Hull-Exponential Moving Average (HEMA)The Hull Exponential Moving Average (HEMA) is an experimental technical indicator that uses a sequence of Exponential Moving Averages (EMAs) with the same logic as HMA - except with EMAs and not WMAs. It aims to create a responsive yet smooth trend indicator than HMA.
HEMA applies a multi-stage EMA process. Initial EMAs are calculated using alphas derived from logarithmic relationships and the input period. Their outputs are then combined in a de-lagging step, which itself uses a logarithmically derived ratio. A final EMA smoothing pass is then applied to this de-lagged series. This creates a moving average that responds quickly to genuine price changes while maintaining effective noise filtering. The specific alpha calculations and the de-lagging formula contribute to its balance between responsiveness and smoothness.
▶️ **Core Concepts**
Logarithmically-derived alphas: Alpha values for the three EMA stages are derived using natural logarithms and specific formulas related to the input period **N**.
Three-stage EMA process: The calculation involves:
An initial EMA (using **αS**) on the source data.
A second EMA (using **αF**) also on the source data.
A de-lagging step that combines the outputs of the first two EMAs using a specific ratio **r**.
A final EMA (using **αFin**) applied to the de-lagged series.
Specific de-lagging formula: Utilizes a constant ratio **r = ln(2.0) / (1.0 + ln(2.0))** to combine the outputs of the first two EMAs, aiming to reduce lag.
Optimized final smoothing: The alpha for the final EMA (**αFin**) is calculated based on the square root of the period **N**.
Warmup compensation: The internal EMA calculations include a warmup mechanism to provide more accurate values from the initial bars. This involves tracking decay factors (**eS**, **eF**, **eFin**) and applying a compensation factor **1.0 / (1.0 - e_decay)** during the warmup period. A shared warmup duration is determined by the smallest alpha among the three stages.
HEMA achieves its characteristics through this multi-stage EMA process, where the specific alpha calculations and the de-lagging step are key to its responsiveness and smoothness.
▶️ **Common Settings and Parameters**
Period (**N**): Default: 10 | Base lookback period for all alpha calculations | When to Adjust: Increase for longer-term trends and more smoothness, decrease for shorter-term signals and more responsiveness
Source: Default: Close | Data point used for calculation | When to Adjust: Change to HL2, HLC3, or OHLC4 for different price representations
Pro Tip: The HEMA's behavior is sensitive to the **Period** setting due to the non-linear relationships in its alpha calculations. Experiment with values around your typical MA periods. Small changes in **N** can have a noticeable impact, especially for smaller **N** values.
▶️ **Calculation and Mathematical Foundation**
Simplified explanation:
HEMA calculates its value through a sequence of three Exponential Moving Averages (EMAs) with specially derived smoothing factors (alphas).
Two initial EMAs are calculated from the source price, using alphas **αS** and **αF**.
The outputs of these two EMAs are combined into a "de-lagged" series.
This de-lagged series is then smoothed by a third EMA, using alpha **αFin**, to produce the final HEMA value.
All internal EMAs use a warmup compensation mechanism for improved accuracy on early bars.
Technical formula (let **N** be the input period):
1. Alpha for the first EMA (slow component related):
αS = 3.0 / (2.0 * N - 1.0)
2. Lambda for **αS** (intermediate value):
λS = -ln(1.0 - αS)
Note: **αS** must be less than 1, which implies 2N-1 > 3 or N > 2 for **λS** to be well-defined without NaN from ln of non-positive number. The code uses nz() for robustness but the formula implies this constraint.
3. De-lagging ratio **r**:
r = ln(2.0) / (1.0 + ln(2.0))
(This is a constant, approximately 0.409365)
4. Alpha for the second EMA (fast component related):
αF = 1.0 - exp(-λS / r)
5. Alpha for the final EMA smoothing:
αFin = 2.0 / (sqrt(N) / 2.0 + 1.0)
6. Applying the stages:
**OutputS = EMA_internal(source, αS, eS_state, emaS_state)**
**OutputF = EMA_internal(source, αF, eF_state, emaF_state)**
8. Calculate the de-lagged series:
DeLag = (OutputF / (1.0 - r)) - (r * OutputS / (1.0 - r))
9. Calculate the final HEMA:
HEMA = EMA_internal(DeLag, αFin, eFin_state, emaFin_state)
🔍 Technical Note: The HEMA implementation uses a shared warmup period controlled by **aMin** (the minimum of **αS**, **αF**, **αFin**). During this period, each internal EMA stage still tracks its own decay factor (**eS**, **eF**, **eFin**) to apply the correct compensation. The **nz()** function is used in the code to handle potential NaN values from alpha calculations if **N** is very small (e.g., **N=1** would make **αS=3**, **1-αS = -2**, **ln(-2)** is NaN).
▶️ **Interpretation Details**
HEMA provides several key insights for traders:
When price crosses above HEMA, it often signals the beginning of an uptrend
When price crosses below HEMA, it often signals the beginning of a downtrend
The slope of HEMA provides insight into trend strength and momentum
HEMA creates smooth dynamic support and resistance levels during trends
Multiple HEMA lines with different periods can identify potential reversal zones
HEMA is particularly effective for trend following strategies where both responsiveness and noise reduction are important. It provides earlier signals than traditional EMAs while exhibiting less whipsaw than standard HMA in choppy market conditions. The indicator excels at identifying the underlying trend direction while filtering out minor price fluctuations.
▶️ **Limitations and Considerations**
Experimental nature: As an experimental indicator, HEMA may behave differently from established HMA in certain market conditions
Lag characteristics: While designed to reduce lag, HEMA may exhibit slightly more lag than HMA in some scenarios due to the long tail of EMA
Mathematical complexity: The multi-stage calculation with specialized alpha parameters makes the behavior less intuitive to understand
Parameter sensitivity: Performance can vary significantly with different period settings
Complementary tools: Works best when combined with volume analysis or momentum indicators for confirmation
▶️ **References**
Hull, A. (2005). "Hull Moving Average," Technical Analysis of Stocks & Commodities .
RetryClaude can make mistakes. Please double-check responses.
在腳本中搜尋"track"
10 Monday's 1H Avg Range + 30-Day Daily RangeWhat This Script Does
This indicator is designed for traders who want to monitor volatility and range behavior at the start of the trading week . It focuses specifically on the first four 15-minute candles of each Monday and tracks their combined high-low range over time.
How It Works
Monday 1H Range Detection:
Each week, it automatically detects and highlights the first 4 candles of Monday on a 15-minute chart (1 hour total). It calculates the range between the highest high and lowest low of these candles.
10-Week Average of Monday 1H Ranges:
It stores and averages the last 10 such ranges, displaying this average in a table for weekly comparison.
30-Day Daily Range Average:
Separately, it calculates the average daily range (high – low) of the last 30 daily candles. This value helps put the Monday 1H range into broader context and can guide Stop Loss or TP planning.
Dynamic Labeling & Visual Highlights:
The script visually highlights the first 4 candles of Monday and places a label showing the pip range once the 4 candles have completed. It also updates a small table with the two averages described above.
How to Use It
Use it on the 15-minute timeframe to activate the Monday 1H logic.
