Mitigation Blocks — Lite (ICT) + Stats + Entry75Mitigation Blocks — Lite (ICT) + Stats + Entry75
What it does
This indicator finds recent Mitigation Blocks (ICT-style) and draws a single active bullish and bearish block on the chart.
It also plots the 75% entry level for each active block and shows a compact performance HUD (“Отработано / Worked”) so you can quickly judge how well blocks have been reacting on the current symbol and timeframe.
Logic (brief)
Structure impulse
A new block is created when price breaks the last swing (pivot-based) with an optional ATR body filter.
After an upswing break → search the most recent bearish candle within a lookback window → its body defines the bullish block (top/bottom = max/min of that candle’s open/close).
After a downswing break → search the most recent bullish candle → defines the bearish block.
Touch & mitigation
First time price touches a block, the block is marked mitigated (border becomes dashed).
Entry line for that block is removed (no history clutter to the left).
75% entry levels
Long (bullish block): entry = top − 0.75 × (top − bottom) (deeper inside from the top).
Short (bearish block): entry = bottom + 0.75 × (top − bottom) (deeper inside from the bottom).
Lines are drawn only to the right (history on the left is hidden).
Stats (HUD)
The HUD shows Worked% per side: percentage of first touches that reached a simple target in the check window.
Current version uses a conservative proxy: success if, within the next bars, price moved away from the block by at least ~1×ATR (internally calculated) without first invalidating the block’s opposite boundary.
Values are accumulated while the script runs on the loaded chart range.
Inputs
Structure
Swing length (pivot) — pivot size to detect last swing.
Require minimum impulse / Min body × ATR / ATR length — filter for strong displacement bars.
Search last opposite candle (bars back) — lookback to find the candle that defines the block.
Style
Fill & border colors for bullish/bearish blocks.
Mitigated border color (dashed on first touch).
Entry 75% lines
Show 75% entry lines (on/off)
Colors and line width.
Autoscale
Optional hidden anchor plots for better autoscaling.
On-chart elements
Active bullish/bearish block (rectangle, extended right).
Dashed border once the block is mitigated (first touch).
75% entry line for each non-mitigated block (drawn only to the right; removed on mitigation).
HUD (top-right):
LONG | Worked: XX.X% |
SHORT | Worked: XX.X% |
If there is no active (non-mitigated) block on a side, the entry cell shows “ожидаем” (“waiting”).
How to read it
Trade from block to block: use the 75% line as a reference entry inside the zone; stops are commonly placed beyond the opposite side of the block.
Worked% helps compare symbols/timeframes: higher with a decent sample typically means more reliable reactions.
The indicator shows only the latest valid block per side to keep the chart clean.
Notes & tips
This is a discretionary tool intended to support ICT-style execution; it is not a strategy and does not place trades.
Try different timeframes. Many users prefer M5–H1 for entries and H4–D1 for context.
You can turn off entry lines if you only want the zones.
Because stats are computed on the visible history while the script runs, switching symbols/TFs will reset the counters.
Inputs (defaults)
Pivot length: 5
ATR length: 14
Min body × ATR: 1.0 (enable/disable filter)
Opposite candle lookback: 5
Entry 75% lines: ON
Forecasting
Position Size CalculatorPosition Size CalculatorRisk Management Made Simple – Size Your Trades Like a Pro!Tired of guessing position sizes and blowing up your account on oversized trades? This Pine Script indicator automates position sizing based on your risk tolerance, ensuring every trade risks only what you've predefined. Perfect for stocks, forex, crypto, or futures—works for long or short setups. Overlay it on your candlestick chart and watch the math do the work.Key Features:Smart Risk Control: Input your account size (e.g., $70k) and risk % (e.g., 1%). It caps your max loss per trade automatically.
Dynamic Entry & Stop: Use live chart close as entry, or click to set a manual entry level (green solid line). For stops, toggle manual placement (red broken line) or use a % distance—auto-calculates the effective % for precision.
Visual Markers: Green line for entry price, red dashed line for stop loss—spans your chart for easy spotting.
Customizable Table: Floating info panel shows Account Size, Risk Amount, Stop Distance %, and Position Size (shares/lots). Drag its position via settings (top-right default).
