RSI On SteroidsThe RSI On Steroids indicator combines the Relative Strength Index (RSI) with the Augmented Dickey-Fuller (ADF) test to enhance trend identification and reduce market noise. This hybrid approach allows traders to detect stronger market movements with greater accuracy, making it useful for both trend confirmation and mean-reversion strategies.
By integrating RSI’s momentum-based insights with the ADF test’s statistical validation of trend persistence, this tool helps filter out weak signals, improving overall market analysis.
How It Works
- The RSI component measures momentum and overbought/oversold conditions based on user-defined upper and lower bands.
- The ADF test analyzes price action, determining whether the market is trending or reverting to a mean.
- Moving Average (MA) smoothing can be applied to both RSI and ADF values, helping to refine signals and reduce short-term fluctuations.
- Threshold levels for both indicators allow for the identification of breakout opportunities or mean-reversion setups.
- Optional bar coloring and background visualization improve clarity, highlighting bullish and bearish conditions.
How to Use It
1. Trend Confirmation & Reversals:
(a) If RSI breaks above the upper band, it signals strong upward momentum.
(b) If ADF crosses above its threshold, it validates a potential trend breakout.
(c) When both RSI and ADF align, the signal is stronger, confirming momentum shifts or trend continuations.
2. Smoothing for Noise Reduction:
(a) Enable MA smoothing to filter out short-term fluctuations and identify clearer signals.
(b) Choose from SMA, EMA, VWMA, WMA, HMA, and RMA to match market conditions and trading preferences.
3. Visual Cues for Decision Making:
(a) Bar and background colors dynamically update based on market conditions.
(b) RSI and ADF plots (optional) allow deeper analysis for traders who prefer visual confirmation.
Default Settings & Recommended Usage
- RSI Period: 16
- RSI MA Length: Enabled 10, EMA
- Upper RSI Band: 54 | Lower RSI Band: 22
- ADF Lookback Period: 20
- ADF MA Smoothing: Enabled 34, EMA
- Upper ADF Threshold: -1.45 | Lower ADF Threshold: -2.3
- Default Settings Adjusted for 2D timeframe for reliable trend confirmation and reversion signals.
Conclusion
The RSI On Steroids indicator merges momentum analysis (RSI) with statistical validation (ADF test) to offer a more robust and precise approach to trend detection. By filtering out market noise and identifying stronger price movements, traders can gain better insights into trend continuations and reversals.
- Important Note: No trading indicator guarantees future results. Historical performance does not predict future success.
- Strategic Consideration: Traders should fine-tune settings, validate signals with additional analysis, and apply risk management strategies to optimize this indicator for real-world trading.
التقلب
ADF For GsThe ADF For Gs indicator implements the Augmented Dickey-Fuller (ADF) test, a statistical method commonly used to determine if a time series is mean-reverting or following a trend. By applying Moving Average (MA) smoothing, this indicator provides an adaptive way to detect market conditions where price action is either trending or reverting to a mean.
How It Works
- The ADF test statistic is calculated within a rolling window defined by the lookback period.
- The lag length is adjustable to account for serial correlation in price changes.
- The test statistic is compared to pre-defined threshold levels (upperEntry and lowerEntry) to identify potential trend breaks and reversals.
- Users can smooth the ADF values with different Moving Average types (SMA, EMA, VWMA, WMA, HMA, RMA), providing flexibility in signal interpretation.
- The indicator also includes dynamic bar and background coloring, visually enhancing trend and reversal conditions.
How to Use It
1. Trend vs. Mean Reversion:
(a) When the ADF statistic crosses above the upper threshold, it suggests a potential trend breakout.
(b) When it crosses below the lower threshold, it indicates a potential mean reversion.
2. Moving Average Smoothing:
(a) If useMA is enabled, the ADF values are smoothed using a selected MA type to filter noise.
(b) This allows for a more gradual trend-following approach.
3. Visual Cues:
(a) Background color changes to indicate bullish or bearish conditions.
(b) Candles are color-coded based on crossover signals to highlight entry/exit opportunities.
Default Settings & Recommended Usage
- Default period: 22 bars (4D timeframe recommended)
- MA smoothing enabled with a 23-length EMA
- Upper Entry level: -1.4 | Lower Entry level: -2.3
- Best used in trending markets to confirm breakout or mean reversion trades
Conclusion
The ADF For Gs indicator is designed to detect market trends and reversals by applying the Augmented Dickey-Fuller (ADF) test with Moving Average smoothing. By combining statistical validation with adaptive trend filtering, it helps traders separate meaningful price movements from temporary fluctuations. Whether used to confirm trends or identify mean-reversion opportunities, this tool provides a structured, data-driven approach to market analysis.
- Important Note: No trading indicator can predict future price movements with certainty. Historical performance does not guarantee future results.