Compare the current week’s Monday range to the 10-week average to see if volatility is increasing or decreasing.
Use the 30-day daily range to determine if the Monday opening movement is unusually large or small.
Consider adjusting trade entries, stops, or targets if the Monday range is disproportionately large compared to recent historical behavior.
What Makes It Original?
This is not a typical volatility indicator like ATR or standard deviation. Instead, it’s a purpose-built tool combining:
Time-specific behavior (first hour of the week),
Historical contextualization (10-week average tracking),
A dual-timeframe analysis (15-min + daily),
A user-friendly table and visual interface.
This script helps intraday or swing traders spot abnormal volatility early in the week and adjust their strategies accordingly—especially in fast-moving Forex or Index markets.
Opening Range Breakout Detector📈 Opening Range Breakout Detector (TF-Independent)
Tracks breakouts with precision. No matter the chart, no matter the timeframe.
This indicator monitors whether price breaks above or below the Opening Range across multiple key durations — 1m, 5m, 10m, 15m, 30m, 45m, and 60m — using 1-minute data under the hood, while you can work on higher timeframe charts (daily, etc.).
Highlights:
✅ Status table shows which ORs broke UP or DOWN
⏱ Control which timeframes to track
🖼 Customizable table position, size and colors
Crafted by @FunkyQuokka
(DAFE) DEVMA - Crossover (Deviation Moving Average) (DAFE) DEVMA - Crossover (Deviation Moving Average)
Let’s keep pushing the edge. After the breakthrough of Deviation over Deviation (DoD)—which gave traders a true lens into volatility’s hidden regime shifts—many asked: “What’s next?” The answer is DEVMA: a crossover engine built not on price, but on the heartbeat of the market itself.
Why is this different?
DEVMA isn’t just a moving average crossover. It’s a regime detector that tracks the expansion and contraction of deviation—giving you a real-time readout of when the market’s energy is about to shift. This is the next step for anyone who wants to anticipate volatility, not just react to it.
What sets DEVMA apart:
Volatility-First Logic:Both fast and slow lines are moving averages of deviation, not price. You’re tracking the market’s “energy,” not just its direction. This is the quant edge that most scripts miss.
Regime-Colored Lines:
The fast and slow DEVMA lines change color in real time—green/aqua for expansion, maroon/orange for contraction—so you can see regime shifts at a glance.
Quant-Pro Visuals:
Subtle glow, clean cross markers, and a minimalist dashboard keep your focus on what matters: the regime, not the noise.
Static Regime Thresholds:
Reference lines at 1.5 and 0.5 (custom colors) give you instant context for “normal” vs. “extreme” volatility states.
No Price Chasing:
This isn’t about following price. It’s about anticipating the next volatility regime—before the crowd even knows what’s coming.
How this builds on DoD:
DoD showed you when volatility itself was about to change. DEVMA takes that insight and turns it into a crossover engine—so you can see, filter, and act on regime shifts in real time. If DoD was the radar, DEVMA is the navigation system.
Inputs/Signals—explained for clarity:
Deviation Lookback:
Controls the sensitivity of the regime detector. Shorter = more signals, longer = only the rarest events.
Fast/Slow DEVMA Lengths:
Fine-tune how quickly the regime lines react. Fast for scalping, slow for swing trading.
Source Selection:
Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks.
VoVix Parameters:
Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective.
Bottom line:
DEVMA is for those who want to see the market’s heartbeat, not just its shadow. Use it to filter your trades, time your entries, or simply understand the market’s true rhythm. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use with discipline, and make it your own.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
*Updated the Dashboard/Metrics Display for better visibility
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
Max Trend Points [BigBeluga]🔵 OVERVIEW
A clean and powerful tool for identifying major trend shifts and quantifying the strength of each move using dynamically calculated price extremes.
This indicator helps traders visualize the most significant trend changes by plotting trend direction lines and dynamically tracking the highest or lowest point within each trend leg. It’s ideal for identifying key price impulses and measuring their magnitude in real time.
🔵 CONCEPTS
Uses an adaptive trend-following logic based on volatility envelopes created from HMA of the price range (high - low).
Identifies trend direction and flips when price breaks above or below these dynamic envelopes.
Tracks swing highs and lows within the current trend leg to highlight trend extremes.
Calculates and displays the percentage gain or drop from trend start to trend peak/valley.
🔵 FEATURES
Trend Shift Detection:
Plots a colored trend line (uptrend or downtrend) that updates based on price action volatility.
Impulse Mapping:
Draws a dashed line between the point of trend change (close) and the current trend leg's extreme (highest high or lowest low).
Percentage Labeling:
Displays a floating label showing the exact percent change from the trend start to the current extreme.
Real-Time Adjustments:
As the trend progresses, the extreme point and the percent label update automatically to reflect new highs/lows.
🔵 HOW TO USE
Look for the trend color shift and circular marker to identify a new potential trend direction.
Use the dashed lines and percent label to evaluate the strength and potential maturity of each move.
Combine this tool with support/resistance levels or other indicators to identify confluence zones.
Adjust the "Factor" input to make the trend detection more or less sensitive depending on your timeframe.
🔵 CONCLUSION
Max Trend Points is an efficient visual indicator for understanding the structure and magnitude of trending moves. It provides essential feedback on how far a trend has traveled, where momentum may be peaking, and when a shift may be underway—all with real-time adaptability and clean presentation.
Liquidity Sweep Detector – PDH/PDL LevelsPrevious Day High/Low Liquidity Sweep Detector (Intraday Accurate)
This indicator tracks the previous day's high and low using intraday data, rather than the daily candle, ensuring precise sweep detection across lower timeframes (15m to 4H).
It monitors for liquidity sweeps—moments when price briefly moves above the previous high or below the previous low—and visually marks these events on the chart.
Key Features
Intraday-accurate PDH/PDL tracking
Real-time sweep detection
On-chart labels marking sweep events
Toggleable table showing sweep status
Alert conditions for PDH/PDL sweep triggers
Best For
Traders who use Smart Money Concepts (SMC), liquidity-based strategies, or look for stop hunts and reversal zones tied to key prior-day levels.
Works well across FX, crypto, and indices on 15m, 1H, and 4H charts.
Reintegration OPR zone 9h30📝 Indicator Description (for TradingView):
Name: Reintegration OPR Zone – 9:30 AM EST (UTC-4)
Purpose:
This indicator is designed for US indices like NAS100, US30, or SPX500. It helps identify potential false breakouts or retests by tracking when the price re-enters the Opening Price Range (OPR) after an initial breakout.
🔍 How it works:
At 9:30 AM New York time (UTC-4), the script captures the high and low of the first 15-minute candle (which is key for the US session open).
It then draws a horizontal box (rectangle) from the high to the low of that candle.
The box extends horizontally for 7 hours (28 candles on a 15-minute chart).
The script tracks if price:
Breaks above or below the OPR zone
Then re-enters the zone (a potential "fakeout" or "retest" signal)
No label or text is displayed on the chart (you requested it to be hidden).
