Momentum Squeeze Breakout EngineDescription
*Momentum Squeeze Breakout Engine* is a quantitative, trend-following breakout strategy engineered to capture explosive directional moves emerging from periods of asset compression (squeezes). By combining precise volatility boundaries, structural market sentiment filters, and micro-momentum triggers, this strategy systematically avoids false breakouts.
### Core Mechanics & Features
1. Volatility Squeeze Identification
The foundation of this strategy relies on the relationship between *Bollinger Bands* and *Keltner Channels. When the Bollinger Bands contract *inside the Keltner Channels, it confirms a highly compressed, low-volatility environment (highlighted by the subtle blue background zones). This indicates stored market energy primed for release.
2. Rigid Structural Macro Filter (200 EMA)
To eliminate counter-trend traps, the strategy utilizes a strict 200-period Exponential Moving Average (EMA) as a macro baseline. Long entries are strictly prohibited if the asset is printing below this line, ensuring you only trade high-probability expansions aligned with the dominant institutional trend.
3. Holistic Intra-Bar Bias
Rather than relying purely on close prices, the script calculates an internal *Holistic Bias* engine. It evaluates where the close falls relative to each bar's high-low range over a specific structural lookback period. A valid breakout requires a positive cumulative sentiment bias (cumBias > 0), ensuring authentic accumulation is taking place.
4. Micro-Momentum (Rate of Change) Filter
To prevent entering "slow drift" scenarios or low-volume fakeouts, a 3-period Rate of Change (ROC) velocity check is integrated. A breakout will only trigger an entry if the price action demonstrates immediate expanding velocity (priceROC > 0).
# Execution Rules
* *BUY Signal:* Generated when a compression zone has broken out within the last 3 bars, the price crosses above the Upper Bollinger Band, the macro trend is bullish (Price > 200 EMA), holistic bias is positive, and positive momentum velocity is confirmed.
* *EXIT Signal:* Generated when the price crosses below the Lower Bollinger Band following a squeeze or when the holistic bias shifts negatively, functioning as a structural trailing mechanism.
* *Signal Spacing:* Features a built-in 15-bar cooldown rule to prevent over-trading and signal clustering within volatile consolidation nodes.
### Best Practices
* *Intended Timeframe:* Optimized for the *1-Hour (1H)* chart.
* *Assets:* Best suited for high-liquidity assets including Major Crypto Pairs (BTC, ETH), Blue- Chip Equities, Indices and Major Forex Pairs.
* *Risk Management:* Default settings utilize a 100% equity allocation model for raw backtesting transparency, but traders should scale their position sizes according to their personal risk tolerances.
### Disclaimer
*Financial and Trading Risk Warning:*
This script is an educational and analytical tool designed to demonstrate quantitative breakout concepts using historical data. It is published as an open-source resource for informational purposes only and does not constitute financial, investment, or trading advice.
Past performance is not indicative of future results. Market conditions change constantly, and systematic strategies can experience significant drawdowns. Automated trading involves substantial risk of capital loss. Never trade with money you cannot afford to lose. The author assumes no liability or responsibility for any financial losses incurred from the use or modification of this code. Always perform your own independent research and forward-test on a demo account before risking live capital. Strategy
BB-RSI Overbought DCA - Short StrategyBB-RSI Overbought DCA — Short Strategy
🔷 What it does:
This is a short-only DCA strategy that fades overbought thrusts confirmed by two independent volatility-and-momentum filters on a lower timeframe. A short entry opens only when Bollinger Bands %B crosses up the upper band AND RSI crosses up an overbought threshold at the same lower-timeframe close — the dual confirmation requires both volatility-expansion and momentum-overheat to align. Nine safety orders form a wide deviation ladder for adverse upward price action. Exit is a fixed percentage Take Profit below the running average entry. No trailing, no Stop Loss.
- Single base order with up to nine safety orders, sized at a 1.03× progression for soft compounding.
- Dual-filter entry: BB %B(20, 2.0) crossing up 1.00 AND RSI(7) crossing up 65, both on 30m.
- Wide deviation ladder: 0.72% to first safety order, 1.55× step multiplier — last safety order at ~63% above base entry.
- Take Profit: 2.11% below average entry. No trailing.
- Every entry, safety order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption.
🔷 Who is it for:
- Swing traders looking for high-win-rate short exposure on crypto perpetuals that frequently overshoot resistance.
- Bot operators who want a mechanical fade engine with dual confirmation and bounded position size.
