RoC Momentum CycleRoC Momentum Cycles (RMC) is derived from RoC (Rate of Change) indicator.
Motivation behind RMC: Addressing RoC’s Shortcomings
While the Rate of Change (RoC) indicator is a valuable tool for assessing momentum, it has notable limitations that traders must be aware of. One of the primary challenges with the traditional RoC is its sensitivity to price fluctuations, which can lead to false signals in volatile markets. This often results in premature entries or exits, impacting trading performance.
By smoothing out the RoC calculations and focusing on more consistent signal generation (using SMA on smoothed RoC), RMC offers a more consistent representation of price trends.
Momentum Cycles
RMC helps visualize momentum cycles in a much better way compared to RoC.
Long Momentum Cycle : A cross-over of smoothed RoC (blue line) above averaged signal (orange line) below zero marks start of a new potential upside cycle which ends when the blue line comes back to zero line from above.
Short Momentum Cycle : A cross-under of blue line below orange line above zero marks beginning of a potential downside cycle which ends when the blue line comes back to zero from below.
Oscylatory skupione
Normalized ZScoreThe Normalized ZScore Indicator is a dynamic tool designed to help traders identify potential overbought and oversold conditions in the market. It calculates the ZScore of the price movement relative to a moving average, allowing users to track the deviation of price from its average and normalize it within a fixed range for clearer signal generation. The indicator can be used for both trend-following and mean-reversion strategies, offering customizable options for various trading styles.
How It Works
This indicator works by calculating two distinct ZScores:
Standard ZScore: Based on the price deviation from a simple moving average (SMA).
Fast ZScore: Calculated using price deviation from the SMA combined with standard deviation over a shorter period.
The ZScore values are normalized between -100 and 100, allowing for consistent and comparable signal outputs across different assets and timeframes.
Key Features
Customizable MA and Deviation Lengths: Adjust the length of the moving average (MA Length) and deviation (Deviation Length) to suit your trading needs.
Overbought/Oversold Zones: The indicator highlights areas where the market may be overbought or oversold using a user-defined threshold.
Color-Coded Signals: The ZScore plot changes color based on market conditions:
Positive ZScore (overbought) = Customizable Positive Color
Neutral ZScore = Customizable Middle Color
Negative ZScore (oversold) = Customizable Negative Color
Trend Filtering Option: The built-in trend filter helps to enhance signal accuracy by factoring in the overall market trend.
Signal Shapes:
Diamonds: Indicate strong long or short entry signals when ZScore crosses predefined thresholds.
X-Crosses: Indicate weaker long or short entry signals for users preferring caution in their trades.
Inputs
MA Length: Set the length of the moving average used for calculating the ZScore.
Deviation Length: Set the length used for deviation calculations.
OBS Threshold: Set the threshold for defining overbought and oversold zones.
Trend Filter: Enable or disable the trend filter for added signal confidence.
Color Settings: Customize the colors for positive, middle, and negative ZScore values.
Visual Features
ZScore Plot: A smooth and color-coded line plot to visualize the ZScore in real-time.
Overbought/Oversold Zones: Visualized with horizontal lines and fill colors to highlight extremes.
Bar Coloring: Bars change colors when ZScore exceeds overbought/oversold zones, enhancing visual clarity.
Signal Markers: Diamond or X-shaped markers appear on the chart to indicate potential trade signals.
How to Use
Entry Points: Look for the ZScore to cross into overbought/oversold regions for potential reversal trades. Use the diamonds and X-crosses for long and short entries.
Trend Filter: Enable the trend filter to avoid taking trades against the overall market trend.
Customize Settings: Adjust the lengths and colors to match your specific trading strategy and timeframe.
Donchian Channels Osciliator with MA validationWhat's it all about?
This nifty little tool, the Donchian Channels Oscillator, helps you spot when a stock might be overbought or oversold. It's like a price detective, looking for clues in the historical data to figure out if it's time to buy or sell.
How does it work?
Think of it as a seesaw. When the price is way above the Donchian Channels, it's like the seesaw is tilted too far to one side. That might mean it's time to sell before it falls. On the other hand, if the price is way below the channels, it's like the seesaw is tilted too far to the other side. This could be a good sign to buy, as the price might be ready to bounce back.
Key Points:
Donchian Channels: These are like safety nets. They're calculated based on the highest and lowest prices over a certain period.
Oscillator: This is just a fancy word for a tool that swings back and forth. In this case, it swings between overbought and oversold zones.
EMA-Line: This is a smoothed-out version of the oscillator. It helps you see the overall trend more clearly.
How to Use It:
Add it to your chart: Find it in the indicator search bar.
Adjust settings: You can tweak the length of the Donchian Channels and the offset to fit your trading style.