- Best Practices: To get the most out of this indicator, traders should test different settings, validate signals with additional tools, and use proper risk management. Adjusting parameters to suit individual strategies can improve accuracy and overall effectiveness.
LOGICAL TRADERthis is no-1 indicator for trading,
for intraday trading
5-10-15 min time tram
stock trading - btc - nifty - banknifty working
Tdi Killer +RSi DivergenceTDI Killer + RSI Divergence: Advanced Indicator for Trend Reversals and Continuations
Overview
The TDI Killer + RSI Divergence is an advanced RSI-based indicator designed to identify high-probability trend reversals and continuations. It integrates the Traders Dynamic Index (TDI) with RSI divergences and dynamic volatility bands to enhance accuracy. This script is closed-source to maintain the integrity of its unique calculations and optimizations.
Key Features
RSI Divergence Detection: Identifies bullish and bearish divergences for potential trend reversals.
Dynamic Volatility Bands: Adjust to market conditions for improved signal reliability.
SharkFin Alerts: Highlights potential breakout zones when RSI reaches critical thresholds.
MBL Slope Confirmation: Confirms trend direction using the Market Base Line (MBL).
Why This Script is Closed-Source
The TDI Killer + RSI Divergence incorporates advanced calculations and optimized methodologies, providing a unique edge over open-source alternatives. By keeping the script closed-source, we ensure that these proprietary techniques remain exclusive to our users.
How to Use
Buy Signals: Triggered when RSI aligns with bullish conditions and confirmed by MBL slope.
Sell Signals: Triggered when RSI aligns with bearish conditions and confirmed by MBL slope.
SharkFin Alerts: Use these alerts to anticipate potential breakouts or reversals.
Compatibility
This indicator works across all timeframes and market types, including forex, stocks, commodities, and cryptocurrencies. It is designed for traders seeking precise and reliable trading setups.
Disclaimer
While the TDI Killer + RSI Divergence is designed to enhance trading accuracy, no indicator guarantees 100% reliability. Always apply proper risk management and combine this tool with other analysis techniques for best results.
Momentum Edge Strategy - 1D BTC OptimizedMomentum Edge Strategy - 1D BTC Optimized
Description
The Momentum Edge Strategy - 1D BTC Optimized is a trend-following and momentum-based trading strategy specifically designed and optimized for Bitcoin (BTC) on the Daily (1D) timeframe. This strategy leverages a confluence of proven technical indicators, including the Ichimoku Cloud, MACD Histogram, and Bollinger Band Width, to identify high-probability trading opportunities in trending markets.
By incorporating multi-timeframe analysis (Weekly trend confirmation) and adaptive risk management using ATR-based stop-loss levels, this strategy ensures robust performance with minimal drawdowns. It is ideal for swing traders looking to capture significant price movements while maintaining strong capital preservation.
Key Features
Trend Detection with Ichimoku Cloud:
Determines whether the market is trending bullish or bearish by analyzing price action relative to the Ichimoku Cloud.
Momentum Confirmation with MACD Histogram:
Confirms trade entries by analyzing bullish or bearish momentum using the MACD histogram.
Volatility Filtering with Bollinger Band Width:
Ensures trades are only executed in sufficiently volatile markets, reducing false signals in low-volatility conditions.
Multi-Timeframe Trend Confirmation:
Aligns entries on the Daily (1D) chart with the broader Weekly (1W) trend for enhanced signal reliability.
Dynamic Risk Management:
Uses ATR-based stop-loss levels that adapt to market volatility, ensuring tight risk control while allowing trades to breathe.
Strong Backtesting Results:
Optimized for Bitcoin on the Daily timeframe, achieving:
Net Profit: +10.80%.
Profit Factor: 2.593.
Percent Profitable: 50.70%.
Max Drawdown: -1.47%.
How It Works
Long Entry Conditions:
Price is above the Ichimoku Cloud.
MACD histogram is greater than -0.05.
Weekly trend confirmation (price above 50-period SMA on Weekly chart).
Bollinger Band Width exceeds the threshold (> 0.02).
Short Entry Conditions:
Price is below the Ichimoku Cloud.
MACD histogram is less than 0.
Weekly trend confirmation indicates bearish conditions (price below 50-period SMA on Weekly chart).
Bollinger Band Width exceeds the threshold (> 0.02).
Stop-Loss Logic:
Stop-loss levels are dynamically adjusted based on ATR and Bollinger Band Width:
In low-volatility conditions, stop-loss is set at recent highs/lows.
In high-volatility conditions, stop-loss is set using ATR multipliers.
Recommended Timeframe and Asset
Optimized for Bitcoin (BTC) on the Daily (1D) timeframe.
While designed for BTC, it may also perform well on other cryptocurrencies with similar trend-driven characteristics after proper backtesting and optimization.
Disclaimers
Not Financial Advice:
This script is provided for educational purposes only and should not be considered financial or investment advice. Always consult a qualified financial advisor before making trading decisions.
