9/21 EMA_DSWThe 9 and 21 EMA strategy involves using the 9-day and 21-day exponential moving averages to identify potential buy and sell signals. A buy signal is generated when the 9 EMA crosses above the 21 EMA, and a sell signal is generated when the 9 EMA crosses below the 21 EMA.
Oscillaltor
VWAP Divergence | dobofulopOverview :
This script identifies potential bullish and bearish divergence signals using the Volume Weighted Average Price (VWAP). It calculates VWAP resets based on a selected “Anchor Period” (Session, Week, Month, Quarter, Year, Decade, Century, or corporate events like Earnings, Dividends, Splits). When price action and VWAP move in opposite directions with a sufficiently large ATR-based move over a chosen lookback period, the script plots divergence dots on the chart.
Key Features:
VWAP Anchoring : Choose an anchor period for resetting VWAP. This could be daily, weekly, monthly, or based on specific corporate events (Earnings, Dividends, Splits).
Divergence Detection : Looks for instances where the price is moving up while VWAP moves down (potential bullish divergence), and vice versa for bearish divergence.
ATR Filter : Uses the ATR (Average True Range) to filter out minor or insignificant price moves, helping to reduce noise.
Gap Check : Automatically invalidates signals if large price gaps occur within the lookback range.
Visual Signals : Bullish divergences are plotted below the bar, while bearish divergences are plotted above, making it easy to spot potential reversal zones.
How to Us
Inputs:
- Anchor Period (Session, Week, Month, etc.) – determines when the VWAP calculation restarts.
- Source (Default: HLC3) – Price source for the VWAP.
- ATR Multiplier and Lookback Period – Fine-tune the threshold for detecting significant moves vs. VWAP.
Interpretation:
- Bullish Divergence Dot: Suggests potential price strength when price moves higher but VWAP moves lower.
- Bearish Divergence Dot: Suggests potential price weakness when price moves lower but VWAP moves higher.
Disclaimer:
This script is provided for educational purposes only and should not be interpreted as financial advice. Past performance does not guarantee future results. Always conduct your own analysis and consider consulting a financial professional before making trading decisions.
ADVDEC.US OSCILLATORThis Pine Script implements an ADVDEC.US Oscillator, which is an indicator designed to analyze the Advance-Decline index (ADVDEC.US) with multiple smoothing techniques and timeframes. Here's what the script does:
Symbol and Inputs:
- The script is based on the ADVDEC.US index, which measures the difference between advancing and declining stocks.
Users can adjust several settings:
- Lookback Period: Defines the number of periods over which the highest and lowest values of the ADVDEC.US index are calculated.
- Smoothing Period: Smooths the oscillator with a simple moving average (SMA) to reduce market noise.
- EMA Period: Applies an Exponential Moving Average (EMA) to the smoothed oscillator for further trend analysis.
- MTF Period: Allows for fetching data from a specified timeframe (default is 5 minutes).
Calculation:
- It calculates the highest and lowest values of the ADVDEC index over the defined lookback period.
- It normalizes the ADVDEC value into a percentage between 0 and 100, representing the position of the current value relative to the range over the lookback period.
- This raw oscillator is then smoothed with an SMA to reduce choppiness.
- Finally, an EMA is calculated on the smoothed oscillator to emphasize the trend direction.
Thresholds:
- Horizontal lines are plotted at key levels (70, 30, and 50) for visual reference, offering an "RSI-style" interpretation of the oscillator.
- The upper and lower thresholds can indicate overbought/oversold conditions, while the midline helps identify neutral levels.
Visualization:
- The smoothed oscillator is plotted in blue.
- The EMA of the smoothed oscillator is plotted in orange.
In summary, this indicator aims to visualize the relationship between advancing and declining stocks with added smoothing and trend-following elements, providing an easy-to-interpret oscillator that can be used for market analysis or decision-making.
Flow-Weighted Volume Oscillator (FWVO)Volume Dynamics Oscillator (VDO)
Description
The Volume Dynamics Oscillator (VDO) is a powerful and innovative tool designed to analyze volume trends and provide traders with actionable insights into market dynamics. This indicator goes beyond simple volume analysis by incorporating a smoothed oscillator that visualizes the flow and momentum of trading activity, giving traders a clearer understanding of volume behavior over time.
What It Does
The VDO calculates the flow of volume by scaling raw volume data relative to its highest and lowest values over a user-defined period. This scaled volume is then smoothed using an exponential moving average (EMA) to eliminate noise and highlight significant trends. The oscillator dynamically shifts above or below a zero line, providing clear visual cues for bullish or bearish volume pressure.
Key features include:
Smoothed Oscillator: Displays the direction and momentum of volume using gradient colors.
Threshold Markers: Highlights overbought or oversold zones based on upper and lower bounds of the oscillator.
Visual Fill Zones: Uses color-filled areas to emphasize positive and negative volume flow, making it easy to interpret market sentiment.
How It Works
The calculation consists of several steps:
Smoothing with EMA: An EMA of the scaled volume is applied to reduce noise and enhance trends. A separate EMA period can be adjusted by the user (Volume EMA Period).
Dynamic Thresholds: The script determines upper and lower bounds around the smoothed oscillator, derived from its recent highest and lowest values. These thresholds indicate critical zones of volume momentum.
How to Use It
Bullish Signals: When the oscillator is above zero and green, it suggests strong buying pressure. A crossover from negative to positive can signal the start of an uptrend.
Bearish Signals: When the oscillator is below zero and blue, it indicates selling pressure. A crossover from positive to negative signals potential bearish momentum.
Overbought/Oversold Zones: Use the upper and lower threshold levels as indicators of extreme volume momentum. These can act as early warnings for trend reversals.
Traders can adjust the following inputs to customize the indicator:
High/Low Period: Defines the period for volume scaling.
Volume EMA Period: Adjusts the smoothing factor for the oscillator.
Smooth Factor: Controls the responsiveness of the smoothed oscillator.
Originality and Usefulness
The VDO stands out by combining dynamic volume scaling, EMA smoothing, and gradient-based visualization into a single, cohesive tool. Unlike traditional volume indicators, which often display raw or cumulative data, the VDO emphasizes relative volume strength and flow, making it particularly useful for spotting reversals, confirming trends, and identifying breakout opportunities.
The integration of color-coded fills and thresholds enhances usability, allowing traders to quickly interpret market conditions without requiring deep technical expertise.
Chart Recommendations
To maximize the effectiveness of the VDO, use it on a clean chart without additional indicators. The gradient coloring and filled zones make it self-explanatory, but traders can overlay basic trendlines or support/resistance levels for additional context.
For advanced users, the VDO can be paired with price action strategies, candlestick patterns, or other trend-following indicators to improve accuracy and timing.
PGO For Loop | mad_tiger_slayerPGO For Loop Indicator
The PGO For Loop indicator, inspired by Alex Orekhov's "Pretty Good Oscillator," and indicator originally made by Mark Johnson, the PGO designed as a fast and responsive tool to capture quick price movements in financial markets. This oscillator leverages a combination of moving averages and Average True Range (ATR) to measure price deviations, providing a concise yet powerful framework for identifying potential trade entry and exit points. What makes this
"enhanced" PGO indicator special is its ability to identify trending periods more accurately. By using thresholds, this allows the script to enter accurate long and short conditions extremely quickly.
Intended Uses:
Used to capture long-term trends:
Used to identify quick reversals:
Used on higher timeframes above 8hrs for more accurate signals
Used in strategies to enter and exit trades quickly
Can be used for Scalping
NOT Intended Uses:
Not to be used as Mean Reversion
Not to be used as valuation (Overbought or Oversold)
Key Features:
Quick Detection of Market Movements:
The indicator's primary focus is on speed, making it suitable for medium-term traders looking to capitalize on rapid price changes. It is particularly effective in trending or volatile markets.
