ORDER BLCOK custom strategy# OB Matrix Strategy - Documentation
**Version:** 1.0
**Author:** HPotter
**Date:** 31/07/2017
The **OB Matrix Strategy** is based on the identification of **bullish and bearish Order Blocks** and the management of conditional orders with multiple Take Profit (TP) and Stop Loss (SL) levels. It uses trend filters, ATR, and percentage-based risk management.
---
## 1. Main Parameters
### Strategy
- `initial_capital`: 50
- `default_qty_type`: percentage of capital
- `default_qty_value`: 10
### Money Management
- `rr_threshold`: minimum Risk/Reward threshold to open a trade
- `risk_percent`: percentage of capital to risk per trade (default 2%)
- `maxPendingBars`: maximum number of bars for a pending order
- `maxBarsOpen`: maximum number of bars for an open position
- `qty_tp1`, `qty_tp2`, `qty_tp3`: quantity percentages for multiple TPs
---
## 2. Order Block Identification
### Order Block Parameters
- `obLookback`: number of bars to identify an Order Block
- `obmode`: method to calculate the block (`Full` or `Breadth`)
- `obmiti`: method to determine block mitigation (`Close`, `Wick`, `Avg`)
- `obMaxBlocks`: maximum number of Order Blocks displayed
### Main Variables
- `bullBlocks`: array of bullish blocks
- `bearBlocks`: array of bearish blocks
- `last_bull_volume`, `last_bear_volume`: volume of the last block
- `dom_block`: dominant block type (Bullish/Bearish/None)
- `block_strength`: block strength (normalized volume)
- `price_distance`: distance between current price and nearest block
---
## 3. Visual Parameters
- `Width`: line thickness for swing high/low
- `amountOfBoxes`: block grid segments
- `showBorder`: show block borders
- `borderWidth`: width of block borders
- `showVolume`: display volume inside blocks
- `volumePosition`: vertical position of volume text
Customizable colors:
- `obHighVolumeColor`, `obLowVolumeColor`, `obBearHighVolumeColor`, `obBearLowVolumeColor`
- `obBullBorderColor`, `obBearBorderColor`
- `obBullFillColor`, `obBearFillColor`
- `volumeTextColor`
---
## 4. Screener Table
- `showScreener`: display the screener table
- `tablePosition`: table position (`Top Left`, `Top Right`, `Bottom Left`, `Bottom Right`)
- `tableSize`: table size (`Small`, `Normal`, `Large`)
The table shows:
- Symbol, Timeframe
- Type and status of Order Block
- Number of retests
- Bullish and bearish volumes
---
## 5. Trend Filters
- EMA as a trend filter (`emaPeriod`, default 223)
- `bullishTrend` if close > EMA
- `bearishTrend` if close < EMA
---
## 6. ATR and Swing Points
- ATR calculated with a customizable period (`atrLength`)
- Swing High/Low for SL/TP calculation
- `f_getSwingTargets` function to calculate SL and TP based on direction
---
## 7. Trade Logic
### Buy Limit on Bullish OB
- Conditions:
- New bullish block
- Uptrend
- RR > threshold (`rr_threshold`)
- SL: `bullishOBPrice * (1 - atr * atrMultiplier)`
- Multiple TPs: TP1 (50%), TP2 (80%), TP3 (100% max)
- Quantity calculation based on percentage risk
### Sell Limit on Bearish OB
- Conditions:
- New bearish block
- Downtrend
- RR > threshold (`rr_threshold`)
- SL: `bearishOBPrice * (1 + atr * atrMultiplier)`
- Multiple TPs: TP1 (50%), TP2 (80%), TP3 (100% max)
- Quantity calculation based on percentage risk
---
## 8. Order Management and Timeout
- Close pending orders after `maxPendingBars` bars
- Close open positions after `maxBarsOpen` bars
- Label management for open orders
---
## 9. Alert Conditions
- `bull_touch`: price inside maximum bullish volume zone
- `bear_touch`: price inside maximum bearish volume zone
- `bull_reject`: confirmation of bullish zone rejection
- `bear_reject`: confirmation of bearish zone rejection
- `new_bull`: new bullish block
- `new_bear`: new bearish block
---
## 10. Level Calculation
- Swing levels based on selected timeframe (`SelectPeriod`)
- `xHigh` and `xLow` for S1 and R1 calculation
- Levels plotted on chart
---
## 11. Take Profit / Stop Loss
- Extended horizontal lines (`extendBars`) to visualize TP and SL
- Customizable colors (`tpColor`, `slColor`)
---
## 12. Notes
- Complete script based on Pine Script v5
- Advanced graphical management with boxes, lines, labels
- Dynamically displays volumes and Order Blocks
- Integrated internal screener
---
### End of Documentation
指標和策略
LW Outside Day Strategy[SpeculationLab]This strategy is inspired by the “Outside Day” concept introduced by Larry Williams in Long-Term Secrets to Short-Term Trading, and has been extended with configurable risk management tools and realistic backtesting parameters.
