EMA RSI Trend Reversal Ver.1Overview:
The EMA RSI Trend Reversal indicator combines the power of two well-known technical indicators—Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI)—to identify potential trend reversal points in the market. The strategy looks for key crossovers between the fast and slow EMAs, and uses the RSI to confirm the strength of the trend. This combination helps to avoid false signals during sideways market conditions.
How It Works:
Buy Signal:
The Fast EMA (9) crosses above the Slow EMA (21), indicating a potential shift from a downtrend to an uptrend.
The RSI is above 50, confirming strong bullish momentum.
Visual Signal: A green arrow below the price bar and a Buy label are plotted on the chart.
Sell Signal:
The Fast EMA (9) crosses below the Slow EMA (21), indicating a potential shift from an uptrend to a downtrend.
The RSI is below 50, confirming weak or bearish momentum.
Visual Signal: A red arrow above the price bar and a Sell label are plotted on the chart.
Key Features:
EMA Crossovers: The Fast EMA crossing above the Slow EMA signals potential buying opportunities, while the Fast EMA crossing below the Slow EMA signals potential selling opportunities.
RSI Confirmation: The RSI helps confirm trend strength—values above 50 indicate bullish momentum, while values below 50 indicate bearish momentum.
Visual Cues: The strategy uses green arrows and red arrows along with Buy and Sell labels for clear visual signals of when to enter or exit trades.
Signal Interpretation:
Green Arrow / Buy Label: The Fast EMA (9) has crossed above the Slow EMA (21), and the RSI is above 50. This is a signal to buy or enter a long position.
Red Arrow / Sell Label: The Fast EMA (9) has crossed below the Slow EMA (21), and the RSI is below 50. This is a signal to sell or exit the long position.
Strategy Settings:
Fast EMA Length: Set to 9 (this determines how sensitive the fast EMA is to recent price movements).
Slow EMA Length: Set to 21 (this smooths out price movements to identify the broader trend).
RSI Length: Set to 14 (default setting to track momentum strength).
RSI Level: Set to 50 (used to confirm the strength of the trend—above 50 for buy signals, below 50 for sell signals).
Risk Management (Optional):
Use take profit and stop loss based on your preferred risk-to-reward ratio. For example, you can set a 2:1 risk-to-reward ratio (2x take profit for every 1x stop loss).
Backtesting and Optimization:
Backtest the strategy on TradingView by opening the Strategy Tester tab. This will allow you to see how the strategy would have performed on historical data.
Optimization: Adjust the EMA lengths, RSI period, and risk-to-reward settings based on your asset and time frame.
Limitations:
False Signals in Sideways Markets: Like any trend-following strategy, this indicator may generate false signals during periods of low volatility or sideways movement.
Not Suitable for All Market Conditions: This indicator performs best in trending markets. It may underperform in choppy or range-bound markets.
Strategy Example:
XRP/USD Example:
If you're trading XRP/USD and the Fast EMA (9) crosses above the Slow EMA (21), while the RSI is above 50, the indicator will signal a Buy.
Conversely, if the Fast EMA (9) crosses below the Slow EMA (21), and the RSI is below 50, the indicator will signal a Sell.
Bitcoin (BTC/USD):
On the BTC/USD chart, when the indicator shows a green arrow and a Buy label, it’s signaling a potential long entry. Similarly, a red arrow and Sell label indicate a short entry or exit from a previous long position.
Summary:
The EMA RSI Trend Reversal Indicator helps traders identify potential trend reversals with clear buy and sell signals based on the EMA crossovers and RSI confirmations. By using green arrows and red arrows, along with Buy and Sell labels, this strategy offers easy-to-understand visual signals for entering and exiting trades. Combine this with effective risk management and backtesting to optimize your trading performance.
Indicators and strategies
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
IU 4 Bar UP StrategyIU 4 Bar UP Strategy
The IU 4 Bar UP Strategy is a trend-following strategy designed to identify and execute long trades during strong bullish momentum, combined with confirmation from the SuperTrend indicator. This strategy is suitable for traders aiming to capitalize on sustained upward market movements.
Features :
1. SuperTrend Confirmation: Incorporates the SuperTrend indicator as a dynamic support/resistance line to filter trades in the direction of the trend.
2. 4 Consecutive Bullish Bars: Detects a series of 4 bullish candles as a signal for strong upward momentum, ensuring robust trade setups.
3. Dynamic Alerts: Sends alerts for trade entries and exits to keep traders informed.
4. Visual Enhancements:
- Plots the SuperTrend indicator on the chart.
- Changes the background color while a trade is active for easy visualization.
Inputs :
- SuperTrend ATR Period: The period used to calculate the Average True Range (ATR) for the SuperTrend indicator.
- SuperTrend ATR Factor: The multiplier for the ATR in the SuperTrend calculation.
Entry Conditions :
A long entry is triggered when:
1. The last 4 consecutive candles are bullish (closing prices are higher than opening prices).
2. The current price is above the SuperTrend line.
3. The strategy is not already in a position.
4. The bar is confirmed (not a partially formed bar).
When all these conditions are met, the strategy enters a long position and provides an alert:
"Long Entry triggered"
Exit Conditions :
The strategy exits the long position when:
1. The closing price drops below the SuperTrend line.
2. An alert is generated: "Close the long Trade"
Visualization :
- The SuperTrend line is plotted, dynamically colored:
- Green when the trend is bullish.
- Red when the trend is bearish.
- The background color turns semi-transparent green while a trade is active, indicating a long position.
Do use proper risk management while using this strategy.
Stronger V4.0 - Optimized Trading Strategy
Name: Stronger V4.0 - Optimized Trading Strategy
Introduction:
Stronger V4.0 is a structured trading strategy designed to identify and act on market breakout and reversal opportunities. By employing advanced filtering tools such as RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), and Bollinger Bands, this strategy aims to reduce market noise and provide reliable trading signals.
