Deviation Adjusted MA Overview
The Deviation Adjusted MA is a custom indicator that enhances traditional moving average techniques by introducing a volatility-based adjustment. This adjustment is implemented by incorporating the standard deviation of price data, making the moving average more adaptive to market conditions. The key feature is the combination of a customizable moving average (MA) type and the application of deviation percentage to modify its responsiveness. Additionally, a smoothing layer is applied to reduce noise, improving signal clarity.
Key Components
Customizable Moving Averages
The script allows the user to select from four different types of moving averages:
Simple Moving Average (SMA): A basic average of the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to recent price changes.
Weighted Moving Average (WMA): Weights prices differently, favoring more recent ones but in a linear progression.
Volume-Weighted Moving Average (VWMA): Adjusts the average by trading volume, placing more weight on high-volume periods.
Standard Deviation Calculation
The script calculates the standard deviation of the closing prices over the selected maLength period.
Standard deviation measures the dispersion or volatility of price movements, giving a sense of market volatility.
Deviation Percentage and Adjustment
Deviation Percentage is calculated by dividing the standard deviation by the base moving average and multiplying by 100 to express it as a percentage.
The base moving average is adjusted by this deviation percentage, making the indicator responsive to changes in volatility. The result is a more dynamic moving average that adapts to market conditions.
The parameter devMultiplier is available to scale this adjustment, allowing further fine-tuning of sensitivity.
Smoothing the Adjusted Moving Average
After adjusting the moving average based on deviation, the script applies an additional Exponential Moving Average (EMA) with a length defined by the smoothingLength input.
This EMA serves as a smoothing filter to reduce the noise that could arise from the raw adjustments of the moving average. The smoothing makes trend recognition more consistent and removes short-term fluctuations that could otherwise distort the signal.
Use cases
The Deviation Adjusted MA indicator serves as a dynamic alternative to traditional moving averages by adjusting its sensitivity based on volatility. The script offers extensive customization options through the selection of moving average type and the parameters controlling smoothing and deviation adjustments.
By applying these adjustments and smoothing, the script enables users to better track trends and price movements, while providing a visual cue for changes in market sentiment.
Volatility
Kijun_ATROVERVIEW
Kijun + ATR is an indicator that combines Lagging Kijun Base Line From Ichimoku Cloud (direction indicator) and Volatility Indicator ATR.
By combining ATR with kijun we can filter out noise from Base Line.
CALCULATIONS
Kijun is calculated by taking average of lowest and highest point of price over set lenght.
ATR is just default Tradingview Indicator that calculates average true range of price over set period of time.
WORKING
When both close > lower and not close < upper are true indicator indicate long by color limeand indicates short when close < upper by color fuchsia (Color can be changed in settings)
Indicator works best in Trending Market Regimes can have problems by signaling tops in Consolidating Market Regimes during bear markets and by sygnaling bottom in short consolidating market regimes during bull market.
TRIN (Arms Index) Trading StrategyThe TRIN (Arms Index), also known as the Short-Term Trading Index, is a technical indicator designed to gauge the internal strength or weakness of the market. It compares the number of advancing and declining stocks to the advancing and declining volume (AD Volume). A TRIN value above 1.0 generally indicates bearish market conditions, while a value below 1.0 suggests bullish market sentiment.
Strategy Rules:
Entry Condition (Long Position): When the TRIN value is above 1.0, the strategy enters a long position, indicating that the market may be oversold, and a potential reversal could occur.
Exit Condition: The strategy exits the long position when the closing price is higher than the previous day’s high, signaling a potential rebound in the market.
This strategy aims to capitalize on short-term market inefficiencies by entering trades during periods of potential market weakness and exiting when signs of recovery appear.
How the TRIN Index Works:
The TRIN is calculated as follows:
TRIN=Advancing Issues / Declining IssuesAdvancing Volume / Declining Volume
TRIN=Advancing Volume / Declining VolumeAdvancing Issues / Declining Issues
A TRIN value above 1.0 indicates that the market is potentially oversold (more declining stocks with higher volume), while a value below 1.0 suggests the market may be overbought (more advancing stocks with higher volume) .
Empirical Evidence:
Market Sentiment Indicator: The TRIN has been widely used as a sentiment indicator. Research by Zweig (1997) suggests that extreme TRIN values can serve as a contrarian signal, indicating potential turning points in the market. For instance, a TRIN above 2.0 is often considered a sign of panic selling, which can precede a market bottom .
Overbought/Oversold Conditions: Studies have shown that indicators like TRIN, which measure market breadth and volume, can be effective in identifying overbought and oversold conditions. According to Fama and French (1988), market sentiment indicators that consider both price and volume data can offer insights into future price movements .
Risks and Limitations:
False Signals:
One of the primary risks of using the TRIN-based strategy is the possibility of false signals. A TRIN value above 1.0 does not always guarantee a market rebound, especially in sustained bearish trends. In such cases, the strategy might enter long positions prematurely, leading to losses.
Research by Brock, Lakonishok, and LeBaron (1992) found that while market indicators like TRIN can be useful, they are not foolproof and can generate multiple false positives, particularly in volatile markets .
Market Regimes:
The effectiveness of the TRIN index can vary depending on the market regime. In strongly trending markets, either bullish or bearish, the TRIN may not provide reliable reversal signals, and relying on it could result in trades that go against the prevailing trend. For instance, during strong bear markets, the TRIN may frequently remain above 1.0, leading to multiple losing trades as the market continues to decline.
Short-Term Focus:
The TRIN strategy is inherently short-term focused, aiming to capture quick market reversals. This makes it sensitive to market noise and less effective for longer-term investors. Moreover, short-term trading strategies often require more frequent adjustments and can incur higher transaction costs, which may erode profitability over time.
Liquidity and Execution Risk:
Since the TRIN strategy requires entering and exiting trades based on short-term market movements, it is vulnerable to liquidity and execution risks. In fast-moving markets, the execution of trades may be delayed, leading to slippage and potentially unfavorable entry or exit points.
Conclusion:
The TRIN (Arms Index) Trading Strategy can be an effective tool for traders looking to capitalize on short-term market inefficiencies and potential reversals. However, it is important to recognize the risks associated with this strategy, including false signals, sensitivity to market regimes, and execution risks. Traders should employ proper risk management techniques and consider combining the TRIN with other indicators to improve the robustness of the strategy.
While the TRIN provides valuable insights into market sentiment, it is not a standalone solution and should be used in conjunction with a broader trading plan that takes into account both technical and fundamental analysis.
References:
Arms, Richard W. "Volume Adjusted Moving Averages." Technical Analysis of Stocks & Commodities, 1993.
Zweig, Martin. Winning on Wall Street. Warner Books, 1997.
Fama, Eugene F., and Kenneth R. French. "Permanent and Temporary Components of Stock Prices." Journal of Political Economy, 1988.
Brock, William, Josef Lakonishok, and Blake LeBaron. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 1992.
Dema AFR | viResearchDema AFR | viResearch
Conceptual Foundation and Innovation
The "Dema AFR" indicator combines the Double Exponential Moving Average (DEMA) with an Average True Range (ATR)-based adaptive factor to create a responsive and adaptable trend-following system. The DEMA is known for its ability to smooth price data while reducing lag, making it highly effective for trend detection. By incorporating the ATR as a volatility factor, this indicator adapts dynamically to market conditions, allowing traders to capture trends while accounting for changes in volatility. The result is the Adaptive Factor Range (AFR), which provides clear signals for potential trend shifts and helps manage risk through its adaptive nature. This combination of DEMA smoothing and an ATR-based factor enables traders to follow trends more effectively while maintaining sensitivity to changing market conditions.
Technical Composition and Calculation
The "Dema AFR" script consists of two main components: the Double Exponential Moving Average (DEMA) and the Adaptive Factor Range (AFR). The DEMA is calculated over a user-defined length, smoothing out price fluctuations while reducing lag compared to traditional moving averages. The ATR is used to create a dynamic factor that adjusts the AFR based on market volatility. The factor is calculated by multiplying the ATR by a user-defined factor value, which scales the ATR to define upper and lower bounds for the AFR. The Adaptive Factor Range is derived from the DEMA, with upper and lower bounds set by adding or subtracting the ATR-based factor from the DEMA. When the price moves outside these bounds, the AFR is adjusted, and signals are generated. If the lower bound is exceeded, the AFR adjusts upward, while exceeding the upper bound causes the AFR to adjust downward. This dynamic adjustment helps the indicator stay responsive to market movements.
