Range Breakout [sgbpulse]Range Breakout
1. Overview
The "Range Breakout " indicator is a powerful tool designed to identify and visually display price ranges on your chart using pivot points. It dynamically draws two distinct boxes – an External Range and an Internal Range – helping traders pinpoint potential support and resistance zones. Beyond its visual representation, the indicator offers a comprehensive set of 12 unique breakout alerts, providing real-time notifications for significant price movements outside these defined ranges. Additionally, it integrates RSI and MFI metrics for momentum confirmation.
2. How It Works
The indicator operates by identifying pivot points based on user-defined "left" and "right" bar lengths. A high pivot is a bar with a specified number of lower highs both to its left and right, and similarly for a low pivot.
External Range: Calculated using longer pivot lengths (default: 15 bars left, 6 bars right). This range represents broader, more significant price consolidation areas.
Internal Range: Calculated using shorter pivot lengths (default: 4 bars left, 3 bars right). This range captures tighter, more immediate price consolidations within the broader trend.
The External Range will always be greater than or equal to the Internal Range, as it's based on a wider historical context. Both ranges are displayed as transparent boxes on your chart, dynamically adjusting as new pivots are formed.
3. Key Features and Settings
Customizable Pivot Lengths:
External Range (Left/Right Bars): Adjust sensitivity for identifying the broader price range. Longer lengths lead to more stable, but less frequent, range updates.
Internal Range (Left/Right Bars): Adjust sensitivity for the tighter, more immediate price range.
Tool Tips: Minimum 6 bars for the External Range, and minimum 2 bars for the Internal Range.
Customizable Range Colors: Easily change the background colors of the External and Internal Range boxes to match your chart's aesthetic.
Dynamic Range Display: The indicator automatically updates the range boxes as new pivot highs and lows are formed, always presenting the most current valid ranges.
RSI / MFI Settings:
Timeframe Source: Select the timeframe for RSI and MFI calculation.
- Chart: Calculation based on the current chart timeframe.
- Daily: Always calculated based on the daily ("D") timeframe, even if the chart is on a lower timeframe.
RSI Length: Period length for RSI calculation (default: 14).
RSI Overbought Level: Overbought level for RSI (default: 70.0).
RSI Oversold Level: Oversold level for RSI (default: 30.0).
MFI Length: Period length for MFI calculation (default: 14).
MFI Overbought Level: Overbought level for MFI (default: 80.0).
MFI Oversold Level: Oversold level for MFI (default: 20.0).
4. Synergy of Ranges & Breakout Strength
The interaction between the External and Internal Ranges provides deep insights into price movement and breakout strength:
Immediate Direction: The movement of the Internal Range (up or down) indicates the short-term directional bias within the broader framework of the External Range.
Strength Confirmation: A breakout of the External Range, followed by a breakout of the Internal Range, confirms the strength of the move and increases confidence in the breakout.
Strong Momentum ("Leaving" Ranges Behind): When price breaks out with exceptionally strong momentum, it continues to move aggressively and does not immediately form new pivots. In such situations, the existing ranges (External and Internal) remain in place while the candles "leave them behind." A "Full Candle" breakout, where the entire candle moves past both ranges, indicates a particularly powerful and decisive move.
Momentum (RSI / MFI) as Confirmation:
- RSI (Relative Strength Index): Measures the speed and change of price movements. Extreme values (above 70 or below 30) indicate overbought/oversold conditions respectively, confirming strong momentum in a breakout.
- MFI (Money Flow Index): Similar to RSI but incorporates volume. Extreme values (above 80 or below 20) indicate strong money flow in/out, reinforcing breakout confirmation.
- Importance of Confirmation: If a breakout occurs but momentum indicators do not confirm it (for example, an upside breakout while RSI is declining), this could signal weakness in the move and the risk of a false breakout (Fakeout).
5. Visuals
The indicator provides clear visual representations on the chart:
Range Boxes:
Two dynamic boxes are drawn on the chart: one for the External Range and one for the Internal Range.
These boxes update continuously, displaying the current range boundaries based on the latest pivots. They provide an immediate visual indication of support and resistance levels.
RSI/MFI Status Labels:
Small text labels appear to the right of the current bar, vertically centered.
They display the status of RSI and MFI: RSI OB (Overbought), RSI OS (Oversold), MFI OB, MFI OS, along with the exact value.
Important: The labels remain on the chart as long as the condition holds (indicator is above/below the level), unlike alerts which mark a singular crossover event.
Plotting of Key Values:
The indicator plots six invisible series on the chart, primarily to allow the user to view the exact numerical values of:
- The upper and lower bounds of the External Range (External High, External Low).
- The upper and lower bounds of the Internal Range (Internal High, Internal Low).
- The calculated RSI and MFI values (RSI, MFI).
These values are accessible for viewing through TradingView's Data Window and also via the Status Line when hovering over the relevant candle. This enables more precise quantitative analysis of range levels and momentum.
6. Comprehensive Breakout Alerts
The "Range Breakout " indicator provides 12 distinct alert conditions for breakouts, allowing you to select the required level of confirmation for each alert. All alerts are triggered only upon a fully confirmed bar close (barstate.isconfirmed) to minimize false signals and ensure reliability.
All breakout alerts are configured to detect a Crossover/Crossunder of the levels, meaning a specific event where the price moves from one side of the range to the other.
External Range Breakout UP
- Close: Price closes above the External Range.
- Real Body: The entire "real body" of the candle (min of open/close prices) closes above the External Range.
- Full Candle: The entire candle (the lowest point of the candle) closes above the External Range.
External Range Breakout DOWN
- Close: Price closes below the External Range.
- Real Body: The entire "real body" of the candle (max of open/close prices) closes below the External Range.
- Full Candle: The entire candle (the highest point of the candle) closes below the External Range.
Internal Range Breakout UP
- Close: Price closes above the Internal Range.
- Real Body: The "real body" of the candle closes above the Internal Range.
- Full Candle: The entire candle closes above the Internal Range.
Internal Range Breakout DOWN
- Close: Price closes below the Internal Range.
- Real Body: The "real body" of the candle closes below the Internal Range.
- Full Candle: The entire candle closes below the Internal Range.
7. Ideal Use Cases
This indicator is ideal for traders who:
Want to clearly identify and monitor price consolidation zones.
Seek confirmation for breakout strategies across various timeframes.
Require reliable and automated alerts for potential entry or exit points based on range expansion.
8. Complementary Indicator
For even more comprehensive market analysis, we highly recommend using this indicator in conjunction with Market Structure Support & Resistance External/Internal & BoS .
This powerful complementary indicator automatically and accurately identifies significant support and resistance levels by locating high and low pivot points, as well as key Pre-Market High/Low levels. Its strength lies in its dynamic adaptability to any timeframe and asset, providing precise and relevant real-time levels while maintaining a clean chart. It also identifies Break of Structure (BoS) to signal potential trend changes or continuations.
Using both indicators together provides a robust framework for identifying defined ranges and potential trend shifts, enabling more informed trading decisions.
View Market Structure Support & Resistance External/Internal & BoS Indicator
9. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
在腳本中搜尋"daily"
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.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Market Matrix ViewThis technical indicator is designed to provide traders with a quick and integrated view of market dynamics by combining several popular indicators into a single tool. It's not a magic bullet, but a practical aid for analyzing buying/selling pressure, trends, volume, and divergences, saving you time in the decision-making process. Built for flexibility, the indicator adapts to various trading styles (scalping, swing, or long-term) and offers customizable settings to suit your needs.
🟡 Multi-Timeframe Trends
➤ This section displays the trend direction (bullish, bearish, or neutral) across 15-minute, 1-hour, 4-hour, and Daily timeframes, providing multi-timeframe market context. Timeframes lower than the one currently selected will show "N/A."
➤It utilizes fast and slow Exponential Moving Averages (EMAs) for each timeframe:
15m: Fast EMA 42, Slow EMA 170
1h: Fast EMA 40, Slow EMA 100
4h: Fast EMA 36, Slow EMA 107
Daily: Fast EMA 20, Slow EMA 60
🟡 Smart Flow & RVOL
➤ This section displays "Buying Pressure" or "Selling Pressure" signals based on indicator confluence, alongside volume activity ("High Activity," "Normal Activity," or "Low Activity").
➤ Smart Flow combines Chaikin Money Flow (CMF) and Money Flow Index (MFI) to detect buying/selling pressure. CMF measures money flow based on price position within the high-low range, while MFI analyzes money flow considering typical price and volume. A signal is generated only when both indicators simultaneously increase/decrease beyond an adjustable threshold ("Buy/Sell Sensitivity") and volume exceeds a Simple Moving Average (SMA) scaled by the "Volume Multiplier."
