Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
Kripto
H-Infinity Volatility Filter [QuantAlgo]Introducing the H-Infinity Volatility Filter by QuantAlgo 📈💫
Enhance your trading/investing strategy with the H-Infinity Volatility Filter , a powerful tool designed to filter out market noise and identify clear trend signals in volatile conditions. By applying an advanced H∞ filtering process, this indicator assists traders and investors in navigating uncertain market conditions with improved clarity and precision.
🌟 Key Features:
🛠 Customizable Noise Parameters: Adjust worst-case noise and disturbance settings to tailor the filter to various market conditions. This flexibility helps you adapt the indicator to handle different levels of market volatility and disruptions.
⚡️ Dynamic Trend Detection: The filter identifies uptrends and downtrends based on the filtered price data, allowing you to quickly spot potential shifts in the market direction.
🎨 Color-Coded Visuals: Easily differentiate between bullish and bearish trends with customizable color settings. The indicator colors the chart’s candles according to the detected trend for immediate clarity.
🔔 Custom Alerts: Set alerts for trend changes, so you’re instantly informed when the market transitions from bullish to bearish or vice versa. Stay updated without constantly monitoring the charts.
📈 How to Use:
✅ Add the Indicator: Add the H-Infinity Volatility Filter to your favourites and apply it to your chart. Customize the noise and disturbance parameters to match the volatility of the asset you are trading/investing. This allows you to optimize the filter for your specific strategy.
👀 Monitor Trend Shifts: Watch for clear visual signals as the filter detects uptrends or downtrends. The color-coded candles and line plots help you quickly assess market conditions and potential reversals.
🔔 Set Alerts: Configure alerts to notify you when the trend changes, allowing you to react quickly to potential market shifts without needing to manually track price movements.
🌟 How It Works and Academic Background:
The H-Infinity Volatility Filter is built on the foundations of H∞ (H-infinity) control theory , a mathematical framework originating from the field of engineering and control systems. Developed in the 1980s by notable engineers such as George Zames and John C. Doyle , this theory was designed to help systems perform optimally under uncertain and noisy conditions. H∞ control focuses on minimizing the worst-case effects of disturbances and noise, making it a powerful tool for managing uncertainty in complex environments.
In financial markets, where unpredictable price fluctuations and noise often obscure meaningful trends, this same concept can be applied to price data to filter out short-term volatility. The H-Infinity Volatility Filter adopts this approach, allowing traders and investors to better identify potential trends by reducing the impact of random price movements. Instead of focusing on precise market predictions, the filter increases the probability of highlighting significant trends by smoothing out market noise.
This indicator works by processing historical price data through an H∞ filter that continuously adjusts based on worst-case noise levels and disturbances. By considering several past states, it estimates the current price trend while accounting for potential external disruptions that might influence price behavior. Parameters like "worst-case noise" and "disturbance" are user-configurable, allowing traders to adapt the filter to different market conditions. For example, in highly volatile markets, these parameters can be adjusted to manage larger price swings, while in more stable markets, they can be fine-tuned for smoother trend detection.
The H-Infinity Volatility Filter also incorporates a dynamic trend detection system that classifies price movements as bullish or bearish. It uses color-coded candles and plots—green for bullish trends and red for bearish trends—to provide clear visual cues for market direction. This helps traders and investors quickly interpret the trend and act on potential signals. While the indicator doesn’t guarantee accuracy in trend prediction, it significantly reduces the likelihood of false signals by focusing on meaningful price changes rather than random fluctuations.
How It Can Be Applied to Trading/Investing:
By applying the principles of H∞ control theory to financial markets, the H-Infinity Volatility Filter provides traders and investors with a sophisticated tool that manages uncertainty more effectively. Its design makes it suitable for use in a wide range of markets—whether in fast-moving, volatile environments or calmer conditions.
The indicator is versatile and can be used in both short-term trading and medium to long-term investing strategies. Traders can tune the filter to align with their specific risk tolerance, asset class, and market conditions, making it an ideal tool for reducing the effects of market noise while increasing the probability of detecting reliable trend signals.
For investors, the filter can help in identifying medium to long-term trends by filtering out short-term price swings and focusing on the broader market direction. Whether applied to stocks, forex, commodities, or cryptocurrencies, the H-Infinity Volatility Filter helps traders and investors interpret market behavior with more confidence by offering a more refined view of price movements through its noise reduction techniques.
Disclaimer:
The H-Infinity Volatility Filter is designed to assist in market analysis by filtering out noise and volatility. It should not be used as the sole tool for making trading or investment decisions. Always incorporate other forms of analysis and risk management strategies. No statements or signals from this indicator or us should be considered financial advice. Past performance is not indicative of future results.
Adaptive VWAP [QuantAlgo]Introducing the Adaptive VWAP by QuantAlgo 📈🧬
Enhance your trading and investing strategies with the Adaptive VWAP , a versatile tool designed to provide dynamic insights into market trends and price behavior. This indicator offers a flexible approach to VWAP calculations by allowing users to adapt it based on lookback periods or fixed timeframes, making it suitable for a wide range of market conditions.
🌟 Key Features:
🛠 Customizable VWAP Settings: Choose between an adaptive VWAP that adjusts based on a rolling lookback period, or switch to a fixed timeframe (e.g., daily, weekly, monthly) for a more structured approach. Adjust the VWAP to suit your trading or investing style.
💫 Dynamic Bands and ATR Filter: Configurable deviation bands with multipliers allow you to visualize price movement around VWAP, while an ATR-based noise filter helps reduce false signals during periods of market fluctuation.
🎨 Trend Visualization: Color-coded trend identification helps you easily spot uptrends and downtrends based on VWAP positioning. The indicator fills the areas between the bands for clearer visual representation of price volatility and trend strength.
🔔 Custom Alerts: Set up alerts for when price crosses above or below the VWAP, signaling potential uptrend or downtrend opportunities. Stay informed without needing to monitor the charts constantly.
✍️ How to Use:
✅ Add the Indicator: Add the Adaptive VWAP to your favourites and apply to your chart. Choose between adaptive or timeframe-based VWAP calculation, adjust the lookback period, and configure the deviation bands to your preferred settings.
👀 Monitor Bands and Trends: Watch for price interaction with the VWAP and its deviation bands. The color-coded signals and band fills help identify potential trend shifts or price extremes.
🔔 Set Alerts: Configure alerts for uptrend and downtrend signals based on price crossing the VWAP, so you’re always informed of significant market movements.
⚙️ How It Works:
The Adaptive VWAP adjusts its calculation based on the user’s chosen configuration, allowing for a flexible approach to market analysis. The adaptive setting uses a rolling lookback period to continuously adjust the VWAP, while the fixed timeframe option anchors VWAP to key timeframes like daily, weekly, or monthly periods. This flexibility enables traders and investors to use the tool in various market environments.
Deviation bands, calculated with customizable multipliers, provide a clear visual of how far the price has moved from the VWAP, helping you gauge potential overbought or oversold conditions. To reduce false signals, an ATR-based filter can be applied, ensuring that only significant price movements trigger trend confirmations.
The tool also includes a fast exponential smoothing function for the VWAP, helping smooth out price fluctuations without sacrificing responsiveness. Trend confirmation is reinforced by the number of bars that price stays above or below the VWAP, ensuring a more consistent trend identification process.
Disclaimer:
The Adaptive VWAP is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Volatility-Adjusted DEMA Supertrend [QuantAlgo]Introducing the Volatility-Adjusted DEMA Supertrend by QuantAlgo 📈💫
Take your trading and investing strategies to the next level with the Volatility-Adjusted DEMA Supertrend , a dynamic tool designed to adapt to market volatility and provide clear, actionable trend signals. This innovative indicator is ideal for both traders and investors looking for a more responsive approach to market trends, helping you capture potential shifts with greater precision.
🌟 Key Features:
🛠 Customizable Trend Settings: Adjust the period for trend calculation and fine-tune the sensitivity to price movements. This flexibility allows you to tailor the Supertrend to your unique trading or investing strategy, whether you're focusing on shorter or longer timeframes.
📊 Volatility-Responsive Multiplier: The Supertrend dynamically adjusts its sensitivity based on real-time market volatility. This could help filter out noise in calmer markets and provide more accurate signals during periods of heightened volatility.
✨ Trend-Based Color-Coding: Visualize bullish and bearish trends with ease. The indicator paints candles and plots trend lines with distinct colors based on the current market direction, offering quick, clear insights into potential opportunities.
🔔 Custom Alerts: Set up alerts for key trend shifts to ensure you're notified of significant market changes. These alerts would allow you to act swiftly, potentially capturing opportunities without needing to constantly monitor the charts.