Features and User Inputs
The "Dema AFR" script provides several customizable inputs, allowing traders to tailor the indicator to their strategies. The DEMA Length controls the smoothing period for the DEMA, while the ATR Period defines the window for calculating the Average True Range. The ATR Factor determines the scale of the adaptive factor, controlling how much the AFR adjusts to volatility. Additionally, customizable bar colors and alert conditions allow traders to visualize the trend direction and receive notifications when key trend shifts occur.
Practical Applications
The "Dema AFR" indicator is designed for traders who want to capture trends while adapting to market volatility. The adaptive nature of the AFR makes it responsive to trend changes, providing early signals of potential trend reversals as the AFR adjusts to market movements. By incorporating ATR into the AFR calculation, the indicator adjusts to changing volatility, helping traders manage risk by staying aligned with market conditions. The AFR also helps confirm whether a price move is supported by momentum, improving the accuracy of trade entries and exits.
Advantages and Strategic Value
The "Dema AFR" script offers a significant advantage by combining the smoothness of the DEMA with the adaptability of the ATR-based factor. This dynamic combination allows the indicator to adjust to market conditions, providing more reliable trend signals in both trending and volatile markets. The adaptive nature of the AFR reduces the risk of false signals and helps traders stay on the right side of the trend while managing risk through volatility-adjusted ranges.
Alerts and Visual Cues
The script includes alert conditions that notify traders of key trend changes. The "Dema AFR Long" alert is triggered when the AFR indicates a potential upward trend, while the "Dema AFR Short" alert signals a potential downward trend. Visual cues such as color changes in the bar chart help traders quickly identify shifts in trend direction, allowing them to make informed decisions in real time.
Summary and Usage Tips
The "Dema AFR | viResearch" indicator provides traders with a powerful tool for trend analysis by combining DEMA smoothing with an ATR-based adaptive factor. This script helps traders stay aligned with trends while accounting for market volatility, improving their ability to detect trend reversals and manage risk. By incorporating this indicator into your trading strategy, you can make more informed decisions, whether in trending or volatile market environments. The "Dema AFR" offers a reliable and flexible solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Kalman PSaR [BackQuant]Kalman PSaR
Overview and Innovation
The Kalman PSaR combines the well-known Parabolic SAR (PSaR) with the advanced smoothing capabilities of the Kalman Filter . This innovative tool aims to enhance the traditional PSaR by integrating Kalman filtering, which reduces noise and improves trend detection. The Kalman PSaR adapts dynamically to price movements, making it a highly effective indicator for spotting trend shifts while minimizing the impact of false signals caused by market volatility.
Please Find the Basic Kalman Here:
Kalman Filter Dynamics
The Kalman Filter is a powerful algorithm for estimating the true value of a system amidst noisy data. In the Kalman PSaR, this filter is applied to the high, low, and closing prices, resulting in a smoother and more accurate representation of price action. The filter’s parameters—process noise and measurement noise—are customizable, allowing traders to fine-tune the sensitivity of the indicator to market conditions. By reducing the impact of noise, the Kalman-filtered PSaR offers clearer signals for identifying trend reversals and continuations.
Enhanced PSaR Calculation
The traditional Parabolic SAR is a popular trend-following indicator that highlights potential entry and exit points based on price acceleration. In the Kalman PSaR, this calculation is enhanced by the Kalman-filtered prices, providing a smoother and more reliable signal. The indicator continuously updates based on the acceleration factor and max step values, while the Kalman filter ensures that sudden price spikes or market noise do not trigger false signals.
Min Step and Max Step: These settings control the sensitivity of the PSaR. The Min Step sets the initial acceleration factor, while the Max Step limits how fast the PSaR adapts to price changes, helping traders fine-tune the indicator’s responsiveness.
Optional Smoothing Techniques To further enhance the signal clarity, the Kalman PSaR includes an optional smoothing feature. Traders can choose from various smoothing methods, such as SMA, Hull, EMA, WMA, TEMA, and more, to reduce short-term fluctuations and emphasize the underlying trend. The smoothing period is customizable, allowing traders to adjust the indicator’s behavior according to their preferred trading style and timeframe.
Color-Coded Candle Painting The Kalman PSaR features color-coded candles that change according to the trend direction. When the price is above the PSaR, candles are painted green to indicate a long trend, and when the price is below the PSaR, candles are painted red to signal a short trend. This visual representation makes it easy to interpret market sentiment at a glance, improving decision-making speed during fast-moving markets.
Key Features and Customization
Kalman Filter Customization: The process noise and measurement noise parameters allow traders to adjust how aggressively the filter adapts to price changes, making it suitable for both volatile and stable markets.
Smoothing Options: A variety of moving average types, such as SMA, Hull, EMA, and more, can be applied to smooth the PSaR values, ensuring that the signal remains clear even in choppy markets.
Dynamic Trend Detection: The Kalman PSaR dynamically updates based on price movements, helping traders spot trend reversals early while filtering out false signals caused by short-term volatility.
Bar Coloring and PSaR Plotting: Traders can choose to color candles based on trend direction or plot the PSaR directly on the chart for additional visual clarity.
Practical Applications
Trend-Following Strategies: The Kalman PSaR excels in trend-following strategies by providing timely signals of trend changes. The dynamic nature of the indicator allows traders to capture significant price movements while avoiding market noise.
Reversal Identification: The indicator’s ability to filter out noise and provide smoother signals makes it ideal for identifying reversals in volatile markets.
Risk Management: By plotting clear stop levels based on the PSaR, traders can use this indicator to effectively manage risk, placing stop-loss orders at key points based on the trend direction.
Conclusion
The Kalman PSaR is a fusion of the classic Parabolic SAR and the Kalman filter, offering enhanced trend detection with reduced noise. Its customizable filtering and smoothing options, combined with dynamic trend-following capabilities, make it a versatile tool for traders seeking to improve their timing and signal accuracy. The adaptive nature of the Kalman filter, combined with the robust PSaR logic, helps traders stay on the right side of the market and manage risk more effectively.
RSI Standard Deviation | viResearchRSI Standard Deviation | viResearch
The "RSI Standard Deviation" indicator, developed by viResearch, introduces a new approach to combining the Relative Strength Index (RSI) with a standard deviation measure to offer a more dynamic view of market momentum. By applying standard deviation to the RSI values, this indicator refines the traditional RSI, providing a more precise and adaptive way to measure overbought and oversold conditions. This unique combination allows traders to better understand the underlying volatility in RSI movements, leading to more informed decisions in trending and ranging markets.
Technical Composition and Calculation:
The core of the "RSI Standard Deviation" lies in calculating the RSI based on user-defined input parameters and then applying standard deviation to these RSI values. This method enhances the sensitivity of the RSI, making it more responsive to market volatility.
RSI Calculation:
RSI Length (len): The script computes the Relative Strength Index over a customizable length (default: 21), offering a traditional measure of momentum in the market. The RSI tracks the speed and change of price movements, oscillating between 0 and 100 to indicate overbought and oversold conditions.
Standard Deviation Applied to RSI:
Standard Deviation Length (sdlen): The script calculates the standard deviation of the RSI values over a user-defined period (default: 35). This standard deviation represents the volatility in RSI movements, adding a new layer of analysis to traditional RSI.
Upper (u) and Lower (d) Bands:
The standard deviation values are used to create upper and lower bands around the RSI, offering an adaptive range that expands or contracts based on market volatility. This helps traders identify moments when the market is more likely to reverse or continue its trend.
Trend Identification:
Uptrend (L): The script identifies an uptrend when the RSI moves above the lower band and stays above the midline (50). This indicates that the market is gaining upward momentum, potentially signaling a long position.
Downtrend (S): A downtrend is identified when the RSI moves below 50, suggesting a weakening market and a potential short position.
Features and User Inputs:
The "RSI Standard Deviation" script offers various customization options, enabling traders to tailor it to their specific needs and strategies:
RSI Length: Traders can adjust the length of the RSI calculation to control how quickly the indicator responds to price movements.
Standard Deviation Length: Adjusting the standard deviation length allows users to control the sensitivity of the upper and lower bands, fine-tuning the indicator’s responsiveness to market volatility.
Source Input: The script can be applied to different price sources, offering flexibility in how it calculates RSI and standard deviation values.
Practical Applications:
The "RSI Standard Deviation" indicator is particularly useful in volatile markets, where traditional RSI may produce false signals due to rapid price movements. By adding a standard deviation measure, traders can filter out noise and better identify trends.
Key Uses:
Trend Following: The standard deviation bands provide a clearer view of momentum shifts in the RSI, allowing traders to follow the trend more confidently.
Volatility Assessment: The indicator dynamically adjusts to market volatility, making it easier to assess when the market is overbought or oversold and when a trend reversal is likely.