Use at Your Own Risk:
Trading involves significant risk, including the potential loss of all invested capital. Past performance is not indicative of future results.
Backtesting Limitations:
Backtesting results are based on historical data and do not account for slippage, spreads, or execution delays in live trading environments.
Timeframe-Specific Optimization:
This strategy has been specifically optimized for Bitcoin on the Daily timeframe. Performance may vary significantly on other assets or timeframes.
User Responsibility:
Users are encouraged to backtest and optimize this strategy for their specific use case before deploying it in live trading.
Users can adjust key parameters such as:
1. ATR Length (`atrLength`) and Multiplier (`atrMultiplier`) to fine-tune risk management.
2. Bollinger Band Width Threshold (`bbWidthThreshold`) to adapt volatility filtering to different assets or market conditions.
Final Thoughts
The Momentum Edge Strategy - 1D BTC Optimized has demonstrated elite-level performance metrics during backtesting on Bitcoin on the 1D timeframe. But backtesting doesn't tell the future, so study how it works, use at your own risk and enjoyment, and let me know any recommendations.
SR & VWAP Never gonna give you up
Never gonna let you down
Never gonna run around and desert you
Never gonna make you cry
Never gonna say goodbye
Never gonna tell a lie and hurt you
MA100 crash buy 3 Zone // 15 minLe but et d'acheter 24/7 lors de panique, pour revendre juste après.
MCh SRSI + MACD avec Stop-Loss et Take-Profit dynamiquesStratégie SRSI + MACD avec Stop-Loss et Take-Profit dynamiques
Cette stratégie combine l'indicateur Stochastic RSI (SRSI) et le MACD normalisé pour générer des signaux d'achat et de vente. Elle intègre également un stop-loss et un take-profit dynamiques basés sur l'ATR pour mieux gérer le risque.
1. Signaux de Trading
Achat (Buy) :
La différence entre K et D du Stochastic RSI est positive.
La différence entre K et MACD normalisé est également positive.
Le MACD ne doit pas être en phase de baisse.
Vente (Sell) :
La différence entre K et D est négative.
La différence entre K et MACD normalisé est également négative.
Le MACD ne doit pas être en phase de hausse.
2. Gestion des Risques
Stop-Loss et Take-Profit :
Le stop-loss et le take-profit sont calculés dynamiquement à partir de l'ATR multiplié par un facteur de risque.
Ils ne sont activés que si l’utilisateur le choisit.
Les niveaux de stop-loss et take-profit sont affichés sous forme de lignes jaunes avec des interruptions pour éviter un affichage continu entre les ordres.
3. Affichage sur le Graphique
Les niveaux de stop-loss et take-profit sont tracés avec plot.style_linebr, ce qui permet de ne pas afficher de lignes continues entre les trades fermés.
Les bougies K-D et K-MACD sont affichées pour visualiser les différences et mieux interpréter les signaux.
Objectif de la Stratégie
L’objectif est d’exploiter les croisements du Stochastic RSI et du MACD tout en adaptant la gestion des risques via l’ATR. Cela permet d’optimiser les entrées et sorties de position en fonction de la volatilité du marché.
BTC Day Trading Strategy with Alerts🏆 Best Indicator for BTC Day Trading:
Recommend using (EMAs) + RSI + VWAP + ATR for a well-rounded approach.
✅ Main Indicator: 9 & 21 EMA Crossover (Momentum & Trend Confirmation)
How It Works:
When the 9 EMA crosses above the 21 EMA, it signals a potential buy (bullish momentum).
When the 9 EMA crosses below the 21 EMA, it signals a potential sell (bearish momentum).
Why?: EMAs react quickly to price changes, making them perfect for day trading.
✅ Support Indicator: VWAP (Volume-Weighted Average Price)
How It Works:
Price above VWAP = bullish (only look for longs).
Price below VWAP = bearish (only look for shorts).
Why?: Institutions & large traders use VWAP to gauge fair value for intraday moves.
✅ Momentum Confirmation: RSI (Relative Strength Index, 14)
Overbought (>70) = Look for short setups.
Oversold (<30) = Look for long setups.
Best Use: Look for bullish or bearish divergences to confirm trend reversals.
✅ Risk Management: ATR (Average True Range, 14)
Helps determine stop-loss placement based on volatility.
Example: If ATR is $500, set SL at 1x or 1.5x ATR to avoid getting stopped out by normal BTC fluctuations.
🔥 Why This Strategy Works for BTC Day Trading
✅ EMA Crossover captures momentum shifts.
✅ VWAP ensures we trade in the dominant direction.
✅ RSI avoids false signals in choppy markets.
✅ ATR Stop-Loss adapts to Bitcoin's volatility.
✅ 2:1 Risk-Reward Ratio ensures good trade management.
📌 How This Script Works
✅ Buys when:
9 EMA crosses above 21 EMA (bullish momentum).
Price is above VWAP (institutional bias is bullish).