The strategy dynamically adapts to changing market conditions, focusing on delivering high-quality signals rather than frequent ones. This allows traders to approach markets with more confidence and clarity.
How the Strategy Works and Key Features:
How Stronger V4.0 Works:
Stronger V4.0 combines advanced technical indicators and custom logic to identify optimal entry and exit points in the market. By dynamically integrating filters like RSI, MACD, and Bollinger Bands, the strategy adjusts to market conditions and minimizes noise to deliver high-quality signals.
Key Features:
Dynamic Price Analysis:
Tracks price movements within specific periods to detect breakout and reversal opportunities.
Advanced Filtering Mechanisms:
RSI Filter: Avoids trades in overbought/oversold market conditions.
MACD Filter: Confirms market momentum and trend direction.
Bollinger Bands: Adapts thresholds based on market volatility.
Risk Management:
Limits trade risk to sustainable levels to preserve equity.
Encourages consistent growth by maintaining a maximum risk per trade.
Customizable Parameters:
Users can toggle long or short trades and adjust filter settings to match their trading preferences.
Minimalist Display:
Focuses on essential signals only, ensuring a clean and easy-to-read chart layout.
Market Breakout Identification:
One of Stronger V4.0's core functionalities is identifying significant breakout points. These breakout points are calculated based on dynamic price movements and market momentum.
Key moments are highlighted when the price exits a consolidation phase and transitions into a new trend. These points represent strong market opportunities, offering actionable insights for traders.
Using adjustable period settings, the strategy enables traders to tailor the analysis to their preferred timeframe and trading style. By eliminating market noise, Stronger V4.0 helps traders focus on high-probability setups and make informed decisions during volatile conditions.
Why Stronger V4.0 Stands Out:
Adaptive Filters:
Dynamically integrates RSI, MACD, and Bollinger Bands to reduce noise and highlight high-probability setups.
Precision Execution:
Focuses on executing trades at optimal moments, ensuring a balance between sustainability and profitability.
Rigorous Testing:
Extensively backtested under realistic market conditions for consistent performance.
Tailored and Exclusive:
Designed for traders seeking a balance between quality and adaptability.
Risk Disclaimer:
Stronger V4.0 has been backtested under various market conditions; however, past performance does not guarantee future results. The strategy is provided as-is, and traders are encouraged to test it thoroughly and apply appropriate risk management measures. Always trade responsibly.
Temporary Help Services Jobs - Trend Allocation StrategyThis strategy is designed to capitalize on the economic trends represented by the Temporary Help Services (TEMPHELPS) index, which is published by the Federal Reserve Economic Data (FRED). Temporary Help Services Jobs are often regarded as a leading indicator of labor market conditions, as changes in temporary employment levels frequently precede broader employment trends.
Methodology:
Data Source: The strategy uses the FRED dataset TEMPHELPS for monthly data on temporary help services.
Trend Definition:
Uptrend: When the current month's value is greater than the previous month's value.
Downtrend: When the current month's value is less than the previous month's value.
Entry Condition: A long position is opened when an uptrend is detected, provided no position is currently held.
Exit Condition: The long position is closed when a downtrend is detected.
Scientific Basis:
The TEMPHELPS index serves as a leading economic indicator, as noted in studies analyzing labor market cyclicality (e.g., Katz & Krueger, 1999). Temporary employment is often considered a proxy for broader economic conditions, particularly in predicting recessions or recoveries. Incorporating this index into trading strategies allows for aligning trades with potential macroeconomic shifts, as suggested by research on employment trends and market performance (Autor, 2001; Valetta & Bengali, 2013).
Usage:
This strategy is best suited for long-term investors or macroeconomic trend followers who wish to leverage labor market signals for equity or futures trading. It operates exclusively on end-of-month data, ensuring minimal transaction costs and noise.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
Moving Average Crossover Strategy with Take Profit and Stop LossThe Moving Average Crossover Strategy is a popular trading technique that utilizes two moving averages (MAs) of different periods to identify potential buy and sell signals. By incorporating take profit and stop loss levels, traders can effectively manage their risk while maximizing potential returns. Here’s a detailed explanation of how this strategy works:
Overview of the Moving Average Crossover Strategy
Moving Averages:
A short-term moving average (e.g., 50-day MA) reacts more quickly to price changes, while a long-term moving average (e.g., 200-day MA) smooths out price fluctuations over a longer period.
The strategy generates trading signals based on the crossover of these two averages:
Buy Signal: When the short-term MA crosses above the long-term MA (often referred to as a "Golden Cross").
Sell Signal: When the short-term MA crosses below the long-term MA (known as a "Death Cross").
Implementing Take Profit and Stop Loss
1. Setting Take Profit Levels
Definition: A take profit order automatically closes a trade when it reaches a specified profit level.
Strategy:
Determine a realistic profit target based on historical price action, support and resistance levels, or a fixed risk-reward ratio (e.g., 2:1).
For instance, if you enter a buy position at $100, you might set a take profit at $110 if you anticipate that level will act as resistance.
2. Setting Stop Loss Levels
Definition: A stop loss order limits potential losses by closing a trade when the price reaches a specified level.
Strategy:
Place the stop loss just below the most recent swing low for buy orders or above the recent swing high for sell orders.
Alternatively, you can use a percentage-based method (e.g., 2-3% below the entry point) to define your stop loss.
For example, if you enter a buy position at $100 with a stop loss set at $95, your maximum loss would be limited to $5 per share.
Example of Using Moving Average Crossover with Take Profit and Stop Loss
Entry Signal:
You observe that the 50-day MA crosses above the 200-day MA at $100. You enter a buy position.
Setting Take Profit and Stop Loss:
You analyze historical price levels and set your take profit at $110.
You place your stop loss at $95 based on recent swing lows.
Trade Management:
If the price rises to $110, your take profit order is executed, securing your profit.
If the price falls to $95, your stop loss is triggered, limiting your losses.