Signal Confirmation: By comparing the RSI to the adaptive standard deviation bands, traders can confirm signals and avoid false entries during periods of high volatility.
Advantages and Strategic Value:
The "RSI Standard Deviation" offers several advantages:
Enhanced Precision: The combination of RSI and standard deviation results in a more refined momentum indicator that adapts to market conditions.
Noise Reduction: The standard deviation bands help filter out short-term market noise, making it easier to identify significant trend changes.
Dynamic Volatility Awareness: By using standard deviation, the indicator adjusts its bands based on real-time volatility, providing more accurate overbought and oversold signals.
Summary and Usage Tips:
The "RSI Standard Deviation" is a powerful tool for traders looking to enhance their RSI analysis with volatility measures. For optimal performance, traders should experiment with different RSI and standard deviation lengths to suit their trading timeframe and strategy. Whether used to follow trends or confirm momentum signals, the "RSI Standard Deviation" provides a reliable and adaptive solution for modern trading environments.
Black-Scholes option price model & delta hedge strategyBlack-Scholes Option Pricing Model Strategy
The strategy is based on the Black-Scholes option pricing model and allows the calculation of option prices, various option metrics (the Greeks), and the creation of synthetic positions through delta hedging.
ATTENTION!
Trading derivative financial instruments involves high risks. The author of the strategy is not responsible for your financial results! The strategy is not self-sufficient for generating profit! It is created exclusively for constructing a synthetic derivative financial instrument. Also, there might be errors in the script, so use it at your own risk! I would appreciate it if you point out any mistakes in the comments! I would be even more grateful if you send the corrected code!
Application Scope
This strategy can be used for delta hedging short positions in sold options. For example, suppose you sold a call option on Bitcoin on the Deribit exchange with a strike price of $60,000 and an expiration date of September 27, 2024. Using this script, you can create a delta hedge to protect against the risk of loss in the option position if the price of Bitcoin rises.
Another example: Suppose you use staking of altcoins in your strategies, for which options are not available. By using this strategy, you can hedge the risk of a price drop (Put option). In this case, you won't lose money if the underlying asset price increases, unlike with a short futures position.
Another example: You received an airdrop, but your tokens will not be fully unlocked soon. Using this script, you can fully hedge your position and preserve their dollar value by the time the tokens are fully unlocked. And you won't fear the underlying asset price increasing, as the loss in the event of a price rise is limited to the option premium you will pay if you rebalance the portfolio.
Of course, this script can also be used for simple directional trading of momentum and mean reversion strategies!
Key Features and Input Parameters
1. Option settings:
- Style of option: "European vanilla", "Binary", "Asian geometric".
- Type of option: "Call" (bet on the rise) or "Put" (bet on the fall).
- Strike price: the option contract price.
- Expiration: the expiry date and time of the option contract.
2. Market statistic settings:
- Type of price source: open, high, low, close, hl2, hlc3, ohlc4, hlcc4 (using hl2, hlc3, ohlc4, hlcc4 allows smoothing the price in more volatile series).
- Risk-free return symbol: the risk-free rate for the market where the underlying asset is traded. For the cryptocurrency market, the return on the funding rate arbitrage strategy is accepted (a special function is written for its calculation based on the Premium Price).
- Volatility calculation model: realized (standard deviation over a moving period), implied (e.g., DVOL or VIX), or custom (you can specify a specific number in the field below). For the cryptocurrency market, the calculation of implied volatility is implemented based on the product of the realized volatility ratio of the considered asset and Bitcoin to the Bitcoin implied volatility index.
- User implied volatility: fixed implied volatility (used if "Custom" is selected in the "Volatility Calculation Method").
3. Display settings:
- Choose metric: what to display on the indicator scale – the price of the underlying asset, the option price, volatility, or Greeks (all are available).
- Measure: bps (basis points), percent. This parameter allows choosing the unit of measurement for the displayed metric (for all except the Greeks).
4. Trading settings:
- Hedge model: None (do not trade, default), Simple (just open a position for the full volume when the strike price is crossed), Synthetic option (creating a synthetic option based on the Black-Scholes model).
- Position side: Long, Short.
- Position size: the number of units of the underlying asset needed to create the option.
- Strategy start time: the moment in time after which the strategy will start working to create a synthetic option.
- Delta hedge interval: the interval in minutes for rebalancing the portfolio. For example, a value of 5 corresponds to rebalancing the portfolio every 5 minutes.
Post scriptum
My strategy based on the SegaRKO model. Many thanks to the author! Unfortunately, I don't have enough reputation points to include a link to the author in the description. You can find the original model via the link in the code, as well as through the search indicators on the charts by entering the name: "Black-Scholes Option Pricing Model". I have significantly improved the model: the calculation of volatility, risk-free rate and time value of the option have been reworked. The code performance has also been significantly optimized. And the most significant change is the execution, with which you can now trade using this script.
Inverted SD Dema RSI | viResearchInverted SD Dema RSI | viResearch
The "Inverted SD Dema RSI" developed by viResearch introduces a new approach to trend analysis by combining the Double Exponential Moving Average (DEMA), Standard Deviation (SD), and Relative Strength Index (RSI). This unique indicator provides traders with a tool to capture market trends by integrating volatility-based thresholds. By using the smoothed DEMA along with standard deviation, the indicator offers improved responsiveness to price fluctuations, while RSI thresholds offer insight into overbought and oversold market conditions.
At the core of the "Inverted SD Dema RSI" is the combination of DEMA and standard deviation for a more nuanced view of market volatility. The use of RSI further aids in detecting price extremes and potential trend reversals.
DEMA Calculation (sublen): The Double Exponential Moving Average (DEMA) smoothes out price data over a user-defined period, reducing lag compared to traditional moving averages. This provides a clearer representation of the market's overall direction.
Standard Deviation Calculation (sublen_2): The standard deviation of the DEMA is used to define the upper (u) and lower (d) bands, highlighting areas where price volatility may signal a change in trend. These dynamic bands help traders gauge price volatility and potential breakouts or breakdowns.
RSI Calculation (len): The script applies the Relative Strength Index (RSI) to the smoothed DEMA values, allowing traders to detect momentum shifts based on a modified data set. This provides a more accurate reflection of market strength when combined with the DEMA.
Thresholds: The RSI is compared to user-defined thresholds (70 for overbought and 55 for oversold conditions). These thresholds help in identifying potential market reversals, especially when the price breaks outside of the calculated standard deviation bands.
Uptrend (L): An uptrend signal is generated when the RSI exceeds the upper threshold (70) and the price is not above the upper standard deviation band, indicating that there may be room for further price appreciation.
Downtrend (S): A downtrend signal occurs when the RSI falls below the lower threshold (55), indicating that the price may continue to decline.
The "Inverted SD Dema RSI" offers a wide range of customizable settings, allowing traders to adjust the indicator based on their trading style or market conditions.
DEMA Length (sublen): Controls the period used to smooth the price data, impacting the sensitivity of the DEMA to recent price movements.
Standard Deviation Length (sublen_2): Defines the length over which the standard deviation is calculated, helping traders control the width of the upper and lower bands.
RSI Length (len): Adjusts the period used for the RSI calculation, providing flexibility in determining overbought and oversold conditions.
RSI Thresholds: Traders can define their own levels for detecting trend reversals, with default values of 70 for an uptrend and 55 for a downtrend.
The "Inverted SD Dema RSI" is particularly well-suited for traders looking to capture trends while accounting for volatility and momentum. By using a smoothed DEMA as the foundation, it effectively filters out noise, making it ideal for detecting reliable trends in volatile markets.
Key Uses:
Trend Following: The indicator’s combination of DEMA, standard deviation, and RSI helps traders follow trends more effectively by reducing noise and identifying key momentum shifts.
Volatility Filtering: The use of standard deviation bands provides a dynamic measure of volatility, ensuring that traders are aware of potential breakouts or breakdowns in the market.
Momentum Detection: The inclusion of RSI ensures that the indicator is not only focused on trend direction but also on the strength of the underlying momentum, helping traders avoid entering trades during weak trends.
The "Inverted SD Dema RSI" provides several key advantages over traditional trend-following indicators:
Reduced Lag: The use of DEMA ensures faster trend detection, reducing the lag associated with simple moving averages.
Noise Reduction: The integration of standard deviation helps filter out irrelevant price movements, making it easier to identify significant trends.
Momentum Awareness: The addition of RSI provides valuable insight into the strength of trends, helping traders avoid false signals during periods of weak momentum.
