Uptrick X PineIndicators: Z-Score Flow StrategyThis strategy is based on the Z-Score Flow Indicator developed by Uptrick. Full credit for the original concept and logic goes to Uptrick.
The Z-Score Flow Strategy combines statistical mean-reversion logic with trend filtering, RSI confirmation, and multi-mode trade execution, offering a flexible and structured approach to trading both reversals and trend continuations.
Core Concepts Behind Z-Score Flow
1. Z-Score Mean Reversion Logic
The Z-score measures how far current price deviates from its statistical mean, in standard deviations.
A high positive Z-score (e.g. > 2) suggests price is overbought and may revert downward.
A low negative Z-score (e.g. < -2) suggests price is oversold and may revert upward.
The strategy uses Z-score thresholds to trigger signals when price deviates far enough from its mean.
2. Trend Filtering with EMA
To prevent counter-trend entries, the strategy includes a trend filter based on a 50-period EMA:
Only allows long entries if price is below EMA (mean-reversion in downtrends).
Only allows short entries if price is above EMA (mean-reversion in uptrends).
3. RSI Confirmation and Lockout System
An RSI smoothing mechanism helps confirm signals and avoid whipsaws:
RSI must be below 30 and rising to allow buys.
RSI must be above 70 and falling to allow sells.
Once a signal occurs, it is "locked out" until RSI re-enters the neutral zone (30–70).
This avoids multiple signals in overextended zones and reduces overtrading.
Entry Signal Logic
A buy or sell is triggered when:
Z-score crosses below (buy) or above (sell) the threshold.
RSI smoothed condition is met (oversold and rising / overbought and falling).
The trend condition (EMA filter) aligns.
A cooldown period has passed since the last opposite trade.
This layered approach helps ensure signal quality and timing precision.
Trade Modes
The strategy includes three distinct trade modes to adapt to various market behaviors:
1. Standard Mode
Trades are opened using the Z-score + RSI + trend filter logic.
Each signal must pass all layered conditions.
2. Zero Cross Mode
Trades are based on the Z-score crossing zero.
This mode is useful in trend continuation setups, rather than mean reversion.
3. Trend Reversal Mode
Trades occur when the mean slope direction changes, i.e., basis line changes color.
Helps capture early trend shifts with less lag.
Each mode can be customized for long-only, short-only, or long & short execution.
Visual Components
1. Z-Score Mean Line
The basis (mean) line is colored based on slope direction.
Green = bullish slope, Purple = bearish slope, Gray = flat.
A wide shadow band underneath reflects current trend momentum.
2. Gradient Fill to Price
A gradient zone between price and the mean reflects:
Price above mean = bearish zone with purple overlay.
Price below mean = bullish zone with teal overlay.
This visual aid quickly reveals market positioning relative to equilibrium.
3. Signal Markers
"𝓤𝓹" labels appear for buy signals.
"𝓓𝓸𝔀𝓷" labels appear for sell signals.
These are colored and positioned according to trend context.
Customization Options
Z-Score Period & Thresholds: Define sensitivity to price deviations.
EMA Trend Filter Length: Filter entries with long-term bias.
RSI & Smoothing Periods: Fine-tune RSI confirmation conditions.
Cooldown Period: Prevent signal spam and enforce timing gaps.
Slope Index: Adjust how far back to compare mean slope.
Visual Settings: Toggle mean lines, gradients, and more.
Use Cases & Strategy Strengths
1. Mean-Reversion Trading
Ideal for catching pullbacks in trending markets or fading overextended price moves.
2. Trend Continuation or Reversal
With multiple trade modes, traders can choose between fading price extremes or trading slope momentum.
3. Signal Clarity and Risk Control
The combination of Z-score, RSI, EMA trend, and cooldown logic provides high-confidence signals with built-in filters.
Conclusion
The Z-Score Flow Strategy by Uptrick X PineIndicators is a versatile and structured trading system that:
Fuses statistical deviation (Z-score) with technical filters.
Provides both mean-reversion and trend-based entry logic.
Uses visual overlays and signal labels for clarity.
Prevents noise-driven trades via cooldown and lockout systems.
This strategy is well-suited for traders seeking a data-driven, multi-condition entry framework that can adapt to various market types.
Full credit for the original concept and indicator goes to Uptrick.
Trend Analysis
Smart Money Pivot Strategy [Jason Kasei]This strategy is designed to identify key pivot points (Pivot High and Pivot Low) in the market and leverage the "Smart Money" concept to capture price breakout opportunities. It supports both long and short trades, offering customizable stop-loss (SL) and take-profit (TP) settings, while visually plotting pivot points and breakout signals on the chart.
Core Features
Pivot Point Detection:
Utilizes ta.pivothigh and ta.pivotlow functions to detect the highest (Pivot High) and lowest (Pivot Low) points within a specified period (default: 20 bars).
Trading Signals:
Long Signal: Triggered when the price breaks above a previous Pivot High, indicating a potential uptrend.
Short Signal: Triggered when the price breaks below a previous Pivot Low, indicating a potential downtrend.
How It Works
Detects Pivot High (PH) and Pivot Low (PL) over the specified period and records their price and time.
Triggers a long entry when the price breaks above a Pivot High and a short entry when it falls below a Pivot Low.
Sets exit conditions automatically based on predefined SL and TP percentages after entry.
Plots breakout points and levels on the chart for analysis.
Considerations
The strategy relies on accurate pivot point detection; adjust the period parameter based on market volatility.
In highly volatile markets, consider widening the stop loss to avoid frequent triggering.
Combine with other indicators or analysis methods to validate signals and avoid blind trading.
Multi-EMA Crossover StrategyMulti-EMA Crossover Strategy
This strategy uses multiple exponential moving average (EMA) crossovers to identify bullish trends and execute long trades. The approach involves progressively stronger signals as different EMA pairs cross, indicating increasing bullish momentum. Each crossover triggers a long entry, and the intensity of bullish sentiment is reflected in the color of the bars on the chart. Conversely, bearish trends are represented by red bars.
Strategy Logic:
First Long Entry: When the 1-day EMA crosses above the 5-day EMA, it signals initial bullish momentum.
Second Long Entry: When the 3-day EMA crosses above the 10-day EMA, it confirms stronger bullish sentiment.
Third Long Entry: When the 5-day EMA crosses above the 20-day EMA, it indicates further trend strength.
Fourth Long Entry: When the 10-day EMA crosses above the 40-day EMA, it suggests robust long-term bullish momentum.
The bar colors reflect these conditions:
More blue bars indicate stronger bullish sentiment as more short-term EMAs are above their longer-term counterparts.
Red bars represent bearish conditions when short-term EMAs are below longer-term ones.
Example: Bitcoin Trading on a Daily Timeframe
Bullish Scenario:
Imagine Bitcoin is trading at $30,000 on March 31, 2025:
First Signal: The 1-day EMA crosses above the 5-day EMA at $30,000. This suggests initial upward momentum, prompting a small long entry.
Second Signal: A few days later, the 3-day EMA crosses above the 10-day EMA at $31,000. This confirms strengthening bullish sentiment; another long position is added.
Third Signal: The 5-day EMA crosses above the 20-day EMA at $32,500, indicating further upward trend development; a third long entry is executed.
Fourth Signal: Finally, the 10-day EMA crosses above the 40-day EMA at $34,000. This signals robust long-term bullish momentum; a fourth long position is entered.
Bearish Scenario:
Suppose Bitcoin reverses from $34,000 to $28,000:
The 1-day EMA crosses below the 5-day EMA at $33,500.
The 3-day EMA dips below the 10-day EMA at $32,000.