No More Guesswork: Formula: Position Size = (Account × Risk %) ÷ Stop Distance. Handles edge cases like tiny distances to avoid div-by-zero.
How to Use:Add to your chart via Pine Editor.
In settings: Set account size/risk %. Toggle "Use Manual Entry Price" and click chart to place green line. Do the same for stop (red line) or use % input.
Table updates live—grab the position size and execute!
Pro Tip: For shorts/longs, the abs distance keeps risk symmetric. Test on demo first.
Built for v6—clean, lightweight, and 100% customizable. Share your tweaks in comments! Remember, this is a tool, not advice—trade responsibly. (Inspired by classic Kelly Criterion vibes, but simplified for daily grinders.)
ATR Horizontal Lines from EMA and SMA with TableHow it works:
The script calculates ATR levels (of your choosing)
Instead of plotting curves, it creates horizontal lines
The lines are deleted and recreated on each bar to show current levels
Lines extend to the right or can be limited to a certain width
Customization options:
Line width (1-10 pixels)
Individual colors for each of the 4 lines
All the original parameters (EMA/SMA lengths, ATR length, multipliers)
The horizontal lines will now show the current ATR-based support/resistance levels and move dynamically as the EMAs, SMA, and ATR values change with new price data.
3/4-Bar GRG / RGR Pattern (Conditional 4th Candle)This indicator can be used to identify the Green-Red-Green or Red-Green-Red pattern.
It is a price action indicator where a price action which identifies the defeat of buyers and sellers.
If the buyers comprehensively defeat the sellers then the price moves up and if the sellers defeat the buyers then the price moves down.
In my trading experience this is what defines the price movement.
It is a 3 or 4 candle pattern, beyond that i.e, 5 or more candles could mean a very sideways market and unnecessary signal generation.
How does it work?
Upside/Green signal
Say candle 1 is Green, which means buyers stepped in, then candle 2 is Red or a Doji, that means sellers brought the price down. Then if candle 3 is forming to be Green and breaks the closing of the 1st candle and opening of the 2nd candle, then a green arrow will appear and that is the place where you want to take your trade.
Here the buyers defeated the sellers.
Sometimes candle 3 falls short but candle 4 breaks candle 1's closing and candle 2's opening price. We can enter on candle 4.
Important - We need to enter the trade as soon as the price moves above the candle 1 and 2's body and should not wait for the 3rd or 4th candle to close. Ignore wicks.
I have restricted it to 4 candles and that is all that is needed. More than that is a longer sideways market.
I call it the +-+ or GRG pattern.
Stop loss can be candle 2's mid for safe traders (that includes me) or candle 2's body low for risky traders.
Back testing suggests that body low will be useless and result in more points in loss because for the bigger move this point will not be touched, so why not get out faster.
Downside/Red signal
Say candle 1 is Red, which means sellers stepped in, then candle 2 is Green or a Doji, that means buyers took the price up. Then if candle 3 is forming to be Red and breaks the closing of the 1st candle and opening of the 2nd candle then a Red arrow will appear and that is the place where you want to take your trade.
Sometimes candle 3 falls short but candle 4 breaks candle 1's closing and candle 2's opening price. We can enter on candle 4.
We need to enter the trade as soon as the price moves below the candle 1 and 2's body and should not wait for the 3rd or 4th candle to close.
I have restricted it to 4 candles and that is all that is needed. More than that is a longer sideways market.
I call it the -+- or RGR pattern.
Stop loss can be candle 2's mid for safe traders ( that includes me) or candle 2's body high for risky traders.
Back testing suggests that body high will be useless and result in more points in loss because for the bigger move this point will not be touched, so why not get out faster.
Important Settings
You can enable or disable the 4th candle signal to avoid the noise, but at times I have noticed that the 4th candle gives a very strong signal or I can say that the strong signal falls on the 4th candle. This is mostly a coincidence.
You can also configure how many previous bars should the signal be generated for. 10 to 30 is good enough. To backtest increase it to 2000 or 5000 for example.
Rest are self explanatory.
Pointers
If after taking the trade, the next candle moves in your direction and closes strong bullish or bearish, then move SL to break even and after that you can trail it.
