Options Series - P_SAR And Supertrend
The provided PineScript combines two well-known indicators—Parabolic SAR (P_SAR) and Supertrend—to create a comprehensive trading tool. Here are some powerful insights and the importance of this script:
⭐ 1. Supertrend Indicator:
What it does: The Supertrend indicator is based on the Average True Range (ATR) and is used to identify trend direction. When the price is above the Supertrend line, it suggests an uptrend, and when below, a downtrend.
Insights:
Trend Following: By adjusting the ATR length (atrPeriod) and the multiplier (factor), you can fine-tune the sensitivity of the Supertrend. A smaller ATR or factor results in more frequent trend changes, whereas larger values make the indicator more robust but slower to react.
Trend Visualization: The script highlights trends with the help of green and red lines, offering a clear visual cue for traders. The uptrend is filled with a translucent green and the downtrend with red, allowing quick identification of market momentum.
⭐ 2. Parabolic SAR (P_SAR):
What it does: The Parabolic SAR is a time/price-based indicator that helps identify potential reversals in the market. The dots (SAR) follow the price and move closer to it as the trend progresses.
Insights:
Trailing Stops: This is commonly used by traders to trail stop losses, as the SAR moves closer to price as the trend strengthens.
Combining with Supertrend: The SAR dots in this script act as an additional confirmation for trend direction. For instance, when the price is above both the SAR and Supertrend, it strongly suggests an uptrend.
⭐ 3. Bar Coloring Based on Trend Confirmation:
What it does: The script calculates conditions based on whether the price is above or below both the Supertrend and SAR values.
Insights:
Bullish/Bearish Confirmation: The combination of these two indicators provides a stronger confirmation of trend direction compared to using either one alone. For example:
Green Bars: If the price is above both the Supertrend and SAR, it signals a strong uptrend (bullish).
Red Bars: If the price is below both, it suggests a strong downtrend (bearish).
Visual Alerts: The candle colors are adjusted based on these conditions, providing a quick visual alert for traders to take action.
⭐ 4. Importance of Using Both Supertrend and P_SAR:
Multiple Confirmations: Combining the Supertrend and Parabolic SAR increases the accuracy of trend-following strategies. Each indicator has its strengths: Supertrend is good for identifying the overall trend, while the SAR excels at identifying potential reversals.
Risk Management: This script can help you not only identify trends but also manage your positions more effectively. The Parabolic SAR, for example, can serve as a dynamic stop-loss level, while the Supertrend can help you stay in trades longer by smoothing out noise in the market.
⭐ 5. Customizable Inputs:
Adaptability: The user can adjust the ATR period, factor, start, increment, and maximum values, tailoring the script to different market conditions and timeframes. This flexibility is essential, as each asset class or market may require different parameter settings.
⭐ 6. Practical Application in Trading:
Entry and Exit Signals: The script can be used to generate entry and exit signals. For instance:
Buy Signal: When the bar turns green (price is above Supertrend and SAR), it could be a signal to go long.
Sell Signal: When the bar turns red (price is below Supertrend and SAR), it could be a signal to go short or exit a long position.
Stop-Loss Placement: The Parabolic SAR dots can act as trailing stop-loss levels, helping traders lock in profits as trends progress.
Trend Continuation vs. Reversal: The Supertrend provides a broader view of the trend, while the Parabolic SAR provides pinpoint entry/exit signals for reversals.
🚀 Conclusion:
This script is a robust combination of trend-following and reversal indicators, making it a versatile tool for traders. The dual confirmation from Supertrend and Parabolic SAR reduces false signals, and the color-coded bars provide quick insights into market conditions. When used properly, this can greatly improve your ability to catch trends early, exit at the right moment, and manage risk effectively.
In den Scripts nach "reversal" suchen
Lsma For Loop | viResearchLsma For Loop | viResearch
Conceptual Foundation and Innovation
The "Lsma For Loop" indicator offers a unique combination of the Least Squares Moving Average (LSMA) with a dynamic scoring system based on a loop function. By comparing the current LSMA value with historical values over a user-defined range, this indicator generates a detailed score that helps detect trend strength and potential reversals. This approach provides traders with a more nuanced analysis of price action, allowing them to identify trends earlier and with more accuracy.
The LSMA, which minimizes lag compared to traditional moving averages, is ideal for detecting trends as it provides a smooth and quick-to-respond line. When combined with the loop-based scoring system, traders can benefit from a powerful tool for analyzing market momentum and capturing profitable trends.
Technical Composition and Calculation
The "Lsma For Loop" script features two essential components:
Least Squares Moving Average (LSMA): The LSMA is calculated over a user-defined length using a linear regression model. It provides a smooth line that follows price trends more closely, reducing the noise that is often present in simple moving averages.
For Loop Scoring System: This system evaluates the LSMA over a range of previous values, generating a score based on whether the current LSMA is higher or lower than its previous values within the specified range. The resulting score reflects the strength of the trend, with higher scores indicating a stronger uptrend and lower scores signaling a downtrend.
Key Calculations:
LSMA Calculation: The LSMA is derived from the closing price over the selected period (len), providing a smooth moving average that fits the price data closely.
For Loop Scoring:
The loop iterates over a range of previous LSMA values, comparing the current LSMA to each past value.
If the current LSMA is higher than a previous value, a positive score is added; if it is lower, a negative score is added. The sum of these comparisons forms the overall score.
Features and User Inputs
The "Lsma For Loop" script offers a range of customization options, allowing traders to tailor the indicator to their specific trading strategies and market conditions:
LSMA Length: Adjust the length of the LSMA, controlling the smoothness of the indicator and how quickly it reacts to price changes.
Loop Range (From and To): Define the range over which the for loop evaluates LSMA values. This provides flexibility in assessing momentum over different timeframes.
Thresholds: Customizable threshold levels are used to define when the score indicates an uptrend or downtrend. This allows traders to fine-tune the sensitivity of the indicator to market movements.
Practical Applications
The "Lsma For Loop" is a versatile tool for traders who want to leverage the advantages of LSMA smoothing while gaining a more detailed view of trend strength. This indicator is particularly useful for:
Identifying Trend Reversals: The loop-based scoring system provides an early indication of potential trend reversals, allowing traders to react before major market movements.
