Hurst Cycle Channel Clone %BA %B of lazy bears Hurst Cycle Channel Clone
Remember to thank him for his great scripts.
With this you can easily see when the close is above,below or in the short or medium cycle channel.
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Tìm kiếm tập lệnh với "Cycle"
Adaptive Zero Lag EMA Strategy [Ehlers + Ric]Behold! A strategy that makes use of Ehlers research into the field of signal processing and wins so consistently, on multiple time frames AND on multiple currency pairs.
The Adaptive Zero Lag EMA (AZLEMA) is based on an informative report by Ehlers and Ric .
I've modified it by using Cosine IFM, a method by Ehlers on determining the dominant cycle period without using fast-Fourier transforms
Instead, we use some basic differential equations that are simplified to approximate the cycle period over a 100 bar sample size.
The settings for this strategy allow you to scalp or swing trade! High versatility!
Since this strategy is frequency based, you can run it on any timeframe (M1 is untested) and even have the option of using adaptive settings for a best-fit.
>Settings
Source : Choose the value for calculations (close, open, high + low / 2, etc...)
Period : Choose the dominant cycle for the ZLEMA (typically under 100)
Adaptive? : Allow the strategy to continuously update the Period for you (disables Period setting)
Gain Limit : Higher = faster response. Lower = smoother response. See for more information.
Threshold : Provides a bit more control over entering a trade. Lower = less selective. Higher = More selective. (range from 0 to 1)
SL Points : Stop Poss level in points (10 points = 1 pip)
TP Points : Take Profit level in points
Risk : Percent of current balance to risk on each trade (0.01 = 1%)
www.mesasoftware.com
www.jamesgoulding.com(Measuring%20Cycles).doc
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In-Phase & Quadrature IFMThis indicator provides a continuous measurement of a securities' dominant cycle period, based on Ehlers ever-impressive reports and analysis tools.
This method uses in-phase and quadrature analysis, making use of the imaginary domain. This method is prone to favor longer periods and can
allow noise to greatly affect the end result.
>What does that even mean?
Essentially, you get a real-time (low lag) plot of the cycle period in bars. If the I-Q IFM reads "16" then you can expect the distance between swing highs and swing lows to be approx. 16 bars.
>How is this useful?
When you throw an RSI or MACD on your chart, you can now set the "Period" or "Length" value with confidence.
Knowing the dominant cycle period tells you that price reversal will occur around these intervals.
>Extending.
The better way to use this tool is by extending the script into any indicators that use a length or period that is set manually.
Simply use the "len" variable in your custom script to replace your input values.
Now you have a way to adaptively set the period value, using signal processing theory instead of just intuition ;)
PM if you have questions.
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Cosine IFM [Ehlers]This indicator provides a continuous measurement of a securities' dominant cycle period, based on Ehlers ever-impressive reports and analysis tools.
>What does that even mean?
Essentially, you get a real-time (low lag) plot of the cycle period in bars. If the COS IFM reads "16" then you can expect the distance between swing highs and swing lows to be approx. 16 bars.
>How is this useful?
When you throw an RSI or MACD on your chart, you can now set the "Period" or "Length" value with confidence.
Knowing the dominant cycle period tells you that price reversal will occur around these intervals.
>Extending.
The better way to use this tool is by extending the script into any indicators that use a length or period that is set manually.
Simply use the "len" variable in your custom script to replace your input values.
Now you have a way to adaptively set the period value, using signal processing theory instead of just intuition ;)
PM if you have questions.
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PoW Floor OscillatorThis model was proposed by @paulewaulpaul as an attempt to model the cost of BTC production using Difficulty (input) and Issuance (output) as the key parameters. The following is paraphrased from the original research piece:
Difficulty D is taken as the estimated number of hashes required to mine a block (denoted in raw hashes). This is proportional to the energy consumption and the energy efficiency and reflects the demand. We use difficulty to estimate production costs. As mining becomes more efficient over time, hash rate becomes cheaper. Therefore we add a damping coefficient k and a scaling factor a (the cost per unit of adjusted difficulty). To get the value per coin, we divide by the issuance I. We get the values for a and k by fitting the function to price. For this we use the lows of the last two halving cycles, deep in the bear market when only the most efficient mining was profitable.