➤ RVOL (Relative Volume) calculates relative volume separately for bullish and bearish candles, comparing recent volume (fast SMA) with a reference volume (slow SMA). Thresholds are adjusted based on the selected mode.
🟡 ADX & RSI
This section displays trend strength ("Strong," "Moderate," or "Weak"), its direction ("Bullish" or "Bearish"), and the RSI momentum status ("Overbought," "Oversold," "Buy/Sell Momentum," or "Neutral").
➤ ADX (Average Directional Index) measures trend strength (above 40 = "Strong," 20–40 = "Moderate," below 20 = "Weak"). Direction is determined by comparing +DI (upward movement) with -DI (downward movement). Additionally, an arrow indicates whether the trend's strength is decreasing or increasing.
➤RSI (Relative Strength Index) evaluates price momentum. Extreme levels (above 80/85 = "Overbought," below 15/20 = "Oversold") and intermediate zones (47–53 = "Neutral," above 53 = "Buy Momentum," below 47 = "Sell Momentum") are adjusted based on the selected mode.
🟡 When these signals are active for a potential trade setup, the table's background lights up green or red, respectively.
🟡 Volume Spikes
➤This feature highlights bars with significantly higher volume than the recent average, coloring them yellow on the chart to draw attention to intense market activity.
➤It uses the Z-Score method to detect volume anomalies. Current volume is compared to a 10-bar Simple Moving Average (SMA) and the standard deviation of volume over the same period. If the Z-Score exceeds a certain threshold, the bar is marked as a volume spike.
🟡 Divergences (Volume Divergence Detection)
➤ This feature marks divergences between price and technical indicators on the chart, using diamond-shaped labels (green for bullish divergences, red for bearish divergences) to signal potential trend reversals.
➤ It compares price deviations from a Simple Moving Average (SMA) with deviations of three indicators: Chaikin Money Flow (CMF), Money Flow Index (MFI), and On-Balance Volume (OBV). A bullish divergence occurs when price falls below its average, but CMF, MFI, and OBV rise above their averages, indicating hidden accumulation. A bearish divergence occurs when price rises above its average, but CMF, MFI, and OBV fall, suggesting distribution. The length of the moving averages is adjustable (default 13/10/5 bars for Scalping/Balanced/Swing), and detection thresholds are scaled by "Divergence Sensitivity" (default 1.0).
🟡 Adaptive Stop-Loss (ATR)
➤Draws dynamic stop-loss lines (red, dashed) on the chart for buy or sell signals, helping traders manage risk.Uses the Average True Range (ATR) to calculate stop-loss levels, set at low/high ± ATR × multiplier
🟡 Alerts for trend direction changes in the Info Panel:
➤ Triggers notifications when the trend shifts to Bullish (when +DI crosses above -DI) or Bearish (when +DI crosses below -DI), helping you stay informed about key market shifts.
How to use: Set alerts in Trading View for “Trend Changed to Bullish” or “Trend Changed to Bearish” with “Once Per Bar Close” for reliable signals.
🟡 Settings (Inputs)
➤ The indicator offers customizable settings to fit your trading style, but it's already optimized for Scalping (1m–15m), Balanced (16m–3h59m), and Swing (4h–Daily) modes, which automatically adjust based on the selected timeframe. The visible inputs allow you to adjust the following parameters:
Show Info Panel: Enables/disables the information panel (default: enabled).
Show Volume Spikes: Turns on/off coloring for volume spike bars (default: enabled).
Spike Sensitivity: Controls the Z-Score threshold for detecting volume spikes (default: 2.0; lower values increase signal frequency).
Show Divergence: Enables/disables the display of divergence labels (default: enabled).
Divergence Sensitivity: Adjusts the thresholds for divergence detection (default: 1.0; higher values reduce sensitivity).
Divergence Lookback Length: Sets the length of the moving averages used for divergences (default: 5, automatically adjusted to 13/10/5 for Scalping/Balanced/Swing).
RVOL Reference Period: Defines the reference period for relative volume (default: 20, automatically adjusted to 7/15/20).
RSI Length: Sets the RSI length (default: 14, automatically adjusted to 5/10/14).
Buy Sensitivity: Controls the increase threshold for Buying Pressure signals (default: 0.007; higher values reduce frequency).
Sell Sensitivity: Controls the decrease threshold for Selling Pressure signals (default: 0.007; higher values reduce frequency).
Volume Multiplier (B/S Pressure): Adjusts the volume threshold for Smart Flow signals (default: 0.6; higher values require greater volume).
🟡 This indicator is created to simplify market analysis, but I am not a professional in Pine Script or technical indicators. This indicator is not a standalone solution. For optimal results, it must be integrated into a well-defined trading strategy that includes risk management and other confirmations.
OpenAI Signal Generator - Enhanced Accuracy# AI-Powered Trading Signal Generator Guide
## Overview
This is an advanced trading signal generator that combines multiple technical indicators using AI-enhanced logic to generate high-accuracy trading signals. The indicator uses a sophisticated combination of RSI, MACD, Bollinger Bands, EMAs, ADX, and volume analysis to provide reliable buy/sell signals with comprehensive market analysis.
## Key Features
### 1. Multi-Indicator Analysis
- **RSI (Relative Strength Index)**
- Length: 14 periods (default)
- Overbought: 70 (default)
- Oversold: 30 (default)
- Used for identifying overbought/oversold conditions
- **MACD (Moving Average Convergence Divergence)**
- Fast Length: 12 (default)
- Slow Length: 26 (default)
- Signal Length: 9 (default)
- Identifies trend direction and momentum
- **Bollinger Bands**
- Length: 20 periods (default)
- Multiplier: 2.0 (default)
- Measures volatility and potential reversal points
- **EMAs (Exponential Moving Averages)**
- Fast EMA: 9 periods (default)
- Slow EMA: 21 periods (default)
- Used for trend confirmation
- **ADX (Average Directional Index)**
- Length: 14 periods (default)
- Threshold: 25 (default)
- Measures trend strength
- **Volume Analysis**
- MA Length: 20 periods (default)
- Threshold: 1.5x average (default)
- Confirms signal strength
### 2. Advanced Features
- **Customizable Signal Frequency**
- Daily
- Weekly
- 4-Hour
- Hourly
- On Every Close
- **Enhanced Filtering**
- EMA crossover confirmation
- ADX trend strength filter
- Volume confirmation
- ATR-based volatility filter
- **Comprehensive Alert System**
- JSON-formatted alerts
- Detailed technical analysis
- Multiple timeframe analysis
- Customizable alert frequency
## How to Use
### 1. Initial Setup
1. Open TradingView and create a new chart
2. Select your preferred trading pair
3. Choose an appropriate timeframe
4. Apply the indicator to your chart
### 2. Configuration
#### Basic Settings
- **Signal Frequency**: Choose how often signals are generated
- Daily: Signals at the start of each day
- Weekly: Signals at the start of each week
- 4-Hour: Signals every 4 hours
- Hourly: Signals every hour
- On Every Close: Signals on every candle close
- **Enable Signals**: Toggle signal generation on/off
- **Include Volume**: Toggle volume analysis on/off
#### Technical Parameters
##### RSI Settings
- Adjust `rsi_length` (default: 14)
- Modify `rsi_overbought` (default: 70)
- Modify `rsi_oversold` (default: 30)
##### EMA Settings
- Fast EMA Length (default: 9)
- Slow EMA Length (default: 21)
##### MACD Settings
- Fast Length (default: 12)
- Slow Length (default: 26)
- Signal Length (default: 9)
##### Bollinger Bands
- Length (default: 20)
- Multiplier (default: 2.0)
##### Enhanced Filters
- ADX Length (default: 14)
- ADX Threshold (default: 25)
- Volume MA Length (default: 20)
- Volume Threshold (default: 1.5)
- ATR Length (default: 14)
- ATR Multiplier (default: 1.5)
### 3. Signal Interpretation
#### Buy Signal Requirements
1. RSI crosses above oversold level (30)
2. Price below lower Bollinger Band
3. MACD histogram increasing
4. Fast EMA above Slow EMA
5. ADX above threshold (25)
6. Volume above threshold (if enabled)
7. Market volatility check (if enabled)
#### Sell Signal Requirements
1. RSI crosses below overbought level (70)
2. Price above upper Bollinger Band
3. MACD histogram decreasing
4. Fast EMA below Slow EMA
5. ADX above threshold (25)
6. Volume above threshold (if enabled)
7. Market volatility check (if enabled)
### 4. Visual Indicators
#### Chart Elements
- **Moving Averages**
- SMA (Blue line)
- Fast EMA (Yellow line)
- Slow EMA (Purple line)
- **Bollinger Bands**
- Upper Band (Green line)
- Middle Band (Orange line)
- Lower Band (Green line)
- **Signal Markers**
- Buy Signals: Green triangles below bars
- Sell Signals: Red triangles above bars
- **Background Colors**
- Light green: Buy signal period
- Light red: Sell signal period
### 5. Alert System
#### Alert Types
1. **Signal Alerts**
- Generated when buy/sell conditions are met
- Includes comprehensive technical analysis
- JSON-formatted for easy integration
2. **Frequency-Based Alerts**
- Daily/Weekly/4-Hour/Hourly/Every Close
- Includes current market conditions
- Technical indicator values
#### Alert Message Format
```json
{
"symbol": "TICKER",
"side": "BUY/SELL/NONE",
"rsi": "value",
"macd": "value",
"signal": "value",
"adx": "value",
"bb_upper": "value",
"bb_middle": "value",
"bb_lower": "value",
"ema_fast": "value",
"ema_slow": "value",
"volume": "value",
"vol_ma": "value",
"atr": "value",
"leverage": 10,
"stop_loss_percent": 2,
"take_profit_percent": 5
}
```
## Best Practices
### 1. Signal Confirmation
- Wait for multiple confirmations
- Consider market conditions
- Check volume confirmation
- Verify trend strength with ADX
### 2. Risk Management
- Use appropriate position sizing
- Implement stop losses (default 2%)
- Set take profit levels (default 5%)
- Monitor market volatility
### 3. Optimization
- Adjust parameters based on:
- Trading pair volatility
- Market conditions
- Timeframe
- Trading style
### 4. Common Mistakes to Avoid
1. Trading without volume confirmation
2. Ignoring ADX trend strength
3. Trading against the trend
4. Not considering market volatility
5. Overtrading on weak signals
## Performance Monitoring
Regularly review:
1. Signal accuracy
2. Win rate
3. Average profit per trade
4. False signal frequency
5. Performance in different market conditions
## Disclaimer
This indicator is for educational purposes only. Past performance is not indicative of future results. Always use proper risk management and trade responsibly. Trading involves significant risk of loss and is not suitable for all investors.