The 5-day EMA falls below the 20-day EMA at $30,000.
The final bearish signal occurs when the 10-day EMA drops below the 40-day EMA at $28,000.
The bars turn increasingly red as bearish conditions strengthen.
Advantages of This Strategy:
Progressive Confirmation: Multiple crossovers provide layered confirmation of trend strength.
Visual Feedback: Bar colors help traders quickly assess market sentiment and adjust positions accordingly.
Flexibility: Suitable for trending markets like Bitcoin during strong rallies or downturns.
Limitations:
Lagging Signals: EMAs are lagging indicators and may react slowly to sudden price changes.
False Breakouts: Crossovers in choppy markets can lead to whipsaws or false signals.
This strategy works best in trending markets and should be combined with additional risk management techniques, e.g., stop loss or optimal position sizes (Kelly Criterion).
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
Apex Trend SniperApex Trend Sniper - Advanced Trend Trading Strategy (Pine Script v5)
🚀 Overview
The Apex Trend Sniper is an advanced, fully automated trend-following strategy designed for crypto, forex, and stock markets. It combines momentum analysis, trend confirmation, volume validation, and adaptive risk management to capture high-probability trades. Unlike many strategies, this system is 100% non-repainting, ensuring reliable backtesting and real-time execution.
🔹 How This Strategy Works (Indicator Mashup)
The Apex Trend Sniper leverages multiple indicators to create a robust multi-layered confirmation system:
1️⃣ Trend Identification with RMI & McGinley Dynamic
📌 What It Does: Identifies the dominant trend and prevents trading against market conditions.
✔ McGinley Dynamic Baseline:
A highly adaptive moving average that dynamically reacts to price changes.
Price above the baseline = bullish trend.
Price below the baseline = bearish trend.
✔ Relative Momentum Index (RMI):
A refined Relative Strength Index (RSI) that filters out weak trends.
Above 50 = bullish confirmation.
Below 50 = bearish confirmation.
2️⃣ Trend Strength Confirmation with Vortex Indicator
📌 What It Does: Confirms that a detected trend is strong and valid.
✔ Vortex Indicator (VI):
Measures directional movement and trend strength.
A bullish trend is confirmed when VI+ > VI-.
A bearish trend is confirmed when VI- > VI+.
3️⃣ Volume Spike Detection for Trade Validation
📌 What It Does: Ensures that trades are placed only during strong market participation.
✔ Volume Confirmation:
A trade signal is only valid if volume spikes above the moving average.
Helps avoid false breakouts and weak trends.
4️⃣ Entry & Exit Strategy with Multi-Level Take Profits
📌 What It Does: Enters trades only when all conditions align and manages risk effectively.
✔ Entry Conditions (All must be met):
Price is above/below McGinley Dynamic.
RMI confirms trend direction.
Vortex indicator confirms trend strength.
Volume spike is detected.
✔ Exit Conditions:
Take Profit 1 (TP1): Secures 50% of the position at the first price target.
Take Profit 2 (TP2): Closes the remaining position at the second price target.
Exit Before Reversal: If an opposite trend signal appears, the position is closed early.
Trend Weakness Exit: If momentum weakens, the trade is exited automatically.
📌 Strategy Customization
🔧 Fully customizable to fit any trading style:
✔ McGinley Dynamic Length – Adjust baseline sensitivity.
✔ RMI & Vortex Settings – Fine-tune momentum filters.
✔ Volume Thresholds – Modify spike detection for better accuracy.
✔ Take Profit Levels – Set TP1 & TP2 based on market volatility.
📢 How to Use Apex Trend Sniper
1️⃣ Apply the strategy to any TradingView chart.
2️⃣ Customize the settings to fit your trading approach.
3️⃣ Use the backtest report to evaluate performance.
4️⃣ Monitor the dashboard to track real-time trade execution.
📌 Recommended Timeframes & Markets
✔ Best Markets:
✅ Crypto (BTC, ETH, SOL, etc.)
✅ Forex (EUR/USD, GBP/USD, JPY/USD, etc.)
✅ Stocks & Indices (S&P500, NASDAQ, etc.)
✔ Optimal Timeframes:
✅ Swing Trading: 1H – 4H – 1D
✅ Intraday & Scalping: 5M – 15M – 30M
📌 Backtest Settings for Realistic Performance
✔ Initial Capital: $1000 (or more for scaling).
✔ Commission: 0.05% (to simulate exchange fees).
✔ Slippage: 1-2 (to account for execution delay).
✔ Date Range: Test across different market conditions.
📢 TradingView Disclaimer
📌 This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk, and past performance does not guarantee future results. Always test strategies thoroughly before applying them in a live market. Users are responsible for their own trading decisions.
🚀 Why Choose Apex Trend Sniper?
✅ Non-Repainting – No misleading signals.
✅ Multi-Layer Confirmation – Reduces false trades.
✅ Volume & Trend Strength Validation – Ensures high-probability entries.
✅ Adaptive Risk Management – Secures profits while maximizing trends.
✅ Versatile Across Markets & Timeframes – Works for crypto, forex, and stocks.
📢 Start Trading Smarter with Apex Trend Sniper! 🚀
🔗 Try it now on TradingView and optimize your trend-following strategy. 🔥
Vortex Sniper XVortex Sniper X – Trend-Following Strategy
🔹 Purpose
Vortex Sniper X is a trend-following strategy designed to identify strong market trends and enter trades in the direction of momentum. By combining multiple technical indicators, this strategy helps traders filter out false signals and only take trades with high confidence.
🔹 Indicator Breakdown
1️⃣ Vortex Indicator (Trend Direction & Strength)
Identifies the trend direction based on the relationship between VI+ and VI-.
Bullish Signal: VI+ crosses above VI-.
Bearish Signal: VI- crosses above VI+.
The wider the gap between VI+ and VI-, the stronger the trend’s momentum.
2️⃣ Relative Momentum Index (RMI – Momentum Confirmation)
Confirms whether price momentum supports the trend direction.
Long confirmation: RMI is rising and above the threshold.
Short confirmation: RMI is falling and below the threshold.
Filters out weak trends that lack sufficient momentum.
3️⃣ McGinley Dynamic (Trend Baseline Filter)
A dynamic moving average that adjusts to market volatility for smoother trend identification.
Long trades only if price is above the McGinley Dynamic.
Short trades only if price is below the McGinley Dynamic.
Prevents trading in choppy or sideways markets.
🔹 Strategy Logic & Trade Execution
✅ Entry Conditions
A trade is executed only when all three indicators confirm alignment:
Trend Confirmation: McGinley Dynamic defines the trend direction.
Vortex Signal: VI+ > VI- (bullish) or VI- > VI+ (bearish).
Momentum Confirmation: RMI must agree with the trend direction.
✅ Exit Conditions
Trend Reversal: If the opposite trade condition is met, the current position is closed.
Trend Weakness: If the trend weakens (detected via trend shifts), the position is exited.
🔹 Take-Profit System
The strategy follows a multi-stage profit-taking approach to secure gains:
Take Profit 1 (TP1): 50% of the position is closed at the first target.
Take Profit 2 (TP2): The remaining 50% is closed at the second target.
🔹 Risk Management (Important Notice)
🔴 This strategy does NOT include a stop-loss by default.
Trades rely on trend reversals or early exits to close positions.
Users should manually configure a stop-loss if risk management is required.
💡 Suggested risk management options:
Set a stop-loss at a recent swing high/low or an important support/resistance level.
Adjust position sizing according to personal risk tolerance.