📈 How to Use:
✅ Add the Indicator: Add the Volatility-Adjusted DEMA Supertrend to your chart. Customize the trend period, volatility settings, and price source to match your trading or investing style. This ensures the indicator aligns with your market strategy.
👀 Monitor Trend Shifts: Watch the color-coded trend lines and candles as they dynamically shift based on real-time market conditions. These visual cues help you spot potential trend reversals and confirm your entries and exits with greater confidence.
🔔 Set Alerts: Configure alerts for key trend shifts, allowing you to stay informed of potential market reversals or continuation patterns, even when you're not actively watching the market.
⚙️ How It Works:
The Volatility-Adjusted DEMA Supertrend is designed to adapt to changes in market conditions, making it highly responsive to price volatility. The indicator calculates a trend line based on price and volatility, dynamically adjusting it to reflect recent market behavior. When the market experiences higher volatility, the trend line becomes more flexible, potentially allowing for greater sensitivity to rapid price movements. Conversely, during periods of low volatility, the indicator tightens its range, helping to reduce noise and avoid false signals.
The indicator includes a volatility-responsive multiplier, which further enhances its adaptability to market conditions. This means the trend direction would always be based on the latest market data, potentially helping you stay ahead of shifts or continuation trends. The Supertrend's visual color-coding simplifies the process of identifying bullish or bearish trends, while customizable alerts ensure you can stay on top of significant changes in market direction.
This tool is versatile and could be applied across various markets and timeframes, making it a valuable addition for both traders and investors. Whether you’re trading in fast-moving markets or focusing on longer-term investments, the Volatility-Adjusted DEMA Supertrend could help you remain aligned with the current market environment.
Disclaimer:
This indicator is designed to enhance your analysis by providing trend information, but it should not be used as the sole basis for making trading or investing decisions. Always combine it with other forms of analysis and risk management practices. No statements or claims aim to be financial advice, and no signals from us or our indicators should be interpreted as such. Past performance is not indicative of future results.
Dynamic Volume RSI (DVRSI) [QuantAlgo]Introducing the Dynamic Volume RSI (DVRSI) by QuantAlgo 📈✨
Elevate your trading and investing strategies with the Dynamic Volume RSI (DVRSI) , a powerful tool designed to provide clear insights into market momentum and trend shifts. This indicator is ideal for traders and investors who want to stay ahead of the curve by using volume-responsive calculations and adaptive smoothing techniques to enhance signal clarity and reliability.
🌟 Key Features:
🛠 Customizable RSI Settings: Tailor the indicator to your strategy by adjusting the RSI length and price source. Whether you’re focused on short-term trades or long-term investments, DVRSI adapts to your needs.
🌊 Adaptive Smoothing: Enable adaptive smoothing to filter out market noise and ensure cleaner signals in volatile or choppy market conditions.
🎨 Dynamic Color-Coding: Easily identify bullish and bearish trends with color-coded candles and RSI plots, offering clear visual cues to track market direction.
⚖️ Volume-Responsive Adjustments: The DVRSI reacts to volume changes, giving greater significance to high-volume price moves and improving the accuracy of trend detection.
🔔 Custom Alerts: Stay informed with alerts for key RSI crossovers and trend changes, allowing you to act quickly on emerging opportunities.
📈 How to Use:
✅ Add the Indicator: Set up the DVRSI by adding it to your chart and customizing the RSI length, price source, and smoothing options to fit your specific strategy.
👀 Monitor Visual Cues: Watch for trend shifts through the color-coded plot and candles, signaling changes in momentum as the RSI crosses key levels.
🔔 Set Alerts: Configure alerts for critical RSI crossovers, such as the 50 line, ensuring you stay on top of potential market reversals and opportunities.
🔍 How It Works:
The Dynamic Volume RSI (DVRSI) is a unique indicator designed to provide more accurate and responsive signals by incorporating both price movement and volume sensitivity into the RSI framework. It begins by calculating the traditional RSI values based on a user-defined length and price source, but unlike standard RSI tools, the DVRSI applies volume-weighted adjustments to reflect the strength of market participation.
The indicator dynamically adjusts its sensitivity by factoring in volume to the RSI calculation, which means that price moves backed by higher volumes carry more weight, making the signal more reliable. This method helps identify stronger trends and reduces the risk of false signals in low-volume environments. To further enhance accuracy, the DVRSI offers an adaptive smoothing option that allows users to reduce noise during periods of market volatility. This adaptive smoothing function responds to market conditions, providing a cleaner signal by reducing erratic movements or price spikes that could lead to misleading signals.
Additionally, the DVRSI uses dynamic color-coding to visually represent the strength of bullish or bearish trends. The candles and RSI plots change color based on the RSI values crossing critical thresholds, such as the 50 level, offering an intuitive way to recognize trend shifts. Traders can also configure alerts for specific RSI crossovers (e.g., above 50 or below 40), ensuring that they stay informed of potential trend reversals and significant market shifts in real-time.
The combination of volume sensitivity, adaptive smoothing, and dynamic trend visualization makes the DVRSI a robust and versatile tool for traders and investors looking to fine-tune their market analysis. By incorporating both price and volume data, this indicator delivers more precise signals, helping users make informed decisions with greater confidence.
Disclaimer:
The Dynamic Volume RSI is designed to enhance your market analysis but should not be used as a sole decision-making tool. Always consider multiple factors before making any trading or investment decisions. Past performance is not indicative of future results.
Bitcoin PivotFind [BTC Cycle Tops & Bottoms Finder]What is PivotFind?
PivotFind is a custom indicator designed to track 30+ data points of different nature (technical, sentiment, macro, on-chain), and across multiple timeframes (from 1D to 60D), to detect the market conditions that may indicate the formation of potential Cycle Tops and Bottoms .
PivotFind's goal is to help you navigate Bitcoin's price movements and key happenings over its approximately 4-year cycles to help you craft a mid-term investment plan focused on the larger swings, rather than the shorter-term fluctuations.
What Does PivotFind Show/Do?
Market Phase Assessment and Visualization:
- Uses color-coded backgrounds (green for bull, red for bear, yellow for trend reversal) to show the current (assessed) market phase. Note that the price line itself changes color to reinforce the current phase identification.
- Helps you understand if we're in a uptrend, downtrend, or potentially changing direction (reversal), often an open question for traders, with a mid-term horizon
Cycle Top and Bottom Warnings:
- Places red dots above the price line to warn of potential cycle peaks.
- Shows green dots below the price line to indicate possible cycle bottoms.
These markers appear when multiple indicators reach certain thresholds, which historically have often coincided with significant market pivots (from bull to bear, or viceversa). Clusters of tops and bottom warnings are expected to appear at truly pivotal moments.
Parabolic Growth Signals:
- Displays upward arrows when conditions suggest potential for the rapid price increases that historically anticipated blow-off tops
- These signals are based on a combination of technical indicators and market sentiment reaching certain thresholds.
Altcoin Season Indicators:
- Marks with white diamonds the conditions that have historically led to "altseasons" (i.e. Altcoins overperforming BTC's growth rate).
- Based on factors like Bitcoin dominance decrease and certain altcoin performance metrics.
Fibonacci Retracement Bands:
Plots long-term support and resistance zones based on Fibonacci retracement levels.
These bands are calculated from previous major market highs and lows and shed light on the nature of short-term retracements in the context of major trends.
Price Scenario
PivotFind also provides reference price levels for the upcoming halving cycle, including potential thresholds for increased market interest (retail FOMO), possible overvaluation, and theoretical cycle peak ranges. These projections are based on historical data and should be considered as points of reference rather than definitive predictions.
Comprehensive Data Tables:
Right-side Table: Shows current cycle stage, Bitcoin/Altcoin market dominance percentages, and evaluates key economic factors (like inflation and interest rates) for their potential impact.
Bottom Table: Displays real-time values of over 30 key indicators, including RSI, MVRV ratio, and Fear & Greed Index.
Alerts
PivotFind offers you the ability to set up custom alerts (via the standard TradingView alert functionality) or receive automated notifications for significant market events. Despite its sophisticated analysis, PivotFind is designed to be user-friendly, with pre-set parameters that don't require complex adjustments.
How Does It Work?
PivotFind analyzes over 30 different indicators across multiple timeframes (from 1 day to 60 days), grouped into four main categories:
1. Technical Analysis:
Uses standard indicators like RSI, Stochastic RSI, Williams %R, Elliot Oscillator, TDI, and mean reversion concepts.
Looks for divergences between price and multiple indicators (like OBV, MFI, CCI, RSI, SRSI, MACD and others) to spot potential reversals.
2. Market Sentiment:
Incorporates the Crypto Fear & Greed Index (0-100 scale).
Tracks social media trends and influencer follower counts as a gauge of public interest.
3. Macroeconomic Factors:
Monitors inflation rates, interest rates, US rate yields, and money supply (M2) figures.
