DMI Delta by 0xjcfOverview
This indicator integrates the Directional Movement Index (DMI), Average Directional Index (ADX), and volume analysis into an Oscillator designed to help traders identify divergence-based trading signals. Unlike typical volume or momentum indicators, this combination provides insight into directional momentum and volume intensity, allowing traders to make well-informed decisions based on multiple facets of market behavior.
Purpose and How Components Work Together
By combining DMI and ADX with volume analysis, this indicator helps traders detect when momentum diverges from price action—a common precursor to potential reversals or significant moves. The ADX filter enhances this by distinguishing trending from range-bound conditions, while volume analysis highlights moments of extreme sentiment, such as solid buying or selling. Together, these elements provide traders with a comprehensive view of market strength, directional bias, and volume surges, which help filter out weaker signals.
Key Features
DMI Delta and Oscillator: The DMI indicator measures directional movement by comparing DI+ and DI- values. This difference (DMI Delta) is calculated and displayed as a histogram, visualizing changes in directional bias. When combined with ADX filtering, this histogram helps traders gauge the strength of momentum and spot directional shifts early. For instance, a rising histogram in a bearish price trend might signal a potential bullish reversal.
Volume Analysis with Extremes: Volume is monitored to reveal when market participation is unusually high, using a customizable multiplier to highlight significant volume spikes. These extreme levels are color-coded directly on the histogram, providing visual cues on whether buying or selling interest is particularly strong. Volume analysis adds depth to the directional insights from DMI, allowing traders to differentiate between regular and powerful moves.
ADX Trending Filter: The ADX component filters trends by measuring the overall strength of a price move, with a default threshold of 25. When ADX is above this level, it suggests that the market is trending strongly, making the DMI Delta readings more reliable. Below this threshold, the market is likely range-bound, cautioning traders that signals might not have as much follow-through.
Using the Indicator in Divergence Strategies
This indicator excels in divergence strategies by highlighting moments when price action diverges from directional momentum. Here’s how it aids in decision-making:
Bullish Divergence: If the price is falling to new lows while the DMI Delta histogram rises, it can indicate weakening bearish momentum and signal a potential price reversal to the upside.
Bearish Divergence: Conversely, if prices are climbing but the DMI Delta histogram falls, it may point to waning bullish momentum, suggesting a bearish reversal.
Visual Cues and Customization
The color-coded output enhances usability:
Bright Green/Red: Extreme volume with strong bullish or bearish signals, often at points of high potential for trend continuation or reversal.
Green/Red Shades: These shades reflect trending conditions (bullish or bearish) based on ADX, factoring in volume. Green signals a bullish trend, and red is a bearish trend.
Blue/Orange Shades: Indicates non-trending or weaker conditions, suggesting a more cautious approach in range-bound markets.
Customizable for Diverse Trading Styles
This indicator allows users to adjust settings like the ADX threshold and volume multiplier to optimize performance for various timeframes and strategies. Whether a trader prefers swing trading or intraday scalping, these parameters enable fine-tuning to enhance signal reliability across different market contexts.
Practical Usage Tips
Entry and Exit Signals: Use this indicator in conjunction with price action. Divergences between the price and DMI Delta histogram can reinforce entry or exit decisions.
Adjust Thresholds: Based on backtesting, customize the ADX Trending Threshold and Volume Multiplier to ensure optimal performance on different timeframes or trading styles.
In summary, this indicator is tailored for traders seeking a multi-dimensional approach to market analysis. It blends momentum, trend strength, and volume insights to support divergence-based strategies, helping traders confidently make informed decisions. Remember to validate signals through backtesting and use it alongside price action for the best results.
Oscillatori
Fair Value Gap Oscillator | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Fair Value Gap Oscillator (FVG Oscillator) indicator! This unique indicator identifies and tracks Fair Value Gaps (FVGs) in price action, presenting them in an oscillator format to reveal market momentum based on FVG strength. It highlights bullish and bearish FVGs while enabling traders to adjust detection sensitivity and apply volume and ATR-based filters for more precise setups. For more information about the process, check the "📌 HOW DOES IT WORK" section.
Features of the new FVG Oscillator:
Fully Customizable FVG Detection
An Oscillator Approach To FVGs
Divergence Markers For Potential Reversals
Alerts For Divergence Labels
Customizable Styling
📌 HOW DOES IT WORK?
Fair Value Gaps are price gaps within bars that indicate inefficiencies, often filled as the market retraces. The FVG Oscillator scans historical bars to identify these gaps, then filters them based on ATR or volume. Each FVG is marked as bullish or bearish according to the trend direction that preceded its formation.
An oscillator is calculated using recent FVGs with this formula :
1. The Oscillator starts as 0.
2. When a new FVG Appears, it contributes (FVG Width / ATR) to the oscillator of the corresponding type.
3. Each confirmed bar, the oscillator is recalculated as OSC = OSC * (1 - Decay Coefficient)
The oscillator aggregates and decays past FVGs, allowing recent FVG activity to dominate the signal. This approach emphasizes current market momentum, with oscillations moving bullish or bearish based on FVG intensity. Divergences are marked where FVG oscillations suggest potential reversals. Bullish Divergence conditions are as follows :
1. The current candlestick low must be the lowest of last 25 bars.
2. Net Oscillator (Shown in gray line by default) must be > 0.
3. The current Bullish FVG Oscillator value should be no more than 0.1 below the highest value from the last 25 bars.
Traders can use divergence signals to get an idea of potential reversals, and use the Net FVG Oscillator as a trend following marker.
🚩 UNIQUENESS
The Fair Value Gap Oscillator stands out by converting FVG activity into an oscillator format, providing a momentum-based visualization of FVGs that reveals market sentiment dynamically. Unlike traditional indicators that statically mark FVG zones, the oscillator decays older FVGs over time, showing only the most recent, relevant activity. This approach allows for real-time insight into market conditions and potential reversals based on oscillating FVG strength, making it both intuitive and powerful for momentum trading.
Another unique feature is the combination of customizable ATR and volume filters, letting traders adapt the indicator to match their strategy and market type. You can also set-up alerts for bullish & bearish divergences.
⚙️ SETTINGS
1. General Configuration
Decay Coefficient -> The decay coefficient for oscillators. Increasing this setting will result in oscillators giving the weight to recent FVGs, while decreasing it will distribute the weight equally to the past and recent FVGs.
2. Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Style
Divergence Labels On -> You can switch divergence labels to show up on the chart or the oscillator plot.
Options Series - Technical Analysis Chart➤ Simple Technical Chart Only:
➤ With MA-20 Overlay and Volatility background bars:
➤ With RSI Candles:
⭐ Overview and How It Works:
This script provides a multi-asset analysis tool to assess various market conditions across four symbols simultaneously. It combines several indicators such as daily price change, Moving Averages (MA), Bollinger Bands (BB), Parabolic SAR, RSI, and VWAP to generate buy/sell signals and trend indicators. Its strength lies in the layered use of indicators to enhance signal reliability, making it valuable for traders needing cross-validation in decision-making.
⭐ Key Features and Functionality:
The script evaluates each symbol's price against various indicators and conditions:
Daily Price Conditions: It checks if each symbol’s close price is above or below the previous day’s open, close, and intra-day ranges, forming a foundational bullish/bearish condition.
Range Breakout 1st 5min Candle (ORB): Opening Range Breakout levels are calculated and compared with current close prices, detecting breakout/breakdown conditions.
ORB Body: This basically calculates the previous day Daily candle body size, if todays Daily candle body size is greater than previous day, then we can say that we are having good momentum else its likely to be in-sidebar trading.
Moving Averages (MA): It leverages EMA-20, 2-day, and 3-day exponential moving averages to gauge short to medium-term trends.
RSI and VWAP: Relative Strength Index (RSI) determines overbought or oversold conditions, while VWAP compares prices to volume-weighted levels.
Bollinger Bands and Trend Analysis: Detects volatility and potential breakout conditions.
Concept of ORB Body:
Current_PrevDay_Body = (math.max(var_Current_PrevD_Open, var_Current_PrevD_Close) - math.min(var_Current_PrevD_Open, var_Current_PrevD_Close))
Current_Upper_ORB = var_Current_D_Open + Current_PrevDay_Body
Current_Lower_ORB = var_Current_D_Open - Current_PrevDay_Body
Current_TodayDay_Body = math.max(var_Current_D_Open, var_Current_Close) - math.min(var_Current_D_Open, var_Current_Close)
Current_ORBBody = Current_TodayDay_Body > Current_PrevDay_Body
Current_Upper_ORB_bull = (var_Current_Close > Current_Upper_ORB)
Current_Lower_ORB_bear = (var_Current_Close < Current_Lower_ORB)
🎨 Visualizations and User Experience:
The script can dynamically display colored backgrounds indicating trends when conditions are met. For example, the bgcolor function changes the background when certain trend-based criteria are satisfied, offering visual cues to users. Additionally, the checkbox input toggles trend bar visualizations, enhancing user experience by providing a quick visual reference without needing to interpret individual data points manually.