Relative StrengthThis strategy employs a custom "strength" function to assess the relative strength of a user-defined source (e.g., closing price, moving average) compared to its historical performance over various timeframes (8, 34, 20, 50, and 200 periods). The strength is calculated as a percentage change from an Exponential Moving Average (EMA) for shorter timeframes and a Simple Moving Average (SMA) for longer timeframes. Weights are then assigned to each timeframe based on a logarithmic scale, and a weighted average strength is computed.
Key Features:
Strength Calculation:
Calculates the relative strength of the source using EMAs and SMAs over various timeframes.
Assigns weights to each timeframe based on a logarithmic scale, emphasizing shorter timeframes.
Calculates a weighted average strength for a comprehensive view.
Visualizations:
Plots the calculated strength as a line, colored green for positive strength and red for negative strength.
Fills the background area below the line with green for positive strength and red for negative strength, enhancing visualization.
Comparative Analysis:
Optionally displays the strength of Bitcoin (BTC), Ethereum (ETH), S&P 500, Nasdaq, and Dow Jones Industrial Average (DJI) for comparison with the main source strength.
Backtesting:
Allows users to specify a start and end time for backtesting the strategy's performance.
Trading Signals:
Generates buy signals when the strength turns positive from negative and vice versa for sell signals.
Entry and exit are conditional on the backtesting time range.
Basic buy and sell signal plots are commented out (can be uncommented for visual representation).
Risk Management:
Closes all open positions and cancels pending orders outside the backtesting time range.
Disclaimer:
Backtesting results do not guarantee future performance. This strategy is for educational purposes only and should be thoroughly tested and refined before risking capital.
Additional Notes:
- The strategy uses a custom "strength" function that can be further customized to explore different timeframes and weighting schemes.
- Consider incorporating additional technical indicators or filters to refine the entry and exit signals.
- Backtesting with different parameters and market conditions is crucial for evaluating the strategy's robustness.
McClellan A-D Volume Integration ModelThe strategy integrates the McClellan A-D Oscillator with an adjustment based on the Advance/Decline (A-D) volume data. The McClellan Oscillator is calculated by taking the difference between the short-term and long-term exponential moving averages (EMAs) of the A-D line. This strategy introduces an enhancement where the A-D volume (the difference between the advancing and declining volume) is factored in to adjust the oscillator value.
Inputs:
• ema_short_length: The length for the short-term EMA of the A-D line.
• ema_long_length: The length for the long-term EMA of the A-D line.
• osc_threshold_long: The threshold below which the oscillator must drop for an entry signal to trigger.
• exit_periods: The number of periods after which the position is closed.
• Data Sources:
• ad_advance and ad_decline are the data sources for advancing and declining issues, respectively.
• vol_advance and vol_decline are the volume data for the advancing and declining issues. If volume data is unavailable, it defaults to na (Not Available), and the fallback logic ensures that the strategy continues to function.
McClellan Oscillator with Volume Adjustment:
• The A-D line is calculated by subtracting the declining issues from the advancing issues. Then, the volume difference is applied to this line, creating a “weighted” A-D line.
• The short and long EMAs are calculated for the weighted A-D line to generate the McClellan Oscillator.
Entry Condition:
• The strategy looks for a reversal signal, where the oscillator falls below the threshold and then rises above it again. The condition is designed to trigger a long position when this reversal happens.
Exit Condition:
• The position is closed after a set number of periods (exit_periods) have passed since the entry.
Plotting:
• The McClellan Oscillator and the threshold are plotted on the chart for visual reference.
• Entry and exit signals are highlighted with background colors to make the signals more visible.
Scientific Background:
The McClellan A-D Oscillator is a popular market breadth indicator developed by Sherman and Marian McClellan. It is used to gauge the underlying strength of a market by analyzing the difference between the number of advancing and declining stocks. The oscillator is typically calculated using exponential moving averages (EMAs) of the A-D line, with the idea being that crossovers of these EMAs indicate potential changes in the market’s direction.
The integration of A-D volume into this model adds another layer of analysis, as volume is often considered a leading indicator of price movement. By factoring in volume, the strategy becomes more sensitive to not just the number of advancing or declining stocks but also how significant those movements are based on trading volume, as discussed in Schwager, J. D. (1999). Technical Analysis of the Financial Markets. This enhanced version aims to capture stronger and more sustainable trends in the market, helping to filter out false signals.
Additionally, volume analysis is often used to confirm price movements, as described in Wyckoff, R. (1931). The Day Trading System. Therefore, incorporating the volume of advancing and declining stocks in the McClellan Oscillator offers a more robust signal for trading decisions.
Z-Strike RecoveryThis strategy utilizes the Z-Score of daily changes in the VIX (Volatility Index) to identify moments of extreme market panic and initiate long entries. Scientific research highlights that extreme volatility levels often signal oversold markets, providing opportunities for mean-reversion strategies.
How the Strategy Works
Calculation of Daily VIX Changes:
The difference between today’s and yesterday’s VIX closing prices is calculated.
Z-Score Calculation:
The Z-Score quantifies how far the current change deviates from the mean (average), expressed in standard deviations:
Z-Score=(Daily VIX Change)−MeanStandard Deviation
Z-Score=Standard Deviation(Daily VIX Change)−Mean
The mean and standard deviation are computed over a rolling period of 16 days (default).
Entry Condition:
A long entry is triggered when the Z-Score exceeds a threshold of 1.3 (adjustable).
A high positive Z-Score indicates a strong overreaction in the market (panic).
Exit Condition:
The position is closed after 10 periods (days), regardless of market behavior.
Visualizations:
The Z-Score is plotted to make extreme values visible.
Horizontal threshold lines mark entry signals.
Bars with entry signals are highlighted with a blue background.
This strategy is particularly suitable for mean-reverting markets, such as the S&P 500.
Scientific Background
Volatility and Market Behavior:
Studies like Whaley (2000) demonstrate that the VIX, known as the "fear gauge," is highly correlated with market panic phases. A spike in the VIX is often interpreted as an oversold signal due to excessive hedging by investors.