Tracks the U.S. Dollar Index (DXY) and bond market health through ETFs like TLT and HYG.
4. On-Chain Analytics:
Analyzes MVRV (Market Value to Realized Value) ratio to spot potential over/undervaluation.
Examines NUPL (Net Unrealized Profit/Loss) and active Bitcoin addresses.
PivotFind analyzes these indicators collectively, looking for significant correlations and confluences, to provide a view of the market's position within the 4-year cycle and spot the conditions for potential Cycle tops and bottoms (cycle pivots).
Who Is This For?
PivotFind may be particularly useful for:
- Long-term investors looking to optimize entry and exit points within the 4-year cycle
- Individuals who want to understand mid-term trends without engaging in daily analysis of multiple charts (due to lack of time and/or financial knowledge)
- Bitcoin Holders and miners planning their decisions around critical market pivot points
It's less suitable for scalpers, day-traders or those focused on short-term price movements.
Value Proposition
PivotFind simplifies market analysis by bringing together a wide range of indicators and data sources across different timeframes. It uses built-in logic to interpret these inputs within the context of Bitcoin's cycles, giving users an efficient way to spot potential major market shifts. This all-in-one approach helps make sense of complex market conditions and supports more informed decision-making.
Since Bitcoin’s broader cycle strongly influences the entire crypto market, PivotFind can also be useful for investors who are focused on Altcoins, not just Bitcoin.
Important Note (Disclaimer)
Past performance, and patterns, do not guarantee future results. Therefore, PivotFind should be used as one of many tools in your analysis. While the indicator provides a multi-faceted and multi-timeframe analysis of factors historically correlated with pivotal price shifts, it cannot predict future prices with certainty. It's a tool to help inform your decisions, not make them for you. Always conduct your own research and remember that all investments, especially in cryptocurrencies, involve risk.
Recommended Settings
PivotFinds works best on the 1D INDEX:BTCUSD chart (dark-mode, logarithmic scale).
This indicator is not publicly available and requires special access.
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
Multi Asset Histogram [ChartPrime]Multi Asset Histogram Indicator
Overview:
The "Multi Asset Histogram" indicator provides a comprehensive visualization of the performance of multiple assets relative to each other. By calculating a score for each asset and displaying it in a histogram format, this indicator helps traders quickly identify the trends, dominant asset and the average performance of the assets in the selected group.
Key Features:
◆ Multi-Asset Score Calculation:
The indicator calculates a trend score for each selected asset based on the price source (e.g., hl2).
The trend score is determined by comparing the current price to the prices over the past bars back defined by user, adding or subtracting points based on whether the current price is higher or lower than previous prices.
// Score Function
trscore(src) =>
total = 0.0
for i = 1 to 50
total += (src >= nz(src ) ? 1 : -1)
total
◆ Flexible Symbol Input:
Traders can input up to 10 different symbols (e.g., BTCUSD, ETHUSD, etc.) to be included in the histogram analysis.
◆ Dynamic Visualization:
A histogram is plotted for each asset, with bars colored based on the score, providing a clear visual representation of the relative performance.
Color gradients from red to aqua indicate the performance, with red representing negative scores and aqua representing positive scores.
◆ Adaptive Histogram Lines:
The width and placement of histogram lines adapt based on the calculated scores, ensuring clear visualization regardless of the values.
Dashed lines represent the mean score of all assets, helping traders identify the overall market trend.
◆Detailed Labels and Values:
Labels are placed on the histogram to display the exact score for each asset.
Mean value and zero line labels provide additional context for the overall performance.
◆ Visual Scaling Lines:
Zero line and mean line are clearly marked, helping traders understand the distribution and scale of scores.
Scales on the left and right of the histogram indicate the performance range.
◆ Informative Table:
A table is displayed on the chart, showing the dominant asset (the one with the highest score) and the mean score of all assets.
The table updates dynamically to reflect real-time changes in asset performance.
◆ Settings:
Length: The value of number bars back is greater or less than the current value of the source
Source: The price source to be used for score calculation (e.g., hl2).
Symbols: Up to 10 different asset symbols can be input for analysis.
Usage Notes:
This indicator is useful for traders who monitor multiple assets simultaneously and need a quick visual reference to identify the strongest and weakest performers.
The color coding and dynamic labels make it easy to interpret the relative performance and make informed trading decisions.
This indicator is designed to enhance multi-asset analysis by providing a clear, visual representation of each asset's performance relative to the others, making it easier to identify trends and dominant assets in the market.
Funding Rate [CryptoSea]The Funding Rate Indicator by is a comprehensive tool designed to analyze funding rates across multiple cryptocurrency exchanges. This indicator is essential for traders who want to monitor funding rates and their impact on market trends.
Key Features
Exchange Coverage: Includes data from major exchanges such as Binance, Bitmex, Bybit, HTX, Kraken, OKX, Bitstamp, and Coinbase.
Perpetual Futures and Spot Markets: Fetches and analyzes pricing data from both perpetual futures and spot markets to provide a holistic view.
Smoothing and Customization: Allows users to smooth funding rates using a moving average, with customizable MA lengths for tailored analysis.
Dynamic Candle Coloring: Option to color candles based on trading conditions, enhancing visual analysis.
In the example below, the indicator shows how the funding rate shifts with market conditions, providing clear visual cues for bullish and bearish trends.
How it Works
Data Integration: Uses a secure security fetching function to retrieve pricing data while preventing look-ahead bias, ensuring accurate and reliable information.
TWAP Calculation: Computes Time-Weighted Average Prices (TWAP) for both perpetual futures and spot prices, forming the basis for funding rate calculations.
Funding Rate Calculation: Determines the raw funding rate by comparing TWAPs of perpetual futures and spot prices, then applies smoothing to highlight significant trends.
Color Coding: Highlights the funding rate with distinct colors (bullish and bearish), making it easier to interpret market conditions at a glance.
In the example below, the indicator effectively differentiates between bullish and bearish funding rates, aiding traders in making informed decisions based on current market dynamics.
Application
Market Analysis: Enables traders to analyze the impact of funding rates on market trends, facilitating more strategic decision-making.
Trend Identification: Assists in identifying potential market reversals by monitoring shifts in funding rates.
Customizable Settings: Provides extensive input settings for exchange selection, MA length, and candle coloring, allowing for personalized analysis.
The Funding Rate Indicator by is a powerful addition to any trader's toolkit, offering detailed insights into funding rates across multiple exchanges to navigate the cryptocurrency market effectively.
RSI Screener / Heatmap - By LeviathanThis script allows you to quickly scan the market by displaying the RSI values of up to 280 tickers at once and visualizing them in an easy-to-understand format using labels with heatmap coloring.
📊 Source
The script can display the RSI from a custom timeframe (MTF) and custom length for the following data:
- Price
- OBV (On Balance Volume)
- Open Interest (for crypto tickers)
📋 Ticker Selection
This script uses a different approach for selecting tickers. Instead of inputting them one by one via input.symbol(), you can now copy-paste or edit a list of tickers in the text area window. This approach allows users to easily exchange ticker lists between each other and, for example, create multiple lists of tickers by sector, market cap, etc., and easily input them into the script. Full credit to @allanster for his functions for extracting tickers from the text. Users can switch between 7 groups of 40 tickers each, totaling 280 tickers.
🖥️ Display Types
- Screener with Labels: Each ticker has its own color-coded label located at its RSI value.
- Group Average RSI: A standard RSI plot that displays the average RSI of all tickers in the group.
- RSI Heatmap (coming soon): Color-coded rows displaying current and historical values of tickers.
- RSI Divergence Heatmap (coming soon): Color-coded rows displaying current and historical regular/hidden bullish/bearish divergences for tickers.
🎨 Appearance
Appearance is fully customizable via user inputs, allowing you to change heatmap/gradient colors, zone coloring, and more.
Multi BTC Rolling APY Calculator [presentTrading]█ Introduction and How it is Different
The "Multi BTC Rolling APY Calculator " is an innovative Pine Script indicator tailored for cryptocurrency traders, providing insights into arbitrage opportunities and market sentiment by calculating the Rolling Annual Percentage Yield (APY) between spot and futures prices of Bitcoin. Unlike traditional APY calculators, this tool specializes in capturing the nuances of the highly volatile and less efficient cryptocurrency markets. Rolling APY is derived from traditional market basis arbitrage but adapted to highlight significant discrepancies that frequently occur between derivative and underlying asset prices in crypto markets.
Historical backtesting has revealed that Bitcoin's Rolling APY can serve as a robust indicator of market sentiment:
- Below 0%: Often indicates panic or 'end-of-world' scenarios.
- 0-5%: Signifies extreme market fear.
- 5-10%: Reflects a calm market environment.
- 10-15%: Suggests a moderately warm market.