RSI-Based Candle Coloring:
➤ The script customizes candle colors based on RSI thresholds, specifically defining upper (60) and lower (40) RSI levels. When the RSI value exceeds the upper threshold, candles are colored as bullish (green), and if it falls below the lower threshold, candles are colored as bearish (red). Neutral RSI values result in a default color (gray).
➤ This setup offers a visually intuitive way to identify potential trend directions based on RSI levels, making it ideal for traders looking to gauge momentum visually.
⭐ Settings and Customization:
With multiple user-configurable inputs, the script allows for tailored analysis. Customizable parameters, such as enabling/disabling trend bars and setting various look-back periods for indicators like Bollinger Bands and Moving Averages, make it adaptable to various trading styles and preferences. It also allows users to modify visual elements like colors and styles, improving flexibility.
⭐ Uniqueness of the Concept:
The unique aspect of this script is its multi-symbol approach combined with complex conditions. By comparing not only one but four symbols simultaneously, it provides a broader market view and allows traders to correlate signals across different assets, offering a potential edge for diversified or comparative strategies. Additionally, the incorporation of ORB and multi-timeframe MAs gives it a robustness often lacking in simpler single-symbol scripts.
🚀 Conclusion:
This script is a powerful multi-indicator tool suited for traders looking for a comparative, multi-symbol analysis. With features like ORB, Bollinger Band-based trend detection, and MA cross-verification, it can assist traders in identifying and validating trend signals across assets. The user-friendly visualizations and customizable settings further enhance its usability, making it versatile for various trading strategies and preferences.
Reversed Choppiness Index with Donchian Channels and SMAIn the chaotic world of trading, where every tick can lead to joy or despair, traders yearn for clarity amid the noise. They crave a mechanism that not only reveals the underlying market trends but also navigates the turbulent waters of volatility with grace. Enter the Reversed Choppiness Index with Donchian Channels and SMA Smoothing—a sophisticated tool crafted for those who refuse to be swayed by the whims of market noise.
This innovative script harnesses the power of the Choppiness Index, flipping it on its head to unveil the true direction of price movement. Choppiness, in its traditional form, indicates when the market is stuck in a sideways range, characterized by erratic price movements that can leave traders bewildered. High choppiness often signals confusion in the market, where prices oscillate without a clear trend, leading to potential losses. Conversely, low choppiness suggests a trending market, whether bullish or bearish, where trades can yield consistent profits. By reversing the Choppiness Index, this tool highlights lower choppiness levels as opportunities for selling when the market shows stability and momentum—perfect for traders looking to enter or exit positions with confidence.
The Donchian Channels serve as reliable markers, defining the boundaries of price action and helping to paint a clearer picture of market dynamics. Traders should look for breakouts from these channels, which may indicate a significant shift in momentum. When the Reversed Choppiness Index trends lower while price breaks above the upper Donchian Band, it may signal a strong buying opportunity, while a rise in choppiness alongside price dipping below the lower band can indicate a potential selling point.
But that's not all—this tool features a dual-layer of smoothing through two distinct Simple Moving Averages (SMAs). The first SMA gently caresses the Reversed Choppiness Index, softening its edges to reveal the underlying trends. The second SMA adds an extra layer of finesse, ensuring traders can spot significant changes with less noise interference.
In a landscape filled with fleeting opportunities and unpredictable swings, this script stands as a beacon of stability. It allows traders to focus on what truly matters—seizing profitable moments without getting caught in the crossfire of volatility. By understanding the dynamics of choppiness through this reversed lens, traders can more effectively navigate their strategies, capitalizing on clearer signals while avoiding the pitfalls of market noise. Embrace this tool and transform the way you trade; the market's whispers will no longer drown out your strategies, paving the way for informed decisions and greater success.
Z-Score RSI StrategyOverview
The Z-Score RSI Indicator is an experimental take on momentum analysis. By applying the Relative Strength Index (RSI) to a Z-score of price data, it measures how far prices deviate from their mean, scaled by standard deviation. This isn’t your traditional use of RSI, which is typically based on price data alone. Nevertheless, this unconventional approach can yield unique insights into market trends and potential reversals.
Theory and Interpretation
The RSI calculates the balance between average gains and losses over a set period, outputting values from 0 to 100. Typically, people look at the overbought or oversold levels to identify momentum extremes that might be likely to lead to a reversal. However, I’ve often found that RSI can be effective for trend-following when observing the crossover of its moving average with the midline or the crossover of the RSI with its own moving average. These crossovers can provide useful trend signals in various market conditions.
By combining RSI with a Z-score of price, this indicator estimates the relative strength of the price’s distance from its mean. Positive Z-score trends may signal a potential for higher-than-average prices in the near future (scaled by the standard deviation), while negative trends suggest the opposite. Essentially, when the Z-Score RSI indicates a trend, it reflects that the Z-score (the distance between the average and current price) is likely to continue moving in the trend’s direction. Generally, this signals a potential price movement, though it’s important to note that this could also occur if there’s a shift in the mean or standard deviation, rather than a meaningful change in price itself.
While the Z-Score RSI could be an insightful addition to a comprehensive trading system, it should be interpreted carefully. Mean shifts may validate the indicator’s predictions without necessarily indicating any notable price change, meaning it’s best used in tandem with other indicators or strategies.
Recommendations
Before putting this indicator to use, conduct thorough backtesting and avoid overfitting. The added parameters allow fine-tuning to fit various assets, but be careful not to optimize purely for the highest historical returns. Doing so may create an overly tailored strategy that performs well in backtests but fails in live markets. Keep it balanced and look for robust performance across multiple scenarios, as overfitting is likely to lead to disappointing real-world results.
XAUUSD 10-Minute StrategyThis XAUUSD 10-Minute Strategy is designed for trading Gold vs. USD on a 10-minute timeframe. By combining multiple technical indicators (MACD, RSI, Bollinger Bands, and ATR), the strategy effectively captures both trend-following and reversal opportunities, with adaptive risk management for varying market volatility. This approach balances high-probability entries with robust volatility management, making it suitable for traders seeking to optimise entries during significant price movements and reversals.
Key Components and Logic:
MACD (12, 26, 9):
Generates buy signals on MACD Line crossovers above the Signal Line and sell signals on crossovers below the Signal Line, helping to capture momentum shifts.
RSI (14):
Utilizes oversold (below 35) and overbought (above 65) levels as a secondary filter to validate entries and avoid overextended price zones.
Bollinger Bands (20, 2):
Uses upper and lower Bollinger Bands to identify potential overbought and oversold conditions, aiming to enter long trades near the lower band and short trades near the upper band.
ATR-Based Stop Loss and Take Profit:
Stop Loss and Take Profit levels are dynamically set as multiples of ATR (3x for stop loss, 5x for take profit), ensuring flexibility with market volatility to optimise exit points.
Entry & Exit Conditions:
Buy Entry: T riggered when any of the following conditions are met:
MACD Line crosses above the Signal Line
RSI is oversold
Price drops below the lower Bollinger Band
Sell Entry: Triggered when any of the following conditions are met:
MACD Line crosses below the Signal Line
RSI is overbought
Price moves above the upper Bollinger Band
Exit Strategy: Trades are closed based on opposing entry signals, with adaptive spread adjustments for realistic exit points.
Backtesting Configuration & Results:
Backtesting Period: July 21, 2024, to October 30, 2024
Symbol Info: XAUUSD, 10-minute timeframe, OANDA data source
Backtesting Capital: Initial capital of $700, with each trade set to 10 contracts (equivalent to approximately 0.1 lots based on the broker’s contract size for gold).
Users should confirm their broker's contract size for gold, as this may differ. This script uses 10 contracts for backtesting purposes, aligned with 0.1 lots on brokers offering a 100-contract specification.
Key Backtesting Performance Metrics:
Net Profit: $4,733.90 USD (676.27% increase)
Total Closed Trades: 526
Win Rate: 53.99%
Profit Factor: 1.44 (1.96 for Long trades, 1.14 for Short trades)
Max Drawdown: $819.75 USD (56.33% of equity)
Sharpe Ratio: 1.726
Average Trade: $9.00 USD (0.04% of equity per trade)
This backtest reflects realistic conditions, with a spread adjustment of 38 points and no slippage or commission applied. The settings aim to simulate typical retail trading conditions. However, please adjust the initial capital, contract size, and other settings based on your account specifics for best results.
Usage:
This strategy is tuned specifically for XAUUSD on a 10-minute timeframe, ideal for both trend-following and reversal trades. The ATR-based stop loss and take profit levels adapt dynamically to market volatility, optimising entries and exits in varied conditions. To backtest this script accurately, ensure your broker’s contract specifications for gold align with the parameters used in this strategy.