Source: Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Z-Score in Financial Strategies:
The Z-Score is a proven method for detecting statistical outliers and is widely used in mean-reversion strategies.
Source: Chan, E. (2009). Quantitative Trading. Wiley Finance.
Mean-Reversion Approach:
The strategy builds on the mean-reversion principle, which assumes that extreme market movements tend to revert to the mean over time.
Source: Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
three Supertrend EMA Strategy by Prasanna +DhanuThe indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
Trend Trader-Remastered StrategyOfficial Strategy for Trend Trader - Remastered
Indicator: Trend Trader-Remastered (TTR)
Overview:
The Trend Trader-Remastered is a refined and highly sophisticated implementation of the Parabolic SAR designed to create strategic buy and sell entry signals, alongside precision take profit and re-entry signals based on marked Bill Williams (BW) fractals. Built with a deep emphasis on clarity and accuracy, this indicator ensures that only relevant and meaningful signals are generated, eliminating any unnecessary entries or exits.
Please check the indicator details and updates via the link above.
Important Disclosure:
My primary objective is to provide realistic strategies and a code base for the TradingView Community. Therefore, the default settings of the strategy version of the indicator have been set to reflect realistic world trading scenarios and best practices.
Key Features:
Strategy execution date&time range.
Take Profit Reduction Rate: The percentage of progressive reduction on active position size for take profit signals.
Example:
TP Reduce: 10%
Entry Position Size: 100
TP1: 100 - 10 = 90
TP2: 90 - 9 = 81
Re-Entry When Rate: The percentage of position size on initial entry of the signal to determine re-entry.
Example:
RE When: 50%
Entry Position Size: 100
Re-Entry Condition: Active Position Size < 50
Re-Entry Fill Rate: The percentage of position size on initial entry of the signal to be completed.
Example:
RE Fill: 75%
Entry Position Size: 100
Active Position Size: 50
Re-Entry Order Size: 25
Final Active Position Size:75
Important: Even RE When condition is met, the active position size required to drop below RE Fill rate to trigger re-entry order.
Key Points:
'Process Orders on Close' is enabled as Take Profit and Re-Entry signals must be executed on candle close.
'Calculate on Every Tick' is enabled as entry signals are required to be executed within candle time.
'Initial Capital' has been set to 10,000 USD.
'Default Quantity Type' has been set to 'Percent of Equity'.
'Default Quantity' has been set to 10% as the best practice of investing 10% of the assets.
'Currency' has been set to USD.
'Commission Type' has been set to 'Commission Percent'
'Commission Value' has been set to 0.05% to reflect the most realistic results with a common taker fee value.
VIX Spike StrategyThis script implements a trading strategy based on the Volatility Index (VIX) and its standard deviation. It aims to enter a long position when the VIX exceeds a certain number of standard deviations above its moving average, which is a signal of a volatility spike. The position is then exited after a set number of periods.
VIX Symbol (vix_symbol): The input allows the user to specify the symbol for the VIX index (typically "CBOE:VIX").
Standard Deviation Length (stddev_length): The number of periods used to calculate the standard deviation of the VIX. This can be adjusted by the user.
Standard Deviation Multiplier (stddev_multiple): This multiplier is used to determine how many standard deviations above the moving average the VIX must exceed to trigger a long entry.
Exit Periods (exit_periods): The user specifies how many periods after entering the position the strategy will exit the trade.
Strategy Logic:
Data Loading: The script loads the VIX data, both for the current timeframe and as a rescaled version for calculation purposes.
Standard Deviation Calculation: It calculates both the moving average (SMA) and the standard deviation of the VIX over the specified period (stddev_length).
Entry Condition: A long position is entered when the VIX exceeds the moving average by a specified multiple of its standard deviation (calculated as vix_mean + stddev_multiple * vix_stddev).
Exit Condition: After the position is entered, it will be closed after the user-defined number of periods (exit_periods).
Visualization:
The VIX is plotted in blue.
The moving average of the VIX is plotted in orange.
The threshold for the VIX, which is the moving average plus the standard deviation multiplier, is plotted in red.
The background turns green when the entry condition is met, providing a visual cue.
Sources:
The VIX is often used as a measure of market volatility, with high values indicating increased uncertainty in the market.
Standard deviation is a statistical measure of the variability or dispersion of a set of data points. In financial markets, it is used to measure the volatility of asset prices.
References:
Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics.
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy.
IU open equal to high/low strategyIU open equal to high/low strategy:
The "IU Open Equal to High/Low Strategy" is designed to identify and trade specific market conditions where the day's first price action shows a strong directional bias. This strategy automatically enters trades based on the relationship between the market's open price and its first high or low of the day.
Entry Conditions:
1. Long Entry: A long position is initiated when the first open price of the session equals the day's first low. This signals a potential upward move.
2. Short Entry: A short position is initiated when the first open price of the session equals the day's first high. This signals a potential downward move.
Exit Conditions:
1. Stop Loss (SL): For both long and short trades, the stop loss is calculated based on the low or high of the candle where the position was entered.
2. Take Profit (TP): The take profit is set using a Risk-to-Reward (RTR) ratio, which is customizable by the user. The TP is calculated relative to the entry price and the distance between the entry and the stop loss.
Additional Features:
- Plots are used to visualize the entry price, stop loss, and take profit levels directly on the chart, providing clear and actionable insights.
- Labels are displayed to indicate the occurrence of the "Open == Low" or "Open == High" conditions for easier identification of potential trade setups.
- A dynamic fill highlights the areas between the entry price and the stop loss or take profit, offering a clear visual representation of the trade's risk and reward zones.
This strategy is designed for traders looking to capitalize on directional momentum at the start of the trading session. It is customizable, allowing users to set their desired Risk-to-Reward ratio and tailor the strategy to fit their trading style.
MFS-3 Bars Pattern Strategy3 Bar Pattern Strategy
Detects an Ignite Candle followed by a Pullback Candle followed by a Confirmation Candle.