RSI is above 50 (confirming bullish momentum).
Sets SL at ATR x 1.5 below entry, TP at 2x SL.
✅ Sells when:
9 EMA crosses below 21 EMA (bearish momentum).
Price is below VWAP (institutional bias is bearish).
RSI is below 50 (confirming bearish momentum).
Sets SL at ATR x 1.5 above entry, TP at 2x SL.
Institutional Liquidity & Order Block StrategyYour script is a powerful institutional trading tool, perfect for traders who want to trade like smart money. It simplifies execution by only showing high-probability buy & sell signals based on liquidity, market structure, and order blocks.
Multi-Asset Ratio (20 vs 5) - LuchapThis indicator calculates and displays the ratio between the sum of the prices of several base assets and the sum of the prices of several quote assets. You can select up to 20 base assets and 5 quote assets, and enable or disable each asset individually to refine your analysis. This ratio allows you to quickly evaluate the relative performance of different groups of assets.
Stochastic-Dynamic Volatility Band ModelThe Stochastic-Dynamic Volatility Band Model is a quantitative trading approach that leverages statistical principles to model market volatility and generate buy and sell signals. The strategy is grounded in the concepts of volatility estimation and dynamic market regimes, where the core idea is to capture price fluctuations through stochastic models and trade around volatility bands.
Volatility Estimation and Band Construction
The volatility bands are constructed using a combination of historical price data and statistical measures, primarily the standard deviation (σ) of price returns, which quantifies the degree of variation in price movements over a specific period. This methodology is based on the classical works of Black-Scholes (1973), which laid the foundation for using volatility as a core component in financial models. Volatility is a crucial determinant of asset pricing and risk, and it plays a pivotal role in this strategy's design.
Entry and Exit Conditions
The entry conditions are based on the price’s relationship with the volatility bands. A long entry is triggered when the price crosses above the lower volatility band, indicating that the market may have been oversold or is experiencing a reversal to the upside. Conversely, a short entry is triggered when the price crosses below the upper volatility band, suggesting overbought conditions or a potential market downturn.
These entry signals are consistent with the mean reversion theory, which asserts that asset prices tend to revert to their long-term average after deviating from it. According to Poterba and Summers (1988), mean reversion occurs due to overreaction to news or temporary disturbances, leading to price corrections.
The exit condition is based on the number of bars that have elapsed since the entry signal. Specifically, positions are closed after a predefined number of bars, typically set to seven bars, reflecting a short-term trading horizon. This exit mechanism is in line with short-term momentum trading strategies discussed in literature, where traders capitalize on price movements within specific timeframes (Jegadeesh & Titman, 1993).
Market Adaptability
One of the key features of this strategy is its dynamic nature, as it adapts to the changing volatility environment. The volatility bands automatically adjust to market conditions, expanding in periods of high volatility and contracting when volatility decreases. This dynamic adjustment helps the strategy remain robust across different market regimes, as it is capable of identifying both trend-following and mean-reverting opportunities.
This dynamic adaptability is supported by the adaptive market hypothesis (Lo, 2004), which posits that market participants evolve their strategies in response to changing market conditions, akin to the adaptive nature of biological systems.
References:
Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
Bollinger, J. (1980). Bollinger on Bollinger Bands. Wiley.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Dynamic Stop Loss & Take ProfitDynamic Stop Loss & Take Profit is a versatile risk management indicator that calculates dynamic stop loss and take profit levels based on the Average True Range (ATR). This indicator helps traders set adaptive exit points by using a configurable ATR multiplier and defining whether they are in a Long (Buy) or Short (Sell) trade.
How It Works
ATR Calculation – The indicator calculates the ATR value over a user-defined period (default: 14).
Stop Loss and Take Profit Multipliers – The ATR value is multiplied by a configurable factor (ranging from 1.5 to 4) to determine volatility-adjusted stop loss and take profit levels.
Trade Type Selection – The user can specify whether they are in a Long (Buy) or Short (Sell) trade.
Long (Buy) Trade:
Stop Loss = Entry Price - (ATR × Stop Loss Multiplier)
Take Profit = Entry Price + (ATR × Take Profit Multiplier)
Short (Sell) Trade:
Stop Loss = Entry Price + (ATR × Stop Loss Multiplier)
Take Profit = Entry Price - (ATR × Take Profit Multiplier)
Features
Configurable ATR length and multipliers
Supports both long and short trades
Clearly plotted Stop Loss (red) and Take Profit (green) levels on the chart
Helps traders manage risk dynamically based on market volatility
This indicator is ideal for traders looking to set adaptive stop loss and take profit levels without relying on fixed price targets.
GER40 Momentum Breakout ScalpingThe strategy capitalizes on short-term momentum by identifying breakouts from the previous day’s price range—specifically, the previous day's high and low. It enters trades when the price moves decisively beyond these levels, with additional confirmation from fast-moving exponential moving averages (EMAs).
