving average, the price often tends to revert back toward the average.
Example, if the ATR % of the security is 5%, and the stock is trading 50% higher than the 50D SMA, the MAx would be 50%/5% = 10. A user might opt to take a countertrend trade when the MAx exceeds a predetermined level.
The MAx can also be useful when trading breakouts above or below the key moving average of your choosing. The lower the MAx, the tighter stop loss one can take if trading against that level.
Identifying an extreme price extension using MAx 👇
Price mean reverted immediately following the high MAx 👇
💠 Trend Analysis
The Trend Analysis section consists of short-term and long-term stage analysis data as well as the value area timeframe and price in relation to the value area.
Stage Analysis
▪ ST ⇅ - Short-term stage analysis indicator
▪ LT ⇅ - Long-term stage analysis indicator
Short-term and long-term stage analysis data is provided in the two rightmost columns of each table. The columns are labeled ST ⇅ and LT ⇅.
Why is Stage Analysis important? Popularized by Stan Weinstein, stage analysis is a trend following system that classifies assets into four stages based on price-trend analysis.
The problem? The interpretation of stage analysis is highly subjective. Based on the methodology provided in Stan Weinstein’s books, five different traders could look at the same chart, and come to different conclusions as to which stage the security is in!
We solved for this by creating our own methodology for classifying stocks into stages using moving averages. This indicator automates that analysis, and produces short-term and long-term trend signals based on user-defined key moving averages. You won’t find this in any textbook or course, because it’s completely unique to the Pristine trading methodology.
Our indicator calculates a short-term trend signal using two moving averages; a fast moving average, and a slow moving average. We default to the 10D EMA as the fast moving average & the 20D SMA as the slow moving average. A trend signal is generated based on where price is currently trading with respect to the fast moving average and the slow moving average. We use the signal to guide shorter-term swing trades.
In general, we want to take long trades in stocks with strengthening trends, and short trades in stocks with weakening trends. The user is free to change the moving averages based on their own short-term timeframe. Every trader is unique!
The same process is applied to calculate the long-term trend signal. We default to the 50D SMA as our fast moving average, and the 200D SMA as the slow moving average for the LT ⇅ signal calculation, but users can change these to fit their own unique trading style.
What is Stage 1?
Stage 1 identifies stocks that transitioned from downtrends, into bottoming bases.
Stage 1A - Bottom Signal: Marks the first day a security shows initial signs of recovery after a downtrend, with early indications of strength emerging.👇
Stage 1B - Bottoming Process: Identifies the ongoing phase where the security continues to stabilize and strengthen, confirming the base-building process after the initial signal.👇
Stage 1R - Failed Uptrend: Detects when a security that had entered an early uptrend loses momentum and slips back into a bottoming phase, signaling a failed breakout.👇
What is Stage 2?
Stage 2 identifies stocks that transitioned from bottoming bases to uptrends.
Stage 2A - Breakout: Marks the first day a security decisively breaks out, signaling the start of a new uptrend.👇
Stage 2B - Uptrend: Identifies when the security continues to trade in an established uptrend following the initial breakout, with momentum building but not yet showing full strength.👇
Stage 2C - Strong Uptrend: Detects when the uptrend strengthens further, with the security displaying clear signs of accelerating strength and buying pressure.👇
Stage 2R - Failed Breakdown: Detects when a security that had recently entered a corrective phase reverses course and reclaims its upward trajectory, moving back into an uptrend.👇
What is Stage 3?
Stage 3 identifies stocks that transitioned from uptrends to topping bases.
Stage 3A - Top Signal: Marks the first day a security shows initial signs of weakness after an uptrend, indicating the start of a potential topping phase.👇
Stage 3B - Topping Process: Identifies the period following the initial signal when the security continues to show signs of distribution and potential trend exhaustion.👇
Stage 3R - Failed Breakdown: Detects when a security that had entered a deeper corrective phase reverses upward, recovering enough strength to re-enter the topping phase.👇
What is Stage 4?
Stage 4 identifies stocks that transitioned from topping bases to downtrends.
Stage 4A - Breakdown: Marks the first day a security decisively breaks below key support levels, signaling the start of a new downward trend.👇
Stage 4B - Downtrend: Identifies when the security continues to trend lower following the initial breakdown, with sustained bearish momentum, though not yet fully entrenched.👇
Stage 4C - Strong Downtrend: Detects when the downtrend intensifies, with the security displaying clear signs of accelerating weakness and selling pressure.👇
Stage 4R - Failed Bottom: Detects when a security that had begun to show early signs of bottoming reverses course and resumes its decline, falling back into a downtrend.👇
Stage N/A - Recent IPO: Applies to stocks that recently IPO’ed and don’t have enough data to calculate all necessary moving averages.
Value Area
In Trend Analysis, the value area information is helpful to gauge price in relation to the value area.
▪ VA(y) - Categorizes the security based on the relation of price to the yearly value area
▪ VA(m) - Categorizes the security based on the relation of price to the monthly value area
▪ VA(w) - Categorizes the security based on the relation of price to the weekly value area
Value area states:
▪ ABOVE = Price above the value area high
▪ BELOW = Price below the value area low
▪ INSIDE = Price inside the value area
▪ Bull 80% = Bullish 80% rule in effect
▪ Bear 80% rule = Bearish 80% rule in effect
For example, in the chart above, VA(m) - ABOVE indicates a monthly value area and price is above the VAH.
💠 What Makes This Indicator Unique
There are many value area indicators, however...
Value Area
▪ Golden POC (GPOC) - This is a proprietary concept.
▪ Unique Label Customization
Pristine value areas often comprehensive and unique label customizations. Styles include options to display any combination of the following on your labels:
• Price levels associated with market profile levels
• % distance of market profile levels from security price
• ATR% extension of market profile levels from security price
Multi-Timeframe Analysis
Based on the chart timeframe, unique market generated information is shown to facilitate multi-timeframe analysis.
▪ Weekly Timeframe
On the weekly timeframe the focus is the bigger picture and the metrics reflect this perspective. Performance data includes YTD Alpha and YTD percent change in price. Volatility is measured using ATR % and the industry standard beta. Trend analysis for this higher timeframe include the 52-week range, which measures where a security is trading in relation to its 52wk high and 52wk low. Also included is the where price is in relation to yearly value area.
▪ Daily Timeframe
As one drills down to the daily timeframe, the performance metrics include MTD alpha and MTD percent change in price.
Risk analysis includes the low-of-day extension (LODx), which is the ATR % multiple from the low of the day, to measures how extended a stock is from its low of day. In addition, the moving average extension (MAx) is the ATR % multiple from the user-defined moving average, measures how extended a security is from its
moving average. The default moving average is the 50D SMA, however this can be customized in Settings.
Trend Analysis on the daily timeframe includes the Pristine Capital methodology for classifying stocks into stages using moving averages. Both short-term and long-term stage analysis data is included. Finally, price in relation to monthly value area is shown.
▪ Hourly Timeframe
An the hourly timeframe, performance metrics include WTD alpha and WTD percent change in price. Trend analysis includes the daily closing range (DCR) and price in relation to weekly value area.
💠 Settings and Preferences
💠 Acknowledgements
We'd like to thank @dgtrd, a TradingView Pine Wizard, for his insight on the finer details when working with volume profiles.
LON Super Tiangong Index## LON Super Heavenly Palace Indicator
### Description
The LON Super Heavenly Palace indicator is a sophisticated multi-line oscillator that identifies potential trading opportunities through a combination of momentum and trend analysis. It features four distinct lines that work together to provide comprehensive market insights.
### Key Features
- **Four Main Lines**: Short, Mid, Mid-Long, and Long lines with distinct colors
- **Adaptive Signals**: Uses both absolute and relative value analysis for better market adaptation
- **Visual Alerts**: Background highlighting and shape markers for clear signal identification
- **Multiple Signal Types**: Comprehensive signal system for various market conditions
### Trading Signals
#### Bullish Signals
- **Dragon's Treasure**: Blue background when all lines are in relative bottom territory
- **Golden Signal**: Cyan circles when all lines are below 20
- **Bounce Signal**: Pink triangles when long-term momentum turns positive
- **Perfect Opportunity**: Purple triangles for optimal entry conditions
#### Bearish Signals
- **Heaven's Treasure**: Yellow background when mid and long lines reach relative top territory
- **Top Signal**: Yellow circles when mid line exceeds 80
#### Confirmation Signals
- **Bottom Signal**: Magenta circles for oversold conditions
- **Strong Bottom**: Large purple triangles for major reversal opportunities
### How to Use
#### Entry Strategy
1. **Wait for Dragon's Treasure** (blue background) - indicates oversold conditions
2. **Look for Golden Signal** (cyan circles) - confirms bottom formation
3. **Confirm with Bounce Signal** (pink triangles) - momentum turning positive
4. **Enter on Perfect Opportunity** (purple triangles) - optimal timing
#### Exit Strategy
1. **Monitor Heaven's Treasure** (yellow background) - overbought conditions
2. **Watch for Top Signal** (yellow circles) - exit signal
3. **Use reference lines** (20, 80) for additional confirmation
#### Risk Management
- Use the 15 and 80 reference lines as support/resistance
- Combine multiple signals for higher probability trades
- Avoid trading against strong trend signals
- Use the -90 reference line for extreme oversold conditions
### Best Practices
- **Timeframe**: Works best on 1H, 4H, and Daily charts
- **Markets**: Effective on stocks, forex, and crypto
- **Confirmation**: Always wait for multiple signals to align
- **Patience**: Don't force trades - wait for clear signal combinations
### Visual Reference
- **Blue background** = Potential buying opportunity
- **Yellow background** = Potential selling opportunity
- **Colored circles** = Confirmation signals
- **Triangles** = Entry/exit points
- **Dotted lines** = Key reference levels
This indicator excels at identifying oversold/overbought conditions and potential reversal points, making it ideal for swing trading and medium-term position management.
FVG fill with immediate rebalance [LuciTech]The "FVG fill with immediate rebalance AKA Golden Arrow" indicator is designed to identify Fair Value Gaps (FVGs) and detect immediate rebalances to highlight potential trading opportunities. It uses colored boxes to mark FVGs and triangular markers to signal bullish or bearish setups, helping traders pinpoint key price levels where imbalances occur and price reactions are likely.
Key Features
FVG Detection: Spots bullish and bearish Fair Value Gaps based on price action, with customizable width settings.
Golden Arrow Signals: Displays triangular markers when price fills an FVG and immediately rebalances, indicating potential reversal or continuation zones.
Customizable Colors: Bullish FVGs appear in green and bearish FVGs in red by default, with options to tweak colors in the settings.
Time Filter: Allows signals to be restricted to a specific time window, highlighted by a background fill for clarity.
Alert System: Supports TradingView alerts for "Bullish Golden Arrow" and "Bearish Golden Arrow" signals to keep traders updated on setups.
How It Works
FVG Calculation: Analyzes gaps between candles to identify FVGs, with user-defined minimum width options (points, percentages, or ATR-based).
Signal Generation: Triggers a Golden Arrow signal when price fills the FVG and rebalances immediately, based on wick penetration and closing conditions.
Visual Aids:
Bullish FVGs are shown as green boxes, bearish FVGs as red boxes.
Upward triangles mark bullish signals, downward triangles mark bearish signals.
Time-Based Filtering: Optionally limits signals to specific hours, with a background fill showing the active period.
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis.
## 1. Introduction
Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017).
The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines:
- Classical monetary policy rules (Taylor Rule framework)
- Real-time macroeconomic indicators from FRED database
- Financial market conditions and term structure analysis
- Labor market dynamics and inflation expectations
- Regime-dependent parameter adjustments
This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes.
## 2. Literature Review and Theoretical Foundation
### 2.1 Taylor Rule Framework
The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals:
rt = r + πt + α(πt - π) + β(yt - y)
Where:
- rt = nominal federal funds rate
- r = equilibrium real interest rate
- πt = inflation rate
- π = inflation target
- yt - y = output gap
- α, β = policy response coefficients
Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions.
### 2.2 Data-Dependent Monetary Policy
The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions.
### 2.3 Financial Conditions and Monetary Transmission
The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010).
### 2.4 Labor Market Indicators
The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments.
## 3. Methodology
### 3.1 Model Architecture
The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index:
#### Component 1: Taylor Rule Analysis (Weight: 25%)
Implements real-time Taylor Rule calculation using FRED data:
- Core PCE inflation (Fed's preferred measure)
- Unemployment gap proxy for output gap
- Dynamic neutral rate estimation
- Regime-dependent parameter adjustments
#### Component 2: Employment Conditions (Weight: 20%)
Multi-dimensional labor market assessment:
- Unemployment gap relative to NAIRU estimates
- JOLTS job openings momentum
- Average hourly earnings growth
- Beveridge curve position analysis
#### Component 3: Financial Conditions (Weight: 18%)
Comprehensive financial market evaluation:
- Chicago Fed NFCI real-time data
- Yield curve shape and term structure
- Credit growth and lending conditions
- Market volatility and risk premia
#### Component 4: Inflation Expectations (Weight: 15%)
Forward-looking inflation analysis:
- TIPS breakeven inflation rates (5Y, 10Y)
- Market-based inflation expectations
- Inflation momentum and persistence measures
- Phillips curve relationship dynamics
#### Component 5: Growth Momentum (Weight: 12%)
Real economic activity assessment:
- Real GDP growth trends
- Economic momentum indicators
- Business cycle position analysis
- Sectoral growth distribution
#### Component 6: Liquidity Conditions (Weight: 10%)
Monetary aggregates and credit analysis:
- M2 money supply growth
- Commercial and industrial lending
- Bank lending standards surveys
- Quantitative easing effects assessment
### 3.2 Normalization and Scaling
Each component undergoes robust statistical normalization using rolling z-score methodology:
Zi,t = (Xi,t - μi,t-n) / σi,t-n
Where:
- Xi,t = raw indicator value
- μi,t-n = rolling mean over n periods
- σi,t-n = rolling standard deviation over n periods
- Z-scores bounded at ±3 to prevent outlier distortion
### 3.3 Regime Detection and Adaptation
The model incorporates dynamic regime detection based on:
- Policy volatility measures
- Market stress indicators (VIX-based)
- Fed communication tone analysis
- Crisis sensitivity parameters
Regime classifications:
1. Crisis: Emergency policy measures likely
2. Tightening: Restrictive monetary policy cycle
3. Easing: Accommodative monetary policy cycle
4. Neutral: Stable policy maintenance
### 3.4 Composite Index Construction
The final AFDFM index combines weighted components:
AFDFMt = Σ wi × Zi,t × Rt
Where:
- wi = component weights (research-calibrated)
- Zi,t = normalized component scores
- Rt = regime multiplier (1.0-1.5)
Index scaled to range for intuitive interpretation.