Concept
The “Outside Day” is a classic price action pattern that reflects strong market rejection or continuation pressure.
An Outside Bar occurs when the current bar’s high exceeds the previous high and the low falls below the previous low.
A body-size filter ensures only significant candles are included.
Entry Logic
Buy setup: Price closes below the previous low (bullish rejection).
Sell setup: Price closes above the previous high (bearish rejection).
Only confirmed bars are used (no intrabar signals).
Stop-Loss Modes
Prev Low/High: Uses the previous swing point ± ATR-based buffer.
ATR: Dynamic stop based on Average True Range × multiplier.
Fixed Pips: User-defined fixed distance (for forex testing).
Take-Profit Modes
Prev High/Low (PHL): Exits near the opposite swing.
Risk-Reward (RR): Targets a user-defined multiple of the stop distance (default = 2 : 1).
Following Price Open (FPO): Exits on the next bar’s open if price opens in profit (used to test overnight price continuation).
Risk Management & Backtest Settings
Default risk per trade is set at 10% of account equity (user-adjustable).
Commission = 0.1% and slippage = 2 ticks are applied to simulate realistic conditions.
For reliable statistics, test on data that yields over 100 trades.
Suitable for daily and 4-hour timeframes across stocks, forex, and crypto markets.
Visual Elements
Green and red triangles show entry signals.
Stop-loss (red) and take-profit (green) reference lines are drawn for clarity.
Optional alerts notify when a valid setup forms.
Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice or guarantee profits.
Always backtest thoroughly and manage your own risk.
Enhancements over Classic Outside Bar Models
Adjustable stop and target logic with ATR and buffer multipliers.
“Following Price Open” exit logic for realistic day-end management.
Optimized to avoid repainting and bar-confirmation issues.
Built with realistic trading costs and position sizing.
策略逻辑
外包线识别
当日最高价高于前一日最高价，且当日最低价低于前一日最低价，即形成外包线。
同时过滤掉较小实体的 K 线，仅保留实体显著大于前一根的形态。
方向过滤
收盘价低于前一日最低价 → 视为买入信号。
收盘价高于前一日最高价 → 视为卖出信号。
止损设置（可选参数）
前低/高止损：以形态前低/前高为止损，带有缓冲倍数。
ATR 止损：根据平均波动率（ATR）动态调整。
固定点数止损：按照用户设定的点数作为止损范围。
止盈设置（可选参数）
前高/低止盈（PHL）：以前高/前低为目标。
固定盈亏比（RR）：根据用户设定的风险回报比自动计算。
隔夜开盘（FPO）：若次日开盘价高于进场价（多单）或低于进场价（空单），则平仓。
信号标记
在图表中标注买入/卖出信号（三角形标记）。
绘制止损与目标位参考线。
使用说明
适用周期：建议用于 日线图（Daily）。
适用市场：股票、外汇、加密货币等各类市场均可。
提示：此策略为历史研究与学习用途，不构成投资建议。实际交易请结合自身风险管理。
Commodity Pulse Matrix (CPM) [WavesUnchained] [Strategy]Commodity Pulse Matrix (CPM) - Strategy Version
⚠️ Development Status
ACTIVE DEVELOPMENT - This strategy is currently under heavy development and optimization. The risk management settings, entry/exit logic, and parameter tuning are still being refined and are NOT yet satisfactory for live trading.
