Accurate ATR Stop Loss Distance — Risk Management ToolAccurate ATR Stop Loss Distance — Risk Management Tool
This indicator calculates an accurate Stop Loss distance in pips using the Average True Range (ATR) multiplied by a user-defined multiplier.
It automatically detects the correct pip size based on the instrument type (Forex, Crypto, Stocks, Indices, Futures), adjusting for 2-, 3-, 4-, or 5-digit quotes — ensuring professional-grade precision that matches institutional ATR-based risk systems.
📊 Features:
Uses ATR × Multiplier to determine precise SL distance in pips.
Automatically adjusts pip value depending on the asset type (handles 5-digit Forex brokers).
Clean and minimal design — displays only one info box in the top-right corner.
Fully customizable text and background colors.
Includes alert condition for automated SL updates.
⚙️ How to use:
Set your preferred ATR period and multiplier.
The indicator instantly displays your Stop Loss distance in pips at the top-right of the chart.
Combine with your entry strategy to calculate lot size or risk per trade.
💡 Ideal for traders who want consistent, objective SL distances derived from volatility rather than arbitrary points or emotions.
Note: Educational and informational tool only. Does not execute trades or give financial advice.
Pesquisar nos scripts por "atr"
(RSI + CCI) × (MACD/ATR)^2⚙️ (RSI + CCI) × (MACD / ATR)² Composite — Normalized, Compressed, Dynamic Colors
This advanced composite oscillator merges three powerful momentum indicators — RSI, CCI, and MACD — into one normalized and volatility-adjusted signal that reacts smoothly across all markets.
By dividing MACD by ATR (Average True Range), the indicator self-scales for different symbols, and an optional tanh-like compression prevents extreme spikes while keeping the movement fluid and responsive.
🧩 Core Formula
(RSI + CCI) × (MACD / ATR)²
(optionally passed through a tanh compression for stability)
RSI and CCI are normalized (RSI ÷ 50, CCI ÷ 100) → roughly −2 to +2 range.
MACD is volatility-adjusted by ATR → scale-independent between assets.
The result is centered around 0 for clear bullish/bearish momentum comparison.
🎨 Visual Features
🟢🔴 Dynamic 4-Color Histogram
Positive + Rising = Strong Teal
Positive + Falling = Light Teal
Negative + Falling = Strong Red
Negative + Rising = Light Red
🟡⚫ 4-Color Smoothing Line
Positive & Rising = Bright Yellow
Positive & Falling = Soft Yellow
Negative & Rising = Grey
Negative & Falling = Dark Grey
Zero-centered layout for intuitive bullish/bearish visualization.
⚙️ Adjustable Parameters
Individual RSI, CCI, and MACD lengths and sources.
ATR length for volatility normalization.
Optional tanh-style compression with adjustable gain (to keep values in ±1 range).
Fully customizable colors and line widths for both bars and smoothing line.
🔔 Alerts
Triggered automatically when the composite crosses above or below zero, signaling potential trend reversals or momentum shifts.
💡 How to Use
Composite > 0 → Bullish momentum ↑
Composite < 0 → Bearish momentum ↓
A brightening line or bar = momentum accelerating.
A fading color = momentum weakening or reversal forming.
Combine with higher-timeframe trend filters (EMA, VWAP, Supertrend) for confirmation.
Squeeze Hour Frequency [CHE]Squeeze Hour Frequency (ATR-PR) — Standalone — Tracks daily squeeze occurrences by hour to reveal time-based volatility patterns
Summary
This indicator identifies periods of unusually low volatility, defined as squeezes, and tallies their frequency across each hour of the day over historical trading sessions. By aggregating counts into a sortable table, it helps users spot hours prone to these conditions, enabling better scheduling of trading activity to avoid or target specific intraday regimes. Signals gain robustness through percentile-based detection that adapts to recent volatility history, differing from fixed-threshold methods by focusing on relative lowness rather than absolute levels, which reduces false positives in varying market environments.
Motivation: Why this design?
Traders often face uneven intraday volatility, with certain hours showing clustered low-activity phases that precede or follow breakouts, leading to mistimed entries or overlooked calm periods. The core idea of hourly squeeze frequency addresses this by binning low-volatility events into 24 hourly slots and counting distinct daily occurrences, providing a historical profile of when squeezes cluster. This reveals time-of-day biases without relying on real-time alerts, allowing proactive adjustments to session focus.
What’s different vs. standard approaches?
- Reference baseline: Classical volatility tools like simple moving average crossovers or fixed ATR thresholds, which flag squeezes uniformly across the day.
- Architecture differences:
- Uses persistent arrays to track one squeeze per hour per day, preventing overcounting within sessions.
- Employs custom sorting on ratio arrays for dynamic table display, prioritizing top or bottom performers.
- Handles timezones explicitly to ensure consistent binning across global assets.