- 15-20%: Indicates an overheated market.
- **Above 20%: Signals FOMO (fear of missing out).
This nuanced understanding of Rolling APY helps investors not only spot arbitrage opportunities but also gauge the emotional state of the market, providing a dual function that enhances trading strategies in the volatile realm of cryptocurrencies.
█ Strategy: How It Works – Detailed Explanation
🔶 Rolling APY Calculation
The Rolling APY calculation is crucial for understanding the annualized potential returns from arbitrage strategies, given by the formula:
APY = ((Future Price - Spot Price) / Spot Price) * (365 / Days Until Expiration) * 100
This annualizes the observed premium or discount on futures contracts relative to the spot price, providing a year-over-year expectation of returns if one were to engage in arbitrage over the specified period.
🔶 Days Calculation
The accuracy of APY is contingent upon the precise calculation of days until each contract expires:
Days = (Expiration Timestamp - Current Timestamp) / 86400000
This calculation ensures the APY reflects true market dynamics for each futures contract's duration.
█ Trade Direction
While this tool does not provide direct trading signals, it informs traders about potential arbitrage opportunities and the prevailing market sentiment. Traders can leverage this data to make strategic decisions, aligning long or short positions with the anticipated market movements and arbitrage conditions.
█ Usage
By inputting specific parameters related to their market analysis, traders can monitor discrepancies in Bitcoin’s pricing across different timelines, which is especially beneficial for those involved in derivatives trading, arbitrage, and sentiment analysis.
█ Default Settings
- Resolution: Controls the frequency of data (default is daily).
- Show numbers in annual: Determines whether APY is displayed on an annual basis.
- Base Symbol and Future Symbols: Specify the spot and futures markets for analysis.
LONG/SHORT PIFRO que esse indicador faz?
Esse indicador tem o objetivo de plotar o valor de Premium Index e Funding Rate de qualquer token que seja negociado nos futuros da Binance. Basta acessar o token, por exemplo "BTCUSDT" ou "BTCUSDT.P" e o indicador funcionará de forma automática.
A ideia de leitura desse indicador é verificar as maiores oscilações e aliar a analise técnica para tomar uma decisão de compra ou venda.
What does this indicator do?
This indicator aims to plot the Premium Index and Funding Rate value of any token that is traded on Binance futures. Just access the token, for example "BTCUSDT" or "BTCUSDT.P" and the indicator will work automatically.
The idea of reading this indicator is to check the biggest fluctuations and combine technical analysis to make a buy or sell decision.
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O que é o Índice Bitcoin Premium?
O índice Bitcoin Premium rastreia o prêmio ou desconto dos contratos perpétuos de Bitcoin em relação ao preço do índice à vista por minuto. O Índice de prêmio é baseado na diferença de preço entre o último preço negociado de um contrato perpétuo e o preço do índice à vista. O preço do índice à vista é um índice à vista ponderado pelo volume, o que significa um preço médio obtido em várias bolsas.
Basicamente, ele mostra para cada criptomoeda se o mercado à vista está negociando acima ou abaixo do contrato perpétuo. O valor pode ser superior, inferior ou igual a 0. Quando o valor está acima de 0, o contrato perpétuo está sendo negociado acima do “preço de referência”, quando o valor está abaixo de 0, o índice à vista está negociando acima do contrato perpétuo .
Como ler o índice premium do Bitcoin?
Existem várias maneiras de visualizar o Índice Bitcoin Premium. Você pode observar o valor (acima ou abaixo de 0) semelhante às taxas de financiamento ou pode observar certos extremos. Esta informação pode ser muito útil na sua estratégia de negociação. O gráfico é exibido como um gráfico de velas com um corpo e o pavio (também conhecido como sombra) da vela. O pavio pode mostrar um certo extremo, enquanto o fechamento da vela mostra o valor.
O valor acima ou abaixo de 0 mostra se o preço dos contratos perpétuos de Bitcoin está sendo negociado acima ou abaixo do índice à vista. Quando o índice à vista está sendo negociado em alta, o prêmio cai abaixo de 0 e fica negativo, geralmente, isso é conhecido como um sinal de alta. Quando o valor está sendo negociado acima de 0 e fica positivo, significa que o contrato perpétuo do Bitcoin está sendo negociado acima do índice à vista, geralmente isso é visto como um sinal de baixa.
Os mercados são um reflexo das emoções humanas e muitas vezes, antes que o preço possa mudar, vemos um certo extremo nas emoções. Esse extremo pode ser identificado no Índice Premium. Quando temos um sinal extremo no Índice Bitcoin Premium as chances de uma reversão aumentam. Esta pode ser uma reversão de curto prazo ou uma reversão maior.
Resumindo, um prêmio de índice à vista é geralmente de alta e um prêmio de derivativos é geralmente um sinal de baixa.
Mas, tal como acontece com as taxas de financiamento, por vezes demora um pouco para que essa pressão de compra ou venda seja expressa no preço e, portanto, é sempre importante combinar esta métrica com outras métricas, como a estrutura de preços.
Por exemplo, aqui na imagem abaixo podemos ver uma leitura extrema no índice premium do Bitcoin. Embora várias horas após o evento ainda vejamos a subida do preço, vemos que está bastante perto de uma reversão e, eventualmente, o preço muda.
Descrição por whaleportal
What is the Bitcoin Premium Index?
The Bitcoin Premium index tracks the premium or discount of Bitcoin perpetual contracts relative to the spot index price per minute. The premium Index is based on the difference in price between the last traded price of a perpetual contract and the spot index price. The spot index price is a volume- weighted spot index, which means an average price taken from multiple exchanges.
Basically, it shows you for each cryptocurrency whether the spot market is trading higher or lower than the perpetual contract. The value can either be above, below, or equal to 0. When the value is above 0, the perpetual contract is trading higher than the “mark price”, when the value is below 0 the spot index is trading higher than the perpetual contract.
How to read the Bitcoin premium index?
There are multiple ways to view the Bitcoin Premium Index. You can either look at the value (above or below 0) similar to the funding rates or you can look at certain extremes. This information can be very helpful in your trading strategy. The chart is displayed as a candlestick chart with a body and the wick (also known as shadow) of the candle. The wick can show a certain extreme, while the close of the candle shows the value.
The value, either above or below 0 shows whether the price of Bitcoin perpetual contracts is trading higher or lower than the spot index. When the spot index is trading higher, the premium will go below 0 and turns negative, usually, this is known to be a bullish sign. When the value is trading higher than 0 and turns positive, it means the Bitcoin perpetual contract is trading higher than the spot index, usually, this is seen as a bearish signal.
The markets are a reflection of human emotions and often before the price can shift we are seeing a certain extreme in emotions. That extreme can be spotted in the Premium Index. When we have an extreme signal in the Bitcoin Premium Index the chances of a reversal increase. This can be either a short-term reversal or a bigger reversal.
In short, a spot index premium is usually bullish and a derivatives premium is usually a bearish signal.
But as with funding rates, it sometimes takes a moment for that buying or selling pressure to be expressed in the price and therefore it is always important to combine this metric with other metrics like the price structure.
For example, here in the image below we can see an extreme reading in the premium index on Bitcoin. Although in several hours after the event we still see the price climb, we do see that it’s rather close to a reversal and eventually the price turns around.
Description by whaleportal
Swing Sniper by Republic of TradersSwing Sniper: A Comprehensive Market Reversal Indicator
Description:
Swing Sniper, developed by Republic of Traders, is a sophisticated trading indicator designed for traders who require precise market reversal signals. It performs optimally across all trading instruments and timeframes, offering both reliability and precision.
How It Works:
Swing Sniper employs a complex signal generation mechanism that activates only when six distinct conditions align within a specific timeframe. This includes:
A modified Commodity Channel Index (CCI) that helps identify short-term price fluctuations.
A Relative Momentum Index (RMI) utilized for recognizing long-term market trends.
A Supertrend indicator serves as a dynamic trend filter.
Several custom parameters that enhance signal reliability.
These components work synergistically to ensure that each trading signal is robust and well-founded. The indicator specializes in capturing significant market reversals by requiring a confirmation of trend reversal through a break and close above or below a previous supply/demand zone.
Usage Instructions:
Upon a valid signal, Swing Sniper advises traders that a potential market reversal has occurred and an entry may be considered in the direction of the new trend. Traders are recommended to set alerts for "once per candle close," allowing them to monitor multiple charts and timeframes simultaneously. Proper risk management is encouraged by placing stop losses just below or above the previous swing low or high and the signal candle's low or high. Take profits should similarly be set to capitalize on potential swings.
Why Choose Swing Sniper:
Swing Sniper is designed not only as a tool for generating entries but as a strategic component of your trading methodology. It brings a clear, analytical approach to navigating the markets, supported by detailed and logical indicator collaboration. This ensures users understand the underlying mechanics and can apply the tool effectively within their trading strategy.