The "Inverted SD Dema RSI" offers a powerful blend of trend-following and momentum detection, making it a versatile tool for modern traders. By integrating DEMA, standard deviation, and RSI, the indicator provides a comprehensive view of market trends and volatility. Traders are encouraged to experiment with different settings for the DEMA length, standard deviation, and RSI thresholds to fine-tune the indicator for their specific trading strategies. Whether used for trend confirmation, volatility assessment, or momentum analysis, the "Inverted SD Dema RSI" offers a valuable tool for traders seeking a comprehensive approach to market analysis.
Volume-Price PercentileDescription:
The "Volume-Price Percentile Live" indicator is designed to provide real-time analysis of the relationship between volume percentiles and price percentiles on any given timeframe. This tool helps traders assess market activity by comparing how current volume levels rank relative to historical volume data and how current price movements (specifically high-low ranges) rank relative to historical price data. The indicator visualizes the ratio of volume percentile to price percentile as a histogram, allowing traders to gauge the relative strength of volume against price movements in real time.
Functionality:
Volume Percentile: Calculates the percentile rank of the current volume within a user-defined rolling period (default is 30 bars). This percentile indicates where the current volume stands in comparison to historical volumes over the specified period.
Price Percentile: Calculates the percentile rank of the current candle's high-low difference within a user-defined rolling period (default is 30 bars). This percentile reflects the current price movement's strength relative to past movements over the specified period.
Percentile Ratio (VP Ratio): The indicator plots the ratio of the volume percentile to the price percentile. This ratio helps identify periods when volume is significantly higher or lower relative to price movement, providing insights into potential market imbalances or strength.
Real-Time Data: By fetching data from a lower timeframe (e.g., 1-minute), the indicator updates continuously within the current timeframe, offering live, intra-candle updates. This ensures that traders can see the histogram change in real-time as new data becomes available, without waiting for the current candle to close.
How to Use:
Adding the Indicator: To use this indicator, add it to your chart on TradingView by selecting it from the Indicators list once it is published publicly.
Setting Parameters:
Volume Period Length: This input sets the rolling window length for calculating the volume percentile (default is 30). You can adjust it based on the desired sensitivity or historical period relevance.
Candle Period Length: This input sets the rolling window length for calculating the price percentile based on the high-low difference of candles (default is 30). Adjust this to match your trading style or analysis period.
Interpreting the Histogram:
The histogram represents the volume percentile divided by the price percentile.
Above 1: A value greater than 1 indicates that volume is relatively strong compared to price movement, which may suggest high activity or potential accumulation/distribution phases.
Below 1: A value less than 1 suggests that price movement is relatively stronger than volume, indicating potential weakness in volume relative to price moves.
Near 1: Values close to 1 suggest a balanced relationship between volume and price movement.
Application: Use this indicator to identify potential breakout or breakdown scenarios, assess the strength of price movements, and confirm trends. When volume percentile consistently leads price percentile, it might signal sustained interest and support for the current price trend. Conversely, if volume percentile lags significantly, it might warn of potential trend weakness.
Best Practices:
Multiple Timeframe Analysis: While the indicator provides real-time updates on any timeframe, consider using it alongside higher timeframe analysis to confirm trends and volume behavior across different periods.
Customization: Adjust the period lengths based on the asset’s typical volume and price behavior, as well as your trading strategy (e.g., short-term scalping vs. long-term trend following).
Complement with Other Indicators: Use this indicator in conjunction with other volume-based tools, trend indicators, or momentum oscillators to gain a comprehensive view of market dynamics.
Median Standard Deviation | viResearchMedian Standard Deviation | viResearch
The "Median Standard Deviation" indicator, developed by viResearch, introduces a unique combination of median smoothing and standard deviation to detect trends and volatility in market data. This tool provides traders with a stable and accurate measure of price trends by integrating median smoothing with a customized calculation of the standard deviation. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation:
The "Median Standard Deviation" indicator incorporates median smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
Median Smoothing:
DEMA Calculation (len_dema): The script applies a Double Exponential Moving Average (DEMA) to smooth the price data over a user-defined period, reducing noise and helping traders focus on broader market trends.
Median Calculation (median_len): The smoothed DEMA data is further refined by calculating the 50th percentile (median) over a specified length, ensuring that the central tendency of price data is captured more accurately than with a simple moving average.
Volatility Measurement:
ATR Calculation (atr_len, atr_mul): The script incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the median, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Analysis:
Standard Deviation Calculation (len_sd): The script calculates the standard deviation of the median over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (sdd, sdl) act as additional indicators of price extremes.
Trend Detection:
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands are used to signal potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs:
The "Median Standard Deviation" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
DEMA Length: Allows traders to adjust the sensitivity of the DEMA smoothing to control the amount of noise filtered from the price data.
Median Length: Users can define the length over which the median price is calculated, providing flexibility in capturing short-term or long-term trends.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing for further customization in detecting price volatility.
Practical Applications:
The "Median Standard Deviation" indicator is particularly effective in volatile markets where price swings can lead to false signals using traditional methods. By combining median smoothing and standard deviation, this tool provides a more robust analysis of trends and price movements.
Key Uses:
Trend Following: The upper and lower bands provide clear signals for entering and exiting trades based on whether the price is moving outside the calculated ranges.
Volatility Detection: The integration of ATR and standard deviation bands allows traders to assess market volatility in real time, enabling more informed trading decisions.
Noise Reduction: The use of median smoothing ensures that short-term price fluctuations do not interfere with broader trend analysis, making this indicator ideal for traders looking to avoid whipsaws in volatile markets.
Advantages and Strategic Value:
The "Median Standard Deviation" indicator offers several key advantages:
Precision in Trend Detection: The combination of median smoothing and standard deviation allows traders to detect trends with greater accuracy, reducing the risk of false signals.
Customization: With several adjustable parameters, traders can fine-tune the indicator to suit different timeframes and trading strategies.
Volatility Sensitivity: By incorporating ATR and standard deviation, this indicator provides an adaptive measure of market volatility, ensuring that traders are always aware of potential price swings.
Summary and Usage Tips:
The "Median Standard Deviation" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of median smoothing and standard deviation provides a nuanced view of market movements, helping traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs, whether used for trend detection, volatility analysis, or noise reduction. The "Median Standard Deviation" offers a reliable and adaptable solution for modern trading strategies.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
Uptrick: Dual Moving Average Volume Oscillator
Title: Uptrick: Dual Moving Average Volume Oscillator (DPVO)
### Overview
The "Uptrick: Dual Moving Average Volume Oscillator" (DPVO) is an advanced trading tool designed to enhance market analysis by integrating volume data with price action. This indicator is specially developed to provide traders with deeper insights into market dynamics, making it easier to spot potential entry and exit points based on volume and price interactions. The DPVO stands out by offering a sophisticated approach to traditional volume analysis, setting it apart from typical volume indicators available on the TradingView platform.
### Unique Features
Unlike traditional indicators that analyze volume and price movements separately, the DPVO combines these two critical elements to offer a comprehensive view of market behavior. By calculating the Volume Impact, which involves the product of the exponential moving averages (EMAs) of volume and the price range (close - open), this indicator highlights significant trading activities that could indicate strong buying or selling pressure. This method allows traders to see not just the volume spikes, but how those spikes relate to price movements, providing a clearer picture of market sentiment.
### Customization and Inputs
The DPVO is highly customizable, catering to various trading styles and strategies:
- **Oscillator Length (`oscLength`)**: Adjusts the period over which the volume and price difference is analyzed, allowing traders to set it according to their trading timeframe.
- **Fast and Slow Moving Averages (`fastMA` and `slowMA`)**: These parameters control the responsiveness of the DPVO. A shorter `fastMA` coupled with a longer `slowMA` can help in identifying trends quicker or smoothing out market noise for more conservative approaches.
- **Signal Smoothing (`signalSmooth`)**: This input helps in reducing signal noise, making the crossover and crossunder points between the DVO and its smoothed signal line clearer and easier to interpret.
### Functionality Details
The DPVO operates through a sequence of calculated steps that integrate volume data with price movement:
1. **Volume Impact Calculation**: This is the foundational step where the product of the EMA of volume and the EMA of price range (close - open) is calculated. This metric highlights trading sessions where significant volume accompanies substantial price movements, suggesting a strong market response.
2. **Dynamic Volume Oscillator (DVO)**: The heart of the indicator, the DVO, is derived by calculating the difference between the fast EMA and the slow EMA of the Volume Impact. This result is then normalized by dividing by the EMA of the volume over the same period to scale the output, making it consistent across various trading environments.
3. **Signal Generation**: The final output is smoothed using a simple moving average of the DVO to filter out market noise. Buy and sell signals are generated based on the crossover and crossunder of the DVO with its smoothed version, providing clear cues for market entry or exit.