- Practical effect: Charts show a persistent table ranking hours by squeeze share, making intraday patterns immediately visible—such as a top hour capturing over 20 percent of total events—unlike static overlays that ignore temporal distribution, which matters for avoiding low-liquidity traps in crypto or forex.
How it works (technical)
The indicator first computes a rolling volatility measure over a specified lookback period. It then derives a relative ranking of the current value against recent history within a window of bars. A squeeze is flagged when this ranking falls below a user-defined cutoff, indicating the value is among the lowest in the recent sample.
On each bar, the local hour is extracted using the selected timezone. If a squeeze occurs and the bar has price data, the count for that hour increments only if no prior mark exists for the current day, using a persistent array to store the last marked day per hour. This ensures one tally per unique trading day per slot.
At the final bar, arrays compile counts and ratios for all 24 hours, where the ratio represents each hour's share of total squeezes observed. These are sorted ascending or descending based on display mode, and the top or bottom subset populates the table. Background shading highlights live squeezes in red for visual confirmation. Initialization uses zero-filled arrays for counts and negative seeds for day tracking, with state persisting across bars via variable declarations.
No higher timeframe data is pulled, so there is no repaint risk from external fetches; all logic runs on confirmed bars.
Parameter Guide
ATR Length — Controls the lookback for the volatility measure, influencing sensitivity to short-term fluctuations; shorter values increase responsiveness but add noise, longer ones smooth for stability — Default: 14 — Trade-offs/Tips: Use 10-20 for intraday charts to balance quick detection with fewer false squeezes; test on historical data to avoid over-smoothing in trending markets.
Percentile Window (bars) — Sets the history depth for ranking the current volatility value, affecting how "low" is defined relative to past; wider windows emphasize long-term norms — Default: 252 — Trade-offs/Tips: 100-300 bars suit daily cycles; narrower for fast assets like crypto to catch recent regimes, but risks instability in sparse data.
Squeeze threshold (PR < x) — Defines the cutoff for flagging low relative volatility, where values below this mark a squeeze; lower thresholds tighten detection for rarer events — Default: 10.0 — Trade-offs/Tips: 5-15 percent for conservative signals reducing false positives; raise to 20 for more frequent highlights in high-vol environments, monitoring for increased noise.
Timezone — Specifies the reference for hourly binning, ensuring alignment with market sessions — Default: Exchange — Trade-offs/Tips: Set to "America/New_York" for US assets; mismatches can skew counts, so verify against chart timezone.
Show Table — Toggles the results display, essential for reviewing frequencies — Default: true — Trade-offs/Tips: Disable on mobile for performance; pair with position tweaks for clean overlays.
Pos — Places the table on the chart pane — Default: Top Right — Trade-offs/Tips: Bottom Left avoids candle occlusion on volatile charts.
Font — Adjusts text readability in the table — Default: normal — Trade-offs/Tips: Tiny for dense views, large for emphasis on key hours.
Dark — Applies high-contrast colors for visibility — Default: true — Trade-offs/Tips: Toggle false in light themes to prevent washout.
Display — Filters table rows to focus on extremes or full list — Default: All — Trade-offs/Tips: Top 3 for quick scans of risky hours; Bottom 3 highlights safe low-squeeze periods.
Reading & Interpretation
Red background shading appears on bars meeting the squeeze condition, signaling current low relative volatility. The table lists hours as "H0" to "H23", with columns for daily squeeze counts, percentage share of total squeezes (summing to 100 percent across hours), and an arrow marker on the top hour. A summary row above details the peak count, its share, and the leading hour. A label at the last bar recaps total days observed, data-valid days, and top hour stats. Rising shares indicate clustering, suggesting regime persistence in that slot.
Practical Workflows & Combinations
- Trend following: Scan for hours with low squeeze shares to enter during stable regimes; confirm with higher highs or lower lows on the 15-minute chart, avoiding top-share hours post-news like tariff announcements.
- Exits/Stops: Tighten stops in high-share hours to guard against sudden vol spikes; use the table to shift to conservative sizing outside peak squeeze times.
- Multi-asset/Multi-TF: Defaults work across crypto pairs on 5-60 minute timeframes; for stocks, widen percentile window to 500 bars. Combine with volume oscillators—enter only if squeeze count is below average for the asset.
Behavior, Constraints & Performance
Logic executes on closed bars, with live bars updating counts provisionally but finalizing on confirmation; table refreshes only at the last bar, avoiding intrabar flicker. No security calls or higher timeframes, so no repaint from external data. Resources include a 5000-bar history limit, loops up to 24 iterations for sorting and totals, and arrays sized to 24 elements; labels and table are capped at 500 each for efficiency. Known limits: Skips hours without bars (e.g., weekends), assumes uniform data availability, and may undercount in sparse sessions; timezone shifts can alter profiles without warning.