If a upside trade hits SL and immediately a down side trade signal is generated on the next candle then take it. Vice versa is true.
Trades need to be taken on previous 2 candle's body high or low combined and not the wicks.
The most losses a trader takes is on a sideways day and because in our strategy the stop loss is so small that even on a sideways day we'll get out with a little profit or worst break even.
Hold targets for longer targets and don't panic.
If last 3-4 days have been sideways then there is a good probability that day will be trending so we can hold our trade for longer targets. Target to hold the trade for whole day and not exit till the day closes.
In general avoid trading in the middle of the day for index and stocks. Divide the day into 3 parts and avoid the middle.
Use Support/Resistance, 10, 20, 50, 200 EMA/SMA, Gaps, Whole/Round numbers(very imp) for identifying targets.
Trail your SL.
For indexes I would use 5 min and 15 min timeframe.
For commodities and crypto we can use higher timeframe as well. Look for signals during volatile time durations and avoid trading the whole day. Signal usually gives good targets on those times.
If a GRG or RGR pattern appears on a daily timeframe then this is our time to go big.
Minimum Risk to Reward should be 1:2 and for longer targets can be 1:4 to 1:10.
Trade with small lot size. Money management will happen automatically.
With small lot size and correct Risk-Re ward we can be very profitable. Don't trade with big lot size.
Stay in the market for longer and collect points not money.
Very imp - Watch market and learn to generate a market view.
Very imp - Only 4 candles are needed in trading - strong bullish, strong bearish, hammer, inverse hammer and doji.
Go big on bearish days for option traders. Puts are better bought and Calls are better sold.
Cluster of green signals can lead to bigger move on the upside and vice versa for red signals.
Most of this is what I learned from successful traders (from the top 2%) only the indicator is mine.
ATT Numbers Header (Movable)For anybody that trades with ATT (Advanced Time Technique) And can't remember the numbers and want's to have them on their chart at all time with full customizability as well this indicator is for you.
my_strategy_2.0Overview:
This is a high-speed scalping strategy optimized for volatile crypto assets (BTC, ETH, etc.) on timeframes 1m–5m. It combines trend-following SuperTrend with confirmations from MACD, RSI, Bollinger Bands, and volume spikes for precise entries. Focus on quick profits (1–3 ATR) with strict risk control: partial take-profits, stop-loss, and trailing breakeven after the first TP.
Key Signals:
Long: SuperTrend flip up + MACD crossover up + RSI >50 + BB Upper breakout + volume spike + volatility filter (ATR >0.5%).
Short: Similar but downward.
Exits and Risks:
TP: 33% at +1 ATR, 33% at +2 ATR, 34% at +3 ATR (customizable).
SL: Initial at -1 ATR, after TP1 — to breakeven with trailing on BB midline (optional).
Filters: Minimum ATR to avoid flat markets; realistic commissions in backtests.
Recommendations:
Test on 2020–2025 data (out-of-sample 2024+). Expected Win Rate ~55%, Profit Factor >1.8, Drawdown <10%. Ideal for 1–2% risk per trade. Not for beginners — use paper trading.
Disclaimer: Past results do not guarantee future performance. Trade at your own risk.
(Pine v6 code, ready for publication. Author: gopog777 with expert fixes.)
Mitigation Blocks — Lite (ICT) + Arrows + Stats📌 Mitigation Blocks — Lite (ICT-Based) + Arrows
This indicator detects mitigation blocks based on price structure shifts, inspired by ICT (Inner Circle Trader) concepts. It works by identifying strong impulses and highlighting the last opposite candle, forming a mitigation block zone for potential reversal or continuation trades.
🔍 Features:
✅ Automatic detection of bullish and bearish mitigation blocks
🟩 Box visualization with border color change on mitigation (first touch)
📉 ATR-based impulse filtering
📌 Entry arrows on first mitigation (touch)
📊 Autoscale anchors for better chart readability
📈 Real-time HUD info panel
📉 Backtest-friendly design (stable, deterministic logic)
🛠️ How it works:
Detects swing highs/lows using pivot points.
Confirms impulse candles breaking recent structure.
Locates the last opposite candle as the mitigation block.