The PoW Floor Model is thus calculated as follows: PoW Floor Pricing Model = 2/3 * (sma(D,180)^0.41 / sum(I,180))
The damping coefficient is k = 0.41 and scaling factor a = 2/3. Statistically, this means that doubling the difficulty increases the estimated production cost by ~33%. We use a moving average for the difficulty and look at a 180 day period. For the upper bands we use the 1.41 and 2 multiples where the factor of 2 estimates the cost of production after the next halving event (assuming constant difficulty).
Coined By
kuntah in Bitcoin: Difficulty per Issuance - A PoW Pricing Model, Oct 2022
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PoW Floor Pricing ModelThis model was proposed by @paulewaulpaul as an attempt to model the cost of BTC production using Difficulty (input) and Issuance (output) as the key parameters. The following is paraphrased from the original research piece:
Difficulty D is taken as the estimated number of hashes required to mine a block (denoted in raw hashes). This is proportional to the energy consumption and the energy efficiency and reflects the demand. We use difficulty to estimate production costs. As mining becomes more efficient over time, hash rate becomes cheaper. Therefore we add a damping coefficient k and a scaling factor a (the cost per unit of adjusted difficulty). To get the value per coin, we divide by the issuance I. We get the values for a and k by fitting the function to price. For this we use the lows of the last two halving cycles, deep in the bear market when only the most efficient mining was profitable.
The PoW Floor Model is thus calculated as follows: PoW Floor Pricing Model = 2/3 * (sma(D,180)^0.41 / sum(I,180))
The damping coefficient is k = 0.41 and scaling factor a = 2/3. Statistically, this means that doubling the difficulty increases the estimated production cost by ~33%. We use a moving average for the difficulty and look at a 180 day period. For the upper bands we use the 1.41 and 2 multiples where the factor of 2 estimates the cost of production after the next halving event (assuming constant difficulty).
Coined By
kuntah in Bitcoin: Difficulty per Issuance - A PoW Pricing Model, Oct 2022
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Forex Visual Market ClockWhat it is
The Forex Visual Market Clock is a professional-grade session dashboard designed to help traders identify global liquidity cycles at a glance. Inspired by classic 24-hour market clocks, this indicator renders a persistent, high-contrast table on your chart that tracks market opens, closes, and the high-volume overlaps between the world's major financial hubs.
How it works
• Local Time Synchronization: The indicator translates global UTC market hours into your specific local timezone using IANA identifiers. This ensures that your "You Are Here" highlight (the white box) stays perfectly aligned with your actual wall clock.
• Automatic DST Management: The script natively handles Daylight Savings Time transitions for the selected local timezone, eliminating the need for manual GMT offset adjustments.
• Liquidity Visualization:
o Color-Coded Tracks: Each city is represented by a unique color-coded bar (Green for London, Orange for New York, Blue for Sydney, Yellow for Tokyo).
o Volume Peak Logic: A dedicated "VOLUME" row turns red during the London/New York overlap, signaling the period of highest historical volatility and liquidity.
• Engineered for Efficiency: Wrapped in barstate.islast logic, the script updates tick-by-tick without degrading chart performance, making it ideal for fast-paced M5 trading.
Inputs
• Local Timezone: A dropdown menu to select your region (e.g., America/Los_Angeles). This defines which hour the white "current time" box highlights.
• Display Corner: A layout setting to anchor the dashboard to any corner of your screen (Upper Left, Upper Right, Lower Left, or Lower Right).
• Visual Controls: Users can customize the opacity of the session bars and the thickness of the grey frame to suit their specific chart theme.
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Wx Gann WindowsWx Gann Windows — Seasonal Time Windows & Forward Markers
Wx Gann Windows highlights the handful of Gann-style seasonal dates that matter most, without cluttering your chart. It draws subtle “time windows” around key dates each year and optionally projects the next 12 months of dates into the future so you can keep them in mind when planning trades or options spreads.