🕒 Timeframe:
Designed for the 15-minute chart (M15)
Assumes New York session open at 9:30 AM EST (UTC-4)
ORB Advanced Cloud Indicator & FIB's by TenAMTraderSummary: ORB Advanced Cloud Indicator with Alerts and Fibonacci Retracement Targets by TenAMTrader
This TradingView script is an advanced version of the Opening Range Breakout (ORB) indicator, enhanced with visual clouds and Fibonacci retracement/extension levels. It is designed to help traders identify key price levels and track price movements relative to those levels throughout the trading day. The script includes alert functionalities to notify traders when price crosses key levels and when Fibonacci levels are reached, which can serve as potential entry and exit targets.
Key Features:
Primary and Secondary Range Calculation:
The indicator calculates the primary range (defined by a start and end time) and optionally, a secondary range.
The primary range includes the highest and lowest prices during the designated time period, as well as the midpoint of this range.
The secondary range (if enabled) tracks another price range during a second time period, with its own high, low, and midpoint.
Visual Clouds:
The script draws colored clouds between the high, midpoint, and low of the opening range.
The upper cloud spans between the Opening High and Midpoint, while the lower cloud spans between the Midpoint and Opening Low.
Similarly, a second set of clouds can be drawn for the secondary range (if enabled).
Fibonacci Levels:
The script calculates Fibonacci retracement and extension levels based on the primary range (the difference between the Opening High and Opening Low).
Fibonacci levels can be used as entry and exit targets in a trading strategy, as these levels often act as potential support/resistance zones.
Fibonacci levels include standard values like -0.236, -0.382, -0.618, and positive extensions like 1.236, 1.618, etc.
Customizable Alerts:
Alerts can be set to trigger when:
The price crosses above the Opening High.
The price crosses below the Opening Low.
The price crosses the Opening Midpoint.
These alerts can help traders act quickly on important price movements relative to the opening range.
Customization Options:
The indicator allows users to adjust the time settings for both the primary and secondary ranges.
Custom colors can be set for the lines, clouds, and Fibonacci levels.
The visibility of each line and cloud can be toggled on or off, giving users flexibility in how the chart is displayed.
Fibonacci Levels Overview:
The script includes several Fibonacci retracement and extension levels:
Negative Retracements (e.g., -0.236, -0.382, -0.50, -0.618, etc.) are plotted below the Opening Low, and can act as potential support levels in a downtrend.
Positive Extensions (e.g., 1.236, 1.382, 1.618, 2.0, etc.) are plotted above the Opening High, and can act as potential resistance levels in an uptrend.
Fib levels can be used as entry and exit targets to capitalize on price reversals or breakouts.
Safety Warning:
This script is for educational and informational purposes only and is not intended as financial advice. While it provides valuable technical information about price ranges and Fibonacci levels, trading always involves risk. Users are encouraged to:
Paper trade or use a demo account before applying this indicator with real capital.
Use proper risk management strategies, including stop-loss orders, to protect against unexpected market movements.
Understand that no trading strategy, indicator, or tool can guarantee profits, and losses can occur.
Important: The creator, TenAMTrader, and TradingView are not responsible for any financial losses resulting from the use of this script. Always trade responsibly, and ensure you fully understand the risks involved in any trading strategy.
OpeningRange (Trading_Tix)Purpose:
The indicator highlights the high, low, and middle (50%) price levels of a specified session's opening range. These levels can serve as key support and resistance zones for trading strategies. The indicator also offers options to extend these levels beyond the session into later timeframes, making it useful for tracking breakout or trend continuation setups.
Key Features:
1. Session Detection:
The indicator identifies a specific session period using the user-defined Session Time. It calculates the start time, high, and low prices during this period:
rangeTime: Defines the session time range (default: 5:00 PM to 2:59 AM).
extendTime: Defines the extended time range where lines/backgrounds can be prolonged.
2. Opening Range Calculation:
High (high_val) and Low (low_val)**:
Tracks the highest and lowest prices during the session.
Middle Line:
A midpoint is calculated by averaging high_val and low_val.
3. Visual Elements:
Horizontal Lines:
Drawn at the high, low, and middle levels.
Customizable in width and color.
Shaded Background Box:
Covers the range between high and low prices.
The box’s color and transparency can be adjusted.
Line and Box Extension:
Optionally extends these elements into the extended time range.
4. Customization:
Users have the flexibility to:
Toggle visibility of lines, middle line, and background box.
Adjust colors, line thickness, and style.
Enable or disable the extension of lines and backgrounds into the extended period.
How It Works:
Initialization:
The script initializes variables to store range data (startTime, high_val, low_val) and drawing objects (lines, boxes).
It detects whether the current bar falls within the session (inSession) or extended timeframe (inExtend).
Plotting:
During the session:
Deletes previous lines and boxes from prior sessions.
Draws new lines at the high, low, and middle levels.
Creates a background box covering the range, if enabled.
During the extended period:
Extends the session lines and box, if the user has opted for extensions.
Updates:
Continuously adjusts the high/low values and updates the lines as new price data arrives.
Use Cases:
This indicator can be valuable for traders who:
Use the opening range to identify potential breakout zones.
Trade based on price consolidation within the range.
Want a visual representation of key price levels to plan entries and exits.
Would you like help refining this script further or adjusting its settings to match your trading style?
Cointegration Buy and Sell Signals [EdgeTerminal]The Cointegration Buy And Sell Signals is a sophisticated technical analysis tool to spot high-probability market turning points — before they fully develop on price charts.
Most reversal indicators rely on raw price action, visual patterns, or basic and common indicator logic — which often suffer in noisy or trending markets. In most cases, they lag behind the actual change in trend and provide useless and late signals.
This indicator is rooted in advanced concepts from statistical arbitrage, mean reversion theory, and quantitative finance, and it packages these ideas in a user-friendly visual format that works on any timeframe and asset class.
It does this by analyzing how the short-term and long-term EMAs behave relative to each other — and uses statistical filters like Z-score, correlation, volatility normalization, and stationarity tests to issue highly selective Buy and Sell signals.
This tool provides statistical confirmation of trend exhaustion, allowing you to trade mean-reverting setups. It fades overextended moves and uses signal stacking to reduce false entries. The entire indicator is based on a very interesting mathematically grounded model which I will get into down below.
Here’s how the indicator works at a high level:
EMAs as Anchors: It starts with two Exponential Moving Averages (EMAs) — one short-term and one long-term — to track market direction.
Statistical Spread (Regression Residuals): It performs a rolling linear regression between the short and long EMA. Instead of using the raw difference (short - long), it calculates the regression residual, which better models their natural relationship.
Normalize the Spread: The spread is divided by historical price volatility (ATR) to make it scale-invariant. This ensures the indicator works on low-priced stocks, high-priced indices, and crypto alike.
Z-Score: It computes a Z-score of the normalized spread to measure how “extreme” the current deviation is from its historical average.
Dynamic Thresholds: Unlike most tools that use fixed thresholds (like Z = ±2), this one calculates dynamic thresholds using historical percentiles (e.g., top 10% and bottom 10%) so that it adapts to the asset's current behavior to reduce false signals based on market’s extreme volatility at a certain time.
Z-Score Momentum: It tracks the direction of the Z-score — if Z is extreme but still moving away from zero, it's too early. It waits for reversion to start (Z momentum flips).
Correlation Check: Uses a rolling Pearson correlation to confirm the two EMAs are still statistically related. If they diverge (low correlation), no signal is shown.