Displays a block box until price revisits the zone.
On the first touch (mitigation), the block is marked and arrows are drawn.
💡 Ideal Use Case:
Apply this on higher timeframes (e.g., 4H) to identify potential limit order zones.
Use the blocks as entry zones and combine with confluence: FVGs, imbalance, S&D, or liquidity levels.
🧠 Extra Tip:
You can extend this script to include:
Win-rate tracking
Auto TP/SL levels based on ATR
Confluence detection (e.g., FVG, order blocks)
EMA Dual with SL/TP ATR basedDouble EMA with cross and direction display.
Calculate stop loss / take profit based on ATR
If entering is not in the recognize direction also SL/TP is display (inversed values)
SL is 2xATR and TP is 4xAT by default - can be change
Also, SL/TP can be calculated at cross or at actual - see the table.
Multi-Market Trend-Pullback Alerts (EMA20/50 + RSI) [v6]//@version=6 replaces 5
Some functions (like label.delete) need to be called as methods
Minor syntax tightening around string concatenation and label management
All alertcondition() and table logic still works, but must be explicitly version 6 compatible
SMA Pro (Tick)Simple moving average based on 100 ticks, by default. Use for high volume markets like ES, NQ, and RTY.
Trend Discovery by Alex Trend States (Up / Reversal / Down)Author: © Alex Neighbors
Version: v6
The Call/Put Arrow Indicator is a complete market direction tool that identifies high-probability CALL (bullish) and PUT (bearish) opportunities using a combination of:
Simple Moving Averages (SMA)
RSI Momentum
MACD confirmation
VWAP trend filtering
Real-time trend classification (Trending Up, Trending Down, or Reversal)
It provides visual buy/sell arrows, trend labels, and alerts, helping traders quickly recognize optimal option entry points and directional momentum changes.
*** How It Works
✅ CALL Arrow (Green, Up Arrow Below Candle):
Triggered when:
Fast SMA > Slow SMA (uptrend)
RSI > Threshold (default 55)
MACD Line > Signal Line
(Optional) Price > VWAP
🔻 PUT Arrow (Red, Down Arrow Above Candle):
Triggered when:
Fast SMA < Slow SMA (downtrend)
RSI < Threshold (default 45)
MACD Line < Signal Line
(Optional) Price < VWAP
**Trend Detection System:
Trending Up: Both SMAs rising with bullish alignment
Trending Down: Both SMAs falling with bearish alignment
Trend Reversal: Detected instantly when Fast SMA crosses the Slow SMA (marked by a diamond)
Visuals
🟩 Green arrows below candles for CALL entries
🟥 Red arrows above candles for PUT entries
🟢/🔴 Diamonds mark trend reversals
Trend status panel in the top-right corner
Optional background or bar coloring for quick visual confirmation
Alerts
You can create alerts for:
CALL Buy Signal
PUT Buy Signal
Trend Reversal Up
Trend Reversal Down
All alerts trigger exactly when arrows or reversals appear on the chart.
--Best Use
Works on any symbol or timeframe (scalping, swing, or trend trading)
Optimized for SPX, QQQ, TSLA, and high-volume tickers
Ideal for traders combining options flow or price action confirmation
Customization
You can adjust:
SMA lengths
RSI thresholds
MACD parameters
VWAP filter toggle
Background/bar coloring and panel display
Why Traders Love It
Simple, clean chart visuals
Non-repainting, confirmed-bar signals
Multi-filter logic for high accuracy
Trend panel for instant context
Use this indicator to stay on the right side of the market.
Identify reversals early, trade the momentum confidently, and never miss your next CALL or PUT setup again.
Current Price (Customizable) by DRtradeCurrent Price Line & Dynamic Label (Fully Customizable)
The ultimate tool for clear, real-time price visualization.
This powerful, lightweight indicator draws a clean horizontal line at the current market price, updating instantly with every price tick. Unlike other current price line scripts, this tool ensures you always see where the price is right now and provides full control over every visual element.
Key Features:
- Real-Time Tracking: The line moves dynamically with price ticks within the current candle, eliminating lag and providing true current market price awareness.
- Line Extension Control: Choose to extend: Left, Right, or Both. Helpful for scalpers and options traders
- Visual Customizations: Color, Style, Size, Width, etc.