Sensible Defaults & Quick Tuning
Start with ATR Length at 14, Percentile Window at 252, and threshold at 10.0 for broad crypto use. If too many squeezes flag (noisy table), raise threshold to 15.0 and narrow window to 100 for stricter relative lowness. For sluggish detection in calm markets, drop ATR Length to 10 and threshold to 5.0 to capture subtler dips. In high-vol assets, widen window to 500 and threshold to 20.0 for stability.
What this indicator is—and isn’t
This is a historical frequency tracker and visualization layer for intraday volatility patterns, best as a filter in multi-tool setups. It is not a standalone signal generator, predictive model, or risk manager—pair it with price action, news filters, and position sizing rules.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Thanks to Duyck
for the ma sorter
Session-Conditioned Regime ATRWhy this exists
Classic ATR is great—until the open. The first few bars often inherit overnight gaps and 24-hour noise that have nothing to do with the intraday regime you actually trade. That inflates early ATR, scrambles thresholds, and invites hyper-recency bias (“today is crazy!”) when it’s just the open being the open.
This tool was built to:
Separate session reality from 24h noise. Measure volatility only inside your defined session (e.g., NYSE 09:30–16:00 ET).
Judge candles against the current regime, not the last 2–3 bars. A rolling statistic from the last N completed sessions defines what “typical” means right now.
Label “large” and “small” objectively. Bars are colored only when True Range meaningfully departs from the session regime—no gut feel, no open-bar distortion (gap inclusion optional).
Overview
Purpose: objectively identify unusually big or small candles within the active trading session, compared to the recent session regime.
Use cases: volatility filters, entry/exit confirmation, session bias detection, adaptive sizing.
This indicator replaces generic ATR with a session-conditioned, regime-aware measure. It colors candles only when their True Range (TR) is abnormally large/small versus the last N completed sessions of the same session window.
How it works
Session gating: Only bars inside the selected session are evaluated (presets for NYSE, CME RTH, FX NY; custom supported).
Per-bar TR: TR = max(high, prevRef) − min(low, prevRef).
prevRef is the prior close for in-session bars.
First bar of the session can include the overnight gap (optional; default off).
Regime statistic: For any bar in session k, aggregate all in-session TRs from the previous N completed sessions (k−N … k−1), then compute Median (default) or Mean.
Today’s anchor: Running statistic from today’s session start → current bar (for context and the on-chart ratio).
Color logic:
Big if TR ≥ bigMult × RegimeStat
Small if TR ≤ smallMult × RegimeStat
Colored states: big bull, big bear, small bull, small bear.
Non-triggering bars retain the chart’s native colors.
Panel (top-right by default)
Regime ATR (Nd): session-conditioned statistic over the past N completed sessions.
Today ATR (anchored): running statistic for the current session.
Ratio (Today/Regime): intraday volatility vs regime.
Sample size n: number of bars used in the regime calculation.
Inputs
Session Preset: NYSE (09:30–16:00 ET), CME RTH (08:30–15:00 CT), FX NY (08:00–17:00 ET), Custom (session + IANA timezone).
Regime Window: number of completed sessions (default 5).
Statistic: Median (robust) or Mean.
Include Open Gap: include overnight gap in the first in-session bar’s TR (default off).
Big/Small thresholds: multipliers relative to RegimeStat (defaults: Big=1.5×, Small=0.67×).
Colors: four independent colors for big/small × bull/bear.
Panel position & text size.
Hidden outputs: expose RegimeStat, TodayStat, Ratio, and Z-score to other scripts.
Alerts
RegimeATR: BIG bar — triggers when a bar meets the “Big” condition.
RegimeATR: SMALL bar — triggers when a bar meets the “Small” condition.
Hidden outputs (for strategies/screeners)
RegimeATR_stat, TodayATR_stat, Today_vs_Regime_Ratio, BarTR_Zscore.
Notes & limitations
No look-ahead: calculations only use information available up to that bar. Historical colors reflect what would have been known then.
Warm-up: colors begin once there are at least N completed sessions; before that, regime is undefined by design.
Changing inputs (session window, multipliers, median/mean, gap toggle) recomputes the full series using the same rolling regime logic per bar.
Designed for standard candles. Styling respects existing chart colors when no condition triggers.
Practical tips
For a broader or tighter notion of “unusual,” adjust Big/Small multipliers.
Prefer Median in markets prone to outliers; use Mean if you want Z-score alignment with the panel’s regime mean/std.
Use the Ratio readout to spot compression/expansion days quickly (e.g., <0.7× = compressed session, >1.3× = expanded).
Roadmap
More session presets:
24h continuous (crypto, index CFDs).
23h/Globex futures (CME ETH with a 60-minute maintenance break).
Regional equities (LSE, Xetra, TSE), Asia/Europe/NY overlaps for FX.
Half-day/holiday templates and dynamic calendars.
Multi-regime comparison: track multiple overlapping regimes (e.g., RTH vs ETH for futures) and show separate stats/ratios.
Robust stats options: trimmed mean, MAD/Huber alternatives; optional percentile thresholds instead of fixed multipliers.