MA100 crash buy 3 Zone // 15 min | ETHLe but et d'acheter 24/7 lors de panique, pour revendre juste après.
Fakeout Resistant Indicator - by YaldabaothThis script, "Fakeout-Resistant Trend Master," is designed to provide highly reliable buy and sell signals while minimizing false breakouts (fakeouts). It combines multiple technical indicators to ensure strong trend confirmations before generating signals
ATR Trailing Stop by GideonMATR Trailing Stop Indicator
This ATR Trailing Stop Indicator is designed for traders who wish to enhance their exit strategies by leveraging volatility-based stops. It offers a systematic approach to trend management and risk control, enabling traders to capture extended trends while protecting their capital during market reversals. Works on Indian Indices as well.
Overview:
The ATR Trailing Stop indicator is a dynamic trend-following tool that adjusts stop levels based on market volatility. By incorporating the Average True Range (ATR), the indicator provides a flexible exit strategy that adapts to changing market conditions, helping traders lock in profits during trends and limit losses during reversals.
How It Works:
True Range and ATR Calculation:
The indicator first calculates the True Range (TR) for each bar, defined as the maximum of:
The difference between the high and low,
The absolute difference between the high and the previous close, and
The absolute difference between the low and the previous close.
Using the TR values, the ATR is computed over a user-defined period (default is 14 bars) with an option to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the smoothing method.
Trailing Stop Determination:
Two potential stop levels are calculated:
For an uptrend, the stop is determined as:
Stop = Close – (Multiplier × ATR)
For a downtrend, the stop is:
Stop = Close + (Multiplier × ATR)
The indicator maintains a persistent trailing stop that dynamically adjusts:
In an uptrend, the trailing stop only moves upward (or remains flat) to secure gains.
In a downtrend, it only moves downward, thereby protecting the position from excessive losses.
A reversal in trend is identified when the price crosses the trailing stop level, at which point the indicator flips the trend and resets the stop level accordingly.
Rationale:
Utilizing the ATR for trailing stops ensures that the stop levels are directly influenced by market volatility. This dynamic adjustment helps accommodate the natural price fluctuations of the market, providing a more adaptive risk management tool compared to fixed stop-loss levels. The approach is particularly useful in volatile markets where traditional static stops might be triggered prematurely.
Customization:
Key parameters that can be adjusted include:
ATR Period: The number of bars used to calculate the ATR.
ATR Multiplier: The factor that determines how far the trailing stop is set from the current price.
Smoothing Method: Option to choose between SMA and EMA for ATR calculation, allowing traders to tailor the sensitivity of the indicator to their specific trading style.
BTC Day Trading Strategy with Alerts(LAWY2024)🏆 Best Indicator for BTC Day Trading:
I recommend using Exponential Moving Averages (EMAs) + RSI + VWAP + ATR for a well-rounded approach.
✅ Main Indicator: 9 & 21 EMA Crossover (Momentum & Trend Confirmation)
How It Works:
When the 9 EMA crosses above the 21 EMA, it signals a potential buy (bullish momentum).
When the 9 EMA crosses below the 21 EMA, it signals a potential sell (bearish momentum).
Why?: EMAs react quickly to price changes, making them perfect for day trading.
✅ Support Indicator: VWAP (Volume-Weighted Average Price)
How It Works:
Price above VWAP = bullish (only look for longs).
Price below VWAP = bearish (only look for shorts).
Why?: Institutions & large traders use VWAP to gauge fair value for intraday moves.
✅ Momentum Confirmation: RSI (Relative Strength Index, 14)
Overbought (>70) = Look for short setups.
Oversold (<30) = Look for long setups.
Best Use: Look for bullish or bearish divergences to confirm trend reversals.
✅ Risk Management: ATR (Average True Range, 14)
Helps determine stop-loss placement based on volatility.
Example: If ATR is $500, set SL at 1x or 1.5x ATR to avoid getting stopped out by normal BTC fluctuations.
📌 How This Script Works
✅ Buys when:
9 EMA crosses above 21 EMA (bullish momentum).
Price is above VWAP (institutional bias is bullish).
RSI is above 50 (confirming bullish momentum).
Sets SL at ATR x 1.5 below entry, TP at 2x SL.
✅ Sells when:
9 EMA crosses below 21 EMA (bearish momentum).
Price is below VWAP (institutional bias is bearish).
RSI is below 50 (confirming bearish momentum).
Sets SL at ATR x 1.5 above entry, TP at 2x SL.
Customizable EMA crossover, BB TP | javieresfelizThis indicator is designed to help traders identify trend changes through the crossover of two exponential moving averages (EMA) and establish a dynamic Take Profit (TP) level based on Bollinger Bands. It is not an automated trading strategy nor does it generate buy/sell signals on its own; it is a complementary tool for technical analysis.
Features:
✅ Customizable EMA crossover – Users can define the periods for the fast and slow EMA to suit their strategy.