Canuck Trading Projection IndicatorCanuck Trading Projection Indicator
Overview
The Canuck Trading Projection Indicator is a powerful PineScript v6 tool designed for TradingView to project potential bullish and bearish price trajectories based on historical price and volume movements. It provides traders with actionable insights by estimating future price targets and assigning confidence levels to each outlook, helping to identify probable market directions across any timeframe. Ideal for both short-term and long-term traders, this indicator combines momentum analysis, RSI filtering, support/resistance detection, and time-weighted trend analysis to deliver robust projections.
Features
Bullish and Bearish Projections: Forecasts price targets for upward (bullish) and downward (bearish) movements over a user-defined projection period (default 20 bars).
Confidence Levels: Assigns percentage confidence scores to each outlook, reflecting the likelihood of the projected price based on historical trends, volatility, and volume.
RSI Filter: Incorporates a 14-period Relative Strength Index (RSI) to validate trends, requiring RSI > 50 for bullish and RSI < 50 for bearish signals.
Support/Resistance Detection: Adjusts confidence levels when projections are near key swing highs/lows (within 2% of average price), boosting confidence by 5% for alignments.
Time-Based Weighting: Prioritizes recent price movements in trend analysis, giving more weight to newer bars for improved relevance.
Customizable Inputs: Allows users to tailor lookback period, projection bars, RSI period, confidence threshold, colors, and label positioning.
Forced Label Spacing: Prevents overlap of bullish and bearish text labels, even for tight projections, using fixed vertical slots when price differences are small (<2% of average price).
Timeframe Flexibility: Works seamlessly across all TradingView timeframes (e.g., 30-minute, hourly, daily, weekly, monthly), adapting projections to the chart’s resolution.
Clean Visualization: Displays projections as green (bullish) and red (bearish) dashed lines, with non-overlapping text labels at the projection endpoints showing price targets and confidence levels.
How It Works
The indicator analyzes historical price and volume data over a user-defined lookback period (default 50 bars) to calculate:
Momentum: Combines price changes and volume to assess trend strength, using a weighted moving average (WMA) for directional bias.
Trend Analysis: Counts bullish (price up, volume above average, RSI > 50) and bearish (price down, volume above average, RSI < 50) trends, weighting recent bars more heavily.
Projections:
Bullish Slope: Positive or flat when momentum is upward, scaled by price change and momentum intensity.
Bearish Slope: Negative or flat when momentum is downward, amplified by bearish confidence for stronger projections.
Projects prices forward by 20 bars (default) using current close plus slope times projection bars.
Confidence Levels:
Base confidence derived from the proportion of bullish/bearish trends, with a 5% minimum to avoid zero confidence.
Adjusted by volatility (lower volatility increases confidence), volume trends, and proximity to support/resistance levels.
Visualization:
Draws projection lines from the current close to the 20-bar future target.
Places text labels at line endpoints, showing price targets and confidence percentages, with forced spacing for readability.
Input Parameters
Lookback Period (default: 50): Number of bars for historical analysis (minimum 10).
Projection Bars (default: 20): Number of bars to project forward (minimum 5).
Confidence Threshold (default: 0.6): Minimum confidence for strong trend indication (0.1 to 1.0).
Bullish Projection Line Color (default: Green): Color for bullish projection line and label.
Bearish Projection Line Color (default: Red): Color for bearish projection line and label.
RSI Period (default: 14): Period for RSI momentum filter (minimum 5).
Label Vertical Offset (%) (default: 1.0): Base offset for labels as a percentage of price range (0.1% to 5.0%).
Minimum Label Spacing (%) (default: 2.0): Minimum vertical spacing between labels for tight projections (0.5% to 10.0%).
Usage Instructions
Add to Chart: Copy the script into TradingView’s Pine Editor, save, and add the indicator to your chart.
Select Timeframe: Apply to any timeframe (e.g., 30-minute, hourly, daily, weekly, monthly) to match your trading strategy.
Interpret Outputs:
Green Line/Label: Bullish price target and confidence (e.g., "Bullish: 414.37, Confidence: 35%").
Red Line/Label: Bearish price target and confidence (e.g., "Bearish: 279.08, Confidence: 41.3%").
Higher confidence indicates a stronger likelihood of the projected outcome.
Adjust Inputs:
Modify Lookback Period to focus on shorter/longer historical trends (e.g., 20 for short-term, 100 for long-term).
Change Projection Bars to adjust forecast horizon (e.g., 10 for shorter, 50 for longer).
Tweak RSI Period or Confidence Threshold for sensitivity to momentum or trend strength.
Customize Colors for visual preference.
Increase Minimum Label Spacing if labels overlap in volatile markets.
Combine with Analysis: Use alongside other indicators (e.g., moving averages, Bollinger Bands) or fundamental analysis to confirm signals, as projections are probabilistic.
Example: TSLA Across Timeframes
Using live TSLA data (close ~346.46 USD, May 31, 2025), the indicator produces:
30-Minute: Bullish 341.93 (13.3%), Bearish 327.96 (86.7%) – Strong bearish sentiment due to intraday volatility.
1-Hour: Bullish 342.00 (33.9%), Bearish 327.50 (62.3%) – Bearish but less intense, reflecting hourly swings.
4-Hour: Bullish 345.52 (73.4%), Bearish 344.44 (19.0%) – Flat outlook, indicating consolidation.
Daily: Bullish 391.26 (68.8%), Bearish 302.22 (31.2%) – Bullish bias from recent uptrend, bearish tempered by longer lookback.
Weekly: Bullish 414.37 (35.0%), Bearish 279.08 (41.3%) – Wide range, reflecting annual volatility.
Monthly: Bullish 396.70 (54.9%), Bearish 296.93 (10.2%) – Long-term bullish optimism.
These results align with market dynamics: short-term intervals capture volatility, while longer intervals smooth trends, providing balanced outlooks.
Notes
Accuracy: Projections are estimates based on historical data and should be used with other analysis tools. Confidence levels indicate likelihood, not certainty.
Timeframe Sensitivity: Short-term intervals (e.g., 30-minute) show larger price swings and higher confidence due to volatility, while longer intervals (e.g., monthly) are more stable.
Customization: Adjust inputs to match your trading style (e.g., shorter lookback for day trading, longer for swing trading).
Performance: Tested on volatile stocks like TSLA, NVIDIA, and others, ensuring robust performance across markets.
Limitations: May produce conservative bearish projections in strong uptrends due to momentum weighting. Adjust lookback or projection_bars for sensitivity.
Feedback
If you encounter issues (e.g., label overlap, projection mismatches), please share your timeframe, settings, or a screenshot. Suggestions for enhancements (e.g., additional filters, visual tweaks) are welcome!
Disclaimer
The Canuck Trading Projection 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.