Customizable Thresholds:
Users can set upper and lower thresholds to define long and short conditions, offering flexibility to adapt the indicator to different trading styles and asset classes.
Noisy but Purposeful:
While the PGO For Loop may generate frequent signals, it is specifically tuned for traders aiming to enter and exit trades quickly, embracing the noise as part of its effectiveness in capturing rapid market dynamics.
Integrated Visuals:
The script plots key levels and provides dynamic visual feedback through colored candles and shapes, enabling intuitive and quick decision-making.
How It Works:
Oscillator Calculation:
The PGO value is derived by comparing the source price's deviation from its moving average to the ATR. This highlights price movements relative to recent volatility.
Signal Identification:
When the oscillator exceeds the upper threshold, it signals potential long opportunities UNTIL the PGO reaches the lower threshold.
When the oscillator drops below the lower threshold, it signals potential short opportunities UNTIL the oscillator reaches above the upper threshold.
No signals occur when the oscillator lies between these thresholds.
Visual Cues:
Color-coded candles indicate market bias (green for long, red for short, gray for neutral).
Upward and downward triangles highlight changes in signal direction.
Note:
This indicator is intentionally "noisy," as it prioritizes capturing fast movements over filtering out minor fluctuations. Users should pair it with other tools or techniques to confirm signals and manage risk effectively.
Enhanced Price Z-Score OscillatorThe Enhanced Price Z-Score Oscillator by tkarolak is a powerful tool that transforms raw price data into an easy-to-understand statistical visualization using Z-Score-derived candlesticks. Simply put, it shows how far prices stray from their average in terms of standard deviations (Z-Scores), helping traders identify when prices are unusually high (overbought) or unusually low (oversold).
The indicator’s default feature displays Z-Score Candlesticks, where each candle reflects the statistical “distance” of the open, high, low, and close prices from their average. This creates a visual map of market extremes and potential reversal points. For added flexibility, you can also switch to Z-Score line plots based on either Close prices or OHLC4 averages.
With clear threshold lines (±2σ and ±3σ) marking moderate and extreme price deviations, and color-coded zones to highlight overbought and oversold areas, the oscillator simplifies complex statistical concepts into actionable trading insights.
True Amplitude Envelopes (TAE)The True Envelopes indicator is an adaptation of the True Amplitude Envelope (TAE) method, based on the research paper " Improved Estimation of the Amplitude Envelope of Time Domain Signals Using True Envelope Cepstral Smoothing " by Caetano and Rodet. This indicator aims to create an asymmetric price envelope with strong predictive power, closely following the methodology outlined in the paper.
Due to the inherent limitations of Pine Script, the indicator utilizes a Kernel Density Estimator (KDE) in place of the original Cepstral Smoothing technique described in the paper. While this approach was chosen out of necessity rather than superiority, the resulting method is designed to be as effective as possible within the constraints of the Pine environment.
This indicator is ideal for traders seeking an advanced tool to analyze price dynamics, offering insights into potential price movements while working within the practical constraints of Pine Script. Whether used in dynamic mode or with a static setting, the True Envelopes indicator helps in identifying key support and resistance levels, making it a valuable asset in any trading strategy.
Key Features:
Dynamic Mode: The indicator dynamically estimates the fundamental frequency of the price, optimizing the envelope generation process in real-time to capture critical price movements.
High-Pass Filtering: Uses a high-pass filtered signal to identify and smoothly interpolate price peaks, ensuring that the envelope accurately reflects significant price changes.
Kernel Density Estimation: Although implemented as a workaround, the KDE technique allows for flexible and adaptive smoothing of the envelope, aimed at achieving results comparable to the more sophisticated methods described in the original research.
Symmetric and Asymmetric Envelopes: Provides options to select between symmetric and asymmetric envelopes, accommodating various trading strategies and market conditions.
Smoothness Control: Features adjustable smoothness settings, enabling users to balance between responsiveness and the overall smoothness of the envelopes.
The True Envelopes indicator comes with a variety of input settings that allow traders to customize the behavior of the envelopes to match their specific trading needs and market conditions. Understanding each of these settings is crucial for optimizing the indicator's performance.
Main Settings
Source: This is the data series on which the indicator is applied, typically the closing price (close). You can select other price data like open, high, low, or a custom series to base the envelope calculations.
History: This setting determines how much historical data the indicator should consider when calculating the envelopes. A value of 0 will make the indicator process all available data, while a higher value restricts it to the most recent n bars. This can be useful for reducing the computational load or focusing the analysis on recent market behavior.
Iterations: This parameter controls the number of iterations used in the envelope generation algorithm. More iterations will typically result in a smoother envelope, but can also increase computation time. The optimal number of iterations depends on the desired balance between smoothness and responsiveness.
Kernel Style: The smoothing kernel used in the Kernel Density Estimator (KDE). Available options include Sinc, Gaussian, Epanechnikov, Logistic, and Triangular. Each kernel has different properties, affecting how the smoothing is applied. For example, Gaussian provides a smooth, bell-shaped curve, while Epanechnikov is more efficient computationally with a parabolic shape.
Envelope Style: This setting determines whether the envelope should be Static or Dynamic. The Static mode applies a fixed period for the envelope, while the Dynamic mode automatically adjusts the period based on the fundamental frequency of the price data. Dynamic mode is typically more responsive to changing market conditions.
High Q: This option controls the quality factor (Q) of the high-pass filter. Enabling this will increase the Q factor, leading to a sharper cutoff and more precise isolation of high-frequency components, which can help in better identifying significant price peaks.
Symmetric: This setting allows you to choose between symmetric and asymmetric envelopes. Symmetric envelopes maintain an equal distance from the central price line on both sides, while asymmetric envelopes can adjust differently above and below the price line, which might better capture market conditions where upside and downside volatility are not equal.
Smooth Envelopes: When enabled, this setting applies additional smoothing to the envelopes. While this can reduce noise and make the envelopes more visually appealing, it may also decrease their responsiveness to sudden market changes.
Dynamic Settings
Extra Detrend: This setting toggles an additional high-pass filter that can be applied when using a long filter period. The purpose is to further detrend the data, ensuring that the envelope focuses solely on the most recent price oscillations.
Filter Period Multiplier: This multiplier adjusts the period of the high-pass filter dynamically based on the detected fundamental frequency. Increasing this multiplier will lengthen the period, making the filter less sensitive to short-term price fluctuations.
Filter Period (Min) and Filter Period (Max): These settings define the minimum and maximum bounds for the high-pass filter period. They ensure that the filter period stays within a reasonable range, preventing it from becoming too short (and overly sensitive) or too long (and too sluggish).
Envelope Period Multiplier: Similar to the filter period multiplier, this adjusts the period for the envelope generation. It scales the period dynamically to match the detected price cycles, allowing for more precise envelope adjustments.
Envelope Period (Min) and Envelope Period (Max): These settings establish the minimum and maximum bounds for the envelope period, ensuring the envelopes remain adaptive without becoming too reactive or too slow.
Static Settings
Filter Period: In static mode, this setting determines the fixed period for the high-pass filter. A shorter period will make the filter more responsive to price changes, while a longer period will smooth out more of the price data.
Envelope Period: This setting specifies the fixed period used for generating the envelopes in static mode. It directly influences how tightly or loosely the envelopes follow the price action.
TAE Smoothing: This controls the degree of smoothing applied during the TAE process in static mode. Higher smoothing values result in more gradual envelope curves, which can be useful in reducing noise but may also delay the envelope’s response to rapid price movements.
