MA OrderBlocks [AlgoAlpha]🟨 HMA OrderBlocks by AlgoAlpha is a powerful tool designed to help traders visualize key pivot zones and order blocks based on the Hull Moving Average (HMA). By dynamically identifying bullish and bearish pivot points, this script provides insights into potential price reversals and trend continuations. With customizable settings, it allows traders to tweak the behavior of the indicator to match their strategies. Plus, it comes packed with built-in alerts for trend changes, making it easier to spot potential trade opportunities.
Key Features :
📊 Trend Detection : Utilizes Hull Moving Average to detect the current trend.
🟢🔴 Bullish & Bearish Zones : Automatically plots bullish and bearish order blocks, using customizable colors for clear visual cues.
🎯 Pivot Points : Detects and marks pivot highs and lows, helping traders spot key price reversals.
🚨 Alerts : Built-in alert system for when the price approaches key bullish or bearish zones, or when the trend changes.
🔨 Customizable MA: Choose from various moving averages (SMA, HMA, EMA, etc.) to suit your strategy.
How to Use :
⭐ Add the Indicator : Add the indicators to favourites by pressing the star icon. Once added, configure settings like the Hull MA period and pivot detection period.
📈 Analyze the Chart : Watch for the plotted order blocks and pivot points to identify possible price action strategies.
🔔 Enable Alerts : Set up alerts to be notified of potential trend reversals or when the price nears a bullish/bearish block.
How It Works :
The script starts by calculating the Hull Moving Average (HMA) based on the user-defined length, which is used to determine the market trend direction. It compares the current HMA value with the previous one to confirm whether the price is trending upwards or downwards. Once a trend change is detected, it plots bullish or bearish order blocks based on recent pivot highs and lows. These zones are extended in real-time as long as they remain invalidated. Zones are invalidated are invalidated when price completely closes through them. If the price gets close to a zone in the opposing direction, a warning system alerts the user that the block may not hold. Additionally, customizable alerts trigger whenever the price trend shifts or the price gets near important bullish/bearish blocks. The script’s logic ensures that order blocks are cleared if price violates them, keeping the chart clean and updated.
Technical Analysis
VPSA - Volume Price Spread AnalysisDear Analysts and Traders,
I am pleased to present the latest version of my indicator, based on the logic of analyzing spread and volume. In this version, the indicator examines spread and volume using min-max normalization. The statistical value is captured through Z-Score standardization, and I have added configurable alerts based on the normalized values of spread, volume, and the sigmas for these variables.
Theory and Evolution of the Indicator
The normalization function used in this program allows for the comparison of two values with different ranges on a single chart. The values that reach the highest within the examined range are assigned a value of one. As in previous versions, I have adopted a bar chart where the wider bar represents volume and the narrower bar represents spread. I believe that using normalization is the most intuitive approach, as the standardization in the earlier sVPSA version could cause confusion. This was due to smaller bars for higher actual values and negative bars, which required additional reliance on actual volume data and significant proficiency in using the indicator. These were limitations stemming from the computational aspect of these issues. As in the previously mentioned script, I also used Z-Score standardization here, which serves as a measure of deviation from the mean. This is visualized in the script as the color of the bars, which in the default configuration are as follows: below one sigma - blue; above one sigma up to two sigmas - green; above two sigmas up to three sigmas - red; and above three sigmas - fuchsia. Additionally, I applied an exponential moving average in this indicator to minimize the influence of older candles on the mean. The indicator has been enhanced with configurable alerts, allowing for substantial control over the conditions triggering them. The alerts enable the definition of normalized variable values and sigma values. Furthermore, the program allows for the definition of logical dependencies for these conditions.
Summary
The program I have developed is a synthesis of the most important and useful functions from the indicators I previously created. The indicator is a standalone and powerful tool that facilitates effective analysis of the spread-volume relationship, which is one of the fundamental methods of analysis according to the Wyckoff and VSA methodologies. The alerts introduced in this version provide extensive possibilities for controlling the dynamics of any market.