Mean Reversion Entry Signal
Mean Reversion Entry Signal Indicator
The Mean Reversion Entry Signal indicator is a trading tool designed for traders looking to capitalize on market corrections. This script leverages mean reversion principles, utilizing price levels and the Relative Strength Index (RSI) to generate potential entry signals for both long and short positions.
Key Features:
1. **Dynamic Price Levels**:
- The indicator calculates critical price levels over a user-defined lookback period, including:
- High (H)**: The highest price point over the lookback period.
- Low (L)**: The lowest price point over the lookback period.
- Midpoint (M)**: The average of the high and low.
- Midpoint High (Mh)** and **Midpoint Low (Ml)**: Additional reference levels derived from M for more nuanced trading signals.
2. User-Configurable Inputs:
- Lookback Period: Traders can specify the number of hours to look back for the calculations, allowing for tailored analysis that fits various trading strategies. By default the lookback is set for 24 hours, as i consider it the most adequate for day trading.
- Aggression Level: This input lets users choose their trading strategy's intensity, affecting the sensitivity of entry signals based on the percentage difference from the midpoint.
3. Entry Signal Generation:
The script evaluates market conditions to signal potential trades:
- Long Entries: Indicated when the price is below the Ml level and the price demonstrates a significant distance from the midpoint (M), coupled with RSI being near the oversold territory.
- Short Entries: Triggered when the price exceeds the Mh level, also indicating a significant distance from M, while the RSI indicates near overbought conditions.
4. Visual Indicators:
Clear visual signals are plotted directly on the chart:
- Long Signals are represented as upward triangles in green.
- Short Signals appear as downward triangles in red.
- Important price levels (M, H, L, Mh, and Ml) are displayed to provide traders with immediate context for potential trades.
5. No Entry Zone:
The area between Mh and Ml is shaded to indicate a "No Entry Zone," helping traders identify regions where conditions may not be favorable for taking new positions.
This can also be used as potencial profit taking area.
Conclusion
1. This indicator was built mainly for day trading, using timeframes between 1 minute and 1 hour. If you want to use it in 1D time frame, for instance, you should adjust the lookback period to 120 hours or so.
2. To use this as a strategy, you should not be afraid to "add to your losers" as the trade goes against you and the signals continue to appear.
Enjoy
Trendfilter ChartIntroduction:
The "Trend Filter Chart" indicator is a comprehensive analytical tool designed to identify market trends through a combination of various technical analysis methods. This indicator utilizes multiple moving averages, power bars, and swing volatility to determine market direction and potential entry points. By combining these elements, the indicator aids in making informed trading decisions and interpreting market movements with greater precision.
The Trend Filter Chart uses several moving averages, including the 18-period and 52-period SMAs, as well as the 8-period SMA for lows and the 10-period SMA for highs. These moving averages are crucial for identifying trends and assisting in the definition of entry points.
A central feature of the indicator is the identification of power bars and ultra bars. These color-coded bars help visualize strong market movements characterized by significant changes in the weighted price range (high-low spread) and percentage price changes. Power bars and ultra bars indicate notable market activities that suggest the involvement of large market participants.
The variable Average Volatility and GSV middle line combines various volatility measures to create a comprehensive moving average. It is formed from the average of the short-term highs and lows, along with the average volatility calculated from the highest and lowest volatility values over the past days.
This calculation allows for capturing and visualizing the current trend in market volatility. This method provides an average trend line used to assess market direction.
Another important feature is the 5-over/Below-Channel signals, which indicate when five consecutive bars trade above or below the moving averages. These signals suggest potential trend continuations or reversals, providing valuable insights for trading decisions.
The integrated color signals support traders in identifying entry opportunities and evaluating market strength.
This indicator also identifies 10 different price patterns, including MA, correction patterns, and Inside/Outside Bar patterns and some others. These patterns are filtered through trend filters to provide potential entry setups. The underlying patterns are based on concepts by Larry Williams.
Depending on the pattern, they work differently in each market. Entry points, stop loss, and profit targets should be backtested in each market, as every market has its own characteristics.
For more information on how to use the patterns, please send me a message.
Disclaimer
The use of this indicator and the generated signals is at your own risk. The author assumes no responsibility for trading decisions made based on these signals. Please be aware that trading financial instruments involves risks.
COT Trendfilter + SignalsCOT Trendfilter + Signals Indicator
Data Processing and Usage: The COT indicator processes Commitments of Traders (COT) data provided by the CFTC. Users can select from various participant groups, including Commercials, Large Speculators, and Small Speculators. However, it is important to note that the signal logic of the indicator is exclusively applicable to the net positions of Commercials. This is because Commercials tend to trade contrarily, meaning their trading decisions often run against the prevailing market trend.
Functionality of the Indicators
1. Cycle COT
The cCOT is an enhanced version of the classic RSI. It incorporates additional smoothing based on market vibrations, along with adaptive upper and lower bands based on cyclical memory. The cCOT uses the current dominant cycle length as input and highlights trading signals when the signal line crosses above or below the adaptive bands. Compared to the standard RSI, the cCOT responds more quickly to market movements.
For detailed information on the cCOT, please refer to Chapter 4 "Fine tuning technical indicators" in the book "Decoding the Hidden Market Rhythm, Part 1" by Lars von Thienen.
2. Adaptive Ultra-Smooth Momentum Indicator
The Adaptive Ultra-Smooth Momentum Indicator (CSI) provides an optimized momentum oscillator based on the current dominant cycle. It addresses three common issues with standard indicators: excessive false signals, signal delay, and the need for length adjustments. The CSI offers adaptive smoothing, zero delay, and accurate detection of turning points.
For further information about the CSI, please refer to Chapter 10 "Cycle Swing Indicator: Trading the swing of the dominant cycle" in the book "Decoding the Hidden Market Rhythm, Part 1" by Lars von Thienen.
Signals and Validation
The indicator generates various trading signals:
cCOT:
A buy signal is indicated by an airplane emoji (🛫), while a sell signal is marked by another airplane emoji (🛬).
COT Momentum:
A buy signal is shown by the symbol “∿” in green, while a sell signal is represented by the same symbol in red.
Standard COT Index (Willco):
A buy signal is depicted by a “B” (in green), while a sell signal is shown by an “S” (in red).
Additionally, the validity of the signals is checked. If a previous signal becomes invalid in the following week, it is marked with a gray “x,” indicating that these signals may not be reliable. Users can also switch between net positions, long, and short to analyze the most relevant data for them.
Background Color
The color in the channel can indicate the strength of the Commercials' long-term trend. A channel background color signals an active long-, short-term trend, while no color suggests that there is no clear long-term trend present.
Strange behavior
When only a sharp spike is displayed and the rest is flat, the length settings of the Cycle Length Index should be increased. This can occur when the length is too short, resulting in an unusual spike to properly generate the channel.
Disclaimer
The use of this indicator and the generated signals is at your own risk. The author assumes no responsibility for trading decisions made based on these signals. Please be aware that trading financial instruments involves risks.
Mean Trend OscillatorMean Trend Oscillator
The Mean Trend Oscillator offers an original approach to trend analysis by integrating multiple technical indicators, using statistic to get a probable signal, and dynamically adapting to market volatility.
This tool aggregates signals from four popular indicators—Relative Strength Index (RSI), Simple Moving Average (SMA), Exponential Moving Average (EMA), and Relative Moving Average (RMA)—and adjusts thresholds using the Average True Range (ATR). By using this, we can use Statistics to aggregate or take the average of each indicators signal. Mathematically, Taking an average of these indicators gives us a better probability on entering a trending state.
By consolidating these distinct perspectives, the Mean Trend Oscillator provides a comprehensive view of market direction, helping traders make informed decisions based on a broad, data-driven trend assessment. Traders can use this indicator to enter long spot or leveraged positions. The Mean Trend Oscillator is intended to be use in long term trending markets. Scalping MUST NOT be used with this indicator. (This indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
The current price of a beginning trend series may tell us something about the next move. Thus, the Mean Trend Oscillator allows us to spot a high probability trending market and potentially exploit this information enter long or shorts strategy. (again, this indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
Concept and Calculation and Inputs
The Mean Trend Oscillator calculates a “net trend” score as follows:
RSI evaluates market momentum, identifying overbought and oversold conditions, essential for confirming trend direction.
SMA, EMA, and RMA introduce varied smoothing methods to capture short- to medium-term trends, balancing quick price changes with smoothed averages.
ATR-Enhanced Thresholds: ATR is used as a dynamic multiplier, adjusting each indicator’s thresholds to current volatility levels, which helps reduce noise in low-volatility conditions and emphasizes significant signals when volatility spikes.
Length could be used to adjust how quickly each indicator can more or how slower each indicator can be.