✅ Trend identification – Visually shows whether the price is in an uptrend, downtrend, or neutral phase.
✅ Crossover alerts – Traders can optionally enable alerts when a bullish or bearish crossover occurs.
✅ Take Profit based on Bollinger Bands – If the trend is bullish, the TP is set at the upper band; if bearish, at the lower band.
How does it work?:
-When the fast EMA crosses above the slow EMA, it is considered a possible bullish trend signal.
-When the fast EMA crosses below the slow EMA, it may indicate a potential shift to a bearish trend.
-The dynamic TP adjusts with Bollinger Bands, reflecting market volatility.
Suggested EMA fast/slow settings for different timeframes:
1m: 5 EMA / 13 EMA
5m: 9 EMA / 21 EMA
15m: 10 EMA / 30 EMA
30m: 10 EMA / 50 EMA
1h: 20 EMA / 50 EMA
4h: 21 EMA / 100 EMA
1D: 50 EMA / 200 EMA
1W: 50 EMA / 200 EMA
Limitations:
⚠️ This indicator does not guarantee profitability and should be used alongside other analysis factors.
⚠️ It does not incorporate commissions, slippage, or risk management, as it is not a backtesting strategy.
⚠️ It should not be interpreted as investment advice.
This script is designed to enhance the visual interpretation of the market and facilitate informed decision-making within technical analysis. 🚀📊
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Este indicador está diseñado para ayudar a los traders a identificar cambios de tendencia mediante el cruce de dos medias móviles exponenciales (EMA) y establecer un nivel de Take Profit (TP) dinámico basado en las Bandas de Bollinger. No es una estrategia de trading automatizada ni genera señales de compra/venta por sí sola; es una herramienta complementaria para el análisis técnico.
Características:
✅ Cruce de EMAs personalizable – Los usuarios pueden definir los períodos de la EMA rápida y la EMA lenta para ajustarse a su estrategia.
✅ Identificación de tendencias – Muestra visualmente si el precio se encuentra en una tendencia alcista, bajista o neutral.
✅ Alertas de cruce – Opcionalmente, los traders pueden activar alertas cuando ocurre un cruce alcista o bajista.
✅ Take Profit basado en Bandas de Bollinger – Si la tendencia es alcista, el TP se establece en la banda superior; si es bajista, en la banda inferior.
¿Cómo funciona?:
-Cuando la EMA rápida cruza por encima de la EMA lenta, se considera una posible señal de tendencia alcista.
-Cuando la EMA rápida cruza por debajo de la EMA lenta, puede indicar un posible cambio a tendencia bajista.
-El TP dinámico se ajusta con las Bandas de Bollinger, reflejando la volatilidad del mercado.
Sugerencia para usar EMA rápida/lenta en diferentes temporalidades:
1m: 5 EMA / 13 EMA
5m: 9 EMA / 21 EMA
15m: 10 EMA / 30 EMA
30m: 10 EMA / 50 EMA
1h: 20 EMA / 50 EMA
4h: 21 EMA / 100 EMA
1D: 50 EMA / 200 EMA
1W: 50 EMA / 200 EMA
Limitaciones:
⚠️ Este indicador no garantiza rentabilidad y debe utilizarse junto con otros factores de análisis.
⚠️ No incorpora comisiones, deslizamiento ni gestión de riesgo, ya que no es una estrategia de backtesting.
⚠️ No se debe interpretar como una recomendación de inversión.
Este script está diseñado para mejorar la interpretación visual del mercado y facilitar la toma de decisiones informadas dentro del análisis técnico. 🚀📊
Refined Ichimoku with MACD and RSI Strategy - HTF OptimizedIndicator Summary: Refined Ichimoku with MACD and RSI Strategy
Philosophy and Approach
The "Refined Ichimoku with MACD and RSI Strategy" is designed as a hybrid trend-following and range-bound trading strategy. It leverages the Ichimoku Cloud for market regime detection, MACD for momentum confirmation, RSI for overbought/oversold conditions, and ATR for dynamic stop-loss placement. The strategy seeks to capture trends in trending markets while also identifying reversal opportunities in range-bound conditions.
Core Philosophy:
Use the Ichimoku Cloud as the foundation for detecting trending vs. range-bound markets.
Combine multiple indicators (MACD, RSI, Stochastic RSI) to improve signal quality and reduce false entries.
Implement robust risk management using ATR-based stop-loss levels.
Approach:
Trending Markets: Enter long trades when price is above the Ichimoku Cloud with bullish momentum (e.g., RSI > 55, MACD histogram > 0). Enter short trades when price is below the cloud with bearish momentum.
Range-Bound Markets: Enter mean-reversion trades at overbought/oversold levels (e.g., RSI < 30 or > 70, Stochastic RSI extremes).
Strengths
Robust Market Regime Detection:
The Ichimoku Cloud effectively distinguishes between trending and range-bound markets, allowing the strategy to adapt dynamically.