Should you encounter any errors or have suggestions regarding the indicator, please feel free to contact me.
I wish you successful analyses! All the best!
CatTheTrader
Machine Learning Support and Resistance [AlgoAlpha]🚀 Elevate Your Trading with Machine Learning Dynamic Support and Resistance!
The Machine Learning Dynamic Support and Resistance by AlgoAlpha leverages advanced machine learning techniques to identify dynamic support and resistance levels on your chart. This tool is designed to help traders spot key price levels where the market might reverse or stall, enhancing your trading strategy with precise, data-driven insights.
Key Features:
🎯 Dynamic Levels: Continuously adjusts support and resistance levels based on real-time price data using a K-means clustering algorithm.
🧠 Machine Learning: Utilizes clustering methods to optimize the identification of significant price zones.
⏳ Configurable Lookback Periods: Customize the training length and confirmation length for better adaptability to different market conditions.
🎨 Visual Clarity: Clearly distinguish bullish and bearish zones with customizable color schemes.
📉 Trailing and Fixed Levels: Option to display both trailing and fixed support/resistance levels for comprehensive analysis.
🚮 Auto-Cleaning: Automatically removes outdated levels after a specified number of bars to keep your chart clean and relevant.
Quick Guide to Using the Machine Learning Dynamic Support and Resistance Indicator
Maximize your trading with this powerful indicator by following these streamlined steps! 🚀✨
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like clustering training length, confirmation length, and whether to show trailing or fixed levels to fit your trading style.
📊 Market Analysis: Monitor the dynamic levels to identify potential reversal points. Use these levels to inform entry and exit points, or to set stop losses.
How It Works
This indicator employs a K-means clustering algorithm to dynamically identify key price levels based on the historical price data within a specified lookback window. It starts by initializing three centroids based on the highest, lowest, and an average between the highest and lowest price over the lookback period. The algorithm then iterates through the price data to cluster the prices around these centroids, dynamically adjusting them until they stabilize, representing potential support and resistance levels. These levels are further confirmed based on a separate confirmation length parameter to identify "fixed" levels, which are then drawn as horizontal lines on the chart. The script continuously updates these levels as new data comes in, while also removing older levels to keep the chart clean and relevant, offering traders a clear and adaptive view of market structure.
Fibonacci Retracements & Trend Following Strategy V2This Pine Script strategy generates trading signals using Fibonacci levels and trend-following indicators.
1. Strategy Summary
This strategy analyzes price movements using a combination of Fibonacci levels and trend-following indicators, providing potential trading signals. The strategy includes Fibonacci levels as well as EMA (Exponential Moving Average) and ADX (Average Directional Index) indicators.
2. Indicators and Parameters
Fibonacci Levels
Fibonacci Level 1, Level 2, Level 3, Level 4: Used as Fibonacci retracement levels. These levels are typically set at 0.236, 0.382, 0.618, and 0.786. Users can adjust these values according to their preferences.
Trend-Following Indicator
Trend Length: The period for calculating the EMA used as the trend-following indicator. For example, if set to 20, the EMA will be calculated over 20 periods.
ADX (Average Directional Index)
ADX Length: The period for calculating the ADX. ADX measures the strength of the price trend and is usually set to 14 periods.
ADX Threshold: A threshold value for the ADX. This value determines when trading signals will be activated.
3. Usage Steps
Displaying the Indicator on the Chart:
On the TradingView platform, paste the code into the Pine Editor and click the "Add to Chart" button to add it to the chart.
Analyzing the Indicators:
Fibonacci Levels: Show retracement levels of price movements. When the price reaches one of these levels, potential reversals may occur.
Trend-Following Indicator: EMAs determine the direction of the trend. Green EMA represents an uptrend, while red EMA represents a downtrend.
ADX: Measures the strength of the trend. When ADX surpasses the threshold value, it indicates a strong trend.
Trading Signals:
Long Signal: Generated when the price is above the second Fibonacci level and the trend is upward. Additionally, the ADX value must be above the set threshold.