Current development areas:
Stop-loss and take-profit optimization
Position sizing and risk management
Entry timing and signal filtering
Backtest validation across different market conditions
⚠️ Use for testing and backtesting only - NOT recommended for live trading yet!
For detailed information about the underlying indicator logic, signals, and analysis methods, please refer to the Commodity Pulse Matrix (CPM) indicator description.
Overview
The CPM Strategy is an automated trading system based on the Commodity Pulse Matrix indicator. It converts the indicator's multi-timeframe confluence signals into executable trades with dynamic ATR-based risk management.
Strategy Core Features
Signal Sources
The strategy trades based on:
Strong Buy/Sell signals from the CPM indicator
Multi-timeframe alignment (configurable: 3/3, 2/3, or score-only)
EMA-200 trend filter (prevents counter-trend entries)
Dynamic signal cooldown (5-8 bars)
Optional reversal zone signals (triple-confirmed)
Risk Management (ATR-Based)
Stop-Loss & Take-Profit
Stop-Loss: 2.5x ATR (default) - Dynamic distance based on volatility
Take-Profit: 4.0x ATR (default) - Risk/Reward ratio of 1.6:1
ATR Length: 14 periods (adjustable)
Both SL and TP adjust to current market volatility
Trailing Stop (Optional)
Enabled by default
Trails at 2.5x ATR distance
Protects profits in trending moves
Can be disabled for fixed SL/TP only
Position Management
Trade Direction Filter
Both Directions (default) - Trade both Long and Short
Long Only - Only enter long positions
Short Only - Only enter short positions
Cooldown After Exit
Default: 3 bars minimum after closing a position
Prevents immediate re-entry (whipsaw protection)
Adjustable from 0 (disabled) to any number of bars
Signal Filtering
Signal Mode (Timeframe Consensus)
Strict (3/3 TFs): All 3 timeframes must agree - Most conservative
Majority (2/3 TFs): At least 2 of 3 timeframes agree - Balanced (default)
Flexible (Score Only): Overall score threshold only - Most signals
Optional Filters
Min ABS(overallScore): Only trade when confluence score meets minimum (default: 0 = disabled)
Confirmed Bar Only: Wait for bar close before entry (prevents repainting) - Recommended ON
Strategy Settings Guide
For Conservative Trading (Lower Risk)
Signal Mode: "Strict (3/3 TFs)"
Stop-Loss: 3.0x ATR or higher
Take-Profit: 5.0x ATR or higher
Trailing Stop: Enabled
Cooldown: 5-10 bars
Min Score: 8.0 or higher
For Aggressive Trading (More Signals)
Signal Mode: "Flexible (Score Only)"
Stop-Loss: 2.0x ATR
Take-Profit: 3.0x ATR
Trailing Stop: Optional
Cooldown: 0-3 bars
Min Score: 4.0 or disabled
For Balanced Trading (Recommended Starting Point)
Signal Mode: "Majority (2/3 TFs)"
Stop-Loss: 2.5x ATR
Take-Profit: 4.0x ATR
Trailing Stop: Enabled
Cooldown: 3 bars
Min Score: 6.0-8.0
TradingView Strategy Tester Settings
Essential Settings to Configure:
Properties Tab
Initial Capital: Set to realistic account size
Order Size: Use "% of Equity" (e.g., 10-25% per trade)
Commission: Set realistic commission (e.g., 0.05% for crypto, 0.1% for stocks)
Slippage: Add realistic slippage (1-3 ticks for liquid markets)
Verify "Recalculate: On Every Tick" is DISABLED (for realistic backtests)
Inputs Tab
Adjust ATR multipliers for your market
Set appropriate cooldown period
Choose signal mode based on desired trade frequency
Enable/disable trailing stop
Configure directional filter if needed
Backtesting Recommendations
Before Using This Strategy:
Test across multiple markets - What works for one commodity may not work for another
Test different timeframes - Strategy behavior changes significantly with TF
Test different market conditions - Trending vs ranging markets
Validate performance metrics - Win rate, profit factor, max drawdown, Sharpe ratio
Forward test on paper account - Before risking real capital
Key Metrics to Monitor:
Win Rate (aim for >40% minimum)
Profit Factor (aim for >1.5)
Max Drawdown (should be acceptable for your risk tolerance)
Sharpe Ratio (higher is better, >1.0 is good)
Average Trade (should be positive after commissions/slippage)
Known Limitations
Range-bound markets: May produce more whipsaws despite filters
Low volatility: ATR-based stops may be too tight
High volatility: ATR-based stops may be too wide
News events: Strategy cannot account for fundamental shocks
Signal timing: Entry timing is still being optimized
Indicator vs Strategy
When to use the Indicator:
- Manual trading with discretion
- Confluence analysis and timing
- Multiple signal validation
- Learning market structure
When to use the Strategy:
- Automated backtesting
- System validation
- Parameter optimization
- Performance measurement
⚠️ The indicator provides richer information and context than the strategy can execute!