Confirming Trend Strength: By evaluating the LSMA against a range of previous values, the script helps confirm whether a trend is strengthening or weakening.
Enhanced Market Positioning: The customizable range and thresholds enable traders to adapt the script to different market conditions, whether they are day trading or swing trading.
Advantages and Strategic Value
The primary advantage of the "Lsma For Loop" script lies in its ability to provide a more granular analysis of LSMA behavior through the use of the for loop. This dynamic approach reduces the likelihood of false signals and offers greater accuracy in detecting trends. The indicator’s versatility makes it a valuable tool for both short-term and long-term trading strategies.
Alerts and Visual Cues
The script includes built-in alert conditions to notify traders of key trend changes:
Lsma For Loop Long: Indicates a potential upward trend when the score exceeds the upper threshold.
Lsma For Loop Short: Signals a potential downward trend when the score falls below the lower threshold.
Additionally, visual cues such as background color changes highlight when the score crosses certain key levels, providing an easy-to-read representation of market trends directly on the chart.
Summary and Usage Tips
The "Lsma For Loop | viResearch" indicator provides traders with a powerful tool that combines LSMA smoothing with a dynamic loop-based scoring system for trend detection. Incorporating this script into your trading strategy can help improve trend identification and enhance decision-making around entries and exits. Whether you are trading in trending markets or looking for early reversal signals, this script offers a reliable and flexible solution.
Note: Backtests are based on past results and are not indicative of future performance.
Uptrick: Momentum Channel Indicator
### 🌟 **Uptrick: Momentum Channel Indicator (MC_Ind)** 🌟
The **"Uptrick: Momentum Channel Indicator"** is a powerful tool designed to help traders gauge market momentum and identify potential overbought or oversold conditions. Whether you're a day trader, swing trader, or long-term investor, this indicator can be your compass 🧭 in the complex world of trading.
### 🎯 **Purpose of the Indicator**
The primary goal of the **Momentum Channel Indicator** is to measure the deviation of price from its moving average (the mid-point) and to smooth this deviation to identify momentum shifts. By plotting overbought and oversold levels, the indicator helps traders spot potential reversal points where the market might change direction, offering valuable entry or exit signals.
### 🔧 **Inputs & Parameters**
Let's break down the input parameters that you can adjust to tailor the indicator to your trading style:
1. **`length1` (Channel Length) 📏**: This is the period over which the moving average (mid-point) and price deviation are calculated. The default value is 14, meaning the last 14 bars are considered for calculations.
2. **`length2` (Smoothing Length) 🧘**: This parameter controls the smoothing of the channel index, with a default value of 28. The higher the value, the smoother the momentum line, reducing noise and making trends more visible.
3. **`overbought1` & `overbought2` (Overbought Levels) 🔴**: These levels, set at 70 and 65 by default, represent the threshold above which the market is considered overbought, potentially signaling a selling opportunity.
4. **`oversold1` & `oversold2` (Oversold Levels) 🟢**: Similarly, these levels, set at -70 and -65, mark the threshold below which the market is considered oversold, indicating a potential buying opportunity.
### 🛠️ **How the Indicator Works**
Now, let's dive into the mechanics of the Momentum Channel Indicator:
1. **Mid-Point Calculation 🏁**: The mid-point is calculated using a simple moving average (SMA) of the closing prices over the `length1` period. This mid-point acts as a reference line from which deviations are measured.
2. **Price Deviation 📊**: The price deviation is the absolute difference between the closing price and the mid-point, smoothed over the same period (`length1`). This represents the typical price movement away from the mid-point.
3. **Channel Index 📉**: The channel index is calculated by dividing the price deviation by a fraction (0.01) of the mid-point, providing a normalized measure of how far the price has deviated from the average.
4. **Smoothing of the Channel Index 🌊**: The smoothed index (`mci1`) is calculated by applying a smoothing filter (SMA) over the channel index using the `length2` parameter. This helps reduce noise and highlight the true momentum of the market.
5. **Momentum Lines 📈**:
- **`mci1`**: The main momentum line, representing the smoothed channel index.
- **`mci2`**: A secondary momentum line, which is a further smoothed version of `mci1` using a 6-period SMA.
6. **Signal Lines 🚦**:
- **Overbought & Oversold Levels**: Horizontal lines plotted at `overbought1`, `overbought2`, `oversold1`, and `oversold2` levels serve as visual cues for overbought and oversold conditions.
- **Zero Line**: A central reference line at 0, indicating neutral momentum.
### 📈 **How to Use the Indicator**
#### 1. **Day Traders ⚡**
For day traders, the Momentum Channel Indicator can be a quick signal generator for short-term trades. Here's how you can use it:
- **Identify Entry Points 🎯**: Look for a **bullish crossover** when `mci1` crosses above `mci2` from below the `oversold1` level. This signals a potential upward reversal.
- **Spot Exit Points 🏁**: Watch for a **bearish crossunder** when `mci1` crosses below `mci2` from above the `overbought1` level. This could indicate a downward reversal.
- **Scalping 🔄**: In a fast-moving market, use the indicator to scalp by entering and exiting trades at these crossover points, with a tight stop-loss strategy.
#### 2. **Swing Traders 🎢**
Swing traders benefit from using the Momentum Channel Indicator to identify potential reversal points over a longer period:
- **Trend Confirmation 📊**: Use the smoothing effect of `mci2` to confirm trends. If `mci2` remains consistently above 0, it indicates a strong bullish trend, and vice versa.
- **Overbought/Oversold Reversals 🚀**: Enter trades when the price approaches the overbought or oversold levels (`overbought1`, `oversold1`). Combine this with other indicators, such as RSI, for more reliable signals.
- **Hold Positions 🧗**: Let the momentum lines guide your hold strategy. If the momentum lines stay aligned (both `mci1` and `mci2` are moving in the same direction), consider holding the position until a crossover or reversal signal appears.