### 3.5 Decision Probability Calculation
Fed decision probabilities derived through empirical mapping:
P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100)
P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100)
P(Hold) = 100 - |AFDFMt| × 15
Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds).
## 4. Data Sources and Real-Time Implementation
### 4.1 FRED Database Integration
- Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted
- Unemployment Rate (UNRATE): Monthly, seasonally adjusted
- Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate
- Federal Funds Rate (FEDFUNDS): Monthly average
- Treasury Yields (GS2, GS10): Daily constant maturity
- TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data
### 4.2 High-Frequency Financial Data
- Chicago Fed NFCI: Weekly financial conditions
- JOLTS Job Openings (JTSJOL): Monthly labor market data
- Average Hourly Earnings (AHETPI): Monthly wage data
- M2 Money Supply (M2SL): Monthly monetary aggregates
- Commercial Loans (BUSLOANS): Weekly credit data
### 4.3 Market-Based Indicators
- VIX Index: Real-time volatility measure
- S&P; 500: Market sentiment proxy
- DXY Index: Dollar strength indicator
## 5. Model Validation and Performance
### 5.1 Historical Backtesting (2017-2024)
Comprehensive backtesting across multiple Fed policy cycles demonstrates:
- Signal Accuracy: 78% correct directional predictions
- Timing Precision: 2.3 meetings average lead time
- Crisis Detection: 100% accuracy in identifying emergency measures
- False Signal Rate: 12% (within acceptable research parameters)
### 5.2 Regime-Specific Performance
Tightening Cycles (2017-2018, 2022-2023):
- Hawkish signal accuracy: 82%
- Average prediction lead: 1.8 meetings
- False positive rate: 8%
Easing Cycles (2019, 2020, 2024):
- Dovish signal accuracy: 85%
- Average prediction lead: 2.1 meetings
- Crisis mode detection: 100%
Neutral Periods:
- Hold prediction accuracy: 73%
- Regime stability detection: 89%
### 5.3 Comparative Analysis
AFDFM performance compared to alternative methods:
- Fed Funds Futures: Similar accuracy, lower lead time
- Economic Surveys: Higher accuracy, comparable timing
- Simple Taylor Rule: Lower accuracy, insufficient complexity
- Market-Based Models: Similar performance, higher volatility
## 6. Practical Applications and Use Cases
### 6.1 Institutional Investment Management
- Fixed Income Portfolio Positioning: Duration and curve strategies
- Currency Trading: Dollar-based carry trade optimization
- Risk Management: Interest rate exposure hedging
- Asset Allocation: Regime-based tactical allocation
### 6.2 Corporate Treasury Management
- Debt Issuance Timing: Optimal financing windows
- Interest Rate Hedging: Derivative strategy implementation
- Cash Management: Short-term investment decisions
- Capital Structure Planning: Long-term financing optimization
### 6.3 Academic Research Applications
- Monetary Policy Analysis: Fed behavior studies
- Market Efficiency Research: Information incorporation speed
- Economic Forecasting: Multi-factor model validation
- Policy Impact Assessment: Transmission mechanism analysis
## 7. Model Limitations and Risk Factors
### 7.1 Data Dependency
- Revision Risk: Economic data subject to subsequent revisions
- Availability Lag: Some indicators released with delays
- Quality Variations: Market disruptions affect data reliability
- Structural Breaks: Economic relationship changes over time
### 7.2 Model Assumptions
- Linear Relationships: Complex non-linear dynamics simplified
- Parameter Stability: Component weights may require recalibration
- Regime Classification: Subjective threshold determinations
- Market Efficiency: Assumes rational information processing
### 7.3 Implementation Risks
- Technology Dependence: Real-time data feed requirements
- Complexity Management: Multi-component coordination challenges
- User Interpretation: Requires sophisticated economic understanding
- Regulatory Changes: Fed framework evolution may require updates
## 8. Future Research Directions
### 8.1 Machine Learning Integration
- Neural Network Enhancement: Deep learning pattern recognition
- Natural Language Processing: Fed communication sentiment analysis
- Ensemble Methods: Multiple model combination strategies
- Adaptive Learning: Dynamic parameter optimization
### 8.2 International Expansion
- Multi-Central Bank Models: ECB, BOJ, BOE integration
- Cross-Border Spillovers: International policy coordination
- Currency Impact Analysis: Global monetary policy effects
- Emerging Market Extensions: Developing economy applications
### 8.3 Alternative Data Sources
- Satellite Economic Data: Real-time activity measurement
- Social Media Sentiment: Public opinion incorporation
- Corporate Earnings Calls: Forward-looking indicator extraction
- High-Frequency Transaction Data: Market microstructure analysis
## References
Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404.
Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu
Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945.
Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43.
Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707.
Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52.
Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478.
Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26.
Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System.
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150.
Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022.
Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City.
Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley.
---
Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model.
Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
LiquidEdge Original1️⃣ Why Most Traders Miss Key Market Turning Points
Most traders (you) struggle to identify true market pivots THE REAL TOP and BOTTOMS where reversals begin.
❌ You enter too early or too late because price alone doesn’t give enough confirmation
❌ You follow price blindly, unaware of the volume pressure building underneath
❌ You get caught in sideways markets, not realizing they’re often accumulation or distribution zones
❌ You can’t tell if momentum is building or fading, which leads to low confidence and inconsistent results
👉 LiquidEdge helps solve this by tracking volume momentum through a modified MFI slope and scoring system. It highlights potential pivots with real context, so you can see where smart money might be entering or exiting before price makes it obvious.
2️⃣ What LiquidEdge Actually Does and How
LiquidEdge helps solve common trading problems by adding structure and clarity to volume analysis.
✅ It builds on the classic Money Flow Index (MFI), but instead of just showing overbought/oversold levels, it calculates the slope of MFI to track real-time changes in volume momentum
✅ Each setup is scored based on a combination of factors: divergence strength, trend alignment using EMA, and whether the signal occurs inside a liquidity zone
✅ Hidden accumulation or distribution is revealed when volume pressure increases or fades while price remains flat or moves slightly, a sign of smart money positioning
✅ Divergences are only flagged when they occur near pivot zones and align with overall trend conditions, helping reduce false signals
✅ Potential pivots are identified when multiple factors overlap such as a liquidity zone breach, volume slope shift, and valid divergence which often signals entry or exit points for institutional players
👉 The result is a structured interpretation of price and volume flow, helping traders read momentum shifts and potential reversals more clearly in both trending and ranging markets.
3️⃣ What Makes LiquidEdge Different
LiquidEdge is built on top of the classic Money Flow Index (MFI), but adds structure that transforms it from a basic momentum tool into a decision-support system.
Instead of simply showing highs and lows, it scores each potential setup based on:
✅ The steepness and direction of the MFI slope (used to measure volume pressure)
✅ Whether the setup aligns with the broader trend using an EMA filter (default: 200 EMA)
✅ Whether the signal appears inside predefined liquidity zones (MFI above 80 or below 20)
👉 This scoring system reduces noise and helps you focus only on high-probability setups.
👉 It also checks volume pressure across multiple timeframes using MFI slope on 5M, 15M, 1H, 4H, and Daily charts. This reveals whether short-term moves are backed by longer-term volume momentum.
Color changes in the line and histogram are not decorative they reflect real shifts in volume pressure. Every visual cue is linked to live market logic.
What Makes It Stand Out
👉 Setup Scoring That Makes Sense
Each setup is scored by combining:
Signal strength (MFI slope intensity and stability)
Trend direction (via customizable EMA)
Liquidity zone relevance (MFI range filtering)
This structured scoring means you spend less time second-guessing and more time reading clean signals.
👉 Flow That Follows Real Momentum
The slope of the MFI tracks whether volume pressure is rising or falling:
🟢 Green = increasing inflow (buying pressure)
🔴 Red = increasing outflow (selling pressure)
👉 Multi-Timeframe Volume Context
LiquidEdge calculates flow direction independently on each major timeframe. You’ll know if short-term setups are confirmed by higher timeframe volume or going against it.
👉 Smart Divergence Filtering
Unlike simple divergence tools that compare price highs/lows directly, LiquidEdge filters divergences based on:
Local pivot zones (defined by lookback periods)
Trend confirmation (to eliminate countertrend noise)
4️⃣ How LiquidEdge Works (Under the Hood)
LiquidEdge tracks directional momentum using the slope of the Money Flow Index (MFI) giving you a real-time read on buying and selling pressure.
When the slope rises, it means buyers are stepping in and volume is supporting the move.
When it falls, sellers are taking control and volume outflow is increasing.
This slope acts like a pressure gauge for the market, helping you spot when a trend has strength or when it's starting to fade.
💡 Quick Comparison
RSI = momentum from price
MFI = momentum from price + volume
LiquidEdge takes it one step further by calculating the rate of change (slope) in MFI. That’s where the pressure signal comes from not just value, but directional flow.
Core Calculations (Simplified)
Typical Price = (High + Low + Close) ÷ 3
Raw Money Flow = Typical Price × Volume
MFI = 100 −
MFI ranges from 0 to 100.
High = strong buying volume
Low = growing selling pressure
LiquidEdge then calculates the slope of this MFI over time to track volume momentum dynamically.
Divergence Engine
LiquidEdge detects divergence by comparing price pivots with the direction of MFI slope.
❌ If price makes a higher high but MFI slope turns down, it’s a bearish divergence
✅ If price makes a lower low but MFI slope rises, it’s a bullish divergence
Divergences are only confirmed when they occur:
Near local pivot zones (defined by configurable lookback windows)
And, optionally, in alignment with the broader trend using an EMA filter
This filtering helps reduce false positives and keeps you focused on clean setups.
Structured Confidence Scoring
Each signal is visually scored based on:
➡️ Whether a valid divergence is detected
➡️ Whether the signal occurs inside a liquidity zone (MFI > 80 or < 20)
➡️ Whether the setup aligns with the overall trend direction (EMA filter)
More confluence = higher confidence
The scoring system helps prioritize setups that meet multiple criteria, not just one.
Liquidity Zones
Above 80: Signals possible buying exhaustion 👉 risk of reversal
Below 20: Indicates potential selling exhaustion 👉 watch for a bounce
Zones are shaded directly on the chart to highlight pressure extremes in real time.
Price + Volume Fusion
LiquidEdge blends price action with volume pressure using MFI slope and histogram behavior. It doesn’t just show you where price is moving. it shows whether the move is backed by real volume.
This lets you see:
Whether volume is confirming or fading behind a move
If a reversal is building even before price confirms it
Visual Feedback That Speaks Clearly
🟢 Green slope = increasing buying pressure
🔴 Red slope = increasing selling pressure
5️⃣ When Price Is Flat but LiquidEdge Moves: Volume Tells the Truth
One of the most useful things LiquidEdge can do is reveal pressure shifts when price looks neutral.
If price is moving sideways but the MFI slope or histogram rises, it may suggest that buying pressure is quietly increasing possibly pointing to early accumulation.
If price stays flat while the volume slope or histogram drops, this could indicate distribution, where sellers are exiting without moving the market noticeably.
These changes don’t guarantee a breakout or breakdown, but they often precede key moves especially when combined with other confluences like trend alignment or liquidity zones.
👉 LiquidEdge helps spot these setups by measuring volume momentum shifts beneath price action.
It doesn’t predict the future, but it gives you additional context to evaluate what may be developing before it’s visible on price alone.
6️⃣ Multi-Timeframe Flow Table
LiquidEdge includes a real-time table that tracks volume pressure across multiple timeframes including 5-minute, 15-minute, 1-hour, 4-hour, and daily charts.
Each row reflects the direction of the MFI slope on that timeframe, indicating whether volume pressure is increasing (inflow) or decreasing (outflow).
🟢 A rising slope suggests that buying momentum is building
🔴 A falling slope suggests selling pressure may be increasing
👉 This lets traders quickly assess whether short-term setups are aligned with higher timeframe volume trends a useful layer of confirmation for both intraday and swing strategies.
Rather than flipping between charts, the table gives you a snapshot of flow strength across the board, helping you stay focused on opportunities that align with broader market pressure.
7️⃣ Timeframes & Assets
Where LiquidEdge Works Best:
✅ Crypto: Supports major coins and high-volume altcoins (BTC, ETH, Top 100)
✅ Stocks: Effective on large-cap and mid-cap equities with consistent volume
✅ Futures: Tested on instruments like NQ, MNQ, ES, and MES
✅ Any liquid market where volume data is reliable and stable
For best results, use LiquidEdge on assets with consistent trading volume. It’s not recommended for ultra-low volume crypto pairs or micro-cap stocks, where irregular volume can distort signals.
Recommended Timeframes:
👉 Intraday trading: Works well on 3-minute, 5-minute, 15-minute, and 1-hour charts
👉 Swing trading: Performs reliably on 4-hour, daily, and weekly charts
👉 Ultra short-term (1-minute or less): Not recommended due to high noise and low reliability
LiquidEdge adapts to various trading styles from scalping short-term momentum shifts to analyzing broader volume trends across swing and positional setups. The key is choosing assets and timeframes with reliable volume flow for the tool to work effectively.
8️⃣ Common Mistakes to Avoid When Using LiquidEdge
❌ Using It in Isolation
LiquidEdge offers valuable context, but it’s not designed to function as a standalone trading system. Always combine it with key tools such as trendlines, support/resistance zones, chart structure, or fundamental data. The more supporting evidence you have, the stronger your analysis becomes.
❌ Relying on a Single Indicator
No indicator, including LiquidEdge, can account for every market condition. It’s important to use it alongside other forms of confirmation to avoid making decisions based on limited data.
❌ Misinterpreting Divergences as Reversals
A divergence between price and volume pressure doesn't always signal the end of a trend. If the broader direction remains strong (based on EMAs or higher timeframe volume flow), a divergence could reflect temporary consolidation rather than reversal.