Day of Week and HTF Period SeparatorDay of Week & HTF Period Separator
A minimalist Pine Script indicator that adds clear, time-based separators and labels to intraday charts for better structure and analysis.
Key Features
• Day Labels
• Displays abbreviated weekday names (MON, TUE, WED, etc.) at a user-defined hour
• Custom text color and position
• Limits display to the most recent 28 days for a clean view
• Time Separators
• Daily: Vertical line at 00:00 each trading day
• 4-Hour: Lines at 00:00, 04:00, 08:00, 12:00, 16:00, 20:00
• Hourly: Divisions at every hour for detailed timing
• Customization
• Individual color picker for each separator type
• Choose line style: Solid, Dashed or Dotted
• Enable or disable any separator or label independently
• Smart limits to avoid clutter on extended history
• Smart Behavior
• Active only on intraday timeframes
• Projects upcoming separators into the future for planning
• Automatically caps historical plotting for performance
• Lines extend across full visible price range
Perfect for traders who need distinct session breaks, precise time-based zoning and an organized chart layout.
Inputs
• Show Day Labels (true/false)
• Label Hour (0–23)
• Day Label Color
• Show Daily Separators (true/false)
• Show 4H Separators (true/false)
• Show 1H Separators (true/false)
• Daily Line Color, Style
• 4H Line Color, Style
• Hourly Line Color, Style
• Max Days to Display
Enhance your intraday analysis with clean, customizable time markers. 👁
Volume Flow RatioVolume Flow Ratio (VFR) Indicator
Overview
The Volume Flow Ratio (VFR) is a sophisticated volume analysis tool that measures current trading volume relative to the maximum volume of the previous period. Unlike traditional volume indicators that show raw volume or simple moving averages, VFR provides context by comparing current activity to recent maximum activity levels.
Core Features
1. Split Period Analysis
- Multiple Timeframe Options:
- Daily: Compares to previous day's maximum
- Weekly: Week-to-week comparison
- NYSE Weekly: Specialized for stock market trading (Monday-Friday only)
- Monthly: Month-to-month analysis
- Quarterly: Quarter-to-quarter perspective
- Yearly: Year-over-year volume comparison
2. Ratio-Based Measurement
- Displays volume as a ratio (0 to 1+) rather than raw numbers
- 1.0 represents volume equal to previous period's maximum
- Example: If previous max was 50,000 contracts:
- Current volume of 25,000 shows as 0.5
- Current volume of 75,000 shows as 1.5
3. Triple Coloring Modes
- Moving Average Based:
- Compares current ratio to its moving average
- Customizable MA period
- Green: Above MA (higher than average activity)
- Red: Below MA (lower than average activity)
- Previous Candle Comparison:
- Simple increase/decrease from previous bar
- Green: Higher than previous bar
- Red: Lower than previous bar
- Candle Color Based:
- Syncs with price action
- Green: Bullish candles (close > open)
- Red: Bearish candles (close < open)
Primary Use Cases
1. Volume Profile Analysis
- Perfect for traders who need to understand when markets are most active
- Helps identify unusual volume spikes relative to recent history
- Useful for timing entries and exits based on market participation
2. Market Activity Traders
Ideal for traders who:
- Need to identify high-liquidity periods
- Want to avoid low-volume periods
- Look for volume breakouts or divergences
- Trade based on institutional participation levels
3. Mean Reversion Traders
Helps identify:
- Overextended volume conditions (potential reversals)
- Volume exhaustion points
- Return to normal volume levels after spikes
4. Momentum Traders
Useful for:
- Confirming trend strength through volume
- Identifying potential trend exhaustion
- Validating breakouts with volume confirmation
Advantages Over Traditional Volume Indicators
1. Contextual Analysis
- Shows relative strength rather than raw numbers
- Easier to compare across different time periods
- Automatically adjusts to changing market conditions
2. Period-Specific Insights
- Respects natural market cycles (daily, weekly, monthly)
- Special handling for NYSE trading days
- Eliminates weekend noise in stock market analysis
3. Flexible Visualization
- Three distinct coloring methods for different trading styles
- Clear reference line at 1.0 for quick analysis
- Histogram style for easy pattern recognition
Best Practices
For Day Traders
- Use Daily split for intraday volume patterns
- MA coloring mode with shorter periods (5-10)
- Focus on ratios during market hours
For Swing Traders
- Weekly or NYSE Weekly splits
- Longer MA periods (15-20)
- Look for sustained volume patterns
For Position Traders
- Monthly or Quarterly splits
- Candle color mode for trend confirmation
- Focus on major volume shifts
Limitations
- Requires one full period to establish baseline
- May be less effective in extremely low volume conditions
- NYSE Weekly mode specific to stock market hours
This indicator is particularly valuable for traders who understand that volume is a crucial component of price action but need a more sophisticated way to analyze it than simple volume bars. It's especially useful for those who trade based on market participation levels and need to quickly identify whether current volume is significant relative to recent history.
Green*DiamondGreen*Diamond (GD1)
Unleash Dynamic Trading Signals with Volatility and Momentum
Overview
GreenDiamond is a versatile overlay indicator designed for traders seeking actionable buy and sell signals across various markets and timeframes. Combining Volatility Bands (VB) bands, Consolidation Detection, MACD, RSI, and a unique Ribbon Wave, it highlights high-probability setups while filtering out noise. With customizable signals like Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, plus vibrant candle and volume visuals, GreenDiamond adapts to your trading style—whether you’re scalping, day trading, or swing trading.
Key Features
Volatility Bands (VB): Plots dynamic upper and lower bands to identify breakouts or reversals, with toggleable buy/sell signals outside consolidation zones.
Consolidation Detection: Marks low-range periods to avoid choppy markets, ensuring signals fire during trending conditions.
MACD Signals: Offers flexible buy/sell conditions (e.g., cross above signal, above zero, histogram up) with RSI divergence integration for precision.
RSI Filter: Enhances signals with customizable levels (midline, oversold/overbought) and bullish divergence detection.
Ribbon Wave: Visualizes trend strength using three EMAs, colored by MACD and RSI for intuitive momentum cues.
Custom Signals: Includes Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, with limits on consecutive signals to prevent overtrading.
Candle & Volume Styling: Blends MACD/RSI colors on candles and scales volume bars to highlight momentum spikes.
Alerts: Set up alerts for VB signals, MACD crosses, Green*Diamond signals, and custom conditions to stay on top of opportunities.
How It Works
Green*Diamond integrates multiple indicators to generate signals:
Volatility Bands: Calculates bands using a pivot SMA and standard deviation. Buy signals trigger on crossovers above the lower band, sell signals on crossunders below the upper band (if enabled).
Consolidation Filter: Suppresses signals when candle ranges are below a threshold, keeping you out of flat markets.
MACD & RSI: Combines MACD conditions (e.g., cross above signal) with RSI filters (e.g., above midline) and optional volume spikes for robust signals.
Custom Logic: Green-Yellow Buy uses MACD bullishness, Pullback Sell targets retracements, and Inverse Pullback Buy catches reversals after downmoves—all filtered to avoid consolidation.
Visuals: Ribbon Wave shows trend direction, candles blend momentum colors, and volume bars scale dynamically to confirm signals.
Settings
Volatility Bands Settings:
VB Lookback Period (20): Adjust to 10–15 for faster markets (e.g., 1-minute scalping) or 25–30 for daily charts.
Upper/Lower Band Multiplier (1.0): Increase to 1.5–2.0 for wider bands in volatile stocks like AEHL; decrease to 0.5 for calmer markets.
Show Volatility Bands: Toggle off to reduce chart clutter.
Use VB Signals: Enable for breakout-focused trades; disable to focus on Green*Diamond signals.
Consolidation Settings:
Consolidation Lookback (14): Set to 5–10 for small caps (e.g., AEHL) to catch quick consolidations; 20 for higher timeframes.
Range Threshold (0.5): Lower to 0.3 for stricter filtering in choppy markets; raise to 0.7 for looser signals.
MACD Settings:
Fast/Slow Length (12/26): Shorten to 8/21 for scalping; extend to 15/34 for swing trading.
Signal Smoothing (9): Reduce to 5 for faster signals; increase to 12 for smoother trends.
Buy/Sell Signal Options: Choose “Cross Above Signal” for classic MACD; “Histogram Up” for momentum plays.
Use RSI Div + MACD Cross: Enable for high-probability reversal signals.
RSI Settings:
RSI Period (14): Drop to 10 for 1-minute charts; raise to 20 for daily.
Filter Level (50): Set to 55 for stricter buys; 45 for sells.
Overbought/Oversold (70/30): Tighten to 65/35 for small caps; widen to 75/25 for indices.
RSI Buy/Sell Options: Select “Bullish Divergence” for reversals; “Cross Above Oversold” for momentum.