Visual Settings
Top Band Color: This setting allows you to choose the color for the upper band of the envelope. This band represents the resistance level in the price action.
Bottom Band Color: Similar to the top band color, this setting controls the color of the lower band, which represents the support level.
Center Line Color: This is the color of the central price line, often referred to as the carrier. It represents the detrended price around which the envelopes are constructed.
Line Width: This determines the thickness of the plotted lines for the top band, bottom band, and center line. Thicker lines can make the envelopes more visible, especially when overlaid on price data.
Fill Alpha: This controls the transparency level of the shaded area between the top and bottom bands. A lower alpha value will make the fill more transparent, while a higher value will make it more opaque, helping to highlight the envelope more clearly.
The envelopes generated by the True Envelopes indicator are designed to provide a more precise and responsive representation of price action compared to traditional methods like Bollinger Bands or Keltner Channels. The core idea behind this indicator is to create a price envelope that smoothly interpolates the significant peaks in price action, offering a more accurate depiction of support and resistance levels.
One of the critical aspects of this approach is the use of a high-pass filtered signal to identify these peaks. The high-pass filter serves as an effective method of detrending the price data, isolating the rapid fluctuations in price that are often lost in standard trend-following indicators. By filtering out the lower frequency components (i.e., the trend), the high-pass filter reveals the underlying oscillations in the price, which correspond to significant peaks and troughs. These oscillations are crucial for accurately constructing the envelope, as they represent the most responsive elements of the price movement.
The algorithm works by first applying the high-pass filter to the source price data, effectively detrending the series and isolating the high-frequency price changes. This filtered signal is then used to estimate the fundamental frequency of the price movement, which is essential for dynamically adjusting the envelope to current market conditions. By focusing on the peaks identified in the high-pass filtered signal, the algorithm generates an envelope that is both smooth and adaptive, closely following the most significant price changes without overfitting to transient noise.
Compared to traditional envelopes and bands, such as Bollinger Bands and Keltner Channels, the True Envelopes indicator offers several advantages. Bollinger Bands, which are based on standard deviations, and Keltner Channels, which use the average true range (ATR), both tend to react to price volatility but do not necessarily follow the peaks and troughs of the price with precision. As a result, these traditional methods can sometimes lag behind or fail to capture sudden shifts in price momentum, leading to either false signals or missed opportunities.
In contrast, the True Envelopes indicator, by using a high-pass filtered signal and a dynamic period estimation, adapts more quickly to changes in price behavior. The envelopes generated by this method are less prone to the lag that often affects standard deviation or ATR-based bands, and they provide a more accurate representation of the price's immediate oscillations. This can result in better predictive power and more reliable identification of support and resistance levels, making the True Envelopes indicator a valuable tool for traders looking for a more responsive and precise approach to market analysis.
In conclusion, the True Envelopes indicator is a powerful tool that blends advanced theoretical concepts with practical implementation, offering traders a precise and responsive way to analyze price dynamics. By adapting the True Amplitude Envelope (TAE) method through the use of a Kernel Density Estimator (KDE) and high-pass filtering, this indicator effectively captures the most significant price movements, providing a more accurate depiction of support and resistance levels compared to traditional methods like Bollinger Bands and Keltner Channels. The flexible settings allow for extensive customization, ensuring the indicator can be tailored to suit various trading strategies and market conditions.
Monest Value Indicator (MVI)
Description
The Monest Value Indicator (MVI) is a modern oscillator designed to address common issues in traditional oscillators like RSI or MACD. Unlike classical oscillators, the MVI dynamically adjusts to relative price movements and market volatility, providing a transparent and reliable valuation for short-term trading decisions.
This indicator normalizes price data around a consensus line and accounts for market volatility using the Average True Range (ATR). It highlights overbought and oversold conditions, offering a unique perspective for traders.
Key Features
Dynamic Overbought/Oversold Levels : Highlights significant price extremes for better entry and exit signals. Volatility Normalization : Adapts to market conditions, ensuring consistent readings across various assets. Consensus-Based Valuation : Uses a moving average of the midrange price for baseline calculations. No Lag or Stickiness : Reacts promptly to price movements without getting stuck in extreme zones.
How It Works
Consensus Line :
Calculated as a 5-day moving average of the midrange:
Consensus = SMA((High + Low) / 2, 5) .
Offset OHLC Data :
All prices are adjusted relative to the consensus line:
Offset Price = Price - Consensus .
Volatility Normalization :
Adjusted prices are normalized using a 5-day ATR divided by 5:
Normalized Price = Offset Price / (ATR / 5) .
MVI Calculation :
The normalized closing price is plotted as the MVI.
Overbought/Oversold Levels :
Default levels are set at +8 (overbought) and -8 (oversold).
How to Use
Identifying Overbought/Oversold Conditions :
When the MVI crosses above +8 , the asset is overbought, signaling a potential reversal or pullback.
When the MVI drops below -8 , the asset is oversold, indicating a potential bounce or upward move.
Trend Confirmation :
Use the MVI to confirm trends by observing sustained movements above or below zero.
Combine with other trend indicators (e.g., Moving Averages) for robust analysis.
Alerts :
Set alerts for when the MVI crosses overbought or oversold levels to stay informed about potential trading opportunities.
Inputs
ATR Length : Default is 5. Adjust to modify the sensitivity of volatility normalization. Consensus Length : Default is 5. Change to tweak the baseline calculation.
Example
Overbought Signal : MVI exceeds +8 , indicating the asset may reverse from an overvalued position. Oversold Signal : MVI drops below -8 , suggesting the asset may recover from an undervalued state. Flat Market : MVI hovers near zero, indicating price consolidation.
Kalman Trend Strength Index (K-TSI)The Kalman Trend Strength Index (K-TSI) is an innovative technical indicator that combines the Kalman filter with correlation analysis to measure trend strength in financial markets. This sophisticated tool aims to provide traders with a more refined method for trend analysis and market dynamics interpretation.
The use of the Kalman filter is a key feature of the K-TSI. This advanced algorithm is renowned for its ability to extract meaningful signals from noisy data. In financial markets, this translates to smoothing out price action while maintaining responsiveness to genuine market movements. By applying the Kalman filter to price data before performing correlation analysis, the K-TSI potentially offers more stable and reliable trend signals.
The synergy between the Kalman-filtered price data and correlation analysis creates an oscillator that attempts to capture market dynamics more effectively. The correlation component contributes by measuring the strength and consistency of price movements relative to time, while the Kalman filter adds robustness by reducing the impact of market noise. Basing these calculations on Kalman-filtered data may help reduce false signals and provide a clearer picture of underlying market trends.
A notable aspect of the K-TSI is its normalization process. This approach adjusts the indicator's values to a standardized range (-1 to 1), allowing for consistent interpretation across different market conditions and timeframes. This flexibility, combined with the noise-reduction properties of the Kalman filter, positions the K-TSI as a potentially useful tool for various market environments.
In practice, traders might find that the K-TSI offers several potential benefits:
Smoother trend identification, which could aid in detecting the start and end of trends more accurately.
Possibly reduced false signals, particularly in choppy or volatile markets.
Potential for improved trend strength assessment, which might lead to more confident trading decisions.
Consistent performance across different timeframes, due to the adaptive nature of the Kalman filter and the normalization process.
The K-TSI's visual representation as a color-coded histogram further enhances its utility. The changing colors and intensities provide an intuitive way to gauge both the direction and strength of trends, making it easier for traders to quickly assess market conditions.
While the K-TSI builds upon existing concepts in technical analysis, its integration of the Kalman filter with correlation analysis offers traders an interesting tool for market analysis. It represents an attempt to address common challenges in technical analysis, such as noise reduction and trend strength quantification.
