Session HeatmapIntraday Seasonality
Overview
Analyzes historical patterns by time of day. Identifies when volatility, volume, and open interest changes tend to be highest or lowest.
Features
Multiple Metrics: TR (volatility), Volume, and Open Interest changes
Flexible Grouping: View patterns by weekday or month to spot day-of-week or seasonal effects
Heatmap Visualization: Blue (low) to Red (high) color scale for quick pattern recognition
Percentile Mode: Reduces outlier impact by using 5th-95th percentile range
Timezone Support: Display in UTC alongside your local time
Metrics Explained
TR: Volatility - when markets move most
Volume: Liquidity - when participation is highest
OI Increase: When new positions are opened
OI Decrease: When positions are closed
OI Net: Net open interest change
Usage
Set your timezone and preferred slot size (30min/1H)
Choose a date range (relative or custom)
Select a metric to analyze
Use "Group By" to see weekday or monthly patterns
Switch to Percentile color scale if outliers dominate
Notes
Chart timeframe should be equal to or smaller than Slot Size
OI metrics require Binance Perpetual symbols
DST is not automatically adjusted; consider seasonal shifts for US/EU sessions
Statistics
Probability-Based Adaptive Detection🙏🏻 PBAD (Probability-Based Adaptive Detection) : adaptive control tool for outliers || novelty detection, made for worst case data & processes, for the highest time complexity O(n^2) compared with the alternatives (would be explained in a sec). Thresholds are completely data driven and axiomatic, no need in provided hyperparameters, are not learned or optimized. The method accepts multiple weights, e.g. both temporal and volatility weights.
Method briefly explained (I can go deeper if any1 asks explicitly):
Performs weighted KDE on initial input data, finds KDE global maximum (mode), creates new “residuals” dataset by centering initial data around this value;
Performs weighted KDE on residuals, uses sigmoid based probability mass targets with increasing probability coverage to construct a set of non-disjoint High Density Intervals (also called HDR, HPD in Bayesian terms);
Uses these intervals to calculate analogs of centralized & standardized moments;
Uses these ^^ moments to construct a set of control thresholds. The scheme used in PBAD is not only based on a central threshold, or on neighboring ones, it utilizes all previous thresholds, gaining more information.
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The most important part is to understand whether you really need PBAD. Because even tho it seems to be the best one given highest algocomplexity, irl it would work worse in cases when it’s not required by your data.
Here’s the menu (aka taxonomy omg) of methods you can use that would let you make the right choice:
Moment-Based Adaptive Detection (MBAD) :
Norm: L2
Time complexity: original O(n), successfully reduced to O(1) in online version
Use case: default, general purpose
Based on: method of moments (powers of residuals from mean)
Thresholds architecture: centralized
Quantile-Based Adaptive Detection (QBAD):
Norm: L1
Time complexity: O(nlogn)
Use case: either bad data Or process instability
Based on: quantile moments (dyadic percentiles of residuals from median)
Thresholds architecture: chained/recursive/sequential
Probability-Based Adaptive Detection (PBAD):
Norm: L0
Time complexity: O(n^2)
Use case: both bad data And process instability
Based on: probability moments (target probability masses of residuals from KDE mode)
Thresholds architecture: decentralized (for lack of a better name xd, the idea is that these thresholds gain information from the all other threshold and are Not exclusively based on the central or neighboring thresholds)
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Examples of true use cases:
^^ an appropriate financial instrument to use PBAD
^^ and another one
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Additional details about how to use it:
Keep the student5 kernel, it’s the best you can do. I added others mostly for comparisons and if you want to use the tool Not for its primary purpose (on a fine data)
“Calculate for N bars” and “Starting at bar N” options allow to reduce calculation period only on the N number of last bars or next bars from a chosen one. It's vital, because calculations here are heavy
Keep plotting offset at 1 (allows to visually compare current bar with the previous threshold values). This is the way it should be done on price data.
HLC3 is the optimal source input, unless you want to use your own better one point estimate of each datapoint (in the best case done by using PBAD itself on OHLC+ values).
In essence it should be used just like MBAD or QBAD, fade/push extensions and limit, fade/push/skip deviations & basis, or other strategies of your. Again, the only reason for 3 methods to exist is to be chosen for according data characteristics.
Btw:
This is the initial version, I don’t consider it perfected tbh, even tho it works as expected, however this method is very situational anyways.
In this script KDE function is modified to ensure the outcoming probabilities Do sum up to 1. I didn’t do this normalization in Weighted KDE Mode script , but there it’s not required since we just need a KDE global max.
see ya
∞
GC1! H1 Stats+GC1! H1 Stats - Detailed Prob & Excursion Indicator
Overview
GC1! H1 Stats - Detailed Prob & Excursion is a specialized statistical overlay indicator for TradingView, tailored for Gold futures (GC1!) on a 1-hour framework. It provides real-time insights into the probability of price returning to the hourly open after sweeping the previous hour’s high (PHH) or previous hour’s low (PHL), based on historical data segmented by hour (0–23) and 20-minute intervals. The indicator visualizes these sweeps with lines, labels, circles, background fills, and “excursion zones” (also called “Magic Boxes”) that highlight median/mean extensions post-sweep, along with percentile lines (75th / 90th / 95th) for gauging potential “pain” or extreme moves. This tool is designed for intraday Gold traders focusing on liquidity sweeps and mean-reversion behavior, helping to quantify edge using empirical probabilities and excursion statistics.
The data is hardcoded from extensive historical analysis of GC1! behavior (e.g., probabilities ranging roughly from ~7% to ~91%, with sample sizes up to 2000+ per segment), making it a backtested reference rather than a dynamic learning model. It emphasizes visual clarity during active hours, with options to filter for Regular Trading Hours (RTH: 09:00–15:59 ET) or high-probability (>70%) events only. Note: This is an educational tool for analyzing market structure; it does not predict future performance or provide trading signals/advice. Past data does not guarantee future results, and users should backtest on current conditions (as of December 2025 data availability) and use at their own risk, in compliance with TradingView’s house rules.
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Key Features
• Sweep Detection & Probability Labels: Identifies when price breaks PHH (upside) or PHL (downside), displaying a centered label with probability of returning to the hourly open, sample size (N), time of sweep, and a checkmark (✅) if the open is retested post-sweep.
• Visual Lines & Markers: Draws hourly open (h.o.), PHH, and PHL lines with customizable styles/colors; adds small circles on sweep bars for quick spotting.
• Breakout→Open Background Fill: Shaded zone from sweep bar until price returns to open, visualizing extension duration and retracement.
• Excursion (Pain) Zone - “Magic Box”: Post-sweep box showing median/mean extension percentages, colored dynamically by probability (green high, orange mid, red low); includes dashed lines for 75th/90th/95th percentiles to mark statistical extremes.
• Time-Segmented Data: Probabilities and excursions vary by hour (0–23) and 20-min segments (0–19 min: _0, 20–39: _1, 40–59: _2), capturing intraday nuances (e.g., higher probs in early/late hours).
• Filters for Focus: RTH-only mode hides non-session elements; high-prob-only shows >70% events to reduce noise.
• Alerts: Triggers on PHH/PHL sweeps with messages for chart checks.
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How It Works
• Data Foundation: Uses pre-computed maps for probabilities (prob_high_taken/prob_low_taken), sample sizes, and excursions (mean, median, p75/p90/p95 as percentages of open). Data is initialized on the first bar via f_init_high_data() and f_init_low_data(), covering 24 hours with 3 segments each (e.g., key "9_1" for 09:20–09:39). Probabilities represent historical likelihood of price returning to open after sweep; excursions quantify average/rare extensions (e.g., 0.156% mean = 0.156% of open price).
• Period Detection: On new 1H bars (new_period_bar), resets visuals, draws lines for open/PHH/PHL extending 1 hour forward, and labels if enabled. Uses request.security on standard ticker for real OHLC, bypassing chart transformations (e.g., Heikin Ashi).
• Sweep Logic: On each bar, checks if real high > PHH or real low < PHL. If so, fetches segment-specific data (hour + floor(minute/20)), displays probability label centered mid-hour. Skips if filtered (RTH-only or <70% prob).
• Excursion Visualization: If enabled, draws “Magic Box” from 1-min to 58-min into the hour, bounded by mean/median levels (top/bottom adjusted for high/low sweep). Adds percentile lines with labels (e.g., “75%”) at right end. Box color reflects prob strength for quick bias assessment.