Subpanel visuals: rolling TodayATR and Ratio plots; optional Z-score ribbon.
Screener/strategy hooks: export boolean series for BIG/SMALL, plus a lightweight strategy template for backtesting entries/exits conditioned on regime volatility.
Performance/QOL: per-symbol presets, smarter warm-up, and finer control over sample caps for ultra-low TF charts.
Changelog
v0.9b (Beta)
Session presets (NYSE/CME RTH/FX NY/Custom) with timezone handling.
Panel enhancements: ratio + sample size n.
Four-state bar coloring (big/small × bull/bear).
Alerts for BIG/SMALL bars.
Hidden Z-score stream for downstream use.
Gap-in-TR toggle for the first in-session bar.
Disclaimer
For educational purposes only. Not investment advice. Validate thresholds and session settings across symbols/timeframes before live use.
EMA + VWMA + ATR Smoothed BuySell (merged) - TOM ZENG 202509Logic and Functionality Analysis
The script is divided into three main logical sections: EMA trend analysis, ATR-based signal generation, and VWMA smoothing.
1. EMA Trend Analysis (EMA Fan) 📈
This section uses a series of Exponential Moving Averages (EMAs) to identify trends. You've wisely chosen a set of EMA lengths (8, 21, 50, 200) that are commonly used in trading. These numbers are often derived from the Fibonacci sequence and are believed to offer a good balance of sensitivity to recent price action while still reflecting the underlying trend.
Purpose: The EMAs serve as dynamic support and resistance levels. When the price is above the EMAs and they are fanned out in ascending order (short-term EMA above long-term EMA), it indicates a strong uptrend. Conversely, a descending order indicates a downtrend.
Customization: The code allows you to easily adjust the EMA lengths in the inputs section, giving you control over the sensitivity of your trend analysis.
2. ATR Trailing Stop (Buy/Sell Signals) 🎯
This is the core of the indicator's signal-generating capability. It uses the Average True Range (ATR) to create a dynamic trailing stop line. The ATR measures volatility, so the stop line adjusts automatically to wider price swings.
Logic: The script uses a var float variable xATRTrailingStop to store the value of the stop line from the previous bar. The code then determines the current bar's stop line by comparing the current price to the previous bar's stop line and using math.max and math.min to smoothly move the line along with the trend.
Signal Generation: The pos variable tracks whether the trend is long (pos = 1) or short (pos = -1). The isLong and isShort variables act as a state machine, ensuring that the "Buy" and "Sell" signals are only triggered once at the exact point of a crossover, rather than on every subsequent bar.
Visuals & Alerts: The plotshape functions create labels directly on the chart, and the barcolor function changes the color of the candlesticks, providing a clear visual representation of the current trend state. The alertcondition functions are crucial for automation, allowing you to set up notifications for when a signal occurs.
3. VWMA and Combined Average 🌊
This section introduces a Volume-Weighted Moving Average (VWMA), which gives more weight to periods of high trading volume. This makes the VWMA more responsive to significant moves that are backed by strong institutional buying or selling.
Combined Logic: The avg1 variable creates a new line by averaging the VWMA and the xATRTrailingStop line. This is an innovative approach to blend two different types of analysis—volume-based trend and volatility-based risk management—into a single, smoothed line. It can act as an additional filter or a unique trading signal on its own.
Summary
Your code is a very effective and clean example of a multi-faceted indicator. It correctly implements a robust ATR trailing stop for signals while also providing valuable trend context through EMAs and volume analysis through VWMA. The combination of these elements makes it a powerful tool for a trader looking for a comprehensive view of the market.
Double Median ATR Bands | MisinkoMasterThe Double Median ATR Bands is a version of the SuperTrend that is designed to be smoother, more accurate while maintaining a good speed by combining the HMA smoothing technique and the median source.
How does it work?
Very simple!
1. Get user defined inputs:
=> Set them up however you want, for the result you want!
2. Calculate the Median of the source and the ATR
=> Very simple
3. Smooth the median with √length (for example if median length = 9, it would be smoothed over the length of 3 since 3x3 = 9)
4. Add ATR bands like so:
Upper = median + (atr*multiplier)
Lower = median - (atr*multiplier)
Trend Logic:
Source crossing over the upper band = uptrend
Source crossing below the lower band = downtrend
Enjoy G´s!
Bullish Divergence SMI Base & Trigger with ATR FilterDescription:
A bullish divergence indicator combining the Stochastic Momentum Index (SMI) and Average True Range (ATR) to pinpoint high-probability entries:
1. Base Arrow (Orange ▲):
• Marks every SMI %K / %D bullish crossover where %K < –70 (deep oversold)—the first half of the divergence setup.
• Each new qualifying crossover replaces the previous base, continuously “arming” the divergence signal.
• Configurable SMI lookbacks, oversold threshold, and a base timeout (default 100 days) to clear stale bases.