A Box will be drawn around the setup and three arrows will identify I, P, C (Ignite, Pullback, Confirmation) the setup.
The strategy will calculate a Stop Loss below the Low Price of the Ignite candle and a Take Profit at 2 times the Stop Loss giving a Risk to Reward Ratio of 1:2.
Extra conditions are included to reduce false triggers:
- A down trend must be detected using 3 SMA (Long, Medium, Short) that should be aligned from Long to Short one above the other.
- The Ignite Candle's body must be BELOW the Short SMA
An input form is available to adjust some strategy parameters.
Performance Note
----------------------
Trading conditions are very strict, so most of the time, no signals will be detected in the Strategy window.
This strategy should only be one of many strategies used for trade setups.
Hope you enjoy it.
Pivot & Source Cross StrategyPivot & ZoneCross Strategy V2
A powerful trading script combining Pivot Points, Retracement Zones, and Dynamic Stop-Loss Management. Suitable for beginners and advanced traders.
Introduction
This script enables traders to leverage Pivot Points and retracement zones for precise entry and exit points. Using price crossover detection and customizable stop-loss management, it offers a structured approach to trading various market conditions.
Features
Pivot Point Calculations: Select between Classic or Fibonacci methods for precise support and resistance levels.
Zone-Based Entry Signals: Identify price crossovers with retracement levels for optimal trade timing.
Customizable Stop-Loss Management: Automatically adjusts stop-loss levels to secure profits or limit losses.
Support for Market or Limit Orders: Choose instant market execution or specific limit entry points.
Flexible Inputs for Sources: Use Source First and Source Second to integrate external indicators like RSI and RSI MA, providing advanced customization options.
Visualization of Key Levels: Easily track retracement zones, Pivot Points, and stop-loss levels directly on the chart.
Configurable Conditions: Tailor entry/exit logic for your trading style.
How to Set Up
Choose Your Higher Timeframe (TIMEFRAME):
This determines the Pivot Points and retracement levels.
Example: Use “D” for daily pivots while trading on lower timeframes.
Select Entry Zone Patterns:
Define the pattern for detecting retracement levels:
xxx: Minor levels (steps of 10).
xx0: Intermediate levels (steps of 50).
x00: Major levels (steps of 100).
Set Entry Conditions for Long and Short Trades:
Activate or deactivate up/down conditions for xxx, xx0, or x00 patterns. Specify the count and range of crosses required for valid signals.
Configure Source Inputs (Source First and Source Second):
Assign external indicators such as RSI and RSI MA to refine entry conditions.
Tip: Adjust RSI settings in its separate indicator to suit your needs.
Select Your Order Type:
Choose between Market orders for instant execution or Limit orders for precision entries. Adjust offset zones for limit orders.
Set Up Stop-Loss Management:
Use dynamic stop-loss patterns with adjustable offsets:
HL: Stop-loss uses high/low levels of the zone.
Close: Stop-loss uses the closing price.
Customize Visualization Options:
Enable or disable xxx, xx0, x00, or 0 levels for cleaner charts. Adjust the display of retracement levels and stop-loss lines.
Apply and Monitor:
Attach the script to your chart, monitor entry/exit signals, and adjust parameters as needed.
How It Works
Calculates Pivot Points based on the chosen method ( Classic or Fibonacci ).
Detects price crossovers with retracement zones to identify potential entry points.
Dynamically adjusts stop-loss levels based on retracement zones and stop-loss patterns.
Supports both market and limit orders with customizable offsets for precise entries.
Allows integration of external sources like RSI for enhanced signal precision.
Important Notes
Use Source First and Source Second to input external indicators like RSI. You can configure RSI settings in its separate indicator to refine signals further.
Always test and optimize parameters before live trading.
Combine this script with your own analysis and proper risk management strategies.
This script is a tool to assist trading decisions but does not guarantee profits. Always trade responsibly.
Three Moving Averages Strategythis is three moving averages strategy is good for day time frame best for swing trading , probability vary for 60 to 80 to increase the probability add other indictors . you can rsi or macd.
Strategy Impulse Pivot EU - [AstroHub]The strategy is built on analyzing market impulses and their intensity. Its main goal is to help traders identify critical market moments when significant changes occur, signaling either a trend continuation or reversal.
Core Methodology
Impulse Movement
Measured by the difference between the current price and the previous bar’s price.
The indicator filters out minor fluctuations, focusing on meaningful changes.
Color Interpretation
Candles are color-coded based on the strength and direction of the impulse, providing a quick graphical understanding:
Green candles: Indicate moderate price growth, potentially signaling the end of the current trend.
Red candles: Reflect moderate price decline, possibly indicating a trend reversal.
Orange candles: Highlight strong price movements in either direction, signaling a potential trend continuation or reversal.
When a Signal Appears
Impulse Threshold : The price must change by at least a specified number of pips (e.g., 30 pips). This filters out weak movements.
Movement Intensity : Impulse is calculated and compared against threshold values to determine the signal’s strength.
Time Filter : Signals are generated 10 seconds before the hourly bar closes (at 59 minutes and 50 seconds). This ensures traders can prepare to act promptly.
Interpreting the Signals
Green Candle
Moderate price growth: A possible moment to take profit on long positions or open short positions.
Red Candle
Moderate price decline: A potential signal to open long positions or close short positions.
Orange Candle
Strong impulse movement:
If the price rises: A likely continuation of an upward trend.
If the price falls: A probable intensification of the downward trend.
I recommend using it on currency pairs with a 1-hour and 4-hour chart. EUR/USD, AUD/USD
Indicator Features
Impulse Analysis : The indicator highlights only significant price changes, ignoring market "noise."
Color Interpretation : Every movement is color-coded, simplifying the visualization of market dynamics.
Time Filter : Signals appear at critical moments — right before the hour closes. This enhances reliability and gives traders time to react.
Opening Levels : The indicator automatically marks opening levels for significant signals on the chart, helping traders visualize entry and exit zones.