Short Signal: Generated when the price is below the second Fibonacci level and the trend is downward. Additionally, the ADX value must be above the set threshold.
Target Prices:
Long Targets: Determines upward targets based on Fibonacci levels. These targets indicate expected prices if the price reverses from Fibonacci levels.
Short Targets: Determines downward targets based on Fibonacci levels. These targets indicate expected prices if the price reverses from Fibonacci levels.
4. Chart Displays
Trend Up (Green Line): Shows the rising EMA.
Trend Down (Red Line): Shows the falling EMA.
Fibonacci Levels (Blue Lines): Shows Fibonacci retracement levels.
Long Targets (Green Circles): Shows targets for long positions.
Short Targets (Red Circles): Shows targets for short positions.
Long Signal (Green Label): Buy signal.
Short Signal (Red Label): Sell signal.
5. Important Notes
Retracement and Target Levels: Fibonacci levels can act as potential retracement or support/resistance levels. However, they should always be used in conjunction with other technical analysis tools.
Trend and ADX: ADX is used to determine the strength of the trend. Be aware that when ADX is low, trends may be weak.
6. Example Scenarios
Example 1: If the trend is upward (green EMA) and the price is above the second Fibonacci level, you may receive a long position signal. If the ADX value is above the threshold, the signal may be stronger.
Example 2: If the trend is downward (red EMA) and the price is below the second Fibonacci level, you may receive a short position signal. If the ADX value is above the threshold, the signal may be stronger.
This updated version contains significant improvements in both technical aspects and user experience. Innovations such as ADX calculations and dynamic Fibonacci levels make the strategy more robust and flexible. The code's readability and comprehensibility have been enhanced, and errors have been corrected.
This guide will help you understand the basic operation of the strategy. It is always recommended to conduct your own research and test the strategy before using it.
GOOD LUCK. // halilvarol
Hullinger Percentile Oscillator [AlgoAlpha]🚀 Introducing the Hullinger Percentile Oscillator by AlgoAlpha! 🚀
This versatile Pine Script™ indicator is designed to help you identify swing trends and potential reversals with precision. Whether you're looking to catch market swings or spot divergences, the Hullinger Percentile Oscillator offers a comprehensive suite of features to enhance your trading strategy.
Key Features
🎯 Customizable Hullinger Settings: Adjust the main length, source, and standard deviation multipliers to fine-tune the indicator to your preferred trading style.
🔄 Dynamic Oscillator Modes: Switch between "Swing" mode for trend identification and "Contrarian" mode for reversal spotting, adapting the indicator to your market view.
📉 Divergence Detection: The indicator includes parameters to control the sensitivity and confirmation of divergence signals, helping to filter out noise and highlight significant market moves.
🌈 Color-Coded Visuals: Easily distinguish between bullish and bearish signals with customizable color settings for a clear visual representation on your chart.
🔔 Alert Integration: Stay ahead of the market with built-in alerts for key conditions, including strong and weak reversals, as well as bullish and bearish swings.
Quick Guide to Using the Hullinger Percentile Oscillator
Maximize your trading edge with the Hullinger Percentile Oscillator by following these steps! 📈✨
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon ⭐. Customize settings like Main Length, Oscillator Mode, and Appearance to fit your trading needs.
📊 Market Analysis: Use "Swing" mode to track trends and "Contrarian" mode to spot reversals. Watch for divergence signals to catch potential trend changes.
🔔 Alerts: Set up alerts to be notified of significant market movements without constantly monitoring your chart.
How It Works
The Hullinger Percentile Oscillator calculates its signals by applying a modified standard deviation approach to the Hull Moving Average (HMA) of a selected price source. It creates both inner and outer bands based on different multipliers. The oscillator then measures the position of the price relative to these bands, smoothing the result for swing trend detection. Depending on the chosen mode, the oscillator either highlights swing trends or potential reversals. Divergences are detected by comparing recent pivot highs and lows in both price and the oscillator, allowing you to spot bullish or bearish divergence setups. Alerts are triggered based on key crossovers or when specific conditions are met, ensuring that you are always informed of crucial market developments.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
Multi-Timeframe EMA Distance & % Change TableDescription of Multi-Timeframe EMA Distance & % Change Table
The Multi-Timeframe EMA Distance & % Change Table indicator is designed to display the distance and percentage change between the current price and the Exponential Moving Averages (EMAs) on multiple timeframes. It creates a table to show these values, with customizable options for decimal precision .