Stationarity Filter (ADF-like): Uses the volatility of the regression residual to determine if the spread is stationary (mean-reverting) — a key concept in cointegration and statistical arbitrage. It’s not possible to build an exact ADF filter in Pine Script so we used the next best thing.
Signal Control: Prevents noisy charts and overtrading by ensuring no back-to-back buy or sell signals. Each signal must alternate and respect a cooldown period so you won’t be overwhelmed and won’t get a messy chart.
Important Notes to Remember:
The whole idea behind this indicator is to try to use some stat arb models to detect shifting patterns faster than they appear on common indicators, so in some cases, some assumptions are made based on historic values.
This means that in some cases, the indicator can “jump” into the conclusion too quickly. Although we try to eliminate this by using stationary filters, correlation checks, and Z-score momentum detection, there is still a chance some signals that are generated can be too early, in the stock market, that's the same as being incorrect. So make sure to use this with other indicators to confirm the movement.
How To Use The Indicator:
You can use the indicator as a standalone reversal system, as a filter for overbought and oversold setups, in combination with other trend indicators and as a part of a signal stack with other common indicators for divergence spotting and fade trades.
The indicator produces simple buy and sell signals when all criteria is met. Based on our own testing, we recommend treating these signals as standalone and independent from each other . Meaning that if you take position after a buy signal, don’t wait for a sell signal to appear to exit the trade and vice versa.
This is why we recommend using this indicator with other advanced or even simple indicators as an early confirmation tool.
The Display Table:
The floating diagnostic table in the top-right corner of the chart is a key part of this indicator. It's a live statistical dashboard that helps you understand why a signal is (or isn’t) being triggered, and whether the market conditions are lining up for a potential reversal.
1. Z-Score
What it shows: The current Z-score value of the volatility-normalized spread between the short EMA and the regression line of the long EMA.
Why it matters: Z-score tells you how statistically extreme the current relationship is. A Z-score of:
0 = perfectly average
> +2 = very overbought
< -2 = very oversold
How to use it: Look for Z-score reaching extreme highs or lows (beyond dynamic thresholds). Watch for it to start reversing direction, especially when paired with green table rows (see below)
2. Z-Score Momentum
What it shows: The rate of change (ROC) of the Z-score:
Zmomentum=Zt − Zt − 1
Why it matters: This tells you if the Z-score is still stretching out (e.g., getting more overbought/oversold), or reverting back toward the mean.
How to use it: A positive Z-momentum after a very low Z-score = potential bullish reversal A negative Z-momentum after a very high Z-score = potential bearish reversal. Avoid signals when momentum is still pushing deeper into extremes
3. Correlation
What it shows: The rolling Pearson correlation coefficient between the short EMA and long EMA.
Why it matters: High correlation (closer to +1) means the EMAs are still statistically connected — a key requirement for cointegration or mean reversion to be valid.
How to use it: Look for correlation > 0.7 for reliable signals. If correlation drops below 0.5, ignore the Z-score — the EMAs aren’t moving together anymore
4. Stationary
What it shows: A simplified "Yes" or "No" answer to the question:
“Is the spread statistically stable (stationary) and mean-reverting right now?”
Why it matters: Mean reversion strategies only work when the spread is stationary — that is, when the distance between EMAs behaves like a rubber band, not a drifting cloud.
How to use it: A "Yes" means the indicator sees a consistent, stable spread — good for trading. "No" means the market is too volatile, disjointed, or chaotic for reliable mean reversion. Wait for this to flip to "Yes" before trusting signals
5. Last Signal
What it shows: The last signal issued by the system — either "Buy", "Sell", or "None"
Why it matters: Helps avoid confusion and repeated entries. Signals only alternate — you won’t get another Buy until a Sell happens, and vice versa.
How to use it: If the last signal was a "Buy", and you’re watching for a Sell, don’t act on more bullish signals. Great for systems where you only want one position open at a time
6. Bars Since Signal
What it shows: How many bars (candles) have passed since the last Buy or Sell signal.
Why it matters: Gives you context for how long the current condition has persisted
How to use it: If it says 1 or 2, a signal just happened — avoid jumping in late. If it’s been 10+ bars, a new opportunity might be brewing soon. You can use this to time exits if you want to fade a recent signal manually
Indicator Settings:
Short EMA: Sets the short-term EMA period. The smaller the number, the more reactive and more signals you get.
Long EMA: Sets the slow EMA period. The larger this number is, the smoother baseline, and more reliable trend bases are generated.
Z-Score Lookback: The period or bars used for mean & std deviation of spread between short and long EMAs. Larger values result in smoother signals with fewer false positives.
Volatility Window: This value normalizes the spread by historical volatility. This allows you to prevent scale distortion, showing you a cleaner and better chart.
Correlation Lookback: How many periods or how far back to test correlation between slow and long EMAs. This filters out false positives when EMAs lose alignment.
Hurst Lookback: The multiplier to approximate stationarity. Lower leads to more sensitivity to regime change, higher produces a more stricter filtering.
Z Threshold Percentile: This value sets how extreme Z-score must be to trigger a signal. For example, 90 equals only top/bottom 10% of extremes, 80 = more frequent.
Min Bars Between Signals: This hard stop prevents back-to-back signals. The idea is to avoid over-trading or whipsaws in volatile markets even when Hurst lookback and volatility window values are not enough to filter signals.
Some More Recommendations:
We recommend trying different EMA pairs (10/50, 21/100, 5/20) for different asset behaviors. You can set percentile to 85 or 80 if you want more frequent but looser signals. You can also use the Z-score reversion monitor for powerful confirmation.
Options Volume [theUltimator5]📊 Option Volume — Multi-Strike Option Flow Visualizer
The Option Volume indicator tracks and visualizes volume activity for up to 10 custom option strike symbols on any ticker. It supports both individual strike analysis and a combined cumulative volume mode, providing an intuitive view of option flow across your selected strikes.
🔧 Features:
Dynamic Strike Control: Select up to 10 strikes and customize each with ticker, expiration date (YYMMDD), and option type (Call or Put).
Volume Display Modes:
🔹 Individual: Shows a separate volume bar for each strike.
🔸 Cumulative: Combines all selected strike volumes into a single bar, colored green for Calls and red for Puts.
Customizable Table Display:
Toggle the option symbol table on/off.
Position the table in any corner of the chart.
Table cell colors match plotted bars in Individual mode, or turn red/green in Cumulative mode based on option type.
Smart Volume Filtering: Only shows volume bars on the bar where volume updates (i.e., no carryover from stale bars).
Input Efficiency: All strike prices are automatically rounded to the nearest 0.5 increment for standardized symbol formatting.
⚙️ How to Use:
Select the ticker you want to analyze.
Input the expiration date and option type (C or P).
Define strike prices (up to 10).
Toggle between Individual or Cumulative volume display.
Adjust the number of visible strikes and table position as needed.
This tool is ideal for traders looking to monitor strike-level option volume behavior, spot flow anomalies, or keep track of high-interest strike activity in real-time.
The indicator currently doesn't support multiple expiration dates or a combination of calls/puts. If you want to view multiple expirations or a both calls and puts at the same time, simply add the indicator multiple times.
