Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Kripto
Project Monday Strategy [AlgoAI System]Overview
Project Monday is a sophisticated trading strategy designed for active market participants. This strategy can be used alongside other forms of technical analysis, providing traders with additional tools to enhance their market insights. While it offers a flexible approach for identifying and exploiting market inefficiencies, Project Monday does not fit every market condition and requires adjustments. Its core principles include technical analysis and risk management, all aimed at making informed trading decisions and managing risk effectively.
Features
Project Monday Strategy works in any market and includes many features:
Efficient Trading Presets: Offers ready-to-use presets that allow traders to start efficient trading with one click.
Confirmation Signals: Provides signals to help traders validate trends, emphasizing informed decision-making (not to be followed blindly).
Reversal Signals: Identifies signals to alert traders to potential reversals, encouraging careful analysis (not to be followed blindly).
Adaptability: Can be adjusted to fit different market conditions, ensuring ongoing effectiveness.
Multi-Market Application: Suitable for use across various asset classes including stocks, forex, commodities, and cryptocurrencies.
Integration: Can be used alongside other technical analysis tools for enhanced decision-making.
Position Sizing: Allows traders to determine optimal trade size using backtesting and trading performance dashboard.
Backtesting: Supports historical testing to refine and validate the strategy.
Continuous Monitoring: Includes features for ongoing performance evaluation and strategy adjustments.
Unique Project Monday Strategy Features on TradingView:
Adaptive Position Sizing: Dynamically adjusts the size of each position based on market conditions and predefined risk management criteria, ensuring optimal trade sizing and risk exposure.
Preliminary Position Opening: Allows traders to enter a position in anticipation of a signal confirmation, enabling them to capture early market movements and improve entry points.
Preliminary Position Closing: Enables traders to exit a position before a signal reversal, helping to lock in profits and minimize potential losses during volatile market conditions.
Adjusting Strategy Parameters:
Price Band Inputs:
Project Monday Strategy uses a set of configurable inputs to tailor its behavior according to the trader's preferences. The following are the key inputs for the price band calculations. Signals are not generated when the price remains within these bands.
“Length of Calculation” determines how many historical data points are used in the trend calculation. A shorter “Length of Calculation” will make the Price Band more responsive to recent price changes but may also increase the noise and the likelihood of false signals. A longer “Length of Calculation” will make the Price Band smoother, with less noise, but may cause more lag in reacting to price changes.
“Offset” determines the position of the Gaussian filter, which is used to weight the data points in the trend calculation. The offset is expressed as a fraction of the “Length of Calculation”, with a value between 0 and 1. A higher “Offset” will shift the Gaussian filter closer to the more recent data points, making the Price Band more responsive to recent price changes but potentially increasing noise. A lower “Offset” will shift the Gaussian filter closer to the centre of the window, resulting in a smoother Price Band but potentially introducing more lag.
“Sigma” refers to the standard deviation used in the Gaussian distribution function. This parameter determines the smoothness of the curve and the degree to which data points close to the centre of the “Length of Calculation” are weighted more heavily than those further away. A smaller “Sigma” will result in a narrower Gaussian filter, leading to a more responsive Price Band but with a higher chance of noise and false signals. A larger “Sigma” will result in a wider Gaussian filter, creating a smoother Price Band but with more lag.
Adjust the “Source” inputs to specify which type of price data should be used for strategy calculations and signal generation.
“Width of Band” input determines the multiplier for the band width. A higher value of “Width of Band” makes the price band wider, which generates fewer signals due to the lower probability of the price moving outside the band. Conversely, a lower multiplier makes the band narrower, generating more signals but also increasing the likelihood of false signals.
Direction input:
The Project Monday strategy includes an input to specify the direction of trades, allowing traders to control whether the strategy should consider long positions, short positions, or both. The following input parameter is used for this purpose:
This input parameter allows traders to define the type of positions the strategy will take. It has three options:
Only Long: The strategy will generate signals exclusively for buying or closing short positions, focusing on potential uptrends.
Only Short: The strategy will generate signals exclusively for selling or closing long positions, focusing on potential downtrends.
Both: The strategy will generate signals for both buying (long positions) and selling (short positions), allowing for a more comprehensive trading approach that captures opportunities in both rising and falling markets.
Signals Filter:
The Project Monday strategy includes inputs to filter signals based on higher timeframes and the length of the data used for filtering. These inputs help traders refine the strategy's performance by considering broader market trends and smoothing out short-term fluctuations.
Filter Timeframe input specifies the timeframe used for filtering signals. By choosing a higher timeframe, traders can filter out noise from shorter timeframes and focus on more significant trends. The options range from intraday minutes (e.g., 1, 5, 15 minutes) to daily (1D, 2D, etc.), weekly (1W, 2W, etc.), and monthly (1M) timeframes. This allows traders to align their strategy with their preferred trading horizon and market perspective.