- Risk-conscious operators — at default settings the maximum deployed capital is ~8.93% of equity, and the realized maximum drawdown over a 2.5-year sample stayed at 1.53%.
- Traders building a low-correlation portfolio: a defensive short with very low DD and an exceptional profit factor pairs well with directional long strategies.
🔷 How does it work:
Bollinger Bands %B Filter: A 30-minute Bollinger Bands(20, 2.0) is sampled via request.security and converted to %B = (close − lower) / (upper − lower). When %B crosses up the configured level (default 1.00 — price exiting the upper band), the BB gate is satisfied. The 30-minute timeframe is sampled with lookahead disabled to avoid repaint.
RSI Filter: A 30-minute RSI(7) is sampled in parallel. When RSI crosses up the configured level (default 65 — entering overbought), the RSI gate is satisfied. Both gates must be satisfied at the same host-bar close to arm a base entry.
Entry: When both filters cross up on the same host bar, a short position opens at the base order size. The base order is configurable as Market (default) or Limit at the bar's close.
Safety Order Ladder: After the base fill, the strategy monitors price deviation upward against the position. The k-th safety order fires when close ≥ base entry × (1 + cumulative deviation), where cumulative deviation grows by the step multiplier (default 1.55). At default settings: 0.72%, 1.84%, 3.57%, 6.25%, 10.40%, 16.48%, 25.90%, 40.51%, 63.14%. Each safety order's size grows by the size multiplier (default 1.03) — soft compounding rather than aggressive martingale.
Exit: A fixed Take Profit at 2.11% below the running average entry. The position closes the moment close ≤ TP target. No trailing, no Stop Loss.
🔷 Why it's unique:
- Dual-Filter Confirmation: Two independent signals on the same lower timeframe must align. %B captures volatility expansion (price extension beyond statistical bounds); RSI captures momentum exhaustion. Together they filter out either-or noise that would trigger single-condition strategies.
- Soft Compounding Ladder: The 1.03× size multiplier is much gentler than typical martingale (1.5–2.0×). It still scales position size with adverse drift but doesn't blow up capital deployment if all safety orders fill.
- Bounded Position Cap: With 9 safety orders at 1.03× progression, the maximum deployed capital is exactly base + 80 × 10.159 = 893 USDT per trade ≈ 8.93% of default equity. Inside the conventional 5–10% per-trade band, no surprises.
- DCA Bot Integration: Every event (base, AO 1–9, exit) emits a fully-formed JSON alert payload. Connect one alert to a DCA Bot's webhook URL and the strategy drives the bot end-to-end.
🔷 Considerations Before Using the Strategy:
Market & Timeframe: Defaults are calibrated for BYBIT:ATOMUSDT perpetual on 30m. The dual-filter combination is portable to other liquid crypto perpetuals that mean-revert from overbought stretches, but filter thresholds (BB level, RSI level) should be reviewed before redeployment.
Strong Uptrends: Like any fade-the-strength setup, this strategy is positioned for ranges and rotations, not breakouts. In sustained uptrends the strategy may fill the entire 9-AO ladder and hold the short while price grinds higher. The dual filter limits exposure to confirmed overbought conditions, which historically have higher mean-reversion expectancy, but a regime shift to a strong trend requires manual oversight.
Performance Profile: This is a high-confidence, low-volatility, low-return defensive short. Over the 2.5-year backtest the strategy returned +3.95% with a 1.53% maximum drawdown — annualized return is modest, but the return-to-DD ratio of ~2.6 and profit factor of 6.23 reflect very tight risk control. Size accordingly: this is a portfolio contributor, not a standalone alpha source.
Funding Rates (Perpetuals): Backtests do not account for perpetual funding rates. Sustained positive funding on ATOMUSDT.P (longs pay shorts) would improve live performance; sustained negative funding (shorts pay longs) would degrade it. Review the historical funding pattern before live deployment.
Commission Calibration: The default commission (0.4%) is set high as a conservative assumption. The actual Bybit perpetual taker fee is approximately 0.06%, so live performance with realistic Bybit fees should be meaningfully better than the published numbers. Update the commission input to match your fee tier for accurate forward expectations.
No Stop Loss Justification: There is no exit on adverse moves beyond the 9-AO ladder. Per-trade risk is structurally capped by the bounded position-size ladder — at defaults that is 893 USDT max deployed = 8.93% of equity, inside the conventional 5–10% per-trade band. If a hard stop is required at the exchange level, layer it on the bot side.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:ATOMUSDT.P (Perpetual)
Timeframe: 30M
Test Period: Mar 1, 2025 — Apr 1, 2026 (~1.1 years).