Confluence of Indicators:
The use of MACD, RSI, and Stochastic RSI ensures that trades are only taken when multiple conditions align, reducing false signals.
Dynamic Risk Management:
ATR-based stop-loss levels adapt to market volatility, minimizing drawdowns while allowing trades to breathe.
Visualization:
Highlights trending markets (green background) and range-bound markets (red background) for easy interpretation.
Plots the Ichimoku Cloud for visual confirmation of market structure.
Performance on Higher Timeframes:
Backtesting results show strong performance on daily (D1) charts, with a profit factor of 2.159 and a net profit of +10.71% over the testing period.
Weaknesses
Low Percent Profitable:
Across all timeframes, the percent profitable is below 40%, indicating that many trades are unprofitable.
This suggests that the entry/exit logic may need further refinement.
Overtrading on Lower Timeframes:
On H4 charts, the strategy executed 430 trades with a profit factor of only 1.219, indicating overtrading and reduced efficiency.
Missed Opportunities in Range-Bound Markets:
While designed to trade reversals in range-bound conditions, the strategy's filters may be too restrictive, leading to missed opportunities.
Complexity:
The combination of multiple indicators (Ichimoku Cloud, MACD, RSI, Stochastic RSI) increases complexity, which may make it harder for users to understand or optimize.
Recommended Timeframes
Daily (D1):
Best performance observed during backtesting.
Strong profit factor (2.159) and manageable drawdowns (-2.10%) make it ideal for swing traders looking to capture long-term trends.
4-Hour (H4):
Marginal profitability observed during backtesting (profit factor of 1.219).
Suitable for traders willing to refine filters to reduce overtrading and improve signal quality.
Avoid Lower Timeframes (e.g., M15):
High noise levels lead to frequent false signals and poor profitability.
Performance Metrics from Backtesting (BTCUSDT)
Timeframe Net Profit Profit Factor Total Trades Percent Profitable Max Drawdown
Daily (D1) +10.71% 2.159 58 37.93% 2.10%
4-Hour (H4) +6.16% 1.219 430 32.56% 2.47%
Final Thoughts
The "Refined Ichimoku with MACD and RSI Strategy" is a versatile tool for traders who prefer higher timeframes like D1 or H4 charts. While it excels in capturing long-term trends with robust risk management, it struggles with low percent profitable rates and overtrading on lower timeframes. By focusing on simplicity and refining entry/exit logic, this strategy has the potential to deliver consistent results for swing traders seeking a balance between trend-following and mean-reversion approaches. By making the code open, it is hoped that experts might be able to adjust the variables within the script to their liking while still benefiting from the overall approach and philosophy of the strategy.
Regarding the three Strategy Indicator Settings:
1. Conversion Line Length (Default: 9)
What It Does:
The Conversion Line (Tenkan-sen) is a short-term moving average that represents the midpoint of the highest high and lowest low over the specified period (default: 9).
It acts as a fast-moving signal line, similar to a short-term moving average.
Recommendations:
Default Setting (9): Works well for most timeframes, especially higher timeframes like Daily (D1) or Weekly, as it captures short-term momentum effectively.
Shorter Timeframes (M15, H1): Consider reducing this value to 6 or 7 to make the Conversion Line more responsive to rapid price changes.
Higher Timeframes (D1, Weekly): Stick with the default value of 9 to avoid excessive noise.
When to Adjust:
Decrease if you want faster signals for scalping or intraday trading.
Increase slightly (e.g., to 10 or 12) if you want smoother signals for swing trading.
2. Base Line Length (Default: 26)
What It Does:
The Base Line (Kijun-sen) is a medium-term moving average that represents the midpoint of the highest high and lowest low over the specified period (default: 26).
It serves as a key support/resistance level and a trend confirmation signal when crossed by the Conversion Line.
Recommendations:
Default Setting (26): Standard for most markets and timeframes. It balances responsiveness with stability.
Shorter Timeframes: Reduce to 20–22 for faster signals in volatile markets.
Higher Timeframes: Stick with the default value of 26 or increase slightly to 30 for smoother trend confirmation.
When to Adjust:
Decrease for quicker trend signals in fast-moving markets.
Increase for long-term trading strategies where you want stronger support/resistance levels.
3. Lagging Span Length (Default: 52)
What It Does:
The Lagging Span (Chikou Span) plots the current closing price shifted backward by the specified number of periods (default: 52).
It helps confirm trends by comparing current price action to past price levels.
Recommendations:
Default Setting (52): Works well across most timeframes, as it aligns with traditional Ichimoku settings designed for long-term trends.
Shorter Timeframes: Reduce slightly to around 40–45 if you want quicker trend confirmations in intraday trading.
Higher Timeframes: Keep at the default value of 52, as it provides reliable confirmation of long-term trends.