• Retest Check: Monitors for open retest post-sweep (high/low cross open, or gap scenarios from prev bar). Adds ✅ to label if hit on subsequent bars (skips sweep bar to avoid false positives). Stops background fill on retest or at 58-min mark.
• Background Fill: Activates on sweep, shades until retest, using user color.
• Cleanup & Performance: Manages labels in arrays, clears on new periods; no excess drawing beyond max counts (500 lines/labels/boxes).
This setup blends statistical backtesting with real-time visualization: hardcoded data provides empirical probabilities/excursions (reducing subjectivity in breakouts), while dynamic elements (lines, fills, boxes) overlay structure on the chart. It helps Gold traders assess if a sweep is “high-edge” (e.g., >70% probability of reverting) or likely to run (low probability, high excursion), pairing historical context with current price action.
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Settings and Customization
Inputs are grouped for ease:
1. Settings:
o Show RTH Only (9:00–15:59): Restricts to main session (default: false; tooltip: for RTH-focused stats).
o Show High Prob Only (>70%): Filters low-prob sweeps visually (default: false; tooltip: highlights confidence).
2. Visuals:
o Show Line Labels: Toggle “h.o.” / “phh” / “phl” (default: true).
o Period Open Line Color: Gray 50% (default).
o Previous High/Low Line Colors: Gray 100% (default).
o Open Line Style/Width: Dotted/1 (default; options: Solid/Dotted/Dashed).
3. Breakout→Open Background:
o Show Breakout→Open Background: Toggle fill (default: true).
o Fill Color: Teal 85% (default).
4. Breakout Circles:
o Show Breakout Circles: Toggle (default: true).
o PHH/PHL Break Circle Colors: White 20% (default).
5. Info Label Style:
o Text Size: Small (default; options: Auto/Tiny/Normal/Large/Huge).
o Label Text Color: White (default).
o Low/Mid/High Probability Colors: Red 20% / Orange 20% / Green 20% (default).
6. Excursion (Pain) Zone:
o Show Excursion Zone: Toggle Magic Box (default: true).
o Excursion Box Color: Gray 75% (default; dynamic overrides).
o 75th/90th/95th Percentile Lines: Orange 30% / Red 30% / Dark Red 100% (default).
No additional tables/plots; all elements are lines/labels/boxes for overlay focus.
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Usage Tips
• Breakout Trading: Watch for sweeps with high probability (>70%, green label) as potential fades back to open; low probability (red) may signal runs—use the excursion box for targets (e.g., exit at 90th percentile for extremes).
• Time Awareness: Probabilities often peak in key liquidity windows and drop in quieter hours; segments capture momentum shifts (e.g., _2 often lower prob).
• RTH Focus: Enable for cleaner stats during high-liquidity session hours; disable for a 24-hour view.
• Visual Filtering: Use high-prob-only in volatile conditions to reduce noise; combine with volume or other confluence tools for confirmation.
• Alerts Integration: Set TradingView alerts on sweeps; check label for probability/N before acting.
• Chart Setup: Best on 1H or lower GC1! charts; adjust text size for readability on smaller screens.
• Backtesting: Manually review historical sweeps against data maps to validate; update hardcoded values if new data emerges (as of 2025).
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Limitations
• Fixed Data: Hardcoded stats may not reflect recent market changes (e.g., post-2025 regime shifts); not adaptive.
• Reactive Only: Detects sweeps after they occur; no predictive signals.
• Timeframe Specific: Locked to 1H logic; may not translate to other assets/timeframes without recoding data.
• Visual Clutter: On busy charts, labels/boxes may overlap—toggle selectively.
• No Live Stats: Sample sizes are historical; real-time N/prob not updated.
• Gaps & Extremes: Handles gaps in retest logic, but rare events (e.g., macro news) may exceed the 95th percentile.
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Disclaimer
This indicator is for informational and educational purposes only. Trading involves significant risk of loss and is not suitable for all investors. The hardcoded data represents past Gold futures (GC1!) performance and does not guarantee future outcomes. No claims of profitability are made—results depend on market conditions, user strategy, and risk management. Consult a financial advisor before trading, and backtest extensively. Abiding by TradingView rules, this tool provides no investment recommendations.
BTC - Bitcoin Strategic Dashboard by RM Title: BTC - Bitcoin Strategic Dashboard | RM
Overview & Philosophy
The Bitcoin Strategic Dashboard is a comprehensive analytics tool designed to provide deeper market context beyond simple price action.
While a standard chart displays price history, this dashboard focuses on the structural health of the market. It aims to answer clearer questions: Is the asset statistically overextended? Is the current volatility compressed or expanding? How is Bitcoin currently correlating with traditional equity markets?
This script aggregates key data points—Performance, Risk, Valuation, and Macro Correlations—into a single, organized table. It is designed to be a quiet, high-density reference tool that sits unobtrusively in the corner of your screen, helping to contextualize daily price movements without cluttering your workspace.
Methodology & Module Breakdown
The dashboard is divided into 5 strategic modules. Here is exactly how to read them, how they are calculated, and how to interpret the data.
1. PERFORMANCE
This section answers: "Is Bitcoin actually beating the traditional market, and by how much?"
BTC Return : The raw percentage growth of Bitcoin.
Timeframes: 1-Year (Tactical Trend) and 4-Year (The Halving Cycle).
Alpha (vs SPX / Gold):
Meaning : "Alpha" measures true outperformance. It tells you how much better your capital worked in Bitcoin compared to the S&P 500 (Stocks) or Gold.
Calculation : We use a Relative Growth Ratio. Instead of simple subtraction, we calculate the growth factor of BTC divided by the growth factor of the Benchmark.
Interpretation :
Green: Bitcoin is outperforming. It is the superior vehicle for capital.
Red: Bitcoin is underperforming traditional assets (Opportunity Cost is high).
2. RISK PROFILE
This section answers: "How dangerous is the market right now?"
Drawdown (DD):
Meaning : The percentage loss from the 1-Year High.
Interpretation : Deep Drawdowns (e.g., > -50%) historically signal generational buying opportunities (Deep Red). Small Drawdowns (< -5%) signal we are near "Discovery Mode" (Blue/Green).
Sharpe Ratio:
Meaning : The industry standard for "Risk-Adjusted Return." It asks: "Is the profit worth the stress?"
Timeframe : Annualized over 365 Days.
Interpretation :
> 1.0: Good. The return justifies the risk.
> 2.0: Excellent. (Dark Green).
< 0.0: Bad. You are taking risk for negative returns.
Sortino Ratio:
Meaning : Similar to Sharpe, but it only counts downside volatility as "risk." Bitcoin often rallies aggressively (Good Volatility); Sortino ignores the upside "risk" and focuses only on minimizing losses.
Volatility (Vol) & Rank:
Meaning : How violently the price is moving.
Calculation : We compare the current 30-Day Volatility against the last 4 Years of volatility history (Rank 0-100).
Interpretation (The Squeeze Strategy) :
BLUE (Cold / <25%): Volatility is historically low. The market is "compressed." Big moves often follow these periods.
RED (Hot / >75%): Volatility is extreme. High risk of mean reversion or panic.
3. VALUATION & MOMENTUM
This section answers: "Is Bitcoin cheap or expensive?"
Mayer Multiple (MM):
Meaning: A "Godfather" of Bitcoin ratios.
Calculation : Current Price divided by the 200-Day Moving Average.
Interpretation :
< 0.8 (Blue): Historically "Cheap."
1.0: Fair Value (Price = Trend).
> 2.4 (Red): Speculative Bubble territory.
RSI (Relative Strength Index):
Timeframe : 14 Days.
Interpretation : >70 suggests the market is overheated (Red). <30 suggests oversold conditions (Blue).
Trend (ADX) :
Meaning : The Average Directional Index measures the strength of a trend, not the direction.
Interpretation : Values >25 (Green) indicate a strong trend is present. Values <20 (Gray) indicate a choppy/sideways market (no trend).
vs 200W (Macro):
Meaning : The distance to the 200-Week Moving Average.
Interpretation : This line is historically the "Cycle Bottom" or "Absolute Support" for Bitcoin. Being close to it (or below it) is rare and often marks cycle lows.
4. MACRO CORRELATIONS
This section answers: "Is Bitcoin moving on its own, or just following the Stock Market?"
vs TradFi (SPX):
Timeframe : 90-Day Correlation Coefficient.