Watch the swings: When the oscillator goes way up, it might be time to sell. When it goes way down, it might be time to buy. But always use this with other indicators for confirmation.
Remember: This is just a tool, not a magic crystal ball. Don't rely solely on it for trading decisions. Always do your own research and consider other factors.
Happy trading!
Momentum-Based Buy/Sell SignalsBuy Signal:
Triggered when ROC > threshold and the MACD line crosses above the Signal line.
Sell Signal:
Triggered when ROC < threshold and the MACD line crosses below the Signal line.
Visual Elements:
Green labels with "Buy" are displayed below the bars for buy signals.
Red labels with "Sell" are displayed above the bars for sell signals.
The background turns green during a buy signal and red during a sell signal for better visual clarity.
Trend CCITrend CCI (TCCI) Indicator
Description:
The Trend CCI (TCCI) indicator is a unique combination of the Commodity Channel Index (CCI) and the Average True Range (ATR), designed to identify trends and market reversals with a refined sensitivity to price volatility. The indicator plots the CCI, adjusted by an ATR filter, and color-codes the trendline to signal uptrends and downtrends.
How It Works:
This indicator uses the CCI to measure price momentum and an ATR-based filter to smooth out market noise, making it easier to detect significant shifts in the market trend. Key parameters such as the ATR Period, ATR Multiplier, and CCI Period have been carefully chosen to optimize the indicator's performance:
1. ATR Period (default: 18)
The ATR Period determines the number of periods used to calculate the **Average True Range**, which reflects market volatility. In this case, an **ATR Period of 18** has been selected for several reasons:
Balance between responsiveness and noise reduction : A period of 18 strikes a balance between being responsive to recent price movements and filtering out minor fluctuations. Shorter ATR periods might be too reactive, creating false signals, while longer periods might miss shorter-term trends.
Adaptable to various market conditions : An 18-period ATR is suitable for both intraday and swing trading strategies, making it versatile across different time frames.
Standard industry practice : Many traders use ATR settings between 14 and 20 periods as a convention for detecting reliable volatility levels.
2. ATR Multiplier (default: 1.5)
The ATR Multiplier is applied to the ATR value to define how sensitive the indicator is to volatility. In this case, a multiplier of 1.5 has been chosen:
Avoiding whipsaws in low volatility markets: By setting the multiplier to 1.5, the indicator filters out smaller, less significant price movements, reducing the likelihood of whipsaw signals (i.e., false trend reversals during periods of low volatility).
Optimizing signal accuracy: A moderate multiplier like 1.5 ensures that the indicator only generates signals when the price moves a significant distance from the average range. Higher multipliers (e.g., 2.0) may ignore valid opportunities, while lower multipliers (e.g., 1.0) might create too many signals.
Enhancing trend clarity : The multiplier’s role in widening the range allows the indicator to respond more clearly during periods of strong trends, reducing signal noise and false positives.
3. CCI Period (default: 63)
The CCI Period defines the number of periods used to calculate the Commodity Channel Index. A 63-period CCI is selected based on the following considerations:
Smoothing the momentum calculation: A longer period, such as 63, is used to smooth out the CCI and reduce the effects of short-term price fluctuations. This period captures longer-term momentum, making it ideal for identifying more significant market trends.
-Filtering out short-term noise: While shorter CCI periods (e.g., 14 or 20) may be more reactive, they tend to produce more signals, some of which may be false. A 63-period CCI focuses on stronger and more sustained price movements, providing fewer but higher-quality signals.
Adapted to intermediate trading: A 63-period CCI aligns well with traders looking for medium-term trend-following strategies, striking a balance between long-term trend identification and responsiveness to significant price shifts.
How to Use:
Green Area: When the trendline turns green, it signals that the CCI is positive, reflecting upward momentum. This can be interpreted as a buy signal, indicating the potential for long positions or continuing bullish trades.
Red Area: When the trendline turns red, it signals that the CCI is negative, reflecting downward momentum. This can be interpreted as a sell signal, indicating potential short positions or bearish trades.
ATR Filter: The ATR helps reduce false signals by ignoring minor price movements. Traders can adjust the ATR Multiplier to make the indicator more or less sensitive based on market conditions. A lower multiplier (e.g., 1.2) may increase signal frequency, while a higher multiplier (e.g., 2.0) reduces it.
Originality:
The Trend CCI (TCCI) stands out due to its combination of the CCI and ATR. While many indicators simply plot raw CCI values, this script enhances the CCI’s effectiveness by incorporating an ATR-based volatility filter. This ensures that only significant trends trigger signals, making it a more reliable tool in volatile markets. The choice of the ATR period, multiplier, and CCI period ensures a refined balance between trend detection and noise reduction, distinguishing it as a powerful trend-following indicator.