#### 3. **Long-Term Investors 🏦**
For long-term investors, the Momentum Channel Indicator helps in fine-tuning entry and exit points based on broader market momentum:
- **Divergence Analysis 📐**: Look for divergence between the price and the momentum lines. If the price makes new highs but the momentum lines do not, it could signal a weakening trend and a potential reversal.
- **Strategic Entry/Exit 🏹**: Use the `overbought2` and `oversold2` levels to strategically enter or exit positions. These secondary levels provide an early warning before the market reaches extreme conditions.
- **Risk Management 🛡️**: The indicator can also be used as part of a risk management strategy by identifying when to reduce exposure in overbought markets or increase exposure in oversold markets.
### 🖼️ **Visualization & Interpretation**
The Momentum Channel Indicator is visually intuitive, with each component providing key insights:
1. **Momentum Lines (MCI1 & MCI2) 📈**:
- **Blue Line (`mci1`)**: Represents the main momentum line, providing immediate insights into market direction.
- **Orange Line (`mci2`)**: A secondary momentum line, further smoothed to confirm trends.
2. **Overbought/Oversold Levels 🔴🟢**:
- **Solid & Dashed Lines**: These lines highlight overbought and oversold regions, guiding traders on when to consider entering or exiting trades.
3. **MCI Difference (Purple Area) 🌌**:
- **Shaded Area**: The difference between `mci1` and `mci2`, shaded in purple, helps visualize the strength of the momentum. The larger the shaded area, the stronger the momentum.
### 🚀 **Advanced Tips & Tricks**
For those looking to maximize the potential of the Momentum Channel Indicator, here are some advanced strategies:
1. **Combine with Volume Indicators 📊**: Use volume indicators like OBV (On-Balance Volume) or Volume Oscillator to confirm momentum signals. For instance, a bullish crossover combined with increasing volume can reinforce a buy signal.
2. **Multiple Timeframe Analysis 🕒**: Apply the Momentum Channel Indicator across multiple timeframes (e.g., daily and weekly) to get a more comprehensive view of the market. This can help in aligning short-term trades with long-term trends.
3. **Adjusting Parameters 🔄**: Depending on market conditions, tweak the `length1` and `length2` parameters. In a highly volatile market, shorter lengths might provide quicker signals, whereas in a stable market, longer lengths could smooth out noise.
4. **Divergence & Convergence 📐**: Watch for divergence between price and momentum lines as a leading indicator of potential reversals. Convergence (when the price and momentum move in sync) can confirm the strength of the trend.
### **Conclusion**
The **Uptrick: Momentum Channel Indicator** is a versatile tool that can be customized for various trading styles and market conditions. Whether you're trading in fast-paced environments or analyzing long-term trends, this indicator offers a clear and intuitive way to gauge market momentum, identify potential reversals, and make informed trading decisions.
By understanding and applying the principles outlined above, you can harness the full power of this indicator, transforming your trading strategy from good to great! 🌟
Pulse RSI | Lyro RSPulse RSI | Lyro RS
The Pulse RSI is a momentum oscillator that enhances the traditional RSI by incorporating volume-weighted price and linear regression. It generates multiple trading signals, including trend shifts, overbought/oversold conditions, and custom threshold levels.
By integrating both price and volume into its calculation, Pulse RSI is more robust and responsive than the standard RSI. This helps you identify trends faster, spot potential reversals sooner, and set up custom alerts based on your own strategy.
Key Features
Four Signal Types:
Type 1 (Trend): Triggers when the indicator's current value crosses its previous value, highlighting short-term momentum shifts.
Type 2 (Midline Trend): The classic midline cross. A bullish bias is indicated above 50, while a bearish bias is indicated below 50.
Type 3 (Overbought/Oversold): Flags potential reversal zones, suggesting where buying or selling opportunities may emerge.
Type 4 (Custom Thresholds): This type lets you define your own threshold levels. Instead of following a trend, use it to mark your specific conditions for a reversal. For example, set a long reversal at a low level (e.g., 5) for an early buy signal, or a short reversal at a high level (e.g., 80) for an early sell signal.
Calculation Method:
The indicator uses a volume-weighted price (Close * High * Low) and applies linear regression to smooth the data. This creates a unique and more stable oscillator, avoiding the chaotic movement seen in others.
Color System:
Choose from multiple color themes like Classic, Mystic, Accented, and Royal, or create your own custom colors for bullish and bearish signals.
Visual Plotting:
Features a clear plot with a glow effect, a midline, adjustable threshold lines, and shapes/labels to mark long/short and overbought/oversold signals.
Alerts:
Instant alerts are available for every signal type, which you can quickly enable based on your trading conditions.
How It Works:
Core Calculation
The indicator calculates a volume-weighted price using (Close * High * Low) multiplied by the absolute volume. This value is then smoothed with linear regression and converted into an oscillator, normalized to a 0-100 scale.
Trading Logic:
Bullish Signals: Trigger when the main plot line crosses above a key level—be it the previous value, the 50 midline, or a custom threshold.
Bearish Signals: Trigger when the main plot line crosses below a key level.
Visual Logic:
The system displays a main plot line, colors candles, and plots signal shapes, all customizable through a variety of color schemes.
Practical Use
Trend Confirmation (Types 1 & 2): Use Type 1 for early momentum shifts and Type 2 to confirm the overall trend direction.
Reversals (Type 3): Consider long entries when oversold signals fire, suggesting an asset is undervalued. Look for exits at overbought signals, which suggest a potential downward reversal.
Custom Thresholds (Type 4): Set tight thresholds to catch early trends and reversals. Be aware that more sensitive settings may also increase false positives.
Customization:
Adjust the Length: A higher setting makes the indicator more suited for long-term trends, while a lower setting makes it more sensitive for short-term moves.
Enable/Disable Signals: Turn the four signal types on or off to match your trading style.
Set Your Levels: Fully adjustable thresholds for Type 4 long/short conditions.
Choose Your Colors: Select from a variety of color schemes for all bullish and bearish elements.
⚠️ Disclaimer
This indicator is a tool for technical analysis and does not guarantee results. It should be used alongside other analysis methods and solid risk management practices. The creators are not responsible for any financial decisions made based on its signals.