🔹 Default Backtest Settings
To ensure realistic backtesting, the following settings are used:
Initial Capital: $1,000
Position Sizing: 10% of equity per trade
Commission: 0.05%
Slippage: 1 pip
Date Range: Can be adjusted for different market conditions
🔹 How to Use This Strategy
📌 To get the best results, follow these steps:
Apply the strategy to any TradingView chart.
Backtest before using it in live conditions.
Adjust the indicator settings as needed.
Set a manual stop-loss if required for your trading style.
Use this strategy in trending markets—avoid sideways conditions.
⚠️ Disclaimer
🚨 Trading involves risk. This strategy is for educational purposes only and should not be considered financial advice.
Past performance does not guarantee future results.
Users are responsible for managing their own risk.
Always backtest strategies before applying them in live trading.
🚀 Final Notes
Vortex Sniper X provides a structured approach to trend-following trading, ensuring:
✔ Multi-indicator confirmation for higher accuracy.
✔ Momentum-backed entries to avoid weak trends.
✔ Take-profit targets to secure gains.
✔ No repainting—historical performance aligns with live execution.
This strategy does not include a stop-loss, so users must apply their own risk management methods.
EMA 10/55/200 - LONG ONLY MTF (4h with 1D & 1W confirmation)Title: EMA 10/55/200 - Long Only Multi-Timeframe Strategy (4h with 1D & 1W confirmation)
Description:
This strategy is designed for trend-following long entries using a combination of exponential moving averages (EMAs) on the 4-hour chart, confirmed by higher timeframe trends from the daily (1D) and weekly (1W) charts.
🔍 How It Works
🔹 Entry Conditions (4h chart):
EMA 10 crosses above EMA 55 and price is above EMA 55
OR
EMA 55 crosses above EMA 200
OR
EMA 10 crosses above EMA 500
These entries indicate short-term momentum aligning with medium/long-term trend strength.
🔹 Confirmation (multi-timeframe alignment):
Daily (1D): EMA 55 is above EMA 200
Weekly (1W): EMA 55 is above EMA 200
This ensures that we only enter long trades when the higher timeframes support an uptrend, reducing false signals during sideways or bearish markets.
🛑 Exit Conditions
Bearish crossover of EMA 10 below EMA 200 or EMA 500
Stop Loss: 5% below entry price
⚙️ Backtest Settings
Capital allocation per trade: 10% of equity
Commission: 0.1%
Slippage: 2 ticks
These are realistic conditions for crypto, forex, and stocks.
📈 Best Used On
Timeframe: 4h
Instruments: Trending markets like BTC/ETH, FX majors, or growth stocks
Works best in volatile or trending environments
⚠️ Disclaimer
This is a backtest tool and educational resource. Always validate on demo accounts before applying to real capital. Do your own due diligence.
Buy on 5% dip strategy with time adjustment
This script is a strategy called "Buy on 5% Dip Strategy with Time Adjustment 📉💡," which detects a 5% drop in price and triggers a buy signal 🔔. It also automatically closes the position once the set profit target is reached 💰, and it has additional logic to close the position if the loss exceeds 14% after holding for 230 days ⏳.
Strategy Explanation
Buy Condition: A buy signal is triggered when the price drops 5% from the highest price reached 🔻.
Take Profit: The position is closed when the price hits a 1.22x target from the average entry price 📈.
Forced Sell Condition: If the position is held for more than 230 days and the loss exceeds 14%, the position is automatically closed 🚫.
Leverage & Capital Allocation: Leverage is adjustable ⚖️, and you can set the percentage of capital allocated to each trade 💸.
Time Limits: The strategy allows you to set a start and end time ⏰ for trading, making the strategy active only within that specific period.
Code Credits and References
Credits: This script utilizes ideas and code from @QuantNomad and jangdokang for the profit table and algorithm concepts 🔧.
Sources:
Monthly Performance Table Script by QuantNomad:
ZenAndTheArtOfTrading's Script:
Strategy Performance
This strategy provides risk management through take profit and forced sell conditions and includes a performance table 📊 to track monthly and yearly results. You can compare backtest results with real-time performance to evaluate the strategy's effectiveness.
The performance numbers shown in the backtest reflect what would have happened if you had used this strategy since the launch date of the SOXL (the Direxion Daily Semiconductor Bull 3x Shares ETF) 📅. These results are not hypothetical but based on actual performance from the day of the ETF’s launch 📈.
Caution ⚠️
No Guarantee of Future Results: The results are based on historical performance from the launch of the SOXL ETF, but past performance does not guarantee future results. It’s important to approach with caution when applying it to live trading 🔍.
Risk Management: Leverage and capital allocation settings are crucial for managing risk ⚠️. Make sure to adjust these according to your risk tolerance ⚖️.
Trendline Breaks with Multi Fibonacci Supertrend StrategyTMFS Strategy: Advanced Trendline Breakouts with Multi-Fibonacci Supertrend
Elevate your algorithmic trading with institutional-grade signal confluence
Strategy Genesis & Evolution
This advanced trading system represents the culmination of a personal research journey, evolving from my custom " Multi Fibonacci Supertrend with Signals " indicator into a comprehensive trading strategy. Built upon the exceptional trendline detection methodology pioneered by LuxAlgo in their " Trendlines with Breaks " indicator, I've engineered a systematic framework that integrates multiple technical factors into a cohesive trading system.
Core Fibonacci Principles
At the heart of this strategy lies the Fibonacci sequence application to volatility measurement:
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval = 0.01, step = 0.01)
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval = 0.01, step = 0.01)
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval = 0.01, step = 0.01)
These precise Fibonacci ratios create a dynamic volatility envelope that adapts to changing market conditions while maintaining mathematical harmony with natural price movements.
Dynamic Trendline Detection
The strategy incorporates LuxAlgo's pioneering approach to trendline detection:
// Pivotal swing detection (inspired by LuxAlgo)
pivot_high = ta.pivothigh(swing_length, swing_length)
pivot_low = ta.pivotlow(swing_length, swing_length)
// Dynamic slope calculation using ATR
slope = atr_value / swing_length * atr_multiplier
// Update trendlines based on pivot detection
if bool(pivot_high)
upper_slope := slope
upper_trendline := pivot_high
else
upper_trendline := nz(upper_trendline) - nz(upper_slope)
This adaptive trendline approach automatically identifies key structural market boundaries, adjusting in real-time to evolving chart patterns.
Breakout State Management
The strategy implements sophisticated state tracking for breakout detection:
// Track breakouts with state variables
var int upper_breakout_state = 0
var int lower_breakout_state = 0
// Update breakout state when price crosses trendlines
upper_breakout_state := bool(pivot_high) ? 0 : close > upper_trendline ? 1 : upper_breakout_state
lower_breakout_state := bool(pivot_low) ? 0 : close < lower_trendline ? 1 : lower_breakout_state
// Detect new breakouts (state transitions)
bool new_upper_breakout = upper_breakout_state > upper_breakout_state
bool new_lower_breakout = lower_breakout_state > lower_breakout_state
This state-based approach enables precise identification of the exact moment when price breaks through a significant trendline.
Multi-Factor Signal Confluence
Entry signals require confirmation from multiple technical factors:
// Define entry conditions with multi-factor confluence
long_entry_condition = enable_long_positions and
upper_breakout_state > upper_breakout_state and // New trendline breakout
di_plus > di_minus and // Bullish DMI confirmation
close > smoothed_trend // Price above Supertrend envelope
// Execute trades only with full confirmation
if long_entry_condition
strategy.entry('L', strategy.long, comment = "LONG")
This strict requirement for confluence significantly reduces false signals and improves the quality of trade entries.