2. Trigger Arrow (Green ▲):
• Completes the bullish divergence: fires on the next SMI bullish crossover where %K > –60 and price has dropped below the base arrow’s close by at least N × ATR (default 1 × 14-day ATR).
• A dashed green line links the base and trigger to visually confirm the divergence.
• Resets after triggering, ready for a new divergence cycle.
Inputs:
• SMI %K Length, EMA Smoothing, %D Length
• Oversold Base Level (–70), Trigger Level (–60)
• ATR Length (14), ATR Multiplier (1.0)
• Base Timeout (100 days)
Ideal for any market, this study highlights genuine bullish divergences—oversold momentum crossovers that coincide with significant price reactions—before entering long trades.
EMA+ATR Band MTF Trend EntryThis is a Multi-Timeframe Trend Trading indicator strategy adapted from Sahil Rohmehtra’s Mentorship programme. The trading decision is made by first accessing the trend in higher timeframe (say Monthly) by using TWO EMAs. If the faster EMA (say 20 period) is above Slower EMA (say 50 period) and the price is above slower EMA then the trend is suitable for buyers. Similarly if faster EMA is below slow EMA and the price is below that then trend is suitable for sellers.
Once we access the trend in the higher timeframe we move to the lower timeframe (say Weekly) and access the 5-period RSI value. If RSI is below 30 then we can prepare for possible buy entry in lower (Daily) timeframe if entry conditions are met in daily timeframe. Similarly sell bias can be initiated when the higher timeframe EMA trend is down, daily RSI is above 70 and sell entry condition is met in daily timeframe. The RSI thresholds can be changed by the user.
Once we identified the RSI bias then wait for the confirmation candle in the lower timeframe (say 1 hour). In the entry timeframe we plot a band of 20 EMA of LOWs ± 1 ATR lines. Here,we wait for a candle to close above the 20 EMA of LOWs + 1 ATR for a buy signal with an increase in On Balance Volume (OBV) value. Similarly for sell signal we should get a candle close below the 20 EMA of LOWs - 1 ATR with corresponding change in OBV. This candle is the signal candle.
Once we get a Buy or Sell signal the corresponding stop loss is the nearest LOW - 1 ATR or HIGH + 1 ATR. The ATR scaling may be changed by the user. Now if another candle closes above the high of the buy signal candle then enter on buy. If the low of the buy signal candle is broken then it is a potential short-term sell entry. Similarly if another candle closes below the sell signal candle then enter short and if there is a close above high of the signal candle then it is a potential buy entry.
Range Filter + ATR Strategy (Low Drawdown)Key Features for Low Drawdown:
Range Filter: Identifies trends while filtering out market noise
ATR-based Position Sizing: Adjusts position size based on volatility to risk a fixed percentage of capital
Trailing Stops: Uses ATR-based trailing stops to lock in profits and limit losses
Conservative Risk Parameters: Defaults to 1% risk per trade (adjustable)
Trend Confirmation: Requires two consecutive closes above/below the range filter
How to Use:
The strategy enters long when price is above the upper range filter for two consecutive bars
Enters short when price is below the lower range filter for two consecutive bars
Uses ATR to size positions appropriately for current volatility
Implements trailing stops based on ATR to protect profits
Optimization Tips:
Adjust the Range Filter period based on your timeframe
Modify the risk percentage (1% is conservative)
Tweak the ATR multiple for trailing stops (1.5 is moderate)
Consider adding a time-based exit if drawdown is still too high
timer/tr/atr [keypoems]Session and Instant Volatility Ticker
What it actually does:
- Session ATR – Reports the historical (e.g. “0200-0600”) average true range of the past x sessions, reports the +1Stdev value.
- Real-time ATR feed – streams the current ATR value every tick.
- Ticker line – Sess. ATR +1Stdev | Current ATR | Previous TR | 🕒 Time-left-in-bar |
Think of it as a volatility check: a single glance tells you if the average candle size is compatible with your usual stop or not.
Open Source.
ChopFlow ATR Scalp StrategyA lean, high-velocity scalp framework for NQ and other futures that blends trend clarity, volume confirmation, and adaptive exits to give you precise, actionable signals—no cluttered bands or lagging indicators.
⸻
🔍 Overview
This strategy locks onto rapid intraday moves by:
• Filtering for directional momentum with the Choppiness Index (CI)
• Confirming conviction via On-Balance Volume (OBV) against its moving average
• Automatically sizing stops and targets with a multiple of the Average True Range (ATR)
It’s designed for scalp traders who need clean, timely entries without wading through choppy noise.
⸻
⚙️ Key Features & Inputs
1. ATR Length & Multiplier
• Controls exit distances based on current volatility.
2. Choppiness Length & Threshold
• Measures trend strength; only fires when the market isn’t “stuck in the mud.”
3. OBV SMA Length
• Smoothes volume flow to confirm genuine buying or selling pressure.
4. Custom Session Hours
• Avoid overnight gaps or low-liquidity periods.
All inputs are exposed for rapid tuning to your preferred scalp cadence.