Master Litecoin Hashrate IndicatorThis script is a custom indicator called "Master Litecoin Hashrate Indicator," designed to track and visualize Litecoin's hashrate trends in the form of both a moving average and raw hashrate data. Here’s a breakdown of how it works:
Overview:
Indicator Type: It’s an overlay set to false, meaning it won’t be plotted directly on the price chart but on a separate pane beneath it.
Litecoin Hashrate: This tracks the computational power used to mine Litecoin, in PH/s (Peta Hashes per second).
Key Components:
Inputs:
ma_length: This is the length of the moving average, calculated as half of 7 (which equals 3.5), to smooth out the hashrate data.
Hashrate Data:
hashrate: The script pulls real-time Litecoin hashrate data using the INTOTHEBLOCK:LTC_HASHRATE security symbol from TradingView.
ma_hashrate: A simple moving average (SMA) is applied to the raw hashrate data over the defined period (ma_length), helping to smooth out short-term fluctuations.
Plotting:
hashrate: The raw hashrate is plotted in yellow with a linewidth of 2.
ma_hashrate: The moving average of the hashrate is plotted in white with a linewidth of 2.
Background Color:
The background color changes dynamically depending on the relationship between the raw hashrate and its moving average:
If the raw hashrate is greater than the moving average, the background turns a yellow color (with 90% transparency).
If the raw hashrate is less than the moving average, the background turns blue (with 90% transparency).
If they are equal, there is no background color change.
Purpose:
This indicator helps to visualize the current hashrate trends and compare them with the longer-term moving average. By doing so, it can highlight periods where the hashrate is either increasing or decreasing significantly, giving traders insights into network activity and mining strength.
Rolling Beta against SPY📈 Pine Script Showcase: Rolling Beta Against SPY
Understanding how your favorite stock or ETF moves in relation to a benchmark like the S&P 500 can offer powerful insights into risk and exposure. This script calculates and visualizes the rolling beta of any asset versus the SPY ETF (which tracks the S&P 500).
🧠 What Is Beta?
Beta measures the sensitivity of an asset's returns to movements in the broader market. A beta of:
- 1.0 means the asset moves in lockstep with SPY,
- >1.0 indicates higher volatility than the market,
- <1.0 implies lower volatility or possible defensive behavior,
- <0 suggests inverse correlation (e.g., hedging instruments).
🧮 How It Works
This script computes rolling beta over a user-defined window (default = 60 periods) using classic linear regression math:
- Calculates daily returns for both the asset and SPY.
- Computes covariance between the two return streams.
- Divides by the variance of SPY returns to get beta.
⚙️ Customization
You can adjust the window size to control the smoothing:
- Shorter windows capture recent volatility changes,
- Longer windows give more stable, long-term estimates.
📊 Visual Output
The script plots the beta series dynamically, allowing you to observe how your asset’s correlation to SPY evolves over time. This is especially useful in regime-change environments or during major macroeconomic shifts.
💡 Use Cases
- Portfolio construction: Understand how your assets co-move with the market.
- Risk management: Detect when beta spikes—potentially signaling higher market sensitivity.
- Market timing: Use beta shifts to infer changing investor sentiment or market structure.
📌 Pro Tip: Combine this rolling beta with volatility, Sharpe ratio, or correlation tracking for a more robust factor-based analysis.
Ready to add a layer of quantitative insight to your chart? Add the script to your watchlist and start analyzing your favorite tickers against SPY today!
Dskyz (DAFE) Turning Point Indicator - Dskyz (DAFE) Turning Point Indicator — Smart Reversal Signals
Inspired by the intelligent logic of a pervious indicator I saw. This script represents a next-generation reversal detection system—completely re-engineered with cutting-edge filters, adaptive logic, and intelligent dashboards.
The Dskyz (DAFE) Turning Point Indicator
🧠 What Is It?
is designed to identify key market reversal zones with extraordinary accuracy by combining trend direction, volatility confirmation, price action patterns, and smart filtering layers—all visualized in a highly interactive and informative chart overlay.
This isn’t just a signal generator—it’s a decision-making assistant.
⚙️ Inputs & How to Use Them
All input fields are grouped for ease-of-use and explanation:
🔸 Reversal Logic Settings
Source: The price source used for signal generation (default: hlcc4). Can be changed to any standard price formula (open, close, hl2, etc.).
ATR Period: Used for determining volatility and dynamic trailing stop logic.
Supertrend Factor / Period: Calculates directional movement to detect trending vs choppy zones.
Reversal Sensitivity Thresholds: Internal logic filters minor pullbacks from true reversals.
🔸 Filters
Trend Filter: Enables trend-only signals (optional).
Volume Spike Filter: Confirms reversals with significant volume activity.
Volatility Zone Coloring: Visually highlights high-volatility areas to avoid late entries or fakeouts.
Custom High/Low Detection: Smart local top/bottom scanning to reinforce accuracy.
🔸 Visual & Dashboard Options
Signal Labels: Toggle signal labels on the chart.
Color Theme: Choose your visual theme for easier visibility.
Dashboard Toggle: Activate a compact dashboard summarizing strategy health (win rate, drawdown, trend state, volatility).
🧩 Functions Used
ta.supertrend(): Determines trend direction for signal confirmation and filtering.
ta.atr(): Calculates real-time volatility to determine trailing stop exits and visual zones.
ta.rsi() (internally optimized): Helps filter overbought/oversold conditions.
Local High/Low Scanner: Tracks recent pivots using a custom dynamic lookback.
Signal Engine: Consolidates multiple confirmation layers before plotting.
🚀 What Makes It Unique?
Unlike traditional reversal indicators, this one combines:
Multi-factor signal validation: No single indicator makes the call—volume, trend, price action, and volatility all contribute.
Adaptive filtering: The indicator evolves with the market—less noise, smarter signals.
Visual volatility heatmap zones: Avoid entering during uncertainty or manipulation spikes.
Interactive trend dashboard: Immediate insight into the strength and condition of the current market phase.
Highly customizable: Turn features on/off to match your trading style—scalping, swing, or trend-following.
Precision timing: Uses optimized versions of RSI and ATR that adjust automatically with price context.
🧬 Recommended for:
Commodity: Futures, Forex, Crypto
Timeframes: 1m to 1h for active traders. 4h+ for swing trades.
Pair With: Support/resistance zones, Fibonacci levels, and smart money concepts for additional confluence.
🎯 Why It Works
- Traditional reversal signals suffer from lag and noise. This system filters both by:
- Using multi-source confirmation, not just price movement.
-Tracking volatility directly, not assuming static markets.
-Detecting exhaustion, not just divergence.
-Keeping your screen clean, with only the most relevant data shown.
🧾 Credit & Acknowledgement
🧠 Original Concept Inspiration: This project was deeply inspired by the work of Enes_Yetkin_ and their approach to reversal detection. This version expands on the concept with additional technical layers, updated visuals, and real-time adaptability.
📌 Final Thoughts
This is more than a reversal tool. It's a market condition interpreter, entry/exit planner, and risk assistant all in one. Every aspect is engineered to give you an edge—especially when timing means everything.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Win-Loss Streak PlotterWin-Loss Streak Plotter
This indicator tracks the win/loss streaks of moving average crossovers (using simple moving averages for illustration purposes). It calculates the price change after each crossover, marking each as a win (green) or loss (red). The win rate is shown separately.