Initial Capital: 10,000 USDT.
Order Size per Trade: 0.8% of Capital base + 9 safety orders at 1.03× progression.
Max Capital Deployed: ~893 USDT per trade (~8.93% of equity).
Commission: 0.4% per trade (conservative — Bybit perpetual taker is ~0.06%).
Slippage: 3 ticks.
Margin for Short Positions: 100%.
Indicator Settings: Default Configuration.
Base Order: 80 USDT, Market by default (Limit toggle available).
Take Profit: 2.11% below average entry (no trailing).
Stop Loss: None — bounded position size is the structural risk cap.
BB %B Filter: 30m BB(20, 2.0), Crossing Up 1.00.
RSI Filter: 30m RSI(7), Crossing Up 65.
Averaging Orders: 9, Deviation 0.72%, Deviation Step 1.55×, Size Multiplier 1.03×.
Strategy: Short Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +395.18 USDT (+3.95%)
Max Equity Drawdown: 154.46 USDT (1.53%)
Total Closed Trades: 267
Percent Profitable: 79.78% (213 / 267)
Profit Factor: 6.23
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, BB filter (period / deviation / level), RSI filter (length / level), the 9-AO ladder, and the Take Profit percentage. Defaults are calibrated for ATOMUSDT.P 30m — recalibrate per asset before deploying.
🔸 Results Review: Run a full-period backtest and confirm Max Drawdown stays inside your personal risk band. Validate that the closed-trade count is statistically meaningful (≥ 100 is a reasonable floor). Update commission to match your exchange's actual fees.
🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The strategy will emit JSON payloads for short entry, each safety order, and exit — formatted for direct DCA Bot consumption.
🔷 INDICATOR SETTINGS
Base Order Size (USDT): USDT amount opened on the short entry.
Use LIMIT for Base: Toggle between Market (default) and Limit at bar close.
Averaging Orders per Trade: Maximum number of safety orders per deal (default 9).
First AO Size (USDT): USDT size of the first safety order; subsequent AOs scale by the Size Multiplier.
Deviation to First AO (%): Distance from base entry at which AO1 becomes eligible.
Deviation Step Multiplier: Ladder factor that widens each subsequent deviation step.
Order Size Multiplier: Factor that grows each subsequent safety order's USDT size.
BB Timeframe / Period / Deviation / Level: 30-minute Bollinger Bands %B filter on the host symbol.
RSI Timeframe / Length / Level: 30-minute RSI filter on the host symbol.
Take Profit (%): Fixed distance from average entry where the short closes for profit.
DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload.
Visualization: Toggle DCA Ladder, fill labels, status table.
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas PulseWire account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. Strategy
Multi-Factor Regime Engine Pro [MarkitTick]💡 This indicator represents a robust framework designed to quantify market regimes by analyzing an array of price action, volatility, and momentum metrics. By synthesizing ten distinct market features into a unified confidence score, it dynamically adjusts its threshold bands, providing a highly adaptive approach to trend identification on any standard chart.
✨ Originality and Utility
Standard trend-following tools often rely on static lookback periods and fixed multipliers, which can lead to delayed signals during sudden market shifts or excessive false signals during consolidation. This indicator diverges from traditional methods by introducing a dynamic, feature-engineered confidence score. Instead of relying on a single data point like closing price or standard volatility, it aggregates inputs from momentum oscillators, directional movement indices, volume profiles, and standard deviation bands. This multi-dimensional analysis allows the indicator's bands to compress during high-confidence trends and expand during uncertain, low-confidence environments, offering a highly responsive and adaptive utility for modern chart analysis. Furthermore, it incorporates strict internal safeguards to prohibit execution on non-standard charts, ensuring the integrity of the data and preventing repainting vulnerabilities.
🔬 Methodology and Concepts
● The Feature Engineering Engine
The core of this indicator is built upon extracting ten distinct normalized features from the market data, evaluating multiple dimensions of price action simultaneously:
Momentum Normalization: Utilizes relative strength metrics, centered and scaled, to gauge underlying momentum bias without relying on absolute thresholds.
Directional Strength: Analyzes directional movement indices to quantify the strength of the current trajectory, applying directional penalties when negative movement overpowers positive movement.
Moving Average Distances: Measures the current price relative to fast and slow moving averages, standardizing the distance using the Average True Range to identify structural overextension.