What it shows
1. Seasonal Windows (background bands)
• Equinox / Solstice windows (Spring, Summer, Autumn, Winter).
• Optional midpoint (cross-quarter) windows: early Feb / May / Aug / Nov.
• Each window is a small number of days (default 3) centered on the approximate calendar date, with a soft background band so price action remains in focus.
2. On-Chart Labels (optional)
• Small labels like “Spring Eq.”, “Winter Sol.”, “Feb Mid” printed just above the current chart’s price range.
• One label per window, on the first bar of the window.
3. Future Projections (next 12 months)
• For each key date, the script projects the next occurrence into the future.
• Draws a vertical dotted line from near the chart low to above the chart high, plus a label such as “Spring Eq. (next)” or “Aug Mid (next)”.
• This gives you a 12-month “time roadmap” for cycles-sensitive planning (e.g., options, swing trades) without manual date marking.
Inputs
Window Settings
• Equinox / Solstice Window (days) – size of the seasonal bands (default 3 days).
• Midpoint Window (days) – size of the mid-Feb / May / Aug / Nov bands.
Visibility
• Show Equinox & Solstice Windows – toggle main seasonal bands on/off.
• Show Midpoint Windows (Feb/May/Aug/Nov) – toggle cross-quarter bands.
• Show Labels (on windows) – show/hide the on-chart labels above price.
Future Projections
• Project Next 12 Months (future markers) – toggle the forward vertical lines + “(next)” labels.
How to use it
• Treat these dates as awareness windows, not prediction signals.
• Use them to:
• Be extra alert for potential turns, accelerations, or exhaustion.
• Tighten risk or avoid opening new positions right into a window if your system suggests caution.
• Plan options expiries or swing entries with time structure in mind.
Always confirm decisions with your own system (trend, structure, volume, breadth, macro), not the dates alone.
Notes & Disclaimer
• Dates are approximate calendar anchors inspired by Gann’s seasonal and cross-quarter work, using simple ±N-day windows.
• Works on any symbol and timeframe; windows are based on calendar dates, not bar count.
• This tool is educational and informational only. It does not place orders and is not financial advice. Always test and integrate with your own strategy and risk management.
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NY Session Bar Counter & Bar painterThe NY Session Bar Counter is a high-visibility technical utility that provides an automated, sequential count of every candle during the New York session (09:30 to 16:00 EST). Unlike standard session highlighters, this tool numbers each bar starting from the market open, allowing traders to identify specific "time-of-day" windows with surgical precision.
This script is specifically engineered for traders who follow setups based on specific bar numbers (e.g., the Bar 17 reversal, the Bar 36 lunch-power-hour, or the final EOD flush).
🚀 Key Features
Precision Timing: Automatically resets every day at 09:30 AM New York time, regardless of your local timezone settings.
Multi-Timeframe Logic: Optimized to work seamlessly on 1m, 5m, 15m, and 30m charts without breaking the daily count.
Historical & Replay Compatibility: Unlike many session tools, this script is fully compatible with Bar Replay and displays historical data across several days (up to 500 labels).
Special Bar Highlighting: Includes a "Paint Bar" feature that allows you to choose a specific bar number (e.g., Bar 17) and automatically color the candle body for instant visual recognition.
Customizable Display: Filter for Odd/Even numbers to reduce chart clutter and adjust font size, color, and position (Above/Below bar).
💡 Why It Is Useful
In the modern trading environment, the market moves in cycles of liquidity and volatility that are often tied to specific times. This script is useful because:
Standardization: It provides a common language for traders. Instead of saying "the 10:50 AM candle," traders can refer to "Bar 17" (on a 5m chart), which is faster and more consistent.
Backtesting Accuracy: When reviewing past days or using Bar Replay, you can easily identify if your strategy triggers at the same relative time every day.
Visual Discipline: By highlighting a "Target Bar," you can train your eyes to wait for specific time windows before looking for a setup, helping to prevent overtrading during low-probability hours.
Operational Efficiency: It removes the manual work of counting bars from the open, allowing you to focus entirely on price action and order flow.
How to Use
Install the script on any intraday timeframe (best on 5m or 15m).