Advanced Risk Management
The strategy includes sophisticated risk controls with multiple methodologies:
// Calculate stop loss based on selected method
get_long_stop_loss_price(base_price) =>
switch stop_loss_method
'PERC' => base_price * (1 - long_stop_loss_percent)
'ATR' => base_price - long_stop_loss_atr_multiplier * entry_atr
'RR' => base_price - (get_long_take_profit_price() - base_price) / long_risk_reward_ratio
=> na
// Implement trailing functionality
strategy.exit(
id = 'Long Take Profit / Stop Loss',
from_entry = 'L',
qty_percent = take_profit_quantity_percent,
limit = trailing_take_profit_enabled ? na : long_take_profit_price,
stop = long_stop_loss_price,
trail_price = trailing_take_profit_enabled ? long_take_profit_price : na,
trail_offset = trailing_take_profit_enabled ? long_trailing_tp_step_ticks : na,
comment = "TP/SL Triggered"
)
This flexible approach adapts to varying market conditions while providing comprehensive downside protection.
Performance Characteristics
Rigorous backtesting demonstrates exceptional capital appreciation potential with impressive risk-adjusted metrics:
Remarkable total return profile (1,517%+)
Strong Sortino ratio (3.691) indicating superior downside risk control
Profit factor of 1.924 across all trades (2.153 for long positions)
Win rate exceeding 35% with balanced distribution across varied market conditions
Institutional Considerations
The strategy architecture addresses execution complexities faced by institutional participants with temporal filtering and date-range capabilities:
// Time Filter settings with flexible timezone support
import jason5480/time_filters/5 as time_filter
src_timezone = input.string(defval = 'Exchange', title = 'Source Timezone')
dst_timezone = input.string(defval = 'Exchange', title = 'Destination Timezone')
// Date range filtering for precise execution windows
use_from_date = input.bool(defval = true, title = 'Enable Start Date')
from_date = input.time(defval = timestamp('01 Jan 2022 00:00'), title = 'Start Date')
// Validate trading permission based on temporal constraints
date_filter_approved = time_filter.is_in_date_range(
use_from_date, from_date, use_to_date, to_date, src_timezone, dst_timezone
)
These capabilities enable precise execution timing and market session optimization critical for larger market participants.
Acknowledgments
Special thanks to LuxAlgo for the pioneering work on trendline detection and breakout identification that inspired elements of this strategy. Their innovative approach to technical analysis provided a valuable foundation upon which I could build my Fibonacci-based methodology.
This strategy is shared under the same Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license as LuxAlgo's original work.
Past performance is not indicative of future results. Conduct thorough analysis before implementing any algorithmic strategy.
ThinkTech AI SignalsThink Tech AI Strategy
The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data.
Usage
The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups.
Settings
The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours.
Style
The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart.
This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
Liquidity + Internal Market Shift StrategyLiquidity + Internal Market Shift Strategy
This strategy combines liquidity zone analysis with the internal market structure, aiming to identify high-probability entry points. It uses key liquidity levels (local highs and lows) to track the price's interaction with significant market levels and then employs internal market shifts to trigger trades.
Key Features:
Internal Shift Logic: Instead of relying on traditional candlestick patterns like engulfing candles, this strategy utilizes internal market shifts. A bullish shift occurs when the price breaks previous bearish levels, and a bearish shift happens when the price breaks previous bullish levels, indicating a change in market direction.
Liquidity Zones: The strategy dynamically identifies key liquidity zones (local highs and lows) to detect potential reversal points and prevent trades in weak market conditions.
Mode Options: You can choose to run the strategy in "Both," "Bullish Only," or "Bearish Only" modes, allowing for flexibility based on market conditions.
Stop-Loss and Take-Profit: Customizable stop-loss and take-profit levels are integrated to manage risk and lock in profits.
Time Range Control: You can specify the time range for trading, ensuring the strategy only operates during the desired period.
This strategy is ideal for traders who want to combine liquidity analysis with internal structure shifts for precise market entries and exits.
This description clearly outlines the strategy's logic, the flexibility it provides, and how it works. You can adjust it further to match your personal trading style or preferences!
Keltner Channel StrategyOverview
The Keltner Channel Strategy is a powerful trend-following and mean-reversion system that leverages the Keltner Channels, EMA crossovers, and ATR-based stop-losses to optimize trade entries and exits. This strategy has proven to be highly effective, particularly when applied to Gold (XAUUSD) and other commodities with strong trend characteristics.
📈 How It Works
This strategy incorporates two trading approaches: 1️⃣ Keltner Channel Reversal Trades – Identifies overbought and oversold conditions when price touches the outer bands.
2️⃣ Trend Following Trades – Uses the 9 EMA & 21 EMA crossover, with confirmation from the 50 EMA, to enter trades in the direction of the trend.
🔍 Entry & Exit Criteria
📊 Keltner Channel Entries (Reversal Strategy)
✅ Long Entry: When the price crosses below the lower Keltner Band (potential reversal).
✅ Short Entry: When the price crosses above the upper Keltner Band (potential reversal).
⏳ Exit Conditions:
Long positions close when price crosses back above the mid-band (EMA-based).
Short positions close when price crosses back below the mid-band (EMA-based).
📈 Trend Following Entries (Momentum Strategy)
✅ Long Entry: When the 9 EMA crosses above the 21 EMA, and price is above the 50 EMA (bullish momentum).
✅ Short Entry: When the 9 EMA crosses below the 21 EMA, and price is below the 50 EMA (bearish momentum).
⏳ Exit Conditions:
Long positions close when the 9 EMA crosses back below the 21 EMA.
Short positions close when the 9 EMA crosses back above the 21 EMA.
📌 Risk Management & Profit Targeting
ATR-based Stop-Losses:
Long trades: Stop set at 1.5x ATR below entry price.
Short trades: Stop set at 1.5x ATR above entry price.
Take-Profit Levels:
Long trades: Profit target 2x ATR above entry price.
Short trades: Profit target 2x ATR below entry price.
🚀 Why Use This Strategy?
✅ Works exceptionally well on Gold (XAUUSD) due to high volatility.
✅ Combines reversal & trend strategies for improved adaptability.
✅ Uses ATR-based risk management for dynamic position sizing.
✅ Fully automated alerts for trade entries and exits.
🔔 Alerts
This script includes automated TradingView alerts for:
🔹 Keltner Band touches (Reversal signals).
🔹 EMA crossovers (Momentum trades).
🔹 Stop-loss & Take-profit activations.
📊 Ideal Markets & Timeframes
Best for: Gold (XAUUSD), NASDAQ (NQ), Crude Oil (CL), and trending assets.
Recommended Timeframes: 15m, 1H, 4H, Daily.
⚡️ How to Use
1️⃣ Add this script to your TradingView chart.
2️⃣ Select a 15m, 1H, or 4H timeframe for optimal results.
3️⃣ Enable alerts to receive trade notifications in real time.
4️⃣ Backtest and tweak ATR settings to fit your trading style.
🚀 Optimize your Gold trading with this Keltner Channel Strategy! Let me know how it performs for you. 💰📊
Trend Hunter Scalping [Daddin Algo]Trend Hunter Scalping Strategy Description
This strategy is a comprehensive scalping system designed to capture high-frequency trading opportunities within short timeframes. It combines multiple technical indicators to assess trend direction, momentum, volatility, and volume dynamics. Importantly, all parameters are user-adjustable, allowing the strategy to be optimized for various market conditions and individual preferences.
Technical Indicators and Settings
EMA (Exponential Moving Average):
The EMA is calculated based on a user-defined period. Rather than being fixed (e.g., a 200-period EMA), the period is adjustable to suit different market conditions. The position of the price relative to the EMA helps confirm the overall trend.