Rate of Change Standardization: Normalizes the rate of change against its own rolling standard deviation to detect statistical anomalies in speed and acceleration.
Standard Deviation Extremes: Evaluates the position of the price relative to upper and lower Bollinger Bands, calculating the precise percentile of the close within the volatility envelope.
Volatility Stability: Compares short-term volatility against long-term volatility baselines to measure market stress and detect rapid expansions.
Volume Anomalies: Assesses current volume against its simple moving average, clamping the result to identify participation spikes that validate price movement.
Price Action Consistency: Calculates the ratio of bullish to bearish closes within the defined lookback period, serving as a raw footprint of buyer versus seller control.
● The Confidence Score Assembly
These standardized features are separated into distinct sub-components. A Directional Score identifies the probable path of the trend by weighting momentum and moving average slopes. A Quality Score measures the structural integrity of that trend by analyzing volume participation and volatility stability. These are mathematically combined to produce a Raw Confidence value. This raw output undergoes an adaptive smoothing process using a dynamic moving average, resulting in a highly stable, final Confidence Score bounded precisely between 0% and 100%.
● Adaptive Ratcheting Bands
The calculated Confidence Score directly influences the width of the trend bands. When the confidence is high, the internal multiplier decreases, tightening the bands closer to the price action to capture shifts quickly and protect accumulated distance. Conversely, when confidence is low, the bands expand to avoid noise and erratic whipsaws. The bands utilize a state-machine logic that only ratchets in the direction of the trend, acting as a trailing threshold that reacts to both price crosses and sudden regime shifts identified by extreme volatility spikes.
🎨 Visual Guide
● Heatmap Candles
The indicator actively repaints the chart candles based on a calculated mathematical "stress" metric.
Colors transition dynamically from a baseline trend color (Deep Sky Blue for bullish conditions, Radical Red for bearish conditions) to a bright orange "Regime Alert" color when underlying volatility spikes significantly.
Candle body opacity is heavily controlled by the alignment of the price action with the overall trend direction, fading to a darker tone during contrary movements or low-confidence pullbacks.
● ML Supertrend Band
Displayed as a prominent, solid line representing the adaptive trailing threshold on the chart.
This band is colored Deep Sky Blue during bullish market phases and Radical Red during bearish phases, updating in real-time as the state machine ratchets.
● Confidence Gradient Cloud
This visual element fills the spatial gap between the median price baseline and the trailing Supertrend band.
The exact opacity and gradient of this cloud are mapped directly to the Confidence Score. A highly opaque, solid cloud represents high confidence, while a highly transparent, fading cloud visually indicates low confidence and potential market transition.
● Visual Labels
Small directional visual markers appear directly above or below the price action when a trend flip occurs.
These labels display an arrow alongside a precise percentage value, representing the exact calculated Confidence Score at the moment the signal was generated.
● Info Table
Located statically in the top right corner, this dashboard displays crucial real-time internal metrics.
It includes the current trend direction, a visual text-based progress bar for the Confidence Score, the live Adaptive Multiplier value adjusting in real-time, the selected Model configuration, and a dynamic text alert that triggers during active Regime Shifts.
📖 How to Use
● Trend Identification
Observe the dominant color of the ML Supertrend Band and the Confidence Gradient Cloud. Deep Sky Blue strongly indicates a bullish environment, while Radical Red suggests a bearish environment. The visibility and thickness of the cloud serve as your primary visual gauge of the trend's structural health.
● Interpreting the Confidence Metric
Monitor the Confidence Score inside the Info Table or at signal generation. A high percentage (e.g., above 70%) suggests that multiple underlying market factors (volume, momentum, standard deviation) are in full agreement with the current directional bias. A rapidly dropping confidence score often precedes a period of choppy consolidation or warns of a potential reversal, allowing for tighter risk parameters.
● Reading Heatmap Candles for Shifts
When the standard colored candles begin transitioning toward the bright orange Regime Alert color, it indicates an abnormal spike in volatility combined with a directional momentum shift. This visually warns the user of a potential "Regime Shift" where the market is undergoing severe internal stress. These specific visual cues often signal an impending breakout from a range or a violent capitulation event.
⚙️ Inputs and Settings
● Model Configuration
Strategic Cycle Mode: Allows the choice between an "Auto" mode and a "Custom" mode. Auto mode dynamically selects the most mathematically optimal lookback lengths, thresholds, and weighting coefficients based purely on the current timeframe in seconds.