Interpretation :
High Positive (Red): BTC is just acting like a tech stock. No "Safe Haven" status.
Negative/Zero (Green): BTC is "decoupled." It is moving independently of Wall Street.
vs DXY (US Dollar):
Interpretation : Bitcoin usually moves inverse to the Dollar.
Negative (Green): Normal healthy behavior.
Positive (Red): Warning signal. If both DXY and BTC rise, something is breaking in the system.
5. HISTORICAL LEDGER
A Year-by-Year breakdown of returns.
Feature : You can toggle the comparison column in the settings to compare Bitcoin against either S&P 500 or Gold.
Usage : Helps visualize the cyclical nature of returns (e.g., the 4-year cycle pattern of Green-Green-Green-Red).
How to Read the Visuals (Heatmap)
The dashboard uses a standardized Bloomberg-style heatmap to let you assess the market state in milliseconds:
🟢 Green: Profit / Good Performance / Positive Alpha.
🔴 Red: Loss / Overheating / High Risk.
🔵 Blue: "Cold" / Cheap / Low Volatility (Potential Buy Zones).
🟠 Orange: Warning / High Drawdown.
⚫ Gray/Black: Neutral or Fair Value.
Settings & Customization
Visuals: Change the text size (Tiny, Small, Normal) to fit your screen resolution.
Modules: You can toggle individual sections on/off to save screen space.
Calculation: Switch the Historical Benchmark between "S&P 500" and "Gold" depending on your thesis.
Disclaimer
This script is for research and educational purposes only. The metrics provided (Sharpe, Sortino, Mayer Multiple) are derived from historical data and do not guarantee future performance. "Cheap" (Low Mayer Multiple) does not mean the price cannot go lower. Always manage your own risk.
Tags
bitcoin, btc, bloomberg, terminal, dashboard, onchain, mayer multiple, sharpe ratio, volatility, alpha, risk management, Rob Maths
Student Wyckoff Relative StrengthSTUDENT WYCKOFF Relative Strength compares one instrument against another and plots their relative performance as a single line.
Instead of asking “is this chart going up or down?”, the script answers a more practical question: “is THIS asset doing better or worse than my benchmark?”
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1. Concept
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The indicator builds a classic relative strength (RS) line:
• Main symbol = the chart you attach the script to.
• Benchmark symbol = any symbol you choose in the settings (index, ETF, sector, another coin, etc.).
RS is calculated as:
RS = Price(main symbol) / Price(benchmark)
If RS is rising, your symbol outperforms the benchmark.
If RS is falling, your symbol underperforms the benchmark.
You can optionally normalize RS from the first bar (start at 1 or 100) to clearly see how many times the asset has outperformed or lagged behind over the visible history.
This is not a “buy/sell” indicator. It is a **context tool** for rotation, selection and Wyckoff-style comparative analysis.
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2. How the RS line is built
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Inputs:
• Source of main symbol – default is close, but you can choose any OHLC/HL2/typical price etc.
• Benchmark symbol – ticker used as reference (index, sector, futures, Bitcoin, stablecoin pair, etc.).
• Benchmark timeframe – by default the current chart timeframe is used, or you can force a different TF.
The script uses `request.security()` with `lookahead_off` and `gaps_off` to pull benchmark prices **without look-ahead**.
A small epsilon is used internally to avoid division by zero when the benchmark price is very close to 0.
Normalization options:
• Normalize RS from first bar – if enabled, the very first valid RS value becomes “1” (or 100), and all further values are expressed relative to this starting point.
• Multiply RS by 100 – purely cosmetic; makes it easier to read RS as a “percentage-like” scale.
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3. Smoothing and color logic
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To help read the trend of relative strength, the script calculates a simple moving average of the RS line:
• RS MA length – period of smoothing over the RS values.
• Show RS moving average – toggle to display or hide this line.
Color logic:
• When RS is above its own MA → the line is drawn with the “stronger” color.
• When RS is below its MA → the line uses the “weaker” color.
• When RS is close to its MA → neutral color.
Optional background shading:
• When RS > RS MA → background can be tinted softly green (phase of relative strength).
• When RS < RS MA → background can be tinted softly red (phase of relative weakness).
This makes it easy to read the **trend of strength** at a glance, without measuring every small swing.
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4. How to interpret it
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Basic reading rules:
• Rising RS line
– The main symbol is outperforming the benchmark.
– In Wyckoff terms, this can indicate a leader within its group, or a sign of accumulation relative to the market.
• Falling RS line
– The main symbol is underperforming the benchmark.
– Can point to laggards, distribution, or simply an asset that is “dead money” compared to alternatives.
• Flat or choppy RS line
– No clear edge versus the benchmark; performance is similar or rotating back and forth.
With normalization on:
• RS > 1 (or > 100) – the asset has grown more than the benchmark since the starting point.
• RS < 1 (or < 100) – it has grown less (or fallen more) than the benchmark over the same period.
The RS moving average and colored background highlight whether this outperformance/underperformance is a **temporary fluctuation** or a more sustained phase.
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5. Practical uses
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This indicator is useful for:
• **Selecting stronger assets inside a group**
– Compare individual stocks vs an index, sector, or industry ETF.
– Compare altcoins vs BTC, ETH, or a crypto index.
– Prefer charts where RS is in a sustained uptrend rather than just price going “up on its own”.
• **Monitoring sector and rotation flows**
– Attach the script to sector ETFs or major coins and switch the benchmark to a broad market index.
– See where capital is rotating: which areas are gaining or losing strength over time.
• **Supporting Wyckoff-style analysis**
– Use RS together with volume, structure, phases and trading ranges.
– A breakout or SOS with rising RS vs the market tells a different story than the same pattern with falling RS.
• **Portfolio review and risk decisions**
– When an asset shows a long period of relative weakness, it may be a candidate to reduce or replace.
– When RS turns up from a long weak phase, it can signal the start of potential leadership (not an entry by itself, but a reason to study the chart deeper).
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6. Notes and disclaimer
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• Works on any symbol and timeframe available on TradingView.
• The last bar can change in real time as new prices arrive; this is normal behaviour for all indicators that depend on current close.
• There are no built-in alerts or trading signals – this tool is meant to support your own analysis and trading plan.
This script is published for educational and analytical purposes only.
It does not constitute financial or investment advice and does not guarantee any performance. Always test your ideas, understand the logic of your tools and use proper risk management.
Seasonal Trend by LogReturn ProSeasonal Trend by LogReturn Pro
Seasonal Trend by LogReturn Pro is a seasonality indicator that analyzes historical average logarithmic returns to visualize recurring price behavior throughout the trading year.
Instead of using simple price averages, this indicator is based on log returns, making it scale-independent and mathematically consistent across different price levels and assets.
🔍 How It Works
The indicator calculates daily logarithmic returns for each trading day of the year.
These returns are aggregated and averaged over a user-defined number of past years.
Based on this historical data, a seasonal trend profile is constructed that represents the statistically expected market behavior over the year.
All calculations are aligned by trading day index, not calendar days, ensuring accurate seasonality even across different years and holidays.
📈 Display Modes
The indicator offers two complementary visualizations:
1. Absolute Seasonal Projection (Main Chart)
- Projects a price path based on historical average log returns.
- Can be displayd:
- Only for the remaining part of the current year, or
- For the entire year, starting from the beginning.
- Useful for visualizing potential seasonal price tendencies relative to the current price.
2. Relative Seasonal Performance (Indicator Pane)
Shows the cumulative seasonal return in percentage terms.
Centered around a zero line for easy interpretation.
Ideal for identifying periods with historically positive or negative seasonal bias.
💡 Use Cases
Identifying seasonal bullish or bearish phases
Timing entries and exits based on historical tendencies
Combining seasonality with technical or fundamental analysis
Gaining a long-term probabilistic market perspective
⚠️ Disclaimer
This indicator is based on historical data and does not predict future price movements.
It should be used as a statistical reference tool, not as a standalone trading signal.
Session ATR Progression Tracker📊 Session ATR Progression Tracker - SIYL Regression Trading Tool
Track how much of your instrument's 7-day Average True Range (ATR) has been covered during the current trading session. This indicator is specifically designed for regression traders who follow the "Stay In Your Lane" (SIYL) methodology, helping you identify when the probability of mean reversion significantly increases. If you are interested in more on that check out Rod Casselli and tradersdevgroup.com.