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Stochastic MACDStochastic MACD Indicator: Quick Guide
This Pine Script indicator, "Stochastic MACD" (SMACD), blends MACD and Stochastic Oscillator principles to help you spot momentum shifts and potential reversals.
What it Shows:
SMACD Line: Tracks momentum.
Signal Line: Averages the SMACD line, creating crossovers.
Histogram: Visualizes momentum strength, changing color with direction.
Overbought/Oversold Levels: (Default 10 and -10) Help identify stretched market conditions. Adjustable in settings.
Visual Signals (Triangles):
Red Down Arrow (Overbought Signal): Appears when both SMACD and Signal lines are above the Overbought level (default 10) AND SMACD crosses the Signal line upwards. This suggests strong overbought conditions and a potential reversal down.
Green Up Arrow (Oversold Signal): Appears when both SMACD and Signal lines are below the Oversold level (default -10) AND SMACD crosses the Signal line upwards. This suggests potential buying opportunities from oversold conditions and a possible reversal up.
How to Use It:
Confirm Trends: Use the histogram and line directions.
Spot Reversals: Look for the red and green triangles for quick alerts.
Combine: Always use with other analysis like price action or support/resistance.
Important: This is an analytical tool, not financial advice. Trading involves risk.
Normalized Volume IndexIn the realm of technical analysis, volume is more than just a measure of market activity—it’s a window into trader psychology. Two classic indicators that harness this insight are the Positive Volume Index (PVI) and Negative Volume Index (NVI). Developed in the early 20th century by Paul L. Dysart and later refined by Norman G. Fosback in 1976, these tools aim to distinguish between the behavior of the so-called “smart money” and the broader market crowd.
- Positive Volume Index (PVI) tracks price changes only on days when trading volume increases. It assumes that rising volume reflects the actions of less-informed retail traders—those who follow the herd.
- Negative Volume Index (NVI), on the other hand, focuses on days when volume decreases, under the premise that institutional investors (the “smart money”) are more active when the market is quiet.
This dichotomy allows traders to interpret market sentiment through the lens of volume behavior. For example, a rising NVI during a price uptrend may suggest that institutional investors are quietly accumulating positions—often a bullish signal.
Traders use PVI and NVI to:
- Confirm trends: If NVI is above its moving average, it often signals a strong underlying trend supported by smart money.
- Spot reversals: Divergences between price and either index can hint at weakening momentum or upcoming reversals.
- Gauge participation: PVI rising faster than price may indicate overenthusiastic retail buying—potentially a contrarian signal.
These indicators are often paired with moving averages (e.g., 255-day EMA) to generate actionable signals. Fosback’s research suggested that when NVI is above its one-year EMA, there’s a high probability of a bull market.
While PVI and NVI are cumulative indices, normalizing them—for example, by rebasing to 100 or converting to percentage changes—offers several benefits:
- Comparability: Normalized indices can be compared across different assets or timeframes.
- Clarity: It becomes easier to visualize relative strength or weakness.
- Backtesting: Normalized values are more suitable for algorithmic strategies and statistical analysis.
Normalization also helps when combining PVI/NVI with other indicators in multi-factor models, ensuring no single metric dominates due to scale differences
In essence, PVI and NVI offer a nuanced view of market dynamics by separating the noise of volume surges from the quiet confidence of institutional moves. When normalized and interpreted correctly, they become powerful allies in a trader’s decision-making toolkit.
How to use this (Educational material):
For instance, on average, when the Negative Volume Index (NVI) remains above its midline, the market tends to trend positively, reflecting consistent institutional participation. However, when the NVI dips and stays below the midline, it often signals a negative trend, indicating that smart money is stepping away or reducing exposure.
Another telling scenario occurs when the Positive Volume Index (PVI) drops below the NVI. While this might coincide with a brief price dip, institutions often interpret this as an opportunity to buy the dip, quietly accumulating positions while retail participants exit in panic. The result? A market recovery driven by smart money.
Conversely, when the PVI consistently remains above the NVI, it may point to retail enthusiasm outpacing institutional support. This imbalance can flag a tired or overextended trend, where the smart money has already positioned itself defensively. When this pattern persists, there's a high likelihood that institutions will pull the plug, leading to a pronounced trend reversal.
MACD of RSI [TORYS]MACD of RSI — Momentum & Divergence Scanner
Description:
This enhanced oscillator applies MACD logic directly to the Relative Strength Index (RSI) rather than price, giving traders a clearer look at internal momentum and early shifts in trend strength. Now featuring a custom histogram, dual MA types, and RSI-based divergence detection — it’s a complete toolkit for identifying exhaustion, acceleration, and hidden reversal points in real time.
How It Works:
Calculates the MACD line as the difference between a fast and slow moving average of RSI. Adds a Signal Line (MA of the MACD) and plots a Histogram to show momentum acceleration/deceleration. Both RSI MAs and the Signal Line can be toggled between EMA and SMA for custom tuning.
Divergence Detection:
Bullish Divergence : Price makes a lower low while RSI makes a higher low → labeled with a green “D” below the curve.
Bearish Divergence : Price makes a higher high while RSI makes a lower high → labeled with a red “D” above the curve.
Configurable lookback window for tuning sensitivity to pivots, with 4 as the sweet spot.
RSI Pivot Dot Signals:
Plots green dots at RSI oversold pivot lows below 30,
Plots red dots at overbought pivot highs above 70.
Helps detect short-term exhaustion or bounce zones, plotted right on the MACD-RSI curve.
RSI 50 Crosses (Optional):
Optional ▲ and ▼ labels when RSI crosses its 50 midline — useful for momentum trend shifts or pullback confirmation, or to detect consolidation.
Histogram:
Plotted as a column chart showing the distance between MACD and Signal Line.
Colored dynamically:
Bright green : Momentum rising above zero
Light green : Weakening above zero
Bright red : Momentum falling below zero
Light red : Weakening below zero
The zero line serves as the mid-point:
Above = Bullish Bias
Below = Bearish Bias
How to Interpret:
Momentum Confirmation:
Use MACD cross above Signal Line with a rising histogram to confirm breakouts or trend entries.
Histogram shrinking near zero = momentum weakening → caution or reversal.