Closed Code : The unique logic is protected, preventing unauthorized copying
Conclusion
This indicator is a powerful tool for analyzing impulse movements and their impact on the market. Its logic is straightforward, and its visualization makes signals easy to interpret. Suitable for both beginners and experienced traders, it offers clear entry and exit points with minimal false signal
Bitcoin Exponential Profit Strategy### Strategy Description:
The **Bitcoin Trading Strategy** is an **Exponential Moving Average (EMA) crossover strategy** designed to identify bullish trends for Bitcoin.
1. **Indicators**:
- **Fast EMA (default 9 periods)**: Represents the short-term trend.
- **Slow EMA (default 21 periods)**: Represents the longer-term trend.
2. **Entry Condition**:
- A **bullish crossover** occurs when the Fast EMA crosses above the Slow EMA.
- The strategy enters a **long position** with a user-defined order size (default 0.01 BTC).
3. **Exit Conditions**:
- **Take Profit**: Closes the position when the profit target is reached (default $100).
- **Stop Loss**: Closes the position when the price drops below the stop loss level (default $50).
- **Bearish Crossunder**: Closes the position when the Fast EMA crosses below the Slow EMA.
4. **Visual Signals**:
- **BUY signals**: Displayed when a bullish crossover occurs.
- **SELL signals**: Displayed when a bearish crossunder occurs.
This strategy is optimized for trend-following behavior, ensuring positions are aligned with upward-moving trends while managing risk through clear stop-loss and take-profit levels.
Refined SMA/EMA Crossover with Ichimoku and 200 SMA FilterYour **Refined SMA/EMA Crossover with Ichimoku and 200 SMA Filter** strategy is a multi-faceted technical trading strategy that combines several key technical indicators to refine entry and exit points for trades. Here's a breakdown of the components and how they work together:
### 1. **SMA/EMA Crossover**
- **Simple Moving Average (SMA) & Exponential Moving Average (EMA) Crossover**:
- The core idea behind the crossover strategy is to use the relationship between two moving averages to generate buy or sell signals.
- **SMA** (Simple Moving Average) gives an average of past prices over a set period.
- **EMA** (Exponential Moving Average) places more weight on recent prices, making it more responsive to price movements.
- A **bullish crossover** occurs when a shorter period moving average (such as a 50-period EMA) crosses above a longer period moving average (such as a 200-period SMA), signaling a potential buy.
- A **bearish crossover** occurs when a shorter period moving average crosses below the longer period moving average, signaling a potential sell.
### 2. **Ichimoku Cloud**
- The **Ichimoku Cloud** is a versatile indicator that provides insight into trend direction, support and resistance levels, and momentum.
- **Cloud (Kumo)**: The space between the Senkou Span A and Senkou Span B lines. It helps identify whether the market is in an uptrend, downtrend, or consolidation.
- **Tenkan-sen** (Conversion Line) and **Kijun-sen** (Base Line): These lines are used for additional confirmation of trend direction.
- **Chikou Span**: A lagging line that is used to confirm the trend.
- The general trading rules based on the Ichimoku Cloud are:
- **Bullish Signal**: When the price is above the cloud and the Tenkan-sen crosses above the Kijun-sen.
- **Bearish Signal**: When the price is below the cloud and the Tenkan-sen crosses below the Kijun-sen.
### 3. **200 SMA Filter**
- The **200 SMA Filter** serves as a long-term trend filter.
- When the price is **above the 200 SMA**, it signals a long-term bullish trend, and you only look for buying opportunities.
- When the price is **below the 200 SMA**, it signals a long-term bearish trend, and you only look for selling opportunities.
- This filter helps to avoid counter-trend trades, aligning your positions with the broader market trend.
### **How the Strategy Works Together**
- **Trade Setup (Long Position)**
1. The **200 SMA Filter** must confirm an **uptrend** by ensuring that the price is above the 200 SMA.
2. A **bullish crossover** (e.g., the 50 EMA crossing above the 200 SMA) occurs.
3. **Ichimoku Cloud** confirms a bullish trend, with the price above the cloud and the Tenkan-sen crossing above the Kijun-sen.
4. You enter a **long trade** with this confluence of signals.
- **Trade Setup (Short Position)**
1. The **200 SMA Filter** must confirm a **downtrend** by ensuring the price is below the 200 SMA.
2. A **bearish crossover** (e.g., the 50 EMA crossing below the 200 SMA) occurs.
3. **Ichimoku Cloud** confirms a bearish trend, with the price below the cloud and the Tenkan-sen crossing below the Kijun-sen.
4. You enter a **short trade** with this confluence of signals.
### **Exit Strategy**
- Exits can be determined based on any of the following:
- **SMA/EMA crossover reversal**: Exit when the shorter-term moving average crosses back below the longer-term moving average for a long position or crosses above for a short position.
- **Ichimoku Cloud reversal**: If the price breaks through the cloud or the Tenkan-sen and Kijun-sen lines cross in the opposite direction.
- **Profit target or stop loss**: Setting predefined profit targets or using a trailing stop to lock in profits as the trade moves in your favor.
Summary of the Strategy
This strategy is designed to identify strong trends and avoid false signals by combining:
SMA/EMA crossovers for immediate market direction signals.
Ichimoku Cloud for confirming the strength and trend direction.
A 200
SMA filter to ensure trades align with the long-term trend.
By using these multiple indicators together, the strategy aims to refine entry and exit points, minimize risk, and increase the likelihood of successful trades.
Tomas Ratio Strategy with Multi-Timeframe AnalysisHello,
I would like to present my new indicator I have compiled together inspired by Calmar Ratio which is a ratio that measures gains vs losers but with a little twist.
Basically the idea is that if HLC3 is above HLC3 (or previous one) it will count as a gain and it will calculate the percentage of winners in last 720 hourly bars and then apply 168 hour standard deviation to the weekly average daily gains.