As with any technical indicator, the K-TSI should be used as part of a broader trading strategy rather than in isolation. Its effectiveness will depend on how well it aligns with a trader's individual approach and market conditions. For traders looking to explore a more refined trend strength oscillator, the Kalman Trend Strength Index could be a worthwhile addition to their analytical toolkit.
Kalman Synergy Oscillator (KSO)The Kalman Synergy Oscillator (KSO) is an innovative technical indicator that combines the Kalman filter with two well-established momentum oscillators: the Relative Strength Index (RSI) and Williams %R. This combination aims to provide traders with a more refined tool for market analysis.
The use of the Kalman filter is a key feature of the KSO. This sophisticated algorithm is known for its ability to extract meaningful signals from noisy data. In financial markets, this translates to smoothing out price action while maintaining responsiveness to genuine market movements. By applying the Kalman filter to price data before calculating the RSI and Williams %R, the KSO potentially offers more stable and reliable signals.
The synergy between the Kalman-filtered price data and the two momentum indicators creates an oscillator that attempts to capture market dynamics more effectively. The RSI contributes its strength in measuring the magnitude and speed of price movements, while Williams %R adds sensitivity to overbought and oversold conditions. Basing these calculations on Kalman-filtered data may help reduce false signals and provide a clearer picture of underlying market trends.
A notable aspect of the KSO is its dynamic weighting system. This approach adjusts the relative importance of the RSI and Williams %R based on their current strengths, allowing the indicator to emphasize the most relevant information as market conditions change. This flexibility, combined with the noise-reduction properties of the Kalman filter, positions the KSO as a potentially useful tool for different market conditions.
In practice, traders might find that the KSO offers several potential benefits:
Smoother oscillator movements, which could aid in trend identification and reversal detection.
Possibly reduced whipsaws, particularly in choppy or volatile markets.
Potential for improved divergence detection, which might lead to more timely reversal signals.
Consistent performance across different timeframes, due to the adaptive nature of the Kalman filter.
While the KSO builds upon existing concepts in technical analysis, its integration of the Kalman filter with traditional momentum indicators offers traders an interesting tool for market analysis. It represents an attempt to address common challenges in technical analysis, such as noise reduction and false signal minimization.
As with any technical indicator, the KSO should be used as part of a broader trading strategy rather than in isolation. Its effectiveness will depend on how well it aligns with a trader's individual approach and market conditions. For traders looking to explore a more refined momentum oscillator, the Kalman Synergy Oscillator could be a worthwhile addition to their analytical toolkit.
Dynamic Score PSAR [QuantAlgo]Dynamic Score PSAR 📈🧬
The Dynamic Score PSAR by QuantAlgo introduces an innovative approach to trend detection by utilizing a dynamic trend scoring technique in combination with the Parabolic SAR. This method goes beyond traditional trend-following indicators by evaluating market momentum through a scoring system that analyzes price behavior over a customizable window. By dynamically adjusting to evolving market conditions, this indicator provides clearer, more adaptive trend signals that help traders and investors anticipate market reversals and capitalize on momentum shifts with greater precision.
💫 Conceptual Foundation and Innovation
At the core of the Dynamic Score PSAR is the dynamic trend score system, which assesses price movements by comparing normalized PSAR values across a range of historical data points. This dynamic trend scoring technique offers a unique, probabilistic approach to trend analysis by evaluating how the current market compares to past price movements. Unlike traditional PSAR indicators that rely on static parameters, this scoring mechanism allows the indicator to adjust in real time to market fluctuations, offering traders and investors a more responsive and insightful view of trends. This innovation makes the Dynamic Score PSAR particularly effective in detecting shifts in momentum and potential reversals, even in volatile or complex market environments.
✨ Technical Composition and Calculation
The Dynamic Score PSAR is composed of several advanced components designed to provide a higher probability of detecting accurate trend shifts. The key innovation lies in the dynamic trend scoring technique, which iterates over historical PSAR values and evaluates price momentum through a dynamic scoring system. By comparing the current normalized PSAR value with previous data points over a user-defined window, the system generates a score that reflects the strength and direction of the trend. This allows for a more refined and responsive detection of trends compared to static, traditional indicators.
To enhance clarity, the PSAR values are normalized against an Exponential Moving Average (EMA), providing a standardized framework for comparison. This normalization ensures that the indicator adapts dynamically to market conditions, making it more effective in volatile markets. The smoothing process reduces noise, helping traders and investors focus on significant trend signals.
Additionally, users can adjust the length of the data window and the sensitivity thresholds for detecting uptrends and downtrends, providing flexibility for different trading and investing environments.
📈 Features and Practical Applications
Customizable Window Length: Adjust the window length to control the indicator’s sensitivity to recent price movements. This provides flexibility for short-term or long-term trend analysis.
Uptrend/Downtrend Thresholds: Set customizable thresholds for identifying uptrends and downtrends. These thresholds define when trend signals are triggered, offering adaptability to different market conditions.
Bar Coloring and Gradient Visualization: Visual cues, including color-coded bars and gradient fills, make it easier to interpret market trends and identify key moments for potential trend reversals.
Momentum Confirmation: The dynamic trend scoring system evaluates price action over time, providing a probabilistic measure of market momentum to confirm the strength and direction of a trend.
⚡️ How to Use
✅ Add the Indicator: Add the Dynamic Score PSAR to your favourites, then to your chart and adjust the PSAR settings, window length, and trend thresholds to match your preferences. Customize the sensitivity to price movements by tweaking the window length and thresholds for different market conditions.
👀 Monitor Trend Shifts: Watch for trend changes as the normalized PSAR values cross key thresholds, and use the dynamic score to confirm the strength and direction of trends. Bar coloring and background fills visually highlight key moments for trend shifts, making it easier to spot reversals.
🔔 Set Alerts: Configure alerts for significant trend crossovers and reversals, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Dynamic Score PSAR by QuantAlgo is a powerful tool that combines traditional trend-following techniques with the flexibility of a dynamic trend scoring system. This innovative approach provides clearer, more adaptive trend signals, reducing the risk of false entries and exits while helping traders and investors capture significant market moves. The ability to adjust the indicator’s sensitivity and thresholds makes it versatile across different trading and investing environments, whether you’re focused on short-term pivots or long-term trend reversals. To maximize its effectiveness, fine-tune the sensitivity settings based on current market conditions and use the visual cues to confirm trend shifts.
Gauss IndicatorGauss Indicator
Class : oscillator
Trading type : any
Time frame : any
Purpose : reversal trading
Level of aggressiveness : any
About Gauss Indicator
Time series forecasting is quite a scientific task, for which specific econometrical models and methods have been developed.
Who is Gauss and Why his Curve is So Important
Johann Gauss was one of the best mathematicians of all times and he gave us a very specific curve (Gaussian Curve) to explain specifics of random variable behavior (so called Normal Distribution)
Gaussian curve has quite interesting property usually called “3 Sigmas Rule”: in a normal distribution: 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.
But Does It Work in the Financial Markets?
Normal Distribution is extremely typical for price behavior in financial markets: FOREX, stock Market, Commodities, Cryptocurrency market.
How can we forecast future prices based on “3 Sigmas Rule”?
If we know past prices (we actually know), we can calculate Mean and Standard Deviation.
After that following “3 Sigmas Rules” we can calculate the fluctuations range for the present day with a known probability (!).
• If we add 1 sigma to mean we can get the price value that wouldn’t be exceeded with a probability of 68%.
• If we add 2 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 95%.
• If we add 3 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 99%.
How Can I Get This Information?
Gauss indicator is a practical implementation of “3 sigmas rule” in trading.
Gauss allows to predict the ranges of price fluctuations for the selected time frames (week, day, hour, etc) with certain probabilities: 68%, 95% and 99%.