### Originality
The DPVO's originality lies in its innovative integration of volume and price movement, a novel approach not typically observed in other volume indicators. By analyzing the product of volume and price change EMAs, the DPVO captures the essence of market dynamics more holistically than traditional tools, which often only reflect volume levels without contextualizing them with price actions. This dual analysis provides traders with a deeper understanding of market forces, enabling them to make more informed decisions based on a combination of volume surges and significant price movements. The DPVO also introduces a unique normalization and smoothing technique that refines the oscillator's output, offering cleaner and more reliable signals that are adaptable to various market conditions and trading styles.
### Practical Application
The DPVO excels in environments where volume plays a crucial role in validating price movements. Traders can utilize the buy and sell signals generated by the DPVO to enhance their decision-making process. The signals are plotted directly on the trading chart, with buy signals appearing below the price bars and sell signals above, ensuring they are prominent and actionable. This setup is particularly useful for day traders and swing traders who rely on timely and accurate signals to maximize their trading opportunities.
### Best Practices
To maximize the effectiveness of the DPVO, traders should consider the following best practices:
- **Market Selection**: Use the DPVO in markets known for strong volume-price correlation such as major forex pairs, popular stocks, and cryptocurrencies.
- **Signal Confirmation**: While the DPVO provides powerful signals, confirming these signals with additional indicators such as RSI or MACD can increase trade reliability.
- **Risk Management**: Always use stop-loss orders to manage risks associated with trading signals. Adjust the position size based on the volatility of the asset to avoid significant losses.
### Practical Example + How to use it
Practical Example1: Day Trading Cryptocurrencies
For a day trader focusing on the highly volatile cryptocurrency market, the DPVO can be an effective tool on a 15-minute chart. Suppose a trader is monitoring Bitcoin (BTC) during a period of high market activity. The DPVO might show an upward crossover of the DVO above its smoothed signal line while also indicating a significant increase in volume. This could signal that strong buying pressure is entering the market, suggesting a potential short-term rally. The trader could enter a long position based on this signal, setting a stop-loss just below the recent support level to manage risk. If the DPVO later shows a crossover in the opposite direction with decreasing volume, it might signal a good exit point, allowing the trader to lock in profits before a potential pullback.
- **Swing Trading Stocks**: For a swing trader looking at stocks, the DPVO could be applied on a daily chart. If the oscillator shows a consistent downward trend along with increasing volume, this could suggest a potential sell-off, providing a sell signal before a significant downturn.
You can look for:
--> Increase in volume - You can use indicators like 24-hour-Volume to have a better visualization
--> Uptrend/Downtrend in the indicator (HH, HL, LL, LH)
--> Confirmation (Buy signal/Sell signal)
--> Correct Price action (Not too steep moves up or down. Stable moves.) (Optional)
--> Confirmation with other indicators (Optional)
Quick image showing you an example of a buy signal on SOLANA:
### Technical Notes
- **Calculation Efficiency**: The DPVO utilizes exponential moving averages (EMAs) in its calculations, which provides a balance between responsiveness and smoothing. EMAs are favored over simple moving averages in this context because they give more weight to recent data, making the indicator more sensitive to recent market changes.
- **Normalization**: The normalization of the DVO by the EMA of the volume ensures that the oscillator remains consistent across different assets and timeframes. This means the indicator can be used on a wide variety of markets without needing significant adjustments, making it a versatile tool for traders.
- **Signal Line Smoothing**: The final signal line is smoothed using a simple moving average (SMA) to reduce noise. The choice of SMA for smoothing, as opposed to EMA, is intentional to provide a more stable signal that is less prone to frequent whipsaws, which can occur in highly volatile markets.
- **Lag and Sensitivity**: Like all moving average-based indicators, the DPVO may introduce a slight lag in signal generation. However, this is offset by the indicator’s ability to filter out market noise, making it a reliable tool for identifying genuine trends and reversals. Adjusting the `fastMA`, `slowMA`, and `signalSmooth` inputs allows traders to fine-tune the sensitivity of the DPVO to match their specific trading strategy and market conditions.
- **Platform Compatibility**: The DPVO is written in Pine Script™ v5, ensuring compatibility with the latest features and functionalities offered by TradingView. This version takes advantage of optimized functions for performance and accuracy in calculations, making it well-suited for real-time analysis.
Conclusion
The "Uptrick: Dual Moving Average Volume Oscillator" is a revolutionary tool that merges volume analysis with price movement to offer traders a more nuanced understanding of market trends and reversals. Its ability to provide clear, actionable signals based on a unique combination of volume and price changes makes it an invaluable addition to any trader's toolkit. Whether you are managing long-term positions or looking for quick trades, the DPVO provides insights that can help refine any trading strategy, making it a standout choice in the crowded field of technical indicators.
Nothing from this indicator or any other Uptrick Indicators is financial advice. Only you are ultimately responsible for your choices.
High-Low Cloud Trend [ChartPrime]The High-Low Cloud Trend - ChartPrime indicator, combines the concepts of trend following and mean reversion into a dynamic cloud representation. This indicator constructs high and low bands based on lookback periods, which adjust dynamically to reflect market conditions. By highlighting the upper and lower extremes, it provides a visual gauge for potential reversals and continuation points.
◆ KEY FEATURES
Dynamic Cloud Bands : Uses high and low derived from user-defined lookback periods to create reactive bands that illustrate trend strength and potential reversal zones.
Color-coded Visualization : Applies distinct colors to the bands based on the trend direction, improving readability and decision-making speed.
Mean Reversion Detection : Identifies points where price extremes may revert to a mean, signaling potential entry or exit opportunities based on deviation from expected values.
Flexible Visualization : Offers options to display volume or price-based metrics within labels, enhancing analytical depth.
◆ FUNCTIONALITY DETAILS
Band Formation : Calculates two sets of bands; one based on a primary lookback period and another for a shorter period to capture mean reversion points.
◆ USAGE
Trend Confirmation : Use the main bands to confirm the prevailing market trend, with the cloud filling acting as a visual guide.
Breakout Identification : Monitor for price breaks through the cloud to identify strong momentum that may suggest a viable breakout.
Risk Management : Adjust positions based on the proximity of price to either band, using these as potential support or resistance areas.
Mean Reversion Strategies : Apply mean reversion techniques when price touches or crosses the bands, indicating a possible return to a central value.
⯁ USER INPUTS
Lookback Period : Sets the primary period for calculating high and low bands.
Mean Reversion Points : Toggles the identification of mean reversion opportunities within the bands.
Volume/Price Display : Chooses between displaying volume or price information in the indicator's labels for enhanced detail.
The High-Low Cloud Trend indicator is a versatile and powerful tool for traders who engage in both trend following and mean reversion strategies. It provides a clear visual representation of market dynamics, helping traders to make informed decisions based on established and emerging patterns. This indicator's dual approach ensures that it is suitable for various trading styles and market conditions.
Periodical Trend [BigBeluga]The Periodical Trend indicator is designed to provide a detailed analysis of market trends and volatility. It utilizes a combination of Moving Averages and volatility measures to plot trend line, highlight potential trend reversals, and indicate mean reversion opportunities. The indicator offers customizable display options, allowing traders to adjust for sensitivity, volatility bands, and price deviation visibility.
🔵 KEY FEATURES
● Periodical Trend Analysis
Uses (high + volatility) or (low - volatility) as the foundation for trend analysis with a set period.
// Condition to update the AVG array based on the selected mode
if mode == "Normal"
? bar_index == 122
: bar_index % period == 0
AVG.push(close) // Add the close price to the AVG array
// Update AVG array based on the period and price comparison
if bar_index % period == 0
if close > AVG.last() // If the current close is greater than the last stored value in AVG
AVG.push(low - vlt) // Add the low price minus volatility to the array
if close < AVG.last() // If the current close is lower than the last stored value in AVG
AVG.push(high + vlt) // Add the high price plus volatility to the array
Provides adjustable sensitivity modes ("Normal" and "Sensitive") for different market conditions.
Trend direction is visualized with dynamic color coding based on the relationship between the trend line and price.
● Volatility Bands
Displays upper and lower volatility bands derived from a moving average of price volatility (high-low).
The bands help identify potential breakout zones, overbought, or oversold conditions.
Users can toggle the visibility of the bands to suit their trading style.
● Mean Reversion Signals
Detects mean reversion opportunities when price deviates significantly from the trend line.
Includes both regular and strong mean reversion signals, marked directly on the chart.
Signals are based on oscillator crossovers, offering potential entry and exit points.
● Price Deviation Oscillator
Plots an oscillator that measures the deviation of price from the average trend line.
The oscillator is normalized using standard deviation, highlighting extreme price deviations.