🚀 How It Works
1. Long Entry triggers when:
• CI < threshold (strong trend)
• OBV > its SMA (positive volume flow)
• You’re within the defined session
2. Short Entry mirrors the above (CI < threshold, OBV < SMA)
3. Exit uses ATR × multiplier for both stop-loss and take-profit
⸻
🎯 Usage Tips
• Start with defaults (ATR 14, multiplier 1.5; CI 14, threshold 60; OBV SMA 10).
• Monitor signal frequency, then tighten/loosen CI or OBV look-back as needed.
• Pair with a fast MA crossover or price-action trigger if you want even sharper timing.
• Backtest across different sessions (early open vs. power hours) to find your edge.
⸻
⚠️ Disclaimer
This script is provided “as-is” for educational and research purposes. Always paper-trade any new setup extensively before deploying live capital, and adjust risk parameters to your personal tolerance.
⸻
Elevate your scalp game with ChopFlow ATR—where trend, volume, and volatility converge for clear, confident entries. Happy scalping!
Smart Breakout with ATR Stop-LossThe Smart Breakout indicator combines a classic 20-day Donchian channel breakout with a tight trailing stop, drawing green lines and “ENTRY” labels at the bar after a valid breakout, and red lines and “EXIT” label at the bar after a stop-loss breach.
By default it uses the chart’s timeframe to compute ATR and stops, but you can flip on Daily lock to freeze both ATR and price reads at the daily resolution—so your stops stay the same whether you view at 1s, 15 m, 4h or lower frequency bars.
Key features:
20-day Donchian breakout: entry when price closes above the highest high of the previous 20 bars
2 × ATR(14) trailing stop: initialized at entry and raised only when the new (close – 2 × ATR) exceeds the prior stop
Daily lock option: Ensures all ATR and close values are calculated on the daily timeframe, keeping stop levels consistent across resolutions
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
DD Keltner Channels (1-3 ATR)This indicator creates Keltner Channels with 1, 2, and 3 ATR multipliers, allowing you to visualize different volatility levels around a moving average.
It's specifically created for people taking the "Deep Dip Buy" stock trading course, and attempts to provide a ready-to-go solution for those struggling with configuring the default Keltner indicator on TradingView to suit their needs for the course.
Any input from students or the instructor is welcome to improve this indicator so it offers more value to those looking to learn how to trade.
Features:
- Uses SMA or EMA as the base (20-period default)
- Displays 6 lines: +3, +2, +1, -1, -2, and -3 ATR levels
- Color-coded for easy identification:
• +/-1 ATR: Green
• +/-2 ATR: Light Gray (thin)
• +/-3 ATR: Dark Gray (thick)
Volume with Sessions, SMA, and ATR Pine Script creates a custom volume indicator with several features, including:
SMA of Volume: It calculates the simple moving average (SMA) of the volume, which helps identify trends and determine if the current volume is above or below the average.
ATR (Average True Range): It calculates the ATR, which measures market volatility over a defined period.
Bullish/Bearish Volume Coloring: The script colors the volume bars depending on whether the price is moving up (bullish) or down (bearish), and whether the volume is above or below the SMA of volume.
Session Highlighting: It defines two major trading sessions:
NYSE (New York Stock Exchange) session from 9:30 AM to 4:00 PM Eastern Time.
LSE (London Stock Exchange) session from 8:00 AM to 4:30 PM GMT. These sessions are highlighted with background colors for easy identification.
Plotting: The volume is plotted as a histogram with varying colors depending on price movement and volume relative to its SMA. The ATR is also plotted as a purple line, and the SMA of volume is displayed as an orange line.
Background Colors: Background colors are applied during the NYSE and LSE sessions to visually differentiate between these trading periods.
Here's a breakdown of each section:
Key Inputs:
smaLength and atrLength: User-defined values for the lengths of the SMA and ATR calculations.
Main Calculations:
smaVolume: The SMA of the volume over the user-defined length (smaLength).
atrValue: The Average True Range over the user-defined length (atrLength).
Color Logic for Volume Bars:
If the current close is higher than the previous close, the volume is considered bullish, and the bar is colored green. If the volume is above the SMA, it’s a darker green; otherwise, it’s a lighter shade.
If the current close is lower than the previous close, the volume is considered bearish, and the bar is colored red. If the volume is above the SMA, it’s a darker red; otherwise, it’s a lighter red.
Plotting:
The script plots the volume as a histogram with dynamic coloring.
The SMA of the volume is plotted as a line.
ATR is plotted as a purple line for reference.
Background Color Highlighting:
The background is colored green during the NYSE session and blue during the LSE session.
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
BB ATR Fractal MMThe Bollinger Bands + ATR with Fractal indicator is a powerful combination of Bollinger Bands, ATR (Average True Range), and Fractal to help identify market volatility and potential entry/exit points on the chart.