Adjust Lookback: Use the settings to determine how many historical days you want to view.
Identify Patterns: Use the "Special Bar Highlight" to mark the bar where your strategy most frequently triggers.
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Trend & Pullback Cycle How to use.
Trend Identification:
Green Columns: The cycle is above 50. Look for Longs.
Red Columns: The cycle is below 50. Look for Shorts.
Pullback Detection:
I added a Colour Change feature. If the Green bars turn Dark Green, it means momentum is fading (a pullback is happening). This is your signal to get ready to enter or add to a position once it turns Bright Green again.
The Yellow Line:
This is your trigger. In the screenshot, you see the bars cross the yellow line.
Entry Signal: When the Histogram crosses above the Yellow line (while generally green) or crosses below it (while generally red).
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NIFTY, SENSEX AND BANKNIFTY Options Expiry MarkerNSE Options Expiry Background Marker
Category: Date/Time Indicators
Timeframe: Daily
Markets: NSE (India) / Any Exchange
Description
Automatically highlights weekly and monthly options expiry days for NIFTY, BANKNIFTY, and SENSEX using color-coded background shading. Works across entire chart history with customizable transparency levels.
Key Features
✅ Background Highlighting - Non-intrusive color shading on expiry days
✅ Multi-Index Support - NIFTY, BANKNIFTY, and SENSEX simultaneously
✅ Weekly & Monthly Expiry - Different transparency levels for easy distinction
✅ Customizable Expiry Days - Set any weekday (Mon-Fri) as expiry day
✅ Adjustable Transparency - Separate controls for weekly and monthly expiries
✅ Full Historical Data - Works on all visible bars across years
✅ Smart Monthly Detection - Automatically identifies last occurrence in month
✅ Color Coded - Blue (NIFTY), Red (BANKNIFTY), Green (SENSEX)
Use Cases
Options trading strategy planning
Identify expiry day volatility patterns
Visual reference for monthly vs weekly cycles
Backtest strategies around expiry days
Track multiple index expiries on single chart
Technical Details
Uses India timezone (GMT+5:30) for accurate date calculations
Handles leap years automatically
Smart algorithm identifies last weekday occurrence per month
Works seamlessly on any chart timeframe (optimized for Daily)
No performance impact - simple background coloring
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Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve.
Mechanism (What It Measures)
The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding:
\text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)}
1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money).
2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure).
3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity.
How to Interpret Signals
Treat the Net Liquidity line as the market's "Fuel Gauge":
📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets.
📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action.
⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent.
Important Notes
Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping.
Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
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DRACO Tomas Delta (Custom/Monthly)🐉 DRACO Delta SessionBox (Custom / Monthly)
Overview
The DRACO Delta SessionBox is an advanced visual and analytical tool designed to measure and display cumulative buying and selling pressure (Δ — delta) within a user-defined time window, such as a specific custom date range, a recurring monthly period, or the entire current month.
It visually represents market accumulation or distribution phases by calculating an approximate delta — the imbalance between bullish and bearish volume — and then aggregates it inside a dynamic “box” that spans only the selected time window.
Core Concept
Delta in this context is an approximation of the real order-flow delta (buy vs sell volume difference).
Since TradingView doesn’t provide raw tick-by-tick trade direction data, this indicator uses a proxy formula based on OHLC and volume data:
Δ per bar
=
Volume
×
(
Close
−
Open
)
max
(
High
−
Low
,
Tick Size
)
Δ per bar=Volume×
max(High−Low,Tick Size)
(Close−Open)
This gives a very effective approximation of intrabar directional pressure — whether volume was dominated by buyers (Δ > 0) or sellers (Δ < 0).
Modes
The indicator can operate in three distinct modes:
🕒 Custom DateTime
The user manually sets an exact date & time range (From – To).
The box only measures delta and volume accumulation within this window.
Ideal for analyzing specific events, like FOMC weeks, quarterly earnings, or macro periods.
📆 Monthly Window
The user selects start and end days of the month (e.g. 5–20).
The same window repeats automatically every month.
Useful for identifying recurring accumulation or distribution cycles within months.