Inputs:
Source: Price series (default: open)
Fast MA: Fast moving average (default: open)
Slow MA: Slow moving average (default: open)
Total Crosses to Analyze: Number of crossovers to track
Crosses per Row: Number of crossovers per row in the table
Output:
A table displays each crossover’s result (win/loss).
A separate win rate table shows the percentage of wins.
Suggestions are always welcomed!
OBVX Conviction Bias🧮 The OBVX Conviction Bias overlay tracks the flow of directional volume using the classic On-Balance Volume calculation, then filters it through a layered moving average system to expose crowd commitment , pressure transitions , and momentum fatigue . The tool applies two smoothed averages to the OBV line—a fast curve and a longer-term baseline scaled using Euler’s constant (2.718)—and visualizes their relationship using a color-coded crossover ribbon and pressure fills. When used correctly, it reveals whether a move is being supported by meaningful volume, or whether the crowd is starting to disengage.
🚦 The core signal compares OBV to its fast moving average. When OBV climbs above the short average, it fills green—suggesting real directional effort. When OBV sinks below, the fill turns maroon—flagging fading conviction or pullback potential. A second fill between the short and long OBV moving averages captures the broader trend of volume intention. If the short is above the long, this space fills greenish, showing constructive pressure. If it flips, the fill fades red, signaling crowd hesitation, rotation, or early exhaustion.
⚖️ All smoothing is user-selectable, defaulting to VWMA for effort-sensitive structure. The long-term average is auto-scaled using the natural exponential multiplier (2.718), offering rhythm that reflects the curve of participation. OBVX Conviction Bias isn’t trying to predict—it’s trying to show you where the crowd is leaning , and whether that lean is gaining traction or losing strength.
🧐 Ideal Use-Cases:
• Detect divergence between volume flow and price action
• Confirm breakout validity with volume alignment
• Fade breakouts where OBV fails to follow through
• Time pullback entries when OBV pressure resumes in trend direction
🍷 Recommended Pairings:
• ZVOL to measure whether volume is statistically significant or just noise (as shown)
• RVOL Effort Matrix to validate crowd effort by tier and structure zone
• SUPeR TReND 2.718 and/or MA Ribbons for directional confluence
• ATR Turbulence to track volatility-phase alignment with volume intention
(US) Historical Trade WarsHistorical U.S. Trade Wars Indicator
Overview
This indicator visualizes major U.S. trade wars and disputes throughout modern economic history, from the McKinley Tariff of 1890 to recent U.S.-China tensions. This U.S.-focused timeline is perfect for macro traders, economic historians, and anyone looking to understand how America's trade conflicts correlate with market movements.
Features
Comprehensive U.S. Timeline: Covers 130+ years of U.S.-centered trade disputes with historically accurate dates.
Color-Coded Events:
🔴 Red: Marks the beginning of a U.S. trade war or major dispute.
🟡 Yellow: Highlights significant events within a trade conflict.
🟢 Green: Shows resolutions or ends of trade disputes.
Global Partners/Rivals: Tracks U.S. trade relations with China, Japan, EU, Canada, Mexico, Brazil, Argentina, and others.
Country Flags: Uses emoji flags for easy visual identification of nations in trade relations with the U.S.
Major Trade Wars Covered:
McKinley Tariff (1890-1894)
Smoot-Hawley Tariff Act (1930-1934)
U.S.-Europe Chicken War (1962-1974)
Multifiber Arrangement Quotas (1974-2005)
Japan-U.S. Trade Disputes (1981-1989)
NAFTA and Softwood Lumber Disputes
Clinton and Bush-Era Steel Tariffs
Obama-Era China Tire Tariffs
Rare Earth Minerals Dispute (2012-2014)
Solar Panel Dispute (2012-2015)
TPP and TTIP Negotiations
U.S.-China Trade War (2018-present)
Airbus-Boeing Dispute
Usage
Analyze how markets historically responded to trade war initiations and resolutions.
Identify patterns in market behavior during periods of trade tensions.
Use as an overlay with price action to examine correlations.
Perfect companion for macro analysis on daily, weekly, or monthly charts.
About
This indicator is designed as a historical reference tool for traders and economic analysts focusing on U.S. trade policy and its global impact. The dates and events have been thoroughly researched for accuracy. Each label includes emojis to indicate the U.S. and its trade partners/rivals, making it easy to track America's evolving trade relationships across time.
Note: This indicator works best on larger timeframes (daily, weekly, monthly) due to the historical span covered.
High and Low DayHigh and Low Day
This indicator automatically tracks and displays the daily high and low of the current trading session directly on your chart.
Each new day, it resets the levels and plots horizontal lines:
Green Line for the daily high
Red Line for the daily low
It also adds labels (“High Day” and “Low Day”) for easy visual reference.
The levels update in real time as new highs or lows are formed throughout the day.
You can toggle the visibility of these lines and labels using the "Mostrar Linhas do Dia Atual" (Show Current Day Lines) setting.
Perfect for intraday traders looking to keep track of key support and resistance levels during the trading day.
Market Clock with Inline HoursThis script displays a powerful, configurable market session clock that shows the open/closed status and trading hours for major global financial markets — including specialized logic for NY Futures (Globex).
🔑 Key Features:
✅ Real-Time Session Status:
Shows whether each selected market is currently OPEN or CLOSED, based on the user’s selected time zone.
✅ NY Futures Weekend Logic:
Built-in logic ensures NY Futures are marked CLOSED:
Friday after 5:00 PM ET
All of Saturday
Sunday until 6:00 PM ET
This reflects the true CME Globex trading schedule.
✅ 12-Hour Format + Timezone Labels:
Session hours are displayed in 12-hour AM/PM format alongside their associated timezone (EST, GMT, JST, etc.) for clarity.
✅ Fully Configurable Markets:
You can choose to display:
NY Market (RTH)
NY Futures (Globex)
London
Tokyo
Frankfurt
And you can easily toggle them on/off in the settings.
✅ Text Size & Position Customization:
Easily control the text size (tiny → huge) and screen position (top/bottom, left/center/right).
✅ Auto Timezone Offset Support:
Select from a list of common time zones (EST, UTC, JST, etc.), or enter your own custom UTC offset for global flexibility.
✅ Compact & Clean Design:
The layout groups each market’s:
Real-time OPEN/CLOSED status
Trading hours
All into a single column, making the layout clean and dashboard-ready.
🧠 Who is this for?
Day traders
Futures traders
Forex traders
Anyone who tracks multiple time zones or global markets
📌 Notes:
Clock updates based on chart timeframe (e.g., every 1m on a 1-minute chart)
Pine Script doesn't support real-time per-second updates, but works well for market status tracking
💬 Feedback Welcome!
This script was designed to be lightweight and user-friendly. Suggestions and improvements are always welcome — feel free to leave a comment or reach out directly.
MÈGAS ALGO : ZIG-ZAG CYCLE INSIGTH [INDICATOR]Overview
The Zig-Zag Cycle Insigth is a revisited version of the classic Zig Zag indicator, designed to provide traders with a more comprehensive and actionable view of price movements.