The idea is that you're supposed to buy if the thick blue line goes up and not buy if it goes down (signalized by the signal line). I liked that idea a lot, but I wanted to add an option to fire open and close signals. I have also added a logic that it not open more trades in relation the purple line which shows confidence in buying.
As input I recommend only adjusting the amount of points required to fire a signal. Note that the lower amount you put, the more open trades it will allow (and vice versa)
Feel free to remove that limiter if you want to. It works without it as well, this script is meant for inexperienced eye.
I will also publish a indicator script with this limiter removed and alerts added for you to test this strategy if you so choose to.
Also, I have added that the trades will enter only if price is above 720 period EMA
Disclaimer
This strategy is for educational purposes only and should not be considered financial advice. Always backtest thoroughly and adjust parameters based on your trading style and market conditions.
Made in collaboration with ChatGPT.
Swing High/Low Pivots Strategy [LV]The Swing High/Low Pivots Strategy was developed as a counter-momentum trading tool.
The strategy is suitable for any market and the default values used in the input settings menu are set for Bitcoin (best on 15min). These values, expressed in minimum ticks (or pips if symbol is Forex) make this tool perfectly adaptable to every symbol and/or timeframe.
Check tooltips in the settings menu for more details about every user input.
STRTEGY ENTRY & EXIT MECHANISMS:
Trades Entry based on the detection of swing highs and lows for short and long entries respectively, validated by:
- Limit orders placed after each new pivot level confirmation
- Moving averages trend filter (if enabled)
- No active trade currently open
Trades Exit when the price reaches take-profit or stop-loss level as defined in the settings menu. A double entry/second take-profit level can be enabled for partial exits, with dynamic stop-loss adjustment for the remaining position.
Enhanced Trade Precision:
By limiting entries to confirmed swing high (HH, LH) or swing low (HL, LL) pivot points, the strategy ensures that trades occur at levels of significant price reversals. This precision reduces the likelihood of entering trades in the midst of a trend or during uncertain price action.
Risk Management Optimization:
The strategy incorporates clearly defined stop-loss (SL) and take-profit (TP) levels derived from the pivot points. This structured approach minimizes potential losses while locking in profits, which is critical for consistent performance in volatile markets.
Trend Filtering for Better Entry:
The use of a configurable moving average filter adds a layer of trend validation. This prevents entering trades against the dominant market trend, increasing the probability of success for each trade.
Avoidance of Noise:
The lookback period (length parameter) confirms pivots only after a set number of bars, effectively filtering out market noise and ensuring that entries are based on reliable, well-defined price movements.
Adaptability Across Markets:
The strategy is versatile and can be applied across different markets (Forex, stocks, crypto) due to its dynamic use of ticks and pips converters. It adapts seamlessly to varying price scales and asset types.
Dual Quantity Entries:
The original and optionnal double-entry mechanism allows traders to capture both short-term and extended profits by scaling out of positions. This adaptive approach caters to varying risk appetites and market conditions.
Clear Visualization:
The plotted pivot points, entry limits, SL, and TP levels provide visual clarity, making it easy for traders to track the strategy's behavior and make informed decisions.
Automated Execution with Alerts:
Integrated alerts for both entries and exits ensure timely actions without the need for constant market monitoring, enhancing efficiency. Configurable alert messages are suitable for API use.
Any feedback, comments, or suggestions for improvement are always welcome.
Hope you enjoy!
R-based Strategy Template [Daveatt]Have you ever wondered how to properly track your trading performance based on risk rather than just profits?
This template solves that problem by implementing R-multiple tracking directly in TradingView's strategy tester.
This script is a tool that you must update with your own trading entry logic.
Quick notes
Before we dive in, I want to be clear: this is a template focused on R-multiple calculation and visualization.
I'm using a basic RSI strategy with dummy values just to demonstrate how the R tracking works. The actual trading signals aren't important here - you should replace them with your own strategy logic.
R multiple logic
Let's talk about what R-multiple means in practice.
Think of R as your initial risk per trade.
For instance, if you have a $10,000 account and you're risking 1% per trade, your 1R would be $100.
A trade that makes twice your risk would be +2R ($200), while hitting your stop loss would be -1R (-$100).
This way of measuring makes it much easier to evaluate your strategy's performance regardless of account size.
Whenever the SL is hit, we lose -1R
Proof showing the strategy tester whenever the SL is hit: i.imgur.com
The magic happens in how we calculate position sizes.
The script automatically determines the right position size to risk exactly your specified percentage on each trade.
This is done through a simple but powerful calculation:
risk_amount = (strategy.equity * (risk_per_trade_percent / 100))
sl_distance = math.abs(entry_price - sl_price)
position_size = risk_amount / (sl_distance * syminfo.pointvalue)
Limitations with lower timeframe gaps
This ensures that if your stop loss gets hit, you'll lose exactly the amount you intended to risk. No more, no less.
Well, could be more or less actually ... let's assume you're trading futures on a 15-minute chart but in the 1-minute chart there is a gap ... then your 15 minute SL won't get filled and you'll likely to not lose exactly -1R
This is annoying but it can't be fixed - and that's how trading works anyway.
Features
The template gives you flexibility in how you set your stop losses. You can use fixed points, ATR-based stops, percentage-based stops, or even tick-based stops.
Regardless of which method you choose, the position sizing will automatically adjust to maintain your desired risk per trade.
To help you track performance, I've added a comprehensive statistics table in the top right corner of your chart.
It shows you everything you need to know about your strategy's performance in terms of R-multiples: how many R you've won or lost, your win rate, average R per trade, and even your longest winning and losing streaks.
Happy trading!
And remember, measuring your performance in R-multiples is one of the most classical ways to evaluate and improve your trading strategies.
Daveatt
DCA Alpha 1.0 Trading Tool for Dollar-Cost Averaging
Description:
DCA Alpha 1.0 is a precision-engineered trading tool designed to assist traders and investors in accumulating assets during market downturns. Using proprietary algorithms that combine momentum decay, extreme price deviation metrics, trend dynamics, divergence analysis, and mean regression, it identifies potential bottom extreme zones in various asset classes such as indices, stocks, crypto, and commodities.