🧭 Whole Month
Automatically measures and visualizes delta for the entire current calendar month.
The box resets when a new month begins.
Provides a macro-level view of monthly directional bias.
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Indian Gold Festival Dates HistoricalIndian Gold Festival Dates (1975-2025)
Marks 8 major Indian festivals associated with gold buying over 50 years of historical data. Essential for analyzing seasonal patterns and cultural demand cycles in gold markets.
Festivals Included:
Dhanteras (Gold) - Most auspicious gold buying day
Diwali (Orange) - Festival of Lights
Akshaya Tritiya (Green) - "Never-ending" prosperity
Dussehra (Red) - Victory and success
Makar Sankranti (Cyan) - Solar new year
Gudi Padwa (Magenta) - Hindu New Year (Maharashtra)
Ugadi (Purple) - Hindu New Year (South India)
Navratri (Yellow) - 9-day festival
Features:
✓ 408 exact historical dates (1975-2025)
✓ Color-coded vertical lines for easy identification
✓ Toggle individual festivals on/off
✓ Adjustable line width and labels
✓ Works on all timeframes (best on daily/weekly)
Perfect for traders analyzing gold seasonality, Indian market sentiment, and cultural demand patterns. Use on XAUUSD, GC1!, or Indian gold futures.
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US30 Quarter Levels (125-point grid) by FxMogul🟦 US30 Quarter Levels — Trade the Index Like the Banks
Discover the Dow’s hidden rhythm.
This indicator reveals the institutional quarter levels that govern US30 — spaced every 125 points, e.g. 45125, 45250, 45375, 45500, 45625, 45750, 45875, 46000, and so on.
These are the liquidity magnets and reaction zones where smart money executes — now visualized directly on your chart.
💼 Why You Need It
See institutional precision: The Dow respects 125-point cycles — this tool exposes them.
Catch reversals before retail sees them: Every impulse and retracement begins at one of these zones.
Build confluence instantly: Perfectly aligns with your FVGs, OBs, and session highs/lows.
Trade like a professional: Turn chaos into structure, and randomness into rhythm.
⚙️ Key Features
Automatically plots US30 quarter levels (…125 / …250 / …375 / …500 / …625 / …750 / …875 / …000).
Color-coded hierarchy:
🟨 xx000 / xx500 → major institutional levels
⚪ xx250 / xx750 → medium-impact levels
⚫ xx125 / xx375 / xx625 / xx875 → intraday liquidity pockets
Customizable window size, label spacing, and line extensions.
Works across all timeframes — from 1-minute scalps to 4-hour macro swings.
Optimized for clean visualization with no clutter.
🎯 How to Use It
Identify liquidity sweeps: Smart money hunts stops at these quarter zones.
Align structure: Combine with session opens, order blocks, or FVGs.
Set precision entries & exits: Trade reaction-to-reaction with tight risk.
Plan daily bias: Watch how New York respects these 125-point increments.
🧭 Designed For
Scalpers, day traders, and swing traders who understand that US30 doesn’t move randomly — it moves rhythmically.
Perfect for traders using ICT, SMC, or liquidity-based frameworks.
⚡ Creator’s Note
“Every 125 points, the Dow breathes. Every 1000, it shifts direction.
Once you see the rhythm, you’ll never unsee it.”
— FxMogul
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MTF FVG Confluence v6 — JSON Alerts via alert()This strategy combines multi-timeframe confluence with candlestick analysis and fair value gaps (FVGs) to generate structured long/short entries. It aligns Daily and 4H EMA trends with 1H MACD momentum, then confirms with engulfing candles and FVG zones for precision entries. Risk management is built-in, featuring stop-loss, 3R take-profit targets, and optional break-even logic, with dynamic JSON alerts for webhook automation.
Categories:
Candlestick analysis
Chart patterns
Cycles
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PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
"\nDate: " + date_str + " " + time_str +
"\nTrade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
"\nRank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
"\nPercentile: " + str.tostring(percentile, "#.#") + "%" +
"\nMagnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
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Improved Weinstein Stage AnalysisThe code provides an actionable, disciplined, and visually informative implementation of the “Stage Analysis” approach pioneered by Stan Weinstein, with enhancements to modernize, automate, and clarify the methodology for today’s traders using TradingView. It faithfully follows the workflow recommended: identify long-term cycles, confirm with volume and relative strength, and only engage aggressively with the market during the advancing (bullish) stage with all “clues” aligned.