🎯 Key Features:
• Real-time ATR Coverage Percentage - See at a glance what percentage of the 7-day ATR has been covered in the current session
• SIYL-Optimized Thresholds - See at a glance when the instrument has achieved 80% and 100% ATR coverage, the proven thresholds where mean reversion probability increases (customizable)
• Flexible Session Modes:
- Daily: Resets at calendar day change
- Session: Uses exchange-defined trading sessions
- Custom Session: Set your exact session start/end times (perfect for futures traders and international markets)
• Visual Alerts - Color-coded display (gray → orange → red) and optional background highlighting
• Repositionable Display - Choose from 9 screen positions to avoid chart clutter
• Session Markers - Green triangles mark the start of each new session
• Detailed Stats - View current range, ATR value, session high/low, and session status
💡 Why Use This Indicator?
This tool is built around a proven concept: regression trading becomes significantly more effective once a session has achieved at least 80% of its 7-day ATR. At this threshold, the probability of price reverting to mean increases substantially, creating higher-probability trade setups for SIYL practitioners.
Benefits for regression traders:
- Identify optimal entry points when mean reversion probability is highest (≥80% ATR coverage)
- Avoid premature regression entries before adequate range has been established
- Recognize when daily moves have "earned their range" and are ripe for reversal
- Time fade-the-move and counter-trend strategies with statistical backing
- Improve win rates by trading only after proven probability thresholds are met
⚙️ Setup Instructions:
1. Add the indicator to your chart
2. Select your preferred "Reset Mode" (recommend "Custom Session" for futures/international markets)
3. If using Custom Session, enter your session times in 24-hour format (e.g., 0930-1600 for US stocks, 1700-1600 for CME futures)
4. Adjust alert thresholds if desired (default: 80% and 100% - proven SIYL thresholds)
5. Position the display where it's most visible on your chart
📈 Works Across All Markets:
Stocks • Futures • Forex • Indices • Crypto • Commodities
Perfect for regression traders, mean reversion specialists, and SIYL practitioners who want to trade with probability on their side by entering only after the session has "earned its range."
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Tip: For futures contracts with overnight sessions that span calendar days (like MES, MNQ, MYM), use "Custom Session" mode with your exchange's official session times for accurate tracking.
VolatilityCone by ImpliedVolatility ProVolatilityCone by ImpliedVolatility Pro
VolatilityCone by ImpliedVolatility Pro is a forward-looking volatility projection tool that visualizes expected price ranges based on implied volatility.
It draws a volatility cone starting from a user-defined date and projects statistically expected price boundaries into the future using standard deviation theory.
🔍 What does this indicator do?
This indicator calculates and plots price ranges that represent ±1, ±2, and ±3 standard deviations from a starting price, based on implied volatility.
The result is a cone-shaped projection that shows where price is statistically likely to move over time.
In addition, the indicator calculates a Z-Score, showing how far the current price deviates from the expected mean in volatility terms.
📐 Key Features
→ Forward projection based on implied volatility
→ Supports up to 3 standard deviation levels
→ Optional display of half standard deviation levels
→ Manually enter implied volatility or automatically fetch IV from another symbol (e.g. VIX)
→ Custom Start Date
→ The cone starts exactly at the selected date
→ Ideal for earnings, events, or cycle-based analysis
→ Displays the statistical mean price
→ Z-Score indicates how extreme the current price is relative to the cone
📊 How to Use
Price inside the cone
→ Normal volatility behavior
Price near ±1σ
→ Typical volatility range
Price near ±2σ or ±3σ
→ Statistically stretched or extreme conditions
Positive Z-Score
→ Price trading above the mean
Negative Z-Score
→ Price trading below the mean
This makes the indicator useful for:
→ Volatility analysis
→ Mean reversion strategies
→ Risk assessment
→ Event-based forecasting
→ Options-related analysis
⚙️ Notes & Disclaimer
This indicator is not a prediction tool, but a statistical projection
It assumes volatility follows a square-root-of-time model
Best used as a context tool, not as a standalone trading signal
Expectativa de Juros (Fed)An indicator that measures future expectations for US interest rates, measured by the difference between the Fed's interest rate and pricing on the CME.
Unmitigated Liquidity ZonesUnmitigated Liquidity Zones
Description:
Unmitigated Liquidity Zones is a professional-grade Smart Money Concepts (SMC) tool designed to visualize potential "draws on liquidity" automatically.
Unlike standard Support & Resistance indicators, this script focuses exclusively on unmitigated price levels — Swing Highs and Swing Lows that price has not yet revisited. These levels often harbor resting liquidity (Stop Losses, Buy/Sell Stops) and act as magnets for market makers.
How it works:
Detection: The script identifies significant Pivot Points based on your customizable length settings.
Visualization: It draws a line extending forward from the pivot, labeled with the exact Price and the Volume generated at that specific swing.
Mitigation Logic: The moment price "sweeps" or touches a level, the script treats the liquidity as "collected" and automatically removes the line and label from the chart. This keeps your workspace clean and focused only on active targets.
Key Features:
Dynamic Cleanup: Old levels are removed instantly upon testing. No chart clutter.
Volume Context: Displays the volume (formatted as K/M/B) of the pivot candle. This helps you distinguish between weak structure and strong institutional levels.
High Visibility: customizable bold lines and clear labels with backgrounds, designed to be visible on any chart theme.
Performance: Optimized using Pine Script v6 arrays to handle hundreds of levels without lag.
How to trade with this:
Targets: Use the opposing liquidity pools (Green lines for shorts, Red lines for longs) as high-probability Take Profit levels.
Reversals (Turtle Soup): Wait for price to sweep a bold liquidity line. If price aggressively reverses after taking the line, it indicates a "Liquidity Grab" setup.
Magnets: Price tends to gravitate toward "old" unmitigated levels.
Settings:
Pivot Length: Sensitivity of the swing detection (default: 20). Higher values find more significant/long-term levels.
Limit: Maximum number of active lines to prevent memory overload.
Visuals: Toggle Price/Volume labels, adjust line thickness and text size.
Simple Candle Strategy# Candle Pattern Strategy - Pine Script V6
## Overview
A TradingView trading strategy script (Pine Script V6) that identifies candlestick patterns over a configurable lookback period and generates trading signals based on pattern recognition rules.
## Strategy Logic
The strategy analyzes the most recent N candlesticks (default: 5) and classifies their patterns into three categories, then generates buy/sell signals based on specific pattern combinations.
### Candlestick Pattern Classification
Each candlestick is classified as one of three types:
| Pattern | Definition | Formula |
|---------|-----------|---------|
| **Close at High** | Close price near the highest price of the candle | `(high - close) / (high - low) ≤ (1 - threshold)` |
| **Close at Low** | Close price near the lowest price of the candle | `(close - low) / (high - low) ≤ (1 - threshold)` |
| **Doji** | Opening and closing prices very close; long upper/lower wicks | `abs(close - open) / (high - low) ≤ threshold` |
### Trading Rules
| Condition | Action | Signal |
|-----------|--------|--------|
| Number of Doji candles ≥ 3 | **SKIP** - Market is too chaotic | No trade |
| "Close at High" count ≥ 2 + Last candle closes at high | **LONG** - Bullish confirmation | Buy Signal |
| "Close at Low" count ≥ 2 + Last candle closes at low | **SHORT** - Bearish confirmation | Sell Signal |
## Configuration Parameters
All parameters are adjustable in TradingView's "Settings/Inputs" tab:
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **K-line Lookback Period** | 5 | 3-20 | Number of candlesticks to analyze |
| **Doji Threshold** | 0.1 | 0.0-1.0 | Body size / Total range ratio for doji identification |
| **Doji Count Limit** | 3 | 1-10 | Number of dojis that triggers skip signal |
| **Close at High Proximity** | 0.9 | 0.5-1.0 | Required proximity to highest price (0.9 = 90%) |
| **Close at Low Proximity** | 0.9 | 0.5-1.0 | Required proximity to lowest price (0.9 = 90%) |
### Parameter Tuning Guide
#### Proximity Thresholds (Close at High/Low)
- **0.95 or higher**: Stricter - only very strong candles qualify
- **0.90 (default)**: Balanced - good for most market conditions
- **0.80 or lower**: Looser - catches more patterns, higher false signals
#### Doji Threshold
- **0.05-0.10**: Strict doji identification
- **0.10-0.15**: Standard doji detection
- **0.15+**: Includes near-doji patterns
#### Lookback Period
- **3-5 bars**: Fast, sensitive to recent patterns
- **5-10 bars**: Balanced approach
- **10-20 bars**: Slower, filters out noise
## Visual Indicators
### Chart Markers
- **Green Up Arrow** ▲: Long entry signal triggered
- **Red Down Arrow** ▼: Short entry signal triggered
- **Gray X**: Skip signal (too many dojis detected)
### Statistics Table
Located at top-right corner, displays real-time pattern counts:
- **Close at High**: Count of candles closing near the high
- **Close at Low**: Count of candles closing near the low
- **Doji**: Count of doji/near-doji patterns
### Signal Labels
- Green label: "✓ Long condition met" - below entry bar
- Red label: "✓ Short condition met" - above entry bar
- Gray label: "⊠ Too many dojis, skip" - trade skipped
## Risk Management
### Exit Strategy
The strategy includes built-in exit rules based on ATR (Average True Range):
- **Stop Loss**: ATR × 2
- **Take Profit**: ATR × 3
Example: If ATR is $10, stop loss is at -$20 and take profit is at +$30
### Position Sizing
Default: 100% of equity per trade (adjustable in strategy properties)
**Recommendation**: Reduce to 10-25% of equity for safer capital allocation
## How to Use
### 1. Copy the Script
1. Open TradingView
2. Go to Pine Script Editor
3. Create a new indicator
4. Copy the entire `candle_pattern_strategy.pine` content
5. Click "Add to Chart"
### 2. Apply to Chart
- Select your preferred timeframe (1m, 5m, 15m, 1h, 4h, 1d)
- Choose a trading symbol (stocks, forex, crypto, etc.)