Filter Length input defines the number of data points used for filtering signals on the selected timeframe. A longer filter length will smooth out the data more, helping to identify sustained trends and reduce the impact of short-term fluctuations. Conversely, a shorter filter length will make the filter more responsive to recent price changes, potentially generating more signals but also increasing sensitivity to market noise.
Adaptive Position Size:
The Project Monday strategy incorporates inputs for unique feature Adaptive Position Sizing (APS), which dynamically adjusts the size of trades based on market conditions and specified parameters. This feature helps optimize risk management and trading performance.
Enable Adaptive Position Size: Users can check or uncheck this box to enable or disable the Adaptive Position Size feature. When checked, the strategy dynamically adjusts position sizes based on the defined parameters. This allows traders to scale their positions according to market volatility and other factors, enhancing risk management and potentially improving returns. When unchecked, the strategy will not adjust position sizes adaptively, and positions will remain fixed as per other settings.
“Timeframe for Adaptive Position Size “input specifies the timeframe used for calculating the position size. Options range from intraday minutes (e.g., 30, 60 minutes) to daily (1D, 3D), weekly (1W), and monthly (1M) timeframes. Selecting an appropriate timeframe helps align position sizing calculations with the trader’s overall strategy and market perspective, ensuring that position sizes are adjusted based on relevant market data.
“APS Length” input defines the number of data points used to calculate the adaptive position size. A longer APS length will result in higher position sizes. Conversely, a shorter APS length will result in smaller position sizes.
Anticipatory Trading:
Project Monday Strategy includes inputs for unique feature Anticipatory Trading, allowing traders to open and close positions preliminarily based on certain conditions. This feature aims to provide an edge by taking action before traditional signals confirm.
Enable Preliminary Position Opening: Users can check or uncheck this box to enable or disable Preliminary Position Opening. When enabled, the strategy will open positions based on preliminary conditions before the standard signals are confirmed. This can help traders capitalize on early trend movements and potentially gain a better entry point.
Enable Preliminary Position Closing: Users can check or uncheck this box to enable or disable Preliminary Position Closing. When enabled, the strategy will close positions based on preliminary conditions before the standard exit signals are confirmed. This can help traders lock in profits or limit losses by exiting positions at the early signs of trend reversals.
“Position Size in %” input specifies the position size as a percentage of the trading capital. By setting this value, traders can control the amount of capital allocated to each trade. For example, a risk value of 40% means that 40% of the available trading capital will be used for each anticipatory trade. This helps in managing risk and ensuring that the position size aligns with the trader's risk tolerance and overall strategy.
Usage:
Signal Generation
Long signal indicates a potential uptrend, suggesting either buying or closing a short position. Short signal indicates a potential downtrend, suggesting either selling or closing a long position. Signals are generated on your chart when the price moves beyond a calculated price band based on the current trend.
Signal Filtering
The strategy includes a filtering mechanism based on the current or another timeframe. Filtering works best with higher timeframes. This component calculates the trend on a higher timeframe and predicts the trend, ensuring trades on the current timeframe are only opened if they align with the higher timeframe trend. Setting the right filter timeframe is crucial for obtaining the best signals.
Position Direction
Users can choose the direction of positions to open via the settings box. Options include only long positions, only short positions, or both.
Adaptive Position Size (APS)
Users can enable the Adaptive Position Size feature to adjust position sizes based on trend strength. The strategy evaluates the strength of the current trend based on a higher timeframe. The stronger the trend, the larger the position size for opening a position.
Anticipatory Trading
Users can activate this unique feature to enhance trading decisions. The strategy assesses the likelihood of receiving a main signal. If the opportunity appears strong, it opens a partial position, as specified in the settings box. As the probability of the signal strengthens, the strategy gradually increases the position size.
Exit Strategy
The strategy exits positions based on receiving a reverse signal. Positions opened through “Anticipatory trading” are exited incrementally as each preliminary signal reverses.
By following these steps, traders can implement the strategy to navigate various market scenarios, manage risk, and adjust trading performance over time. Adjusting parameters and monitoring signals diligently are key to adapting the strategy to individual trading styles and market conditions.
You will get
By purchasing the Project Monday strategy, you not only gain access to a cutting-edge system but also receive ready-to-use presets designed to help you start trading immediately and achieve optimal results. Additionally, you benefit from comprehensive support and the option to request custom presets for your desired financial instruments through our dedicated support team, ensuring you have the tools and assistance needed for successful trading.
Risk Disclaimer
This information is not a personalized investment recommendation, and the financial instruments or transactions mentioned in it may not be appropriate for your financial situation, investment objective(s), risk tolerance, and/or expected return. AlgoAI shall not be liable for any losses incurred in the event of transactions or investments in financial instruments mentioned in this information.