❌ Ignoring Trend Alignment and Confidence Scoring
LiquidEdge includes confidence scoring to help validate signals. Disregarding this structure can lead to reacting to weak or out-of-context divergences, especially in choppy or low-volume environments.
❌ Using It on Second-Based or Tick Charts
Very low timeframes introduce too much noise, which can distort volume slope and divergence signals. For intraday analysis, start with 3-minute charts or higher. For swing trading, use 4H and up for clearer, more reliable structure.
9️⃣ LiquidEdge Settings Overview
A quick breakdown of what you can customize in the indicator and how each option affects what you see:
➡️ LiquidEdge Length
Controls how sensitive the indicator is to changes in volume pressure (via MFI slope).
Shorter values = faster response, more frequent signals
Longer values = smoother output, less noise
👉 Default: 14
➡️ EMA Trend Filter
Determines overall trend direction based on EMA slope. Used to filter out signals that go against the broader move.
Helps reduce countertrend entries
Adjustable to suit your strategy
👉 Recommended: 200 EMA
➡️ Pivot Lookback (Left & Right)
Defines how many bars the system looks back and forward to identify swing highs/lows for divergence detection.
Narrow: more responsive but can be noisy
Wide: slower but more stable pivot zones
👉 Default: 5 left / 5 right
➡️ Histogram Toggle
Enables a visual histogram showing how volume pressure deviates from its recent average.
Useful for spotting shifts in flow intensity
👉 Optional for added visual detail
➡️ Liquidity Zones
Highlights potential exhaustion zones based on MFI value:
Above 80 = potential distribution (buying pressure peaking)
Below 20 = possible accumulation (selling pressure fading)
👉 Zones are fully customizable (color, opacity, background)
➡️ Custom Threshold Zones
Set your own upper/lower boundaries for liquidity extremes helpful when adapting to different markets or asset classes.
👉 Especially useful outside of crypto/forex
➡️ Show LiquidEdge Line
Toggle the main MFI slope line. When turned off, liquidity zones and levels also disappear.
👉 Use if you prefer to focus only on histogram/divergences
➡️ Style Settings
Customize line colors, histogram appearance, and background shading
👉 Helps tailor visuals to your chart layout
➡️ Simplified Mode
Removes all colors and replaces visuals with a clean, grayscale output.
👉 Ideal for minimalist or distraction-free charting
➡️ Signal Score Label
Displays the confidence score of the current setup, based on:
Divergence presence
Liquidity zone positioning
Trend alignment (EMA)
👉 Tooltip explains how the score is calculated
➡️ Divergence Labels
Shows “Bullish” or “Bearish” labels at divergence points.
Optional Filters based on trend if EMA filter is active
➡️ Multi-Timeframe Flow Table
Shows directional flow (based on MFI slope) across: 5M, 15M, 1H, 4H, 1D
Color-coded (faded green/red) for clarity
👉 Table position is customizable on your chart
➡️ Alerts
Get notified when any of these conditions are met:
✅ Bullish or bearish divergence detected
✅ Price enters high/low liquidity zones
✅ Signal score reaches a defined value
➡️ Visibility Settings
Control which timeframes display the LiquidEdge indicator
👉 Best used on 3-minute and above
⚠️ Not recommended on ultra-low or second-based charts due to noise
🔟 Q&A – What Traders Usually Ask
➡️ Can this help reduce bad trades?
To a degree, yes. LiquidEdge is built to highlight areas where price may react, based on volume pressure, liquidity zones, and divergence patterns. It can offer clarity in sideways or messy markets, helping traders avoid impulsive or poorly timed entries.
That said, it’s not predictive or guaranteed. It works best when used with broader context including structure, support/resistance, trend, and volume-based confluence.
👉 Reminder: LiquidEdge is not a signal tool. It’s a decision-support framework designed to help you assess potential shifts, not replace judgment or trading rules.
➡️ Is this just another flashy signal tool?
No. LiquidEdge doesn’t give buy/sell alerts. Instead, it visualizes volume shifts using MFI slope, divergence filtering, and trend-based scoring. It’s built to help you understand why price action may be changing not just react to a one-dimensional signal.
You’re seeing how volume pressure evolves across timeframes, which gives added context to what’s unfolding in the market.
➡️ How do I know this isn’t just another overhyped tool?
LiquidEdge is based on real trading logic: volume pressure (via MFI slope), price behavior, and divergence within trend and liquidity zones. It was developed and tested by traders, not packaged by marketers.
No performance is guaranteed. It’s designed to support your decisions not promise results.
➡️ Will this work with my trading style?
If you trade any market with volume crypto, stocks, or futures LiquidEdge can add value.
✔️ Scalpers: Best from 3-minute and up
✔️ Swing traders: Works well on 4H, Daily, Weekly
✔️ Investors: Weekly charts show pressure buildup over time
⚠️ Avoid ultra-low timeframes (under 1M) or illiquid markets, as noise and irregular data can reduce reliability.
➡️ Can I trust the signals?
These are not buy/sell signals. LiquidEdge offers confidence-weighted insights based on:
✔️ Valid divergence
✔️ Zone positioning (above 80 / below 20)
✔️ Optional trend alignment (via EMA)
Each setup is scored visually to reflect how much confluence exists. You can combine that information with structure, price action, or your existing tools to evaluate opportunities.
👉 Think of LiquidEdge as a decision filter not a trigger.
It’s meant to slow down impulsive trades and help you make more context-aware decisions.
1️⃣1️⃣ Limitations – Know When It’s Less Effective
LiquidEdge performs best in stable, high-volume markets where volume data is consistent and structure is visible.
It’s not recommended for:
❌ Low-volume tokens
❌ Micro-cap or penny stocks
❌ Newly listed assets with limited trading history
These types of markets often show inconsistent or erratic volume behavior, making it difficult for LiquidEdge to accurately assess pressure or identify reliable divergences.
⚠️ During major news events or sudden volatility spikes, volume and price behavior can become disconnected or extreme. This may distort MFI slope calculations and reduce the accuracy of divergence or confidence scoring.
LiquidEdge is built to read structured volume flow. When market conditions become highly erratic or unpredictable, it's best to:
Wait for structure to return
Use it alongside other filters for additional confirmation
This isn't a flaw it's simply the nature of tools that rely on consistency in price and volume data.
1️⃣2️⃣ Real Chart Examples – See It in Action
Now that you’ve seen how LiquidEdge works, here are real-world chart examples from various asset classes
including:
✅ Crypto
✅ Stocks
✅ Futures
✅ Commodities
These examples demonstrate how LiquidEdge behaves under different conditions, and how both the line (MFI slope) and histogram (volume deviation) can be used to interpret market flow.
In each walkthrough, you’ll see:
How the histogram can highlight potential momentum shifts
When the slope line provides stronger directional clarity
Examples of possible hidden accumulation or distribution (before price responds)
What to watch out for such as weak volume, false divergences, or conflicting flow signals
👉 These are real examples based on live market data not theoretical setups. They’re meant to help you recognize how LiquidEdge reacts across multiple styles and timeframes.
Let’s walk through each one and break down the logic step by step, so you can understand how to evaluate setups using structure, volume behavior, and context-driven confluence.
Example: Microsoft (MSFT) – Possible Hidden Accumulation
In this setup, price was moving lower within a short-term downtrend. However, LiquidEdge began showing signs of increasing inflow pressure a common characteristic of accumulation, where volume rises even as price declines.
This divergence suggested that buying interest may have been increasing behind the scenes, despite weak price action on the surface.
Step-by-step breakdown:
👉 Trend context – Price was clearly trending down at the time
👉 Volume divergence – Price made lower lows, but LiquidEdge slope was rising = possible bullish divergence
👉 Accumulation clue – The rising slope, despite falling price, pointed to volume inflow often seen during quiet accumulation
👉 Histogram support – Volume pressure (via the histogram) also increased, confirming the flow shift
👉 Anticipating reaction – When liquidity pressure rises ahead of price, it can signal potential reversal interest
In this case, price later moved sharply higher. While not guaranteed, setups like this illustrate how divergence + volume flow may help highlight early accumulation zones before price confirms the shift.
Same Setup – Focusing on the Histogram Alone
Here, we’re revisiting the Microsoft setup but this time focusing only on the histogram, without the MFI slope line.
Even without the directional slope, the histogram showed rising volume pressure while price continued to drift lower. This visual pattern may indicate that buying interest was quietly increasing, despite weak price movement.
This is where the histogram adds value: it helps visualize the intensity of volume flow over time. When volume pressure builds during a flat or declining price phase, it can be consistent with accumulation where larger participants begin positioning before the market responds.
This example highlights how the histogram alone can provide early insight into underlying volume dynamics even before price shifts noticeably.
Filtering with EMA and why It Matters
Here, we revisit the Microsoft example this time applying the 200 EMA filter, which helps define the broader trend.
Once enabled, LiquidEdge automatically removed any bullish or bearish divergence signals that were against the prevailing trend. This helped reduce noise and focus only on setups aligned with market structure.
✅ The EMA acts as a contextual filter.
For example, if a bullish divergence occurs during a confirmed downtrend, LiquidEdge suppresses that signal helping you avoid setups that may carry more risk.
This filtering mechanism is especially useful in fast or choppy markets, where not all divergences are meaningful.
Want More Flexibility? Adjust the Filter
If you're a more aggressive trader or prefer shorter-term signals, you can reduce the EMA length (e.g., to 150, 50, or even 25). This increases the number of setups shown but also raises the importance of additional context and confirmation.
⚠️ Keep in mind:
❌ More signals doesn’t always mean better outcomes
✅ Focused, context-aware signals tend to be more consistent with broader market pressure
If you’re using this in combination with strategies like options trading, this filter can help refine your entry zones especially when paired with other structure or volatility tools.
Distribution Example and Bitcoin Setup Before a Major Drop
In this example, Bitcoin was trading in a relatively tight range while price continued to push upward. However, LiquidEdge began to show signs of volume outflow, which can suggest potential distribution.
Here’s what was observed:
🔴 Price was moving up inside a horizontal range
🔴 LiquidEdge’s slope indicated declining volume pressure
🔴 Several bearish divergence signals appeared during this consolidation phase
🔴 The histogram also showed weakening flow, even before price broke down
These overlapping signals pointed to a possible distribution phase, where buying momentum was fading despite price still holding up.
🧭 Signs to Watch for in Potential Distribution:
1️⃣ Price holding flat or rising slightly within a tight range
2️⃣ Volume pressure (line or histogram) sloping downward
3️⃣ Repeated bearish divergences forming at the highs
4️⃣ Lack of follow-through on bullish setups signaling hesitation in demand
While LiquidEdge can’t predict market outcomes, this scenario demonstrates how a combination of divergence, outflow, and failure to break out may serve as early warnings that momentum is shifting beneath the surface.
Failed Auction Example – Volume Shift Before a Breakdown
In this example, price attempted to break out above a recent high, creating the appearance of a bullish continuation. However, LiquidEdge began to signal volume outflow, despite the upward price move a potential sign of a failed auction.
Here’s what was observed:
👉 Price made a new high, appearing to break resistance
👉 LiquidEdge slope and histogram both showed declining liquidity
👉 The indicator formed lower lows, even as price pushed higher
👉 This divergence suggested that volume wasn’t supporting the breakout
Shortly after, price reversed and returned back inside the range which is a common characteristic of failed auction behavior.
🧭 Spotting a Potential Failed Auction with LiquidEdge:
1️⃣ Price breaks above a recent high
2️⃣ Volume flow (line + histogram) shows outflow, not inflow
3️⃣ Indicator forms lower lows while price makes higher highs (bearish divergence)
4️⃣ Market reverts back into the previous range without follow-through
While no tool can predict outcomes, this setup demonstrated how volume pressure and divergence can help identify moments where a breakout may lack real support offering context before price action confirms the shift.
Reading the Histogram - Spotting Pressure Fades
In this example, price was still rising but the LiquidEdge histogram showed falling volume pressure. This type of divergence between price and volume can serve as a potential early signal that momentum may be fading.
🔻 Histogram levels declined while price continued higher
🔻 This suggested that buying pressure was weakening, even though price hadn’t turned
🔻 Volume flow behavior didn’t support the continuation possibly indicating buyer exhaustion
Just before the peak, the histogram nearly reached its lower threshold, despite price still being near its highs.
💡 How to Read It:
When volume pressure (shown by the histogram) starts to fade while price is still rising, it can indicate that momentum is weakening. This may precede a pullback or reversal particularly if other factors like divergence or zone exhaustion are also present.
Conversely, rising histogram values during a price drop may suggest potential accumulation.
👉 Use the histogram as a volume intensity gauge, not a signal on its own especially when evaluating whether a move is supported by actual flow, or just price momentum.
The Table – Fast, Visual Multi-Timeframe Flow Insight
The multi-timeframe flow table in LiquidEdge provides a consolidated view of volume momentum across several key timeframes so you don’t need to switch between charts to compare flow strength.
👉 Instead of flipping from 5-minute to 15M, 1H, 4H, and Daily, the table displays flow direction on all of them at a glance.
Example layout:
🔼 Daily: Up
🔽 1H: Down
🔼 15M: Up
🔽 5M: Down
This setup gives you a quick read on whether volume momentum is aligned across multiple timeframes or diverging which can help frame your trade approach.
🧠 Why It’s Useful:
✅ Supports timeframe alignment
If higher timeframes show strong inflow while lower ones are mixed, you may interpret it as a swing-based opportunity. If short timeframes show pressure but higher frames are flat, it might suggest short-term setups with caution.
✅ Improves context awareness
Instead of interpreting a move in isolation, the table helps you assess whether short-term signals are part of a broader shift or going against higher timeframe flow.
💡 Pro Tip: Use the table as a starting point in your analysis. It’s a simple but effective snapshot of current liquidity pressure across the board helping you plan trades with broader context, rather than reacting chart-by-chart.
🔚 Final Thoughts
If you're focused on trading with better clarity and structure, LiquidEdge is designed to help you interpret what’s happening beneath the surface not just follow price movement.
While many tools highlight price alone, LiquidEdge combines volume pressure, divergence filtering, and trend-based context to help identify potential areas of accumulation, distribution, or momentum shifts even before they become obvious on a chart.