- The strategy will generate signals on all historical bars and in real-time
### 3. Configure Parameters
1. Right-click the strategy on chart → "Settings"
2. Adjust parameters in the "Inputs" tab
3. Strategy will recalculate automatically
4. Backtest results appear in the Strategy Tester panel
### 4. Backtesting
1. Click "Strategy Tester" (bottom panel)
2. Set date range for historical testing
3. Review performance metrics:
- Win rate
- Profit factor
- Drawdown
- Total returns
## Key Features
✅ **Execution Model Compliant** - Follows official Pine Script V6 standards
✅ **Global Scope** - All historical references in global scope for consistency
✅ **Adjustable Sensitivity** - Fine-tune all pattern detection thresholds
✅ **Real-time Updates** - Works on both historical and real-time bars
✅ **Visual Feedback** - Clear signals with labels and statistics table
✅ **Risk Management** - Built-in ATR-based stop loss and take profit
✅ **No Repainting** - Signals remain consistent after bar closes
## Important Notes
### Before Trading Live
1. **Backtest thoroughly**: Test on at least 6-12 months of historical data
2. **Paper trading first**: Practice with simulated trades
3. **Optimize parameters**: Find the best settings for your trading instrument
4. **Manage risk**: Never risk more than 1-2% per trade
5. **Monitor performance**: Review trades regularly and adjust as needed
### Market Conditions
The strategy works best in:
- Trending markets with clear directional bias
- Range-bound markets with defined support/resistance
- Markets with moderate volatility
The strategy may underperform in:
- Highly choppy/noisy markets (many false signals)
- Markets with gaps or overnight gaps
- Low liquidity periods
### Limitations
- Works on chart timeframes only (not intrabar analysis)
- Requires at least 5 bars of history (configurable)
- Fixed exit rules may not suit all trading styles
- No trend filtering (will trade both directions)
## Technical Details
### Historical Buffer Management
The strategy declares maximum bars back to ensure enough historical data:
```pine
max_bars_back(close, 20)
max_bars_back(open, 20)
max_bars_back(high, 20)
max_bars_back(low, 20)
```
This prevents runtime errors when accessing historical candlestick data.
### Pattern Detection Algorithm
```
For each bar in lookback period:
1. Calculate (high - close) / (high - low) → close_to_high_ratio
2. If close_to_high_ratio ≤ (1 - threshold) → count as "Close at High"
3. Calculate (close - low) / (high - low) → close_to_low_ratio
4. If close_to_low_ratio ≤ (1 - threshold) → count as "Close at Low"
5. Calculate abs(close - open) / (high - low) → body_ratio
6. If body_ratio ≤ doji_threshold → count as "Doji"
Signal Generation:
7. If doji_count ≥ cross_count_limit → SKIP_SIGNAL
8. If close_at_high_count ≥ 2 AND last_close_at_high → LONG_SIGNAL
9. If close_at_low_count ≥ 2 AND last_close_at_low → SHORT_SIGNAL
```
## Example Scenarios
### Scenario 1: Bullish Signal
```
Last 5 bars pattern:
Bar 1: Closes at high (95%) ✓
Bar 2: Closes at high (92%) ✓
Bar 3: Closes at mid (50%)
Bar 4: Closes at low (10%)
Bar 5: Closes at high (96%) ✓ (last bar)
Result:
- Close at high count: 3 (≥ 2) ✓
- Last closes at high: ✓
- Doji count: 0 (< 3) ✓
→ LONG SIGNAL ✓
```
### Scenario 2: Skip Signal
```
Last 5 bars pattern:
Bar 1: Doji pattern ✓
Bar 2: Doji pattern ✓
Bar 3: Closes at mid
Bar 4: Doji pattern ✓
Bar 5: Closes at high
Result:
- Doji count: 3 (≥ 3)
→ SKIP SIGNAL - Market too chaotic
```
## Performance Optimization
### Tips for Better Results
1. **Use Higher Timeframes**: 15m or higher reduces false signals
2. **Combine with Indicators**: Add volume or trend filters
3. **Seasonal Adjustment**: Different parameters for different seasons
4. **Instrument Selection**: Test on liquid, high-volume instruments
5. **Regular Rebalancing**: Adjust parameters quarterly based on performance
## Troubleshooting
### No Signals Generated
- Check if lookback period is too large
- Verify proximity thresholds aren't too strict (try 0.85 instead of 0.95)
- Ensure doji limit allows for trading (try 4-5 instead of 3)
### Too Many False Signals
- Increase proximity thresholds to 0.95+
- Reduce lookback period to 3-4 bars
- Increase doji limit to 3-4
- Test on higher timeframes
### Strategy Tester Shows Losses
- Review individual trades to identify patterns
- Adjust stop loss and take profit ratios
- Change lookback period and thresholds
- Test on different market conditions
## References
- (www.tradingview.com)
- (www.tradingview.com)
- (www.investopedia.com)
- (www.investopedia.com)
## Disclaimer
**This strategy is provided for educational and research purposes only.**
- Not financial advice
- Past performance does not guarantee future results
- Always conduct thorough backtesting before live trading
- Trading involves significant risk of loss
- Use proper risk management and position sizing
## License
Created: December 15, 2025
Version: 1.0
---
**For updates and modifications, refer to the accompanying documentation files.**
EAP Trader NY BreakoutMy own profitable NY Breakout Playbook - backtested with statistics
by
EAP Trader
Backtest any Indicator [Target Mode] StrategyUniversal Backtester Strategy with Sequential Logic
This strategy serves as a highly versatile, universal backtesting engine designed to test virtually any indicator-based trading system without requiring custom code for every new idea. It transforms standard indicator comparisons into a robust trading strategy with advanced features like sequential entry steps, dynamic target modes, and automated webhook alerts.
The core philosophy of this script is flexibility. Whether you are testing simple crossovers (e.g., MA Cross) or complex multi-stage setups (e.g., RSI overbought followed by a MACD flip), this tool allows you to configure logic via the settings panel and immediately see backtested results with professional-grade risk management.
Core Logic: Source vs. Target Mode
The fundamental building block of this strategy is the "Comparator" engine. Instead of hard-coding specific indicators, the script allows users to define logic slots (L1-L5 for Longs, S1-S5 for Shorts).
Each slot operates on a flexible comparison logic:
Source: The primary indicator you are testing (e.g., Close Price, RSI, Volume).
Operator: The condition to check (Equal/Cross, Greater Than, Less Than).
Target Mode:
Value Mode: Compares the Source against a fixed number (e.g., RSI > 70).
Source Mode: Compares the Source against another dynamic indicator (e.g., Close > SMA 200).
This "Target Mode" switch allows the strategy to adapt to almost any technical analysis concept, from oscillator levels to moving average trends.