Bollinger Bands help to assess the market’s volatility by calculating upper and lower bands based on the simple moving average (SMA) and standard deviation. It’s an excellent tool for identifying overbought and oversold conditions.
ATR (Average True Range) is used to measure market volatility. It helps determine how much the price is moving, and it can be used to adjust the Bollinger Bands, creating bands that reflect the current volatility more accurately.
Fractal helps to identify peaks and troughs in the market, supporting decision-making by highlighting potential reversal points. Fractals mark regions where price may reverse direction, making it easier to spot possible trade opportunities.
How to Use:
Bollinger Bands Upper and Lower Bands: These bands help to identify overbought or oversold conditions. If the price breaks above the upper band, the market may be overbought. If the price breaks below the lower band, the market may be oversold.
ATR: It indicates the volatility level of the market. When the market shows large volatility (ATR increases), the Bollinger Bands expand to reflect higher price swings.
Fractal: Arrows appear at the market’s peaks and troughs, helping identify entry points for buying (at fractal lows) or selling (at fractal highs). These signals can help you make trading decisions based on potential price reversals.
SMA + RSI + Volume + ATR StrategySMA + RSI + Volume + ATR Strategy
1. Indicators Used:
SMA (Simple Moving Average): This is a trend-following indicator that calculates the average price of a security over a specified period (50 periods in this case). It's used to identify the overall trend of the market.
RSI (Relative Strength Index): This measures the speed and change of price movements. It tells us if the market is overbought (too high) or oversold (too low). Overbought is above 70 and oversold is below 30.
Volume: This is the amount of trading activity. A higher volume often indicates strong interest in a particular price move.
ATR (Average True Range): This measures volatility, or how much the price is moving in a given period. It helps us adjust stop losses and take profits based on market volatility.
2. Conditions for Entering Trades:
Buy Signal (Green Up Arrow):
Price is above the 50-period SMA (indicating an uptrend).
RSI is below 30 (indicating the market might be oversold or undervalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
Sell Signal (Red Down Arrow):
Price is below the 50-period SMA (indicating a downtrend).
RSI is above 70 (indicating the market might be overbought or overvalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
3. Take Profit & Stop Loss:
Take Profit: When a trade is made, the strategy will set a target price at a certain percentage above or below the entry price (1.5% in this case) to automatically exit the trade once that target is hit.
Stop Loss: If the price goes against the position, a stop loss is set at a percentage below or above the entry price (0.5% in this case) to limit losses.
4. Execution of Trades:
When the buy condition is met, the strategy will enter a long position (buying).
When the sell condition is met, the strategy will enter a short position (selling).
5. Visual Representation:
Green Up Arrow: Appears on the chart when the buy condition is met.
Red Down Arrow: Appears on the chart when the sell condition is met.
These arrows help you see at a glance when the strategy suggests you should buy or sell.
In Summary:
This strategy uses a combination of trend-following (SMA), momentum (RSI), volume, and volatility (ATR) to decide when to buy or sell a stock. It looks for opportunities when the market is either oversold (buy signal) or overbought (sell signal) and makes sure there’s enough volume and volatility to back up the move. It also includes take-profit and stop-loss levels to manage risk.
Adaptive Fractal Grid Scalping StrategyThis Pine Script v6 component implements an "Adaptive Fractal Grid Scalping Strategy" with an added volatility threshold feature.
Here's how it works:
Fractal Break Detection: Uses ta.pivothigh and ta.pivotlow to identify local highs and lows.
Volatility Clustering: Measures volatility using the Average True Range (ATR).
Adaptive Grid Levels: Dynamically adjusts grid levels based on ATR and user-defined multipliers.
Directional Bias Filter: Uses a Simple Moving Average (SMA) to determine trend direction.
Volatility Threshold: Introduces a new input to specify a minimum ATR value required to activate the strategy.
Trade Execution Logic: Places limit orders at grid levels based on trend direction and fractal levels, but only when ATR exceeds the volatility threshold.
Profit-Taking and Stop-Loss: Implements profit-taking at grid levels and a trailing stop-loss based on ATR.
How to Use
Inputs: Customize the ATR length, SMA length, grid multipliers, trailing stop multiplier, and volatility threshold through the input settings.
Visuals: The script plots fractal points and grid levels on the chart for easy visualization.
Trade Signals: The strategy automatically places buy/sell orders based on the detected fractals, trend direction, and volatility threshold.
Profit and Risk Management: The script includes logic for taking profits and setting stop-loss levels to manage trades effectively.
This strategy is designed to capitalize on micro-movements during high volatility and avoid overtrading during low-volatility trends. Adjust the input parameters to suit your trading style and market conditions.
RSI + ADX + ATR 18-01-25Combining RSI (Relative Strength Index), ADX (Average Directional Index), and ATR (Average True Range) creates a synergistic approach to technical analysis. This powerful trio covers momentum, trend strength, and volatility, providing comprehensive insights into market conditions. Here's a deeper exploration of their combined results:
1. Momentum Assessment with RSI
Purpose: RSI measures the speed and magnitude of recent price changes to determine overbought or oversold levels.