Gauss can be used to generate Trading signals, Stop-loss parameters, Take-profit parameters, Synthetic Levels (both Support and Resistance).
Actually, ALL information you need to trade.
Structure of the Gauss Indicator
1. Three blue lines – synthetic support lines. They describe 3 different buy zones with certain probabilities of success:
- First blue line (Buy zone #1) - the price today will not fall below this mark with a probability of 68%;
- Second blue line (Buy zone #2) - the price today will not fall below this mark with a probability of 95%;
- Third blue line (Buy zone #3) - the price today will not fall below this mark with a probability of 99%.
2. Three red lines – synthetic resistance lines. They describe 3 different sell zones with certain probabilities of success:
- First red line (Sell zone #1) - the price today will not rise above this mark with a probability of 68%;
- Second red line (Sell zone #2) - the price today will not rise above this mark with a probability of 95%;
- Third red line (Sell zone #3) - the price today will not rise above this mark with a probability of 99%.
3. Green line – shows current price. When it gets close to the red/blue line sell/buy signals are generated.
Trading rules
General rules are as follows: buy at the blue lines, sell at the red lines.
Take-profits for sells are set at the nearest blue line, for buys – at the nearest red line. Stop-losses for sells are set above the last red line, for buys – below the last blue line.
Overbought & Oversold Oscillator - By CryptoEasonThis is an overbought/oversold indicator that combines EMA / ATR / RSI and Bollinger Bands.
Overbought Definition:
When the RSI is greater than 70, and the price is above EMA20 + 2.5 * ATR.
When the price meets the overbought condition, the oscillator value will exceed 40, and a red bar will be displayed on the chart.
Oversold Definition:
When the RSI is less than 30, and the price is below EMA20 - 2.5 * ATR.
When the price meets the oversold condition, the oscillator value will drop below -40, and a green bar will be displayed on the chart.
The default average price used is EMA20, but you can modify it to SMA20 or adjust the length in the settings.
The default RSI length is set to 14, but this can also be customized. You can also adjust the ATR overbought/oversold multiplier in the settings, for example, setting it to 3.
Bollinger Bands:
The Bollinger Bands are used as a supplementary tool.
When the price is overbought and above the upper Bollinger Band, a red dot will be displayed.
When the price is oversold and below the lower Bollinger Band, a green dot will be displayed.
Buy and Sell Signals:
When the price moves from an overbought condition to a non-overbought condition, a sell signal is generated.
When the price moves from an oversold condition to a non-oversold condition, a buy signal is generated.
Altcoin Buy/Sell Signals:
In crypto markets, we usually view the bitcoin chart, so for the reason of convenience, I have also included altcoins buy and sell signals for 15 different altcoins. The default list includes: ETH / SOL / AVAX / DOT / APT / NEAR / ADA / SUI / MATIC / OP / PEPE / BLUR / GLMR / ASTR / APE.
You can customize these 15 altcoin pairs in the settings to any altcoins you prefer. When a buy or sell signal appears for one of these altcoins, you can quickly switch to its chart to view the signal. This is for convenience, so you don't need to check each chart's overbought/oversold status one by one; you only need to view the charts when a signal appears.
Reminder:
The overbought/oversold indicator works best in ranging markets. Use carefully when applying this indicator in a trending market. During trends, the price can keep remaining at overbought / oversold level.
Note:
If you think this indicator should have additional features that are currently not available, feel free to leave a comment and let me know.
=============== 中文說明（Chinese Introduction）===============
這是一個超買超賣指標，該指標結合了 EMA / ATR / RSI 與 Bollinger Bands。
我將超買定義為：
當RSI大於70，且價格大於 EMA20 + 2.5*ATR
當價格符合超買定義時，此時振盪器的值會大於40，並在圖表上顯示紅柱。
我將超賣定義為：
RSI < 30 且價格小於 EMA20 - 2.5 * ATR
當價格符合超賣定義時，此時振盪器的值為低於-40，並在圖表上顯示綠柱。
平均價格使用的是EMA20，但你可以在設定中修改成SMA20，或是其它長度。
預設RSI長度為14，你可以在設定中修改成其它參數。
你也可以在設定中將 ATR 超買超賣乘數改成其他倍數，例如3。
Bollinger Bands 在這個指標中的作用為輔助，當價格位於超買且在布林帶上邊界之外，會顯示紅點，當價格位於超賣且價格低於布林帶下邊界之外，會顯示綠點。
超指標還提供了買入與賣出信號：
當價格從超買狀態變為非超買狀態時，顯示賣出信號。
當價格從超賣狀態變為非超賣狀態時，顯示買入信號。
我還再這個指標上加入了山寨幣的買入賣出信號，一共十五組，預設為：
ETH / SOL / AVAX / DOT / APT /NEAR / ADA / SUI / MATIC / OP / PEPE / BLUR / GLMR / ASTR / APE
你可以客製化這十五組山寨幣的標的，在設定中修改成你喜歡的山寨幣。
當你在圖表上發現了某個山寨幣出現買入賣出信號，你可以迅速切換圖表到該山寨幣圖表上，提供這個山寨幣買入賣出信號，僅僅是為了方便性，讓你不用逐一檢查每個圖表的超買超賣狀態，僅在出現信號再查看即可。
提醒：
超買超賣指標比較適合用在震盪行情，當趨勢行情來臨時，需要謹慎使用這個超買超賣指標。
因為當趨勢來臨時，價格可以一直處在超買狀態或超賣狀態。
註：
如果你認為這個指標應該多增加什麼功能，但是目前沒有，歡迎留言告訴我。
RSI (Kernel Optimized) | Flux Charts💎 GENERAL OVERVIEW
Introducing our new KDE Optimized RSI Indicator! This indicator adds a new aspect to the well-known RSI indicator, with the help of the KDE (Kernel Density Estimation) algorithm, estimates the probability of a candlestick will be a pivot or not. For more information about the process, please check the "HOW DOES IT WORK ?" section.
Features of the new KDE Optimized RSI Indicator :
A New Approach To Pivot Detection
Customizable KDE Algorithm
Realtime RSI & KDE Dashboard
Alerts For Possible Pivots
Customizable Visuals
❓ HOW TO INTERPRET THE KDE %
The KDE % is a critical metric that reflects how closely the current RSI aligns with the KDE (Kernel Density Estimation) array. In simple terms, it represents the likelihood that the current candlestick is forming a pivot point based on historical data patterns. a low percentage suggests a lower probability of the current candlestick being a pivot point. In these cases, price action is less likely to reverse, and existing trends may continue. At moderate levels, the possibility of a pivot increases, indicating potential trend shifts or consolidations.Traders should start monitoring closely for confirmation signals. An even higher KDE % suggests a strong likelihood that the current candlestick could form a pivot point, which could lead to a reversal or significant price movement. These points often align with overbought or oversold conditions in traditional RSI analysis, making them key moments for potential trade entry or exit.
📌 HOW DOES IT WORK ?
The RSI (Relative Strength Index) is a widely used oscillator among traders. It outputs a value between 0 - 100 and gives a glimpse about the current momentum of the price action. This indicator then calculates the RSI for each candlesticks, and saves them into an array if the candlestick is a pivot. The low & high pivot RSIs' are inserted into two different arrays. Then the a KDE array is calculated for both of the low & high pivot RSI arrays. Explaining the KDE might be too much for this write-up, but for a brief explanation, here are the steps :
1. Define the necessary options for the KDE function. These are : Bandwidth & Nº Steps, Array Range (Array Max - Array Min)
2. After that, create a density range array. The array has (steps * 2 - 1) elements and they are calculated by (arrMin + i * stepCount), i being the index.