Traders can choose to display the oscillator for in-depth analysis of price behavior relative to the trend.
● Dynamic Trend Coloring
The indicator colors the background on the direction of the trend.
Green indicates bullish trends, while blue indicates bearish trends.
The trend colors adapt dynamically to market conditions, providing clear visual cues for traders.
🔵 HOW TO USE
● Trend Analysis
The trend line represents the current market direction. A green trend line suggests a bullish trend, while a blue trend line indicates a bearish trend.
Use the trend line in conjunction with volatility bands to confirm potential breakouts or areas of consolidation.
● Volatility Bands
Volatility bands offer insight into potential overbought or oversold conditions.
Price exceeding these bands can signal a strong trend continuation or a possible reversal.
● Mean Reversion Strategies
Look for mean reversion signals (regular and strong) when price shows signs of reverting to the trend line after significant deviation.
Regular signals are represented by small dots, while strong signals are represented by larger circles.
These signals can be used as entry or exit points, depending on the market context.
● Price Deviation Analysis
The oscillator provides a detailed view of price deviations from the trend line.
A positive oscillator value indicates that the price is above the trend, while a negative value suggests it is below.
Use the oscillator to identify potential overbought or oversold conditions within the trend.
🔵 USER INPUTS
● Period
Defines the length of the period used for calculating the trend line. A higher period smooths out the trend, while a shorter period makes the trend line more sensitive to price changes.
● Mode
Choose between "Normal" and "Sensitive" modes for trend detection. The "Sensitive" mode responds more quickly to price changes, while the "Normal" mode offers smoother trend lines.
● Volatility Bands
Toggle the display of upper and lower volatility bands. These bands help identify potential areas of price exhaustion or continuation.
● Price Deviation
Toggle the display of the price deviation oscillator. This oscillator shows the deviation of the current price from the trend line and highlights extreme conditions.
● Mean Reversion Signals
Toggle the display of mean reversion signals. These signals highlight potential reversal points when the price deviates significantly from the trend.
● Strong Mean Reversion Signals
Toggle the display of stronger mean reversion signals, which occur at more extreme deviations from the trend.
● Width
Adjust the thickness of the trend line for better visibility on the chart.
🔵 CONCLUSION
The Periodical Trend indicator combines trend analysis, volatility bands, and mean reversion signals to provide traders with a comprehensive tool for market analysis. By offering customizable display options and dynamic trend coloring, this indicator can adapt to different trading styles and market conditions. Whether you are a trend follower or a mean reversion trader, the Periodical Trend indicator helps identify key market opportunities and potential reversals.
For optimal results, it is recommended to use this indicator alongside other technical analysis tools and within the context of a well-structured trading strategy.
Open-Close Price DifferenceInput time A (open time) and time B (closing time)
do not do anything with the year-month-date, it's there because I don't know how to fix it and it needs to be in such format.
the difference of price will be shown on the indicator window one candle after the closing time (opening at such time)
For research purpose only, no other intended purposes.
Position Sizer by VolatilityDescription :
The **Position Sizer by Volatility (PSV)** is an indicator that helps traders determine what percentage of their deposit a position will occupy, taking into account the current market volatility. PSV calculates the range of price movements over recent periods and shows how large this movement is compared to historical data. The lower the value, the lower the volatility, and the smaller the stop-loss required relative to the current price.
Explanation of PSV Parameters:
- ` len ` (Period Length):** This parameter sets the number of candles (bars) on the chart that will be used to calculate volatility. For example, if `len` is set to 250, the indicator will analyze price movements over the last 250 bars. The larger the value, the longer the period used for volatility assessment.
- ` percent ` (Percentile):** This parameter determines how strong price fluctuations you want to account for. For instance, if you set `percent` to 95, the indicator will focus on the 5% of instances where the price range was the largest over the specified period. This helps evaluate volatility during periods of sharp price movements, which may require a larger stop-loss. A higher percentile accounts for rarer but stronger movements, and vice versa.
Uptrick: Crypto Volatility Index** Crypto Volatility Index(VIX) **
Overview
The Crypto Volatility Index (VIX) is a specialized technical indicator designed to measure the volatility of cryptocurrency prices. Leveraging advanced statistical methods, including logarithmic returns and variance, the Crypto VIX offers a refined measure of market fluctuations. This approach makes it particularly useful for traders in the highly volatile cryptocurrency market, providing insights that traditional volatility indicators may not capture as effectively.
Purpose
The Crypto VIX aims to deliver a nuanced understanding of market volatility, tailored specifically for the cryptocurrency space. Unlike other volatility measures, the Crypto VIX employs sophisticated statistical methods to reflect the unique characteristics of cryptocurrency price movements. This makes it especially valuable for cryptocurrency traders, helping them navigate the inherent volatility of digital assets and manage their trading strategies and risk exposure more effectively.
Calculation
1. Indicator Declaration
The Crypto VIX is plotted in a separate pane below the main price chart for clarity:
indicator("Crypto Volatility Index (VIX)", overlay=false, shorttitle="Crypto VIX")
2. Input Parameters
Users can adjust the period length for volatility calculations:
length = input.int(14, title="Period Length")
3. Calculating Daily Returns
The daily returns are calculated using logarithmic returns:
returns = math.log(close / close )
- **Logarithmic Returns:** These returns provide a normalized measure of price changes, making it easier to compare returns over different periods and across different assets.
4. Average Return Calculation
The average return over the specified period is computed with a Simple Moving Average (SMA):
avg_return = ta.sma(returns, length)
5. Variance Calculation
Variance measures the dispersion of returns from the average:
variance = ta.sma(math.pow(returns - avg_return, 2), length)
- Variance : This tells us how much the returns deviate from the average, giving insight into how volatile the market is.
6. Standard Deviation (Volatility) Calculation
Volatility is derived as the square root of the variance:
volatility = math.sqrt(variance)
- Standard Deviation : This provides a direct measure of volatility, showing how much the price typically deviates from the mean return.
7. Plotting the Indicator
The volatility and average return are plotted:
plot(volatility, color=#21f34b, title="Volatility Index")
plot(avg_return, color=color.new(color.red, 80), title="Average Return", style=plot.style_columns)
Practical Examples
1. High Volatility Scenario
** Example :** During significant market events, such as major regulatory announcements or geopolitical developments, the Crypto VIX tends to rise sharply. For instance, if the Crypto VIX moves from a baseline level of 0.2 to 0.8, it indicates heightened market volatility. Traders might see this as a signal to adjust their strategies, such as reducing position sizes or setting tighter stop-loss levels to manage increased risk.
2. Low Volatility Scenario
** Example :** In a stable market, where prices fluctuate within a narrow range, the Crypto VIX will show lower values. For example, a drop in the Crypto VIX from 0.4 to 0.2 suggests lower volatility and stable market conditions. Traders might use this information to consider longer-term trades or take advantage of potential consolidation patterns.
Best Practices
1. Combining Indicators
- Moving Averages : Use the Crypto VIX with moving averages to identify trends and potential reversal points.
- Relative Strength Index (RSI): Combine with RSI to assess overbought or oversold conditions for better entry and exit points.
- Bollinger Bands : Pair with Bollinger Bands to understand volatility relative to price movements and spot potential breakouts.
2. Adjusting Parameters
- Short-Term Trading : Use a shorter period length (e.g., 7 days) to capture rapid volatility changes suitable for day trading.
- Long-Term Investing : A longer period length (e.g., 30 days) provides a smoother view of volatility, helping long-term investors navigate market trends.
Backtesting and Performance Insights
While specific backtesting data for the Crypto VIX is not yet available, the indicator is built on established principles of volatility measurement, such as logarithmic returns and standard deviation. These methods are well-regarded in financial analysis for accurately reflecting market volatility. The Crypto VIX is designed to offer insights similar to other effective volatility indicators, tailored specifically for the cryptocurrency markets. Its adaptation to digital assets and ability to provide precise volatility measures underscore its practical value for traders.
Originality and Uniqueness
The Crypto Volatility Index (VIX) distinguishes itself through its specialized approach to measuring volatility in the cryptocurrency markets. While the concepts of logarithmic returns and standard deviation are not new, the Crypto VIX integrates these methods into a unique framework designed specifically for digital assets.
- Tailored Methodology : Unlike generic volatility indicators, the Crypto VIX is adapted to the unique characteristics of cryptocurrencies, providing a more precise measure of price fluctuations that reflects the inherent volatility of digital markets.
- Enhanced Insights : By focusing on cryptocurrency-specific price behavior and incorporating advanced statistical techniques, the Crypto VIX offers insights that traditional volatility indicators might miss. This makes it a valuable tool for traders navigating the complex and fast-moving cryptocurrency landscape.