Additionally, the visual aspect—using color-coded trendlines that dynamically shift between green and red—simplifies the interpretation of market trends, offering traders a clear and immediate understanding of trend direction and momentum strength.
Final Recommendations:
Use in Trending Markets The TCCI is most effective in trending markets, where its signals align with broader market momentum. In sideways or low-volatility markets, consider adjusting the ATR multiplier or using other complementary indicators to confirm the signals.
Risk Management: Always integrate robust risk management practices, such as using stop-loss orders and position sizing, to protect against sudden market reversals or periods of heightened volatility.
Adjust for Volatility: Consider the volatility of the asset being traded. In highly volatile assets, a higher ATR multiplier (e.g., 2.0) may be necessary to filter out noise, while in more stable assets, a lower multiplier (e.g., 1.2) might generate earlier signals.
By using the Trend CCI (TCCI) indicator with a deeper understanding of its key parameters, traders can better identify trends, reduce noise, and improve their overall decision-making in the markets.
Good Profits!
E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
E9 MACD
The E9 MACD (Moving Average Convergence Divergence) indicator is a powerful tool used in technical analysis to help traders identify potential buy and sell signals based on price action. It is designed to provide clear visual cues and alerts for trading decisions. Here’s how it applies to price action and its key functionalities:
Key Features and Functionality
MACD Line and Signal Line:
MACD Line: Represents the difference between a fast and a slow moving average of the price. It helps in identifying the momentum of the price movement.
Signal Line: A smoothed average of the MACD Line, used to generate trading signals when the MACD Line crosses above or below it.
Histogram: The histogram shows the difference between the MACD Line and the Signal Line. It visually represents the strength of the trend, with positive values indicating bullish momentum and negative values indicating bearish momentum.
Trend Coloring:
Uptrend: When the MACD Line is above the Signal Line, the bars can be colored green to indicate a potential buying opportunity.
Downtrend: When the MACD Line is below the Signal Line, the bars can be colored red to signal a potential selling opportunity.
Timeframe Flexibility:
The E9 MACD can be adjusted to different timeframes, allowing traders to analyze short-term or long-term trends based on their trading strategy. This flexibility helps in tailoring the indicator’s analysis to different market conditions.
Visual Alerts and Highlights:
The indicator includes options to highlight price bars and background colors when significant crossovers occur, making it easier to spot key trading signals.
Circles can be plotted on the MACD Line to indicate cross events, enhancing visual clarity.
Customizable Appearance:
Traders can customize the appearance of the MACD Line, Signal Line, and Histogram, including color and line width, to suit their personal preferences and improve readability.
Alerts for Trading Signals:
The E9 MACD can generate alerts for crossovers of the MACD Line and Signal Line, helping traders stay informed of potential trading opportunities even when they are not actively monitoring the charts.
Application in Trading
The E9 MACD is particularly useful for:
Identifying potential entry and exit points based on the crossing of the MACD Line and Signal Line.
Gauging the strength of the current trend through the histogram.
Adjusting to different timeframes to align the indicator with various trading strategies, from day trading to long-term investing.
By providing clear visual indicators and alerts, the E9 MACD helps traders make more informed decisions and better understand the momentum and direction of price movements.
TASC 2024.10 Adaptive Oscillator Threshold█ OVERVIEW
This script introduces a more dynamic approach to generating trading signals using the RSI indicator and a threshold that adapts to price trends and dispersion. This methodology comes from Francesco Bufi's article "Overbought/Oversold Oscillators: Useless Or Just Misused" from the October 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
According to Francesco Bufi's observations, an oscillator-based buy signal should have a threshold that varies with the trend direction: higher during uptrends and lower during downtrends. Additionally, the level should decrease as the distance from the price to its mean increases to reduce signals in volatile conditions. Accordingly, Bufi proposes a formula for an adaptive buy level whose value is proportional to the trend (linear regression slope) and inversely proportional to the typical distance between price and its mean (standard deviation). Traders can apply this method to any oscillator to add adaptivity without modifying the oscillator's calculations, as it's simply an adaptive technique for interpreting the calculated values.
This script demonstrates the application of Bufi's Adaptive Threshold (BAT) in a simple RSI-based strategy and allows users to compare its performance to the traditional fixed-threshold approach. Bufi's observations suggest that using the BAT instead of a static threshold can help improve the backtest performance of oscillator-based systems.
█ DISCLAIMER
This strategy script educates users on the trading systems outlined by the TASC article. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script.
Power MarketPower Market Indicator
Description: The Power Market Indicator is designed to help traders assess market strength and make informed decisions for entering and exiting positions. This innovative indicator provides a comprehensive view of the evolution of Simple Moving Averages (SMA) over different periods and offers a clear measure of market strength through a total score.