Key Features:
Inputs:
- Timeframes (tf1, tf2, tf3, tf4): User-defined timeframes for EMA calculations (e.g., 1 minute, 15 minutes, daily, etc.).
- EMA Levels (emaLevel, emaLevel2, emaLevel3): User-defined periods for three different EMAs.
EMA Calculations:
- Computes EMAs for the specified levels (50, 100, 200) on each of the user-selected timeframes.
Plotting:
- Plots the EMAs on the chart with distinct colors: Orange, Teal, and Green for different EMAs.
Display Options:
- Checkbox (displayAsPercentage): Allows the user to toggle between displaying distances or percentage changes.
- Decimal Precision:
- decimalPlacesDistance: Specifies the number of decimal places for rounded distance values.
- decimalPlacesPercentage: Specifies the number of decimal places for rounded percentage values.
Table Creation:
- Location: Table is placed in the top-right corner of the chart.
- Headers: Includes columns for each timeframe and EMA distance/percentage.
Distance and Percentage Calculations:
- Distances: Calculated as the difference between the current price and the EMA values for each timeframe.
- Percentages: Calculated as the distance divided by the EMA value, converted to a percentage.
Decimal Rounding:
- Custom Rounding Function: Ensures that distance and percentage values are displayed with the user-specified number of decimal places.
Color Coding:
- Distance Values: Colored green if positive, red if negative.
- Table Entries: Display either the rounded distance or percentage, based on user selection.
Table Update:
- The table is dynamically updated with either distance or percentage values based on the user's choice and rounded to the specified number of decimal places.
This indicator provides a comprehensive overview of EMA distances and percentage changes across multiple timeframes, with detailed control over the precision of the displayed values.
Hammers & star Patterns After a Trend
1. **Candlestick Patterns Detection:**
- **Hammers** and **Inverted Hammers** are specific candlestick patterns that can indicate potential reversals in the market.
- **Hammer**: A candle with a small body and a long lower wick, showing a possible reversal after a downtrend.
- **Inverted Hammer**: A candle with a small body and a long upper wick, indicating a possible reversal after an uptrend.
2. **Volume Consideration:**
- The script checks if these patterns occur with **high trading volume**. If the volume is significantly higher than the average volume over a certain period, the pattern is highlighted.
3. **Trend Detection:**
- The script looks for a significant trend before the pattern appears:
- **Downtrend**: A significant downward movement in price is required before a Hammer is considered.
- **Uptrend**: A significant upward movement is required before an Inverted Hammer is considered.
4. **Additional Patterns:**
- **Morning Star** and **Evening Star** patterns are also detected:
- **Morning Star**: A three-candle pattern where the first candle is a large bearish candle, followed by a small-bodied candle, and then a large bullish candle, indicating a potential reversal from downtrend to uptrend.
- **Evening Star**: The opposite pattern, signaling a potential reversal from uptrend to downtrend.
5. **Visual Indicators:**
- The script **plots arrows** and **labels** on the chart to show where these patterns occur:
- **Hammers** and **Inverted Hammers** are marked with triangle arrows.
- **Morning Stars** and **Evening Stars** are marked with labels.
In summary, this script helps traders identify key candlestick patterns that may signal potential reversals in price trends, with special emphasis on patterns that occur with high volume and after significant price movements.
Market Structure Based Stop LossMarket Structure Based Dynamic Stop Loss
Introduction
The Market Structure Based Stop Loss indicator is a strategic tool for traders designed to be useful in both rigorous backtesting and live testing, by providing an objective, “guess-free” stop loss level. This indicator dynamically plots suggested stop loss levels based on market structure, and the concepts of “interim lows/highs.”