This advanced tool not only highlights significant price swings but also incorporates additional features such as cycle analysis, real-time data tracking, and Fibonacci retracement levels. These enhancements make it an invaluable resource for identifying trends, potential reversal points, and market structure.
This indicator adheres to TradingView's guidelines and is optimized for both technical analysts and active traders who seek deeper insights into market dynamics.
Key Features:
1. Customizable Thresholds for Price Movements:
- Users can set personalized thresholds for price movement percentages and time periods.
This ensures that only significant price swings are plotted, reducing noise and increasing
clarity.
- Straight lines connect swing highs and lows, providing a cleaner visual representation of
the trend.
2. Cycle Analysis Table:
- A dynamic table is included to analyze price cycles based on three key factors:
- Price Change: Measures the magnitude of each swing (high-to-low or low-to-high).
- Time Duration (Bar Count): Tracks the number of bars elapsed between consecutive swings,
offering precise timing insights.
- Volume: Analyzes trading volume during each segment of the cycle.
- The indicator calculates the **maximum**, **minimum**, and **mean** values for each
parameter across all completed cycles, providing deeper statistical insights into market
behavior.
- This table updates in real-time, offering traders a quantitative understanding of how price
behaves over different cycles.
3. Real-Time Data Integration:
- The indicator displays live updates of current price action relative to the last identified
swing high/low. This includes:
- Current distance from the last pivot point.
- Percentage change since the last pivot.
- Volume traded since the last pivot.
4. Fibonacci Retracement Levels:
- Integrated Fibonacci retracement levels are dynamically calculated based on the most
recent significant swing high and low.
- Key retracement levels (23.6%, 38.2%, 50%, 61.8%, and 78.6%) are plotted alongside the Zig
Zag lines, helping traders identify potential support/resistance zones.
- Extension levels (100%, 161.8%, etc.) are also included to anticipate possible breakout
targets.
5. Customizable Alerts:
- Users can configure alerts for specific real-time conditions, such as:
- Price Change
- Duration
- Volume
- Fibonacci Retracement Levels
How It Works:
1. Zig Zag Identification:
- The indicator scans historical price data to identify significant turning points where the
price moves by at least the user-defined percentage threshold.
- These turning points are connected by straight lines to form the Zig Zag pattern.
2. Cycle Analysis:
For each completed cycle (from one swing high/low to the next), the indicator calculates:
- Price Change: Difference between the start and end prices of the cycle.
- Maximum Price Change: The largest price difference observed across all cycles.
- Minimum Price Change: The smallest price difference observed across all cycles.
- Mean Price Change: The average price difference across all cycles.
- Time Duration (Bar Count): Number of bars elapsed between consecutive swings.
- Maximum Duration: The longest cycle in terms of bar count.
- Minimum Duration: The shortest cycle in terms of bar count.
- Mean Duration: The average cycle length in terms of bar count.
- Volume: Total volume traded during the cycle.
- Maximum Volume: The highest volume traded during any single cycle.
- Minimum Volume: The lowest volume traded during any single cycle.
- Mean Volume: The average volume traded across all cycles.
- These calculations provide traders with a statistical overview of market behavior, enabling
them to identify patterns and anomalies in price, time, and volume.
3. Fibonacci Integration:
- Once a new swing high or low is identified, the indicator automatically calculates Fibonacci
retracement and extension levels.
- These levels serve as reference points for potential entry/exit opportunities.
4. Real-Time Updates:
- As the market evolves, the indicator continuously monitors the relationship between the
current price and the last identified swing point.
- Real-time metrics, such as percentage change and volume, are updated dynamically.
5. Alerts Based on Real-Time Parameters:
- The indicator allows users to set customizable alerts based on real-time conditions:
- Price Change Alert: Triggered when the real-time price change is less or greater than a
predefined percentage threshold (e.g., > or < fixed value).
- Duration Alert: Triggered when the cycle duration (in bars) is less or greater than a
predefined
bar count threshold (e.g., > or < fixed value).
- Volume Alert: Triggered when the trading volume during the current cycle is less or greater
than a predefined volume threshold (e.g., > or < fixed value).
Advantages of Zig-Zag Cycle Insigth
- Comprehensive Insights: Combining cycle analysis, Fibonacci retracements, and real-time data
provides a holistic view of market conditions.
- Statistical Analysis: The inclusion of maximum, minimum, and mean values for price change,
duration, and volume offers deeper insights into market behavior.
- Actionable Signals: Customizable alerts ensure traders never miss critical market events based
on real-time price, duration, and volume parameters.
- User-Friendly Design: Clear visuals and intuitive controls make it accessible for traders of all
skill levels.
Reference:
TradingView/ZigZag
TradingView/AutofibRetracement
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outcomes.
Multi-timeframe Trend & Momentum DashboardMulti-Timeframe Trend & Momentum Dashboard
This indicator is a comprehensive multi-timeframe analysis tool designed for traders who want to quickly assess market trends and momentum across several timeframes. It combines trend detection with duration tracking and displays key information in an easy-to-read on-chart table. Key features include:
Multi-Timeframe Analysis:
Analyzes nine different timeframes (from 1-minute up to 1-week) simultaneously, helping you gauge the overall market trend at a glance.
Trend Detection & Duration:
Uses a combination of a short-term EMA and a long-term SMA to determine whether the market is bullish, bearish, or neutral. It also tracks how long the current trend has persisted in terms of consecutive bars and displays this duration next to each timeframe.
RSI Display & Visual Alerts:
Calculates the RSI for each timeframe. RSI values are color-coded—green when above 50 (indicating bullish momentum) and red when below 50 (indicating bearish conditions). Additionally, if the market is bearish on a particular timeframe while the RSI is above 50, the RSI cell flashes yellow to alert you of a potential trend reversal or divergence.
On-Chart Trend Start Markers:
When a new trend is detected on your current chart’s timeframe, the indicator automatically marks the bar with a label showing the new trend direction, providing a clear visual cue for trend changes.
This powerful tool is perfect for traders looking to combine multi-timeframe trend analysis with momentum indicators, enabling a more informed and dynamic trading strategy. Whether you’re a day trader or swing trader, the Multi-Timeframe Trend & Momentum Dashboard brings clarity to market conditions across multiple time horizons.
OG Volume PowerDescription:
The OG Volume Power is an elite-level volume analysis suite built for identifying momentum surges, trend continuation, and buyer/seller imbalances at critical price levels. It combines real-time VWAP tracking, a dynamic Point of Control (POC), and volume delta clusters to give traders a complete picture of price and volume interaction.
🔍 Key Features:
Real-Time VWAP:
Tracks volume-weighted average price to identify mean reversion and intraday fair value zones. Ideal for institutional-level entries and exits.
Dynamic POC (Point of Control):
Automatically finds the price level with the highest volume over the last N candles (default 50), helping traders pinpoint where market participants are most committed.
Buyer/Seller Volume Delta Clusters:
Highlights imbalances between buying and selling pressure using bullish and bearish volume deltas that exceed the 20-bar volume average — excellent for momentum detection and early trend recognition.