Key Features:
Multi-Period SMA Analysis:
Calculates Simple Moving Averages (SMA) for 10 different periods ranging from 10 to 100.
Provides detailed analysis by comparing the current closing price with these SMAs.
Market Strength Measurement:
Assesses market strength by calculating a total score based on the relationship between the closing price and the SMAs.
The total score is displayed as a histogram with distinct colors for positive and negative values.
Smoothed Curve for Better View:
A smoothing of the total score is applied using a 5-period Simple Moving Average to represent the overall trend more smoothly.
Dynamic Information Table:
Real-time display of the maximum and minimum values among the SMAs, as well as the difference between these values, providing valuable insights into the variability of moving averages.
Visual Reference Lines:
Horizontal lines at zero, +50, and -50 for easy evaluation of key score levels.
How to Use the Indicator:
Position Entries: Use high positive scores to identify buying opportunities when market strength is strong.
Position Exits: Negative scores may signal market weakness, allowing you to exit positions or wait for a better opportunity.
Data Analysis: The table helps you understand the variability of SMAs, offering additional context for your trading decisions.
This powerful tool provides an in-depth view of market dynamics and helps you navigate your trading strategies with greater confidence. Embrace the Power Market Indicator and optimize your trading decisions today!
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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Ultra Money FlowIntroduction
The Ultra Money Flow script is a technical indicator for analyzing stock trends. It highlights buying and selling power, helping you identify bullish (rising) or bearish (falling) market trends.
Detailed Description
The Ultra Money Flow script calculates and visually displays two main components: Fast and Slow money flow. These components represent short-term and long-term trends, respectively.
Here's how it works:
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Inputs
You can adjust the speed of analysis (Fast Length and Slow Length) and the type of smoothing applied (e.g., Simple Moving Average, Exponential Moving Average).
Choose colors for visualizing the trends, with blue for bullish (positive) and orange for bearish (negative) movements.
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Money Flow Calculation
The script analyzes price changes (delta) over specified periods.
It separates upward price movements (buying power) from downward ones (selling power).
It then calculates the difference between these powers for both Fast and Slow components.
The types of smoothing methods range from traditional ones like the Simple Moving Average (SMA) to advanced ones like the Double Expotential Moving Average (DEMA) or the Triple Exponential Moving Average (TEMA) or the Recursive Moving Average (RMA) or the Weigthend Moving Average (WMA) or the Volume Weigthend Moving Average (VWMA) or Hull Moving Average (HMA).
Very Special ones are the Triple Weigthend Moving Average (TWMA) wich created RedKTrader .
I created the Multi Weigthend Moving Average (MWMA) wich is a simple signal line to the TWMA.
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Divergence
This indicator can show divergence by comparing the direction of price movements with the indicator value.
If the price and the indicator move in opposite directions, you can use these signals to help decide when to buy or sell.
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Auto Scaling
The script adjusts its calculations based on the time frame you are viewing, whether it's minutes, hours, or days, ensuring accurate representation across different time scales.
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Plotting
The script plots the Fast component as a histogram and the Slow component as a line, using the chosen colors to indicate bullish or bearish trends.
The thickness and transparency of these plots give additional clues about the strength of the trend.
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By using this indicator, traders can easily spot shifts in buying and selling power, allowing for better-informed decisions in the market.
Special Thanks
I use the TWMA-Function created from RedKTrader to smooth the values.
Special thanks to him for creating and sharing this function!
MACD Diff SignalWhen the MACD Absolute Histogram is above a threshold (set by nth lowest absolute histogram value in the rolling window) the indicator produces the MACD Histogram level, otherwise it produces 0. This Indicator is good for identifying bullish or bearish momentum.
Tian Di Grid Merge Version 6.0
Strategy Introduction:
1. We know that the exchange can only set a maximum of 100 grids. However, our grid strategy can set a maximum of 350 grids.
2. We have added the modes of proportional and differential warehousing.
3. It should be noted that we have not set any filtering conditions, which means that when the price falls below the grid, we will execute a buy action at the closing price, and when the price falls above the grid, we will execute a sell action;
4. We suggest limiting the trading time cycle to 5 meters, as sometimes errors may appear on TV due to the dense grid or the inability to draw so many grids;
5. Please ensure that the minimum spacing between each grid is not less than 0.1%, as this is extremely difficult to profit from, and on the other hand, it may not function due to excessively dense spacing;
6. The maximum number of grids is 350, and the minimum number is currently 3;
matters needing attention:
Don't choose to go long or short together, and don't choose to go even short or short;
Closing position setting: It is recommended to select it to avoid order accumulation;
Unable to trade: If unable to trade normally, switch to a 1m cycle;
Number of cells: Calculate it yourself, 350 is just the maximum number of cells that can be adjusted;
Grid spacing: minimum 0.1%, below which no profit can be made;
Position value: default is 100u, which is the amount already leveraged;
Multiple investment: The order amount for each order is the same, and there is no need for multiple investment;
Open both long and short positions: You can open multiple positions for one account and open one position for one account. Do not open both long and short positions for the same target at the same time
Custom MACD Oscillator with Bar ColoringCustom MACD Oscillator with Bar Coloring
This custom MACD indicator is a fusion of two powerful MACD implementations, combining the best features of both the MACD Crossover by HPotter and the Multiple Time Frame Custom MACD Indicator by ChrisMoody. The indicator enhances the traditional MACD with customizable options and dynamic bar coloring based on the relationship between the MACD and Signal lines, providing a clear visual representation of momentum shifts in the market.