- Label Positioning: Left of Candle, Above Candle, or Right of Candle
All customization options are available in the indicator's settings menu.
Ping me with feature reqeusts.
EMA 20+50 + MACD Strateji ( omerprıme)EASY BUY-SELL basitçe al -sat yapabileceğiniz macd indikatörü ve ema kullanılmış bir indikatördür unutmayın ki ne kadar basit o kadar verimli.
Moving Averages) to generate trading signals and trend confirmation.
Trend Identification with EMA
Two EMAs are used to determine the overall market trend (commonly a short-term EMA and a long-term EMA).
When the short EMA crosses above the long EMA, it indicates an uptrend.
When the short EMA crosses below the long EMA, it signals a downtrend.
Signal Confirmation with MACD
The MACD line and Signal line are analyzed to detect momentum shifts.
A bullish signal occurs when the MACD line crosses above the Signal line, especially if the EMAs confirm an uptrend.
A bearish signal occurs when the MACD line crosses below the Signal line, especially if the EMAs confirm a downtrend.
Trading Logic
Buy signals appear only when both the EMA trend is bullish and the MACD confirms momentum to the upside.
Sell signals appear only when both the EMA trend is bearish and the MACD confirms momentum to the downside.
Predictive Pivot Matrix OHLC data, integrates volume profile for POC/Value Area tracking (including virgin POC), applies rule-based "ML" scoring to evaluate pivot strength via factors like proximity, volume, touches, trend, and confluence, monitors adaptive success rates, projects 5-day future pivots using trend/volatility, detects overlapping confluence zones, and generates visuals (lines, labels, table), alerts, and buy/sell signals on key crossings.
Brownian Motion Probabilistic Forecasting (Time Adaptive)Probabilistic Price Forecast Indicator
Overview
The Probabilistic Price Forecast is an advanced technical analysis tool designed for the TradingView platform. Instead of predicting a single future price, this indicator uses a Monte Carlo simulation to model thousands of potential future price paths, generating a cone of possibilities and calculating the probability of specific outcomes.
This allows traders to move beyond simple price targets and ask more sophisticated questions, such as: "What is the probability that this stock will increase by 5% over the next 24 hours?"
Core Concept: Geometric Brownian Motion
The indicator's forecasting model is built on the principles of Geometric Brownian Motion (GBM) , a widely accepted mathematical model for describing the random movements of financial asset prices. The core idea is that the next price step is a function of the asset's historical trend (drift), its volatility, and a random "shock."
The formula used to project each price step in the simulation is:
next_price = current_price * exp( (μ - (σ²/2))Δt + σZ√(Δt) )
Where:
μ (mu) represents the drift , which is the average historical return.
σ (sigma) represents the volatility , measured by the standard deviation of historical returns.
Z is a random variable from a standard normal distribution, representing the random "shock" or new information affecting the price.
Δt (delta t) is the time step for each projection.
How It Works
The indicator performs a comprehensive analysis on the most recent bar of the chart:
**Historical Analysis**: It first analyzes a user-defined historical period (e.g., the last 240 hours of price data) to calculate the asset's historical drift (μ) and volatility (σ) from its logarithmic returns.
**Monte Carlo Simulation**: It then runs thousands of simulations (e.g., 2000) of future price paths over a specified forecast period (e.g., the next 24 hours). Each path is unique due to the random shock (Z) applied at every step.
**Probability Distribution**: After all simulations are complete, it collects the final price of each path and sorts them to build a probability distribution of potential outcomes.
**Visualization and Signaling**: Finally, it visualizes this distribution on the chart and generates signals based on the user's criteria.
Key Features & Configuration
The indicator is highly configurable, allowing you to tailor its analysis to your specific needs.
Time-Adaptive Periods
The lookback and forecast periods are defined in hours , not bars. The script automatically converts these hour-based inputs into the correct number of bars based on the chart's current timeframe, ensuring the analysis remains consistent across different chart resolutions.
Forecast Quartiles
You can visualize the forecast as a "cone of probability" on the chart. The indicator draws lines and a shaded area representing the price levels for different quartiles (percentiles) of the simulation results. By default, this shows the range between the 25th and 95th percentiles.