3. Then, define a kernel function. This indicator has 3 different kernel distribution modes : Uniform, Gaussian and Sigmoid
4. Then, define a temporary value for the current element of KDE array.
5. For each element E in the pivot RSI array, add "kernel(densityRange.get(i) - E, 1.0 / bandwidth)" to the temporary value.
6. Add 1.0 / arrSize * to the KDE array.
Then the prefix sum array of the KDE array is calculated. For each candlestick, the index closest to it's RSI value in the KDE array is found using binary search. Then for the low pivot KDE calculation, the sum of KDE values from found index to max index is calculated. For the high pivot KDE, the sum of 0 to found index is used. Then if high or low KDE value is greater than the activation threshold determined in the settings, a bearish or bullish arrow is plotted after bar confirmation respectively. The arrows are drawn as long as the KDE value of current candlestick is greater than the threshold. When the KDE value is out of the threshold, a less transparent arrow is drawn, indicating a possible pivot point.
🚩 UNIQUENESS
This indicator combines RSI & KDE Algorithm to get a foresight of possible pivot points. Pivot points are important entry, confirmation and exit points for traders. But to their nature, they can be only detected after more candlesticks are rendered after them. The purpose of this indicator is to alert the traders of possible pivot points using KDE algorithm right away when they are confirmed. The indicator also has a dashboard for realtime view of the current RSI & Bullish or Bearish KDE value. You can fully customize the KDE algorithm and set up alerts for pivot detection.
⚙️ SETTINGS
1. RSI Settings
RSI Length -> The amount of bars taken into account for RSI calculation.
Source -> The source value for RSI calculation.
2. Pivots
Pivot Lengths -> Pivot lengths for both high & low pivots. For example, if this value is set to 21; 21 bars before AND 21 bars after a candlestick must be higher for a candlestick to be a low pivot.
3. KDE
Activation Threshold -> This setting determines the amount of arrows shown. Higher options will result in more arrows being rendered.
Kernel -> The kernel function as explained in the upper section.
Bandwidth -> The bandwidth variable as explained in the upper section. The smoothness of the KDE function is tied to this setting.
Nº Bins -> The Nº Steps variable as explained in the upper section. It determines the precision of the KDE algorithm.
FloWave Oscillator [StabTrading]The FloWave Oscillator is a powerful trading tool designed to identify market trends and reversals by analysing reversal zones based on momentum and fear algorithms.
Serving as the first stage in a comprehensive trading system, it is intentionally straightforward, allowing traders to clearly see potential entry points across all charts and timeframes.
By inputting their own market sentiment, traders can customize the algorithm to align with their trading style. This flexibility helps traders navigate complex market environments with greater precision, whether they are seeking to capitalize on short-term opportunities or ride longer-term trends.
💡 Features
Reversal Zones - The FloWave Oscillator identifies key reversal zones driven by momentum and fear dynamics. Lighter green zones signal the initial stages of a potential reversal, while darker green zones indicate that a trend flip is imminent.
Trading Style Customization - The indicator allows traders to adjust their trading style with sensitivity settings ranging from Very Aggressive to Very Conservative. This flexibility lets traders tailor the indicator to their preferred time horizon—whether they seek to scalp short-term opportunities or capture long-term reversals.
🔥 Sensitivity Settings
Very Aggressive/Aggressive - These settings increase the indicator's sensitivity, generating more frequent signals, ideal for traders focused on short-term gains or those navigating choppy markets.
Neutral - Offers a balanced approach, combining both aggressive and conservative elements. It's a starting point for traders to evaluate performance before adjusting to more specific styles.
Conservative/Very Conservative - These settings reduce signal frequency, focusing on stronger, more reliable reversals. Best suited for long-term traders aiming to minimize risk and avoid premature market entries or exits.
🛠️ Usage/Practice
In the above example we’ll analysis how the indicator accurately predicts both the tops and bottoms of a market cycle.
Top of the Bull Market - The trendline initially shows two light red reversal zones, signalling a potential weakening in the upward momentum. As the trend progresses, a dark red zone emerges, confirming that a more substantial trend reversal to the downside is likely. This sequence provides an early warning, allowing traders to prepare for a possible market shift.
First Bull Signal - In the following phase, the indicator mirrors the previous action but in the opposite direction, identifying a reversal towards the upside. This behaviour demonstrates the indicator's ability to adapt to changing market conditions.
Bottom of the Bear Market - As the market continues its downward trajectory, the indicator presents two dark green reversal zones, highlighting areas where the selling pressure may be easing. These dark green zones offer three distinct opportunities to dollar-cost average (DCA) into the asset, allowing traders to build or enhance their positions during the end of the bear cycle. The indicator’s sensitivity in this phase ensures that traders can navigate the bearish market with confidence.
Continuation of Bull Cycle - In this segment, the indicator does not display any dark green reversal zones, implying that the uptrend remains robust. The absence of these zones suggests that the upward momentum is likely to continue, providing traders with another opportunity to add to their long positions. This scenario underscores the indicator’s capacity to identify when a trend is strong enough to warrant additional investment.
Potential Correction in an Uptrend - A light red zone appears, signalling a possible correction within the ongoing uptrend. However, the absence of a dark red zone indicates that the correction may be minor and that the overall trend is still upward. Traders might view this as a conservative point to take some profits off the table, managing risk while staying aligned with the broader bull market.
Bearish Signal - Eventually, a dark red reversal zone emerges, indicating that the trend has lost its upward momentum. This signal serves as a strong indicator that the uptrend may be concluding, prompting traders to consider exiting their positions or taking a more defensive stance. As the market enters a sideways phase, the trader can switch to a more aggressive trading style, seeking opportunities to scalp within the range while navigating the flat market conditions.
In this example, we demonstrate how to identify scalp trading opportunities by combining the Very Conservative and Very Aggressive settings. The key strategy is to use the Very Conservative trend to confirm the validity of reversal zones identified by the Very Aggressive setting.
The VC trend doesn’t indicate a buy reversal zone, but it shows an upward divergence. This suggests that the reversal buy zone on the VA chart is a potential entry point due to the supportive VC trend.
Multiple sell zones appear on the VA chart, but the VC trend shows a strong and steady uptrend. This suggests that we should wait for confirmation from the VC trend before considering a sell position, as the market is still moving upward strongly.
The VA chart shows several buy zones, but the VC trend indicates a strong downtrend, and no buy zone appears on the conservative setting. This suggests waiting for the next VA buy zone, confirmed by an upward divergence on the VC trend, before entering a trade.
Similar to Point 3 but in the opposite direction, the VA chart shows sell zones, but the VC trend indicates caution. The strategy would be to wait for confirmation from the VC trend before making a move.
🔶Conclusion
When used in conjunction with other indicators like the MeanRevert Matrix, the FloWave Oscillator becomes an integral part of a comprehensive trading system. It helps traders make informed decisions by providing clear signals that are aligned with the current market sentiment and broader economic trends. By following the implementation guidelines and adjusting the indicator settings as market conditions change, traders can effectively enhance their trading performance.
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.
GannLSVZO Indicator [Algo Alert]The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and Exits (orange X) and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swings and the Gan swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Nautilus Oscillator [BigBeluga]NAUTILUS OSCILLATOR
The Nautilus Oscillator by BigBeluga is an advanced technical analysis tool designed to help traders identify trend direction, strength, and potential reversal points in the market. This versatile indicator combines multiple analytical elements to provide a comprehensive view of market conditions.
Why It’s Unique:
The Nautilus Oscillator is unique too, its blend of multiple technical analysis tools into a single, coherent indicator.
By smoothing with a unique and highly valued in signal processing filter, and incorporating dynamic thresholds, this oscillator offers a more refined and adaptable approach to identifying trading signals.