Time Coherency for Inputs: Each indicator must be calculated where each signal is relatively around the same area.
For example:
Simply:
SMA, RMA, EMA, and RSI enters long around each intended trend period. Doesn't have to be perfect, but the indicators all enter long around there.
Each indicator contributes a score (+1 for bullish and -1 for bearish), and these scores are averaged to generate the final trend score:
A positive score, shown as a green line, suggests bullish conditions.
A negative score, indicated by a red line, signifies bearish conditions.
Thus, giving us a signal to long or short.
How to Use the Mean Trend Oscillator
This indicator’s output is straightforward and can fit into various trading strategies:
Bullish Signal: A green line shows that the trend is bullish, based on a positive average score across the indicators, signaling a consideration of longing an asset.
Bearish Signal: A red line indicates bearish conditions, with an overall negative trend score, signaling a consideration to shorting an asset.
By aggregating these indicators, the Mean Trend Oscillator helps traders identify strong trends while filtering out minor fluctuations, making it a versatile tool for both short- and long-term analysis. This multi-layered, adaptive approach to trend detection sets it apart from traditional single-indicator trend tools.
Weekly RSI Buy/Sell SignalsWeekly RSI Buy/Sell Signal Indicator
This indicator is designed to help traders identify high-probability buy and sell opportunities on the weekly chart by using the Relative Strength Index (RSI). By utilizing weekly RSI values, this indicator ensures signals align with broader market trends, providing a clearer view of potential price reversals and continuation.
How It Works:
Weekly RSI Calculation: This script calculates the RSI using a 14-period setting, focusing on the weekly timeframe regardless of the user’s current chart view. The weekly RSI is derived using request.security, allowing for consistent signals even on intraday charts.
Signal Conditions:
Buy Signal: A buy signal appears when the RSI crosses above the oversold threshold of 30, suggesting that price may be gaining momentum after a potential bottom.
Sell Signal: A sell signal triggers when the RSI crosses below the overbought threshold of 70, indicating a possible momentum shift downwards.
Visual Cues:
Buy/Sell Markers: Clear green "BUY" and red "SELL" markers are displayed on the chart when buy or sell conditions are met, making it easy to identify entry and exit points.
RSI Line and Thresholds: The weekly RSI value is plotted in real time with color-coded horizontal lines at 30 (oversold) and 70 (overbought), providing a visual reference for key levels.
This indicator is ideal for traders looking for reliable, trend-based signals on higher timeframes and can be a helpful tool for filtering out shorter-term market noise.
DSL Strategy [DailyPanda]
Overview
The DSL Strategy by DailyPanda is a trading strategy that synergistically combines the idea from indicators to create a more robust and reliable trading tool. By integrating these indicators, the strategy enhances signal accuracy and provides traders with a comprehensive view of market trends and momentum shifts. This combination allows for better entry and exit points, improved risk management, and adaptability to various market conditions.
Combining ideas from indicators adds value by:
Enhancing Signal Confirmation : The strategy requires alignment between trend and momentum before generating trade signals, reducing false entries.
Improving Accuracy : By integrating price action with momentum analysis, the strategy captures more reliable trading opportunities.
Providing Comprehensive Market Insight : The combination offers a better perspective on the market, considering both the direction (trend) and the strength (momentum) of price movements.
How the Components Work Together
1. Trend Identification with DSL Indicator
Dynamic Signal Lines : Calculates upper and lower DSL lines based on a moving average (SMA) and dynamic thresholds derived from recent highs and lows with a specified offset. These lines adapt to market conditions, providing real-time trend insights.
ATR-Based Bands : Adds bands around the DSL lines using the Average True Range (ATR) multiplied by a width factor. These bands account for market volatility and help identify potential stop-loss levels.
Trend Confirmation : The relationship between the price, DSL lines, and bands determines the current trend. For example, if the price consistently stays above the upper DSL line, it indicates a bullish trend.
2. Momentum Analysis
RSI Calculation : Computes the RSI over a specified period to measure the speed and change of price movements.
Zero-Lag EMA (ZLEMA) : Applies a ZLEMA to the RSI to minimize lag and produce a more responsive oscillator.
DSL Application on Oscillator : Implements the DSL concept on the oscillator by calculating dynamic upper and lower levels. This helps identify overbought or oversold conditions more accurately.
Signal Generation : Detects crossovers between the oscillator and its DSL lines. A crossover above the lower DSL line signals potential bullish momentum, while a crossover below the upper DSL line signals potential bearish momentum.
3. Integrated Signal Filtering
Confluence Requirement : A trade signal is generated only when both the DSL indicator and oscillator agree. For instance, a long entry requires both an uptrend confirmation from the DSL indicator and a bullish momentum signal from the oscillator.
Risk Management Integration : The strategy uses the DSL indicator's bands for setting stop-loss levels and calculates take-profit levels based on a user-defined risk-reward ratio. This ensures that every trade has a predefined risk management plan.
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Originality and Value Added to the Community
Unique Synergy : While both indicators are available individually, this strategy is original in how it combines them to enhance their strengths and mitigate their weaknesses, offering a novel approach not present in existing scripts.
Enhanced Reliability : By requiring confirmation from both trend and momentum indicators, the strategy reduces false signals and increases the likelihood of successful trades.
Versatility : The customizable parameters allow traders to adapt the strategy to different instruments, timeframes, and trading styles, making it a valuable tool for a wide range of trading scenarios.
Educational Contribution : The script demonstrates an effective method of combining indicators for improved trading performance, providing insights that other traders can learn from and apply to their own strategies.
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How to Use the Strategy
Adding the Strategy to Your Chart
Apply the DSL Strategy to your desired trading instrument and timeframe on TradingView.
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Configuring Parameters
DSL Indicator Settings :
Length (len) : Adjusts the sensitivity of the DSL lines (default is 34).
Offset : Determines the look-back period for threshold calculations (default is 30).
Bands Width (width) : Changes the distance of the ATR-based bands from the DSL lines (default is 1).
DSL-BELUGA Oscillator Settings :
Beluga Length (len_beluga) : Sets the period for the RSI calculation in the oscillator (default is 10).
DSL Lines Mode (dsl_mode) : Chooses between "Fast" (more responsive) and "Slow" (smoother) modes for the oscillator's DSL lines.
Risk Management :
Risk Reward (risk_reward) : Defines your desired risk-reward ratio for calculating take-profit levels (default is 1.5).
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Interpreting Signals
Long Entry Conditions :
Trend Confirmation : Price is above the upper DSL line and the upper DSL band (dsl_up1 > dsl_dn).
Price Behavior : The last three candles have both their opens and closes above the upper DSL line.
Momentum Signal : The DSL-BELUGA oscillator crosses above its lower DSL line (up_signal), indicating bullish momentum.
Short Entry Conditions :
Trend Confirmation : Price is below the lower DSL line and the lower DSL band (dsl_dn < dsl_up1).
Price Behavior : The last three candles have both their opens and closes below the lower DSL band.
Momentum Signal : The DSL-BELUGA oscillator crosses below its upper DSL line (dn_signal), indicating bearish momentum.
Exit Conditions :
Stop-Loss : Automatically set at the DSL indicator's band level (upper band for longs, lower band for shorts).
Take-Profit : Calculated based on the risk-reward ratio and the initial risk determined by the stop-loss distance.
Visual Aids
Signal Arrows : Upward green arrows for long entries and downward blue arrows for short entries appear on the chart when conditions are met.
Stop-Loss and Take-Profit Lines : Red and green lines display the calculated stop-loss and take-profit levels for active trades.
Background Highlighting : The chart background subtly changes color to indicate when a signal has been generated.
Backtesting and Optimization
Use TradingView's strategy tester to backtest the strategy over historical data.
Adjust parameters to optimize performance for different instruments or market conditions.
Regularly review backtesting results to ensure the strategy remains effective.
Pullback Scalp Trade V2Pullback Scalp Trading Indicator
This indicator combines multiple technical analysis tools to identify potential pullback trading opportunities in trending markets. It uses a dual moving average system along with RSI for confirmation, providing a comprehensive approach to trend-following and momentum trading.
Key Features:
1. Trend Identification:
- Uses 50 and 200 period moving averages to define the overall trend
- Visual trend zone highlighting for clear market direction
- Customizable MA periods for different timeframes
2. Signal Generation System:
- Combines RSI crossovers with trend direction
- Buy signals occur when:
* Price is above 200 MA (uptrend)
* RSI crosses above its SMA
* RSI is below the lower threshold (default 50)
- Sell signals occur when:
* Price is below 200 MA (downtrend)
* RSI crosses below its SMA
* RSI is above the upper threshold (default 50)
3. Customizable Parameters:
- Short and Long MA periods
- MA types (SMA, EMA, VWMA)
- RSI length and RSI-SMA length
- RSI signal thresholds
- Trend MA periods
Usage Guidelines:
- Best used on higher timeframes (1H and above) for trend trading
- Wait for price to respect the trend zone before taking trades
- Use additional confirmation from price action or other indicators
- Adjust RSI levels based on market volatility
Limitations:
- Like all indicators, this tool may generate false signals in choppy markets
- Should not be used as a sole decision-making tool
- Past performance does not guarantee future results
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Türkçe Açıklama:
Bu indikatör, trendli piyasalarda potansiyel geri çekilme fırsatlarını belirlemek için birden fazla teknik analiz aracını birleştirir. Trend takibi ve momentum ticareti için kapsamlı bir yaklaşım sunan ikili hareketli ortalama sistemi ile RSI'yı bir arada kullanır.