Technical Details
Pine Script v6
Non-repainting: Uses confirmed bars for HTF data
Strategy type: Long/Short with dynamic stops
Risk management: ATR-based (adaptive to volatility)
Position sizing: Configured in Strategy Tester
Pyramiding: Default 1 (no adding to positions)
Important Notes
⚠️ Strategy parameters are still under optimization - Current settings may not be optimal for all markets or timeframes
⚠️ Backtest thoroughly before live trading - Test across different market conditions and timeframes
⚠️ Risk management is critical - Use appropriate position sizing (1-2% risk per trade recommended)
⚠️ Market conditions change - A strategy that works in trending markets may fail in ranging markets
⚠️ Commission and slippage matter - Always include realistic costs in backtests
✅ Start with conservative settings and optimize gradually
✅ Paper trade before going live
✅ Monitor performance and adjust as needed
✅ Never risk more than you can afford to lose
Disclaimer
Educational and testing purposes only. Not financial advice.
This strategy is provided as-is for backtesting and educational purposes. Past performance is not indicative of future results. Trading involves substantial risk of loss. The developer is not responsible for any losses incurred from using this strategy. Always do your own research, backtest thoroughly, and consult with a qualified financial advisor before making trading decisions.
NEVER use this strategy with real money until:
You have thoroughly backtested it on your specific market and timeframe
You understand all parameters and their impact
You have forward tested it on a paper account
You are comfortable with the maximum drawdown and risk profile
The strategy has been marked as production-ready by the developer
Version
v1.2 - Strategy Adapter (Active Development)
Based on: Commodity Pulse Matrix v1.2 Indicator
Last Updated: 2025-10-10
For detailed indicator documentation, see the Commodity Pulse Matrix (CPM) indicator description.
Larry Williams Bonus Track PatternThis strategy trades the day immediately following an Inside Day, under specific directional and timing conditions. It is designed for daily-based setups but executed on intraday charts to ensure orders are placed exactly at the open of the following day, rather than at the daily bar close.
Entry Conditions
Only trades on Monday, Thursday, or Friday.
The previous day must be an Inside Day (its high is lower than the prior high and its low is higher than the prior low).
The bar before the Inside Day must be bullish (close > open).
On the following day (t):
The daily open must be below both the Inside Day’s high and the highest high of the two days before that.
A buy stop is placed at the highest high of the three previous days (Inside Day and the two days before it).
If the new day’s open is already above that level (gap up), the strategy enters long immediately at the open.
Exit Rules
Stop Loss: Fixed, defined in points or percentage (user input).
FPO (First Profitable Open): the position is closed at the first daily open after the entry day where the open price is above the average entry price (the first profitable open).
Notes
The script must be applied on an intraday timeframe (e.g., 15-minute or 1-hour) so that the strategy can:
Detect the Inside Day pattern using daily data (request.security).
Execute orders in real time at the next day’s open.
Running it directly on the daily timeframe will delay executions by one bar due to Pine Script’s evaluation model.
DeepSeek_Multi-Timeframe EMA Strategy BTC_1HStrategy Description: "DeepSeek_Multi-Timeframe EMA Strategy BTC_1H"
This is a trading strategy for TradingView that uses a multi-timeframe Exponential Moving Average (EMA) crossover system to generate trade signals on a 1-hour Bitcoin (BTC) chart.