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Alternate Hourly HighlightAlternate Hourly Highlight
This indicator automatically highlights every alternate one-hour window on your chart, making it easy to visually identify and separate each trading hour. The background alternates color every hour, helping traders spot hourly cycles, session changes, or develop time-based trading strategies.
Works on any timeframe.
No inputs required—just add to your chart and go!
Especially useful for intraday traders who analyze price action, volatility, or volume by the hour.
For custom colors or session windows, feel free to modify the script!
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Setup Score OscillatorSetup Score Oscillator – Full Description
🎯 Purpose of the Script
This script is a manual trading setup scoring tool, designed to help traders quantify the quality of a trade setup by combining multiple technical, cyclical, and contextual signals.
Instead of relying on a single indicator, the trader manually selects which signals are present, and the script calculates a total score (0–100%), displayed as an oscillator in a separate panel (like RSI or MACD).
🔧 How it works in practice
1. Manual signal inputs
The script presents a set of checkboxes in the settings, where the trader can enable/disable the following signals:
✅ Confirmed Support/Resistance
✅ Aligned Volume Profile
✅ Favorable Cyclic Timing
✅ Valid Trend Line
✅ Aligned Cyclical Moving Averages
✅ Relevant Fibonacci Level
✅ Classic Volume Signal (spike, dry-up, etc.)
✅ Oscillator confirmation (e.g., divergences)
✅ Extreme Sentiment
✅ Relevant or incoming News
Each selected signal contributes to the total score based on its weight.
2. Scoring system
Each signal has a default weight (e.g., 20% for support/resistance, 15% for cycles, etc.).
Optionally, the trader can enable the “custom weights” checkbox and adjust each signal’s weight directly in the settings.
3. Score visualization
The final score (sum of all active weights) is plotted as an oscillator ranging from 0 to 100%, with dynamic coloring:
Range Color Meaning
0–39% Red No valid setup
40–54% Yellow Watchlist only
55–69% Orange Good setup
70–100% Green Strong setup
Several horizontal threshold lines are displayed:
50% → neutral threshold
40%, 55%, 70% → operational levels
4. Optional background coloring
When the score exceeds 55% or 70%, the oscillator background lightly changes color to highlight stronger setups (non-intrusive).
📌 Practical benefits
Objectifies subjective analysis: each decision becomes a number.
Prevents overtrading: no entries if the score is too low.
Adaptable to any trading style: swing, intraday, positional.
User-friendly: no coding needed – just tick boxes.
Italiano:
Setup Score Oscillator – Descrizione completa
🎯 Obiettivo dello script
Lo script è uno strumento manuale di valutazione dei setup di trading, pensato per aiutare il trader a quantificare la qualità di un'opportunità operativa basandosi su più segnali tecnici, ciclici e contestuali.
Invece di affidarsi a un solo indicatore, il trader seleziona manualmente quali segnali sono presenti, e lo script calcola un punteggio complessivo percentuale (0–100%), rappresentato come oscillatore in una finestra separata (tipo RSI, MACD, ecc.).
🔧 Come funziona operativamente
1. Input manuale dei segnali
Lo script mostra una serie di checkbox nelle impostazioni, dove il trader può attivare o disattivare i seguenti segnali:
✅ Supporto/Resistenza confermata
✅ Volume Profile allineato
✅ Cicli o timing favorevole
✅ Trend line valida
✅ Medie mobili cicliche allineate
✅ Livello di Fibonacci rilevante
✅ Volume classico significativo (spike, dry-up)
✅ Conferme da oscillatori (es. divergenze)
✅ Sentiment estremo (es. euforia o panico)
✅ News importanti imminenti o appena uscite
Ogni casella attiva contribuisce al punteggio totale, con un peso specifico.