Temel Özellikler:
1. Trend Belirleme:
- Genel trendi tanımlamak için 50 ve 200 periyotlu hareketli ortalamalar
- Görsel trend bölgesi vurgulaması
- Farklı zaman dilimleri için özelleştirilebilir MA periyotları
2. Sinyal Üretim Sistemi:
- RSI kesişimlerini trend yönü ile birleştirir
- Alış sinyalleri şu durumlarda oluşur:
* Fiyat 200 MA'nın üzerinde (yükseliş trendi)
* RSI, SMA'sını yukarı keser
* RSI alt eşiğin altında (varsayılan 50)
- Satış sinyalleri şu durumlarda oluşur:
* Fiyat 200 MA'nın altında (düşüş trendi)
* RSI, SMA'sını aşağı keser
* RSI üst eşiğin üzerinde (varsayılan 50)
3. Özelleştirilebilir Parametreler:
- Kısa ve Uzun MA periyotları
- MA tipleri (SMA, EMA, VWMA)
- RSI uzunluğu ve RSI-SMA uzunluğu
- RSI sinyal seviyeleri
- Trend MA periyotları
Kullanım Önerileri:
- Trend ticareti için yüksek zaman dilimlerinde (1S ve üzeri) kullanılması önerilir
- İşlem almadan önce fiyatın trend bölgesine saygı göstermesini bekleyin
- Fiyat hareketi veya diğer indikatörlerden ek teyit alın
- RSI seviyelerini piyasa volatilitesine göre ayarlayın
Sınırlamalar:
- Tüm indikatörler gibi, dalgalı piyasalarda yanlış sinyaller üretebilir
- Tek başına karar verme aracı olarak kullanılmamalıdır
- Geçmiş performans, gelecekteki sonuçların garantisi değildir
3CRGANG - TMASlope3CRGANG - TMASlope: Slope-Based Trend Insights with Multi-Timeframe Support
The 3CRGANG - TMASlope indicator is crafted to provide traders with precise trend insights by analyzing the slope of the TMA (Triangular Moving Average). This tool goes beyond traditional indicators, focusing on slope detection to help traders gauge momentum and trend direction across multiple timeframes.
Key Features of TMASlope
Multi-Timeframe Trend Alignment : TMASlope includes a table showing trend statuses for up to three selected timeframes. This helps traders check for trend consistency across timeframes, providing a clearer picture of overall momentum.
Color-Coded Histogram for Quick Reference : The histogram visually distinguishes between uptrends, downtrends, and ranging markets. This color-coded display offers an at-a-glance understanding of market conditions.
Adaptability to Different Markets : In markets where volume data may be missing, TMASlope is designed to adapt, ensuring that the indicator remains effective and reliable in any environment.
User-Centric Design and Customization
TMASlope is designed with simplicity and customization in mind. Traders can adjust threshold settings to match their specific trading style. The indicator also includes customizable color themes and visual alerts to support more intuitive decision-making.
Visual Alerts and Practical Use
The indicator’s trend status table provides “Buy Only,” “Sell Only,” or “Ranging” signals based on momentum. The histogram offers further visual guidance for when to consider entering, holding, or exiting trades.
Example of TMASlope in Action
In volatile or low-volume markets, TMASlope helps traders make sense of price movements by delivering stable, clear signals. The multi-timeframe trend table supports strategic alignment by confirming trends across timeframes, helping traders make informed choices in any market condition.
EMD Oscillator (Zeiierman)█ Overview
The Empirical Mode Decomposition (EMD) Oscillator is an advanced indicator designed to analyze market trends and cycles with high precision. It breaks down complex price data into simpler parts called Intrinsic Mode Functions (IMFs), allowing traders to see underlying patterns and trends that aren’t visible with traditional indicators. The result is a dynamic oscillator that provides insights into overbought and oversold conditions, as well as trend direction and strength. This indicator is suitable for all types of traders, from beginners to advanced, looking to gain deeper insights into market behavior.
█ How It Works
The core of this indicator is the Empirical Mode Decomposition (EMD) process, a method typically used in signal processing and advanced scientific fields. It works by breaking down price data into various “layers,” each representing different frequencies in the market’s movement. Imagine peeling layers off an onion: each layer (or IMF) reveals a different aspect of the price action.
⚪ Data Decomposition (Sifting): The indicator “sifts” through historical price data to detect natural oscillations within it. Each oscillation (or IMF) highlights a unique rhythm in price behavior, from rapid fluctuations to broader, slower trends.
⚪ Adaptive Signal Reconstruction: The EMD Oscillator allows traders to select specific IMFs for a custom signal reconstruction. This reconstructed signal provides a composite view of market behavior, showing both short-term cycles and long-term trends based on which IMFs are included.
⚪ Normalization: To make the oscillator easy to interpret, the reconstructed signal is scaled between -1 and 1. This normalization lets traders quickly spot overbought and oversold conditions, as well as trend direction, without worrying about the raw magnitude of price changes.
The indicator adapts to changing market conditions, making it effective for identifying real-time market cycles and potential turning points.
█ Key Calculations: The Math Behind the EMD Oscillator
The EMD Oscillator’s advanced nature lies in its high-level mathematical operations:
⚪ Intrinsic Mode Functions (IMFs)
IMFs are extracted from the data and act as the building blocks of this indicator. Each IMF is a unique oscillation within the price data, similar to how a band might be divided into treble, mid, and bass frequencies. In the EMD Oscillator:
Higher-Frequency IMFs: Represent short-term market “noise” and quick fluctuations.
Lower-Frequency IMFs: Capture broader market trends, showing more stable and long-term patterns.
⚪ Sifting Process: The Heart of EMD
The sifting process isolates each IMF by repeatedly separating and refining the data. Think of this as filtering water through finer and finer mesh sieves until only the clearest parts remain. Mathematically, it involves:
Extrema Detection: Finding all peaks and troughs (local maxima and minima) in the data.
Envelope Calculation: Smoothing these peaks and troughs into upper and lower envelopes using cubic spline interpolation (a method for creating smooth curves between data points).
Mean Removal: Calculating the average between these envelopes and subtracting it from the data to isolate one IMF. This process repeats until the IMF criteria are met, resulting in a clean oscillation without trend influences.
⚪ Spline Interpolation
The cubic spline interpolation is an advanced mathematical technique that allows smooth curves between points, which is essential for creating the upper and lower envelopes around each IMF. This interpolation solves a tridiagonal matrix (a specialized mathematical problem) to ensure that the envelopes align smoothly with the data’s natural oscillations.
To give a relatable example: imagine drawing a smooth line that passes through each peak and trough of a mountain range on a map. Spline interpolation ensures that line is as smooth and close to reality as possible. Achieving this in Pine Script is technically demanding and demonstrates a high level of mathematical coding.
⚪ Amplitude Normalization
To make the oscillator more readable, the final signal is scaled by its maximum amplitude. This amplitude normalization brings the oscillator into a range of -1 to 1, creating consistent signals regardless of price level or volatility.
█ Comparison with Other Signal Processing Methods
Unlike standard technical indicators that often rely on fixed parameters or pre-defined mathematical functions, the EMD adapts to the data itself, capturing natural cycles and irregularities in real-time. For example, if the market becomes more volatile, EMD adjusts automatically to reflect this without requiring parameter changes from the trader. In this way, it behaves more like a “smart” indicator, intuitively adapting to the market, unlike most traditional methods. EMD’s adaptive approach is akin to AI’s ability to learn from data, making it both resilient and robust in non-linear markets. This makes it a great alternative to methods that struggle in volatile environments, such as fixed-parameter oscillators or moving averages.
█ How to Use
Identify Market Cycles and Trends: Use the EMD Oscillator to spot market cycles that represent phases of buying or selling pressure. The smoothed version of the oscillator can help highlight broader trends, while the main oscillator reveals immediate cycles.
Spot Overbought and Oversold Levels: When the oscillator approaches +1 or -1, it may indicate that the market is overbought or oversold, signaling potential entry or exit points.
Confirm Divergences: If the price movement diverges from the oscillator's direction, it may indicate a potential reversal. For example, if prices make higher highs while the oscillator makes lower highs, it could be a sign of weakening trend strength.