Core Logic & Trading Rules
The strategy's logic is based on the alignment of two different EMA timeframes:
Higher Timeframe (HTF) Trend Filter: A slower EMA (default: 50) is calculated on a higher timeframe (default: 1D). This defines the primary, long-term trend.
Lower Timeframe (LTF) Signal Trigger: A faster EMA (default: 20) is calculated on the current chart timeframe (1H). This is used for precise entry and exit timing.
Long Entry Conditions (All must be true):
Trend Alignment: The LTF EMA (20) must be above the HTF EMA (50).
Price Position: The current closing price must be above the HTF EMA (50), confirming the bullish trend.
Entry Trigger: The closing price must cross above the LTF EMA (20).
Exit Condition (for Long Positions):
The strategy closes any open long position when:
The LTF EMA (20) is below the HTF EMA (50) (counter-trend), and
The closing price crosses below the LTF EMA (20).
Key Features & Configuration
Strategy Configuration: It uses a strategy script, which can perform backtesting and forward-testing.
Initial Capital: $1,000.
Order Sizing: 100% of equity per trade (default_qty_value = 100).
Pyramiding: Only 1 active position is allowed at a time (pyramiding = 1).
Commission: 0.1% is factored into calculations.
Order Execution: Orders are executed at the close of the 1-hour bar where the signal appears (process_orders_on_close=true).
Visualization:
The HTF EMA (50) is plotted as a thick purple line.
The LTF EMA (20) is plotted as an orange line.
Green upward triangles below the bar indicate Long Entry signals.
Red downward triangles above the bar indicate Exit (Short) signals.
Summary
In essence, this strategy aims to "buy the dip" within a larger uptrend. It waits for the higher timeframe to be bullish, and then enters on a short-term pullback to the faster moving average. It exits the trade when the shorter-term trend turns bearish relative to the longer-term trend. It does not take short/sell positions; it only goes long or is out of the market.
Larry Williams Oops StrategyThis strategy is a modern take on Larry Williams’ classic Oops setup. It trades intraday while referencing daily bars to detect opening gaps and align entries with the prior day’s direction. Risk is managed with day-based stops, and—unlike the original—all positions are closed at the end of the session (or at the last bar’s close), not at a fixed profit target or the first profitable open.
Entry Rules
Long setup (bullish reversion): Today opens below yesterday’s low (down gap) and yesterday’s candle was bearish. Place a buy stop at yesterday’s low + Filter (ticks).
Short setup (bearish reversion): Today opens above yesterday’s high (up gap) and yesterday’s candle was bullish. Place a sell stop at yesterday’s high − Filter (ticks).
Longs are only taken on down-gap days; shorts only on up-gap days.
Protective Stop
If long, stop loss trails the current day’s low.
If short, stop loss trails the current day’s high.
Exit Logic
Positions are force-closed at the end of the session (in the last bar), ensuring no overnight exposure. There is no take-profit; only stop loss or end-of-day flat.
Notes
This strategy is designed for intraday charts (minutes/seconds) using daily data for gaps and prior-day direction.
Longs/shorts can be enabled or disabled independently.
Aggressive Options Trade Strategy - CALLS (2025+) - ASALEHMomentum-driven options strategy built for call buyers. Uses RSI, MACD, and EMA alignment with volatility filters to spot aggressive long setups and manage exits with profit targets and trailing stops.
Larry Williams - Smash Day (SL/TP in %)This strategy implements Larry Williams’ “Smash Day” reversal concept on any symbol and timeframe (daily is the classic). A Smash Day is a bar that closes beyond a recent extreme and then potentially reverses on the next session.