Exhaustion & Reversals:
Dot signals near RSI extremes + histogram peak can suggest overbought/oversold pressure.
Use divergence labels ("D") to spot early reversal signals before price breaks structure.
Inputs & Settings:
RSI Length
Fast/Slow MA Lengths for MACD (applied to RSI)
Signal Line Length
MA Type: Choose between EMA and SMA for MACD and Signal Line
Pivot Sensitivity for dot markers
Divergence Logic Toggle
Show/hide RSI 50 Crosses
Best For:
Traders who want momentum insight from inside RSI, not price
Scalpers using divergence or exhaustion entries
Swing traders seeking entry confirmation from signal crossovers
Anyone using multi-timeframe confluence with RSI and trend filters
Pro Tips:
Combine this with:
Bollinger Bands breakouts and reversals
VWAP or EMAs to filter entries by trend
Volume spikes or BBW squeezes for volatility confirmation
TTM Scalper Alert to sync structure and momentum
Body Percentage of Range (Colored)Short Description:
This indicator measures the dominance of the candle's body relative to its total range (High - Low), providing a visual gauge of intra-candle strength versus indecision. Columns are colored based on whether the body constitutes more or less than a defined percentage (default 50%) of the candle's total height.
Detailed Description:
What it Does:
The "Body Percentage of Range" indicator calculates, for each candle, what percentage of the total price range (High minus Low) is occupied by the candle's body (absolute difference between Open and Close).
A value of 100% means the candle has no wicks (a Marubozu), indicating strong conviction during that period.
A value of 0% means the candle has no body (a Doji), indicating perfect indecision.
Values in between show the relative balance between the directional move (body) and the price exploration/rejection (wicks).
How to Interpret:
The indicator plots this percentage as columns:
Column Height: Represents the percentage of the body relative to the total range. Higher columns indicate a larger body dominance.
Column Color:
Green Columns: Appear when the body percentage is above the user-defined threshold (default 50%). This suggests that the directional move within the candle was stronger than the indecision (wicks). Often seen during trending moves or strong momentum candles.
Red Columns: Appear when the body percentage is at or below the user-defined threshold (default 50%). This suggests that wicks dominate the candle (body is 50% or less of the range), indicating significant indecision, struggle between buyers and sellers, or potential reversals. These are common in choppy, consolidating, or reversal market conditions.
Orange Line (Optional MA): A Simple Moving Average (SMA) of the body percentages is plotted to help smooth the readings and identify broader periods where candle structure indicates more trending (high MA) vs. ranging/indecisive (low MA) characteristics.
Potential Use Cases:
Identifying Choppy vs. Trending Markets: Sustained periods of low, predominantly red columns (and often a low/declining MA) can signal a choppy, range-bound market where trend-following strategies might underperform. Conversely, periods with frequent high, green columns suggest a more trending environment.
Confirming Breakouts/Momentum: High green columns appearing alongside increased volume during a breakout can add conviction to the move's strength.
Spotting Potential Exhaustion/Reversals: A very tall green column after a strong trend, followed immediately by a low red column (like a Doji or Spinning Top pattern appearing on the price chart), might signal potential exhaustion or a pending reversal, indicating indecision has suddenly entered the market.
Filtering Entries: Traders might avoid taking entries (especially trend-following ones) when the indicator shows a consistent pattern of low red columns, suggesting high market indecision.
Settings:
Color Threshold %: Allows you to set the percentage level above which columns turn green (default is 50%).
Smoothing MA Length: Adjusts the lookback period for the Simple Moving Average.
Disclaimer:
This indicator is a tool for technical analysis and should be used in conjunction with other methods (like price action, volume analysis, other indicators) and robust risk management. It does not provide direct buy/sell signals and past performance is not indicative of future results.
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
Neural Pulse System [Alpha Extract]Neural Pulse System (NPS)
The Neural Pulse System (NPS) is a custom technical indicator that analyzes price action through a probabilistic lens, offering a dynamic view of bullish and bearish tendencies.
Unlike traditional binary classification models, NPS employs Ordinary Least Squares (OLS) regression with dynamically computed coefficients to produce a smooth probability output ranging from -1 to 1.
Paired with ATR-based bands, this indicator provides an intuitive and volatility-aware approach to trend analysis.
🔶 CALCULATION
The Neural Pulse System utilizes OLS regression to compute probabilities of bullish or bearish price action while incorporating ATR-based bands for volatility context:
Dynamic Coefficients: Coefficients are recalculated in real-time and scaled up to ensure the regression adapts to evolving market conditions.
Ordinary Least Squares (OLS): Uses OLS regression instead of gradient descent for more precise and efficient coefficient estimation.
ATR Bands: Smoothed Average True Range (ATR) bands serve as dynamic boundaries, framing the regression within market volatility.
Probability Output: Instead of a binary result, the output is a continuous probability curve (-1 to 1), helping traders gauge the strength of bullish or bearish momentum.
Formula:
OLS Regression = Line of best fit minimizing squared errors
Probability Signal = Transformed regression output scaled to -1 (bearish) to 1 (bullish)
ATR Bands = Smoothed Average True Range (ATR) to frame price movements within market volatility
🔶 DETAILS
📊 Visual Features:
Probability Curve: Smooth probability signal ranging from -1 (bearish) to 1 (bullish)
ATR Bands: Price action is constrained within volatility bands, preventing extreme deviations
Color-Coded Signals:
Blue to Green: Increasing probability of bullish momentum
Orange to Red: Increasing probability of bearish momentum
Interpretation:
Bullish Bias: Probability output consistently above 0 suggests a bullish trend.
Bearish Bias: Probability output consistently below 0 indicates bearish pressure.
Reversals: Extreme values near -1 or 1, followed by a move toward 0, may signal potential trend reversals.
🔶 EXAMPLES
📌 Trend Identification: Use the probability output to gauge trend direction.
📌Example: On a 1-hour chart, NPS moves from -0.5 to 0.8 as price breaks resistance, signaling a bullish trend.
Reversal Signals: Watch for probability extremes near -1 or 1 followed by a reversal toward 0.
Example: NPS hits 0.9, price touches the upper ATR band, then both retreat—indicating a potential pullback.