2. Sistema di punteggio
Ogni segnale ha un peso predefinito (es. 20% per supporti/resistenze, 15% per cicli, ecc.).
Facoltativamente, il trader può attivare la funzione “Enable custom weights” per personalizzare i pesi di ciascun segnale direttamente da input.
3. Visualizzazione del punteggio
Il punteggio complessivo (somma dei pesi attivati) viene tracciato come oscillatore da 0 a 100%, con colori dinamici:
Range Colore Significato
0–39% Rosso Nessun setup valido
40–54% Giallo Osservazione
55–69% Arancione Setup buono
70–1005 Verde Setup forte
Sono tracciate anche delle linee guida orizzontali a:
50% → soglia neutra
40%, 55%, 70% → soglie operative
4. Colorazione dello sfondo (facoltativa)
Quando il punteggio supera 55% o 70%, lo sfondo dell’oscillatore cambia leggermente colore per evidenziare il segnale (non invasivo).
📌 Vantaggi pratici
Oggettivizza l’analisi soggettiva: ogni decisione manuale si trasforma in un numero.
Evita overtrading: se il punteggio è troppo basso, non si entra.
Adattabile a ogni stile: swing, intraday, position.
Facile da usare anche senza codice: basta spuntare le caselle.
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S&P 500 Estimated PE (Sampled Every 4)📊 **S&P 500 Estimated PE Ratio (from CSV)**
This indicator visualizes the forward-looking estimated PE ratio of the S&P 500 index, imported from external CSV data.
🔹 **Features:**
- Real historical daily data from 2008 onward
- Automatically aligns PE values to closest available trading date
- Useful for macro valuation trends and long-term entry signals
📌 **Best for:**
- Investors interested in forward-looking valuation
- Analysts tracking over/undervaluation trends
- Long-term timing overlay on price action
Category: `Breadth indicators`, `Cycles`
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Bollinger Volatility AnalyzerThe Bollinger Volatility Analyzer (BVA) is a powerful enhancement of the traditional Bollinger Bands indicator, tailored to help traders identify volatility cycles and catch potential breakouts with better precision and timing. It builds upon the foundational concept of Bollinger Bands—using a moving average and standard deviation bands—but adds crucial insights into market contraction and expansion, which can be instrumental in timing entries and exits.
Here's how it works and why it's useful
At its core, the indicator calculates a moving average (called the "basis") and plots two bands—one above and one below—based on a multiple of standard deviation. These bands expand during volatile periods and contract during quiet ones. The width between these bands, normalized as a percentage of the basis, gives us a sense of how compressed or expanded the market currently is. When the band width drops below a user-defined threshold (like 2%), the script highlights this with an orange triangle below the bar. This is the "squeeze" condition, signaling a potential buildup of market energy—a kind of calm before the storm.
What makes this version of Bollinger Bands particularly powerful is that it not only detects squeezes, but also tells you when price breaks out of that squeeze range. If price closes above the upper band after a squeeze, a green "Breakout ↑" label is shown; if it closes below the lower band, a red "Breakout ↓" appears. These breakout labels act as entry signals, suggesting that volatility is returning and a directional move has begun.
This indicator is especially useful in markets that tend to alternate between consolidation and breakout phases, such as forex, crypto, and even individual stocks. Traders who look for early signs of momentum—whether for swing trading, scalping, or position building—can benefit from this tool. During a quiet market phase, the indicator warns you that a move might be coming; when the move starts, it tells you the direction.
In fast-moving markets, BVA helps filter out noise by focusing only on high-probability conditions: quiet consolidation followed by a strong breakout. It’s not a complete system by itself—it works best when paired with volume confirmation or oscillators like RSI—but as a volatility trigger and directional guide, it’s a reliable component of a trading workflow.
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Mercury Venus Conjunction Sextiles 2019-2026How to Use It and What It Means Astrologically
How to Use the Script in TradingView
This Pine Script, called "Mercury Venus Aspects 2019–2026," is made to highlight the dates of Mercury-Venus conjunctions (0°) and sextiles (60°) from 2019 to 2026 on TradingView charts. Here's how to use it:
click “Add to Chart.” It will apply to any chart you have open—stocks, forex, crypto, etc.