Key Features:
MACD Oscillator: Built on the core MACD principle, showing the difference between two Exponential Moving Averages (EMA) for momentum tracking.
Signal Line: A Simple Moving Average (SMA) of the MACD, helping to identify potential entry/exit points through crossovers.
Multiple Time Frame Support: Allows users to view MACD and Signal data from different timeframes, giving a broader view of the market dynamics.
Bar Coloring: Bars are colored green when the MACD is above the Signal line (bullish), red when the MACD is below (bearish), and blue during neutral conditions.
Histogram with Custom Colors: A customizable histogram visualizes the difference between the MACD and Signal lines with color-coding to represent changes in momentum.
Cross Dots: Visual markers at points where the MACD crosses the Signal line for easy identification of potential trend shifts.
This indicator is a versatile tool for traders who want to visualize MACD-based momentum and crossover signals in multiple timeframes with clear visual cues on price bars.
Advanced Stochastic ForLoopAdvanced Stochastic ForLoop
OVERVIEW
Advanced Stochastic ForLoop is an improved version of Stochastic it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (set by user treshold for both directions)
-FAST THRESHOLD (when theres an change in signal by set margin e.g 0.4 -> 0.2 means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
Alerts included when line color is:
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
Multi-Asset Cross Timeframe Divergence Ind. (MACDI) // AlgoFyreThe Multi-Asset Cross Timeframe Divergence Indicator (MACDI) identifies divergences in momentum like RSI across multiple assets and timeframes. It visually highlights lagging correlated asset momentum divergences, helping traders spot inefficiencies and potential trade opportunities in the following asset.
🔶 KEY FEATURES
🔸Average Momentum Trendline for Each Timeframe
The Average Momentum Trendline feature calculates the average momentum of multiple assets over specified timeframes. It uses smoothed values to determine the momentum trend for each timeframe on the average aggregated momentum of both assets. This trendline helps traders identify the overall direction of the market momentum, providing a clearer picture of potential price movements.
🔸Real-time Divergence Indication and Alert Table
The Real-time Divergence Indications and Alert Table feature visualizes detected divergences between the momentum values of the two assets across different timeframes. It identifies both bullish and bearish divergences, signaling lagging reversals in the the following asset and potential trading opportunities. When a divergence is detected, the system generates real-time visual indications on the chart and in an overview table for traders to act promptly. The alert table provides a comprehensive overview of all detected divergences, making it easier for traders to monitor and respond to market changes.
🔸Color and Size Based Labels on Price Chart based on Divergence Type
The Color and Size Based Labels feature visually represents divergences directly on the price chart. Bullish and bearish divergences are marked with distinct colors and sizes, making them easily identifiable at a glance. Larger labels indicate higher timeframes and thus generally more significance.
🔶 INSTRUCTION GUIDELINES
🔸Identify Divergence Clusters
The more divergences align, the higher the probability of a potential trend reversal in the asset. When multiple multi-timeframe divergences occur in both lower and higher timeframes within a local cluster, the probability of a reversal increases. This is valid for both for bullish and bearish divergences.
🔸Spot Low Probability Divergences
To further increase the probability, analyze the current state of the average momentum trendline. For a bullish reversal, a relatively low level of the average momentum trendline is preferred, whereas for a bearish reversal, a relatively high level is preferred.
🔶 INDIVIDUAL CONFIGURATION
🔸Leading Asset
This input allows the user to select the leading asset for the divergence analysis.
🔸Following Asset
This input allows the user to select the following asset for the divergence analysis.
🔸Higher Timeframe
This input sets the higher timeframe for the analysis.
🔸Lower Timeframe
This input sets the lower timeframe for the analysis.
🔸Show RSI Divergence
This input enables or disables the display of RSI divergence signals.
🔸RSI Length
This input sets the length of the RSI calculation.
🔸RSI Source
This input sets the source data for the RSI calculation (e.g., close price).
🔸RSI Smoothing Length
This input sets the length of the smoothing applied to the RSI values.