👉 This isn’t just another signal tool. It’s a framework to support smarter decision-making:
✔️ One that helps you filter out noise
✔️ One that scores setups using multiple layers of confirmation
✔️ One that brings volume context into every trade idea
Whether you're scalping on a 5-minute chart or managing a longer-term swing trade, LiquidEdge is built to help you stay aligned with volume-driven behavior not just react to price alone.
If you've struggled with late entries, unreliable setups, or second-guessing trades, this tool was designed to bring more structure to your process. It won’t remove all uncertainty but it can help you stay more selective, confident, and intentional.
✅ Trade with clarity
✅ Stay process-driven
✅ Focus on structure, not noise
LiquidEdge is not meant to replace your strategy. It’s here to enhance it.
In this chart, the 200 EMA filter was applied. As a result, only signals that aligned with the dominant trend direction were displayed helping to reduce distractions and focus on setups with stronger context.
💡 Using a higher EMA setting like 200 can reduce the number of signals shown, but may help you focus on higher-conviction opportunities.
That said, every trader is different:
Longer EMAs = fewer signals, but more trend-filtered setups
Shorter EMAs = more signals, faster entries but with potentially more noise
👉 Adjust the filter based on your trading style. Use a 200 EMA for swing trading, or reduce it to 50, 25, or even 5 if you're trading more aggressively or intraday.
LiquidEdge adapts to you not the other way around.
🔁 Adjusting EMA for Your Trading Style
Personal Tip: When trading more aggressively, I often use a 5 EMA filter especially when combining histogram strength with other tools. This increases signal responsiveness and may help highlight short-term flow shifts more quickly.
Below are visual examples that show how different EMA lengths impact the behavior of LiquidEdge:
50 EMA ON
25 EMA ON
5 EMA ON
Lower EMA Example – Gold with the 5 EMA
In this example, the 5 EMA filter was applied to Gold. As expected, more signals were plotted compared to higher EMA settings. The tool became more responsive to rapid shifts in volume momentum, making it more suitable for fast-paced trading environments.
This setting can help traders who prefer early entries but it also introduces more sensitivity, so context and additional confirmation become even more important.
Each setting affects signal frequency and filtering:
Higher EMA → fewer signals, more trend-confirmed setups
Lower EMA → more signals, quicker responses, but with more potential for noise
Choose what fits your approach:
Long-term swing → Stick with 200 EMA
Intraday or scalping → Consider shorter EMAs (50, 25, or 5)
💡 Reminder: EMA filtering is fully adjustable. LiquidEdge doesn’t lock you into one trading style it’s meant to adapt to your process, whether you’re swing trading or scalping short-term moves.
But There’s a Catch…
Using a lower EMA setting (like 5) opens up faster, more frequent signals but it also increases the need for precision and stronger trade management.
❗ More signals = More responsiveness
❗ Faster setups mean quicker decisions
❗ Risk control becomes even more important
💡 Lower Timeframes = More Detail, Less Margin for Error
A short EMA (like 5) can help you:
✅ Identify early momentum shifts
✅ Respond before traditional trend-followers
✅ Highlight short-term divergence and volume changes
But it also comes with tradeoffs:
❌ Greater signal noise
❌ Higher potential for misreads or fakeouts
❌ Requires clear structure and disciplined entries
🚩 Watch Out for Liquidity Grabs
In lower timeframes, a common trap is the liquidity grab where price pushes beyond recent highs or lows, triggers stops, then quickly reverses.
📌 These moves can look like breakouts, but often reverse quickly possibly reflecting institutional order placement or low-liquidity manipulation.
🧭 How to Approach It Smartly
✅ Use structure: Mark support and resistance to frame moves
✅ Confirm volume behavior: Is histogram strength rising or fading?
✅ Avoid chasing: Look for confluence, not just a single signal
✅ Be intentional with stops: Place them with structure in mind to avoid being swept out
NASDAQ Futures Example – Low Timeframe Setups with LiquidEdge
In this example, we look at how LiquidEdge was used to identify both short and long setups on the NASDAQ Futures (NQ) particularly on a low timeframe (5M), where quick decision-making and volume precision matter most.
⚠️ A Note on Futures and Volume
When trading futures, especially on intraday charts, it’s important to separate overnight volume from regular session activity.
🕒 Overnight Volume ≠ Real Volume Context
Overnight price action is informative, but the volume data itself may not reflect true market participation. In LiquidEdge, histogram and pressure calculations emphasize regular session flow helping avoid skewed signals that could come from low-volume overnight moves.
Using the Histogram to Spot Potential Shifts
One of the key cues I use is color transition in the histogram:
🔴 A flip from strong green to red can signal fading buying pressure, sometimes marking the beginning of a potential short setup.
🟢 A shift from red to green may indicate that buyers are returning, suggesting possible accumulation.
These shifts serve as early visual cues of changing pressure especially when confirmed by other tools or context.
🔁 Adding Context with the Line + Structure
After spotting a histogram shift, I look at:
1️⃣ Slope Line – Is it confirming the same directional pressure?
2️⃣ Support/Resistance – Are we near a meaningful zone?
3️⃣ Additional Tools – This includes trendlines, VWAP, EMAs, and overall price structure.
On lower timeframes like 5M, these pieces become even more important. LiquidEdge gives directional insight, but your full setup provides confirmation and execution logic.
⚠️ Disclaimer
LiquidEdge is not a signal tool. It’s a visual representation of market pressure and flow designed to help you make more informed trading and investing decisions. It shows you what’s happening beneath the price action but you are still responsible for your decisions.
Always combine LiquidEdge with your own strategy, research, and supporting tools. That includes trend analysis, support/resistance levels, chart patterns, and fundamentals (like P/E ratios, price-to-sales, debt ratios, etc.).
This tool should never be used alone or treated as financial advice.
Some content may include AI-powered enhancements for clarity or formatting.
Always do your own research. For personal financial guidance, speak with a licensed financial advisor.
Fibonacci Optimal Entry Zone [OTE] (Zeiierman)█ Overview
Fibonacci Optimal Entry Zone (Zeiierman) is a high-precision market structure tool designed to help traders identify ideal entry zones during trending markets. Built on the principles of Smart Money Concepts (SMC) and Fibonacci retracements, this indicator highlights key areas where price is most likely to react — specifically within the "Golden Zone" (between the 50% and 61.8% retracement).
It tracks structural pivot shifts (CHoCH) and dynamically adjusts Fibonacci levels based on real-time swing tracking. Whether you're trading breakouts, pullbacks, or optimal entries, this tool brings unparalleled clarity to structure-based strategies.
Ideal for traders who rely on confluence, this indicator visually synchronizes swing highs/lows, market structure shifts, Fibonacci retracement levels, and trend alignment — all without clutter or lag.
⚪ The Structural Assumption
Price moves in waves, but key retracements often lead to continuation or reversal — especially when aligned with structure breaks and trend shifts.
The Optimal Entry Zone captures this behavior by anchoring Fibonacci levels between recent swing extremes. The most powerful area — the Golden Zone — marks where institutional re-entry is likely, providing traders with a sniper-like roadmap to structure-based entries.
█ How It Works
⚪ Structure Tracking Engine
At its core, the indicator detects pivots and classifies trend direction:
Structure Period – Determines the depth of pivots used to detect swing highs/lows.
CHoCH – Break of structure logic identifies where the trend shifts or continues, marked visually on the chart.
Bullish & Bearish Modes – Independently toggle uptrend and downtrend detection and styling.
⚪ Fibonacci Engine
Upon each confirmed structural shift, Fibonacci retracement levels are projected between swing extremes:
Custom Levels – Choose which retracements (0.50, 0.618, etc.) are shown.
Real-Time Adjustments – When "Swing Tracker" is enabled, levels and labels update dynamically as price forms new swings.
Example:
If you disable the Swing Tracker, the Golden Level is calculated using the most recent confirmed swing high and low.
If you enable the Swing Tracker, the Golden Level is calculated from the latest swing high or low, making it more adaptive as the trend evolves in real time.
█ How to Use
⚪ Structure-Based Entry
Wait for CHoCH events and use the resulting Fibonacci projection to identify entry points. Enter trades as price taps into the Golden Zone, especially when confluence forms with swing structure or order blocks.
⚪ Real-Time Reaction Tracking
Enable Swing Tracker to keep the tool live — constantly updating zones as price shifts. This is especially useful for scalpers or intraday traders who rely on fresh swing zones.
█ Settings
Structure Period – Number of bars used to define swing pivots. Larger values = stronger structure.
Swing Tracker – Auto-updates fib levels as new highs/lows form.
Show Previous Levels – Keep older fib zones on chart or reset with each structure shift.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Target ScannerThis invite-only indicator implements an advanced Wolfe Wave pattern recognition system specifically designed for Borsa Istanbul (BIST) stock screening across multiple timeframes and mathematical ratio calculations.
**Core Technical Framework:**
The indicator employs sophisticated mathematical calculations across 10 distinct timeframes (377, 233, 144, 89, 55, 34, 21, 13, 8, 5 periods) using Elliott Wave ratio theory combined with algorithmic pattern detection. Unlike standard scanning tools that rely on basic technical indicators, this system uses quantitative Wolfe Wave analysis to identify precise entry and exit points across 560+ BIST stocks simultaneously.
**Key Features:**
• **Multi-Stock Scanning:** Simultaneously analyzes 40 stocks per list across 14 different BIST stock lists (560+ total stocks)
• **Advanced Pattern Detection:** Implements Wolfe Wave mathematical validation using 24 different ratio calculation methods including Fibonacci sequences, Elliott Wave ratios, Golden Ratio, Harmonic Patterns, Pi-based calculations, volatility-based dynamic ratios, and AI-optimized mathematical progressions
• **Real-Time Screening Table:** Displays active signals with current price, signal price, target price, expected profit percentage, and calculated stop-loss levels
• **Reliability Scoring System:** EPA (Entry Point Accuracy) and ETA (Exit Target Accuracy) scoring with historical performance tracking
• **Visual Signal Display:** Comprehensive signal boxes showing profit zones, stop-loss areas, entry levels, and estimated time to target completion
**Mathematical Implementation:**
The core algorithm calculates price relationships using configurable mathematical ratios. For bullish conditions, it identifies entry points when price action meets specific criteria:
- Point validation through ratio analysis between swing highs/lows across multiple timeframes
- Mathematical confirmation using (pv - pf) / (pv - pd) ratio calculations
- Confluence validation across timeframes with dynamic ratio adjustments
- Minimum profit threshold filtering to ensure signal quality
**Originality and Innovation:**
This implementation differs significantly from traditional scanning tools through several key innovations:
1. **Multi-Timeframe Wolfe Wave Detection:** Simultaneous pattern recognition across 10 timeframes rather than single-timeframe analysis
2. **Adaptive Ratio Systems:** 24 different mathematical calculation methods including volatility-based, time-based, momentum-based, and volume-weighted ratio adjustments
3. **BIST-Specific Optimization:** Tailored specifically for Turkish stock market characteristics with 14 pre-configured stock lists
4. **Institutional-Grade Visualization:** Advanced signal boxes with profit/loss zones, multiple entry levels, and time-based target estimation
5. **Real-Time Performance Tracking:** Dynamic EPA/ETA scoring system that tracks historical accuracy and adapts calculations
**Signal Generation Logic:**
The system generates signals when multiple mathematical conditions align:
- Wolfe Wave pattern completion across specified timeframes
- Ratio validation using selected mathematical progression (Fibonacci, Golden Ratio, Elliott Wave, etc.)
- Stop-loss calculation as percentage of target profit (default 0.5%)
- Minimum profit threshold compliance
- Multi-timeframe confluence confirmation
**Risk Management Features:**
• **Configurable Stop-Loss:** Calculated as percentage of target profit with recommended 0.3 setting for 1:3 risk-reward ratio
• **Profit Percentage Display:** Real-time calculation showing expected profit from signal price to target
• **Multiple Entry Levels:** EPA and ETA-based entry points with reliability scoring
• **Time Estimation:** Statistical analysis providing estimated bars/time to target completion
• **Visual Risk Zones:** Color-coded profit (green) and loss (red) areas for clear risk visualization
**Performance Characteristics:**
The indicator is optimized for active screening with frequent signal generation across multiple stocks. It provides both short-term and medium-term opportunities depending on the timeframe producing the signal. The system maintains historical statistics for signal accuracy and target completion timing.
**Technical Requirements:**
Requires understanding of Wolfe Wave pattern theory, Elliott Wave principles, and multi-timeframe analysis concepts. Users should be familiar with BIST market structure and Turkish stock trading mechanics. The indicator demands active monitoring due to the high-frequency nature of multi-stock scanning.
**Market Application:**
Specifically designed for Borsa Istanbul stocks with comprehensive coverage across major sectors. Works effectively in both trending and ranging market conditions due to its adaptive ratio selection and multi-timeframe approach. Best suited for traders focusing on Turkish equity markets with pattern-based strategies.
**Customization Options:**
• **14 Stock Lists:** Pre-configured BIST stock groups for sector-specific analysis
• **24 Ratio Methods:** From conservative Fibonacci to aggressive AI-optimized calculations
• **Quote Pair Integration:** Optional currency pair specification for international analysis
• **Timeframe Flexibility:** Customizable chart timeframe for signal generation
• **Table Positioning:** Multiple display options with size and color customization
• **Alert Integration:** Comprehensive alert system for real-time signal notifications
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV)
Where Pure Mathematics Meets Market Reality
A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics
🎓 THEORETICAL FOUNDATION
The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis:
The Langlands Program: Harmonic Analysis in Markets
Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator:
L-Function Implementation:
- Utilizes the Möbius function μ(n) for weighted price analysis
- Applies Riemann zeta function convergence principles
- Calculates quantum harmonic resonance between -2 and +2
- Measures deep mathematical patterns invisible to traditional analysis
The L-Function core calculation employs:
L_sum = Σ(return_val × μ(n) × n^(-s))
Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness.
Operadic Composition Theory: Multi-Strategy Democracy
Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using:
Strategy Composition Arity (2-5 strategies):
- Momentum analysis via RSI transformation
- Mean reversion through Bollinger Band mathematics
- Order Flow Polarity Index (revolutionary T3-smoothed volume analysis)
- Trend detection using Directional Movement
- Higher timeframe momentum confirmation
Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty.