Color Settings:
Adjust bullish/bearish colors for visibility (e.g., brighter green/red for dark themes).
Border Thickness (1): Increase to 2–3 for clearer candle outlines.
Volume Settings:
Volume Average Length (20): Shorten to 10 for scalping; extend to 30 for swing trades.
Volume Multiplier (2.0): Raise to 3.0 for AEHL’s volume surges; lower to 1.5 for steady stocks.
Bar Height (10%): Increase to 15% for prominent bars; decrease to 5% to reduce clutter.
Ribbon Settings:
EMA Periods (10/20/30): Tighten to 5/10/15 for scalping; widen to 20/40/60 for trends.
Color by MACD/RSI: Disable for simpler visuals; enable for dynamic momentum cues.
Gradient Fill: Toggle on for trend clarity; off for minimalism.
Custom Signals:
Enable Green-Yellow Buy: Use for momentum confirmation; limit to 1–2 signals to avoid spam.
Pullback/Inverse Pullback % (50): Set to 30–40% for small caps; 60–70% for indices.
Max Buy Signals (1): Increase to 2–3 for active markets; keep at 1 for discipline.
Tips and Tricks
Scalping Small Caps (e.g., AEHL):
Use 1-minute charts with VB Lookback = 10, Consolidation Lookback = 5, and Volume Multiplier = 3.0 to catch $0.10–$0.20 moves.
Enable Green-Yellow Buy and Inverse Pullback Buy for quick entries; disable VB Signals to focus on Green*Diamond logic.
Pair with SMC+ green boxes (if you use them) for reversal confirmation.
Day Trading:
Try 5-minute charts with MACD Fast/Slow = 8/21 and RSI Period = 10.
Enable RSI Divergence + MACD Cross for high-probability setups; set Max Buy Signals = 2.
Watch for volume bars turning yellow to confirm entries.
Swing Trading:
Use daily charts with VB Lookback = 30, Ribbon EMAs = 20/40/60.
Enable Pullback Sell (60%) to exit after rallies; disable RSI Color for cleaner candles.
Check Ribbon Wave gradient for trend strength—bright green signals strong bulls.
Avoiding Noise:
Increase Consolidation Threshold to 0.7 on volatile days to skip false breakouts.
Disable Ribbon Wave or Volume Bars if the chart feels crowded.
Limit Max Buy Signals to 1 for disciplined trading.
Alert Setup:
In TradingView’s Alerts panel, select:
“GD Buy Signal” for standard entries.
“RSI Div + MACD Cross Buy” for reversals.
“VB Buy Signal” for breakout plays.
Set to “Once Per Bar Close” for confirmed signals; “Once Per Bar” for scalping.
Backtesting:
Replay on small caps ( Float < 5M, Price $0.50–$5) to test signals.
Focus on “GD Buy Signal” with yellow volume bars and green Ribbon Wave.
Avoid signals during gray consolidation squares unless paired with RSI Divergence.
Usage Notes
Markets: Works on stocks, forex, crypto, and indices. Best for volatile assets (e.g., small-cap stocks, BTCUSD).
Timeframes: Scalping (1–5 minutes), day trading (15–60 minutes), or swing trading (daily). Adjust settings per timeframe.
Risk Management: Combine with stop-losses (e.g., 1% risk, $0.05 below AEHL entry) and take-profits (3–5%).
Customization: Tweak inputs to match your strategy—experiment in replay to find your sweet spot.
Disclaimer
Green*Diamond is a technical tool to assist with trade identification, not a guarantee of profits. Trading involves risks, and past performance doesn’t predict future results. Always conduct your own analysis, manage risk, and test settings before live trading.
Feedback
Love Green*Diamond? Found a killer setup?
EMA and VWAP by Phil VoEMA and VWAP by Phil Vo
Description
This indicator combines two powerful technical analysis tools: Exponential Moving Averages (EMAs) and Volume Weighted Average Price (VWAP). Designed to assist traders in identifying trends and key price levels, this script overlays two customizable EMAs and a daily VWAP on your chart.
* EMA 1 (Blue): A fast-moving EMA with a default period of 9, ideal for short-term trend analysis.
* EMA 2 (Red): A slower EMA with a default period of 21, useful for confirming longer-term trends.
* VWAP (Yellow): The Volume Weighted Average Price, calculated using the typical price (HLC3) and volume, resetting daily. It serves as a dynamic support/resistance level and reflects the average price weighted by volume.
Features
* Customizable EMAs: Adjust the periods of both EMAs via the settings (minimum period: 1).
* Visual Clarity: Each line is plotted in a distinct color (Blue for EMA 1, Red for EMA 2, Yellow for VWAP) with a linewidth of 2 for easy identification.
* Daily VWAP: The VWAP resets at the start of each trading day, providing a reliable intraday reference point.
* Tooltips: Hover over the input settings to see descriptions of each EMA period.
How to Use
1. Add the indicator to your chart.
2. Customize the EMA periods in the settings if desired (defaults are 9 and 21).
3. Use the EMAs to spot trends:
* When EMA 1 crosses above EMA 2, it may signal a bullish trend.
* When EMA 1 crosses below EMA 2, it may indicate a bearish trend.
4. Use the VWAP as a dynamic support/resistance level:
* Prices above VWAP might suggest bullish momentum.
* Prices below VWAP might indicate bearish pressure.
Settings
* EMA 1 Length: Set the period for the fast EMA (default: 9).
* EMA 2 Length: Set the period for the slow EMA (default: 21).
Notes
* The VWAP resets daily by default, making it most suitable for intraday trading.
* This script is open-source under the Mozilla Public License 2.0, so feel free to study or modify it!
Author
Created by Phil Vo. Happy trading!
How to Add This to TradingView
When you publish the script:
1. Paste the description above into the "Description" field in the "Publish Script" dialog.
2. Set the title as "EMA and VWAP by Phil Vo".
3. Choose "Public" visibility and "Open" access to share it with the community.
4. Add tags like "EMA", "VWAP", "Moving Average", "Trend", and "Volume" to help users find it.
This description provides a clear explanation of the indicator’s purpose, usage instructions, and customization options, making it accessible and helpful for TradingView users. Let me know if you’d like to adjust anything!
VIX Implied MovesKey Features:
Three Timeframe Bands:
Daily: Blue bands showing ±1σ expected move
Weekly: Green bands showing ±1σ expected move
30-Day: Red bands showing ±1σ expected move
Calculation Methodology:
Uses VIX's annualized volatility converted to specific timeframes using square root of time rule
Trading day convention (252 days/year)
Band width = Price × (VIX/100) ÷ √(number of periods)
Visual Features:
Colored semi-transparent backgrounds between bands
Progressive line thickness (thinner for shorter timeframes)
Real-time updates as VIX and ES prices change
Example Calculation (VIX=20, ES=5000):
Daily move = 5000 × (20/100)/√252 ≈ ±63 points
Weekly move = 5000 × (20/100)/√50 ≈ ±141 points
Monthly move = 5000 × (20/100)/√21 ≈ ±218 points
This indicator helps visualize expected price ranges based on current volatility conditions, with wider bands indicating higher market uncertainty. The probabilistic ranges represent 68% confidence levels (1 standard deviation) derived from options pricing.
Custom Volatility Price-Based IndicatorThis script provides an interactive volatility-based indicator that helps traders visualize key price levels based on the opening price, volatility (ATR), and the first 3 30-minute intervals of the trading day. It offers flexibility through user inputs for volatility adjustments, making it a customizable tool for assessing potential price movements and volatility for the current trading day.
Step 1: Input Volaiti
ATR Length: User-defined period for calculating volatility (default is 14).
Custom Multiplier Value: Allows users to adjust volatility with a multiplier. Defaults to using ATR if set to 0.
Step 2: Volatility Calculation
ATR Daily: Fetches the daily Average True Range (ATR) for volatility.
Volatility Adjustment: If the custom multiplier is used, it adjusts the ATR accordingly.
Step 3: Upper and Lower Levels
Opening Price: Displays the opening price of the current day.
Upper/Lower Levels: Calculated by adding/subtracting the adjusted volatility to/from the opening price.
Step 4: Plot Opening Price
Plots the Opening Price on the price scale in white.
Step 5: Highest and Lowest of First 3 30-Minute Intervals
Records the highest and lowest prices in the first three 30-minute intervals (9:30-11:00 AM).
Step 6: Adjusted Prices
Adjusted Top/Bottom: Adds/subtracts the ATR to the highest and lowest prices from Step 5 and plots them in purple and pink.
Plotting:
Displays the upper, lower, opening, and adjusted price levels as steplines in different colors for easy visualization.
This script helps traders visualize volatility-based levels, including the opening price and early market range, with customizable adjustments based on ATR.