RSI & RSIOver:
The Relative Strength Index (RSI) measures momentum and the speed of price changes. Entry signals are generated when the RSI crosses its moving average. Additionally, overbought and oversold thresholds (set by the user) add an extra layer of confirmation for the signals.
ADX:
The Average Directional Index (ADX) assesses the strength of the current trend. When the ADX is above a user-specified threshold, the signals are considered more reliable. This helps in filtering out signals during weak trending periods.
Bollinger Bands:
Bollinger Bands gauge market volatility. The settings—including the length and the multiplier—are adjustable, providing flexibility to accommodate tightening or expanding volatility conditions.
Parabolic SAR:
This indicator identifies dynamic support and resistance levels, confirming the trend direction and helping pinpoint potential entry and exit points.
Pivot Levels (Fibonacci):
Calculated from the previous period's high, low, and close, pivot points and Fibonacci levels indicate potential reversal points and serve as support and resistance levels. These levels provide context for setting trailing stops and managing risk.
Volume Filter:
A volume condition ensures that trading signals are only considered valid when the current volume exceeds a multiple of its short-term moving average. This filter is adjustable, helping to confirm the strength of the market move.
Daddin Line:
Derived from a short-term moving average of the closing prices with a user-defined offset, the Daddin Line acts as an additional confirmation tool. Its parameters can be customized to better align with specific trading environments.
Trading Logic and Management
Signal Direction and Entry:
The strategy can generate both long (buy) and short (sell) signals, or be limited to one direction based on user preference. Entry orders are executed when all the selected indicator conditions are met. Additionally, maximum consecutive trade limits are implemented to help control risk.
Exit & Take Profit:
Trades are exited automatically when a user-defined profit percentage is reached. This take-profit percentage is flexible, enabling adjustments to match different market conditions or trading goals.
Trailing Stop (Dynamic Stop Loss):
A trailing stop mechanism is implemented using Fibonacci pivot levels. Once a position is open, the stop loss is dynamically updated as the price moves favorably. This ensures that profits are protected while minimizing losses in case of a sudden reversal.
Additional Features and Backtesting
Time Filtering (Backtesting):
The strategy includes a date range filter for backtesting. Users can define the start and end dates to evaluate the strategy’s performance during specific market periods, making it easier to assess its historical effectiveness.
Customizable Parameters:
Every indicator and risk management setting is fully customizable. This adaptability allows traders to tailor the strategy to different assets, timeframes, and market environments, ensuring optimal performance across diverse trading scenarios.
Conclusion
The Trend Hunter Scalping strategy effectively integrates multiple technical indicators to validate trends and manage risks efficiently. Its highly flexible, user-adjustable parameters make it adaptable to varying market conditions, providing traders with a robust framework for capturing quick trading opportunities.This strategy is designed to optimize both entry and exit points while offering comprehensive risk management controls.
ICT Bread and Butter Sell-SetupICT Bread and Butter Sell-Setup – TradingView Strategy
Overview:
The ICT Bread and Butter Sell-Setup is an intraday trading strategy designed to capitalize on bearish market conditions. It follows institutional order flow and exploits liquidity patterns within key trading sessions—London, New York, and Asia—to identify high-probability short entries.
Key Components of the Strategy:
🔹 London Open Setup (2:00 AM – 8:20 AM NY Time)
The London session typically sets the initial directional move of the day.
A short-term high often forms before a downward push, establishing the daily high.
🔹 New York Open Kill Zone (8:20 AM – 10:00 AM NY Time)
The New York Judas Swing (a temporary rally above London’s high) creates an opportunity for short entries.
Traders fade this move, anticipating a sell-off targeting liquidity below previous lows.
🔹 London Close Buy Setup (10:30 AM – 1:00 PM NY Time)
If price reaches a higher timeframe discount array, a retracement higher is expected.
A bullish order block or failure swing signals a possible reversal.
The risk is set just below the day’s low, targeting a 20-30% retracement of the daily range.
🔹 Asia Open Sell Setup (7:00 PM – 2:00 AM NY Time)
If institutional order flow remains bearish, a short entry is taken around the 0-GMT Open.
Expect a 15-20 pip decline as the Asian range forms.
Strategy Rules:
📉 Short Entry Conditions:
✅ New York Judas Swing occurs (price moves above London’s high before reversing).
✅ Short entry is triggered when price closes below the open.
✅ Stop-loss is set 10 pips above the session high.
✅ Take-profit targets liquidity zones on higher timeframes.
📈 Long Entry (London Close Reversal):
✅ Price reaches a higher timeframe discount array between 10:30 AM – 1:00 PM NY Time.
✅ A bullish order block confirms the reversal.
✅ Stop-loss is set 10 pips below the day’s low.
✅ Take-profit targets 20-30% of the daily range retracement.
📉 Asia Open Sell Entry:
✅ Price trades slightly above the 0-GMT Open.
✅ Short entry is taken at resistance, targeting a quick 15-20 pip move.
Why Use This Strategy?
🚀 Institutional Order Flow Tracking – Aligns with smart money concepts.
📊 Precise Session Timing – Uses market structure across London, New York, and Asia.
🎯 High-Probability Entries – Focuses on liquidity grabs and engineered stop hunts.
📉 Optimized Risk Management – Defined stop-loss and take-profit levels.
This strategy is ideal for traders looking to trade with institutions, fade liquidity grabs, and capture high-probability short setups during the trading day. 📉🔥
Heiken Ashi Supertrend ATR-SL StrategyThis indicator combines Heikin Ashi candle pattern analysis with Supertrend to generate high-probability trading signals with built-in risk management. It identifies potential entries and exits based on specific Heikin Ashi candlestick formations while providing automated ATR-based stop loss management.
Trading Logic:
The system generates long signals when a green Heikin Ashi candle forms with no bottom wick (indicating strong bullish momentum). Short signals appear when a red Heikin Ashi candle forms with no top wick (showing strong bearish momentum). The absence of wicks on these candles signals a high-conviction market move in the respective direction.
Exit signals are triggered when:
1. An opposite pattern forms (red candle with no top wick exits longs; green candle with no bottom wick exits shorts)
2. The ATR-based stop loss is hit
3. The break-even stop is activated and then hit
Technical Approach:
- Select Heiken Ashi Canldes on your Trading View chart. Entried are based on HA prices.
- Supertrend and ATR-based stop losses use real price data (not HA values) for trend determination
- ATR-based stop losses automatically adjust to market volatility
- Break-even functionality moves the stop to entry price once price moves a specified ATR multiple in your favor
Risk Management:
- Default starting capital: 1000 units
- Default risk per trade: 10% of equity (customizable in strategy settings)
- Hard Stop Loss: Set ATR multiplier (default: 2.0) for automatic stop placement
- Break Even: Configure ATR threshold (default: 1.0) to activate break-even stops
- Appropriate position sizing relative to equity and stop distance
Customization Options:
- Supertrend Settings:
- Enable/disable Supertrend filtering (trade only in confirmed trend direction)
- Adjust Factor (default: 3.0) to change sensitivity
- Modify ATR Period (default: 10) to adapt to different timeframes
Visual Elements:
- Green triangles for long entries, blue triangles for short entries
- X-marks for exits and stop loss hits
- Color-coded position background (green for long, blue for short)
- Clearly visible stop loss lines (red for hard stop, white for break-even)
- Comprehensive position information label with entry price and stop details
Implementation Notes:
The indicator tracks positions internally and maintains state across bars to properly manage stop levels. All calculations use confirmed bars only, with no repainting or lookahead bias. The system is designed for swing trading on timeframes from 1-hour and above, where Heikin Ashi patterns tend to be more reliable.