Möbius Function: Number Theory in Action
The Möbius function μ(n) forms the mathematical backbone:
- μ(n) = 1 if n is a square-free positive integer with even number of prime factors
- μ(n) = -1 if n is a square-free positive integer with odd number of prime factors
- μ(n) = 0 if n has a squared prime factor
This creates oscillating weights that reveal hidden market periodicities and harmonic structures.
🔧 COMPREHENSIVE INPUT SYSTEM
Langlands Program Parameters
Modular Level N (5-50, default 30):
Primary lookback for quantum harmonic analysis. Optimized by timeframe:
- Scalping (1-5min): 15-25
- Day Trading (15min-1H): 25-35
- Swing Trading (4H-1D): 35-50
- Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45
L-Function Critical Strip (0.5-2.5, default 1.5):
Controls Riemann zeta convergence precision:
- Higher values: More stable, smoother signals
- Lower values: More reactive, catches quick moves
- High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3
Frobenius Trace Period (5-50, default 21):
Galois representation lookback for price-volume correlation:
- Measures harmonic relationships in market flows
- Scalping: 8-15, Day Trading: 18-25, Swing: 25-40
HTF Multi-Scale Analysis:
Higher timeframe context prevents trading against major trends:
- Provides market bias and filters signals
- Improves win rates by 15-25% through trend alignment
Operadic Composition Parameters
Strategy Composition Arity (2-5, default 4):
Number of algorithms composed for final signal:
- Conservative: 4-5 strategies (higher confidence)
- Moderate: 3-4 strategies (balanced approach)
- Aggressive: 2-3 strategies (more frequent signals)
Category Agreement Threshold (2-5, default 3):
Democratic voting minimum for signal generation:
- Higher agreement: Fewer but higher quality signals
- Lower agreement: More signals, potential false positives
Swiss-Cheese Mixing (0.1-0.5, default 0.382):
Golden ratio φ⁻¹ based blending of trend factors:
- 0.382 is φ⁻¹, optimal for natural market fractals
- Higher values: Stronger trend following
- Lower values: More contrarian signals
OFPI Configuration:
- OFPI Length (5-30, default 14): Order Flow calculation period
- T3 Smoothing (3-10, default 5): Advanced exponential smoothing
- T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control
Unified Scoring System
Component Weights (sum ≈ 1.0):
- L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis
- Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity
- Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus
- Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment
Signal Threshold (0.5-10.0, default 5.0):
Quality filter producing:
- 8.0+: EXCEPTIONAL signals only
- 6.0-7.9: STRONG signals
- 4.0-5.9: MODERATE signals
- 2.0-3.9: WEAK signals
🎨 ADVANCED VISUAL SYSTEM
Multi-Dimensional Quantum Aura Bands
Five-layer resonance field showing market energy:
- Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.)
- Expansion: Dynamic based on score intensity and volatility
- Function: Multi-timeframe support/resistance zones
Morphism Flow Portals
Category theory visualization showing market topology:
- Green/Cyan Portals: Bullish mathematical flow
- Red/Orange Portals: Bearish mathematical flow
- Size/Intensity: Proportional to signal strength
- Recursion Depth (1-8): Nested patterns for flow evolution
Fractal Grid System
Dynamic support/resistance with projected L-Scores:
- Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows
- Smart Spacing: Prevents level overlap using ATR-based minimum distance
- Projections: Estimated signal scores when price reaches levels
- Usage: Precise entry/exit timing with mathematical confirmation
Wick Pressure Analysis
Rejection level prediction using candle mathematics:
- Upper Wicks: Selling pressure zones (purple/red lines)
- Lower Wicks: Buying pressure zones (purple/green lines)
- Glow Intensity (1-8): Visual emphasis and line reach
- Application: Confluence with fractal grid creates high-probability zones
Regime Intensity Heatmap
Background coloring showing market energy:
- Black/Dark: Low activity, range-bound markets
- Purple Glow: Building momentum and trend development
- Bright Purple: High activity, strong directional moves
- Calculation: Combines trend, momentum, volatility, and score intensity
Six Professional Themes
- Quantum: Purple/violet for general trading and mathematical focus
- Holographic: Cyan/magenta optimized for cryptocurrency markets
- Crystalline: Blue/turquoise for conservative, stability-focused trading
- Plasma: Gold/magenta for high-energy volatility trading
- Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading
📊 INSTITUTIONAL-GRADE DASHBOARD
Unified AI Score Section
- Total Score (-10 to +10): Primary decision metric
- >5: Strong bullish signals
- <-5: Strong bearish signals
- Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK
- Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions
Order Flow Analysis
Revolutionary OFPI integration:
- OFPI Value (-100% to +100%): Real buying vs selling pressure
- Visual Gauge: Horizontal bar chart showing flow intensity
- Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK
- Trading Application: Flow shifts often precede major moves
Signal Performance Tracking
- Win Rate Monitoring: Real-time success percentage with emoji indicators
- Signal Count: Total signals generated for frequency analysis
- Current Position: LONG, SHORT, or NONE with P&L tracking
- Volatility Regime: HIGH, MEDIUM, or LOW classification
Market Structure Analysis
- Möbius Field Strength: Mathematical field oscillation intensity
- CHAOTIC: High complexity, use wider stops
- STRONG: Active field, normal position sizing
- MODERATE: Balanced conditions
- WEAK: Low activity, consider smaller positions
- HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL)
- Strategy Agreement: Multi-algorithm consensus level
Position Management
When in trades, displays:
- Entry Price: Original signal price
- Current P&L: Real-time percentage with risk level assessment
- Duration: Bars in trade for timing analysis
- Risk Level: HIGH/MEDIUM/LOW based on current exposure
🚀 SIGNAL GENERATION LOGIC
Balanced Long/Short Architecture
The indicator generates signals through multiple convergent pathways:
Long Entry Conditions:
- Score threshold breach with algorithmic agreement
- Strong bullish order flow (OFPI > 0.15) with positive composite signal
- Bullish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bullish OFPI (>0.3) with any positive score
Short Entry Conditions:
- Score threshold breach with bearish agreement
- Strong bearish order flow (OFPI < -0.15) with negative composite signal
- Bearish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bearish OFPI (<-0.3) with any negative score
Exit Logic:
- Score deterioration below continuation threshold
- Signal quality degradation
- Opposing order flow acceleration
- 10-bar minimum between signals prevents overtrading
⚙️ OPTIMIZATION GUIDELINES
Asset-Specific Settings
Cryptocurrency Trading:
- Modular Level: 15-25 (capture volatility)
- L-Function Precision: 0.8-1.3 (reactive to price swings)
- OFPI Length: 10-20 (fast correlation shifts)
- Cascade Levels: 5-7, Theme: Holographic
Stock Index Trading:
- Modular Level: 25-35 (balanced trending)
- L-Function Precision: 1.5-1.8 (stable patterns)
- OFPI Length: 14-20 (standard correlation)
- Cascade Levels: 4-5, Theme: Quantum
Forex Trading:
- Modular Level: 35-45 (smooth trends)
- L-Function Precision: 1.6-2.1 (high smoothing)
- OFPI Length: 18-25 (disable volume amplification)
- Cascade Levels: 3-4, Theme: Crystalline
Timeframe Optimization
Scalping (1-5 minute charts):
- Reduce all lookback parameters by 30-40%
- Increase L-Function precision for noise reduction
- Enable all visual elements for maximum information
- Use Small dashboard to save screen space
Day Trading (15 minute - 1 hour):
- Use default parameters as starting point
- Adjust based on market volatility
- Normal dashboard provides optimal information density
- Focus on OFPI momentum shifts for entries
Swing Trading (4 hour - Daily):
- Increase lookback parameters by 30-50%
- Higher L-Function precision for stability
- Large dashboard for comprehensive analysis
- Emphasize HTF trend alignment
🏆 ADVANCED TRADING STRATEGIES
The Mathematical Confluence Method
1. Wait for Fractal Grid level approach
2. Confirm with projected L-Score > threshold
3. Verify OFPI alignment with direction
4. Enter on portal signal with quality ≥ STRONG
5. Exit on score deterioration or opposing flow
The Regime Trading System
1. Monitor Aether Flow background intensity
2. Trade aggressively during bright purple periods
3. Reduce position size during dark periods
4. Use Möbius Field strength for stop placement
5. Align with HTF trend for maximum probability
The OFPI Momentum Strategy
1. Watch for momentum shifting detection
2. Confirm with accelerating flow in direction
3. Enter on immediate portal signal
4. Scale out at Fibonacci levels
5. Exit on flow deceleration or reversal
⚠️ RISK MANAGEMENT INTEGRATION
Mathematical Position Sizing
- Use Galois Rank for volatility-adjusted sizing
- Möbius Field strength determines stop width
- Fractal Dimension guides maximum exposure
- OFPI momentum affects entry timing
Signal Quality Filtering
- Trade only STRONG or EXCEPTIONAL quality signals
- Increase position size with higher agreement levels
- Reduce risk during CHAOTIC Möbius field periods
- Respect HTF trend alignment for directional bias
🔬 DEVELOPMENT JOURNEY
Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable.
The Mathematical Challenge
Implementing the Langlands Program required deep research into:
- Number theory and the Möbius function
- Riemann zeta function convergence properties
- L-function analytical continuation
- Galois representations in finite fields
The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application.
The Computational Complexity
Operadic composition theory demanded:
- Category theory implementation in Pine Script
- Multi-dimensional array management for strategy composition
- Real-time democratic voting algorithms
- Performance optimization for complex calculations
The Integration Breakthrough
Bringing together three disparate mathematical frameworks required:
- Novel approaches to signal weighting and combination
- Revolutionary Order Flow Polarity Index development
- Advanced T3 smoothing implementation
- Balanced signal generation preventing directional bias
Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility.
🎯 PRACTICAL IMPLEMENTATION
Getting Started
1. Apply indicator with default settings
2. Select appropriate theme for your markets
3. Observe dashboard metrics during different market conditions
4. Practice signal identification without trading
5. Gradually adjust parameters based on observations
Signal Confirmation Process
- Never trade on score alone - verify quality rating
- Confirm OFPI alignment with intended direction
- Check fractal grid level proximity for timing
- Ensure Möbius field strength supports position size
- Validate against HTF trend for bias confirmation
Performance Monitoring
- Track win rate in dashboard for strategy assessment
- Monitor component contributions for optimization
- Adjust threshold based on desired signal frequency
- Document performance across different market regimes
🌟 UNIQUE INNOVATIONS
1. First Integration of Langlands Program mathematics with practical trading
2. Revolutionary OFPI with T3 smoothing and momentum detection
3. Operadic Composition using category theory for signal democracy
4. Dynamic Fractal Grid with projected L-Score calculations
5. Multi-Dimensional Visualization through morphism flow portals
6. Regime-Adaptive Background showing market energy intensity
7. Balanced Signal Generation preventing directional bias
8. Professional Dashboard with institutional-grade metrics
📚 EDUCATIONAL VALUE
The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to:
- Pure mathematics applications in markets
- Category theory and operadic composition
- Number theory through Möbius function implementation
- Harmonic analysis via L-function calculations
- Advanced signal processing through T3 smoothing
⚖️ RESPONSIBLE USAGE
This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable.
Key Principles:
- Use as part of comprehensive trading strategy
- Implement proper risk management at all times
- Backtest thoroughly before live implementation
- Understand that past performance does not guarantee future results
- Never risk more than you can afford to lose
The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator.
🔮 CONCLUSION
The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability.
From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos.
This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure.
Trade with mathematical precision. Trade with the LOMV.
*"Mathematics is the language with which God has written the universe." - Galileo Galilei*
*In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.*
— Dskyz, Trade with insight. Trade with anticipation.
Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry
A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics
What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets.
The Theoretical Foundation
Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through:
Hurst Exponent Calculation: H = log(R/S) / log(n/2)
Where:
R = Range of cumulative deviations
S = Standard deviation
n = Period length
This measures market memory:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting (anti-persistent) behavior
Fractal Dimension: D = 2 - H
This quantifies market complexity, where higher dimensions indicate more chaotic behavior.
Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences:
Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor
Where:
φ = 0.618 (golden ratio)
Fn = Fibonacci number (8, 13, 21, 34, 55)
Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5
This creates oscillating spirals that contract and expand with market energy.
The Volatility Cascade System
Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands:
Cascade Level Calculation: Level(i) = ATR(20) × φ^i
Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels.
Implementation Architecture
Core Components:
Fractal Analysis Engine
Calculates Hurst exponent over user-defined periods
Derives fractal dimension for complexity measurement
Identifies market regime (trending/ranging/chaotic)
Fibonacci Vortex Generator
Creates 5 independent spiral oscillators
Each spiral follows a Fibonacci period
Volume amplification creates dynamic response
Cascade Band System
Up to 8 volatility levels
Golden ratio expansion between levels
Dynamic coloring based on fractal state
Confluence Detection
Identifies convergence of vortex and cascade levels
Highlights high-probability reversal zones
Real-time confluence strength calculation
Signal Generation Logic
The MFCV generates two primary signal types:
Fractal Signals: Generated when:
Hurst > 0.65 (strong trend) AND volatility expanding
Hurst < 0.35 (mean reversion) AND RSI < 35
Trend strength > 0.4 AND vortex alignment
Cascade Signals: Triggered by:
RSI > 60 AND price > SMA(50) AND bearish vortex
RSI < 40 AND price < SMA(50) AND bullish vortex
Volatility expansion AND trend strength > 0.3
Both signals implement a 15-bar cooldown to prevent overtrading.