Dynamic Open Levels# Dynamic Open Levels Indicator v1.0
Release Date: November 5, 2024
Introducing the Dynamic Open Levels indicator on TradingView! This tool helps traders visualize and analyze key opening price levels across multiple timeframes, making your market analysis more effective.
---
### Key Features
- Multiple Timeframes : Yearly, Quarterly, Monthly, Weekly, Daily, 4H, and 1H levels available.
- Visibility Controls : Easily toggle visibility for each timeframe to suit your trading style.
- Line Customization : Set custom thickness and colors for lines, making charts easy to interpret.
- Monthly: Purple
- Weekly: Blue
- Daily: Green
- 4H: Red
- 1H: Orange
- Dynamic Coloring : Lines adjust color based on market conditions—teal for bullish (`rgb(34, 171, 148)`) and coral for bearish (`rgb(247, 82, 95)`).
### Labels & Customization
- Real-Time Labels : Each level is labeled for easy identification (e.g., Y for Yearly, Q for Quarterly).
- Label Settings : Customize opacity, text color, size, and position for clarity without cluttering your chart.
- Sizes : Choose from tiny, small, normal, large, to huge.
- Offset : Set labels from 1 to 10 to position them precisely.
- Color Management : Organize all colors under a dedicated Line Colors group for easy adjustments.
### Advanced Plotting & Performance
- Real-Time Updates : Levels are updated dynamically with the latest open prices.
- Extended Lines : Lines extend to the right, offering a consistent reference for future price movement.
- Optimized Performance : Handles up to 500 lines efficiently to maintain smooth performance.
---
### Installation Instructions
1. Add to Chart :
- Go to the Indicators section in TradingView.
- Search for Dynamic Open Levels and add it to your chart.
2. Customize Settings :
- Line Thickness : Adjust to suit your preference.
- Visibility : Toggle timeframes like Yearly, Monthly, Weekly, etc., as needed.
- Labels : Configure opacity, text color, size, and offset under the Label Settings group.
---
### Documentation & Support
For guidance on using the Dynamic Open Levels indicator, visit our Documentation (#). If you need assistance, check out our Support Channel (#).
---
Thank you for choosing Dynamic Open Levels . Stay tuned for future updates that will continue to improve your trading experience!
H A Z E D
Dual Timeframe Williams Percent RangeThis is a dual timeframe Williams Percent Range indicator.
Function:
The idea behind this indicator is for trader to see what the Williams %r is doing on higher timeframes without the need to change the chart. I added the "Smoothing" function to take the jagged lines out of the higher timeframe. It has a better flow this way.
If we choose the 4H and the Daily timeframes for example. In this bullish situation I wait for the Daily WPR to cross above the -50 mid line. Then the faster 4H WPR will eventually hit the bottom and begin to rise again back into the trend.
This is the "Reset" of the 4H WPR and when the 4H WPR crosses up above the -50 mid line again it means price should begin to rise on the chart. I added the option to change the colour when the signal lines cross the -50. It is good to use a fast time frame so you can see the WPR hitting the bottom in an uptrend, but not too fast.
The Heiken Ashi candle sticks are a very good addition to this system. You can also use a colour changing 200 EMA if you run the "1H/Daily" in the WPR. Or the 50 EMA if you run the Daily 4H.
This system could be used on lower timeframes too but I have not tested it there.
The Dual WPR indicator, the colour changing 50 EMA and Heiken Ashi have been optimised for the 4H/Daily.
If you want to set alerts the the faster WPR line crossing the -50 is good, on candle close.
This way you will only need one alert per chart.
If you get an alert on the EURUSD 4H that the 4H WPR has crossed up then look to see what what the Daily WPR is doing. If it is also above the -50 mid line then EURUSD is probably trending up.
Thank you to TradingView for supplying the Williams %r template.
I hope this helps some other traders out there.
I combined the Supertrend and the Coloured EMA in the main screen into one indicator.
This is my first indicator published :-)
Have fun out there and good luck.
Eddie T.
Stocksgeeks MBIThis indicator displays the Stocksgeeks market breadth dashboard for NSE (India) stocks.
Market breadth provides insights into the participation of stocks in a market's movement & the conviction in the overall mood of the underlying index. Various interpretations of market breadth exist, including gauging the quantity of new highs and new lows, or the number of advancing & declining stocks, or the percentage of stocks above or below certain moving averages.
This dashboard includes the following metrics:
4R
A count or ratio of advancing & declining stocks objectively depicts their participation in an index or stock universe. A positive market breadth is said to happen when more stocks are advancing than are declining.
The 4R column is based on 4% advances & declines.
The advances are calculated as the number of stocks having a daily percentage change ≥ 4% divided by the total number of stocks having a daily percentage change < -4%.
4R is the ratio between NSE (India) stocks advancing or declining by 4% daily.
4 chg is the % change from yesterday’s 4R value to today’s 4R value.
20R
When most of the stocks are trading above a specific moving average, the market breadth is termed strong. This dashboard uses 20-day EMA for short-term timeframes.
20R is the ratio between the % of NSE (India) stocks above & below the 20-day moving average.
20 chg is the % change from yesterday’s 20R value to today’s 20R value.
50R
For medium to long-term timeframes, this dashboard uses 50-day EMA.
50R is the ratio between the % of NSE (India) stocks above & below the 50-day moving average.
50 chg is the % change from yesterday’s 50R value to today’s 50R value.
52WH &52WL
These 2 columns display the net number of stocks on NSE (India) making new 52-week highs or new 52-week lows. A market is considered strong (bullish) when new highs exceed new lows.
Interpretation
The 52 week highs must be greater than 52 weeks lows for a bullish bias.
This is how the individual columns are coded:
4R: above 200 is green, below 50 is red
20R: above 75 is green, below 50 is red
50R: above 85 is green, below 60 is red
For all the changes (4 chg, 20 chg, 50 chg): above 20 is green and below -20 is red
To decide the overall color for the day, we subtract the number of red boxes from the number of green boxes for the day. If the output is greater than equal to 3, then the day color is green, and if this is less than equal to -3 then the day color is red. In case of no consensus, the overall day color is neutral.
The color of the 20R & 50R indicates the trend (green is uptrend, & red is downtend). The color of the 4R column & the chg columns (4 chg, 20 chg, 50 chg) indicates the strength of the trend.
Features
⦿ Expanded mode : This is the default state & displays the market breadth for the past 10 days.
⦿ Mini mode : This displays only the overall color for the day.
⦿ One-day mode : Turning off both the expanded & the mini mode displays the one-day mode, which displays the market breadth columns for the current day only.
⦿ Dark mode : One-click dark mode, as usual.
Dependency
The script uses the Pine Seeds service to import custom data hosted in a GitHub repository and accesses it via TradingView as the frontend. So, the number of bars appearing on charts is fully dependent on the amount of historical data available. Any error or omission, if there, is a reflection of the hosted data, & not that of Tradingview.
Limitations
Such data has some limitations, like it can only be updated at EOD (End-of-Day), & only daily-based timeframes can be applied to such data. Irrespective of the intraday changes, only the last saved value on the chart is seen. So, it's best to use this script as EOD, rather than intraday. At the time of publication of this script, 375 days of historical data was available.
Credits
The Stocksgeeks interpretation of the market breadth is from Umang , who has graciously allowed his concepts to be coded into a script for TradingView. This script uses the NSE Market Breadth data from Chhirag_Kedia via a pine seed from EquityCraze . Hats off to these amazing individuals, without whose efforts, such scripts wouldn't have seen the light of this day!
NSE Market Breadth based on 4% Advance & DeclineThis indicator displays a ratio count of NSE (India) stocks advancing or declining by 4% daily.
Market breadth provides insights into the participation of stocks in a market's movement.
Various interpretations of market breadth exist, including gauging the quantity of new highs and new lows or evaluating up and down volume. Nevertheless, all breadth indicators fundamentally stem from the same basic concept, which can be expressed mathematically as the number of advancing & declining stocks.
Thus, a count or ratio of advancing & declining stock objectively depicts the participation of stocks in an index or stock universe.
A 4% advance or decline shows a significant range expansion.
⦿ The script calculates advances as a ratio of the daily percentage change ≥ 4% & the total number of stocks.
⦿ Declines are calculated as a ratio of the daily percentage change < -4% & the total number of stocks.
⦿ Net breadth is simply calculated by subtracting the declines from the advances. (4% up - 4% down). This depicts whether the day was bearish or bullish.
Green area depicts the 4% advances.
Red area depicts the 4% declines.
The table provides the actual values for the Advances, declines & the net breadth for the day.
There is an option to turn on dark mode in the settings.
There is an option to display only the net breadth .
You can turn on the Expanded mode for the table which will display the data for the past week.
Among other options, you can choose to not display colors in the table .