MA Crossover Strategy V6//@version=6
strategy("MA Crossover Strategy V6", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// === Inputs ===
shortLength = input.int(9, title="Short MA Length", minval=1)
longLength = input.int(21, title="Long MA Length", minval=1)
useEMA = input.bool(false, title="Use EMA Instead of SMA")
// === Moving Averages ===
shortMA = useEMA ? ta.ema(close, shortLength) : ta.sma(close, shortLength)
longMA = useEMA ? ta.ema(close, longLength) : ta.sma(close, longLength)
// === Plot MAs ===
plot(shortMA, color=color.orange, title="Short MA", linewidth=2)
plot(longMA, color=color.blue, title="Long MA", linewidth=2)
// === Entry Conditions ===
longCondition = ta.crossover(shortMA, longMA)
shortCondition = ta.crossunder(shortMA, longMA)
// === Strategy Logic ===
if (longCondition)
strategy.entry("Long", strategy.long)
if (shortCondition)
strategy.entry("Short", strategy.short)
// === Optional: Plot Buy/Sell Signals ===
plotshape(longCondition, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(shortCondition, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
the Father, the Son, and the Holy SpiritThis is a tool used to find great trades! It's the Father, the Son, and the Holy Spirit.
Short Only Bot (3Commas Webhook Uyumlu)Short işlem açmaya ce 3commans ile uyumlu hacim odaklı indikatör. halka açık herkes kullanabilir.
Trend following system WeeklySystem 1 — Weekly Trend Flip Strategy
System 1 (Weekly) is a trend-following strategy designed to trigger only on weekly timeframe signals.
It aims to catch clean trend shifts and avoid lower-timeframe noise.
Uses fast and slow EMAs with ATR filtering to detect strong weekly momentum
Enters long on a bullish flip of the EMAs
Exits on a bearish flip or neutral zone (optional)
Ideal for position traders, swing traders, and investors who want fewer, higher-quality signals
Signals are generated only on weekly candle closes
📊 Tip: This strategy works best on assets with clear medium-term trends. You can use it alongside daily or intraday systems for additional confirmation.
SAN_Price Action BOS Strategy Price Action strategy with Break of structure including 20-30EMA crossover with perfect BUY/SELL alert is a beauty of this one
Final Compact RSI • MACD • CCI — One Pane + WMA GateFinal Edit - Compact RSI • MACD • CCI — One Pane + WMA Gate
Rebound Sigma Pro - StrategyOverview
Rebound Sigma Pro is a mean-reversion indicator that detects statistically oversold conditions in trending markets.
It helps traders identify potential short-term rebounds based on momentum exhaustion and volatility-adjusted entry zones.
Concept
The indicator combines two quantitative components:
Short-term momentum to detect short-term exhaustion
Trend filter to ensure setups align with the long-term direction
When a stock in an uptrend becomes temporarily oversold, a limit-entry signal is plotted.
The trade is then tracked until short-term conditions normalize or a time-based exit occurs.
Visual Signals
Green Triangle: Suggests placing a limit order for the next session
Green Circle: Confirms entry was filled
Red Triangle: Signals an exit for the next session’s open
Orange Background: Pending order
Green Background: Position active
Red Background: Exit phase
Yellow Line: Entry reference price
User Inputs
Limit Entry (% below previous close) – Default 1 %
Use Limit Entry – Switch between limit or market entries
Enable Time Exit – Optional holding-period constraint
Maximum Holding Days
All other internal parameters (momentum length, filters) are pre-configured.
Alerts
Limit Order Signal: New setup detected
Entry Confirmed: Order filled
Exit Signal: Exit expected next day
Usage
Designed for liquid equities and ETFs
Works best in confirmed uptrends
Backtesting encouraged to adapt parameters per symbol and timeframe
Notes
Not an automated strategy; manual order execution required
Past behavior does not imply future performance
Always apply sound position sizing and risk management
Disclaimer
This indicator is provided for educational and analytical purposes only.
It does not constitute financial advice or performance assurance.
RoboScalp-X: Precision Intraday Engine [NASDAQ Futures]RoboScalp-X is a precision-engineered intraday scalping and breakout strategy designed for U.S. futures markets — specifically Micro E-mini NASDAQ-100 (MNQ).
It uses volatility-based breakout detection, strict stop-loss and target logic, and is optimized for short-duration trend scalps.
💹 Performance Snapshot
Tested on MNQ (Jun 2025 – Oct 2025)
Total Return: +2,348%
Profit Factor: 1.83
Win Rate: 78% (170 / 217 trades)
Max Drawdown: 50,500 USD
🧠 Why RoboScalp-X
This system is ideal for traders who want automated precision trading in volatile U.S. indices, focusing on quick, high-accuracy entries.