Strategic Cycle: When in custom mode, this determines the core lookback period for all volatility and momentum calculations. Smaller values drastically increase reactivity, while larger values provide smoother, long-term macroeconomic analysis.
Macro Trend Threshold: Sets the baseline mathematical width of the threshold bands. Higher values require significantly larger price movements to trigger a trend flip, reducing noise.
Prediction Weight: Controls the internal sensitivity of the bands to rapid changes in the Confidence Score, determining how aggressively the bands compress.
● Visual Settings & Colors
Dedicated toggles are provided to enable or disable the Confidence Labels, the Info Table, and the Heatmap Candles to keep the chart interface as clean as desired.
All core graphical colors, including the specific bands, gradient clouds, table text, and alert highlights, are fully customizable by the user via hex selection.
● Webhook Settings
The indicator is pre-configured to output detailed, formatted JSON payloads designed for external execution automation.
Users can securely define specific action strings for entering and closing both long and short positions directly within the settings menu, mapping exactly to their webhook parser logic.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Multi-Variate Feature Standardization
The mathematical foundation of this tool relies heavily on statistical normalization techniques designed to process heterogeneous data. Financial time series data is notoriously non-stationary and spans vastly different numerical scales. To effectively combine disparate metrics like Volume (often measured in millions) and relative strength oscillators (strictly bounded between 0 and 100), the indicator employs rigorous Min-Max scaling and localized Z-score approximations. For instance, the rate of change is evaluated against its own rolling standard deviation over a defined period, successfully standardizing the momentum readout into a continuous, comparable spectrum bounded cleanly between -1.0 and 1.0.
● Linear Weighted Ensembles
The internal architecture utilizes a deterministic linear weighted model to synthesize the final output. By assigning highly specific fractional coefficients to directional features (like the exponential moving average slope and relative strength) and structural features (like Bollinger Band width extremes and volatility stability), the script constructs a singular composite index. This mirrors standard ensemble methodologies found in data science, where the consensus of multiple independent weak learners generates a stronger, more reliable predictive metric than any single indicator could achieve in isolation.
● Volatility-Adjusted State Machines
The adaptive threshold logic operates as a strict finite-state machine incorporating the Average True Range metric. The specific mathematical innovation lies in rendering the ATR multiplier as an inverse linear function of the composite confidence index. In quantitative terms, this produces a dynamically dampened volatility envelope. When the composite index approaches a maximum value indicating high convergence, the dampening factor aggressively compresses the envelope, mathematically acknowledging that high-conviction trends exhibit less erratic mean-reversion behavior and therefore require drastically tighter invalidation levels to preserve structural alpha.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
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Bollinger Band + Mid BandBollinger Band + Mid Band
This indicator combines the classic Bollinger Bands with enhanced customization options, allowing traders to fine-tune the settings according to their specific strategies.
Key Features:
Moving Average Flexibility: Choose between Simple Moving Average (SMA), Exponential Moving Average (EMA), or Weighted Moving Average (WMA) as the central basis for the Bollinger Bands. This flexibility allows you to align the indicator with your preferred method of trend analysis.
Dual Band Deviation: The indicator includes two sets of upper and lower bands based on different standard deviation multipliers. This helps you analyze both the tightness of price action and potential breakout zones.
Customizable Colors: The mid-band, upper bands, and lower bands can be fully customized in terms of color, allowing you to personalize the visual representation of the indicator on your charts.
Dynamic Transparency: The space between the outer Bollinger Bands can be filled with a customizable transparent color, making it easy to visualize price movements within the bands.
Alerts for Crossovers: Alerts are triggered whenever the price crosses above the upper band or below the lower band, giving you timely notifications of potential breakout or breakdown scenarios.
Overbought/Oversold Visualization: The background of the chart changes color when the price crosses above the upper band (indicating overbought conditions) or below the lower band (indicating oversold conditions), providing a visual cue to help you identify market extremes.
Labeling for Significant Events: Labels appear on the chart whenever the price crosses the upper or lower bands, helping you quickly identify key moments for further analysis.
This script is designed for traders who want to leverage Bollinger Bands in their technical analysis but require additional flexibility and customization options. Whether you're using it for trend analysis, volatility assessment, or identifying overbought and oversold conditions, this tool can be tailored to fit a wide variety of trading styles.
Usage:
Ideal for traders looking to enhance the standard Bollinger Bands with more dynamic and customizable features.
Suitable for any market, including stocks, forex, and cryptocurrencies.
Useful in identifying volatility squeezes, breakouts, and potential reversal points.
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