There is an option plot ' comfort' levels ' of +/- 10 also.
Interpretation
A market where advances are more than declines is indicative of a healthy bull market. But extreme breadth can signal exhaustion, often leading to a reversal. This is true in case of advances as well as declines.
If a market continues to rise while breadth does not increase, this is considered a divergence, which frequently leads to a reversal of the prevailing trend.
Dependency:
The script uses the Pine Seeds service to import custom data hosted in a GitHub repository and accesses it via TradingView as the frontend. So, the number of bars appearing on charts is fully dependent on the amount of historical data available. Any error or omission, if there, is a reflection of the hosted data, & not that of TradingView.
Limitations:
Such data has some limitations, like it can only be updated at EOD (End-of-Day), & only daily-based timeframes can be applied to such data. Irrespective of the intraday changes, only the last saved value on the chart is seen. So, it's best to use this script as EOD, rather than intraday.
At the time of publication of this script, historical data was available till the year 2004.
The universe of stocks chosen for the data is all stocks with latest Close >= 1 and Market Cap > 10.
Credits:
NSE Market Breadth data is from Chhirag_Kedia , & the Pine seeds are courtesy of EquityCraze
RVol LabelThis Code is update version of Code Provided by @ssbukam, Here is Link to his original Code and review the Description
Below is Original Description
1. When chart resolution is Daily or Intraday (D, 4H, 1H, 5min, etc), Relative Volume shows value based on DAILY. RVol is measured on daily basis to compare past N number of days.
2. When resolution is changed to Weekly or Monthly, then Relative Volume shows corresponding value. i.e. Weekly shows weekly relative volume of this week compared to past 'N' weeks. Likewise for Monthly. You would see change in label name. Like, Weekly chart shows W_RVol (Weekly Relative Volume). Likewise, Daily & Intraday shows D_RVol. Monthly shows M_RVol (Monthly Relative Volume).
3. Added a plot (by default hidden) for this specific reason: When you move the cursor to focus specific candle, then Indicator Value displays relative volume of that specific candle. This applies to Intraday as well. So if you're in 1HR chart and move the cursor to a specific candle, Indicator Value shows relative volume for that specific candlestick bar.
4. Updating the script so that text size and location can be customized.
Changes to Updated Label by me
1. Added Today's Volume to the Label
2. Added Total Average Volume to the Label
3. Comparison vs Both in Single Line and showing how much volume has traded vs the average volume for that time of the day
4. Aesthetic Look of the Label
How to Use Relative Volume for Trading
Using Relative Volume (RVol) in trading can be a valuable tool to help you identify potential trading opportunities and gain insight into market behavior. Here are some ways to use RVol in your trading strategy:
Identifying High-Volume Breakouts: RVol can help you spot potential breakouts when the volume surges significantly above its average. High RVol during a breakout suggests strong market interest, increasing the probability of a sustained move in the direction of the breakout.
Confirming Trends and Reversals: RVol can act as a confirmation tool for trends and reversals. A trend accompanied by rising RVol indicates a strong and sustainable move. Conversely, a trend with declining RVol might suggest a weakening trend or potential reversal.
Spotting Volume Divergence: When the price is moving in one direction, but RVol is declining or not confirming the move, it may indicate a divergence. This discrepancy could suggest a potential reversal or trend change.
Support and Resistance Confirmation: High RVol near key support or resistance levels can indicate potential price reactions at those levels. This confirmation can be valuable in determining whether a level is likely to hold or break.
Filtering Trade Signals: Incorporate RVol into your existing trading strategy as a filter. For example, you might consider taking trades only if RVol is above a certain threshold, ensuring that you focus on high-impact trading opportunities.
Avoiding Low-Volume Traps: Low RVol can indicate a lack of interest or participation in the market. In such situations, price movements may be erratic and less reliable, so it's often wise to avoid trading during low RVol periods.
Monitoring News Events: Around significant news events or earnings releases, RVol can help you gauge the market's reaction to the information. High RVol during such events can present trading opportunities but be cautious of increased volatility and potential gaps.
Adjusting Trade Size: During periods of extremely high RVol, it might be prudent to adjust your position size to account for higher risk.
Using Relative Volume in Morning Session
If the Volume traded in first 15 minute to 30 Minutes is already at 50% or 100% depending upon the ticker, it means that it is going to have very high Volume vs average by end of the day.
This gives me conviction for Long or Short Trades
Remember that RVol is not a standalone indicator; it works best when used in conjunction with other technical and fundamental analysis tools. Additionally, RVol's effectiveness may vary across different markets and trading strategies. Therefore, backtesting and validating the use of RVol in your trading approach is essential.
Lastly, risk management is crucial in trading. While RVol can provide valuable insights, it cannot guarantee profitable trades. Always use appropriate risk management strategies, such as setting stop-loss levels, and avoid overexposing yourself to the market based solely on RVol readings.
Neon Juliet - PreviewThere is no TLDR, but there is a summary at the end. I strongly encourage to read full description before trying it out. Enjoy!
Background
=========
Having successful and adamant trading systems typically consists of two (oversimplified) elements: signals and risk management system. In most zero-sum games, such as trading, signals must offer an advantage against the market, and risk management system provides a safety mechanism to allow the system to exist in the future. Let me explain.
Say, I have a solid risk management system: it is diversified, with take profit and stop loss thresholds set for low risk, on average I trade less than 3% of my assets, and there’s a loss recovery mechanism, etc. Hypothetically, it’s pristine. Now, let’s trade this portfolio against a flip of a coin, essentially a signal that provides 50% probability of things turning out in my favour. How profitable is such system? My answer: it isn’t. I might be able to sustain this system for some time, but eventually this system is going to have to loosen risk restrictions to stay ahead of the commissions and borrowing costs, resulting in overtime detrimental trend.
Conversely, if the signals provide greater than 50% confidence of things turning out in my favour, but risk management is poor, I’d expect such system to end up in a disaster soon, perhaps after a few euphoric gains. (I’d isolate a top-notch signals, say >90% confidence, in another bucket, but this idealistic system is non-achievable in my practice, so I’ll leave it be)
Neon Juliet was developed to offer an advantage against given markets. Probabilities generated by this model are statistical historical outcomes. This model developed using only price action and is unable to consume any other data or price data across instruments. In other words, it doesn’t know anything you don’t see already on a chart.
Neon J performs best on complex instruments where there’s great diversity of actors and considerable daily volume .
Methodology
==========
In principle, Neon J is based on Bayes’ Theorem. Simply put, prior knowledge of price action ( aka patterns) provides basis for probability of future price action development (ex. long or short trend).
The training process is implemented outside of this script mainly due to Pine Script limitations. This script, however, contains inference portion of the model.
As input for training, daily candle data is used. From this data, feature engineering step of the training develops features, like price average divergence/convergence (think MACD ), price strength (think RSI , ADX ); multiple periods used to diversify long and short patterns. This is done to develop a “state” that is reflective of recent price development. Ex. what we’d call a trend is just a strong and consistent upward price action, but we’d need to look at most recent N candles and their pattern to know that.
Once features are developed, I train a model using Reinforcement Learning technique. Simply put, this technique allows an agent to interact with a trading simulator and take actions (ex. go long, go short, etc.). After many iterations, the agent learns conditions (patterns) that lead to positive outcomes and those that lead to negative outcomes. This learning is quantitative, which means there’s a way to tell which probabilities are strong and which are weak. These probabilities are indicated by this script.
Trained Neon J models are instruments-specific. Meaning, that model for DJI is not compatible with SP500 or any other instrument. Experimentally, I proved that such approach over-performs generalizable models (those that are trained on data from multiple instruments)
Neon J currently only support daily time frame. The limitation is purely practical to reduce the development load and model size.
Results
======
Tests show 60%-70% success rate (on average, some instruments are worse than that, some better) of individual signal when threshold is set to 0.3 (roughly equivalent to 65% probability). This is calculated with Pine Script Strategy with the following entry/exit rules:
Entry when individual signal (a dot) is above 0.3 (long) or below -0.3 (short)
Exit when 14-period smooth signal (a column) is above 0.0 (short exit) or below 0.0 (long exit)
No stop loss or take profit levels.
Pyramiding is set to 100 (to allow unrestricted action of all signals)
All trades are closed on last tested bar (to conclude all signals in-flight)
Percent Profitable is what we take as success rate in the context of this assessment. This number represents how many signals were profitable vs all signals actioned.
It is also worth noting that this assessment was performed on a time period previously unseen by the model. Simply put, we only train a model with data up until date X, then we test starting from date X onward. This ensures that the assessment is unbiased by the model already “knowing” the future. In practice, this gives confidence that future (unknown) market dynamics is going to be representative of our test results.
Be aware, the above “strategy” is not my recommended usage of this signal, it is simply an assessment technique that is meant to be as simple and unconstrained as possible.