It’s built for algorithmic consistency — targeting small yet frequent profits while maintaining tight risk control.
📬 Get This Strategy or Build Your Own
If you’d like to buy, customize, or develop a similar strategy for Futures, Forex, Crypto, or Indian markets, reach out here:
🌐 Upwork Profile - www.upwork.com
📧 manakthorat@gmail.com
⚠️ Disclaimer: This strategy is for educational and research purposes only. Market conditions may affect results; always use appropriate risk management and forward testing before applying to live trading.
RoboScalp-X: Precision Intraday EngineRoboScalp-Buy 1.0 is a systematic scalping strategy built for the Indian indices such as NIFTY 50 and BANKNIFTY on the 15-minute timeframe.
💹 Performance Highlights:
Tested on NIFTY 50 (2022–2025)
Profit Factor: 1.61
Win Rate: 76%
Total Return: +203%
📈 Designed for traders who want automated, data-backed scalping logic with high accuracy and risk management.
📬 Want to Get This Strategy or a Custom Version?
If you’d like to buy, customize, or develop a similar strategy for your own trading, feel free to reach out:
🌐 Upwork Profile - www.upwork.com
📧 manakthorat@gmail.com
⚠️ For educational and research purposes only. Past performance does not guarantee future results.
Traders Club RSI, EMA Strategy 🔻 Arun Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Arun R5.41🔻 Arun Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Robo scalp-Buy-1.0Profitable gold strategy.
use on 3 min time frame and default values for best results.
Adaptive Chikou Strategy - Level 1This strategy is based on the Ichimoku cloud system and the power of delaying the signal. I changed how the averages are calculated to better detect the range areas.
The strategy uses this concept to determine the market regime, whether the price is below or above its delayed signal, and acts accordingly:
Bull (green) – when the price is above the average of the highs, delayed, the strategy favors long entries.
Bear (red) – when the price is below the average of the lows delayed, the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 4 key parameters.
The first parameter controls the lookback period for the highest and lowest functions.
The second controls how much we delay the signal of these 2 functions.
The third adjusts how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The fourth parameter is similar to the third, but for bear conditions. The bigger it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Percent Rank Strategy - Level 1This strategy is based on the Percent Rank math, a statistical measure that evaluates how the current price compares to its historical prices over a specified lookback period.
In simple terms, Percent Rank tells you the percentile position of the current price within a recent window, for example, a value of 80% means the price is higher than 80% of the previous prices in that period, while 20% means it’s lower than 80% of them.
The strategy uses this concept to determine the market regime, whether price is high, low, or neutral relative to its recent range, and acts accordingly:
Bull (green) – when the price percent rank is usually above 50% the price is normally high, and the strategy favors long entries.
Bear (red) – when the price percent rank is usually below 50% the price is normally low, and the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 3 key parameters.
The first parameter controls the maximum lookback period for the percent rank array and so the maximum cycle length.
The second controls how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The third parameter is similar to the second, but for bear conditions. The smaller it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Correlation Cycle Strategy - Level 1This strategy is based on John Ehlers idea of the correlation cycle, and that markets often oscillate. They move up and down in cycles, though not perfectly sinusoidal, they can be approximated by a sinusoidal wave. This script measures the strength of the correlation between price and a range of ideal sine wave components of different periods. By doing this, we estimate which cycle length the market is most currently following and from that, we find the phase to learn in which part of the cycle we are in.
Bull (green) – when price is at the bottom of the sinusoidal going to the top (positive phases), the strategy favors long entries.
Bear (red) – when price is at the top of the sinusoidal going down to the bottom (negative phases), the strategy favors short entries.
Range (brown) – when the phase is in the transition zones we detect range conditions and no trades are initiated.
The transition between these regimes depends mainly on 3 key parameters.
The first parameter controls the maximum lookback period for correlation detection and so the maximum cycle length.
The second controls how much range is detected in bull conditions, it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The third parameter is similar to the second, but for bear conditions. The bigger it is, the less bear and the more range conditions are detected
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