█ Settings
Window Length (N): Defines the number of historical bars used for EMD analysis. A larger window captures more data but may slow down performance.
Number of IMFs (M): Sets how many IMFs to extract. Higher values allow for a more detailed decomposition, isolating smaller cycles within the data.
Amplitude Window (L): Controls the length of the window used for amplitude calculation, affecting the smoothness of the normalized oscillator.
Extraction Range (IMF Start and End): Allows you to select which IMFs to include in the reconstructed signal. Starting with lower IMFs captures faster cycles, while ending with higher IMFs includes slower, trend-based components.
Sifting Stopping Criterion (S-number): Sets how precisely each IMF should be refined. Higher values yield more accurate IMFs but take longer to compute.
Max Sifting Iterations (num_siftings): Limits the number of sifting iterations for each IMF extraction, balancing between performance and accuracy.
Source: The price data used for the analysis, such as close or open prices. This determines which price movements are decomposed by the indicator.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
RSI - EMA - WMA ( Phat-Truong )Indicator: RSI ( EMA - WMA )
This indicator, named "RSI ( EMA - WMA )", is a versatile tool designed to provide insights into market momentum and trend strength by combining multiple technical indicators.
The Relative Strength Index (RSI) is a popular momentum oscillator used to measure the speed and change of price movements. In this indicator, RSI is plotted alongside its Exponential Moving Average (EMA) and Weighted Moving Average (WMA). EMA and WMA are smoothing techniques applied to RSI to help identify trends more clearly.
Key features of this indicator include:
RSI: The main RSI line is plotted on the chart, offering insights into overbought and oversold conditions.
EMA of RSI: The Exponential Moving Average of RSI smooths out short-term fluctuations, aiding in trend identification.
WMA of RSI: The Weighted Moving Average of RSI gives more weight to recent data points, providing a faster response to price changes.
Additionally, this indicator marks specific RSI levels considered as bullish and bearish trends, helping traders identify potential entry or exit points based on market sentiment.
By combining these technical indicators, traders can gain a comprehensive understanding of market dynamics, helping them make more informed trading decisions.
MoonrushCAPITALCOM:US100
Moonrush Indicator - Multi-Timeframe Trend Analysis Tool
Moonrush is a trend analysis tool that helps traders see market trends and identify potential entry or exit points using a combination of Exponential Moving Averages (EMAs) and overbought/oversold signals. The tool has the ability to display data in an easy-to-read dashboard, eliminating the need for users to frequently change charts to get an overview of trends across multiple timeframes.
Key Features and Methods
Multi-Timeframe Trend Analysis:
Moonrush analyzes trends on 1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, and 1-day timeframes. It calculates the trend by comparing two user-defined EMA values (EMAfast and EMAslow). If the EMAfast crosses above the EMAslow, it indicates an uptrend (shown in green), while if it crosses below, it indicates a downtrend (shown in red). This allows traders to see the consistency of trends across multiple timeframes.
Customizable Dashboard:
Moonrush provides a dashboard that shows the trend and RSI index for each timeframe, with a table that allows traders to quickly assess market conditions. By displaying the RSI level, it can indicate overbought or oversold conditions. Green is used to indicate overbought conditions, while red is used for oversold conditions.
Overbought/Oversold Color Display:
The dashboard highlights overbought and oversold zones on the support EMA and resistance EMA lines, making it easier for users to identify reversal opportunities.
Key Parameters for Flexibility
EMA Adjustment and Toggle Switch:
Users can adjust the EMAfast and EMAslow parameters to suit their preferences, including turning the EMA display on or off as needed.
Dashboard Customization:
Traders can adjust the size and position of the dashboard to enhance usability, ensuring a clear display without cluttering the chart.
Focus on Risk Management:
Although Moonrush helps in trend detection, users should use this analysis in conjunction with appropriate risk management techniques. It is important to understand how Moonrush works, as the intersection of the EMA and RSI can help identify reversal and continuation patterns. However, users should consider the limitations of this indicator and examine the signals within a broader trading strategy.
How to Use Moonrush
Trend Confirmation:
Check the dashboard to see if trends across multiple timeframes are consistent, to create opportunities to follow or counter the trend.
Identifying Reversals:
Use the overbought and oversold color representations on the EMA support/resistance lines as reversal signals.
Customization:
Adjust the EMA values to your trading style and turn the display on or off as needed.
Moonrush, which combines EMA crossovers and RSI indicators, offers a versatile approach to trend analysis across multiple timeframes. However, traders should note that no single indicator can guarantee success. Users should conduct thorough backtesting and use it in accordance with their personal trading goals and risk tolerance.
##Please note that the tool (Moonrush) is not a guarantee of future market performance and should be used in conjunction with appropriate risk management. Users should ensure that they fully understand the methodology and limitations of the indicator before making any investment decisions. In addition, past performance is not an indication of future results.
CMF and Scaled EFI OverlayCMF and Scaled EFI Overlay Indicator
Overview
The CMF and Scaled EFI Overlay indicator combines the Chaikin Money Flow (CMF) and a scaled version of the Elder Force Index (EFI) into a single chart. This allows traders to analyze both indicators simultaneously, facilitating better insights into market momentum and volume dynamics , specifically focusing on buying/selling pressure and momentum , without compromising the integrity of either indicator.
Purpose
Chaikin Money Flow (CMF): Measures buying and selling pressure by evaluating price and volume over a specified period. It indicates accumulation (buying pressure) when values are positive and distribution (selling pressure) when values are negative.
Elder Force Index (EFI): Combines price changes and volume to assess the momentum behind market moves. Positive values indicate upward momentum (prices rising with strong volume), while negative values indicate downward momentum (prices falling with strong volume).
By scaling the EFI to match the amplitude of the CMF, this indicator enables a direct comparison between pressure and momentum , preserving their shapes and zero crossings. Traders can observe the relationship between price movements, volume, and momentum more effectively, aiding in decision-making.
Understanding Pressure vs. Momentum
Chaikin Money Flow (CMF):
- Indicates the level of demand (buying pressure) or supply (selling pressure) in the market based on volume and price movements.
- Accumulation: When institutional or large investors are buying significant amounts of an asset, leading to an increase in buying pressure.
- Distribution: When these investors are selling off their holdings, increasing selling pressure.
Elder Force Index (EFI):
- Measures the strength and speed of price movements, indicating how forceful the current trend is.
- Positive Momentum: Prices are rising quickly, indicating a strong uptrend.
- Negative Momentum: Prices are falling rapidly, indicating a strong downtrend.
Understanding the difference between pressure and momentum is crucial. For example, a market may exhibit strong buying pressure (positive CMF) but weak momentum (low EFI), suggesting accumulation without significant price movement yet.
Features
Overlay of CMF and Scaled EFI: Both indicators are plotted on the same chart for easy comparison of pressure and momentum dynamics.
Customizable Parameters: Adjust lengths for CMF and EFI calculations and fine-tune the scaling factor for optimal alignment.
Preserved Indicator Integrity: The scaling method preserves the shape and zero crossings of the EFI, ensuring accurate analysis.
How It Works
CMF Calculation:
- Calculates the Money Flow Multiplier (MFM) and Money Flow Volume (MFV) to assess buying and selling pressure.
- CMF is computed by summing the MFV over the specified length and dividing by the sum of volume over the same period:
CMF = (Sum of MFV over n periods) / (Sum of Volume over n periods)
EFI Calculation:
- Calculates the EFI using the Exponential Moving Average (EMA) of the price change multiplied by volume:
EFI = EMA(n, Change in Close * Volume)
Scaling the EFI:
- The EFI is scaled by multiplying it with a user-defined scaling factor to match the CMF's amplitude.
Plotting:
- Both the CMF and the scaled EFI are plotted on the same chart.
- A zero line is included for reference, aiding in identifying crossovers and divergences.
Indicator Settings
Inputs
CMF Length (`cmf_length`):
- Default: 20
- Description: The number of periods over which the CMF is calculated. A higher value smooths the indicator but may delay signals.
EFI Length (`efi_length`):
- Default: 13
- Description: The EMA length for the EFI calculation. Adjusting this value affects the sensitivity of the EFI to price changes.
EFI Scaling Factor (`efi_scaling_factor`):
- Default: 0.000001
- Description: A constant used to scale the EFI to match the CMF's amplitude. Fine-tuning this value ensures the indicators align visually.
How to Adjust the EFI Scaling Factor
Start with the Default Value:
- Begin with the default scaling factor of `0.000001`.
Visual Inspection:
- Observe the plotted indicators. If the EFI appears too large or small compared to the CMF, proceed to adjust the scaling factor.
Fine-Tune the Scaling Factor:
- Increase or decrease the scaling factor incrementally (e.g., `0.000005`, `0.00001`, `0.00005`) until the amplitudes of the CMF and EFI visually align.