This indicator is best suited for traders looking to combine the pattern recognition strengths of Heikin Ashi candles with the trend-following capabilities of Supertrend, all while maintaining disciplined risk management through automated stops.
iD EMARSI on ChartSCRIPT OVERVIEW
The EMARSI indicator is an advanced technical analysis tool that maps RSI values directly onto price charts. With adaptive scaling capabilities, it provides a unique visualization of momentum that flows naturally with price action, making it particularly valuable for FOREX and low-priced securities trading.
KEY FEATURES
1 PRICE MAPPED RSI VISUALIZATION
Unlike traditional RSI that displays in a separate window, EMARSI plots the RSI directly on the price chart, creating a flowing line that identifies momentum shifts within the context of price action:
// Map RSI to price chart with better scaling
mappedRsi = useAdaptiveScaling ?
median + ((rsi - 50) / 50 * (pQH - pQL) / 2 * math.min(1.0, 1/scalingFactor)) :
down == pQL ? pQH : up == pQL ? pQL : median - (median / (1 + up / down))
2 ADAPTIVE SCALING SYSTEM
The script features an intelligent scaling system that automatically adjusts to different market conditions and price levels:
// Calculate adaptive scaling factor based on selected method
scalingFactor = if scalingMethod == "ATR-Based"
math.min(maxScalingFactor, math.max(1.0, minTickSize / (atrValue/avgPrice)))
else if scalingMethod == "Price-Based"
math.min(maxScalingFactor, math.max(1.0, math.sqrt(100 / math.max(avgPrice, 0.01))))
else // Volume-Based
math.min(maxScalingFactor, math.max(1.0, math.sqrt(1000000 / math.max(volume, 100))))
3 MODIFIED RSI CALCULATION
EMARSI uses a specially formulated RSI calculation that works with an adaptive base value to maintain consistency across different price ranges:
// Adaptive RSI Base based on price levels to improve flow
adaptiveRsiBase = useAdaptiveScaling ? rsiBase * scalingFactor : rsiBase
// Calculate RSI components with adaptivity
up = ta.rma(math.max(ta.change(rsiSourceInput), adaptiveRsiBase), emaSlowLength)
down = ta.rma(-math.min(ta.change(rsiSourceInput), adaptiveRsiBase), rsiLengthInput)
// Improved RSI calculation with value constraint
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
4 MOVING AVERAGE CROSSOVER SYSTEM
The indicator creates a smooth moving average of the RSI line, enabling a crossover system that generates trading signals:
// Calculate MA of mapped RSI
rsiMA = ma(mappedRsi, emaSlowLength, maTypeInput)
// Strategy entries
if ta.crossover(mappedRsi, rsiMA)
strategy.entry("RSI Long", strategy.long)
if ta.crossunder(mappedRsi, rsiMA)
strategy.entry("RSI Short", strategy.short)
5 VISUAL REFERENCE FRAMEWORK
The script includes visual guides that help interpret the RSI movement within the context of recent price action:
// Calculate pivot high and low
pQH = ta.highest(high, hlLen)
pQL = ta.lowest(low, hlLen)
median = (pQH + pQL) / 2
// Plotting
plot(pQH, "Pivot High", color=color.rgb(82, 228, 102, 90))
plot(pQL, "Pivot Low", color=color.rgb(231, 65, 65, 90))
med = plot(median, style=plot.style_steplinebr, linewidth=1, color=color.rgb(238, 101, 59, 90))
6 DYNAMIC COLOR SYSTEM
The indicator uses color fills to clearly visualize the relationship between the RSI and its moving average:
// Color fills based on RSI vs MA
colUp = mappedRsi > rsiMA ? input.color(color.rgb(128, 255, 0), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(240, 9, 9, 95), '', group= 'RSI < EMA', inline= 'dn')
colDn = mappedRsi > rsiMA ? input.color(color.rgb(0, 230, 35, 95), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(255, 47, 0), '', group= 'RSI < EMA', inline= 'dn')
fill(rsiPlot, emarsi, mappedRsi > rsiMA ? pQH : rsiMA, mappedRsi > rsiMA ? rsiMA : pQL, colUp, colDn)
7 REAL TIME PARAMETER MONITORING
A transparent information panel provides real-time feedback on the adaptive parameters being applied:
// Information display
var table infoPanel = table.new(position.top_right, 2, 3, bgcolor=color.rgb(0, 0, 0, 80))
if barstate.islast
table.cell(infoPanel, 0, 0, "Current Scaling Factor", text_color=color.white)
table.cell(infoPanel, 1, 0, str.tostring(scalingFactor, "#.###"), text_color=color.white)
table.cell(infoPanel, 0, 1, "Adaptive RSI Base", text_color=color.white)
table.cell(infoPanel, 1, 1, str.tostring(adaptiveRsiBase, "#.####"), text_color=color.white)
BENEFITS FOR TRADERS
INTUITIVE MOMENTUM VISUALIZATION
By mapping RSI directly onto the price chart, traders can immediately see the relationship between momentum and price without switching between different indicator windows.
ADAPTIVE TO ANY MARKET CONDITION
The three scaling methods (ATR-Based, Price-Based, and Volume-Based) ensure the indicator performs consistently across different market conditions, volatility regimes, and price levels.
PREVENTS EXTREME VALUES
The adaptive scaling system prevents the RSI from generating extreme values that exceed chart boundaries when trading low-priced securities or during high volatility periods.
CLEAR TRADING SIGNALS
The RSI and moving average crossover system provides clear entry signals that are visually reinforced through color changes, making it easy to identify potential trading opportunities.
SUITABLE FOR MULTIPLE TIMEFRAMES
The indicator works effectively across multiple timeframes, from intraday to daily charts, making it versatile for different trading styles and strategies.
TRANSPARENT PARAMETER ADJUSTMENT
The information panel provides real-time feedback on how the adaptive system is adjusting to current market conditions, helping traders understand why the indicator is behaving as it is.
CUSTOMIZABLE VISUALIZATION
Multiple visualization options including Bollinger Bands, different moving average types, and customizable colors allow traders to adapt the indicator to their personal preferences.
CONCLUSION
The EMARSI indicator represents a significant advancement in RSI visualization by directly mapping momentum onto price charts with adaptive scaling. This approach makes momentum shifts more intuitive to identify and helps prevent the scaling issues that commonly affect RSI-based indicators when applied to low-priced securities or volatile markets.
TheRookAlgoPROThe Rook Algo PRO is an automated strategy that uses ICT dealing ranges to get in sync with potential market trends. It detects the market sentiment and then place a sell or a buy trade in premium/discount or in breakouts with the desired risk management.
Why is useful?
This algorithm is designed to help traders to quickly identify the current state of the market and easily back test their strategy over longs periods of time and different markets its ideal for traders that want to profit on potential expansions and want to avoid consolidations this algo will tell you when the expansion is likely to begin and when is just consolidating and failing moves to avoid trading.
How it works and how it does it?
The Algo detects the current and previous market structure to identify current ranges and ICT dealing ranges that are created when the market takes buyside liquidity and sellside liquidity, it will tell if the market is in a consolidation, expansion, retracement or in a potential turtle soup environment, it will tell if the range is small or big compared to the previous one. Is important to use it in a trending markets because when is ranging the signals lose effectiveness.
This algo is similar to the previously released the Rook algo with the additional features that is an automated strategy that can take trades using filters with the desired risk reward and different entry types and trade management options.
Also this version plots FVGS(fair value gaps) during expansions, and detects consolidations with a box and the mid point or average. Some bars colors are available to help in the identification of the market state. It has the option to show colors of the dealing ranges first detected state.