🔸Smoothing Method
This input sets the method used for smoothing the RSI values.
🔶 CONCLUSION
The Multi-Asset Cross Timeframe Divergence Indicator (MACDI) is a powerful tool for identifying momentum divergences across multiple assets and timeframes. Its visual cues and customizable table make it easy to use and interpret, providing valuable insights for trading decisions.
Relative Strength and MomentumRelative Strength and Momentum Indicator
Unlock deeper market insights with the Relative Strength and Momentum Indicator—a powerful tool designed to help traders and investors identify the strongest stocks and sectors based on relative performance. This custom indicator displays essential information on relative strength and momentum for up to 15 different symbols, compared against a benchmark index, all within a clear and organized table format.
Key Features:
1. Customizable Inputs: Choose up to 15 symbols to compare, along with a benchmark index, allowing you to tailor the indicator to your trading strategy. The 'Lookback Period' input defines how many weeks of data are analyzed for relative strength and momentum.
2. Relative Strength Calculation: For each selected symbol, the indicator calculates the Relative Strength (RS) against the chosen benchmark. This RS is further refined using an exponential moving average (EMA) to smooth the results, providing a more stable trend overview.
3. Momentum Analysis: Momentum is determined by analyzing the rate of change in relative strength. The indicator calculates a momentum rank for each symbol, based on its relative strength’s improvement or deterioration.
4. Percentile Ranking System: Each symbol is assigned a percentile rank (from 1 to 100) based on its relative strength compared to the others. Similarly, momentum rankings are also assigned from 1 to 100, offering a clear understanding of which assets are outperforming or underperforming.
5. Visual Indicators:
a. Green: Signals improving or stable relative strength and momentum.
b. Red: Indicates declining relative strength or momentum.
c. Aqua: Highlights symbols performing well on both relative strength and momentum—ideal candidates for further analysis.
6. Two Clear Tables:
a. Relative Strength Rank Table: Displays weekly rankings of relative strength for each symbol.
b. Momentum Table: Shows momentum trends, helping you identify which symbols are gaining or losing strength.
7. Color-Coded for Easy Analysis: The tables are color-coded to make analysis quick and straightforward. A green color means the symbol is performing well in terms of relative strength or momentum, while red indicates weaker performance. Aqua marks symbols that are excelling in both areas.
Use Case:
a. Sector Comparison: Identify which sectors or indexes are showing both relative strength and momentum to pick high-potential stocks. This allows you to align with broader market trends for improved trade entries.
b. Stock Selection: Quickly compare symbols within the same sector to find the stronger performers.
Volume Wave Trend ConfirmationUtility of the Indicator
The core utility of this indicator lies in its ability to utilize volume, a less frequently exploited metric in MACD analysis, providing several strategic advantages:
Trend Confirmation: By focusing on volume, the indicator confirms whether movements in price are backed by significant trading activity. A rising MACD line above the signal line, paired with increasing volume, can confirm the strength of an uptrend. Conversely, if the histogram turns negative while the MACD line falls below the signal line during a price drop, it confirms a robust downtrend.
Early Warning Signals: Changes in the histogram and divergences between the MACD and Signal lines can serve as early warnings of potential reversals or slowdowns in market momentum. For instance, a shrinking histogram in an uptrend might suggest that the upward movement is losing steam.
Market Sentiment: The integration of volume into the MACD framework allows the indicator to provide insights into underlying market sentiment. Higher volumes during price movements indicate stronger conviction among traders, making the trend more reliable.
Indicator Functionality
The "Volume Wave Trend Confirmation" indicator is built on the Moving Average Convergence Divergence (MACD) framework, but with a unique twist: it uses the smoothed moving averages (SMA) of trading volumes instead of price. The indicator calculates two specific SMAs of the volume — a shorter 33-period SMA and a longer 100-period SMA — and computes their difference. This difference is then used as the input for the MACD calculation, with typical parameters set at 12, 26, and a signal line of 9.
MACD Line (Blue): Represents the main line, calculated as the difference between the 12-period and 26-period exponential moving averages (EMA) of the volume difference.
Signal Line (Orange): A 9-period EMA of the MACD line, acting as a trigger for buy or sell signals.
Histogram (Blue/Purple): Measures the distance between the MACD line and the Signal line, colored blue when positive (above the Signal line) and purple when negative (below the Signal line).
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling.
A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools.
The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured.
Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns.
The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration.
How does it work?
This indicator calculates acceleration based the highs and lows of each dataset
Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration
It then plots multiple lines with customizable variance from the primary selected length
Practical Tips:
The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles.