Independent Bullish and Bearish Signals
The indicator allows you to set independent criteria for bullish and bearish signals, providing greater flexibility. You can configure:
A bullish signal for an X% confidence of a Y% price increase.
A bearish signal for a W% confidence of a Z% price decrease.
For example, you can set it to alert you for a 90% chance of a 2% drop, while simultaneously looking for a 60% chance of a 10% rally.
How to Interpret the Indicator
The Forecast Cone : The blue shaded area on the chart represents the probable range of future prices. The width of the cone indicates the expected volatility; a wider cone means higher uncertainty. The price labels on the right side of the cone show the calculated percentile levels at the end of the forecast period.
Green Signal Label : A green "UP signal" label appears when the probability of the price increasing by your target percentage exceeds your defined confidence level.
Red Signal Label : A red "DOWN signal" label appears when the probability of the price decreasing by your target percentage exceeds your confidence level.
This tool provides a statistical edge for understanding future possibilities but should be used in conjunction with other analysis techniques.
Volume Based Sampling [BackQuant]Volume Based Sampling
What this does
This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition:
Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold.
Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold.
The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison.
Why event-based sampling matters
Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular:
Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds.
The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds.
Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks.
How the indicator works (plain English)
Choose your bucket type
Volume : accumulate volume until it meets a threshold.
Dollar Bars : accumulate close × volume until it meets a dollar threshold.
Pick the threshold rule
Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars).
Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar).
Build the synthetic bar
While a bucket fills, the script tracks:
o_s: first price of the bucket (synthetic open)
h_s: running maximum price (synthetic high)
l_s: running minimum price (synthetic low)
c_s: last price seen (synthetic close)
v_s: cumulative native volume inside the bucket
d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled)
Emit a new sample
Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity.
Maintain a rolling history efficiently
A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable.
Compute synthetic-space statistics
The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time.
Inputs and options you will actually use
Data Settings
Sampling Method : Volume or Dollar Bars.
Rolling Lookback : window used to estimate the dynamic threshold from recent activity.
Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes.
Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target.
Max Stored Samples : cap on synthetic history to keep performance snappy.
Use Ring Buffer : turn on to recycle storage when at capacity.
Indicator Settings
SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes.
Visuals
Show Synthetic Bars : plot the synthetic OHLC candles.
Candle Color Mode :
Green/Red: directional close vs open
Volume Intensity: opacity scales with synthetic size
Neutral: single color
Adaptive: graded by how large the bucket was relative to threshold
Mark new samples : drop a small marker whenever a new synthetic bar prints.
Comparison & Research
Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ.
How to read it, step by step
Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars.
Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information.
Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility.
Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument.
Quant finance background and citations
Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars.
Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management.
AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca )
Practical use cases
1) Regime-aware moving averages
The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation.
2) Breakout logic on “equal-information” samples
The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets.
3) Volatility-adaptive backtests
If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream).
4) Regime diagnostics
Avg Bars per Sample trending down: activity is dense; expect larger realized ranges.
Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk.
Interpreting the info panel
Method : your sampling choice and current threshold.
Total Samples : how many synthetic bars have been formed.
Current Vol/Dollar : how much of the next bucket is already filled.
Bars in Bucket : native bars consumed so far in the current bucket.
Avg Bars/Sample : lower means higher trading intensity.
Avg Return / Return StdDev : return stats computed over synthetic closes .
Research directions you can build from here
Imbalance and run bars
Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets
Volume-time indicators
Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes.
Liquidity and toxicity overlays
Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated.
Dollar-risk parity sampling for portfolios
Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering.
Microstructure feature set
Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca )
Tips for clean usage
Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale.
Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time.
Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
Portfolio Simulator & BacktesterMulti-asset portfolio simulator with different metrics and ratios, DCA modeling, and rebalancing strategies.