How to use it?
Start selecting the desired type of entry you want to trade, you can choose to take Discount longs, premium sells, breakouts longs and sells, this first four options are the selected by default. You can enable riskier options like trades without confirmation in premium and discount or turtle soup of the current or previous dealing range. This last ones are ideal for traders looking to enter on a counter trend but has to be used with caution with a higher timeframe reference.
In the picture below we can see a premium sell signal configuration followed by a discount buy signal It display the stop break even level and take profit.
This next image show how the riskier entries work. Because we are not waiting for a confirmation and entering on a counter trend is normal to experience some stop losses because the stop is very tight. Should only be used with a clear Higher timeframe reference as support of the trade idea. This algo has the option to enable standard deviations from the normal stop point to prevent liquidity sweeps. The purple or blue arrows indicate when we are in a potential turtle soup environment.
The algo have a feature called auto-trade enable by default that allow for a reversal of the current trade in case it meets the criteria. And also can take all possible buys or all possible sells that are riskier entries if you just want to see the market sentiment. This is useful when the market is very volatile but is moving not just ranging.
Then we configure the desired trade filters. We have the options to trade only when dealing ranges are in sync for a more secure trend, or we can disable it to take riskier trades like turtle soup trades. We can chose the minimum risk reward to take the trade and the target extension from the current range and the exit type can be when we hit the level or in a retracement that is the default setting. These setting are the most important that determine profitability of the strategy, they has be adjusted depending on the timeframe and market we are trading.
The stop and target levels can also be configured with standard deviations from the current range that way can be adapted to the market volatility.
The Algo allow the user to chose if it want to place break even, or trail the stop. In the picture below we can see it in action. This can work when the trend is very strong if not can lead to multiple reentries or loses.
The last option we can configure is the time where the trades are going to be taken, if we trade usually in the morning then we can just add the morning time by default is set to the morning 730am to 1330pm if you want to trade other times you should change this. Or if we want to enter on the ICT macro times can also be added in a filter. Trade taken with the macro times only enable is visible in the picture below.
Strategy Results
The results are obtained using 2000usd in the MNQ! In the 15minutes timeframe 1 contract per trade. Commission are set to 2USD, slippage to 1tick, the backtesting range is from May 2 2024 to March 2025 for a total of 119 trades, this Strategy default settings are designed to take trades on the daily expansions, trail stop and Break even is activated the exit on profit is on a retracement, and for loses when the stop is hit. The auto-trade option is enable to allow to detect quickly market changes. The strategy give realistic results, makes around 200% of the account in around a year. 1.4 profit factor with around 37% profitable trades. These results can be further improve and adapted to the specific style of trading using the filters.
Remember entries constitute only a small component of a complete winning strategy. Other factors like risk management, position-sizing, trading frequency, trading fees, and many others must also be properly managed to achieve profitability. Past performance doesn’t guarantee future results.
Summary of features
-Easily Identify the current dealing range and market state to avoid consolidations
-Recognize expansions with FVGs and consolidation with shaded boxes
-Recognize turtle soups scenarios to avoid fake out breakout
-Configurable automated trades in premium/discount or breakouts
-Auto-trade option that allow for reversal of the current trade when is no longer valid
-Time filter to allow only entries around the times you trade or on the macro times.
-Risk Reward filter to take the automated trades with visible stop and take profit levels
-Customizable trade management take profit, stop, breakeven level with standard deviations
-Trail stop option to secure profit when price move in your favor
-Option to exit on a close, retracement or reversal after hitting the take profit level
-Option to exit on a close or reversal after hitting stop loss
-Dashboard with instant statistics about the strategy current settings and market sentiment
Multi-Timeframe MACD Strategy ver 1.0Multi-Timeframe MACD Strategy: Enhanced Trend Trading with Customizable Entry and Trailing Stop
This strategy utilizes the Moving Average Convergence Divergence (MACD) indicator across multiple timeframes to identify strong trends, generate precise entry and exit signals, and manage risk with an optional trailing stop loss. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trade accuracy, reduce exposure to false signals, and capture larger market moves.
Key Features:
Dual Timeframe Analysis: Calculates and analyzes the MACD on both the current chart's timeframe and a user-selected higher timeframe (e.g., Daily MACD on a 1-hour chart). This provides a broader market context, helping to confirm trends and filter out short-term noise.
Configurable MACD: Fine-tune the MACD calculation with adjustable Fast Length, Slow Length, and Signal Length parameters. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Flexible Entry Options: Choose between three distinct entry types:
Crossover: Enters trades when the MACD line crosses above (long) or below (short) the Signal line.
Zero Cross: Enters trades when the MACD line crosses above (long) or below (short) the zero line.
Both: Combines both Crossover and Zero Cross signals, providing more potential entry opportunities.
Independent Timeframe Control: Display and trade based on the current timeframe MACD, the higher timeframe MACD, or both. This allows you to focus on the information most relevant to your analysis.
Optional Trailing Stop Loss: Implements a configurable trailing stop loss to protect profits and limit potential losses. The trailing stop is adjusted dynamically as the price moves in your favor, based on a user-defined percentage.
No Repainting: Employs lookahead=barmerge.lookahead_off in the request.security() function to prevent data leakage and ensure accurate backtesting and real-time signals.
Clear Visual Signals (Optional): Includes optional plotting of the MACD and Signal lines for both timeframes, with distinct colors for easy visual identification. These plots are for visual confirmation and are not required for the strategy's logic.
Suitable for Various Trading Styles: Adaptable to swing trading, day trading, and trend-following strategies across diverse markets (stocks, forex, cryptocurrencies, etc.).
Fully Customizable: All parameters are adjustable, including timeframes, MACD Settings, Entry signal type and trailing stop settings.
How it Works:
MACD Calculation: The strategy calculates the MACD (using the standard formula) for both the current chart's timeframe and the specified higher timeframe.
Trend Identification: The relationship between the MACD line, Signal line, and zero line is used to determine the current trend for each timeframe.
Entry Signals: Buy/sell signals are generated based on the selected "Entry Type":
Crossover: A long signal is generated when the MACD line crosses above the Signal line, and both timeframes are in agreement (if both are enabled). A short signal is generated when the MACD line crosses below the Signal line, and both timeframes are in agreement.
Zero Cross: A long signal is generated when the MACD line crosses above the zero line, and both timeframes agree. A short signal is generated when the MACD line crosses below the zero line and both timeframes agree.
Both: Combines Crossover and Zero Cross signals.
Trailing Stop Loss (Optional): If enabled, a trailing stop loss is set at a specified percentage below (for long positions) or above (for short positions) the entry price. The stop-loss is automatically adjusted as the price moves favorably.
Exit Signals:
Without Trailing Stop: Positions are closed when the MACD signals reverse according to the selected "Entry Type" (e.g., a long position is closed when the MACD line crosses below the Signal line if using "Crossover" entries).
With Trailing Stop: Positions are closed if the price hits the trailing stop loss.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to assess its performance and optimize parameters for different assets and timeframes.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees a bullish MACD crossover on the current timeframe. They check the MTF MACD strategy and see that the Daily MACD is also bullish, confirming the strength of the uptrend.
Filtering Noise: A trader using a 15-minute chart wants to avoid false signals from short-term volatility. They use the strategy with a 4-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and enables the trailing stop loss. As the price rises, the trailing stop is automatically adjusted upwards, protecting profits. The trade is exited either when the MACD reverses or when the price hits the trailing stop.