Customize the Display
You can turn on/off the visibility of conjunctions and sextiles using checkboxes under "Inputs" in the settings.
You can also adjust the label size (small, normal, large, or huge) for better readability on your chart.
What You’ll See on the Chart
Conjunctions appear as blue shaded zones with labels like “C1,” “C2,” etc. These mark dates when Mercury and Venus are at the same degree.
Sextiles show up in orange with labels like “S1,” “S2,” marking when they’re about 60° apart.
Each event spans a 2-day window (one day before and after the exact aspect).
How to Use It Practically
You can overlay the script on market charts to look for any patterns between these planetary aspects and price movements.
You can also use it to plan personal or financial activities, since these aspects often affect communication, money, and relationships.
What to Keep in Mind
Dates are approximate and based on average planetary cycles (Mercury: ~88 days, Venus: ~225 days). For exact timing, use an ephemeris.
Only conjunctions and sextiles are shown. Oppositions, squares, and trines aren’t included because Mercury and Venus never get far enough apart (more than 75°).
This script is great for astrologers, traders, and enthusiasts who want to see Mercury-Venus aspects directly on their charts and explore their possible effects.
Astrological Meaning of Mercury-Venus Aspects
What Mercury and Venus Represent
Mercury rules communication, thinking, technology, travel, and trade. In global events (mundane astrology), it affects media, markets, and movement of information.
Venus is about love, beauty, money, and pleasure. It influences relationships, aesthetics, and finance. In the world stage, it’s linked to luxury, art, fashion, and economic balance.
When Mercury and Venus form aspects (like conjunctions or sextiles), their energies mix in helpful ways that can affect people and events.
Conjunction (0°) – Mercury and Venus Together
These two planets are in the same sign and degree, so their qualities merge.
For people:
Positive: Smooth communication, charm, creativity, and better relationships. Great for romance, art, and social interaction.
Negative: Too much focus on appearances, sweet talk, or pleasure can cloud judgment. Decisions may lack depth.
For the economy:
Positive: Boosts in media, entertainment, fashion, and tech. Good for trade, deals, and optimism in financial markets.
Negative: Risk of overspending or unrealistic expectations. May cause small market bubbles or misleading hype.
Sextile (60°) – Mercury and Venus in Harmony
These two planets are two signs apart, creating a smooth, supportive energy.
For people:
Positive: Easy conversations, creative teamwork, small financial wins, and pleasant social experiences.
Negative: Energy is mild, so opportunities might be missed if not acted on. People may avoid hard decisions.
For the economy:
Positive: Gradual improvements in areas like marketing, social media, hospitality, and design. Good for diplomacy.
Negative: Lack of strong initiative could limit bigger gains. Minor missteps are possible due to a laid-back attitude.
General Effects
These aspects are mostly beneficial. They support creativity, financial thinking, and social harmony.
Downsides: Conjunctions may lead to overindulgence or shallow choices, while sextiles may cause missed chances due to low energy.
These aspects rarely cause major economic shifts on their own but can amplify trends depending on other planetary influences (like Saturn or Uranus).
Zodiac Sign Influence
Fire signs (Aries, Leo, Sagittarius): Bold communication, energetic spending, gains in media or entertainment.
Earth signs (Taurus, Virgo, Capricorn): Practical results, stable finances, growth in real-world assets like property or food.
Air signs (Gemini, Libra, Aquarius): Intellectual growth, tech innovation, and social ideas flourish.
Water signs (Cancer, Scorpio, Pisces): Emotional depth in conversations, artistic growth, and financial sensitivity.
Mercury-Venus aspects are gentle but helpful. They combine logic (Mercury) with emotion and value (Venus). They’re good times for love, communication, and money—but their benefits depend on how we use the energy. This script lets you easily track these moments on a chart and explore how they might align with real-life trends or decisions.
Disclaimer: This script and its interpretations are for informational and educational purposes only. They do not constitute financial, trading, or professional astrological advice. Always conduct your own research and consult qualified professionals before making any financial or personal decisions. Use at your own discretion.
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