⚙️ How It Works:
Green triangle: Buyer surge (bullish delta + above average volume)
Red triangle: Seller surge (bearish delta + above average volume)
Magenta line: Dynamic POC (highest volume price over recent candles)
Orange line: VWAP (acts as a magnetic force for price)
📈 Best For:
Intraday scalping or swing trading on SPY, QQQ, BTC, or Forex
Volume flow confirmation before breakout entries
Filtering false breakouts with delta strength signals
🧠 Pro Tip:
Use OG Volume Power alongside your trend indicators (like OG EMA Stack or OG Supertrend) to confirm that volume is backing the move. Look for surges near VWAP or POC zones for sniper-level entries.
Hurst-Based Trend Persistence w/Poisson Prediction
---
# **Hurst-Based Trend Persistence w/ Poisson Prediction**
## **Introduction**
The **Hurst-Based Trend Persistence with Poisson Prediction** is a **statistically-driven trend-following oscillator** that provides traders with **a structured approach to identifying trend strength, persistence, and potential reversals**.
This indicator combines:
- **Hurst Exponent Analysis** (to measure how persistent or mean-reverting price action is).
- **Color-Coded Trend Detection** (to highlight bullish and bearish conditions).
- **Poisson-Based Trend Reversal Probability Projection** (to anticipate when a trend is likely to end based on statistical models).
By integrating **fractal market theory (Hurst exponent)** with **Poisson probability distributions**, this indicator gives traders a **probability-weighted view of trend duration** while dynamically adapting to market volatility.
---
## **Simplified Explanation (How to Read the Indicator at a Glance)**
1. **If the oscillator line is going up → The trend is strong.**
2. **If the oscillator line is going down → The trend is weakening.**
3. **If the color shifts from red to green (or vice versa), a trend shift has occurred.**
- **Strong trends can change color without weakening** (meaning a bullish or bearish move can remain powerful even as the trend shifts).
4. **A weakening trend does NOT necessarily mean a reversal is coming.**
- The trend may slow down but continue in the same direction.
5. **A strong trend does NOT guarantee it will last.**
- Even a powerful move can **suddenly reverse**, which is why the **Poisson-based background shading** helps anticipate probabilities of change.
---
## **How to Use the Indicator**
### **1. Understanding the Rolling Hurst-Based Trend Oscillator (Main Line)**
The **oscillator line** is based on the **Hurst exponent (H)**, which quantifies whether price movements are:
- **Trending** (values above 0 → momentum-driven, persistent trends).
- **Mean-reverting** (values below 0 → price action is choppy, likely to revert to the mean).
- **Neutral (Random Walk)** (values around 0 → price behaves like a purely stochastic process).
#### **Interpreting the Oscillator:**
- **H > 0.5 → Persistent Trends:**
- Price moves tend to sustain in one direction for longer periods.
- Example: Strong uptrends in bull markets.
- **H < 0.5 → Mean-Reverting Behavior:**
- Price has a tendency to revert back to its mean.
- Example: Sideways markets or fading momentum.
- **H ≈ 0.5 → Random Walk:**
- No clear trend; price is unpredictable.
A **gray dashed horizontal line at 0** serves as a **baseline**, helping traders quickly assess whether the market is **favoring trends or mean reversion**.
---
### **2. Color-Coded Trend Signal (Visual Confirmation of Trend Shifts)**
The oscillator **changes color** based on **price slope** over the lookback period:
- **🟢 Green → Uptrend (Price Increasing)**
- Price is rising relative to the selected lookback period.
- Suggests sustained bullish pressure.
- **🔴 Red → Downtrend (Price Decreasing)**
- Price is falling relative to the selected lookback period.
- Suggests sustained bearish pressure.
#### **How to Use This in Trading**
✔ **Stay in trends until a color change occurs.**
✔ **Use color changes as confirmation for trend reversals.**
✔ **Avoid counter-trend trades when the oscillator remains strongly colored.**
---
### **3. Poisson-Based Trend Reversal Projection (Anticipating Future Shifts)**
The **shaded orange background** represents a **Poisson-based probability estimation** of when the trend is likely to reverse.
- **Darker Orange = Higher Probability of Trend Reversal**
- **Lighter Orange / No Shade = Low Probability of Immediate Reversal**
💡 **The idea behind this model:**
✔ Trends **don’t last forever**, and their duration follows **statistical patterns**.
✔ By calculating the **average historical trend duration**, the indicator predicts **how likely a trend shift is at any given time**.
✔ The **Poisson probability function** is applied to determine the **expected likelihood of a reversal as time progresses**.
---
## **Mathematical Foundations of the Indicator**
This indicator is based on **two primary statistical models**:
### **1. Hurst Exponent & Trend Persistence (Fractal Market Theory)**
- The **Hurst exponent (H)** measures **autocorrelation** in price movements.
- If past trends **persist**, H will be **above 0.5** (meaning trend-following strategies are favorable).
- If past trends tend to **mean-revert**, H will be **below 0.5** (meaning reversal strategies are more effective).
- The **Rolling Hurst Oscillator** calculates this exponent over a moving window to track real-time trend conditions.
#### **Formula Breakdown (Simplified for Traders)**
The Hurst exponent (H) is derived using the **Rescaled Range (R/S) Analysis**:
\
Where:
- **R** = **Range** (difference between max cumulative deviation and min cumulative deviation).
- **S** = **Standard deviation** of price fluctuations.
- **Lookback** = The number of periods analyzed.
---
### **2. Poisson-Based Trend Reversal Probability (Stochastic Process Modeling)**
The **Poisson process** is a **probabilistic model used for estimating time-based events**, applied here to **predict trend reversals based on past trend durations**.
#### **How It Works**
- The indicator **tracks trend durations** (the time between color changes).
- A **Poisson rate parameter (λ)** is computed as:
\
- The **probability of a reversal at any given time (t)** is estimated using:
\
- **As t increases (trend continues), the probability of reversal rises**.
- The indicator **shades the background based on this probability**, visually displaying the likelihood of a **trend shift**.
---
## **Dynamic Adaptation to Market Conditions**
✔ **Volatility-Adjusted Trend Shifts:**
- A **custom volatility calculation** dynamically adjusts the **minimum trend duration** required before a trend shift is recognized.
- **Higher volatility → Requires longer confirmation before switching trend color.**
- **Lower volatility → Allows faster trend shifts.**
✔ **Adaptive Poisson Weighting:**
- **Recent trends are weighted more heavily** using an exponential decay function:
- **Decay Factor (0.618 by default)** prioritizes **recent intervals** while still considering historical trends.
- This ensures the model adapts to changing market conditions.
---
## **Key Takeaways for Traders**
✅ **Identify Persistent Trends vs. Mean Reversion:**
- Use the oscillator line to determine whether the market favors **trend-following or counter-trend strategies**.
✅ **Visual Trend Confirmation via Color Coding:**
- **Green = Uptrend**, **Red = Downtrend**.
- Trend changes help confirm **entry and exit points**.
✅ **Anticipate Trend Reversals Using Probability Models:**
- The **Poisson projection** provides a **statistical edge** in **timing exits before trends reverse**.
✅ **Adapt to Market Volatility Automatically:**
- Dynamic **volatility scaling** ensures the indicator remains effective in **both high and low volatility environments**.
Happy trading and enjoy!