Commitment to Originality and Utility:
Swing Sniper is a unique creation, adhering to TradingView’s standards by offering actionable insights that are distinct from other indicators available on the platform. It is meticulously crafted, featuring an original combination of technical analysis tools tailored to enhance market reversal detection.
Disclaimer:
Past performance is not indicative of future results. Always exercise due diligence and consider market conditions when trading.
Visualization Aid:
The accompanying chart visualization helps users identify signal examples, marked with a red triangle for market reversals short and a green triangle for market reversals long.
Embrace the strategic depth and precision of Swing Sniper and enhance your trading confidence and accuracy in financial markets.
Blockcircle Hard Forks & HalvingsThe Hard Forks & Halvings indicator simply displays the dates of system wide network upgrades being completed for Bitcoin and Ethereum.
Those upgrades are called hard forks and halvings.
In the screenshot you will see that March 13 marked for the system wide Ethereum network upgrade called "ETH Dencun", it is marked in blue.
HOW IT WORKS?
For example:
Bitcoin Halvings: Nov 28, 2012, Jul 9, 2016, May 11, 2020, etc..
Bitcoin Hard Forks: Aug 2015, Feb 2016, Mar 2016, Aug 2017, etc..
Ethereum Hard Forks: Jul 30, 2015, Mar 14, 2016, Mar 13, 2024, etc...
It's conveniently an indicator so it allows you to overlay it on top of any price chart, e.g. BTC/USD, ETH/USD, ARB/USD, MATIC/USD, OP/USD, RONIN/USD, STRK/USD, etc...so you can measure the exact impact each individual significant event had on the underlying asset price.
HOW TO USE IT?
You can apply this to examine price impact on competing Layer 1s and complimentary and key beneficiary Layer 2s like ARB/OP/MATIC/STRK, which are worth monitoring closely in light of the recent Ethereum Hard Fork Dencun Upgrade and Bitcoin Halving on April 18-19.
WHAT MAKES IT' USEFUL AND ORIGINAL?
I could not find an indicator that does anything remotely close to this, so decided to build it as it's so useful to track these key dates. You can plan ahead!
One of the key benefits is a sharp reduction in Layer 2 transaction processing fees, and will lay the ground work required for "Data Blobs", think of it as a form of transaction optimization to improve scalability for the entire Ethereum ecosystem.
This will strongly accelerate staking and retaking efforts. This indicator has already helped so much in being to forecast that we were going to experience a bit of a pull back post Dencun upgrade, because historically, we've generally reverted back to the mean post upgrade.
If you have any questions about it, please post it them! Thank you
Neural Network Synthesis: Trend and Valuation [QuantraSystems]Neural Network Synthesis - Trend and Valuation
Introduction
The Neural Network Synthesis (𝓝𝓝𝒮𝔂𝓷𝓽𝓱) indicator is an innovative technical analysis tool which leverages neural network concepts to synthesize market trend and valuation insights.
This indicator uses a bespoke neural network model to process various technical indicator inputs, providing an improved view of market momentum and perceived value.
Legend
The main visual component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is the Neural Synthesis Line , which dynamically oscillates within the valuation chart, categorizing market conditions as both under or overvalued and trending up or down.
The synthesis line coloring can be set to trend analysis or valuation modes , which can be reflected in the bar coloring.
The sine wave valuation chart oscillates around a central, volatility normalized ‘fair value’ line, visually conveying the natural rhythm and cyclical nature of asset markets.
The positioning of the sine wave in relation to the central line can help traders to visualize transitions from one market phase to another - such as from an undervalued phase to fair value or an overvalued phase.
Case Study 1
The asset in question experiences a sharp, inefficient move upwards. Such movements suggest an overextension of price, and mean reversion is typically expected.
Here, a short position was initiated, but only after the Neural Synthesis line confirmed a negative trend - to mitigate the risk of shorting into a continuing uptrend.
Two take-profit levels were set:
The midline or ‘fair value’ line.
The lower boundary of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicators valuation chart.
Although mean-reversion trades are typically closed when price returns to the mean, under circumstances of extreme overextension price often overcorrects from an overbought condition to an oversold condition.
Case Study 2
In the above study, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is applied to the 1 Week Bitcoin chart in order to inform long term investment decisions.
Accumulation Zones - Investors can choose to dollar cost average (DCA) into long term positions when the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicates undervaluation
Distribution Zones - Conversely, when overvalued conditions are indicated, investors are able to incrementally sell holdings expecting the market peak to form around the distribution phase.
Note - It is prudent to pay close attention to any change in trend conditions when the market is in an accumulation/distribution phase, as this can increase the likelihood of a full-cycle market peak forming.
In summary, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is also an effective tool for long term investing, especially for assets like Bitcoin which exhibit prolonged bull and bear cycles.
Special Note
It is prudent to note that because markets often undergo phases of extreme speculation, an asset's price can remain over or undervalued for long periods of time, defying mean-reversion expectations. In these scenarios it is important to use other forms of analysis in confluence, such as the trending component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator to help inform trading decisions.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
Example Settings
As used above.
Swing Trading
Smooth Length = 150
Timeframe = 12h
Long Term Investing
Smooth Length = 30
Timeframe = 1W
Methodology
The 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator draws upon the foundational principles of Neural Networks, particularly the concept of using a network of ‘neurons’ (in this case, various technical indicators). It uses their outputs as features, preprocesses this input data, runs an activation function and in the following creates a dynamic output.
The following features/inputs are used as ‘neurons’:
Relative Strength Index (RSI)
Moving Average Convergence-Divergence (MACD)
Bollinger Bands
Stochastic Momentum
Average True Range (ATR)
These base indicators were chosen for their diverse methodologies for capturing market momentum, volatility and trend strength - mirroring how neurons in a Neural Network capture and process varied aspects of the input data.
Preprocessing:
Each technical indicator’s output is normalized to remove bias. Normalization is a standard practice to preprocess data for Neural Networks, to scale input data and allow the model to train more effectively.
Activation Function:
The hyperbolic tangent function serves as the activation function for the neurons. In general, for complete neural networks, activation functions introduce non-linear properties to the models and enable them to learn complex patterns. The tanh() function specifically maps the inputs to a range between -1 and 1.
Dynamic Smoothing:
The composite signal is dynamically smoothed using the Arnaud Legoux Moving Average, which adjusts faster to recent price changes - enhancing the indicator's responsiveness. It mimics the learning rate in neural networks - in this case for the output in a single layer approach - which controls how much new information influences the model, or in this case, our output.
Signal Processing:
The signal line also undergoes processing to adapt to the selected assets volatility. This step ensures the indicator’s flexibility across assets which exhibit different behaviors - similar to how a Neural Network adjusts to various data distributions.
Notes:
While the indicator synthesizes complex market information using methods inspired by neural networks, it is important to note that it does not engage in predictive modeling through the use of backpropagation. Instead, it applies methodologies of neural networks for real-time market analysis that is both dynamic and adaptable to changing market conditions.
Weighted Average Volume Depth [QuantraSystems]Weighted Average Volume Depth
Introduction
The Weighted Average Volume Depth (𝓦𝓐𝓥𝓓) indicator is calibrated to provide extensive insights, calculated using volumetric price action and volume depth, and provides dynamic adjustments based upon historical volatility.
This indicator is a valuable asset for traders and investors, aiming to capture trends, measure dynamic volatility, and provide market reversion analysis in a systematic way.
Legend
Volumetric Top Cap: Plotted at y = 0, this line represents the probabilistic maximum value, or ‘cap’ for the signal line. It is colored using a binary color scheme, and indicates the dominant trend direction - green for an uptrend and purple for a downtrend.
Base Line: Calculated using a volume-weighted volatility measurement, this line is used as the benchmark to calculate momentum in the 𝓦𝓐𝓥𝓓 indicator.
Signal Line: The signal line represents the volume and volatility weighted measurements, and oscillates between the Base Line and Top Cap. Its position between these levels provides the depth of insights available in this script.
When the signal line is remaining in close proximity to the base line, this is indicative of a low volatility market environment. These periods are also reflected as muted bar coloring when the ‘Trend Intensity’ setting is enabled.
Conversely, when the signal line approaches, or even breaks above the Top Cap, this is characteristic of an unsustainable trending action - and probabilistically speaking, a reversion or consolation is likely to occur at these levels.
Highlighting: When this setting is enabled, background coloring is applied when the Signal Line breaks above the Top Cap. This highlights green as an oversold zone, and purple as an overbought zone.
Reversal Signals: When price begins to reverse from a zone of overextension, a signal is plotted when this reversion occurs from a high probability zone.
Circle - Shows a possible bullish reversal.