- The optimal scaling factor may vary depending on the asset and timeframe.
Verify Alignment:
- Ensure that the scaled EFI preserves the shape and zero crossings of the original EFI.
- Overlay the original EFI (if desired) to confirm alignment.
How to Use the Indicator
Analyze Buying/Selling Pressure and Momentum:
- Positive CMF (>0): Indicates accumulation (buying pressure).
- Negative CMF (<0): Indicates distribution (selling pressure).
- Positive EFI: Indicates positive momentum (prices rising with strong volume).
- Negative EFI: Indicates negative momentum (prices falling with strong volume).
Look for Indicator Alignment:
- Both CMF and EFI Positive:
- Suggests strong bullish conditions with both buying pressure and upward momentum.
- Both CMF and EFI Negative:
- Indicates strong bearish conditions with selling pressure and downward momentum.
Identify Divergences:
- CMF Positive, EFI Negative:
- Buying pressure exists, but momentum is negative; potential for a bullish reversal if momentum shifts.
- CMF Negative, EFI Positive:
- Selling pressure exists despite rising prices; caution advised as it may indicate a potential bearish reversal.
Confirm Signals with Other Analysis:
- Use this indicator in conjunction with other technical analysis tools (e.g., trend lines, support/resistance levels) to confirm trading decisions.
Example Usage
Scenario 1: Bullish Alignment
- CMF Positive: Indicates accumulation (buying pressure).
- EFI Positive and Increasing: Shows strengthening upward momentum.
- Interpretation:
- Strong bullish signal suggesting that buyers are active, and the price is likely to continue rising.
- Action:
- Consider entering a long position or adding to existing ones.
Scenario 2: Bearish Divergence
- CMF Negative: Indicates distribution (selling pressure).
- EFI Positive but Decreasing: Momentum is positive but weakening.
- Interpretation:
- Potential bearish reversal; price may be rising but underlying selling pressure suggests caution.
- Action:
- Be cautious with long positions; consider tightening stop-losses or preparing for a possible trend reversal.
Tips
Adjust for Different Assets:
- The optimal scaling factor may differ across assets due to varying price and volume characteristics.
- Always adjust the scaling factor when analyzing a new asset.
Monitor Indicator Crossovers:
- Crossings above or below the zero line can signal potential trend changes.
Watch for Divergences:
- Divergences between the CMF and EFI can provide early warning signs of trend reversals.
Combine with Other Indicators:
- Enhance your analysis by combining this overlay with other indicators like moving averages, RSI, or Ichimoku Cloud.
Limitations
Scaling Factor Sensitivity:
- An incorrect scaling factor may misalign the indicators, leading to inaccurate interpretations.
- Regular adjustments may be necessary when switching between different assets or timeframes.
Not a Standalone Indicator:
- Should be used as part of a comprehensive trading strategy.
- Always consider other market factors and indicators before making trading decisions.
Disclaimer
No Guarantee of Performance:
- Past performance is not indicative of future results.
- Trading involves risk, and losses can exceed deposits.
Use at Your Own Risk:
- This indicator is provided for educational purposes.
- The author is not responsible for any financial losses incurred while using this indicator.
Code Summary
//@version=5
indicator(title="CMF and Scaled EFI Overlay", shorttitle="CMF & Scaled EFI", overlay=false)
cmf_length = input.int(20, minval=1, title="CMF Length")
efi_length = input.int(13, minval=1, title="EFI Length")
efi_scaling_factor = input.float(0.000001, title="EFI Scaling Factor", minval=0.0, step=0.000001)
// --- CMF Calculation ---
ad = high != low ? ((2 * close - low - high) / (high - low)) * volume : 0
mf = math.sum(ad, cmf_length) / math.sum(volume, cmf_length)
// --- EFI Calculation ---
efi_raw = ta.ema(ta.change(close) * volume, efi_length)
// --- Scale EFI ---
efi_scaled = efi_raw * efi_scaling_factor
// --- Plotting ---
plot(mf, color=color.green, title="CMF", linewidth=2)
plot(efi_scaled, color=color.red, title="EFI (Scaled)", linewidth=2)
hline(0, color=color.gray, title="Zero Line", linestyle=hline.style_dashed)
- Lines 4-6: Define input parameters for CMF length, EFI length, and EFI scaling factor.
- Lines 9-11: Calculate the CMF.
- Lines 14-16: Calculate the EFI.
- Line 19: Scale the EFI by the scaling factor.
- Lines 22-24: Plot the CMF, scaled EFI, and zero line.
Feedback and Support
Suggestions: If you have ideas for improvements or additional features, please share your feedback.
Support: For assistance or questions regarding this indicator, feel free to contact the author through TradingView.
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By combining the CMF and scaled EFI into a single overlay, this indicator provides a powerful tool for traders to analyze market dynamics more comprehensively. Adjust the parameters to suit your trading style, and always practice sound risk management.
RS+ Majors Allocation | viResearchRS+ Majors Allocation | viResearch
Conceptual Foundation and Innovation
The "RS+ Majors Allocation" script is a comprehensive strategy for managing a crypto portfolio focused on BTC, ETH, and SOL. By dynamically rotating between these major assets, the strategy aims to identify the strongest performer in real-time and allocate capital accordingly. The script incorporates a relative strength (RS) model that leverages price movements and a custom scoring system to rank each asset's performance. This allows the strategy to maintain positions in favorable market conditions while moving to cash during periods of weakness.
The script also includes a trend regime filter to further refine allocations. This filter ensures that an asset's own trend aligns with the market’s trend before committing to an allocation, adding another layer of protection against downturns. The approach is designed to outperform traditional buy-and-hold strategies by minimizing risk exposure during unfavorable market conditions.
Technical Composition and Calculation
The "RS+ Majors Allocation" script combines several technical elements to execute the strategy:
Relative Strength Model: Each asset (BTC, ETH, SOL) is evaluated through a ratio matrix, comparing their performance relative to one another. A scoring system is applied to these ratios to rank the assets, determining which is outperforming. This dynamic evaluation is central to the strategy's decision-making process.
Trend Regime Filter: This filter uses trend indicators to assess whether the market and individual assets are in a favorable state. If an asset’s trend score does not meet the criteria, it won't be allocated capital, thus avoiding exposure to potential downturns.
Equity Tracking and Allocation: The script tracks the portfolio's equity performance over time, plotting it against a traditional buy-and-hold strategy for comparison. Allocation decisions are based on the scores of BTC, ETH, and SOL, with the system selecting the top-performing asset and moving to cash if no asset meets the criteria.
Performance Metrics: To evaluate the effectiveness of the strategy, the script calculates several key performance indicators:
Sharpe Ratio: Measures risk-adjusted returns.
Sortino Ratio: Focuses on downside risk by considering only negative fluctuations.
Omega Ratio: Analyzes returns relative to risk.
Maximum Drawdown: Shows the largest peak-to-trough decline, indicating potential loss exposure.
Features and User Inputs
The script offers a range of customizable parameters to tailor the strategy to individual preferences and market conditions:
Asset Selection: Users can choose the specific assets to include in the rotation, with the script currently focusing on BTC, ETH, and SOL. The trend regime filter is optional, allowing for a more aggressive or conservative approach.
Equity Visualization: The script provides real-time equity tracking, comparing the portfolio's performance with individual assets. Users can adjust visualization settings to focus on specific assets or the overall strategy.
Starting Date: The backtesting period can be set to begin at a specific date, helping to analyze the strategy’s performance over different timeframes.
Bar Colors and Alerts: Visual cues, including colored bars, indicate the active trend direction of the selected asset. Additionally, alerts notify traders when the system rotates between assets or moves to cash.
Practical Applications
The "RS+ Majors Allocation" script is designed for traders who want to manage a crypto portfolio with a focus on risk-adjusted returns. It is particularly effective in several scenarios:
Asset Rotation: The dynamic scoring system allows the script to rotate between BTC, ETH, and SOL based on relative strength, capitalizing on the strongest performer at any given time.
Downside Protection: The trend regime filter helps avoid exposure during market-wide downturns by staying in cash, minimizing drawdowns during periods of high volatility.
Active Portfolio Management: By using real-time data to make allocation decisions, the script offers a more hands-on approach to portfolio management compared to passive holding strategies.
Advantages and Strategic Value
This script brings a structured and disciplined approach to portfolio management, combining trend analysis, relative strength, and performance metrics to optimize returns. The use of a scoring system for asset rotation, along with the trend filter, makes it versatile and adaptable to different market environments. The script aims to outperform traditional buy-and-hold strategies by focusing on the strongest assets while reducing risk during unfavorable conditions.
The visual and performance feedback provided by the script allows traders to gain deeper insights into their portfolio’s behavior, helping to make data-driven decisions.