The filter is designed to have as flat a frequency response as possible in the passband. This means that within the range of frequencies it allows through, minimizes distortion and maintains the true shape of the signal more accurately than many other types of filters.
The addition of a trend filter and divergence detection further enhances its capability, making it a versatile tool for both trend-following and reversal strategies. The built-in dashboard and clean chart management features provide traders with a streamlined, informative, and visually appealing trading experience. This makes the Nautilus Oscillator not just a tool for analysis but a comprehensive trading system in itself.
🔵 KEY FEATURES
● Main Oscillator Line
Smoothly transitions between bullish (green) and bearish (purple) colors
Helps visualize mean-reversion, market trend, and momentum
● Histogram
Displayed below the main oscillator line
Represents the rate of change of the main oscillator
Acts as a leading indicator, often showing changes faster than the main oscillator line
Can be viewed as a predictive element, potentially indicating future movements of the main oscillator
Histogram crossover signals (small dots) can indicate short-term momentum shifts
Useful for early detection of potential trend changes or momentum shifts
● Confluence Arrows
Arrows displayed above and below the oscillator
Provide additional confluence signals that work in conjunction with the histogram
Act as supplementary indicators to confirm the main oscillator signals
Help in identifying stronger, more reliable trading opportunities when aligned with other indicator elements
● Trend Filter
Displayed as horizontal lines above and below the oscillator
Upper lines (above the oscillator): Indicate an uptrend
Lower lines (below the oscillator): Indicate a downtrend
Three lines appear when a strong trend is present
Only one line is displayed when there's no trend
Color-coded for easy identification (typically green for up, purple for down)
Color intensity indicates the strength of the trend. More intensive color indicates stronger trend
Provides a clear visual representation of the overall market trend
Helps traders align their strategies with the broader market direction
● Overbought/Oversold Thresholds
Can be set to static levels or dynamically adjust based on market volatility
Helps identify potential reversal points in the market
● Signals
Strong signals: Displayed as circles on both the oscillator and main chart (optional)
Simple signals: Shown as X marks on both the oscillator and main chart (optional)
Histogram crossover signals: Small dots on the histogram
● Stop Levels
Optional feature that plots potential stop-loss levels for strong signals
Based on the Market volatility for adaptability to different market conditions
● Divergences
Identifies and displays bullish and bearish divergences between price and the oscillator
Helps spot potential trend reversals
● Dashboard
Provides at-a-glance information about current market conditions
Displays trend direction, last signal, histogram direction, threshold mode, and divergence status
🔵 HOW TO USE
● Trend Identification
Use the main oscillator line color and position, along with the trend filter lines, to determine the overall market trend
● Entry Signals
Strong signals (circles) suggest potential entry points in the direction of the trend
Simple signals (X marks) can be used for more frequent, but potentially less reliable, entry opportunities
Histogram crossover signals (dots) can indicate changes faster than the main oscillator line
Look for alignment with confluence arrows for stronger entry signals
● Exit Signals
Use the overbought/oversold thresholds as potential enter and exit points
Stop levels (if enabled) provide dynamic exit points for risk management
● Reversal Identification
Watch for divergences between price and the oscillator for potential trend reversals
Pay attention to the histogram direction for early signs of momentum shifts
Notice changes in the trend filter lines (from three lines to one, or vice versa)
● Confirmation
Use the dashboard to quickly confirm the current market state and indicator readings
Combine signals from different elements (main line, histogram, trend filter, confluence arrows) for stronger confirmation
🔵 CUSTOMIZATION
The Nautilus Oscillator offers several customization options to suit different trading styles:
Adjust the main oscillator length
Set static or dynamic overbought/oversold thresholds
Enable/disable and customize stop levels
Toggle divergence display and adjust its parameters
Show/hide the information dashboard
Display simple signals on the main chart
By fine-tuning these settings, traders can adapt the Nautilus Oscillator to various market conditions and personal trading strategies.
The Nautilus Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and reversal detection in one comprehensive tool. Its visual cues and customizable features make it suitable for both novice and experienced traders across various timeframes and markets. The integration of multiple analytical elements – including the predictive histogram, confluence arrows, and adaptive trend filter – offers traders a rich set of data points to inform their trading decisions.
DSL Oscillator [BigBeluga]DSL Oscillator BigBeluga
The DSL (Discontinued Signal Lines) Oscillator is an advanced technical analysis tool that combines elements of the Relative Strength Index (RSI), Discontinued Signal Lines, and Zero-Lag Exponential Moving Average (ZLEMA). This versatile indicator is designed to help traders identify trend direction, momentum, and potential reversal points in the market.
What are Discontinued Signal Lines (DSL)?
Discontinued Signal Lines are an extension of the traditional signal line concept used in many indicators. While a standard signal line compares an indicator's value to its smoothed (slightly lagging) state, DSL takes this idea further by using multiple adaptive lines that respond to the indicator's current value. This approach provides a more nuanced view of the indicator's state and momentum, making it easier to determine trends and desired states of the indicator.
🔵 KEY FEATURES
● Discontinued Signal Lines (DSL)
Uses multiple adaptive lines that respond to the indicator's value
Provides a more nuanced view of the indicator's state and momentum
Helps determine trends and desired states of the indicator more effectively
Available in "Fast" and "Slow" modes for different responsiveness
Acts as dynamic support and resistance levels for the oscillator
● DSL Oscillator
Based on a combination of RSI and Discontinued Signal Lines
// Discontinued Signal Lines
dsl_lines(src, length)=>
UP = 0.
DN = 0.
UP := (src > ta.sma(src, length)) ? nz(UP ) + dsl_mode / length * (src - nz(UP )) : nz(UP )
DN := (src < ta.sma(src, length)) ? nz(DN ) + dsl_mode / length * (src - nz(DN )) : nz(DN )
Smoothed using Zero-Lag Exponential Moving Average for reduced lag
// Zero-Lag Exponential Moving Average function
zlema(src, length) =>
lag = math.floor((length - 1) / 2)
ema_data = 2 * src - src
ema2 = ta.ema(ema_data, length)
ema2
Oscillates between 0 and 100
Color-coded for easy interpretation of market conditions
● Signal Generation
Generates buy signals when the oscillator crosses above the lower DSL line below 50
Generates sell signals when the oscillator crosses below the upper DSL line above 50
Signals are visualized on both the oscillator and the main chart
● Visual Cues
Background color changes on signal occurrences for easy identification
Candles on the main chart are colored based on the latest signal
Oscillator line color changes based on its position relative to the DSL lines
🔵 HOW TO USE
● Trend Identification
Use the color and position of the DSL Oscillator relative to its Discontinued Signal Lines to determine the overall market trend
● Entry Signals
Look for buy signals (green circles) when the oscillator crosses above the lower DSL line
Look for sell signals (blue circles) when the oscillator crosses below the upper DSL line
Confirm signals with the triangles on the main chart and background color changes
● Exit Signals
Consider exiting long positions on exit signals and short positions on Entery signals
Watch for the oscillator crossing back between the DSL lines as a potential early exit signal
● Momentum Analysis
Strong momentum is indicated when the oscillator moves rapidly towards extremes and away from the DSL lines
Weakening momentum can be spotted when the oscillator struggles to reach new highs or lows, or starts converging with the DSL lines
The space between the DSL lines can indicate potential momentum strength - wider gaps suggest stronger trends
● Confirmation
Use the DSL lines as dynamic support/resistance levels for the oscillator
Look for convergence between oscillator signals and price action on the main chart
Combine signals with other technical indicators or chart patterns for stronger confirmation
🔵 CUSTOMIZATION
The DSL Oscillator offers several customization options:
Adjust the main calculation length for the DSL lines
Choose between "Fast" and "Slow" modes for the DSL lines calculation
By fine-tuning these settings, traders can adapt the DSL Oscillator to various market conditions and personal trading strategies.