Advanced Entry System: Sequential Steps (1-5)
Unlike standard backtesters that usually require all conditions to happen simultaneously (AND logic), this strategy implements a State Machine for sequential execution. Each of the 5 entry slots (L1-L5 / S1-S5) is assigned a "Step" number.
The logic flows as follows:
Stage 1: The strategy waits for all conditions assigned to "Step 1" to be true.
Latch & Wait: Once Step 1 is met, the strategy "remembers" this and advances to Stage 2. It waits for a subsequent bar to satisfy Step 2 conditions.
Trigger: The actual trade entry is only executed once the highest assigned step is completed.
Example Use Case:
Step 1: Price closes below the Lower Bollinger Band (Dip).
Step 2: RSI crosses back above 30 (Confirmation).
Execution: Buy Signal triggers on the Step 2 confirmation candle.
This creates a realistic "Setup -> Trigger" workflow common in professional trading, preventing premature entries.
Exit Logic & Risk Management
The strategy employs a dual-layer exit system to maximize profit retention and protect capital.
1. Signal-Based Exits (OR Logic) There are 5 configurable exit slots (LX1-LX5 / SX1-SX5). Unlike entries, these operate on "OR" logic. If any enabled exit condition is met (e.g., RSI becomes overbought OR Price crosses below EMA), the position is closed immediately.
2. Hard Stop & Take Profit
Fixed %: Users can set a hard percentage-based Stop Loss and Take Profit.
Trailing Stop: A toggleable "Trailing?" feature allows the Stop Loss to dynamically trail the price.
Longs: The SL moves up as the price makes new highs.
Shorts: The SL moves down as the price makes new lows.
Automated Alerts & Webhooks
This script is built with automation in mind. It includes a dedicated makeJson() function that constructs a JSON payload compatible with most trading bots (e.g., 3Commas, TradersPost, Tealstreet).
Alert Modes Supported: | Alert Type | Description | | :--- | :--- | | Order Fills Only | Triggers standard TradingView strategy alerts when the broker emulator fills an order. | | Alert() Function | Triggers specific JSON payloads defined in the code ("action": "buy", "ticker": "MNQ", etc.). |
The script automatically calculates the alert quantity based on your equity percentage settings, ensuring the payload matches your backtest sizing.
Dashboard & Visuals
To aid in rapid analysis, the strategy includes visual tools directly on the chart:
Performance Table: A dashboard (top-right) displays real-time stats including Net Profit, Win Rate, Profit Factor, and Max Drawdown.
Trade Markers: Custom labels (goLong, exLong) show exactly where trades opened and closed, including the trade number and profit percentage.
SL/TP Visualization: Dynamic step-lines (Orange for SL, Lime for TP) show exactly where your protection levels are sitting, helping you visually verify if your stops are too tight or too loose.
Index Construction Tool🙏🏻 The most natural mathematical way to construct an index || portfolio, based on contraharmonic mean || contraharmonic weighting. If you currently traded assets do not satisfy you, why not make your own ones?
Contraharmonic mean is literally a weighted mean where each value is weighted by itself.
...
Now let me explain to you why contraharmonic weighting is really so fundamental in two ways: observation how the industry (prolly unknowably) converged to this method, and the real mathematical explanation why things are this way.
How it works in the industry.
In indexes like TVC:SPX or TVC:DJI the individual components (stocks) are weighted by market capitalization. This market cap is made of two components: number of shares outstanding and the actual price of the stock. While the number of shares holds the same over really long periods of time and changes rarely by corporate actions , the prices change all the time, so market cap is in fact almost purely based on prices itself. So when they weight index legs by market cap, it really means they weight it by stock prices. That’s the observation: even tho I never dem saying they do contraharmonic weighting, that’s what happens in reality.
Natural explanation
Now the main part: how the universe works. If you build a logical sequence of how information ‘gradually’ combines, you have this:
Suppose you have the one last datapoint of each of 4 different assets;
The next logical step is to combine these datapoints somehow in pairs. Pairs are created only as ratios , this reveals relationships between components, this is the only step where these fundamental operations are meaningful, they lose meaning with 3+ components. This way we will have 16 pairs: 4 of them would be 1s, 6 real ratios, and 6 more inverted ratios of these;
Then the next logical step is to combine all the pairs (not the initial single assets) all together. Naturally this is done via matrices, by constructing a 4x4 design matrix where each cell will be one of these 16 pairs. That matrix will have ones in the main diagonal (because these would be smth like ES/ES, NQ/NQ etc). Other cells will be actual ratios, like ES/NQ, RTY/YM etc;
Then the native way to compress and summarize all this structure is to do eigendecomposition . The only eigenvector that would be meaningful in this case is the principal eigenvector, and its loadings would be what we were hunting for. We can multiply each asset datapoint by corresponding loading, sum them up and have one single index value, what we were aiming for;
Now the main catch: turns out using these principal eigenvector loadings mathematically is Exactly the same as simply calculating contraharmonic weights of those 4 initial assets. We’re done here.
For the sceptics, no other way of constructing the design matrix other than with ratios would result in another type of a defined mean. Filling that design matrix with ratios Is the only way to obtain a meaningful defined mean, that would also work with negative numbers. I’m skipping a couple of details there tbh, but they don’t really matter (we don’t need log-space, and anyways the idea holds even then). But the core idea is this: only contraharmonic mean emerges there, no other mean ever does.
Finally, how to use the thing:
Good news we don't use contraharmonic mean itself because we need an internals of it: actual weights of components that make this contraharmonic mean, (so we can follow it with our position sizes). This actually allows us to also use these weights but not for addition, but for subtraction. So, the script has 2 modes (examples would follow):
Addition: the main one, allows you to make indexes, portfolios, baskets, groups, whatever you call it. The script will simply sum the weighted legs;
Subtraction: allows you to make spreads, residual spreads etc. Important: the script will subtract all the symbols From the first one. So if the first we have 3 symbols: YM, ES, RTY, the script will do YM - ES - RTY, weights would be applied to each.
At the top tight corner of the script you will see a lil table with symbols and corresponding weights you wanna trade: these are ‘already’ adjusted for point value of each leg, you don’t need to do anything, only scale them all together to meet your risk profile.
Symbols have to be added the way the default ones are added, one line : one symbol.
Pls explore the script’s Style setting:
You can pick a visualization method you like ! including overlays on the main chart pane !
Script also outputs inferred volume delta, inferred volume and inferred tick count calculated with the same method. You can use them in further calculations.
...
Examples of how you can use it
^^ Purple dotted line: overlay from ICT script, turned on in Style settings, the contraharmonic mean itself calculated from the same assets that are on the chart: CME_MINI:RTY1! , CME_MINI:ES1! , CME_MINI:NQ1! , CBOT_MINI:YM1!
^^ precious metals residual spread ( COMEX:GC1! COMEX:SI1! NYMEX:PL1! )
^^ CBOT:ZC1! vs CBOT:ZW1! grain spread
^^ BDI (Bid Dope Index), constructed from: NYSE:MO , NYSE:TPB , NYSE:DGX , NASDAQ:JAZZ , NYSE:IIPR , NASDAQ:CRON , OTC:CURLF , OTC:TCNNF
^^ NYMEX:CL1! & ICEEUR:BRN1! basket
^^ resulting index price, inferred volume delta, inferred volume and inferred tick count of CME_MINI:NQ1! vs CME_MINI:ES1! spread
...
Synthetic assets is the whole new Universe you can jump into and never look back, if this is your way
...
∞
Seasonality Scanner by thedatalayers.comThe Seasonality Scanner automatically detects seasonal patterns by scanning a user-defined number of past years (e.g., the last 10 years).
Based on this historical window, the indicator identifies the strongest seasonal tendency for the currently selected date range.
The scanner evaluates all valid seasonal windows using two filters:
• Hit Rate - the percentage of profitable years
• Average Return - the highest mean performance across the analyzed period
The best-scoring seasonal setup is displayed directly on the chart, including the exact start and end dates of the identified pattern for the chosen time range.
Users can define the period they want to analyze, and the indicator will automatically determine which seasonal window performed best over the selected history.
Recommended Settings (Standard Use)
For optimal and consistent results, the following settings are recommended:
• Search Window: 20-30
• Minimum Length: 5
• Time Period: from 2015 onward
• US Election Cycle: All Years
These settings provide a balanced and reliable baseline to detect meaningful seasonal tendencies across markets.
This indicator helps traders understand when recurring seasonal patterns typically occur and how they may align with ongoing market conditions.