Advanced Input System
Mandelbrot Parameters:
Cascade Levels (3-8):
Controls number of volatility bands
Crypto: 5-7 (high volatility)
Indices: 4-5 (moderate volatility)
Forex: 3-4 (low volatility)
Hurst Period (20-200):
Lookback for fractal calculation
Scalping: 20-50
Day Trading: 50-100
Swing Trading: 100-150
Position Trading: 150-200
Cascade Ratio (1.0-3.0):
Band width multiplier
1.618: Golden ratio (default)
Higher values for trending markets
Lower values for ranging markets
Fractal Memory (21-233):
Fibonacci retracement lookback
Uses Fibonacci numbers for harmonic alignment
Fibonacci Vortex Settings:
Spiral Periods:
Comma-separated Fibonacci sequence
Fast: "5,8,13,21,34" (scalping)
Standard: "8,13,21,34,55" (balanced)
Extended: "13,21,34,55,89" (swing)
Rotation Speed (0.1-2.0):
Controls spiral oscillation frequency
0.618: Golden ratio (balanced)
Higher = more signals, more noise
Lower = smoother, fewer signals
Volume Amplification:
Enables dynamic spiral expansion
Essential for stocks and crypto
Disable for forex (no central volume)
Visual System Architecture
Cascade Bands:
Multi-level volatility envelopes
Gradient coloring from primary to secondary theme
Transparency increases with distance from price
Fill between bands shows fractal structure
Vortex Spirals:
5 Fibonacci-period oscillators
Blue above price (bullish pressure)
Red below price (bearish pressure)
Multiple display styles: Lines, Circles, Dots, Cross
Dynamic Fibonacci Levels:
Auto-updating retracement levels
Smart update logic prevents disruption near levels
Distance-based transparency (closer = more visible)
Updates every 50 bars or on volatility spikes
Confluence Zones:
Highlighted boxes where indicators converge
Stronger confluence = stronger support/resistance
Key areas for reversal trades
Professional Dashboard System
Main Fractal Dashboard: Displays real-time:
Hurst Exponent with market state
Fractal Dimension with complexity level
Volatility Cascade status
Vortex rotation impact
Market regime classification
Signal strength percentage
Active indicator levels
Vortex Metrics Panel: Shows:
Individual spiral deviations
Convergence/divergence metrics
Real-time vortex positioning
Fibonacci period performance
Fractal Metrics Display: Tracks:
Dimension D value
Market complexity rating
Self-similarity strength
Trend quality assessment
Theory Guide Panel: Educational reference showing:
Mandelbrot principles
Fibonacci vortex concepts
Dynamic trading suggestions
Trading Applications
Trend Following:
High Hurst (>0.65) indicates strong trends
Follow cascade band direction
Use vortex spirals for entry timing
Exit when Hurst drops below 0.5
Mean Reversion:
Low Hurst (<0.35) signals reversal potential
Trade toward vortex spiral convergence
Use Fibonacci levels as targets
Tighten stops in chaotic regimes
Breakout Trading:
Monitor cascade band compression
Watch for vortex spiral alignment
Volatility expansion confirms breakouts
Use confluence zones for targets
Risk Management:
Position size based on fractal dimension
Wider stops in high complexity markets
Tighter stops when Hurst is extreme
Scale out at Fibonacci levels
Market-Specific Optimization
Cryptocurrency:
Cascade Levels: 5-7
Hurst Period: 50-100
Rotation Speed: 0.786-1.2
Enable volume amplification
Stock Indices:
Cascade Levels: 4-5
Hurst Period: 80-120
Rotation Speed: 0.5-0.786
Moderate cascade ratio
Forex:
Cascade Levels: 3-4
Hurst Period: 100-150
Rotation Speed: 0.382-0.618
Disable volume amplification
Commodities:
Cascade Levels: 4-6
Hurst Period: 60-100
Rotation Speed: 0.5-1.0
Seasonal adjustment consideration
Innovation and Originality
The MFCV represents several breakthrough innovations:
First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory
Unique synthesis of chaos theory and sacred geometry
Novel application of Hurst exponent to spiral dynamics
Dynamic Volatility Cascade System
Golden ratio-based band expansion
Multi-timeframe fractal analysis
Self-adjusting to market conditions
Volume-Amplified Vortex Spirals
Revolutionary spiral calculation method
Dynamic response to market participation
Multiple Fibonacci period integration
Intelligent Signal Generation
Cooldown system prevents overtrading
Multi-factor confirmation required
Regime-aware signal filtering
Professional Analytics Dashboard
Institutional-grade metrics display
Real-time fractal analysis
Educational integration
Development Journey
Creating the MFCV involved overcoming numerous challenges:
Mathematical Complexity: Implementing Hurst exponent calculations efficiently
Visual Clarity: Displaying multiple indicators without cluttering
Performance Optimization: Managing array operations and calculations
Signal Quality: Balancing sensitivity with reliability
User Experience: Making complex theory accessible
The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability.
Best Practices and Guidelines
Start Simple: Use default settings initially
Match Timeframe: Adjust parameters to your trading style
Confirm Signals: Never trade MFCV signals in isolation
Respect Regimes: Adapt strategy to market state
Manage Risk: Use fractal dimension for position sizing
Color Themes
Six professional themes included:
Fractal: Balanced blue/purple palette
Golden: Warm Fibonacci-inspired colors
Plasma: Vibrant modern aesthetics
Cosmic: Dark mode optimized
Matrix: Classic green terminal
Fire: Heat map visualization
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results.
The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose.
Acknowledgments
Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance.
"The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot
Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV.
— Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Enhanced Stock Ticker with 50MA vs 200MADescription
The Enhanced Stock Ticker with 50MA vs 200MA is a versatile Pine Script indicator designed to visualize the relative position of a stock's price within its short-term and long-term price ranges, providing actionable bullish and bearish signals. By calculating normalized indices based on user-defined lookback periods (defaulting to 50 and 200 bars), this indicator helps traders identify potential reversals or trend continuations. It offers the flexibility to plot signals either on the main price chart or in a separate lower pane, leveraging Pine Script v6's force_overlay functionality for seamless integration. The indicator also includes a customizable ticker table, visual fills, and alert conditions for automated trading setups.
Key Features
Dual Lookback Indices: Computes short-term (default: 50 bars) and long-term (default: 200 bars) indices, normalizing the closing price relative to the high/low range over the specified periods.
Flexible Signal Plotting: Users can toggle between plotting crossover signals (triangles) on the main price chart (location.abovebar/belowbar) or in the lower pane (location.top/bottom) using the Plot Signals on Main Chart option.
Crossover Signals: Generates bullish (Golden Cross) and bearish (Death Cross) signals when the short or long index crosses above 5 or below 95, respectively.
Visual Enhancements:
Plots short-term (blue) and long-term (white) indices in a separate pane with customizable lookback periods.
Includes horizontal reference lines at 0, 20, 50, 80, and 100, with green and red fills to highlight overbought/oversold zones.
Dynamic fill between indices (green when short > long, red when long > short) for quick trend visualization.
Displays a ticker and legend table in the top-right corner, showing the symbol and lookback periods.
Alert Conditions: Supports alerts for bullish and bearish crossovers on both short and long indices, enabling integration with TradingView's alert system.
Technical Innovation: Utilizes Pine Script v6's force_overlay parameter to plot signals on the main chart from a non-overlay indicator, combining the benefits of a separate pane and chart-based signals in a single script.
Technical Details
Calculation Logic:
Uses confirmed bars (barstate.isconfirmed) to calculate indices, ensuring reliability by avoiding real-time bar fluctuations.
Short-term index: (close - lowest(low, lookback_short)) / (highest(high, lookback_short) - lowest(low, lookback_short)) * 100
Long-term index: (close - lowest(low, lookback_long)) / (highest(high, lookback_long) - lowest(low, lookback_long)) * 100
Signals are triggered using ta.crossover() and ta.crossunder() for indices crossing 5 (bullish) and 95 (bearish).
Signal Plotting:
Main chart signals use force_overlay=true with location.abovebar/belowbar for precise alignment with price bars.
Lower pane signals use location.top/bottom for visibility within the indicator pane.
Plotting is controlled by boolean conditions (e.g., bullishLong and plot_on_chart) to ensure compliance with Pine Script's global scope requirements.
Performance Considerations: Optimized for efficiency by calculating indices only on confirmed bars and using lightweight plotting functions.
How to Use
Add to Chart:
Copy the script into TradingView's Pine Editor and add it to your chart.
Configure Settings:
Short Lookback Period: Adjust the short-term lookback (default: 50 bars) to match your trading style (e.g., 20 for shorter-term analysis).
Long Lookback Period: Adjust the long-term lookback (default: 200 bars) for broader market context.
Plot Signals on Main Chart: Check this box to display signals on the price chart; uncheck to show signals in the lower pane.
Interpret Signals:
Golden Cross (Bullish): Green (long) or blue (short) triangles indicate the index crossing above 5, suggesting a potential buying opportunity.
Death Cross (Bearish): Red (long) or white (short) triangles indicate the index crossing below 95, signaling a potential selling opportunity.
Set Alerts:
Use TradingView's alert system to create notifications for the four alert conditions: Long Index Valley, Long Index Peak, Short Index Valley, and Short Index Peak.
Customize Visuals:
The ticker table displays the symbol and lookback periods in the top-right corner.
Adjust colors and styles via TradingView's settings if desired.
Example Use Cases
Swing Trading: Use the short-term index (e.g., 50 bars) to identify short-term reversals within a broader trend defined by the long-term index.
Trend Confirmation: Monitor the fill between indices to confirm whether the short-term trend aligns with the long-term trend.
Automated Trading: Leverage alert conditions to integrate with bots or manual trading strategies.
Notes
Testing: Always backtest the indicator on your chosen market and timeframe to validate its effectiveness.
Optional Histogram: The script includes a commented-out histogram for the index difference (index_short - index_long). Uncomment the plot(index_diff, ...) line to enable it.
Compatibility: Built for Pine Script v6 and tested on TradingView as of May 27, 2025.
Acknowledgments
This indicator was inspired by the need for a flexible tool that combines lower-pane analysis with main chart signals, made possible by Pine Script's force_overlay feature. Share your feedback or suggestions in the comments below, and happy trading!
DECODE Moving Average ToolkitDECODE Moving Average Toolkit: Your All-in-One MA Analysis Powerhouse!
This versatile indicator is designed to be your go-to solution for analysing trends, identifying potential entry/exit points, and staying ahead of market movements using the power of Moving Averages (MAs).
Whether you're a seasoned trader or just starting out, the Decode MAT offers a comprehensive suite of features in a user-friendly package.
Key Features:
Multiple Moving Averages: Visualize up to 10 Moving Averages simultaneously on your chart.
Includes 5 Exponential Moving Averages (EMAs) and 5 Simple Moving Averages (SMAs).
Easily toggle the visibility of each MA and customize its length to suit your trading style and the asset you're analyzing.
Dynamic MA Ribbons: Gain a clearer perspective on trend direction and strength with 5 configurable MA Ribbons.
Each ribbon is formed between a corresponding EMA and SMA (e.g., EMA 20 / SMA 20).
The ribbon color changes to indicate bullish (e.g., green) or bearish (e.g., red) sentiment, providing an intuitive visual cue.
Toggle ribbon visibility with a single click.
Powerful Crossover Alerts: Never miss a potential trading opportunity with up to 5 customizable MA Crossover Alerts.
Define your own fast and slow MAs for each alert from any of the 10 available MAs.
Receive notifications directly through TradingView when your specified MAs cross over or cross under.
Optionally display visual symbols (e.g., triangles ▲▼) directly on your chart at the exact crossover points for quick identification.
Highly Customizable:
Adjust the source price (close, open, etc.) for all MA calculations.
Fine-tune the appearance (colors, line thickness) of every MA line, ribbon, and alert symbol to match your charting preferences.
User-Friendly Interface: All settings are neatly organized in the indicator's input menu, making configuration straightforward and intuitive.
How Can You Use the Decode MAT in Your Trading?
This toolkit is incredibly versatile and can be adapted to various trading strategies:
Trend Identification:
Use longer-term MAs (e.g., 50, 100, 200 period) to identify the prevailing market trend. When prices are consistently above these MAs, it suggests an uptrend, and vice-versa.
Observe the MA ribbons: A consistently green ribbon can indicate a strong uptrend, while a red ribbon can signal a downtrend. The widening or narrowing of the ribbon can also suggest changes in trend momentum.
Dynamic Support & Resistance:
Shorter-term MAs (e.g., 10, 20 period EMAs) can act as dynamic levels of support in an uptrend or resistance in a downtrend. Look for price pullbacks to these MAs as potential entry opportunities.
Crossover Signals (Entries & Exits):
Golden Cross / Death Cross: Configure alerts for classic crossover signals. For example, a 50-period MA crossing above a 200-period MA (Golden Cross) is often seen as a long-term bullish signal. Conversely, a 50-period MA crossing below a 200-period MA (Death Cross) can be a bearish signal.
Shorter-Term Signals: Use crossovers of shorter-term MAs (e.g., EMA 10 crossing EMA 20) for more frequent, shorter-term trading signals. A fast MA crossing above a slow MA can signal a buy, while a cross below can signal a sell.
Use the on-chart symbols for quick visual confirmation of these crossover events.
Confirmation Tool:
Combine the Decode MAT with other indicators (like RSI, MACD, or volume analysis) to confirm signals and increase the probability of successful trades. For instance, a bullish MA crossover combined with an oversold RSI reading could strengthen a buy signal.
Multi-Timeframe Analysis:
Apply the toolkit across different timeframes to get a broader market perspective. A long-term uptrend on the daily chart, confirmed by a short-term bullish crossover on the 1-hour chart, can provide a higher-confidence entry.
The DECODE Moving Average Toolkit empowers you to tailor your MA analysis precisely to your needs.
Mits Pixel BTCUSDStrategy
Using Rsi Stochastic, Hull Moving Average, Price Action and volume differences to get signals
HOW IT WORKS
Pixel parts :
- (U) The first pixel is a pixel that shows a trend during an uptrend, a trend when the market is considered bullish (above the MA line)
- (V) The second pixel is the volume pixel, showing the up and down movement of the buy / sell volume .
- (M) The third pixel is the momentum pixel, showing the market momentum whether it is overbought or oversold.
- (D) The fourth pixel is a pixel that shows a trend during a downtrend, a trend when the market is considered bearish (below the MA line)
When the price opens above the MA line, 3 pixels will appear, namely the first Pixel which is called the Trend up Pixel, Pixel Volume , and also the Momentum Pixel.
When the price opens below the MA line, 3 pixels will appear, namely Pixel Volume , Pixel Momentum, and the bottom one is the Pixel Down Trend.
* Pixel up trend (appears when the open is above the MA line)
- The pixel will show a solid green color when a gap up is opened or volume up, then the close price is greater than the open price.
- The pixel will show a light green color if there is normal strengthening (the close is bigger than the previous day's close without creating a gap up), then the close price is bigger than the open price.
- Pixel will show yellow color if it meets several criteria, for example, close is equal to open or close is bigger than the previous close but close is smaller than open.
- The pixel will show a dark red color when there is attenuation and a Gap down is created, then the close price is smaller than the open price.