📌 Example snapshots:
Volatility Context: ATR bands help assess whether price action aligns with typical market conditions.
Example: During low volatility, the probability signal hovers near 0, and ATR bands tighten, suggesting a potential breakout.
🔶 SETTINGS
Customization Options:
ATR Period – Defines lookback length for ATR calculation (shorter = more responsive, longer = smoother).
ATR Multiplier – Adjusts band width for better volatility capture.
Regression Length – Controls how many bars feed into the coefficient calculation (longer = smoother, shorter = more reactive).
Scaling Factor – Adjusts the strength of regression coefficients.
Output Smoothing – Option to apply a moving average for a cleaner probability curve
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Uptrick Signal Density Cloud🟪 Introduction
The Uptrick Signal Density Cloud is designed to track market direction and highlight potential reversals or shifts in momentum. It plots two smoothed lines on the chart and fills the space between them (often called a “cloud”). The bars on the chart change color depending on bullish or bearish conditions, and small triangles appear when certain reversal criteria are met. A metrics table displays real-time values for easy reference.
🟩 Why These Features Have Been Linked Together
1) Dual-Line Structure
Two separate lines represent shorter- and longer-term market tendencies. Linking them in one tool allows traders to view both near-term changes and the broader directional bias in a single glance.
2) Smoothed Averages
The script offers multiple smoothing methods—exponential, simple, hull, and an optimized approach—to reduce noise. Using more than one type of moving average can help balance responsiveness with stability.
3) Density Cloud Concept
Shading the region between the two lines highlights the gap or “thickness.” A wider gap typically signals stronger momentum, while a narrower gap could indicate a weakening trend or potential market indecision. When the cloud is too wide and crosses a certain threshold defined by the user, it indicates a possible reversal. When the cloud is too narrow it may indicate a potential breakout.
🟪 Why Use This Indicator
• Trend Visibility: The color-coded lines and bars make it easier to distinguish bullish from bearish conditions.
• Momentum Tracking: Thicker cloud regions suggest stronger separation between the faster and slower lines, potentially indicating robust momentum.
• Possible Reversal Alerts: Small triangles appear within thick zones when the indicator detects a crossover, drawing attention to key moments of potential trend change.
• Quick Reference Table: A metrics table shows line values, bullish or bearish status, and cloud thickness without needing to hover over chart elements.
🟩 Inputs
1) First Smoothing Length (length1)
Default: 14
Defines the lookback period for the faster line. Lower values make the line respond more quickly to price changes.
2) Second Smoothing Length (length2)
Default: 28
Defines the lookback period for the slower line or one of the moving averages in optimized mode. It generally responds more slowly than the faster line.
3) Extra Smoothing Length (extraLength)
Default: 50
A medium-term period commonly seen in technical analysis. In optimized mode, it helps add broader perspective to the combined lines.
4) Source (source)
Default: close
Specifies the price data (for example, open, high, low, or a custom source) used in the calculations.
5) Cloud Type (cloudType)
Options: Optimized, EMA, SMA, HMA
Determines the smoothing method used for the lines. “Optimized” blends multiple exponential averages at different lengths.
6) Cloud Thickness Threshold (thicknessThreshold)
Default: 0.5
Sets the minimum separation between the two lines to qualify as a “thick” zone, indicating potentially stronger momentum.
🟪 Core Components
1) Faster and Slower Lines
Each line is smoothed according to user preferences or the optimized technique. The faster line typically reacts more quickly, while the slower line provides a broader overview.
2) Filled Density Cloud
The space between the two lines is filled to visualize in which direction the market is trending.
3) Color-Coded Bars
Price bars adopt bullish or bearish colors based on which line is on top, providing an immediate sense of trend direction.
4) Reversal Triangles
When the cloud is thick (exceeding the threshold) and the lines cross in the opposite direction, small triangles appear, signaling a possible market shift.
5) Metrics Table
A compact table shows the current values of both lines, their bullish/bearish statuses, the cloud thickness, and whether the cloud is in a “reversal zone.”
🟩 Calculation Process
1) Raw Averages
Depending on the mode, standard exponential, simple, hull, or “optimized” exponential blends are calculated.
2) Optimized Averages (if selected)
The faster line is the average of three exponential moving averages using length1, length2, and extraLength.
The slower line similarly uses those same lengths multiplied by 1.5, then averages them together for broader smoothing.
3) Difference and Threshold
The absolute gap between the two lines is measured. When it exceeds thicknessThreshold, the cloud is considered thick.
4) Bullish or Bearish Determination
If sma1 (the faster line) is above sma2 (the slower line), conditions are deemed bullish; otherwise, they are bearish. This distinction is reflected in both bar colors and cloud shading.
5) Reversal Markers
In thick zones, a crossover triggers a triangle at the point of potential reversal, alerting traders to a possible trend change.
🟪 Smoothing Methods
1) Exponential (EMA)
Prioritizes recent data for quicker responsiveness.
2) Simple (SMA)
Takes a straightforward average of the chosen period, smoothing price action but often lagging more in volatile markets.
3) Hull (HMA)
Employs a specialized formula to reduce lag while maintaining smoothness.
4) Optimized (Blended Exponential)
Combines multiple EMA calculations to strike a balance between responsiveness and noise reduction.
🟩 Cloud Logic and Reversal Zones
Cloud thickness above the defined threshold typically signals exceeding momentum and can lead to a quick reversal. During these thick periods, if the width exceeds the defined threshold, small triangles mark potential reversal points. In order for the reversal shape to show, the color of the cloud has to be the opposite. So, for example, if the cloud is bearish, and exceeds momentum, defined by the user, a bullish signal appears. The opposite conditions for a bullish signal. This approach can help traders focus on notable changes rather than minor oscillations.
🟪 Bar Coloring and Layered Lines
Bars take on bullish or bearish tints, matching the faster line’s position relative to the slower line. The lines themselves are plotted multiple times with varying opacities, creating a layered, glowing look that enhances visibility without affecting calculations.
🟩 The Metrics Table
Located in the top-right corner of the chart, this table displays:
• SMA1 and SMA2 current values.
• Bullish or bearish alignment for each line.