Cross - Shows a possible bearish reversal.
Case Study
In the above image, we showcase three distinct trades in short succession, showcasing the 𝓦𝓐𝓥𝓓’s speed and accuracy under the right conditions.
The first long trade was initiated upon receiving a bullish reversal signal. The trade was then closed after the price experienced a sharp upwards movement - and an overbought signal was indicated by the purple shading.
The second, short trade was entered on the next bar, after a bearish reversal signal was printed by the indicator (a white cross). Similarly, this trade was closed upon the oversold signal.
Once again, a reversal signal was indicated by the 𝓦𝓐𝓥𝓓 indicator. This time a bullish signal (a white circle), and hence a long position was opened. However, this trade was held until a negative trend confirmation (signaled by the Top Cap’s shift in color). This makes apparent the indicator’s flexible nature, and showcases the multiple signaling types available for traders to use.
Recommended Settings
The optimal settings for the 𝓦𝓐𝓥𝓓 indicator will vary upon the chosen asset’s average level volatility, as well as the timeframe it is applied to.
Due to increased volatility levels on lower timeframes, it is recommended to increase the 'Top Cap Multiplier' to take into account the increased frequency of false signals found in these trading environments. The same can be said when used on highly volatile assets - a trader will likely benefit from using a higher 'Top Cap Multiplier.'
On more price-stable assets, as well as any asset on higher timeframes, there is merit to tightening the length of the 'Top Cap Multiplier,' due to the slower nature of price action.
Methodology
The 𝓦𝓐𝓥𝓓 starts with calculating the volume weighted average price and the volume weighted variance - which is the expectation of the squared deviation of a variable from its mean, giving insights into the distribution of trading volume.
Using the volume weighted variance, a standard deviation value is calculated based on user input. This value acts as the ‘Volumetric Top Cap’ - seen in the 𝓦𝓐𝓥𝓓 indicator window as the zero line.
The signal line is calculated as the difference between the current price and the theoretical upper or lower VWAP deviation bands. This line acts as the trigger for identifying prevailing trends and high probability reversal points.
The base line serves as a reference point for historical momentum. It is calculated using an exponential moving average of the lowest signal line values over a defined lookback period. This baseline helps in assessing whether the current momentum is high or low relative to historical norms.
Notes
Bar coloring can be turned off - especially useful when stacking multiple indicators as recommended, or set to 'Trend Intensity,' or 'Binary Trend' (which reflects the top cap coloring).
It is always recommended to never rely on a single indicator - and instead build and test multiple strategies utilizing more than one indicator as confirmation.
Pulse Profiler [QuantraSystems]Pulse Profiler
Introduction
The Pulse Profiler ( ℙℙ ) is specifically designed to unambiguously indicate weakening momentum after a strong impulse. The upper and lower standard deviation bands also allow the user to assess the strength of an impulse and differentiate it from general noise.
Due to the ℙℙ ’s rapid responsiveness to exhaustion in price movement it is ideally used for the trader to recognize when to start taking profit when combined with other indicators.
The novum is that by dynamically balancing its sensitivity to recent movements the ℙℙ considers the asset’s inherent volatility. By reducing noise without sacrificing signal, and by visualizing it in our typical modern QuantraAI style, the ℙℙ enhances the traders’ ability to distinguish impulses with weakening momentum from strong trending movements.
Legend
Impulse: The ℙℙ showing strength based on momentum and volume.
Dynamic standard deviation bands: Rolling probability based bands based on a rolling normal distribution. Adjustable, recommended are σ = 1.5 to σ = 2.5.
Neutral lines: Dynamic thresholds which get often respected as support or resistance.
Case Study
To properly employ the ℙℙ , the trader should use it to identify out-of-the-ordinary 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 which cause a following exhaustion.
The rolling standard deviation bands incorporate the asset’s historical behavior in regards to its inherent volatility on a rolling basis. If the asset shows strong 𝓲𝓶𝓹𝓾𝓵𝓼𝓮𝓼 that go beyond the rolling standard deviation, the event has been highly improbable. The trader then needs to determine if the price change was caused by critical external factors. If not, it is highly probable that the momentum exhausts and that price movement plateaus to enter a range.
These signals indicate that it is highly probable that closing a position upon these conditions is the correct choice.
If the 𝓲𝓶𝓹𝓾𝓵𝓼𝓮 reverses and retraces into the opposite direction, while moving more than 1.5σ across just 3 bars on the 4H chart, the signal indicates that a reversal is pushing the price down – in both momentum and volume.
A sharp reversal thus becomes more probable than not.
The ℙℙ can also be calibrated to find possible trend exhaustions on a longer timeframe (1D).
Please always use multiple Quantra indicators to add confirmations to your signals.
Recommended Settings
Swing Trading (4H chart)
Standard Deviation Lookback: 150
Standard Deviation Multiplier (σ): 2.5
Display Variant: Classic
Choose Mode for Bar Coloring: Signal
Trend exhaustion (1D chart)
Standard Deviation Lookback: 200
Standard Deviation Multiplier (σ): 2.0
Display Variant: Classic
Choose Mode for Bar Coloring: Extremes
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
The ℙℙ is also sensitive to divergences for those interested in utilizing this feature.
Through a special combination of price, volume and momentum you get a holistic overview on the impulse strengths of movements.
The two neutral lines in the center act as dynamic, volume and volatility adjusted thresholds. Often the signal line respects them as support and resistance.
The upper and lower standard deviation lines express the rarity of an impulse based on the asset’s inherent volatility.
The indicator needs a long enough timespan to build up its probability estimation, therefore the asset needs sufficient price history.
The indicator requires thorough volume data. If the source of an asset pair does not forward it, try to find another source or exchange for the same pair.
Signal Mode on the 4H chart is a relevant part of this indicator when used in isolation and helps to analyze momentum adjusted by volatility.
Methodology
The ℙℙ combines the Arnaud Legoux Moving Average (ALMA) with a bespoke volume and momentum calculation, with a classical Exponential Moving Average (EMA) on price data.
The ℙℙ itself integrates ALMA for volume and momentum with an EMA calculation on price, creating a unique blend that expresses impulses using their three raw main components.
The indicator calculates dynamic standard deviation bands based on an adjustable lookback period and the adjustable sigma (σ), to signal when the impulse strength is just uncommon or even extraordinary when compared to the usual price movements:
σ = 1.5 the probability of similar impulse strength occuring is 13.37% / 2, hence ~ 6.69%
σ = 2.0 the probability of similar impulse strength occuring is ~ 2.28%
σ = 2.5 the probability of similar impulse strength occuring is ~ 0.62%
By detecting extremely improbable conditions the indicator can create an inversely highly probable signal to its user.
Neutral bands are calculated based on the ℙℙ alongside a rolling, dynamic multiplier. This effectively provides dynamic thresholds for approximating common volatility.
Heikin Ashi method: The indicator uses a custom function to calculate Heikin Ashi values, useful for smoothing impulse data and identifying trends.
Reversion Signals: Specifically for Heikin Ashi displays, we plot triangles as signals, useful to easily spot potential reversals.
The Signal Mode uses these different thresholds to highlight significant market moves.
Rate of Change Suite [QuantraSystems]Rate of Change Suite
Introduction
The "Rate of Change Suite" (𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮) refines traditional RoC concepts by incorporating additional elements that provide more nuanced views of market trends, potential reversions, and momentum shifts.
Its main benefits are that it allows traders to detect momentum changes and frontrun trend shifts.
The suite is designed to be highly adaptable, catering to various trading styles, timeframes and market conditions. It is comprised of 3 metrics:
The RoC base line plots the rate of change, the Signal Histogram to confirm trends, and the Signal Confirmation Oscillator to inform reversal probabilities. For the early detection of trend shifts, the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is a comprehensive tool for the toolkit of modern traders.
A core component of the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is the ability to apply its processing techniques to any other indicator found on TradingView - essentially leveraging the signal power of existing analysis methods. This is achieved by modifying the ‘Source’ input.
Legend
𝓡𝓸𝓒 base line: The primary component of the suite, the RoC Line, offers a direct view of market momentum. An upward trending RoC line informs the potential for a long position, while a downward trend might signal the opportunity for a short position. Both include a secondary confirmation by the color change of the line itself. The Heikin Ashi transformed version of the RoC line provides greater resistance to rapid movements, or outliers.
Signal Histogram: This feature works in tandem with the base RoC Line, providing an additional third confirmation of trends. A rising histogram supports the presence of an upward trend. Conversely, a declining histogram aligns with downward trends.
Signal Confirmation Oscillator: This dotted-line is crucial for detecting peaks or troughs in market momentum: These can precede reversals or shifts in the prevailing trend. Traders can use this signal to anticipate and prepare for potential changes quicker than others.