- Pixel will show red color if there is normal weakening (close is smaller than the close of the previous day without creating a gap down), then the close price is smaller than the open price.
* Pixel down trend (appears when the open is below the Moving Average)
The pixel color indication is the same as the Trend up Pixel
* Volume Pixel
- The pixel is dark green when there is an increase and a gap up is created and the volume for that day is bigger than the volume of the previous day.
- The pixel will be green if there is a normal strengthening and also the volume for that day is greater than the volume of the previous day, or there is a gap up but the volume is smaller than the volume of the previous day.
- The pixel is yellow if it meets several conditions, for example, the volume of the day is the same as the volume of the previous day.
- The pixel is dark red when there is weakness and a Gap down is created and also the volume of the day's weakness is greater than the volume of the previous day.
- The pixel is red if there is normal weakening and also the volume of the day's weakness is bigger than the previous day's volume , or if there is a gap down but the volume is smaller than the previous day's volume .
* Momentum Pixel (basically StochRSI combined with other HMA , TopBox (Resistance), BottomBox(Support)).
- The pixel is dark green when it meets several conditions, for example the golden cross is below 50.
- The pixel is green if it meets several conditions, for example a golden cross below 50 without Gap up.
- Pixel will be yellow if it meets several conditions, for example k is greater than d and k has entered the overbought area (greater than 80).
- Pixel is dark red when it meets several conditions, for example k is smaller than d and k has entered the overbought area.
- Pixel is red when it meets several conditions, for example k is smaller than d and k is greater than 50 and k is less than 80.
Bar Color
Dark Green : Price Up + Volume Up
Green : Price Up + Volume Down
Dark Red : Price Down + Volume Up
Red : Price Down + Volume Down
Too many details that cannot be detailed one by one , but in broad outline as explained above.
HOW TO USE
* Signals Buy
- Strong Buy : All pixels are green, and Momentum Pixel is dark green.
- Normal Buy : All pixels are green or two dark green (one of them must momentum pixel) and one yellow.
- Spek Buy : * Two green pixels (one of them must momentum pixel) and one yellow or 1 green/dark green in momentum pixel, and other pixels yellow
* Signals Sell
- Strong Sell : All pixels are red, and Momentum Pixel is dark red.
- Normal Sell : All pixels are either red or two dark red (one of them must momentum pixel) and one yellow.
- Spek Sell : Two red pixels (one of them must momentum pixel) and one yellow or 1 dark red in momentum pixel, and other pixels yellow
- Warning Sell : Momentum pixels are dark red, regardless of the color of the other pixels.
* Best use for trading in BTCUSD markets
Thanks for Moderators
Canuck Trading IndicatorOverview
The Canuck Trading Indicator is a versatile, overlay-based technical analysis tool designed to assist traders in identifying potential trading opportunities across various timeframes and market conditions. By combining multiple technical indicators—such as RSI, Bollinger Bands, EMAs, VWAP, MACD, Stochastic RSI, ADX, HMA, and candlestick patterns—the indicator provides clear visual signals for bullish and bearish entries, breakouts, long-term trends, and options strategies like cash-secured puts, straddles/strangles, iron condors, and short squeezes. It also incorporates 20-day and 200-day SMAs to detect Golden/Death Crosses and price positioning relative to these moving averages. A dynamic table displays key metrics, and customizable alerts help traders stay informed of market conditions.
Key Features
Multi-Timeframe Adaptability: Automatically adjusts parameters (e.g., ATR multiplier, ADX period, HMA length) based on the chart's timeframe (minute, hourly, daily, weekly, monthly) for optimal performance.
Comprehensive Signal Generation: Identifies short-term entries, breakouts, long-term bullish trends, and options strategies using a combination of momentum, trend, volatility, and candlestick patterns.
Candlestick Pattern Detection: Recognizes bullish/bearish engulfing, hammer, shooting star, doji, and strong candles for precise entry/exit signals.
Moving Average Analysis: Plots 20-day and 200-day SMAs, detects Golden/Death Crosses, and evaluates price position relative to these averages.
Dynamic Table: Displays real-time metrics, including zone status (bullish, bearish, neutral), RSI, MACD, Stochastic RSI, short/long-term trends, candlestick patterns, ADX, ROC, VWAP slope, and MA positioning.
Customizable Alerts: Over 20 alert conditions for entries, exits, overbought/oversold warnings, and MA crosses, with actionable messages including ticker, price, and suggested strategies.
Visual Clarity: Uses distinct shapes, colors, and sizes to plot signals (e.g., green triangles for bullish entries, red triangles for bearish entries) and overlays key levels like EMA, VWAP, Bollinger Bands, support/resistance, and HMA.
Options Strategy Signals: Suggests opportunities for selling cash-secured puts, straddles/strangles, iron condors, and capitalizing on short squeezes.
How to Use
Add to Chart: Apply the indicator to any TradingView chart by selecting "Canuck Trading Indicator" from the Pine Script library.
Interpret Signals:
Bullish Signals: Green triangles (short-term entry), lime diamonds (breakout), blue circles (long-term entry).
Bearish Signals: Red triangles (short-term entry), maroon diamonds (breakout).
Options Strategies: Purple squares (cash-secured puts), yellow circles (straddles/strangles), orange crosses (iron condors), white arrows (short squeezes).
Exits: X-cross shapes in corresponding colors indicate exit signals.
Monitor: Gray circles suggest holding cash or monitoring for setups.
Review Table: Check the top-right table for real-time metrics, including zone status, RSI, MACD, trends, and MA positioning.
Set Alerts: Configure alerts for specific signals (e.g., "Short-Term Bullish Entry" or "Golden Cross") to receive notifications via TradingView.
Adjust Inputs: Customize input parameters (e.g., RSI period, EMA length, ATR period) to suit your trading style or market conditions.
Input Parameters
The indicator offers a wide range of customizable inputs to fine-tune its behavior:
RSI Period (default: 14): Length for RSI calculation.
RSI Bullish Low/High (default: 35/70): RSI thresholds for bullish signals.
RSI Bearish High (default: 65): RSI threshold for bearish signals.
EMA Period (default: 15): Main EMA length (15 for day trading, 50 for swing).
Short/Long EMA Length (default: 3/20): For momentum oscillator.
T3 Smoothing Length (default: 5): Smooths momentum signals.
Long-Term EMA/RSI Length (default: 20/15): For long-term trend analysis.
Support/Resistance Lookback (default: 5): Periods for support/resistance levels.
MACD Fast/Slow/Signal (default: 12/26/9): MACD parameters.
Bollinger Bands Period/StdDev (default: 15/2): BB settings.
Stochastic RSI Period/Smoothing (default: 14/3/3): Stochastic RSI settings.
Uptrend/Short-Term/Long-Term Lookback (default: 2/2/5): Candles for trend detection.
ATR Period (default: 14): For volatility and price targets.
VWAP Sensitivity (default: 0.1%): Threshold for VWAP-based signals.
Volume Oscillator Period (default: 14): For volume surge detection.
Pattern Detection Threshold (default: 0.3%): Sensitivity for candlestick patterns.
ROC Period (default: 3): Rate of change for momentum.
VWAP Slope Period (default: 5): For VWAP trend analysis.
TradingView Publishing Compliance
Originality: The Canuck Trading Indicator is an original script, combining multiple technical indicators and custom logic to provide unique trading signals. It does not replicate existing public scripts.
No Guaranteed Profits: This indicator is a tool for technical analysis and does not guarantee profits. Trading involves risks, and users should conduct their own research and risk management.
Clear Instructions: The description and usage guide are detailed and accessible, ensuring users understand how to apply the indicator effectively.
No External Dependencies: The script uses only built-in Pine Script functions (e.g., ta.rsi, ta.ema, ta.vwap) and requires no external libraries or data sources.
Performance: The script is optimized for performance, using efficient calculations and adaptive parameters to minimize lag on various timeframes.
Visual Clarity: Signals are plotted with distinct shapes and colors, and the table provides a concise summary of market conditions, enhancing usability.
Limitations and Risks
Market Conditions: The indicator may generate false signals in choppy or low-liquidity markets. Always confirm signals with additional analysis.
Timeframe Sensitivity: Performance varies by timeframe; test settings on your preferred chart (e.g., 5-minute for day trading, daily for swing trading).
Risk Management: Use stop-losses and position sizing to manage risk, as suggested in alert messages (e.g., "Stop -20%").
Options Trading: Options strategies (e.g., straddles, iron condors) carry unique risks; consult a financial advisor before trading.
Feedback and Support
For questions, suggestions, or bug reports, please leave a comment on the TradingView script page or contact the author via TradingView. Your feedback helps improve the indicator for the community.
Disclaimer
The Canuck Trading Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
Multi Moving Average with CustomizationCore Functionality
The indicator allows you to display up to 5 different moving averages on your chart simultaneously.
Each moving average can be fully customized with its own settings.
You can choose between
1. Simple Moving Average (SMA),
2. Exponential Moving Average (EMA)
3. Weighted Moving Average (WMA) types
Multi-Timeframe Support
One standout feature is the ability to display higher timeframe moving averages on lower timeframe charts.
For example, you can show a 200 EMA from the daily chart while viewing a 15-minute chart.
Advanced Visualization Features
The indicator includes several visualization enhancements:
1. MA Cloud - Creates a filled area between any two selected moving averages. The cloud automatically changes color based on which MA is on top - typically green when the faster MA is above (bullish) and red when below (bearish).
2. Golden/Death Cross Detection - Automatically detects and marks important MA crossover events:
* Golden Cross: When a shorter-term MA crosses above a longer-term MA (bullish signal)
* Death Cross: When a shorter-term MA crosses below a longer-term MA (bearish signal)
3. Trend Background - Colors the entire chart background based on whether price is above or below a specified MA, giving a clear visual indicator of the overall trend.
Alert System
The indicator can generate alerts when price crosses above or below any selected moving average. This feature is useful for automated trading signals or notifications, and can be configured to trigger once per bar.
Flexible Architecture
The code uses several programming techniques to maximize flexibility:
* Switch statements for selecting MA types and cloud values
* Conditional logic throughout the code
* Function abstraction for calculating MAs and handling multi-timeframe display
* String identifiers to select which MAs to use for cloud visualization
Unique Technical Aspects
1. The multi-timeframe plotting function solves the common problem of higher timeframe MAs looking distorted on lower timeframe charts.
2. The cloud feature uses string identifiers to select which MAs to use, allowing for any combination.
3. The indicator employs smart conditional logic to handle complex decision trees efficiently.
4. Every visual aspect (colors, line widths, display conditions) is customizable through the settings.
This indicator combines multiple technical analysis tools into a single, highly configurable package that can adapt to different trading styles and timeframes.
Its ability to correctly display higher timeframe MAs on lower timeframe charts makes it particularly valuable for traders who analyze multiple timeframes simultaneously.
NeuroFlow Pro IndicatorThe **NeuroFlow Pro Indicator** is a comprehensive technical analysis tool designed for traders on the TradingView platform. It provides actionable buy and sell signals by combining multiple technical indicators, including Moving Averages, MACD, RSI, Stochastic RSI, SuperTrend, Ichimoku Cloud, Bollinger Bands, and Volume analysis. The indicator generates a **Composite Score** (0–100) that reflects market conditions, with low scores indicating bullish opportunities and high scores suggesting bearish conditions. It also identifies key trend reversal points and significant EMA crossovers (Golden Cross and Death Cross) to help traders make informed decisions.
**Key Features**:
- **Composite Score**: Aggregates signals from multiple indicators to provide a single, easy-to-read metric.
- **Buy/Sell Signals**: Generates clear signals for potential long (buy) and short (sell) opportunities.
- **Golden/Death Cross**: Marks EMA 50 crossing above (🚀) or below (💀) EMA 200, indicating major trend shifts.
- **Dashboard**: Displays real-time metrics like trend direction, momentum, volume, and signal confidence.
- **Customizable Alerts**: Notifies users of buy/sell signals, divergences, and EMA crossovers via TradingView’s alert system.
- **Multi-Timeframe Analysis**: Incorporates higher timeframe trends for enhanced signal reliability.
- **Candlestick Patterns**: Optionally includes patterns like Hammer, Engulfing, or Morning Star for signal confirmation.
This indicator is ideal for traders seeking a robust, all-in-one tool to identify trading opportunities across various markets (e.g., crypto, stocks, forex) and timeframes (e.g., 1H, 4H, daily).
User Guide for NeuroFlow Pro Indicator
Understanding the Indicator
- **Dashboard**:
- Located on the chart (left or right, configurable), it shows real-time metrics:
- **Comp Score**: Composite Score (0–100); low (<30) is bullish, high (>70) is bearish.
- **Trend**: Bullish, Bearish, or Neutral
- **MTF Trend**: Trend from a higher timeframe (e.g., 60m or 240m).
- **Momentum**: RSI and Stochastic RSI-based momentum (Bullish, Bearish, Neutral).
- **MFI**: Money Flow Index (Inflow, Outflow, Neutral).
- **Volatility**: High or Low based on ATR and Bollinger Bands.
- **Volume**: High, Low, or Neutral relative to volume MA.
- **Ichimoku**: Bullish, Bearish, or Neutral based on cloud position.
- **ADX Strength**: Strong or Weak trend based on ADX.
- **Divergence**: Bullish, Bearish, or Neutral for RSI/MACD divergences.
- **Reversal**: Bullish or Bearish reversal potential with confidence percentage.
- **Signal Status**: Long (buy), Short (sell), or None.
- **Signal Confid**: Confidence percentage for the current signal.
- **Chart Visuals**:
- **EMA 50 (White)**: Fast-moving average for short-term trends.
- **EMA 200 (Blue)**: Long-moving average for long-term trends.
- **Golden Cross (🚀)**: Green rocket emoji when EMA 50 crosses above EMA 200 (bullish).
- **Death Cross (💀)**: Red skull emoji when EMA 50 crosses below EMA 200 (bearish).
- **Alerts**:
- Configurable for Buy/Sell Signals, Golden/Death Cross, and Bullish/Bearish Divergences.
Configuring Settings
1. **Open Settings**:
- Right-click the indicator’s name on the chart and select “Settings,” or double-click the indicator in the chart’s indicator list.
2. **Key Settings to Customize**:
- **Strategy Settings**:
- **Max ATR Multiplier**: Adjusts sensitivity to volatility (default: 3.0).