- Innovative Application : The Crypto VIX combines established financial metrics in a novel way, offering a fresh perspective on market volatility and contributing to more effective risk management and trading strategies in the cryptocurrency space.
Summary
The Crypto Volatility Index (VIX) is a specialized tool for measuring cryptocurrency market volatility. By utilizing advanced statistical methods such as logarithmic returns and standard deviation, it provides a detailed measure of price fluctuations. While not entirely original in its use of these methods, the Crypto VIX stands out through its tailored application to the unique characteristics of the cryptocurrency market. Traders can use the Crypto VIX to gauge market risk, adjust their strategies, and make informed trading decisions, supported by practical examples, best practices, and clear visual aids.
Dynamic Rate of Change OscillatorDynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram
Detailed Description for Publication
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a sophisticated technical analysis tool designed to enhance your understanding of market momentum. Created using Pine Script v5 on the TradingView platform, this indicator integrates multiple Rate of Change (RoC) calculations into a unified momentum oscillator. The resulting data is displayed as a color-coded histogram, providing a clear visual representation of momentum changes.
Key Features and Functionality
Multi-Length RoC Calculation:
Short-term RoC: Calculated over a user-defined period (shortRoCLength), this captures variations in price momentum over a shorter duration, offering insights into the immediate price action.
Long-term RoC: This uses a longer period (longRoCLength) to provide a broader view of momentum, helping to smooth out short-term fluctuations and highlight more established trends.
Mid-term RoC: A weighted average of the short-term and long-term RoCs, the mid-term RoC (midRoCWeight) allows you to balance sensitivity and stability in the oscillator's behavior.
Weighted RoC Calculation:
The indicator calculates a single weighted average RoC by integrating short-term, long-term, and mid-term RoCs. The weighting factor can be adjusted to prioritize different market dynamics according to the trader’s strategy. This flexible approach enables the oscillator to remain applicable across diverse market conditions.
Oscillator Calculation and Smoothing:
The oscillator value is computed by subtracting a 14-period Weighted Moving Average (WMA) from the weighted RoC, which helps to normalize the oscillator, making it more responsive to changes in momentum.
The oscillator is then smoothed using a Simple Moving Average (SMA) over a user-defined period (smoothLength). This process reduces market noise, making the oscillator's signals clearer and easier to interpret.
Color-Coded Histogram:
The smoothed oscillator is displayed as a histogram, which is color-coded to reflect bullish or bearish momentum. You can customize the colors to match your charting style, with green typically representing upward momentum and red representing downward momentum.
The color-coded histogram allows for quick visual identification of momentum changes on the chart, aiding in your market analysis.
Zero-Line Reference:
A horizontal line at the zero level is plotted as a reference point. This zero-line helps in identifying when the histogram shifts from positive to negative or vice versa, which can be useful in understanding momentum shifts.
The zero-line offers a straightforward visual cue, making it easier to interpret the oscillator's signals in relation to market movements.
Customization and Versatility
The Dynamic RoC Oscillator with Histogram is designed with flexibility in mind, making it suitable for a wide range of trading styles, from short-term trading to longer-term analysis. Users have the ability to fine-tune the indicator’s input parameters to align with their specific needs:
Adjustable RoC Periods: Customize the short-term and long-term RoC lengths to match the timeframes you focus on.
Weighted Sensitivity: Adjust the mid-term RoC weight to emphasize different aspects of momentum according to your analysis approach.
Smoothing Options: Modify the smoothing moving average length to control the sensitivity of the oscillator, allowing you to balance responsiveness with noise reduction.
Use Cases
Momentum Analysis: Gain a clearer understanding of momentum changes within the market, which can aid in the evaluation of market trends.
Trend Analysis: The oscillator can help in assessing trends by highlighting when momentum is increasing or decreasing.
Chart Visualization: The color-coded histogram provides a visually intuitive method for monitoring momentum, helping you to more easily interpret market behavior.
Conclusion
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a versatile and powerful tool for traders who seek a deeper analysis of market momentum. With its dynamic calculation methods and high degree of customization, this indicator can be tailored to suit a variety of trading strategies. By integrating it into your TradingView charts, you can enhance your technical analysis capabilities, gaining valuable insights into market momentum.
This indicator is easy to use and highly customizable, making it a valuable addition to any trader’s toolkit. Add it to your charts on the TradingView platform and start exploring its potential to enrich your market analysis.
Volume ReversalsThe "Volume Reversals" indicator is a trading tool designed to identify potential buy and sell signals based on volume patterns.
Features
Filter Signals : Traders can enable or disable additional filtering of signals, which refines the conditions under which buy and sell labels are displayed.
Buy and Sell Labels: The indicator dynamically places labels on the chart to signify buy ("▲+") and sell ("▼+") opportunities. Buy labels appear at low points of bars with a green upward-pointing arrow, while sell labels appear at high points with a red downward-pointing arrow.
Customizable Alerts: Users can set alerts for buy and sell signals, receiving notifications when conditions match predefined patterns.
Logic Explained
Volume Comparison: The script examines a sequence of the last five volume bars to detect increasing or decreasing trends.
Price Action Analysis: Each volume bar is paired with a corresponding price action (bullish or bearish) from the same period.
Signal Conditions: A signal is generated under two scenarios:
Normal Conditions: Sequential increase/decrease in volume over three bars accompanied by bearish/bullish price action, followed by a dip in volume with a bullish/bearish bar.
Filtered Conditions (if filter is active): Requires all last four bars to be bearish/bullish, the most recent bar's volume to be less than the immediate previous, and then exceeds the volume two bars prior, closing bullish/bearish.
This indicator is suited for various assets and timeframes, especially in markets where volume plays a significant role in price dynamics.
Swing Points [Syafiq.Jr]The Swing Points indicator by Syafiq.Jr is designed to identify and visualize pivotal market structures such as Higher Highs (HH), Lower Highs (LH), Lower Lows (LL), and Higher Lows (HL) directly on the chart. This tool is essential for traders who utilize swing trading strategies and rely on understanding market trends through key price levels.
Key Features:
Pivot Strength: Configurable pivot strength to customize the sensitivity of swing points.
Customizable Visuals: Users can adjust the colors and visibility of the zones for each swing point category (HH, LH, LL, HL) based on their preferences.
Multiple Timeframe Support: The indicator offers the flexibility to display swing points from the current timeframe or higher timeframes such as 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, and daily intervals.
Dynamic Extension Lines: Automatically extend key levels across the chart for ongoing reference.
Configurable Font Sizes: Adjust the font size for labels marking the swing points to ensure clear visualization.
This indicator is ideal for traders who need to spot and track critical swing points across different timeframes, enabling better decision-making in trending and ranging markets.
Uptrick: Logarithmic Crypto Bands
Description :
Introduction
The `Uptrick: Logarithmic Crypto Bands` indicator introduces an innovative approach to technical analysis tailored specifically for the cryptocurrency markets. By leveraging logarithmic transformations combined with dynamic exponential bands, this indicator offers a sophisticated method for identifying critical support and resistance levels, assessing market trends, and evaluating volatility. Its unique approach stands out from traditional indicators by addressing the specific challenges of high volatility and erratic price movements inherent in cryptocurrency trading.
Originality and Usefulness
** 1. Unique Logarithmic Transformation: **
- Innovation : Unlike traditional indicators that often use raw price data, the Uptrick: Logarithmic Crypto Bands applies a logarithmic transformation to the closing prices: logPrice = math.log(close). This approach is original because it reduces the impact of extreme price fluctuations, providing a smoother and more stable price series. This transformation addresses a common issue in cryptocurrency markets where large price swings can obscure true market trends.
- Advantage : The logarithmic transformation compresses the price range, which allows traders to better identify long-term trends and reduce the noise caused by outlier price movements. This results in a more reliable basis for analysis and enhances the ability to detect meaningful market patterns.
**2. Dynamic Exponential Bands :**
- Innovation : The indicator employs exponential calculations to derive dynamic support and resistance levels based on a central base line : baseLine * math.pow(multiplier, n). Unlike static bands that remain fixed regardless of market conditions, these bands adjust dynamically according to market volatility.
- Advantage : The dynamic nature of the bands provides a more responsive and adaptive tool for traders. As market volatility changes, the bands widen or narrow accordingly, offering a more accurate reflection of potential support and resistance levels. This adaptability improves the tool's effectiveness in varying market conditions compared to static or traditional bands.
Detailed Description and Substantiation
**1. Logarithmic Price Calculation :**
- Code : ` logPrice = math.log(close)
- Description : This calculation converts the closing price into its logarithmic value. By compressing the price range, it minimizes the distortion caused by extreme price movements, which can be particularly pronounced in the volatile cryptocurrency markets.