It provides a robust framework for managing risk in both long and short positions. By leveraging historical price movements and real time market dynamics, this indicator helps traders identify quantitatively consistent risk levels while optimizing trade returns.
Legend
This indicator utilizes various inputs to customize its functionality, including "Stop Loss Sensitivity" and "Wick Depth," which dictate how closely the stop loss levels hug the price's highs and lows. The stop loss levels are plotted as lines on the trading chart, providing clear visual cues for position management. As seen in the chart below, this indicator dynamically plots stop loss levels for both long and short positions at every point in time.
A “Stop Loss Table” is also included, in order to enhance precision trading and increase backtesting accuracy. It is customizable in both size and positioning.
Case Study
Methodology
The methodology behind this indicator focuses on the precision placement of stop losses using market structure as a guide. It calculates stop losses by identifying the "lowest close" and the corresponding "lowest low" for long setups, and inversely for short setups. By adjusting the sensitivity settings, traders can tweak the indicator's responsiveness to price changes, ensuring that the stop losses are set with a balance between tight risk control and enough room to avoid premature exits due to market noise. The indicator's ability to adapt to different trading styles and time frames makes it an essential tool for traders aiming for efficiency and effectiveness in their risk management strategies.
An important point to make is the fact that the stop loss levels are always placed within the wicks. This is important to avoid what can be described as a “floating stop loss”. A stop loss placed outside of a wick is susceptible to an outsized degree of slippage. This is because traders always cluster their stop losses at high/low wicks, and a stop loss placed outside of this level will inevitably be caught in a low liquidity cascade or “wash-out.” When price approaches a cluster of stop losses, it is highly probable that you will be stopped out anyway, so it is prudent to attempt to be the trader who gets stopped out first in order to avoid high slippage, and losses above what you originally intended.
// For long positions: stop-loss is slightly inside the lowest wick
float dynamic_SL_Long = lowestClose - (lowestClose - lowestLow) * (1 - WickDepth)
// For short positions: stop-loss is slightly inside the highest wick
float dynamic_SL_Short = highestClose + (highestHigh - highestClose) * (1 - WickDepth)
The percentage depth of the wick in which the stop loss is placed is customisable with the “Wick Depth” variable, in order to customize stop loss strategies around the liquidity of the market a trader is executing their orders in.
Big Candle HighlighterBig Candle Highlighter
The Big Candle Highlighter indicator highlights significant candles based on their percentage difference between the open and close prices. This tool helps traders quickly identify candles with substantial price movements, which can be crucial for spotting key price action, potential reversals, or significant market events.
Key Features:
Percentage Threshold : Customize the minimum percentage difference from open to close required to mark a candle as "big."
Bullish and Bearish Markers : Bullish big candles are marked with a label below the bar in green, while bearish big candles are marked with a label above the bar in red.
Background Highlighting : Optionally highlight the background of big candles for better visual emphasis.
Inputs:
Percentage Threshold (% ): Set the percentage threshold to define what constitutes a "big" candle. For example, a threshold of 2.0 means that only candles with a 2% or more difference between open and close will be marked.
Color for Big Bullish Candle : Choose the color for labeling and highlighting bullish big candles.
Color for Big Bearish Candle : Choose the color for labeling and highlighting bearish big candles.
Usage :
This indicator is useful for traders looking to identify significant price movements and potential trading opportunities. By focusing on candles that show substantial changes from open to close, you can better understand market dynamics and make more informed trading decisions.
Add the Big Candle Marker to your charts to enhance your technical analysis and stay ahead of market trends.
Last Candle OHLC (Ticks or Points)What the Code Does
1. **Draws Lines and Labels**:
- It draws lines on your chart to show the high, low, open, and close prices from the previous period (like the previous day or week).
- It also labels these lines with numbers that tell you how far the current price is from these levels.
2. **Shows Price Movement**:
- You can see how far the price has moved from these levels in terms of small price changes (ticks) or larger units (points).
- This helps you understand price movements and potential levels of support or resistance.