How to use this script
================
The script calculates a probability. A term probability here is used in a loose form and means “a numeric value in roughly -1 to 1 space that represents the likelyhood of bullish or bearish price action”. Keep in mind that probability values can go over 1.0 or below -1.0. This is due to the fact that these value are normalized to -1/1 space using 95-percentile (this detail is largely unimportant for usability’s sake).
Indications
--------------
Dots (circles) indicate individual probability value on any given bar. Indicated value on a given bar indicates the probability of future price action. High (positive) values indicate high probability of long action in the future. Low (negative) values indicate high probability of short action in the future. You should interpret future as a gradient (a trend developing slowly over time) instead of being isolated to what’s immediately follows (ex. next bar)
Columns (histogram) provided as convenient view of smoothed probabilities of last N bars. This is controlled by the Smoothing parameter and defaults to 14.
Parameters
---------------
Model parameter is the backbone of this script. It is a required parameter and it is unique for each instrument. Example models provided at the end (see below). This parameter is a long 10000+ character representation of a model.
The script has two additional parameters for configuring interpretation: Threshold and Smoothing.
Threshold controls the level at which values change color (ex. above 0.3, turn neon blue, and below -0.3 turn neon purple).
Smoothing parameter provides a way to smooth out individual probabilities into a exponential moving average with the periods provided. This average is indicated using columns on the indicator.
Model expiration
----------------------
Models are valid for 1 month after training. This is done by design to prevent model deterioration. A month is proven to be a maximum period of time to hold model performance steady. After that, deterioration is likely to occur. Optimal time for model lifetime is 10 days (this is what I use for live trading), and of course most optimal (but unpractical for now) is to re-train daily.
Validity indicated with blue-tinted indicator background, while red-tinted background indicates expired period.
Preview
======
This script is released as a public script for anyone to try. My motives for this release are two-fold:
To subject the model to a variety of conditions, including traders with different experiences trading different instruments (subject to specific models offered of course). Essentially, my own testing is not enough to grasp a full breadths of scenarios. I’d like to harden it and understand where it is strong and where it might fall short (pun intended).
Get an idea on how Neon J might be useful when making trading decision. I tried to make the representation of the signals unconstrained and unopinionated, so there’s room to explore and experiment. I found that Neon J can be packaged in a number of different ways.
At this moment the script is closed-source. I might consider open-sourcing this script in future depending on how much feedback I get from this submission and whether it’d be deemed useful to others.
Summary
=======
Neon J is a set of probabilistic models for predicting future price action with ~65% accuracy. It indicates individual signals (circles) for probability of price action in a foreseeable future, while smoothed signals (columns) are provided for a more dynamic view of probable price action. Blue circle - strong long probability; Purple circle - strong short probability. Blue column - strong long trend ahead or in-progress; Purple column - strong short trend ahead or in-progress.
To use it, copy models below and provide them an input to “model” parameter when applying to a chart. Models are instrument-specific. Only daily (D) charts should be used.
The script is provided for evaluation purposes.
Models!
======
At last, here are the models (a piece of text you need to input in script parameters for each instrument)
TVC:DJI :
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VANTAGE:SP500 :
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BINANCE:BTCUSD
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For more models, see a link on bio (description length limitation in this description restricts me to publish more).
Unimportant details
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“Neon” is the project code name, “J” is the iteration (versions “A” to “I” all led to a solid “J”)
Formatting options here make formatting very difficult, so forgive me poor readability.
Expected Move PlotterI get a lot of requests about my indicators that I use. Unfortunately, at this time I cannot make those public but I thought about creating a makeshift alternative people could use as a reference.
I came up with this very simple yet extremely effective indicator. I call it the average or expected move plotter, but its essentially the average move plotter.
All it does is it averages out the move from open to high and low on a monthly, weekly and daily basis over the past 5 days and plots the expected move.
It really is that simple!
I have broken it down by month, week and day, so you can see the average expected move on whichever time frame you prefer.
I will use TSLA as the example.
Here is the daily:
Here is the weekly:
And here is the monthly:
You can switch between whichever timeframe you are working on and it permits all traders (day traders and swing traders) to assist in setting realistic target prices within their desired time frame.
It works on any stock, index, commodity or future.
I have also ensured that it will work with Heikin Ashi candles, for those (like myself) who are fond of those candles.
Let me know if you have any questions and if you like it!
Take care everyone and trade safe!
*SSS 50% HTF** SSS 50% - HTF (Higher Timeframe) -D/W/M/Q Edition **
This indicator is based on Sara Strat Sniper's - 50% Rule for trading Outside Bars and helps you visual the method quickly.
This indicator allows you to select: Outside: Day/Week/Month/Quarter Warning Levels with Previous High and Low Levels available within the indicators settings.
Please note - Daily warning and high/low levels are set to the indicators default. Feel free to change and save as required. Any issues let me know. See known issues below.
** Indicator Setup Requirements **
For Indicator to correctly display the 50% price level you need to setup your chart correctly. Right-click your chart background, select Settings, select Scales and Tick “Indicator Last Value Label". Now your 50% Price level will be displayed.
Known Issues:
This indicator does not work when you try to view a lower timeframes levels on a higher timeframe chart.
Example 1: Selecting Daily Warning, High and Low Levels will not be displayed correctly on a Weekly timeframe and above etc. The Daily selection however will be displayed correctly on all lower timeframes from the 1 minute chart to the Daily.
Example 2: Selecting Weekly Warning, High and Low Levels will not be displayed correctly on a Monthly timeframe and above etc. The Weekly selection however will be displayed correctly on all lower timeframes from the 1 minute chart to the Weekly. Please apply these same rules for all other timeframe indicator selections.
Monthly Warning, High and Low levels will not work correctly on a Weekly chart when the current Weekly candlestick is forming between the end of a previous Month and start of new Month. Once the first Weekly candle of a new Month closes the Monthly levels will now be displayed correctly. Please note, selecting the Monthly levels when viewing a Monthly chart will work as normal and Monthly levels displayed on a Weekly chart will be corrected once the first Weeks candle has closed. I believe this error is caused by a pine script repainting issue when assessing historical price data which is out of my limited scripting brains control.
Multi-timeframe Dashboard for RSI And Stochastic RSI Dashboard to check multi-timeframe RSI and Stochastic RSI on 4h, 8h, 12h, D and W
Great side tool to assist on the best time to buy and sell and asset.
Shows a green arrow on a good buy moment, and a red when to sell, for all timeframes. In case there are confluence on more than one, you have the info that you need.
Uses a formula with a weight of 5 for RSI and 2 for Stochastic RSI, resulting on a factor used to set up a color for each of the timeframes.
Legend per each timeframe:
- Blue: Excellent buy, RSI and Stoch RSI are low
- Green: Great buy, RSI and Stoch RSI with a quite positive entry point
- White: Good buy
- Yellow: A possible sell, depending on combination of timeframes. Not recommended for a buy
- Orange: Good sell, depending on combination of timeframes
- Red: If on more than one timeframe, especially higher ones, it is a good time to sell
For reference (But do your own research):
- Blue on Weekly: Might represent several weeks of growth. Lower timeframes will cycle from blue to red, while daily and Weekly gradually change
- Blue on Daily: Might represent 7-15 days of growth, depending on general resistance and how strongly is the weekly
PS: Check the RSI, Stochastic RSI and other indicators directly as well
TV Day Plan Template 1This is a template for daytraders, swing traders, supply and demand traders, and even swing traders. As traders we are always scanning charts for levels and zones. This template makes it easy and convenient to find, change, and chart levels. As a daytrader, I will use this daily. I always have daily and weekly targets in mind. This will ensure I don't lose track of the bigger picture while trading the smaller moves. Levels in this chart are not auto calculated. They are manually input. This script is a quick and convenient way to chart multiple levels without having to go through each drawing, change the settings, and then redraw the level. Currently this will only save levels for one ticker. A workaround is to use multiple instances and then hide the ones not in use. Another way is to use the second part to this script, Day Plan Levels Template 2. If only using one instance, you can save the levels as default. This will save them. However, if saving levels as default while using multiple instances of this indicator, the other levels will erase. The way that I use this that I have daily levels for #ES in one instance and then daily levels for #NQ in another instance.
This script is very customizable
Options include
On/Off Toggles
Light/Heavy Versions - Light versions does not plot. Heavy version will plot and show levels in info bar and price axis
Balance Levels
Control Levels
3 Support and 3 Resistance levels for daily and weekly
2 Support and 2 Resistance Clouds
Balance and Control Clouds
"0" value disables and hides levels
Key Levels SpacemanBTC IDWMKey levels, plotted automatically
Additional timeframes can be added on request
Useful for seeing strength of the trend in the market