This indicator is intended to be used exclusively on the daily timeframe, as all calculations are based on daily candles.
Using it on lower timeframes may result in inaccurate or misleading seasonal readings.
Seasonality Calculation Tool by thedatalayers.comThe Seasonality Calculation Tool is designed to analyze and evaluate the strength of any seasonal pattern detected by the Seasonality Indicator.
While the Seasonality Indicator displays the historical seasonal curve, this tool goes one step further by examining how reliable and consistent that curve truly is.
The tool checks whether a seasonal pattern is strong, distorted by a few outlier years, or statistically meaningful. It calculates the average return within the selected seasonal window and highlights how accurate or robust the pattern has been over the evaluated period.
To support manual confirmation and deeper analysis, the tool also visualizes the seasonal windows directly on the chart. This allows traders to review past occurrences and backtest the pattern themselves to validate the quality of the signal.
The Seasonality Calculation Tool is an ideal complement to the main Seasonality Indicator, helping traders identify high-quality, data-driven seasonal tendencies and avoid misleading or weak seasonal patterns.
This script is intended to be used exclusively on the daily timeframe, as all calculations rely on daily candle data.
The settings are intuitive and easy to adjust, allowing users to quickly evaluate any seasonal window displayed by the Seasonality Indicator.
Seasonality by thedatalayers.comThe Seasonality Indicator calculates the average historical performance of the currently selected asset by analyzing a user-defined number of past years (e.g., the last 10 years).
The number of years included in the calculation can be adjusted directly in the settings panel.
Based on this historical window, the indicator creates an average seasonal curve, which represents how the market typically behaved during each part of the year.
This averaged curve acts as a forecast for the upcoming months, highlighting periods where the market has shown a consistent tendency in the past.
Traders can use this seasonal projection to identify times of higher statistical likelihood for upward or downward movement.
The indicator works especially well when combined with the Seasonality Analysis Tool, which helps identify specific historical windows and strengthens overall seasonal decision-making.
This indicator must be used exclusively on the daily timeframe, as all calculations are based on daily candle data.
Other timeframes will not display accurate seasonal structures.
The Seasonality Indicator provides a clear, data-driven view of recurring annual patterns and allows traders to better understand when historical tendencies may influence future price action.
Vertical Time LinesVertical Time Lines is an indicator that draws vertical lines at specific times of each day on the price chart.
⚙️ Main Features
Up to 5 independent time lines
Precise hour and minute editing (HH:MM)
Individual enable/disable option per line
Customizable line color and style
Works on any asset and any timeframe
📝 Note
Due to Pine Script limitations, the lines are drawn using UTC time, not the time zone configured on the chart.
Lines are generated only when a candle exists exactly at the configured minute. If candles for the specified hours and minutes are not visible on the chart, the lines will not be displayed.
Z-Score & StatsThis is an advanced indicator that measures price deviation from its mean using statistical z-scores, combined with multiple analytical features for trading signals.
Core Functionality-
Z-Score Calculation Engine:
The indicator uses a custom standardization function that calculates how many standard deviations the current price is from its rolling mean. Unlike simple moving averages, this provides a normalized view of price extremes. The calculation maintains a sliding window of data points, efficiently updating mean and variance values as new data arrives while removing old data points. This approach handles missing values gracefully and uses sample variance (rather than population variance) for more accurate statistical measurements.
Statistical Zones & Visual Framework:
The indicator creates a visual representation of statistical probability zones:
±1 Standard Deviation: Encompasses about 68% of normal price behavior (green zone)
±2 Standard Deviations: Covers approximately 95% of price movements (orange zone)
±3 Standard Deviations: Represents 99.7% probability range (red zone)
±3.5 and ±4 Thresholds: Extreme outlier levels that trigger special alerts
The z-score line changes color dynamically based on which zone it occupies, making it easy to identify the current market extremity at a glance.
Advanced Features:
Volume Contraction Analysis
The script monitors volume patterns to identify periods of reduced trading activity. It compares current volume against a moving average and flags when volume drops below a specified threshold (default 70%). Volume contraction often precedes significant price moves and is factored into the optimal entry detection system.
Momentum-Based Direction Model:
Rather than just showing current z-score levels, the indicator projects where the z-score is likely to move based on recent momentum. It calculates the rate of change in the z-score and extrapolates forward for a specified number of bars. This creates a directional arrow that indicates whether conditions are bullish (negative z-score with upward momentum) or bearish (positive z-score with downward momentum).
Divergence Detection System:
The script automatically identifies four types of divergences between price action and z-score behavior :-
Regular Bullish Divergence: Price makes lower lows while z-score makes higher lows, suggesting weakening downward pressure
Regular Bearish Divergence: Price makes higher highs while z-score makes lower highs, indicating exhaustion in the uptrend
Hidden Bullish Divergence: Price makes higher lows while z-score makes lower lows, confirming trend continuation in an uptrend
Hidden Bearish Divergence: Price makes lower highs while z-score makes higher highs, confirming downtrend continuation
The system uses pivot detection with configurable lookback periods and distance requirements, then draws connecting lines and labels directly on the chart when divergences occur.
Yearly Statistics Tracking:
The indicator maintains historical records of maximum z-score deviations over yearly periods (configurable bar count). This provides context by showing whether current extremes are unusual compared to typical annual ranges. The average yearly maximum helps traders understand if the current market is exhibiting normal volatility or exceptional conditions.
Mean Reversion Probability:
Based on the current z-score magnitude, the indicator calculates and displays the statistical probability that price will revert toward the mean. Higher absolute z-scores indicate stronger mean reversion probabilities, ranging from 38% at ±0.5 standard deviations to 99.7% at ±3 standard deviations.
Comprehensive Statistics Table:
A customizable on-chart table displays real-time statistics including:
Current z-score value with directional indicator
Predicted z-score based on momentum
Current year's maximum absolute z-score
Historical average yearly maximum
Mean reversion probability percentage
Zone status classification (Normal, Moderate, High, Extreme)
Directional bias (Bullish, Bearish, Neutral)
Active divergence status
Volume contraction status with ratio
Optimal setup detection (combining extreme z-scores with volume contraction)
Optimal Entry Setup Detection:
The most sophisticated feature identifies high-probability trading setups by combining multiple factors. An "Optimal Long" signal triggers when z-score reaches -3.5 or below AND volume is contracted. An "Optimal Short" signal appears when z-score exceeds +3.5 AND volume is contracted. This combination suggests extreme price deviation occurring on low volume, often preceding strong reversals.
Alert System:
The script includes a unified alert mechanism that triggers when z-score crosses specific thresholds:
Crossing above/below ±3.5 standard deviations (extreme levels)
Crossing above/below ±4 standard deviations (critical levels)
Alerts fire once per bar with confirmation (previous bar must be on opposite side of threshold) to avoid false signals.
Practical Application:
This indicator is designed for mean reversion traders who seek statistically significant price extremes. The combination of z-score measurement, volume analysis, momentum projection, and divergence detection creates a multi-layered confirmation system. Traders can use extreme z-scores as potential reversal zones, while the direction model and divergence signals help time entries more precisely. The volume contraction filter adds an additional layer of confluence, identifying moments when reduced participation may precede explosive moves back toward the mean.
Chart Attached: NSE GMR Airports, EoD 12/12/25
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice.Happy Trading
Session Trader - Optimal Hours📊 Overview
Never miss the best trading hours again! This indicator provides a comprehensive, real-time session tracker that shows you EXACTLY when to trade crypto and when to stay out of the market. Automatically converts all times to your local timezone, highlights the current active session, and shows what's coming next.
Perfect for crypto traders who want to maximize profits by trading during high-liquidity, high-volume sessions while avoiding choppy, low-liquidity periods that lead to losses.
✨ Key Features
🎯 Real-Time Session Tracking
LIVE indicator shows which session is currently active with bright highlighting
NEXT UP feature highlights the upcoming session when between trading periods
Smart header displays current status at a glance
Real-time countdown timers for every session (opens/closes)
📍 6 Critical Trading Sessions Covered
✅ BEST TRADING SESSIONS (Green):
London Open (07:00-09:00 UTC) - High volatility kickoff, institutional orders
London-NY Overlap (13:30-15:30 UTC) - THE BEST period! Maximum liquidity & volume
NY Momentum (15:30-18:00 UTC) - Strong trending moves, continuation plays
❌ AVOID TRADING SESSIONS (Red):
4. Pre-Asia Quiet (21:00-00:00 UTC) - Low liquidity, erratic moves, wide spreads
5. Asia Lunch (03:30-05:00 UTC) - Choppy markets, whipsaws, unreliable patterns
6. Post-US Drift (20:00-21:00 UTC) - Market slows, unpredictable behavior
🌍 Automatic Timezone Conversion
Times display in YOUR chart timezone - no manual conversion needed!