Core Features
Portfolio Construction
Up to 5 assets with customizable weights (must total 100%)
Support for any tradable symbol: stocks, ETFs, crypto, indices, commodities
Real-time validation of allocations
Dollar Cost Averaging
Monthly or Quarterly contributions
Applies to both portfolio and benchmark for fair comparison
Model real-world investing behavior
Rebalancing
Four strategies: None, Monthly, Quarterly, Yearly
Automatic rebalancing to target weights
Transaction cost modeling (customizable fee %)
Key Metrics Table
CAGR: Annualized compound return (S&P 500 avg: ~10%)
Alpha: Excess return vs. benchmark (positive = outperformance)
Sharpe Ratio: Return per unit of risk (>1.0 is good, >2.0 excellent)
Sortino Ratio: Like Sharpe but only penalizes downside (better metric)
Calmar Ratio: CAGR / Max Drawdown (>1.0 good, >2.0 excellent)
Max Drawdown: Largest peak-to-trough decline
Win Rate: % of positive days (doesn't indicate profitability)
Visualization
Dual-chart comparison - Portfolio vs. Benchmark
Dollar or percentage view toggle
Customizable colors and line width
Two tables: Statistics + Asset Allocation
Adjustable table position and text size
🚀 Quick Start Guide
Enter 1-5 ticker symbols (e.g., SPY, QQQ, TLT, GLD, BTCUSD)
Make sure percentage weights total 100%
Choose date range (ensure chart shows full period - zoom out!)
Configure DCA and rebalancing (optional)
Select benchmark (default: SPX)
Analyze results in statistics table
💡 Pro Tips
Chart data matters: Load SPY or your longest-history asset as main chart
If you select an asset that was not available for the selected period, the chart will not show up! E.g. BTCUSD data: Only available from ~2017 onwards.
Transaction fees: 0.1% default (adjust to match your broker)
⚠️ Important Notes
Requires visible chart data (zoom out to show full date range)
Limited by each asset's historical data availability
Transaction fees and costs are modeled, but taxes/slippage are not
Past performance ≠ future results
Use for research and education only, not financial advice
Let me know if you have any suggestions to improve this simulator.
KAPITAS TBR 12am-8:30measures the range between 12am(true day open)-8:30am and has % levels where price is sensitive and likely to reverse
KAPITAS CBDR# PO3 Mean Reversion Standard Deviation Bands - Pro Edition
## 📊 Professional-Grade Mean Reversion System for MES Futures
Transform your futures trading with this institutional-quality mean reversion system based on standard deviation analysis and PO3 (Power of Three) methodology. Tested on **7,264 bars** of real MES data with **proven profitability across all 5 strategies**.
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## 🎯 What This Indicator Does
This indicator plots **dynamic standard deviation bands** around a moving average, identifying extreme price levels where institutional accumulation/distribution occurs. Based on statistical probability and market structure theory, it helps you:
✅ **Identify high-probability entry zones** (±1, ±1.5, ±2, ±2.5 STD)
✅ **Target realistic profit zones** (first opposite STD band)
✅ **Time your entries** with session-based filters (London/US)
✅ **Manage risk** with built-in stop loss levels
✅ **Choose your strategy** from 5 backtested approaches
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## 🏆 Backtested Performance (Per Contract on MES)
### Strategy #1: Aggressive (±1.5 → ∓0.5) 🥇
- **Total Profit:** $95,287 over 1,452 trades
- **Win Rate:** 75%
- **Profit Factor:** 8.00
- **Target:** 80 ticks ($100) | **Stop:** 30 ticks ($37.50)
- **Best For:** Active traders, 3-5 setups/day
### Strategy #2: Mean Reversion (±1 → Mean) 🥈
- **Total Profit:** $90,000 over 2,322 trades
- **Win Rate:** 85% (HIGHEST)
- **Profit Factor:** 11.34 (BEST)
- **Target:** 40 ticks ($50) | **Stop:** 20 ticks ($25)
- **Best For:** Scalpers, 6-8 setups/day
### Strategy #3: Conservative (±2 → ∓1) 🥉
- **Total Profit:** $65,500 over 726 trades
- **Win Rate:** 70%
- **Profit Factor:** 7.04
- **Target:** 120 ticks ($150) | **Stop:** 40 ticks ($50)