The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
VWAP PressureKey Features and Utility:
Intrabar Focus: Unlike standard VWAP, which provides a cumulative average throughout the day, the Intrabar VWAP focuses on volume-weighted price calculations within shorter time frames. This allows traders to see how price and volume interact moment-to-moment, offering a granular view of market sentiment.
Market Pressure Analysis: The indicator examines the difference between a smoothed weighted average price of the close and intrabar price movements. This analysis helps in identifying the market pressure at high volume areas. When the market exhibits high volume at low prices within a bar, it suggests accumulation, whereas high volume at high prices indicates distribution.
Momentum and Pressure Shift Signals: By applying a modified MACD calculation to the smoothed difference, the indicator provides signals on shifts in market pressure. Positive values indicate upward price momentum (buying pressure), while negative values suggest downward momentum (selling pressure).
Market DirectionThe "Market Direction" indicator combines four advanced sub-indicators to provide a comprehensive and multi-dimensional analysis of market trends, momentum, and potential reversals. This innovative approach leverages different aspects of price action, volume, and market sentiment, offering traders an in-depth view of market conditions.
1. Fractal Indicator: Multi-Scale Price Action Analysis
The Fractal Indicator identifies significant highs and lows over six different pivot lengths, offering a nuanced view of price action across multiple timeframes. By comparing distances from current closing prices to these key fractal points, the indicator determines potential trend reversals and market direction. This approach enables traders to adapt their strategies to various market conditions, capturing both short-term fluctuations and long-term trends.
2. Volume MACD Indicator: Enhanced Market Momentum
The Volume MACD Indicator goes beyond traditional MACD analysis by incorporating volume-weighted movement and the structural attributes of candlesticks (such as body length and wicks). This hybrid model offers a more comprehensive understanding of market momentum by integrating both price action and trading volume. The use of Smoothed Moving Averages (SMMA) reduces noise and ensures more stable signals, helping traders focus on sustainable trends and longer-term investment opportunities.
3. Cumulative Volume Momentum Indicator: Volume Dynamics Insight
The Cumulative Volume Momentum Indicator evaluates the momentum of cumulative buying and selling volumes, offering a clear picture of market strength and potential reversals. By comparing the relationship between open, close, high, and low prices, and applying a MACD approach to these volume dynamics, this indicator helps traders identify momentum shifts that often precede price movements. The visualization through histograms adds clarity to bullish and bearish volume momentum, enhancing decision-making in volatile markets.
4. POC-Price Momentum Indicator: Market Depth and Sentiment
The POC-Price Momentum Indicator assesses the difference between the Point of Control (POC) and closing prices, providing insights into underlying market sentiment. Positive differences indicate a buildup of upward momentum, while negative differences suggest a bearish tilt. By calculating moving averages of these differences, the indicator highlights the strength and sustainability of ongoing trends, helping traders align their strategies with the broader market direction.
Unified Rating for Confirming Market Direction
The "Market Direction" indicator consolidates the outputs of these four sub-indicators into a single, aggregated sentiment score. This score helps traders confirm the prevailing market trend by weighing the combined insights from fractal analysis, volume momentum, price action, and POC dynamics. A positive score suggests a bullish market, while a negative score indicates bearish conditions.
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal
### Overview
The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis.
### Unique Features
This indicator integrates multiple crucial elements of market behavior:
- Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements.
- Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment.
- Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding.
- Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations.
Customization and Inputs
The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions:
Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends.
ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements.
Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better.
Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes.
Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction.
Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends.
These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends.
### Functionality Details
The indicator operates through a sophisticated algorithm that integrates multiple market dimensions:
1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the market’s momentum and stability.
2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts.
3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades.
The indicator performs its calculations as follows:
Momentum and Volatility Calculation:
roc = ta.roc(close, rocLength)
atr = ta.atr(atrLength)
Volume and Trend Analysis:
volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength)
emaShort = ta.ema(close, shortEmaLength)
emaLong = ta.ema(close, longEmaLength)
emaDifference = emaShort - emaLong
Composite Signal Calculation:
Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal:
rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength)
atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength)
volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength)
emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength)
compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4
### Originality
The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics.
### Practical Application
The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for:
- Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes.
- Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points.
- Position Traders : Utilize long-term market trend data to align with overall market movements.
### Best Practices
To maximize the effectiveness of the Uptrick indicator, consider the following:
- Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation.
- Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy.
- Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR.
### Practical Examples and Demonstrations
- Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout.
- Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position.
### Alerts and Their Uses
- Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events.
- Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions.
Technical Notes
Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions.
Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation.
Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions.
### Conclusion
The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Inverse Fisher Oscillator [BigBeluga]The Inverse Fisher Oscillator is a powerful tool for identifying market trends and potential reversal points by applying the Inverse Fisher Transform to normalized price data. This indicator plots multiple smoothed oscillators, each color-coded to signify their relation to dynamic volatility bands. Additionally, the Butterworth filter is incorporated to further refine trend signals. The Inverse Fisher Oscillator offers traders a visually appealing and insightful approach to trend analysis and market direction detection.