Case Study
Primarily a tool to follow trends, the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 implies much more – you can trade with a confirmed trend signal entry and a mean reversion signal for the exit:
Here we see two practical cases of the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 on the 1h BTC chart.
In the first scenario, the trader waits for three confirmations from the indicator.
The 𝓡𝓸𝓒 baseline to lead the run and looks for confirmation two and three:
𝓡𝓸𝓒 base line color shifts
and the Signal Histogram follows past the null midline.
The trader has adjusted their risk beforehand and enters the long position.
The 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 shows traders when to take profit:
The Signal Confirmation Oscillator (SCO, dotted line) moves beyond the 𝓡𝓸𝓒 baseline and the Signal Histogram. The trader can take 50% of the profit already.
The trader waits patiently, and if the SCO reverses, the rest of the position is closed.
The same works inversely for the second trade, which successfully frontran the decline shortly after.
Recommended Settings
Day Trading (1H chart)
Length: 30
Smooth Length: 10
Display Variant: Classic
Choose Mode: Trend Following
Investing – Follow Trend (1D chart)
Default settings
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars’ colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
Divergence Sensitivity: Quantra’s 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is finely tuned to detect divergences, a key feature for identifying possible trend reversals.
Trend Following and Reversions: Primarily a tool for trend following, the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is also adept at spotting potential reversions and slowdowns in momentum.
Range Trading Compatibility: In its Heikin Ashi Candles mode, the suite becomes particularly effective for range trading strategies.
High Customizability: Traders can customize the suite with various visualization options, including classic line representation, HA transformation, and bar coloring. These can be based on Heikin Ashi Candles or Trend Following approaches, providing flexibility to adapt to different trading scenarios.
Methodology
The 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is built on a foundation of functions that define and calculate the Rate of Change. They employ a variety of moving average types (SMA, EMA, DEMA, TEMA, WMA, etc.) which can be selected to optimize the RoC line.
A bespoke function to calculate Heikin-Ashi values is engineered to offer a more consistent view of the trend.
The Signal Histogram is derived by mathematically processing the base RoC signal. The Signal Confirmation Oscillator is based on a modified formula, adjusted to align with the RoC dynamics.
With a range of customization options for its visual presentation, including color schemes and display styles, the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 is designed to cater to both trend following indications as well as finding signals for mean reversion trades. This multifaceted approach enables the 𝓡𝓸𝓒 𝓢𝓾𝓲𝓽𝓮 to allow the trader to combine signals of both types to de-risk his positions.
Regression Sloped RSI [QuantraSystems]Regression Sloped RSI
Introduction
The Regression Sloped RSI (𝓡𝓢-𝓡𝓢𝓘) enhances the classical RSI by incorporating a form of linear regression analysis, which adjusts the traditional RSI in relation to the calculated slope over a specified lookback period.
Its innovative approach reduces the occurrence of false signals compared to the classical RSI. Furthermore, it is particularly effective in markets characterized by strong trends. This is because it responds faster while retaining a high level of whipsaw resistance. The Heikin-Ashi style processing is critical to this.
It also provides robust reversal signals from dynamic overbought and oversold zones to further enhance mean-reversion trading.
Legend
The coloring of the 𝓡𝓢-𝓡𝓢𝓘 changes based on trend direction: A bright green when upwards, lilac when downwards. The strength of the trend is expressed in its distance to Null. Its acceleration is found in the Heikin-Ashi (HA) candles.
The 𝓡𝓢-𝓡𝓢𝓘 in combination with the HA bars can be used to achieve earlier entries, when the former passes across the latter in an obvious divergence.
Case Study
In this example the 𝓡𝓢-𝓡𝓢𝓘 is used to make a few intra-day trades on the Ethereum 15 minute chart. Each trade was open for approximately 5 hours. On the first trade we enter a long in an early entry. The indicator gives us three confirmations which we should all check for. First we have a positive candle developing, secondly the 𝓡𝓢-𝓡𝓢𝓘 (line) rises above the Heikin-Ashi candles, thirdly the classical RSI (the saturated surface in the background) rises as well.
The trader should then calculate their position sizing responsibly and enter into a short daytrade. Please always have invalidation rules, for example a) if the initial HA candle closes negative b) you can place your stop loss at 1SD into the opposite direction.
Always use adequate risk management, never risk more than 1% of your portfolio, unless you are a seasoned trader with your own calculated position sizes.
Always forward test your rules, assets, timeframe and settings sufficiently.
It is always recommended to use multiple Quantra indicators to add confirmations to your signals - this is by design.
Recommended Settings
Please reset to defaults before enabling recommended settings.
Intra-Day Trading (15min chart)
RSI Length: 22
LR Length: 25
Smoothing: EMA
Toggle SD Bands: On
Mode for Coloring: Candles
Trend Following (4H chart)
RSI Length: 40
LR Length: 35
Smoothing: LSMA
Toggle SD Bands: Off
Mode for Coloring: Extremes or Trend Following
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
The 𝓡𝓢-𝓡𝓢𝓘 is finely tuned to detect divergences.
Primarily utilized for trend following, the 𝓡𝓢-𝓡𝓢𝓘 also demonstrates effectiveness in identifying reversions, intensity of movements and the navigation of range-bound markets.
Allows for easy identification of slowdowns in momentum and thus negative rate of change.
Methodology
The 𝓡𝓢-𝓡𝓢𝓘 takes the classical RSI using a specified lookback length and computes the slope of a linear regression line applied to the RSI values. This slope is used to adjust the RSI.
This sloped RSI can be further smoothed using various Moving Averages with customizable lengths.
For a more nuanced view of market trends, the 𝓡𝓢-𝓡𝓢𝓘 applies a specialized Heikin Ashi method. This transformation modifies the Sloped RSI values in order to weigh and reflect the average price, offering a smoother representation compared to traditional candlestick patterns.
The 𝓡𝓢-𝓡𝓢𝓘 calculates upper and lower bounds based on a specified standard deviation multiplier and adjustable lookback period, providing a dynamic framework to identify extrema and thus overbought and oversold conditions.
Particularly in the Heikin Ashi mode, the 𝓡𝓢-𝓡𝓢𝓘 can display reversion signals. These are plotted as shapes on the chart, indicating high probability reversal points in the market trend.
Wave Pendulum Trend [QuantraSystems]Wave Pendulum Trend
Introduction
The Wave Pendulum Trend (𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭) extrapolates market trends using physical principles derived from waves and pendulums. This indicator is a bespoke build, and its performance and behavior cannot be compared to existing indicators.
It is designed for trend following but is also effective for identifying mean reversions, momentum strength, and shows range-bound market periods within the dynamic bands.
In order to ascertain a smooth yet rapid trend direction of the market, the 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 combines several factors. A bespoke set of functions captures the momentum of price movements and dynamically weighs it over time. The indicator then extrapolates acceleration from the change in delta of price movements.
Legend
With bar coloring enabled, the price section mirrors current trend conditions. Please keep this feature disabled if you intend to use multiple indicators to avoid confusion.
The 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 presents extensive market insights. The purple and green bands around the oscillator signal the selected standard deviation (default σ = 2), for the trader to calculate how common the trending movements are in relation to the selected asset’s history.
The inner, dynamic thresholds, indicated by the blue “Range-bound market” label in the graphic above, border the area that signals a ranging market if both 𝓐𝓬𝓬𝓮𝓵𝓮𝓻𝓪𝓽𝓲𝓸𝓷 and 𝓜𝓸𝓶𝓮𝓷𝓽𝓾𝓶 signals remain inside. If either line exceeds these thresholds, care is advised as a shift in market behavior is underway.
“Trend strength” in the graphic provides a good estimate for the trending movements strength.
If the signal lines exceed the set standard deviation in non-classic mode, a reversal is very likely.
Case Study
As shown in the above case study we see two profitable swing trades on the 4H chart of Ethereum. Please note the display variant here is set to “Heikin-Ashi”.
We always recommend using a multitude of indicators to attain multiple signals on the likelihood of opening the correct position. However, this standalone scenario serves as an example on how the 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 added two profitable swing trades.
The first short trade was opened after the 𝓐𝓬𝓬𝓮𝓵𝓮𝓻𝓪𝓽𝓲𝓸𝓷 and 𝓜𝓸𝓶𝓮𝓷𝓽𝓾𝓶 reversed after crossing the threshold of standard deviation. This trade offered a late entry only, these two factors were followed late by the third signal in this case – the trend reversal. Such a trade would require additional indicators to signal at the same time, so the trader can get more confirmations. The trade was closed after 6D with an 8% gain on a 1x short position.
The second trade is a long position that enters in the same manner. The trader takes the reversal beyond the select standard deviation as a likely entry. After 7D a triple confirmation was received, as indicated by the triangle, that a reversal or at least a plateau is extremely likely. The trade was closed after 7D with a 17.23% gain on a 1x long position.