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.
=============
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
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
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
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
local
█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
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.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
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.
Crypto MVRV ZScore - Strategy [PresentTrading]█ Introduction and How it is Different
The "Crypto Valuation Extremes: MVRV ZScore - Strategy " represents a cutting-edge approach to cryptocurrency trading, leveraging the Market Value to Realized Value (MVRV) Z-Score. This metric is pivotal for identifying overvalued or undervalued conditions in the crypto market, particularly Bitcoin. It assesses the current market valuation against the realized capitalization, providing insights that are not apparent through conventional analysis.
BTCUSD 6h Long/Short Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy leverages the Market Value to Realized Value (MVRV) Z-Score, specifically designed for cryptocurrencies, with a focus on Bitcoin. This metric is crucial for determining whether Bitcoin is currently undervalued or overvalued compared to its historical 'realized' price. Below is an in-depth explanation of the strategy's components and calculations.
🔶Conceptual Foundation
- Market Capitalization (MC): This represents the total dollar market value of Bitcoin's circulating supply. It is calculated as the current price of Bitcoin multiplied by the number of coins in circulation.
- Realized Capitalization (RC): Unlike MC, which values all coins at the current market price, RC is computed by valuing each coin at the price it was last moved or traded. Essentially, it is a summation of the value of all bitcoins, priced at the time they were last transacted.
- MVRV Ratio: This ratio is derived by dividing the Market Capitalization by the Realized Capitalization (The ratio of MC to RC (MVRV Ratio = MC / RC)). A ratio greater than 1 indicates that the current price is higher than the average price at which all bitcoins were purchased, suggesting potential overvaluation. Conversely, a ratio below 1 suggests undervaluation.
🔶 MVRV Z-Score Calculation
The Z-Score is a statistical measure that indicates the number of standard deviations an element is from the mean. For this strategy, the MVRV Z-Score is calculated as follows:
MVRV Z-Score = (MC - RC) / Standard Deviation of (MC - RC)
This formula quantifies Bitcoin's deviation from its 'normal' valuation range, offering insights into market sentiment and potential price reversals.
🔶 Spread Z-Score for Trading Signals
The strategy refines this approach by calculating a 'spread Z-Score', which adjusts the MVRV Z-Score over a specific period (default: 252 days). This is done to smooth out short-term market volatility and focus on longer-term valuation trends. The spread Z-Score is calculated as follows:
Spread Z-Score = (Market Z-Score - MVVR Ratio - SMA of Spread) / Standard Deviation of Spread
Where:
- SMA of Spread is the simple moving average of the spread over the specified period.
- Spread refers to the difference between the Market Z-Score and the MVRV Ratio.
🔶 Trading Signals
- Long Entry Condition: A long (buy) signal is generated when the spread Z-Score crosses above the long entry threshold, indicating that Bitcoin is potentially undervalued.
- Short Entry Condition: A short (sell) signal is triggered when the spread Z-Score falls below the short entry threshold, suggesting overvaluation.
These conditions are based on the premise that extreme deviations from the mean (as indicated by the Z-Score) are likely to revert to the mean over time, presenting opportunities for strategic entry and exit points.
█ Practical Application
Traders use these signals to make informed decisions about opening or closing positions in the Bitcoin market. By quantifying market valuation extremes, the strategy aims to capitalize on the cyclical nature of price movements, identifying high-probability entry and exit points based on historical valuation norms.
█ Trade Direction
A unique feature of this strategy is its configurable trade direction. Users can specify their preference for engaging in long positions, short positions, or both. This flexibility allows traders to tailor the strategy according to their risk tolerance, market outlook, or trading style, making it adaptable to various market conditions and trader objectives.
█ Usage
To implement this strategy, traders should first adjust the input parameters to align with their trading preferences and risk management practices. These parameters include the trade direction, Z-Score calculation period, and the thresholds for long and short entries. Once configured, the strategy automatically generates trading signals based on the calculated spread Z-Score, providing clear indications for potential entry and exit points.
It is advisable for traders to backtest the strategy under different market conditions to validate its effectiveness and adjust the settings as necessary. Continuous monitoring and adjustment are crucial, as market dynamics evolve over time.
█ Default Settings
- Trade Direction: Both (Allows for both long and short positions)
- Z-Score Calculation Period: 252 days (Approximately one trading year, capturing a comprehensive market cycle)
- Long Entry Threshold: 0.382 (Indicative of moderate undervaluation)
- Short Entry Threshold: -0.382 (Signifies moderate overvaluation)
These default settings are designed to balance sensitivity to market valuation extremes with a pragmatic approach to trade execution. They aim to filter out noise and focus on significant market movements, providing a solid foundation for both new and experienced traders looking to exploit the unique insights offered by the MVRV Z-Score in the cryptocurrency market.