Summary and Usage Tips
The "RS+ Majors Allocation" script is a powerful tool for managing a crypto portfolio with a focus on performance optimization and risk management. By incorporating this strategy, traders can dynamically allocate capital to the top-performing assets while protecting their portfolio from significant downturns. Adjust the trend regime filter, threshold settings, and asset choices to fit your market outlook and trading goals. The script's equity tracking and performance metrics will provide clear insights into how well the strategy is performing compared to a traditional buy-and-hold approach.
Remember to use backtesting to assess the script's effectiveness over different timeframes and market conditions. Keep in mind that past performance does not guarantee future results, so consider using this strategy in conjunction with other analysis tools for a comprehensive approach to trading.
Range Tightening Indicator (RTI)The Range Tightening Indicator (RTI) quantifies price volatility relative to recent price action, helping traders identify low-volatility consolidations that often precede breakouts.
Range Tightening is calculated by measuring the range between each bar’s high and low prices over a chosen lookback period.
A 5-bar period is recommended for shorter-term momentum setups and a 15-bar period is recommended for swing trading. An option for a custom period is available to suit specific strategies. The default look back for custom is 50, ideal for longer term traders.
Other Key Features:
Dynamic Color Coding: The RTI line turns green when volatility doubles after a drop to or below 20, flagging significant volatility shifts commonly seen before breakouts.
Low-Volatility Dots: Orange dots appear on the RTI line when two or more consecutive bars show RTI values below 20, visually marking extended low-volatility periods.
Volatility Zones: Shaded zones provide quick context:
Zone 1 (0-5): Extremely tight volatility, shown in red.
Zone 2 (5-10): Low volatility, shown in light green.
Zone 3 (10-15): Moderate low volatility, shown in green.
The RTI indicator is ideal for traders looking to anticipate breakout conditions, with features that highlight consolidation phases, support momentum strategies, and help improve entry timing by focusing on shifts in volatility.
This indicator was inspired after Deepvue's RMV Indicator, but uses a different calculation. Results may vary.
Supertrend StrategyThe Supertrend Strategy was created based on the Supertrend and Relative Strength Index (RSI) indicators, widely respected tools in technical analysis. This strategy combines these two indicators to capture market trends with precision and reliability, looking for optimizing exit levels at oversold or overbought price levels.
The Supertrend indicator identifies trend direction based on price and volatility by using the Average True Range (ATR). The ATR measures market volatility by calculating the average range between an asset’s high and low prices over a set period. It provides insight into price fluctuations, with higher ATR values indicating increased volatility and lower values suggesting stability. The Supertrend Indicator plots a line above or below the price, signaling potential buy or sell opportunities: when the price closes above the Supertrend line, an uptrend is indicated, while a close below the line suggests a downtrend. This line shifts as price movements and volatility levels change, acting as both a trailing stop loss and trend confirmation.
To enhance the Supertrend strategy, the Relative Strength Index (RSI) has been added as an exit criterion. As a momentum oscillator, the RSI indicates overbought (usually above 70) or oversold (usually below 30) conditions. This integration allows trades to close when the asset is overbought or oversold, capturing gains before a possible reversal, even if the percentage take profit level has not been reached. This mechanism aims to prevent losses due to market reversals before the Supertrend signal changes.
### Key Features
1. **Entry criteria**:
- The strategy uses the Supertrend indicator calculated by adding or subtracting a multiple of the ATR from the closing price, depending on the trend direction.
- When the price crosses above the Supertrend line, the strategy signals a long (buy) entry. Conversely, when the price crosses below, it signals a short (sell) entry.
- The strategy performs a reversal if there is an open position and a change in the direction of the supertrend occurs
2. **Exit criteria**:
- Take profit of 30% (default) on the average position price.
- Oversold (≤ 5) or overbought (≥ 95) RSI
- Reversal when there is a change in direction of the Supertrend
3. **No Repainting**:
- This strategy is not subject to repainting, as long as the timeframe configured on your chart is the same as the supertrend timeframe .
4. **Position Sizing by Equity and risk management**:
- This strategy has a default configuration to operate with 35% of the equity. At the time of opening the position, the supertrend line is typically positioned at about 12 to 16% of the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity can be adjusted by the user according to their risk management.
5. **Backtest results**:
- This strategy was subjected to deep backtesting and operations in replay mode, including transaction fees of 0.12%, and slippage of 5 ticks.
- The past results in deep backtest and replay mode were compatible and profitable (Variable results depending on the take profit used, supertrend and RSI parameters). However, it should be noted that few operations were evaluated, since the currency in question has been created for a short time and the frequency of operations is relatively small.
- Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
Default Settings
Chart timeframe: 2h
Supertrend Factor: 3.42
ATR period: 14
Supertrend timeframe: 2 h
RSI timeframe: 15 min
RSI Lenght: 5 min
RSI Upper limit: 95
RSI Lower Limit: 5
Take Profit: 30%
BYBIT:1000000MOGUSDT.P
Machine Learning RSI Bands"Machine Learning RSI Bands" Indicator
The "Machine Learning RSI Bands" (MLRSIB) indicator leverages advanced algorithmic analysis to enhance traditional RSI strategies:
RSI Customization: Users can customize the RSI settings including source, length, and thresholds for overbought/oversold conditions.
Innovative Machine Learning Application: The script uses a proprietary function FOUNDATION_400x10x2 from the 'FOUNDATION' library, which analyzes the last 400 occurrences of data points, considering various market dynamics like volume changes or RSI movements based on the selected sampling method. Outputs four optimal outcomes for both upper and lower band conditions, representing the most statistically significant patterns or predictions.
Dynamic Band Visualization: Plots the average of these four outcomes as colored lines (red for the upper band, green for the lower band) on the chart, serving as dynamic support and resistance or overbought/oversold levels.
Signal Plotting: Displays triangles above or below the bars to signal potential short or long entries when the RSI crosses these machine learning-adjusted bands under certain confidence conditions.
Market Volatility Indicator: Adjusts the chart's background color based on volatility, using an average deviation analysis to gauge market calmness or agitation.
Alert System: Provides alert conditions for when these sophisticated signals are triggered, allowing for timely trading actions.
This indicator is designed for traders interested in combining traditional technical analysis with machine learning to refine their market entry and exit strategies, focusing on patterns identified from recent market behavior.
Atr Target TP & Protecion Zone [Pinescriptlabs]This indicator provides an adaptive trailing stop system with dynamic price targets and protection zones, ideal for position management.
Main Features:
🚦 ADAPTIVE TRAILING STOP:
Automatically adjusts based on volatility (ATR) and volume
Two modes: "Modified" and "UnModified" for true range calculation
Displayed as a line with colored background (green for longs, red for shorts)
🎯 TARGET ZONES (T1 & T2):
Calculates two target zones (T1 and T2) based on:
Market strength (combination of RSI, volume, MFI, ADX, MACD)
Current volatility (ATR)
Distance from current price
Visualized with blue boxes (T1) and purple boxes (T2)
🛡️ PROTECTION ZONE:
Automatically activates in sideways markets
Provides an additional buffer to the trailing stop
Helps avoid premature exits in volatile markets
📊 INFORMATION PANELS:
Top Right Panel displays:
Current trend direction
Target status (T1 & T2)
Market strength
Current ATR
RSI level
Bottom Right Panel displays:
Trailing status (WIDE/NORMAL)
Volume impact
Directional strength
Protection zone status
Español:
Este indicador proporciona un sistema de trailing stop adaptativo con objetivos de precio dinámicos y zonas de protección, ideal para la gestión de posiciones.
**Características Principales**:
🚦 **TRAILING STOP ADAPTATIVO**:
- Se ajusta automáticamente según la volatilidad (ATR) y el volumen
- Dos modos: "Modified" y "UnModified" para el cálculo del rango verdadero
- Se visualiza como una línea con fondo coloreado (verde para largos, rojo para cortos)
🎯 **ZONAS OBJETIVO (T1 y T2)**:
- Calcula dos zonas objetivo (T1 y T2) basadas en:
- Fuerza del mercado (combinación de RSI, volumen, MFI, ADX, MACD)
- Volatilidad actual (ATR)
- Distancia al precio actual
- Visualización mediante cajas azules (T1) y moradas (T2)
🛡️ **ZONA DE PROTECCIÓN**:
- Se activa automáticamente en mercados laterales
- Proporciona un buffer adicional al trailing stop
- Ayuda a evitar salidas prematuras en mercados volátiles
📊 **PANELES INFORMATIVOS**:
*Panel Superior Derecho* muestra:
- Dirección de la tendencia actual
- Estado de los objetivos (T1 y T2)
- Fuerza del mercado
- ATR actual
- Nivel de RSI
*Panel Inferior Derecho* muestra:
- Estado del trailing (WIDE/NORMAL)
- Impacto del volumen
- Fuerza direccional
- Estado de la zona de protección