- Purpose : To provide a stabilized price series that facilitates more accurate trend analysis and reduces the influence of erratic price fluctuations.
**2. Moving Averages of Logarithmic Prices :**
- ** Long-Term Moving Average :**
- Code : maLongLogPrice = ta.sma(logPrice, longLength)
longLength = 2000
- ** Description : A simple moving average of the logarithmic price over a long period. This average helps filter out short-term noise and provides insight into the long-term market trend.
- Purpose : To offer a perspective on the overall market direction, making it easier to identify enduring trends and distinguish them from short-term price movements.
- Short-Term Moving Average :
- Code : maShortLogPrice = ta.sma(logPrice, shortLength) shortLength = 900
- Description : A simple moving average of the logarithmic price over a shorter period. This component captures more immediate price trends and potential reversal points.
- Purpose : To detect short-term trends and changes in market direction, allowing traders to make timely trading decisions based on recent price action.
**3. Base Line Calculation :**
- Code : baseLine = math.exp(maShortLogPrice)
- Description : Converts the short-term moving average of the logarithmic price back to the original price scale. This base line serves as the central reference point for calculating the surrounding bands.
- Purpose : To establish a benchmark level from which the exponential bands are calculated, providing a central reference for assessing potential support and resistance levels.
**4. Band Calculation and Plotting :**
- ** Code :**
- Band 1: plot(baseLine * math.pow(multiplier, 1), color=color.new(color.yellow, 20), linewidth=1, title="Band 1")
- Band 2: plot(baseLine * math.pow(multiplier, 2), color=color.new(color.yellow, 20), linewidth=1, title="Band 2")
- Band 3: plot(baseLine * math.pow(multiplier, 3), color=color.new(color.yellow, 20), linewidth=1, title="Band 3")
- Band 4: plot(baseLine * math.pow(multiplier, 4), color=color.new(color.yellow, 20), linewidth=1, title="Band 4")
- Band 5: plot(baseLine * math.pow(multiplier, 5), color=color.new(color.yellow, 10), linewidth=1, title="Band 5")
- Band 6: plot(baseLine * math.pow(multiplier, 6), color=color.new(color.yellow, 0), linewidth=1, title="Band 6")
- * Multiplier : Set at 1.3, adjusts the spacing between bands to accommodate varying levels of market volatility.
- Description : Bands are plotted at exponential intervals from the base line. Each band represents a potential support or resistance level, with the spacing between them increasing exponentially. The color opacity of each band indicates its level of significance, with closer bands being more relevant for immediate trading decisions.
** How to Use the Indicator :**
**1. Identifying Support and Resistance Levels :**
- Support Levels : The lower bands, closer to the base line, can act as potential support levels. When the price approaches these bands from above, they may indicate areas where the price could stabilize or reverse direction.
- Resistance Levels : The upper bands, further from the base line, serve as resistance levels. When the price nears these bands from below, they can act as barriers to price movement, potentially leading to reversals or stalls.
**2. Confirming Trends :**
- Uptrend Confirmation : When the price consistently remains above the base line and moves towards higher bands, it signals a strong bullish trend. This confirmation helps traders capitalize on upward price movements.
- Downtrend Confirmation : When the price stays below the base line and approaches lower bands, it indicates a bearish trend. This confirmation assists traders in acting on downward price movements.
3. Analyzing Volatility :
- Wide Bands : Wider spacing between bands reflects higher market volatility. This indicates a more turbulent trading environment, where price movements are less predictable. Traders may need to adjust their strategies to handle increased volatility.
- Narrow Bands : Narrower bands suggest lower volatility and a more stable market environment. This can result in more predictable price movements and clearer trading signals.
**4. Entry and Exit Points :**
- Entry Points : Consider buying when the price bounces off the base line or a band, which could signal support in an uptrend.
- Exit Points : Evaluate selling or taking profits when the price nears upper bands or shows signs of reversal at these levels. This approach helps in locking in gains or minimizing losses during a downtrend.
**Chart Example:**
Here you can see how the price reacted getting closer to this level. All green circles show a bounce-off. So just from looking at the chart we can see a potential bounce again pretty soon.
** Disclosure :**
- ** Performance Claims :** The `Uptrick: Logarithmic Crypto Bands` indicator is designed to assist traders in analyzing price levels and trends. It is important to understand that this tool provides historical data analysis and does not guarantee future performance. The features and benefits described are based on historical market behavior and should not be seen as a prediction of future results. Traders should use this indicator as part of a broader trading strategy and consider other factors before making trading decisions.
Market Sessions - by Alexander RottasMarket Sessions - Alexander Rottas
This TradingView indicator displays market sessions for USA, EUROPE, and ASIA on your chart. It provides a clear and intuitive way to identify the active market periods, making it easier to plan your trades.
Features:
Session Display: Optionally show market sessions for USA, EUROPE, and ASIA.
Customizable Timings: Set start and end times in UTC for each market session.
Visual Indicators: Color-coded squares indicate active sessions and their combinations:
USA Session: Blue
EUROPE Session: Purple
ASIA Session: Dull Orange
Combined Sessions: Lighter shades to show overlapping sessions
Session Labels: Dynamic labels at the start of each session to easily identify session beginnings on weekdays.
User-Friendly Design: This indicator is designed to be non-intrusive and easy to use, with a simple setup and clear visual cues. Unlike other complex tools, it integrates seamlessly into your chart without overwhelming your view, making it an ideal choice for traders seeking a straightforward way to track market sessions.
DISCLAIMER: This script is provided for educational purposes only. It cannot be used for commercial purposes or plagiarized. All rights reserved by the author. Unauthorized use or distribution of this script is prohibited. For more details, please contact the author directly.
Volatility with Power VariationVolatility Analysis using Power Variation
The "Volatility with Power Variation" indicator is designed to measure market volatility. It focuses on providing traders with a clear understanding of how much the market is moving and how this movement changes over time.. This indicator helps in identifying potential periods of market expansion or contraction, based on volatility.
What the indicator does:
This indicator analyzes volatility which refers to the degree of variation in the returns of a financial instrument over time. It's an important measure to understand how much the price and returns of a asset fluctuates. High volatility means large price swings, meanwhile low volatility indicates smaller and consolidating movements. Realized (Historical) Volatility refers to volatility based on past price data.
Power Variation
Power Variation is an extension of the traditional methods used to calculate realized volatility. Instead of simply summing up squared returns (as done in calculating variance), Power Variation raises the magnitude of returns to a power p . This allows the indicator to capture different types of market behavior depending on the chosen value of p .
When P = 2, the Power variation behaves like a traditional variance measure. Lower values of p (e.g., p=1) make the indicator more sensitive to smaller price changes, meanwhile higher values make it more responsive to large jumps, but smaller price moves wont affect the measure that much or won't most likely.
Bipower Variation
Bipower variation is another method used to analyze the changes in price. It specifically isolates the continuous part of price movements from the jumps, which can help by understanding whether volatility is coming from regular market activity or from sharp, sudden moves.
How to Use the Indicator.
Understand Realized and Historical Volatility. Volatility after periods of low volatility you can eventually expect a expansion or an increase in volatility. Conversely, after periods of high volatility, the market often contracts and volatility decreases. If the variation plot is really low and you start seeing it increasing, shown by the standard deviation channels and moving average and you see it trending and increasing then that means you can expect for volatility to increase which means more price moves and expansions. Also if the scaling seems messed up, then use the logarithmic chart scale.
Wick Strength [MS]Overview
The Wick Strength indicator is a unique script designed to measure and visualize the relative strength of candlestick wicks over time. By analyzing the relationship between upper and lower wicks, this indicator provides insights into potential market dynamics and price action patterns.
How It Works
The Wick Strength indicator calculates the "strength" of candlestick wicks by comparing the upward and downward movements within each candle's range. This calculation results in a dynamic line plot that represents the evolving wick strength across your chosen timeframe.
Strength is not range-bound, allowing the score to reach extremes and be compared relatively across time.
Interpretation
Positive values indicate stronger upper wicks (potential bearish pressure)
Negative values suggest stronger lower wicks (potential bullish pressure)
Extreme readings might signal overextended moves or potential reversals
Key Features
Measures relative wick strength candle by candle
Smooths the values by summation based on user preference
Adaptable to all timeframes and markets
Potential Applications
While extensive backtesting has not been performed, the Wick Strength indicator may offer valuable insights for:
Identifying potential divergences between price action and wick strength
Spotting changes in market sentiment or volatility
Complementing other technical analysis tools for a more comprehensive trading approach
Developing unique trading strategies based on wick behavior