• Cloud thickness.
• Reversal zone status (in or out of zone).
This numeric readout allows for a quick data check without hovering over the chart.
🟪 Why These Specific Moving Average Lengths Are Used
Default lengths of 14, 28, and 50 are common in technical analysis. Fourteen captures near-term price movement without overreacting. Twenty-eight, roughly double 14, provides a moderate smoothing level. Fifty is widely regarded as a medium-term benchmark. Multiplying each length by 1.5 for the slower line enhances separation when combined with the faster line.
🟩 Originality and Usefulness
• Multi-Layered Smoothing. The user can select from several moving average modes, including a unique “optimized” blend, possibly reducing random fluctuations in the market data.
• Combined Visual and Numeric Clarity. Bars, clouds, and a real-time table merge into a single interface, enabling efficient trend analysis.
• Focus on Significant Shifts. Thick cloud zones and triangles draw attention to potentially stronger momentum changes and plausible reversals.
• Flexible Across Markets. The adjustable lengths and threshold can be tuned to different asset classes (stocks, forex, commodities, crypto) and timeframes.
By integrating multiple technical concepts—cloud-based trend detection, color coding, reversal markers, and an immediate reference table—the Uptrick Signal Density Cloud aims to streamline chart reading and decision-making.
🟪 Additional Considerations
• Timeframes. Intraday, daily, and weekly charts each yield different signals. Adjust the smoothing lengths and threshold to suit specific trading horizons.
• Market Types. Though applicable across asset classes, parameters might need tweaking to address the volatility of commodities, forex pairs, or cryptocurrencies.
• Confirmation Tools. Pairing this indicator with volume studies or support/resistance analysis can improve the reliability of signals.
• Potential Limitations. No indicator is foolproof; sudden market shifts or choppy conditions may reduce accuracy. Cautious position sizing and risk management remain essential.
🟩 Disclaimers
The Uptrick Signal Density Cloud relies on historical price data and may lag sudden moves or provide false positives in ranging conditions. Always combine it with other analytical techniques and sound risk management. This script is offered for educational purposes only and should not be considered financial advice.
🟪 Conclusion
The Uptrick Signal Density Cloud blends trend identification, momentum assessment, and potential reversal alerts in a single, user-friendly tool. With customizable smoothing methods and a focus on cloud thickness, it visually highlights important market conditions. While it cannot guarantee predictive accuracy, it can serve as a comprehensive reference for traders seeking both a quick snapshot of the current trend and deeper insights into market dynamics.
Salience Theory Crypto Returns (AiBitcoinTrend)The Salience Theory Crypto Returns Indicator is a sophisticated tool rooted in behavioral finance, designed to identify trading opportunities in the cryptocurrency market. Based on research by Bordalo et al. (2012) and extended by Cai and Zhao (2022), it leverages salience theory—the tendency of investors, particularly retail traders, to overemphasize standout returns.
In the crypto market, dominated by sentiment-driven retail investors, salience effects are amplified. Attention disproportionately focused on certain cryptocurrencies often leads to temporary price surges, followed by reversals as the market stabilizes. This indicator quantifies these effects using a relative return salience measure, enabling traders to capitalize on price reversals and trends, offering a clear edge in navigating the volatile crypto landscape.
👽 How the Indicator Works
Salience Measure Calculation :
👾 The indicator calculates how much each cryptocurrency's return deviates from the average return of all cryptos over the selected ranking period (e.g., 21 days).
👾 This deviation is the salience measure.
👾 The more a return stands out (salient outcome), the higher the salience measure.
Ranking:
👾 Cryptos are ranked in ascending order based on their salience measures.
👾 Rank 1 (lowest salience) means the crypto is closer to the average return and is more predictable.
👾 Higher ranks indicate greater deviation and unpredictability.
Color Interpretation:
👾 Green: Low salience (closer to average) – Trending or Predictable.
👾 Red/Orange: High salience (far from average) – Overpriced/Unpredictable.
👾 Text Gradient (Teal to Light Blue): Helps visualize potential opportunities for mean reversion trades (i.e., cryptos that may return to equilibrium).
👽 Core Features
Salience Measure Calculation
The indicator calculates the salience measure for each cryptocurrency by evaluating how much its return deviates from the average market return over a user-defined ranking period. This measure helps identify which assets are trending predictably and which are likely to experience a reversal.
Dynamic Ranking System
Cryptocurrencies are dynamically ranked based on their salience measures. The ranking helps differentiate between:
Low Salience Cryptos (Green): These are trending or predictable assets.
High Salience Cryptos (Red): These are overpriced or deviating significantly from the average, signaling potential reversals.
👽 Deep Dive into the Core Mathematics
Salience Theory in Action
Salience theory explains how investors, particularly in the crypto market, tend to prefer assets with standout returns (salient outcomes). This behavior often leads to overpricing of assets with high positive returns and underpricing of those with standout negative returns. The indicator captures these deviations to anticipate mean reversions or trend continuations.
Salience Measure Calculation
// Calculate the average return
avgReturn = array.avg(returns)
// Calculate salience measure for each symbol
salienceMeasures = array.new_float()
for i = 0 to array.size(returns) - 1
ret = array.get(returns, i)
salienceMeasure = math.abs(ret - avgReturn) / (math.abs(ret) + math.abs(avgReturn) + 0.1)
array.push(salienceMeasures, salienceMeasure)
Dynamic Ranking
Cryptos are ranked in ascending order based on their salience measures:
Low Ranks: Cryptos with low salience (predictable, trending).
High Ranks: Cryptos with high salience (unpredictable, likely to revert).
👽 Applications
👾 Trend Identification
Identify cryptocurrencies that are currently trending with low salience measures (green). These assets are likely to continue their current direction, making them good candidates for trend-following strategies.
👾 Mean Reversion Trading
Cryptos with high salience measures (red to light blue) may be poised for a mean reversion. These assets are likely to correct back towards the market average.
👾 Reversal Signals
Anticipate potential reversals by focusing on high-ranked cryptos (red). These assets exhibit significant deviation and are prone to price corrections.