- **Best For:** Patient traders, 1-3 setups/day, HIGHEST $/trade
*Full statistics for all 5 strategies included in documentation*
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## 📈 Key Features
### Dynamic Standard Deviation Bands
- **±0.5 STD** - Intraday mean reversion zones
- **±1.0 STD** - Primary reversion zones (68% of price action)
- **±1.5 STD** - Extended zones (optimal balance)
- **±2.0 STD** - Extreme zones (95% of price action)
- **±2.5 STD** - Ultra-extreme zones (rare events)
- **Mean Line** - Dynamic equilibrium
### Temporal Session Filters
- **London Session** (3:00-11:30 AM ET) - Orange background
- **US Session** (9:30 AM-4:00 PM ET) - Blue background
- **Optimal Entry Window** (10:30 AM-12:00 PM ET) - Green highlight
- **Best Exit Window** (3:00-4:00 PM ET) - Red highlight
### Visual Trade Signals
- 🟢 **Green zones** = Enter LONG (price at lower bands)
- 🔴 **Red zones** = Enter SHORT (price at upper bands)
- 🎯 **Target lines** = Exit zones (opposite bands)
- ⛔ **Stop levels** = Risk management
### Smart Alerts
- Alert when price touches entry bands
- Alert on optimal time windows
- Alert when targets hit
- Customizable for each strategy
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## 💡 How to Use
### Step 1: Choose Your Strategy
Select from 5 backtested approaches based on your:
- Risk tolerance (higher STD = larger stops)
- Trading frequency (lower STD = more setups)
- Time availability (different session focuses)
- Personality (scalper vs swing trader)
### Step 2: Apply to Chart
- **Timeframe:** 15-minute (tested and optimized)
- **Symbol:** MES, ES, or other liquid futures
- **Settings:** Adjust band colors, widths, alerts
### Step 3: Wait for Setup
Price touches your chosen entry band during optimal windows:
- **BEST:** 10:30 AM-12:00 PM ET (88% win rate!)
- **GOOD:** 12:00-3:00 PM ET (75-82% win rate)
- **AVOID:** Friday after 1 PM, FOMC Wed 2-4 PM
### Step 4: Execute Trade
- Enter when price touches band
- Set stop at indicated level
- Target first opposite band
- Exit at target or stop (no exceptions!)
### Step 5: Manage Risk
- **For $50K funded account ($250 limit): Use 2 MES contracts**
- Stop after 3 consecutive losses
- Reduce size in low-probability windows
- Track cumulative daily P&L
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## 📅 Optimal Trading Windows
### By Time of Day
- **10:30 AM-12:00 PM ET:** 88% win rate (BEST) ⭐⭐⭐
- **12:00-1:30 PM ET:** 82% win rate (scalping)
- **1:30-3:00 PM ET:** 76% win rate (afternoon)
- **3:00-4:00 PM ET:** Best EXIT window
### By Day of Week
- **Wednesday:** 82% win rate (BEST DAY) ⭐⭐⭐
- **Tuesday:** 78% win rate (highest volume)
- **Thursday:**
Hummingbird Probability Mapping IndicatorHummingbird Probability Mapping Indicator - A nature inspired indicator that utilizes combinations of the following trend patterns and projects a probability mapping with greater than 70% accuracy based on real-time analysis.
EMA Trend
MACD
RSI
VWAP Spread
Burst
Squeeze
Volatility (ATRp)
Qi Dass
Foxbrady D/G CrossFoxbrady D/G Cross - Golden Cross & Death Cross Indicator**
A clean and simple indicator that identifies Golden Cross and Death Cross events using the classic 50-day and 200-day simple moving averages.
Features:
- Blue line: 50-day SMA (fast moving average)
- Red line: 200-day SMA (slow moving average)
- Green "GC" label appears at the exact crossover point when a Golden Cross occurs (bullish signal)
- Red "DC" label appears at the exact crossover point when a Death Cross occurs (bearish signal)
- Built-in alert conditions for both events
- Customizable MA periods to suit your trading style
How to Use:
The Golden Cross (50 MA crossing above 200 MA) is traditionally viewed as a bullish long-term signal, while the Death Cross (50 MA crossing below 200 MA) is considered a bearish indicator. This indicator makes it easy to spot these events historically and receive alerts when they occur in real-time.
Perfect for swing traders and long-term investors looking to identify major trend changes.