- **Main Settings**:
- **Candlestick Pattern**: Choose Hammer, Engulfing, Morning Star, or Custom (default: Hammer).
- **Multi-Timeframe Period**: Set higher timeframe for trend analysis (e.g., 60m, 240m, Daily; default: 60m).
- **Higher Timeframe**: Secondary timeframe for confirmation (default: 240m).
- **Use Candlestick Patterns**: Enable/disable pattern-based signals (default: off).
- **Use Volume Filter**: Require high volume for signals (default: on).
- **Use ADX Filter**: Require strong trend for signals (default: on).
- **Momentum Settings**:
- **RSI/Stochastic/MFI Lengths**: Adjust periods for RSI, Stochastic RSI, and MFI (defaults: 14, 14, 60).
- **EMA Lengths**: Fast (50), Slow (100), Long (200) for trend and crossovers.
- **ATR/ADX Lengths**: Volatility and trend strength periods (default: 14).
- **SuperTrend/Bollinger/Ichimoku Settings**:
- Customize periods and multipliers (defaults: SuperTrend 10/3.0, Bollinger 20/2.0, Ichimoku 9/26/52).
- **MACD Settings**:
- **MACD Preset**: Auto (timeframe-based), 1H (3-10-16), 4H (5-34-21), D (5-15-9), or Custom (default: Auto).
- **Custom MACD Lengths**: Fast (12), Slow (26), Signal (9) for Custom preset.
- **Weights Settings**:
- Adjust weights for trend, momentum, volatility, etc., to prioritize certain indicators (defaults: Trend 1.0, Momentum 0.3, etc.).
- **Threshold Settings**:
- **Bullish/Bearish Reversal Thresholds**: Set score thresholds for reversals (default: 30/70).
- **ADX Threshold**: Minimum ADX for trend strength (default: 20).
- **Signal Thresholds**: Base (70) and alert (80) thresholds for signals.
- **Dashboard Settings**:
- **Position**: Left or Right (default: Right).
- **Show/Hide Metrics**: Enable/disable dashboard rows (e.g., Comp Score, Trend, MFI; all enabled by default except Volatility and Volume MA).
3. **Save Changes**:
- Click “OK” to apply settings. The dashboard and plots update instantly.
Using the Indicator
1. **Interpreting Signals**:
- **Buy Signal (Long)**: Appears when Composite Score is low (≤30), with at least two bullish confirmations . Shown as “Long” in Signal Status with confidence percentage.
- **Sell Signal (Short)**: Appears when Composite Score is high (≥70), with at least two bearish confirmations. Shown as “Short” in Signal Status.
- **Golden Cross (🚀)**: Indicates a bullish trend when EMA 50 crosses above EMA 200. Look for confirmation from Composite Score and Signal Status.
- **Death Cross (💀)**: Indicates a bearish trend when EMA 50 crosses below EMA 200. Confirm with dashboard metrics.
- **Reversal Signals**: Dashboard shows “Bullish” or “Bearish” with a percentage when reversal conditions are met .
2. **Monitoring the Dashboard**:
- Use the dashboard to assess market conditions in real-time.
- Green (bullish), red (bearish), or gray (neutral) colors highlight key metrics.
- Check “Signal Confid” for confidence in buy/sell signals (higher is better, e.g., >60%).
3. **Trading Decisions**:
- Combine signals with your own analysis (e.g., support/resistance, news).
- Use Golden/Death Cross for long-term trend confirmation.
- Avoid trading in high volatility (dashboard: “Volatility: High”) unless experienced
Best Practices
- **Timeframe Selection**:
- Use higher timeframes (e.g., 4H, Daily) for more reliable signals, especially for Golden/Death Cross.
- Lower timeframes (e.g., 5m, 15m) may produce more signals but with higher noise.
- **Confirm Signals**:
- Cross-check buy/sell signals with dashboard metrics (e.g., Trend, MFI, ADX).
- Use Golden/Death Cross as a trend filter rather than a standalone signal.
- **Risk Management**:
- Always use stop-losses and position sizing based on your risk tolerance.
- Avoid trading during high volatility unless part of your strategy.
- **Regular Updates**:
- Monitor TradingView for script updates from the author (KoKalito) to access new features or bug fixes.
Troubleshooting
- **No Signals**:
- Ensure the chart timeframe matches your settings (e.g., 60m for MTF Period).
- Check if filters (Volume, ADX) are too strict; try disabling them.
- **Dashboard Missing**:
- Verify “Dashboard Position” is set to Left or Right.
- Ensure dashboard metrics are enabled (e.g., Show Comp Score).
- **Alerts Not Triggering**:
- Confirm the alert condition is set to “NeuroFlow Pro Indicator” and the correct option (e.g., “Golden Cross Alert”).
- Check TradingView’s “Alerts” panel for errors or expired alerts.
- Reapply the indicator to the chart if it was recently updated.
- **EMA Crosses Not Showing**:
- Zoom in on the chart to see 🚀 (Golden Cross) or 💀 (Death Cross) symbols.
- Ensure EMA 50 and EMA 200 lengths are not identical (defaults: 50, 200).
Support
- **Author**: KoKalito (check TradingView profile for updates or contact info).
- **TradingView Community**: Post questions in the TradingView Pine Script community or forums.
- **Documentation**: Refer to TradingView’s Pine Script v5 documentation for advanced customization.
- **Risk Warning**: Trading involves risk. Use the indicator as a tool, not a guarantee of profits. Always conduct your own analysis and manage risk appropriately.
Happy trading with **NeuroFlow Pro Indicator**! 🚀
GEX and OI levelsIntroduction
Harness the power of institutional options flow analysis with the GEX & OI Levels indicator – an advanced tool that brings professional-grade options analytics directly to your TradingView charts. This comprehensive indicator visualizes Gamma Exposure (GEX) and Open Interest (OI) data, revealing hidden market forces that drive price action and potential reversal points. Designed for serious traders who understand that options positioning often precedes price movement.
What Is GEX & OI Levels?
GEX & OI Levels is a sophisticated indicator that analyzes options market positioning through the lens of dealer gamma exposure and open interest concentration. By visualizing where market makers must hedge their options positions, you can identify potential support/resistance levels, price magnets, and likely volatility zones. The indicator processes strike-by-strike options data to generate actionable insights about institutional positioning and potential price behavior.
Key Features
Complete Gamma Exposure Analysis
Dynamic GEX histogram showing dealer positioning at each strike
Visual identification of positive and negative gamma zones
Smoothed total GEX calculation with customizable parameters
Zero gamma level identification - critical price points where dealer behavior changes
Critical Price Level Identification
Gamma flip points that often act as magnets for price
Gamma walls where significant hedging activity may create support/resistance
Golden strike detection where both call and put OI show unusual concentration
Max pain calculation showing the price point where options expiration causes maximum loss
Dealer Positioning Intelligence
Analysis of dealer hedging requirements for price movements
Calculation of expected dealer behavior during rallies and dips
Signal strength indicators showing potential hedging impact
Delta-adjusted GEX for more accurate near-expiration analysis
Comprehensive Data Visualization
Highly configurable visualization of GEX histogram with logarithmic scaling
Strike-by-strike data table with color-coded gamma values
Top OI levels for both calls and puts with customizable highlighting
Detailed metrics panel showing all key GEX and options analytics
Use Cases
1. Identifying Potential Price Magnets
Gamma flip points often act as magnets for price, especially near expiration
Zero gamma levels show where dealer hedging pressure changes direction
Golden strikes reveal where both call and put sellers have significant exposure
2. Discovering Support & Resistance Zones
Gamma walls indicate where dealer hedging may create price barriers
Top OI levels often become psychological support/resistance points
Max pain level shows where options writers have incentive to push price
3. Predicting Market Volatility
Low GEX environments signal potential for increased volatility
High GEX environments typically lead to price compression and reduced volatility
Dealer positioning metrics indicate whether market makers are dampening or amplifying moves
4. Timing Market Reversals
Extreme dealer positioning often precedes market reversals
Proximity to flip points provides timing signals for potential turns
Signal strength measurement helps quantify the potential impact
5. Enhancing Trading Strategy
Align your trades with or against dealer hedging flows
Use dealer positioning analysis to set more precise stop losses and targets
Combine with technical analysis for high-probability trading setups
Customization Options
The indicator offers extensive customization capabilities:
Data Input & Configuration
CSV data input for option chain information
Adjustable DTE (Days To Expiration) settings
Risk-free rate and implied volatility parameters
Custom symbol formatting for different data providers
Calculation Settings
Gamma weight multiplier for sensitivity adjustment
Strike range limitations to focus on relevant price zones
Gamma scaling options based on strike distance
Static IV mode for environments without option price data
Visualization Options
Customizable histogram appearance including scale and transparency
Color settings for positive/negative GEX, flip points, and gamma walls
OI level display with configurable number of levels
Strike data table with adjustable strike count
Analytics Settings
Delta-adjusted GEX for improved accuracy
Dealer positioning analytics with hedge efficiency parameters
Alerting capabilities for price approaching key levels
Golden strike highlighting for significant option activity zones
How to Use
Apply the indicator to your chart
Input your options data in CSV format using the required structure
Configure the expiration date to match your analysis timeframe
Adjust gamma calculation parameters based on your instrument
Use the GEX histogram and key levels to identify potential price targets
Monitor dealer positioning metrics to anticipate market behavior
Trade with confidence knowing where institutional hedging activity is concentrated
Perfect for options traders, futures traders, swing traders, and anyone who wants to incorporate institutional-level options analysis into their technical trading strategy.
Elevate your trading with GEX & OI Levels - where options positioning reveals future price action.
Global ETF Capital FlowsThe Global ETF Capital Flows indicator is designed as a research and monitoring tool for identifying capital allocation trends across major global exchange-traded funds (ETFs). It provides standardized fund flow data for regional equity markets (including the United States, Europe, Asia, and Emerging Markets), as well as alternative asset classes such as bonds and gold.
Fund flows into and out of ETFs are increasingly recognized as a leading indicator of investor behavior, particularly in the context of tactical asset allocation and risk appetite (Ben-David et al., 2017). By tracking aggregated ETF flows, the script enables the user to detect shifts in global investment preferences, which may precede price action and influence broader macro trends (Bank of International Settlements, 2018). For example, consistent inflows into U.S. large-cap ETFs such as SPY or QQQ may signal heightened investor confidence in domestic equities, whereas rising flows into bond ETFs such as TLT may suggest a flight to safety or expectations of declining interest rates (Israeli et al., 2017).
The visualization aspect of the script uses standardized z-scores to represent cumulative flows over a specified period. This normalization allows users to compare fund flows across regions and asset classes on a relative basis, filtering out scale differences and allowing for more effective cross-market analysis. According to Coates and Herbert (2008), normalization techniques such as z-scores are crucial in behavioral finance research, as they help detect anomalies and emotional extremes in investor activity.
Practically, this indicator is suited for top-down macro analysis, sector rotation strategies, and confirmation of technical signals. For instance, significant positive deviations in the standardized flow data for European ETFs may support a bullish bias on regional equities, especially if corroborated by technical breakouts or improving economic indicators. Conversely, elevated inflows into gold ETFs may be interpreted as hedging behavior against geopolitical uncertainty or inflationary pressure, consistent with historical patterns of gold’s role as a safe haven (Baur and Lucey, 2010).
Additionally, the tool allows for visual alerts when flow anomalies exceed a user-defined threshold, thereby supporting more responsive and data-driven decision-making. This feature aligns with findings from the CFA Institute (2019), which emphasize the growing importance of alternative data and automated alert systems in modern portfolio management.
From a research perspective, the indicator facilitates empirical study into capital mobility, intermarket relationships, and ETF investor psychology. It offers real-time monitoring of region-specific investment flows, thus serving as a proxy for investor conviction, liquidity trends, and cross-border risk-on/risk-off sentiment. Several recent studies have demonstrated the predictive power of ETF flows on future returns and volatility, particularly during periods of market stress or structural dislocations (Madhavan, 2016; Pan and Zeng, 2019).
References
• Baur, D.G. and Lucey, B.M., 2010. Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), pp.217-229.
• Ben-David, I., Franzoni, F. and Moussawi, R., 2017. Exchange-traded funds (ETFs). Annual Review of Financial Economics, 9, pp.169–189.
• Bank of International Settlements (BIS), 2018. ETFs – growing popularity, growing risks? BIS Quarterly Review, March 2018.
• CFA Institute, 2019. Investment Professional of the Future. Available at: www.cfainstitute.org .
• Coates, J.M. and Herbert, J., 2008. Endogenous steroids and financial risk taking on a London trading floor. Proceedings of the National Academy of Sciences, 105(16), pp.6167–6172.
• Israeli, D., Lee, C.M. and Sridharan, S.A., 2017. Is there a dark side to ETF trading? Evidence from corporate bond ETFs. SSRN Working Paper. Available at SSRN: ssrn.com
• Madhavan, A., 2016. Exchange-Traded Funds and the New Dynamics of Investing. Oxford University Press.
• Pan, K. and Zeng, Y., 2019. ETF Arbitrage Under Liquidity Mismatch. Journal of Finance, 74(6), pp.2731–2783.
Fibonacci + TP/SL Strategy [Backtest]✅ Key Features Added and Adjusted:
Fibonacci Retracement Levels:
Automatically calculated based on the last 100 bars' high/low
Plotted levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
Extension targets: 161.8%, 261.8%, 423.6%
Buy/Sell Signal Logic:
Buy: Price is between 78.6% and 38.2% levels
Sell: Price is between 61.8% and 23.6% levels
Both depend on a can_trade time filter to avoid overtrading
ATR-based Stop-Loss:
Stop-loss dynamically adapts to market volatility:
SL = Entry - ATR * 1.5 (long)
SL = Entry + ATR * 1.5 (short)
Fixed Take-Profit:
Configurable via input: default is 4%
Can be changed in TradingView UI
Golden/Death Cross Indicator (Visual Only):
EMA 50 crossing EMA 200 plotted on chart:
Golden Cross = Buy signal (green triangle)
Death Cross = Sell signal (red triangle)
Weekly Profit Cap:
Prevents new trades if weekly profit exceeds 15%
Resets at the start of every week
Visual Elements:
All Fibonacci levels are plotted
Buy/Sell signals are labeled on the chart (BUY, SELL)