👽 Why It Works in Crypto
The cryptocurrency market is dominated by retail investors prone to sentiment-driven behavior. This leads to exaggerated price movements, making the salience effect a powerful predictor of reversals.
👽 Indicator Settings
👾 Ranking Period : Number of bars used to calculate the average return and salience measure.
Higher Values: Smooth out short-term volatility.
Lower Values: Make the ranking more sensitive to recent price movements.
👾 Number of Quantiles : Divide ranked assets into quantile groups (e.g., quintiles).
Higher Values: More detailed segmentation (deciles, percentiles).
Lower Values: Broader grouping (quintiles, quartiles).
👾 Portfolio Percentage : Percentage of the portfolio allocated to each selected asset.
Enter a percentage (e.g., 20 for 20%), automatically converted to a decimal (e.g., 0.20).
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
MultiLayer Acceleration/Deceleration Strategy [Skyrexio]Overview
MultiLayer Acceleration/Deceleration Strategy leverages the combination of Acceleration/Deceleration Indicator(AC), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Acceleration/Deceleration Indicator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Acceleration/Deceleration shall create one of two types of long signals (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created long signal.
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one long signal, another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about Acceleration/Deceleration signals. AC indicator is calculated using the Awesome Oscillator, so let's first of all briefly explain what is Awesome Oscillator and how it can be calculated. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO), where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now we can explain which AC signal types are used in this strategy. The first type of long signal is when AC value is below zero line. In this cases we need to see three rising bars on the histogram in a row after the falling one. The second type of signals occurs above the zero line. There we need only two rising AC bars in a row after the falling one to create the signal. The signal bar is the last green bar in this sequence. The strategy places the buy stop order one tick above the candle's high, which corresponds to the signal bar on AC indicator.
After that we can have the following scenarios:
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower high. If current AC bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AC bar become decreasing. In the second case buy order cancelled and strategy wait for the next AC signal.
If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. All open trades are closed when the trend shifts to a downtrend, as determined by the combination of the Alligator and Fractals described earlier.
Why we use AC signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC bars after period of falling AC bars indicates the high probability of local pull back end and there is a high chance to open long trade in the direction of the most likely main uptrend. The numbers of rising bars are different for the different AC values (below or above zero line). This is needed because if AC below zero line the local downtrend is likely to be stronger and needs more rising bars to confirm that it has been changed than if AC is above zero.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next AC signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.15%
Maximum Single Profit: +24.57%
Net Profit: +2108.85 USDT (+21.09%)
Total Trades: 111 (36.94% win rate)
Profit Factor: 2.391
Maximum Accumulated Loss: 367.61 USDT (-2.97%)
Average Profit per Trade: 19.00 USDT (+1.78%)
Average Trade Duration: 75 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Easy CotHow to Use the Commitment of Traders (COT) Report for Market Analysis
The Commitment of Traders (COT) report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that breaks down the open interest in various futures markets. It categorizes traders into three main groups: Commercials, Non-Commercials, and Retail Traders (Non-Reportable positions). Understanding and analyzing the COT report can provide insights into market sentiment and potential reversals, especially in commodity, currency, and stock index futures.
Key Components of the COT Report
Commercials (Hedgers)
These are entities involved in the production or consumption of the underlying asset. For example, oil producers might hedge by selling oil futures to lock in prices, while airlines might buy futures to hedge against rising prices.
Commercials typically act as hedgers, so their positions can indicate the need for protection rather than speculative intent. Because they are less price-sensitive, their positions are usually opposite to the trend near market reversals.
Non-Commercials (Large Speculators)
This group includes hedge funds, asset managers, and large traders who take speculative positions to profit from price movements.
Non-Commercials are often trend-followers, meaning they increase long positions in an uptrend and short positions in a downtrend. When Non-Commercials become extremely bullish or bearish, it may signal a potential market reversal.
Retail Traders (Non-Reportable Positions)
These are smaller individual traders whose positions are too small to be reported individually.
Retail traders tend to be less experienced and are often on the wrong side of major market moves, so extreme positions by retail traders can sometimes signal a market turning point.
How to Interpret the COT Data
1. Identify Extreme Positions
Extreme Long or Short Positions: When a group reaches a historically extreme level of long or short positions, it often signals a potential reversal. For instance, if Non-Commercials are overwhelmingly long, it may indicate that the uptrend is overextended, and a reversal could be near.
Contrarian Indicator: Since Retail Traders are often on the wrong side, you may look for signals where they are extremely long or short, indicating a possible reversal in the opposite direction.
2. Look for Divergences
Divergence Between Groups: If Non-Commercials (speculators) and Retail Traders are moving in opposite directions, it could indicate that a trend is losing momentum and a reversal is possible.
Commercials vs. Non-Commercials: Commercials are often positioned opposite to Non-Commercials. If there’s a divergence where Non-Commercials are highly bullish, but Commercials are increasingly bearish, it might suggest a coming reversal.
3. Trend Confirmation and Reversal Signals
Trend Confirmation: If both Non-Commercials and Retail Traders are aligned in one direction, it might confirm the trend. However, keep in mind that such alignment may signal the later stages of a trend.
Reversal Signals: Look for signs when Non-Commercials are reaching a peak in one direction while Retail Traders peak in the opposite. Such situations can often indicate that the current trend is close to exhaustion.
Using the COT Report in Trading Strategies
Contrarian Trading Strategy
Extreme Positions as Reversal Signals: Use COT data to identify extreme positions. For instance, if Non-Commercials have a very high long position in a commodity, it might suggest that a bullish trend is overextended and a bearish reversal could be near.
Retail Trader Extremes: If Retail Traders are heavily long or short, consider taking the opposite position once you have additional confirmation signals (e.g., technical indicators).
Following the Trend with Large Speculators
Non-Commercials tend to be trend-followers, so if you see them increasingly long (or short) on an asset, it could be a signal to follow the trend until extreme levels are reached.
Using Divergences for Entry and Exit Points
Entry: If Non-Commercials are long, but Retail Traders are heavily short, consider entering a long position as it may confirm the trend.
Exit: If Non-Commercials begin to reduce their positions while Retail Traders increase theirs, it might be time to consider exiting, as the trend could be losing momentum.