🔵 KEY FEATURES
● Inverse Fisher Oscillator Visualization
Multiple Oscillators : The indicator calculates and plots six different Inverse Fisher Oscillators, each smoothed at increasing levels to provide a layered view of price momentum.
Color-Coded Signals : The oscillator lines are color-coded based on their relation to the volatility bands—green for bullish momentum, red for bearish momentum, and yellow for neutral movements.
● Butterworth Filter Integration
Filtering : The Butterworth filter is applied to mid-line Bands to reduce noise, allowing for clearer trend detection.
// Calculate constants for the Butterworth filter
float piPrd = math.pi / mid_len
float g = math.sqrt(2)
float a1 = math.exp(-g * piPrd)
float b1 = 2 * a1 * math.cos(g * piPrd)
float coef2 = b1
float coef3 = -a1 * a1
float coef1 = (1 - b1 + a1 * a1) / 4
// Source data for the Butterworth filter
float source = ifish // The first inverse Fisher Oscillator is used as the source
// Previous source and butter filter values
var float butter = na // Initialize the 'butter' variable
// Handle null values using the nz function
float prevB1 = nz(butter , source) // Use 'source' as a fallback if butter is null
float prevB2 = nz(butter , source) // Use 'source' as a fallback if butter is null
// Calculate the Butterworth filter value
butter := coef1 * (source + (2 * source ) + source ) + (coef2 * prevB1) + (coef3 * prevB2)
● Numbered Signal Marks
Signal Markers : The indicator plots numbered signals on the chart when an oscillator crosses above the upper volatility band or below the lower volatility band.
Numbered Lines : Numbers correspond to the different oscillators (1-6), helping traders easily identify which smoothing level generated the signal.
Visual Cues : The signals are color-coded—green for bullish crossovers and red for bearish crossunders—providing clear visual cues for trend accumulation phases.
Mid-Line Option : Traders can choose between plotting the Butterworth filter as a dynamic mid-line or simply displaying it as part of the bands.
Volatility Bands : Dynamic volatility bands provide additional context for interpreting the strength and sustainability of trends.
● Dashboard Display
Real-Time Market Trend Overview : The dashboard in the bottom-right corner of the chart displays the market trend based on the Inverse Fisher Oscillator for six different smoothing levels, providing a clear visual summary of market direction.
Direction Symbols : Directional symbols (up, down, or neutral) are displayed in the dashboard, color-coded to represent bullish, bearish, or neutral momentum.
Current Price Display : The dashboard also shows the current price and highlights whether it is above or below the opening price.
🔵 HOW TO USE
● Identifying Trend Reversals
Bullish Reversals : When the oscillators short period lines start to cross above the upper volatility band (green), it indicates potential bullish momentum.
Bearish Reversals : When the oscillator crosses below the lower volatility band (red), it signals potential bearish momentum.
Neutral Signals : When the oscillator remains within the bands (yellow), it suggests that the market is in a neutral or consolidating state. Traders may choose to wait for a clearer trend signal.
● Using the Dashboard for Trend Overview
Market Trend Summary : The dashboard provides a quick overview of market direction across six different smoothing levels. Green arrows indicate bullish momentum, red arrows indicate bearish momentum, and wavy lines suggest neutrality.
Price Context : The dashboard also displays the current price, helping traders quickly assess whether the price is moving in the expected direction relative to their trend analysis.
● Volatility Band Interpretation
Volatility-Based Signals : Pay attention to how the oscillators interact with the volatility bands. Strong trends will often result in oscillators staying above or below the bands, while weaker trends or consolidations will see oscillators hovering within the bands.
🔵 CUSTOMIZATION
Length and Smoothing : Adjust the length and smoothing parameters to fit different market conditions and timeframes.
Bands Multiplier : Customize the multiplier for the volatility bands to make them more or less sensitive to price changes.
Mid-Line Type : Choose whether to display the Butterworth filter as a mid-line or incorporate it into the volatility bands.
Signal Markers : Toggle on or off the number markers for signal crossovers, making it easier to identify key entry and exit points.
🔵 CONCLUSION
The Inverse Fisher Oscillator combines the power of the Inverse Fisher Transform and the Butterworth filter to provide a sophisticated approach to trend and reversal detection. By leveraging volatility-based analysis and visually intuitive signals, this indicator helps traders spot potential entry and exit points with greater clarity. The customizable dashboard display adds further value, offering a real-time summary of market conditions to enhance decision-making. Use this tool in conjunction with other technical analysis methods to develop a well-rounded trading strategy.