Disclaimer:
The MACD is a lagging indicator and can produce false signals, especially in ranging markets. This strategy is for educational and informational purposes only and should not be considered financial advice. Backtest and optimize the strategy thoroughly, combine it with other technical analysis tools, and always implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Liquidity Sweep Filter Strategy [AlgoAlpha X PineIndicators]This strategy is based on the Liquidity Sweep Filter developed by AlgoAlpha. Full credit for the concept and original indicator goes to AlgoAlpha.
The Liquidity Sweep Filter Strategy is a non-repainting trading system designed to identify liquidity sweeps, trend shifts, and high-impact price levels. It incorporates volume-based liquidation analysis, trend confirmation, and dynamic support/resistance detection to optimize trade entries and exits.
This strategy helps traders:
Detect liquidity sweeps where major market participants trigger stop losses and liquidations.
Identify trend shifts using a volatility-based moving average system.
Analyze volume distribution with a built-in volume profile visualization.
Filter noise by differentiating between major and minor liquidity sweeps.
How the Liquidity Sweep Filter Strategy Works
1. Trend Detection Using Volatility-Based Filtering
The strategy applies a volatility-adjusted moving average system to determine trend direction:
A central trend line is calculated using an EMA smoothed over a user-defined length.
Upper and lower deviation bands are created based on the average price deviation over multiple periods.
If price closes above the upper band, the strategy signals an uptrend.
If price closes below the lower band, the strategy signals a downtrend.
This approach ensures that trend shifts are confirmed only when price significantly moves beyond normal market fluctuations.
2. Liquidity Sweep Detection
Liquidity sweeps occur when price temporarily breaks key levels, triggering stop-loss liquidations or margin call events. The strategy tracks swing highs and lows, marking potential liquidity grabs:
Bearish Liquidity Sweeps – Price breaks a recent high, then reverses downward.
Bullish Liquidity Sweeps – Price breaks a recent low, then reverses upward.
Volume Integration – The strategy analyzes trading volume at each sweep to differentiate between major and minor sweeps.
Key levels where liquidity sweeps occur are plotted as color-coded horizontal lines:
Red lines indicate bearish liquidity sweeps.
Green lines indicate bullish liquidity sweeps.
Labels are displayed at each sweep, showing the volume of liquidated positions at that level.
3. Volume Profile Analysis
The strategy includes an optional volume profile visualization, displaying how trading volume is distributed across different price levels.
Features of the volume profile:
Point of Control (POC) – The price level with the highest traded volume is marked as a key area of interest.
Bounding Box – The profile is enclosed within a transparent box, helping traders visualize the price range of high trading activity.
Customizable Resolution & Scale – Traders can adjust the granularity of the profile to match their preferred time frame.
The volume profile helps identify zones of strong support and resistance, making it easier to anticipate price reactions at key levels.
Trade Entry & Exit Conditions
The strategy allows traders to configure trade direction:
Long Only – Only takes long trades.
Short Only – Only takes short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish trend shift is confirmed.
A bullish liquidity sweep occurs (price sweeps below a key level and reverses).
The trade direction setting allows long trades.
Short Entry:
A bearish trend shift is confirmed.
A bearish liquidity sweep occurs (price sweeps above a key level and reverses).
The trade direction setting allows short trades.
Exit Conditions
Closing a Long Position:
A bearish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Closing a Short Position:
A bullish trend shift occurs.
The position is liquidated at a predefined liquidity sweep level.
Customization Options
The strategy offers multiple adjustable settings:
Trade Mode: Choose between Long Only, Short Only, or Long & Short.
Trend Calculation Length & Multiplier: Adjust how trend signals are calculated.
Liquidity Sweep Sensitivity: Customize how aggressively the strategy identifies sweeps.
Volume Profile Display: Enable or disable the volume profile visualization.
Bounding Box & Scaling: Control the size and position of the volume profile.
Color Customization: Adjust colors for bullish and bearish signals.
Considerations & Limitations
Liquidity sweeps do not always result in reversals. Some price sweeps may continue in the same direction.
Works best in volatile markets. In low-volatility environments, liquidity sweeps may be less reliable.
Trend confirmation adds a slight delay. The strategy ensures valid signals, but this may result in slightly later entries.
Large volume imbalances may distort the volume profile. Adjusting the scale settings can help improve visualization.
Conclusion
The Liquidity Sweep Filter Strategy is a volume-integrated trading system that combines liquidity sweeps, trend analysis, and volume profile data to optimize trade execution.
By identifying key price levels where liquidations occur, this strategy provides valuable insight into market behavior, helping traders make better-informed trading decisions.
Key use cases for this strategy:
Liquidity-Based Trading – Capturing moves triggered by stop hunts and liquidations.
Volume Analysis – Using volume profile data to confirm high-activity price zones.
Trend Following – Entering trades based on confirmed trend shifts.
Support & Resistance Trading – Using liquidity sweep levels as dynamic price zones.
This strategy is fully customizable, allowing traders to adapt it to different market conditions, timeframes, and risk preferences.
Full credit for the original concept and indicator goes to AlgoAlpha.
Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
GRIM309 CallPut StrategyThis draws the 5, 10, 20, 50 and 200 EMA lines.
It creates suggestions of when to open and close call positions (GREEN) as well as open and close put positions (RED) it has a early warning system, and in case there is a spike between the last 5 positions it will signal close the position, this is optional (isWarning)
There is also a cooldown period, when set at 2 it means wait a position before initiating another, I did not like the position closing and then opening directly afterwards, you could cooldown for 3 and skip 2 candles or more etc. Set to 1 then it will open/close without cooling down.
Additionally the very bottom shows wether it is in an uptrend or downtrend currently (Yellow triangle)
Fibonacci-Only Strategy V2Fibonacci-Only Strategy V2
This strategy combines Fibonacci retracement levels with pattern recognition and statistical confirmation to identify high-probability trading opportunities across multiple timeframes.
Core Strategy Components:
Fibonacci Levels: Uses key Fibonacci retracement levels (19% and 82.56%) to identify potential reversal zones
Pattern Recognition: Analyzes recent price patterns to find similar historical formations
Statistical Confirmation: Incorporates statistical analysis to validate entry signals
Risk Management: Includes customizable stop loss (fixed or ATR-based) and trailing stop features
Entry Signals:
Long entries occur when price touches or breaks the 19% Fibonacci level with bullish confirmation
Short entries require Fibonacci level interaction, bearish confirmation, and statistical validation
All signals are visually displayed with color-coded markers and dashboard
Trading Method:
When a triangle signal appears, open a position on the next candle
Alternatively, after seeing a signal on a higher timeframe, you can switch to a lower timeframe to find a more precise entry point
Entry signals are clearly marked with visual indicators for easy identification
Risk Management Features:
Adjustable stop loss (percentage-based or ATR-based)
Optional trailing stops for protecting profits
Multiple take-profit levels for strategic position exit
Customization Options:
Timeframe selection (1m to Daily)
Pattern length and similarity threshold adjustment
Statistical period and weight configuration
Risk parameters including stop loss and trailing stop settings
This strategy is particularly well-suited for cryptocurrency markets due to their tendency to respect Fibonacci levels and technical patterns. Crypto's volatility is effectively managed through the customizable stop-loss and trailing-stop mechanisms, making it an ideal tool for traders in digital asset markets.
For optimal performance, this strategy works best on higher timeframes (30m, 1h and above) and is not recommended for low timeframe scalping. The Fibonacci pattern recognition requires sufficient price movement to generate reliable signals, which is more consistently available in medium to higher timeframes.
Users should avoid trading during sideways market conditions, as the strategy performs best during trending markets with clear directional movement. The statistical confirmation component helps filter out some sideways market signals, but it's recommended to manually avoid ranging markets for best results.