Benefit in Combination:
When RSI indicates overbought (above 70) or oversold (below 30) levels, it signals a potential reversal or correction.
However, these signals can be false in strongly trending markets, which is why ADX is used alongside it.
2. Trend Strength Confirmation with ADX
Purpose: ADX confirms the presence and strength of a trend.
Benefit in Combination:
If RSI shows a potential reversal but ADX indicates a strong trend (above 25), the trend is likely to continue, and RSI signals may need to be approached with caution.
Conversely, if ADX is below 20 (weak trend), RSI signals are more likely to indicate genuine reversals, as the market lacks a strong directional push.
3. Volatility Analysis with ATR
Purpose: ATR evaluates the level of price volatility.
Benefit in Combination:
High ATR values indicate volatile conditions where prices can move significantly; this helps in setting wider stop-loss levels to avoid premature exits.
Low ATR values suggest quieter markets, where tighter stop-losses and profit targets are more suitable.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
Multi-Timeframe ATRsThis Multi-Timeframe ATR Indicator displays the Average True Range (ATR) values from multiple timeframes on a single chart, allowing traders to assess market volatility across different time periods. The indicator calculates and plots the ATR for the 1-hour, 3-hour, 4-hour, 1-day, and 2-day timeframes, with the option to toggle each timeframe on or off based on user preferences. By visualizing these ATR values, traders can identify potential price movement expectations for various timeframes and better understand how volatility is shifting across the market. This tool is handy for traders who want to gauge volatility over different time periods and incorporate it into their trading strategies.
By evaluating higher timeframes when entering trades, a trader can better understand market conditions. This insight helps the trader make informed decisions about whether to remain in the trade for a longer period.
The indicator is fully customizable, with color-coded plots for each timeframe and optional labels that display the ATR values directly on the chart. It is ideal for traders looking to add volatility insights to their technical analysis without cluttering their charts.
Supertrend StrategyThe Supertrend Strategy was created based on the Supertrend and Relative Strength Index (RSI) indicators, widely respected tools in technical analysis. This strategy combines these two indicators to capture market trends with precision and reliability, looking for optimizing exit levels at oversold or overbought price levels.
The Supertrend indicator identifies trend direction based on price and volatility by using the Average True Range (ATR). The ATR measures market volatility by calculating the average range between an asset’s high and low prices over a set period. It provides insight into price fluctuations, with higher ATR values indicating increased volatility and lower values suggesting stability. The Supertrend Indicator plots a line above or below the price, signaling potential buy or sell opportunities: when the price closes above the Supertrend line, an uptrend is indicated, while a close below the line suggests a downtrend. This line shifts as price movements and volatility levels change, acting as both a trailing stop loss and trend confirmation.
To enhance the Supertrend strategy, the Relative Strength Index (RSI) has been added as an exit criterion. As a momentum oscillator, the RSI indicates overbought (usually above 70) or oversold (usually below 30) conditions. This integration allows trades to close when the asset is overbought or oversold, capturing gains before a possible reversal, even if the percentage take profit level has not been reached. This mechanism aims to prevent losses due to market reversals before the Supertrend signal changes.
### Key Features
1. **Entry criteria**:
- The strategy uses the Supertrend indicator calculated by adding or subtracting a multiple of the ATR from the closing price, depending on the trend direction.
- When the price crosses above the Supertrend line, the strategy signals a long (buy) entry. Conversely, when the price crosses below, it signals a short (sell) entry.
- The strategy performs a reversal if there is an open position and a change in the direction of the supertrend occurs
2. **Exit criteria**:
- Take profit of 30% (default) on the average position price.
- Oversold (≤ 5) or overbought (≥ 95) RSI
- Reversal when there is a change in direction of the Supertrend
3. **No Repainting**:
- This strategy is not subject to repainting, as long as the timeframe configured on your chart is the same as the supertrend timeframe .
4. **Position Sizing by Equity and risk management**:
- This strategy has a default configuration to operate with 35% of the equity. At the time of opening the position, the supertrend line is typically positioned at about 12 to 16% of the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity can be adjusted by the user according to their risk management.
5. **Backtest results**:
- This strategy was subjected to deep backtesting and operations in replay mode, including transaction fees of 0.12%, and slippage of 5 ticks.
- The past results in deep backtest and replay mode were compatible and profitable (Variable results depending on the take profit used, supertrend and RSI parameters). However, it should be noted that few operations were evaluated, since the currency in question has been created for a short time and the frequency of operations is relatively small.
- Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
Default Settings
Chart timeframe: 2h
Supertrend Factor: 3.42
ATR period: 14
Supertrend timeframe: 2 h
RSI timeframe: 15 min
RSI Lenght: 5 min
RSI Upper limit: 95
RSI Lower Limit: 5
Take Profit: 30%
BYBIT:1000000MOGUSDT.P