Recommended Settings
Trend Following / Investing (1D chart)
Please use the default settings!
Swing Trading (4H chart)
Wave MA - Type: TEMA
Wave MA – Length: 30
Display Variant: Heikin-Ashi
Bar Coloring: Off
Choose Mode for Coloring: Signal
Notes
Quantra Standard Value Contents:
The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA.
Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both.
A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy.
To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals:
Settings: TEMA and DEMA length settings should be longer compared to other Moving Averages (MAs). Due to its complex calculations, the indicator requires a larger amount of historical data for accurate computation.
Sensitivity to Divergences: The Wave Pendulum Trend is particularly sensitive to divergences, making it a useful tool in spotting potential trend reversals or continuations.
Trend Following and Reversions: While it is primarily used for trend following, it also excels in identifying market reversions.
Momentum and Acceleration: The interaction between momentum and acceleration is a key feature of this indicator.
Visualization: The indicator offers various visualization options, including bar coloring based on HA Candles and extremes and trends. It also introduces a novel approach to visualizing the oscillator in the "Classic" mode and provides an adjustable Standard Deviation (SD) measure for reversal signals in non-classic modes.
Choose Mode for Coloring
Trend Following (Indicator above mid line counts as uptrend, below is downtrend)
Extremes (Everything beyond the SD bands is highlighted to signal mean reversion)
Candles (Color of HA candles as barcolor)
Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits)
Methodology
The methodology behind the Wave Pendulum Trend is inspired by wave and pendulum theories to extrapolate market moves. By calculating the momentum and its acceleration from price data, it provides a nuanced view of the market trend.
Traders should observe the color coding, which reflects the interplay between momentum, acceleration, and set thresholds for acceleration. The Signal Mode is particularly useful for quickly identifying trend, momentum, and acceleration exhaustions.
Additionally, the indicator can help filter out ranges with insufficient momentum acceleration. Traders are encouraged to experiment with this mode and adjust the threshold settings to suit their strategies.
Bandwidth Volatility - Silverman Rule of thumb EstimatorOverview
This indicator calculates volatility using the Rule of Thumb bandwidth estimator and incorporating the standard deviations of returns to get historical volatility. There are two options: one for the original rule of thumb bandwidth estimator, and another for the modified rule of thumb estimator. This indicator comes with the bandwidth , which is shown with the color gradient columns, which are colored by a percentile of the bandwidth, and the moving average of the bandwidth, which is the dark shaded area.
The rule of thumb bandwidth estimator is a simple and quick method for estimating the bandwidth parameter in kernel density estimation (KSE) or kernel regression. It provides a rough approximation of the bandwidth without requiring extensive computation resources or fine-tuning. One common rule of thumb estimator is Silverman rule, which is given by
h = 1.06*σ*n^(-1/5)
where
h is the bandwidth
σ is the standard deviation of the data
n is the number of data points
This rule of thumb is based on assuming a Gaussian kernel and aims to strike a balance between over-smoothing and under-smoothing the data. It is simple to implement and usually provides reasonable bandwidth estimates for a wide range of datasets. However , it is important to note that this rule of thumb may not always have optimal results, especially for non-Gaussian or multimodal distributions. In such cases, a modified bandwidth selection, such as cross-validation or even applying a log transformation (if the data is right-skewed), may be preferable.
How it works:
This indicator computes the bandwidth volatility using returns, which are used in the standard deviation calculation. It then estimates the bandwidth based on either the Silverman rule of thumb or a modified version considering the interquartile range. The percentile ranks of the bandwidth estimate are then used to visualize the volatility levels, identify high and low volatility periods, and show them with colors.
Modified Rule of thumb Bandwidth:
The modified rule of thumb bandwidth formula combines elements of standard deviations and interquartile ranges, scaled by a multiplier of 0.9 and inversely with a number of periods. This modification aims to provide a more robust and adaptable bandwidth estimation method, particularly suitable for financial time series data with potentially skewed or heavy-tailed data.
Formula for Modified Rule of Thumb Bandwidth:
h = 0.9 * min(σ, (IQR/1.34))*n^(-1/5)
This modification introduces the use of the IQR divided by 1.34 as an alternative to the standard deviation. It aims to improve the estimation, mainly when the underlying distribution deviates from a perfect Gaussian distribution.
Analysis
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Modelling Requirements
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Pros of Bandwidth as a volatility measure
Robust to Data Distribution: Bandwidth volatility, especially when estimated using robust methods like Silverman's rule of thumb or its modifications, can be less sensitive to outliers and non-normal distributions compared to some other measures of volatility
Flexibility: It can be applied to a wide range of data types and can adapt to different underlying data distributions, making it versatile for various analytical tasks.
How can traders use this indicator?
In finance, volatility is thought to be a mean-reverting process. So when volatility is at an extreme low, it is expected that a volatility expansion happens, which comes with bigger movements in price, and when volatility is at an extreme high, it is expected for volatility to eventually decrease, leading to smaller price moves, and many traders view this as an area to take profit in.
In the context of this indicator, low volatility is thought of as having the green color, which indicates a low percentile value, and also being below the moving average. High volatility is thought of as having the yellow color and possibly being above the moving average, showing that you can eventually expect volatility to decrease.
Dynamic Momentum GaugeOverview
The Dynamic Momentum Gauge is an indicator designed to provide information and insights into the trend and momentum of a financial asset. While this indicator is not directional , it helps you know when there will be a trend, big move, or when momentum will have a run, and when you should take profits.
How It Works
This indicator calculates momentum and then removes the negative values to focus instead on when the big trend could likely happen and when it could end, or when you should enter a trade based on momentum or exit. Traders can basically use this indicator to time their market entries or exits, and align their strategies with momentum dynamics.
How To Use
As previously mentioned, this is not a directional indicator but more like a timing indicator. This indicator helps you find when the trend moves, and big moves in the markets will occur and its possibly best to exit the trades. For example, if you decide to enter a long trade if the Dynamic Momentum Gauge value is at an extreme low and another momentum indicator that you use has conditions that you would consider to long with, then this indicator is basically telling you that there isn't more space for the momentum to squeeze any longer, can only really expand from that point or stay where it currently is, but this is also a mean reverting process so it does tend to go back up from the low point.
Settings:
Length: This is the length of the momentum, by default its at 100.
Normalization Length: Length of the Normalization which ensures the the values fall within a consistent range.
Scalper's Volatility Filter [QuantraSystems]Scalpers Volatility Filter
Introduction
The 𝒮𝒸𝒶𝓁𝓅𝑒𝓇'𝓈 𝒱𝑜𝓁𝒶𝓉𝒾𝓁𝒾𝓉𝓎 𝐹𝒾𝓁𝓉𝑒𝓇 (𝒮𝒱𝐹) is a sophisticated technical indicator, designed to increase the profitability of lower timeframe trading.
Due to the inherent decrease in the signal-to-noise ratio when trading on lower timeframes, it is critical to develop analysis methods to inform traders of the optimal market periods to trade - and more importantly, when you shouldn’t trade.
The 𝒮𝒱𝐹 uses a blend of volatility and momentum measurements, to signal the dominant market condition - trending or ranging.
Legend
The 𝒮𝒱𝐹 consists of a signal line that moves above and below a central zero line, serving as the indication of market regime.
When the signal line is positioned above zero, it indicates a period of elevated volatility. These periods are more profitable for trading, as an asset will experience larger price swings, and by design, trend-following indicators will give less false signals.
Conversely, when the signal line moves below zero, a low volatility or mean-reverting market regime dominates.
This distinction is critical for traders in order to align strategies with the prevailing market behaviors - leveraging trends in volatile markets and exercising caution or implementing mean-reversion systems in periods of lower volatility.
Case Study
Here we can see the indicator's unique edge in action.
Out of the four potential long entries seen on the chart - displayed via bar coloring, two would result in losses.
However, with the power of the 𝒮𝒱𝐹 a trader can effectively filter false signals by only entering momentum-trades when the signal line is above zero.
In this small sample of four trades, the 𝒮𝒱𝐹 increased the win rate from 50% to 100%
Methodology
The methodology behind the 𝒮𝒱𝐹 is based upon three components:
By calculating and contrasting two ATR’s, the immediate market momentum relative to the broader, established trend is calculated. The original method for this can be credited to the user @xinolia
A modified and smoothed ADX indicator is calculated to further assess the strength and sustainability of trends.
The ‘Linear Regression Dispersion’ measures price deviations from a fitted regression line, adding further confluence to the signals representation of market conditions.
Together, these components synthesize a robust, balanced view of market conditions, enabling traders to help align strategies with the prevailing market environment, in order to potentially increase expected value and win rates.