This indicator highlights market conditions where assets are oversold, undervalued, or experiencing capitulation—providing disciplined, unleveraged dollar-cost averaging (DCA) opportunities. Ideal for long-term growth strategies, DCA Alpha 1.0 helps cut through market noise, pinpointing moments of peak fear and maximum reward potential.
Whether navigating volatile crypto markets, timing corrections in indices, or accumulating commodities, DCA Alpha 1.0 serves as a vital tool for mastering the art of buying low and building your assets up strategically.
Instructions:
Getting Started:
Add the Indicator:
Install DCA Alpha 1.0 on your TradingView chart.
Select your preferred asset class: stocks, indices, crypto, or commodities.
Choose an appropriate timeframe (e.g., daily or weekly for long-term DCA strategies).
Customize Inputs: Adjust the following settings to align with your strategy:
Percentage of Equity to Trade: Define the portion of your portfolio to allocate per signal (default: 1% equity).
Profit Target Percentages: Set thresholds for locking in gains (default: 50% on lower timeframes, 500% on higher timeframes).
Zones and Signals:
Extreme Negative Zones:
What It Represents:
These zones highlight conditions where prices are deeply oversold, indicating extreme bearish sentiment. The market is likely nearing a bottom, offering high-probability buying opportunities.
Entry Signals:
When the price enters these extreme negative zones, visual markers (e.g., green triangles or other indicators) will signal a potential buying opportunity. These moments are indicative of market exhaustion, signaling that a reversal could be imminent.
Momentum Decay & Divergence:
Momentum decay occurs when price movement slows over time. In extreme negative zones, if prices continue to fall but at a diminishing rate (e.g., decreased volume or a fading oscillator), it suggests weakening bearish momentum. This, coupled with bullish divergence (oscillator forming higher lows while price makes lower lows), signifies a reversal, making it an ideal point to consider dollar-cost averaging into the asset.
Neutral Zones:
What It Represents:
The neutral zone is a state of market equilibrium, where prices are neither overbought nor oversold. The market is in a balanced state, with no strong trend emerging.
Mean Regression:
In a neutral zone, the market is reverting to its mean or average price after overreacting in either direction. A price transition from extreme zones (overbought/oversold) to the neutral zone suggests a reversion to the market's long-term average, making this a period of reduced volatility and uncertainty.
Entering or Exiting Neutral Zones:
Traders should avoid entering or exiting positions during neutral zone conditions unless transitioning from an extreme zone (negative or positive). Transitioning from an extreme negative zone to neutral may suggest an opportunity to accumulate assets gradually, while a shift from neutral to an extreme negative zone may indicate a deeper correction and warrant caution.
Momentum Decay & Divergence (Exiting Neutral Zone):
If prices are rising but the oscillator shows lower highs (bearish divergence), and momentum is fading, this could signal a pullback. A transition out of the neutral zone in this context may prompt traders to hold off on new positions or consider profit-taking.
Extreme Positive Zones:
What It Represents:
Markets can also become overbought or overvalued. When price enters extreme positive zones, the asset may be overvalued, suggesting potential selling or a waiting period.
Exit Signals:
Red triangle indicators signal potential exit points when prices reach overbought conditions, signaling a time to lock in profits and reduce exposure.
Momentum Decay & Divergence (Exiting Positive Zone):
When prices are making new highs but momentum is weakening (momentum decay) and the oscillator is showing lower highs (bearish divergence), this could indicate a faltering rally. Such conditions represent an ideal time to reduce exposure or exit positions.
Key Inputs for Customization:
Percentage of Equity to Trade:
This setting allows you to allocate a portion of your total portfolio per buy signal. By default, 1% of equity is used per signal, but this can be adjusted based on your risk tolerance and strategy.
Profit Target Percentages:
These thresholds help lock in gains once the price moves a set percentage in your favor.
Lower Timeframes: Default profit target of 50%.
Higher Timeframes: Default profit target of 500%.
These settings can be customized for specific risk/reward preferences.
Warning!!! : Aggressive Mode
Aggressive Mode is an advanced feature designed for traders who want to increase the frequency of signals during periods of market volatility. This mode will trigger more frequent entries, even into slightly less extreme zones, capturing short-term reversals.
What Aggressive Mode Does:
It amplifies signals by allowing the tool to identify more frequent price reversals, including brief market corrections, increasing trade frequency. While this can offer more trading opportunities, it also exposes you to higher risk.
Warning:
Aggressive Mode should be used only by experienced traders familiar with short-term volatility. The increased frequency of signals could lead to higher risk exposure. Ensure robust risk management practices, such as stop-loss orders and profit-taking strategies, are in place before activating this mode.
Default Setting:
Aggressive Mode is disabled by default. It can be activated at your discretion based on your experience level and risk appetite.
Best Practices:
Focus on High-Quality Assets: Prioritize assets with strong recovery potential (e.g., major indices, blue-chip cryptocurrencies).
Use Longer Timeframes: Minimize market noise and optimize your DCA strategy by focusing on higher timeframes (e.g., daily or weekly charts).
Review Trading Inputs: Regularly adjust your inputs to ensure they align with your financial goals and risk tolerance.
Implement Risk Management: Use stop-loss orders and profit targets to manage risk, especially when using Aggressive Mode.
Disclaimer:
DCA Alpha 1.0 is designed specifically for unleveraged, long-term dollar-cost averaging strategies. It is not intended for day trading or leveraged positions. The tool excels at identifying market dips but cannot guarantee success. Users are fully responsible for their own risk management, including the use of stop-losses, profit targets, and position sizing.
Aggressive Mode increases trade frequency and may lead to higher exposure and potential losses. Only experienced traders should consider using this mode. Always understand the risks involved before incorporating this tool into your trading strategy.