Works in Berlin, New York, Tokyo, Sydney, or anywhere in the world
Switch between 12-hour and 24-hour formats
🎨 Visual Clarity
Active TRADE sessions = Bright green background, impossible to miss
Active AVOID sessions = Bright red background, clear warning
NEXT UP session = Orange highlight when between sessions
Inactive sessions = Faded gray, stays out of your way
Color-coded status column with clear ✓ TRADE or ✗ AVOID indicators
⚙️ Fully Customizable
9 table positions (top-left, top-right, bottom-center, etc.)
6 text sizes (tiny to huge) for any screen size
Toggle individual sessions on/off
Show/hide descriptions for cleaner view
Custom colors for each session type
Countdown timer toggle
🔔 Built-In Alerts
Automatic alerts when TRADE sessions start
Alerts when AVOID sessions begin (so you don't enter bad conditions)
Customizable per session
📖 How To Use
Basic Setup:
Add indicator to any crypto chart (BTC, ETH, etc.)
Times automatically convert to your chart's timezone
Watch the header - shows current session or next upcoming
Look for bright colors:
🟢 Bright green = TRADE NOW
🔴 Bright red = AVOID NOW
🟠 Orange = NEXT UP (coming soon)
Trading Strategy:
Focus on GREEN sessions (London Open, London-NY Overlap, NY Momentum)
Avoid RED sessions (Pre-Asia Quiet, Asia Lunch, Post-US Drift)
Prepare for ORANGE sessions (next up - get ready!)
Use countdown timers to plan entries/exits perfectly
Pro Tips:
London-NY Overlap is the BEST - highest volume, tightest spreads, cleanest trends
First 30 minutes of London can have quick reversals - use caution
NY Momentum is perfect for riding trends with trailing stops
NEVER trade during Asia Lunch - choppy, unpredictable, costs you money
Post-US Drift looks tempting but often leads to whipsaws
🔧 Indicator Settings
Display Options:
Table Position: Choose from 9 positions on your chart
Text Size: Auto, Tiny, Small, Normal, Large, Huge
Time Format: 12-hour (AM/PM) or 24-hour format
Show Countdown: Toggle real-time countdown timers
Show Description: Toggle detailed session descriptions
Highlight Next Session: Orange highlight for upcoming session
Session Toggles:
Enable/disable any of the 6 sessions individually:
London Open
London-NY Overlap
NY Momentum
Pre-Asia Quiet
Asia Lunch
Post-US Drift
Color Customization:
Active TRADE session color (default: bright green)
Active AVOID session color (default: bright red)
NEXT UP session color (default: orange)
Inactive session color (default: faded gray)
Alerts:
Individual alert toggles for each session
Alerts fire when sessions start (not every bar)
Includes context in alert message
📊 Session Details
🟢 London Open (07:00-09:00 UTC)
Status: TRADE ✓
Characteristics:
London opens with high volatility as European traders enter
Major institutional orders create significant price movements
Perfect for breakout and trend-following strategies
Watch for quick reversals in first 30 minutes
Good liquidity and volume
🟢 London-NY Overlap (13:30-15:30 UTC)
Status: TRADE ✓
THE BEST TRADING PERIOD!
Maximum liquidity as London & NY markets overlap
Institutional volume peaks, creating clean trends
Reliable technical setups, tightest spreads
Best execution quality
Focus on momentum and breakout trades
🟢 NY Momentum (15:30-18:00 UTC)
Status: TRADE ✓
Characteristics:
Strong directional moves as US market dominates
Trending behavior ideal for position trades
Continuation patterns highly reliable
Major news impact is highest during this period
Use trailing stops to ride trends effectively
🔴 Pre-Asia Quiet (21:00-00:00 UTC)
Status: AVOID ✗
WARNING:
Pre-Asian session with minimal liquidity
Thin order books cause erratic price action
Fake breakouts and stop-hunting common
Wide spreads increase trading costs
High risk, low reward - wait for better conditions
🔴 Asia Lunch (03:30-05:00 UTC)
Status: AVOID ✗
WARNING:
Asian lunch break creates choppy, directionless markets
Low volume leads to whipsaws and false signals
Market makers widen spreads significantly
Technical patterns unreliable
Not worth the risk - take a break!
🔴 Post-US Drift (20:00-21:00 UTC)
Status: AVOID ✗
WARNING:
Post-US session as major markets close
Liquidity dries up, causing unpredictable moves
High slippage risk
Market enters consolidation before Asian open
Better to wait for next quality session
🎯 Who Is This For?
Perfect for:
✅ Crypto day traders who want to maximize profits by timing the markets
✅ Scalpers who need high liquidity and tight spreads
✅ Swing traders who want to enter during optimal conditions
✅ Beginners who need clear guidance on when to trade
✅ Anyone tired of choppy sessions that eat away profits
Ideal Markets:
Bitcoin (BTC/USD, BTC/USDT)
Ethereum (ETH/USD, ETH/USDT)
Major altcoins (SOL, XRP, ADA, etc.)
Any 24/7 crypto market
💡 Why Session Timing Matters
Trading crypto during low-liquidity sessions is one of the biggest mistakes traders make:
❌ Trading during bad sessions causes:
Wider spreads (higher costs per trade)
Choppy, unpredictable price action
Fake breakouts and stop-hunting
Poor trade execution and slippage
Emotional frustration and overtrading
✅ Trading during optimal sessions gives you:
Tight spreads (lower costs)
Clean, trending price action
Reliable technical patterns
Better execution quality
Higher win rates and confidence
The difference between a profitable trader and a losing trader is often WHEN they trade, not HOW they trade.
🚀 Technical Details
Version: Pine Script v6
Type: Overlay indicator (table display)
Repainting: Non-repainting (all times are fixed to session schedules)
Updates: Real-time on every bar
Performance: Lightweight, no lag
Compatibility: Works on any timeframe (1m to 1D+)
📈 Best Practices
Plan your trading schedule around GREEN sessions
Set alerts for session starts so you never miss opportunities
Use the countdown to prepare entries/exits in advance
Combine with your strategy - this indicator tells you WHEN, your strategy tells you WHAT
Respect the RED sessions - discipline is profit
Keep descriptions ON when learning, turn OFF for cleaner charts later
🔄 Updates & Support
This indicator is actively maintained. Future updates may include:
Session volume statistics
Historical session performance tracking
Additional regional sessions
More customization options
Lot Size Panel Lite Multi (@JP7FX)Lot Size Panel Lite Multi is a fast, no-nonsense risk and position sizing tool built for active traders who need answers immediately.
This indicator removes all chart clutter and focuses on one thing only. Correct lot size based on your stop loss and risk.
It is designed for scalpers, day traders, and funded account traders who do not want complex menus or slow workflows.
What it does
Calculates precise lot size from stop loss and risk
Supports percentage risk or fixed cash risk
Works across Forex, Gold, Crypto, Index/CFD, and Stocks
Displays results in a clean on-chart panel
Supports multiple accounts at once
Key features
Risk first layout. Stop loss and risk inputs are at the top
Multi account support with A1 enabled by default
Per account currency handling with automatic FX conversion
Manual FX fallback option when TradingView rates are unavailable
Customisable panel colours and layout
Movable panel with multiple screen positions
How to use
Select your Asset Type
Enter your Stop Loss in pips
Choose Risk mode
Percent uses account balance
Cash risks a fixed amount
Set your account balance and currency
Read the calculated lot size instantly
Index and CFD users
For Index and Stock instruments, set the “value per pip per 1 lot” to match your broker.
Example:
If 1 lot equals $10 per point, enter 10
Who this is for
Traders who execute fast and want zero friction
Prop firm traders managing multiple accounts
Traders who want correct risk every trade without thinking
This is the Lite version of the JP7FX lot sizing tools.
It strips everything back to speed, clarity, and accuracy.
Trade smart.
JP7FX
RO H1 Signal CandleMarks specific H1 signal candles based on Bucharest (RO) time.
Designed for clean backtesting and time-based analysis.
Displays a small marker on selected hourly candles only.