The DSL Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and signal generation in one comprehensive tool. Its dynamic nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of RSI, Discontinued Signal Lines, and ZLEMA offers traders a sophisticated yet intuitive tool to inform their trading decisions.
The use of Discontinued Signal Lines sets this oscillator apart from traditional indicators by providing a more adaptive and nuanced view of market conditions. This can potentially lead to more accurate trend identification and signal generation, especially in markets with varying volatility.
Traders can use the DSL Oscillator to identify trends, spot potential reversals, and gauge market momentum. The combination of the oscillator, dynamic signal lines, and clear visual signals provides a holistic view of market conditions. As with all technical indicators, it's recommended to use the DSL Oscillator in conjunction with other forms of analysis and within the context of a well-defined trading strategy.
S&P Short-Range Oscillator**SHOULD BE USED ON THE S&P 500 ONLY**
The S&P Short-Range Oscillator (SRO), inspired by the principles of Jim Cramer's oscillator, is a technical analysis tool designed to help traders identify potential buy and sell signals in the stock market, specifically for the S&P 500 index. The SRO combines several market indicators to provide a normalized measure of market sentiment, assisting traders in making informed decisions.
The SRO utilizes two simple moving averages (SMAs) of different lengths: a 5-day SMA and a 10-day SMA. It also incorporates the daily price change and market breadth (the net change of closing prices). The 5-day and 10-day SMAs are calculated based on the closing prices. The daily price change is determined by subtracting the opening price from the closing price. Market breadth is calculated as the difference between the current closing price and the previous closing price.
The raw value of the oscillator, referred to as SRO Raw, is the sum of the daily price change, the 5-day SMA, the 10-day SMA, and the market breadth. This raw value is then normalized using its mean and standard deviation over a 20-day period, ensuring that the oscillator is centered and maintains a consistent scale. Finally, the normalized value is scaled to fit within the range of -15 to 15.
When interpreting the SRO, a value below -5 indicates that the market is potentially oversold, suggesting it might be a good time to start buying stocks as the market could be poised for a rebound. Conversely, a value above 5 suggests that the market is potentially overbought. In this situation, it may be prudent to hold on to existing positions or consider selling if you have substantial gains.
The SRO is visually represented as a blue line on a chart, making it easy to track its movements. Red and green horizontal lines mark the overbought (5) and oversold (-5) levels, respectively. Additionally, the background color changes to light red when the oscillator is overbought and light green when it is oversold, providing a clear visual cue.
By incorporating the S&P Short-Range Oscillator into your trading strategy, you can gain valuable insights into market conditions and make more informed decisions about when to buy, sell, or hold your stocks. However, always consider other market factors and perform your own analysis before making any trading decisions.
The S&P Short-Range Oscillator is a powerful tool for traders looking to gain insights into market sentiment. It provides clear buy and sell signals through its combination of multiple indicators and normalization process. However, traders should be aware of its lagging nature and potential complexity, and use it in conjunction with other analysis methods for the best results.
Disclaimer
The S&P Short-Range Oscillator is for informational purposes only and should not be considered financial advice. Trading involves risk, and you should conduct your own research or consult a financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Use at your own risk.
ATH/ATL Tracker [LuxAlgo]The ATH/ATL Tracker effectively displays changes made between new All-Time Highs (ATH)/All-Time Lows (ATL) and their previous respective values, over the entire history of available data.
The indicator shows a histogram of the change between a new ATH/ATL and its respective preceding ATH/ATL. A tooltip showing the price made during a new ATH/ATL alongside its date is included.
🔶 USAGE
By tracking the change between new ATHs/ATLs and older ATHs/ATLs, traders can gain insight into market sentiment, breadth, and rotation.
If many stocks are consistently setting new ATHs and the number of new ATHs is increasing relative to old ATHs, it could indicate broad market participation in a rally. If only a few stocks are reaching new ATHs or the number is declining, it might signal that the market's upward momentum is decreasing.
A significant increase in new ATHs suggests optimism and willingness among investors to buy at higher prices, which could be considered a positive sentiment. On the other hand, a decrease or lack of new ATHs might indicate caution or pessimism.
By observing the sectors where stocks are consistently setting new ATHs, users can identify which sectors are leading the market. Sectors with few or no new ATHs may be losing momentum and could be identified as lagging behind the overall market sentiment.
🔶 DETAILS
The indicator's main display is a histogram-style readout that displays the change in price from older ATH/ATLs to Newer/Current ATH/ATLs. This change is determined by the distance that the current values have overtaken the previous values, resulting in the displayed data.
The largest changes in ATH/ATLs from the ticker's history will appear as the largest bars in the display.
The most recent bars (depending on the selected display setting) will always represent the current ATH or ATL values.
When determining ATH & ATL values, it is important to filter out insignificant highs and lows that may happen constantly when exploring higher and lower prices. To combat this, the indicator looks to a higher timeframe than your chart's timeframe in order to determine these more significant ATHs & ATLs.
For Example: If a user was on a 1-minute chart and 5 highs-new highs occur across 5 adjacent bars, this has the potential to show up as 5 new ATHs. When looking at a higher timeframe, 5 minutes, only the highest of the 5 bars will indicate a new ATH. To assist with this, the indicator will display warnings in the dashboard when a suboptimal timeframe is selected as input.
🔹 Dashboard
The dashboard displays averages from the ATH/ATL data to aid in the anticipation and expectations for new ATH/ATLs.
The average duration is an average of the time between each new ATH/ATL, in this indicator it is calculated in "Days" to provide a more comprehensive understanding.
The average change is the average of all change data displayed in the histogram.
🔶 SETTINGS
Duration: The designated higher timeframe to use for filtering out insignificant ATHs & ATLs.
Order: The display order for the ATH/ATL Bars, Options are to display in chronological (oldest to newest) or reverse chronological order (newest to oldest).
Bar Width: Sets the width for each ATH/ATL bar.
Bar Spacing: Sets the # of empty bars in between each ATH/ATL bar.
Dashboard Settings: Parameters for the dashboard's size and location on the chart.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
Relative Momentum Index with Laguerre FilterThe Relative Momentum Index
The Relative Momentum Index (RMI) is an oscillator that is a variation of the Relative Strength Index (RSI), but incorporates momentum over a variable lookback period rather than just consecutive price changes, which can help identify reversals and filter out noise.
It measures the momentum of price changes over a specified period, rather than just the magnitude of price changes like the RSI does.
It counts up and down days from the current closing price relative to the closing price a certain number of days ago (e.g. 5 days ago), instead of just comparing consecutive daily closes like the RSI
It is calculated by taking the ratio of the average upward price changes to the average downward price changes over a given period, where each change is measured from the close X days ago (X is the “momentum” period)
Like the RSI, the RMI oscillates between 0 and 100, with readings above 70 considered overbought and below 30 oversold.
In trending markets, the RMI tends to remain in overbought or oversold territory for extended periods. In trading ranges, it oscillates more predictably between the overbought and oversold levels.
The RMI is generally considered better than the RSI at identifying potential reversal points, as it incorporates a momentum factor rather than just strength.
It can be used in a similar way to the RSI for trade signals, such as buying when it rises above 30 from below, or selling when it falls below 70 from above
The Laguerre filter
A Laguerre filter is a type of infinite impulse response (IIR) filter used for smoothing signals or data. The Laguerre filter provides a way to apply variable smoothing to a signal by adjusting its pole position, allowing you to control the balance between smoothness and lag based on your preferences. It is an alternative to simple moving averages that can better preserve the shape of the original signal.