When to Adjust:
Decrease for faster confirmation in high-volatility environments.
Increase only if you are focusing on very long-term trends, such as on Monthly charts.
General Disclaimer
Not Financial Advice:
This script is provided for educational and informational purposes only. It should not be considered financial or investment advice. Always consult with a qualified financial advisor before making trading decisions.
Use at Your Own Risk:
Trading involves significant risk, and past performance is not indicative of future results. Users are solely responsible for any losses incurred while using this strategy.
No Guarantee of Profitability:
While this strategy has been backtested on historical data, there is no guarantee that it will perform similarly in live market conditions due to differences in market behavior, slippage, and latency.
Technical Disclaimer
Indicator Limitations:
This strategy relies on technical indicators such as the Ichimoku Cloud, MACD, RSI, and ATR. These indicators are lagging or reactive by nature and may not accurately predict future price movements.
Timeframe-Specific Performance:
This strategy has shown better performance on higher timeframes (e.g., Daily). It may not perform well on lower timeframes (e.g., M15) due to increased market noise.
Customization Required:
The default settings (e.g., Conversion Line Length = 9, Base Line Length = 26, Lagging Span Length = 52) are optimized for general use but may require adjustment based on the user's trading style, asset class, or timeframe.
Market Risks Disclaimer
Market Conditions Matter:
The effectiveness of this strategy depends heavily on market conditions. It performs best in trending markets and may struggle in highly volatile or range-bound environments without adjustments.
Slippage and Execution Risks:
Backtesting results do not account for slippage, spreads, or order execution delays that occur in live trading environments.
No Adaptation to News Events:
This strategy does not incorporate fundamental analysis or news events that can significantly impact price movements.
User Responsibility Disclaimer
Backtesting and Optimization:
Users are encouraged to backtest and optimize the strategy on their chosen assets and timeframes before deploying it in live trading.
Monitor Regularly:
This strategy is not a "set-and-forget" tool. Users should monitor trades regularly and adjust settings as needed to adapt to changing market conditions.
Risk Management Required:
Proper risk management practices (e.g., position sizing, stop-loss placement) are crucial when using this strategy to minimize potential losses.
Market SessionsThis script was inspired by Simple Market Session by tradergav.
I have improved and optimized it, making it compatible with Pine Script v6 and adding new features/enhancements.
All credit to the original author for the initial idea.
1. Purpose
The script highlights four major market sessions on your TradingView chart — Sydney, Tokyo, London, and New York. Each session is displayed as a colored background during its active hours.
2. How it Works
Default Times in UTC+1
The script starts with fixed session times (in UTC+1 time).
Adjusting to Your Timezone
You tell the script your own UTC offset. The script then shifts each session’s start/end time so they appear correctly in your local time on the chart.
**For example, if you set your timezone to UTC+3, the script calculates the difference from its default base (UTC+1), which is +2 hours, and shifts all the session times by that amount.
In simple terms:
You pick your local timezone offset, and the indicator automatically shows when each of the four major sessions is open in your local time on your TradingView chart. That’s it!
Institutional Liquidity & Order Block StrategyYour script is a powerful institutional trading tool, perfect for traders who want to trade like smart money. It simplifies execution by only showing high-probability buy & sell signals based on liquidity, market structure, and order blocks.
ICT Master Final**Title:** ICT Master Final – Advanced Smart Money Concepts Indicator
**Description:**
The **ICT Master Final** indicator is a powerful tool designed for traders utilizing **Smart Money Concepts (SMC)** and **ICT (Inner Circle Trader) methodology**. It helps identify critical price action patterns such as **Fair Value Gaps (FVGs), Order Blocks (OBs), and Kill Zones**, offering precise trade setups in high-probability areas.
### **Key Features:**
✅ **Fair Value Gaps (FVGs)** – Highlights bullish and bearish FVG zones for potential liquidity imbalances.
✅ **Order Blocks (OBs)** – Detects significant bullish and bearish order blocks based on price action and ATR thresholds.
✅ **Kill Zones** – Identifies key trading sessions (New York Morning & Afternoon) where institutional activity is prevalent.
✅ **Custom Alerts** – Get notified when an order block aligns with a kill zone for high-probability trade setups.
### **How It Works:**
- **FVGs Detection:** Finds gaps in price structure, marking areas where price may return to fill liquidity.
- **Order Blocks Identification:** Detects strong institutional levels based on market structure shifts.
- **Kill Zones Highlighting:** Displays optimal trading times using New York session timing (9:30-11:30 AM & 12:30-4:00 PM EST).
### **Who Is This For?**
📈 **Day Traders & Scalpers** – Ideal for those trading intraday liquidity.
📊 **ICT & SMC Traders** – Perfect for traders following institutional trading strategies.
🔍 **Forex, Indices, Crypto Traders** – Works across multiple asset classes and timeframes.
**🚀 Add this to your chart and enhance your trading precision with institutional-grade insights!**