3. **Customizable**:
- You can choose whether to show these lines and labels, and you can select if you want to see the movement in ticks or points.
- The lines can extend into the future on your chart to help you anticipate where prices might be in the coming days.
### How It’s Useful:
1. **Identify Key Levels**:
- It helps you spot important price levels from past periods, which can act as support or resistance.
2. **Understand Price Movement**:
- You get a visual sense of how much the price has moved from key levels, which can help you gauge market volatility.
3. **Plan Trades**:
- By seeing where the price has been and how it has moved, you can better plan your trades, like deciding where to enter or exit based on these levels.
4. **Flexible for Different Markets**:
- It works across various markets, like stocks, futures, and forex, adjusting to the specific characteristics of each instrument.
In short, this tool helps you visualize and understand past price movements and levels on your chart, aiding in your trading decisions.
S&P Short-Range Oscillator**SHOULD BE USED ON THE S&P 500 ONLY**
The S&P Short-Range Oscillator (SRO), inspired by the principles of Jim Cramer's oscillator, is a technical analysis tool designed to help traders identify potential buy and sell signals in the stock market, specifically for the S&P 500 index. The SRO combines several market indicators to provide a normalized measure of market sentiment, assisting traders in making informed decisions.
The SRO utilizes two simple moving averages (SMAs) of different lengths: a 5-day SMA and a 10-day SMA. It also incorporates the daily price change and market breadth (the net change of closing prices). The 5-day and 10-day SMAs are calculated based on the closing prices. The daily price change is determined by subtracting the opening price from the closing price. Market breadth is calculated as the difference between the current closing price and the previous closing price.
The raw value of the oscillator, referred to as SRO Raw, is the sum of the daily price change, the 5-day SMA, the 10-day SMA, and the market breadth. This raw value is then normalized using its mean and standard deviation over a 20-day period, ensuring that the oscillator is centered and maintains a consistent scale. Finally, the normalized value is scaled to fit within the range of -15 to 15.
When interpreting the SRO, a value below -5 indicates that the market is potentially oversold, suggesting it might be a good time to start buying stocks as the market could be poised for a rebound. Conversely, a value above 5 suggests that the market is potentially overbought. In this situation, it may be prudent to hold on to existing positions or consider selling if you have substantial gains.
The SRO is visually represented as a blue line on a chart, making it easy to track its movements. Red and green horizontal lines mark the overbought (5) and oversold (-5) levels, respectively. Additionally, the background color changes to light red when the oscillator is overbought and light green when it is oversold, providing a clear visual cue.
By incorporating the S&P Short-Range Oscillator into your trading strategy, you can gain valuable insights into market conditions and make more informed decisions about when to buy, sell, or hold your stocks. However, always consider other market factors and perform your own analysis before making any trading decisions.
The S&P Short-Range Oscillator is a powerful tool for traders looking to gain insights into market sentiment. It provides clear buy and sell signals through its combination of multiple indicators and normalization process. However, traders should be aware of its lagging nature and potential complexity, and use it in conjunction with other analysis methods for the best results.
Disclaimer
The S&P Short-Range Oscillator is for informational purposes only and should not be considered financial advice. Trading involves risk, and you should conduct your own research or consult a financial advisor before making investment decisions. The author is not responsible for any losses incurred from using this indicator. Use at your own risk.
Auto Fitting GARCH OscillatorOverview
The Auto Fitting GARCH Oscillator is a sophisticated volatility indicator that dynamically fits GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to the price data. It optimizes the parameters of the GARCH model to provide a reliable measure of volatility, which is then normalized to fit within a 0-100 range, making it easy to interpret as an oscillator. This indicator helps traders identify periods of high and low volatility, which can be crucial for making informed trading decisions.
Key Features
Dynamic GARCH(p, q) Fitting: Automatically optimizes the GARCH model parameters for the best fit.
Volatility Oscillator: Normalizes the volatility measure to a 0-100 range, indicating overbought and oversold conditions.
Customizable Timeframes: Adapts to various chart timeframes, from intraday to monthly data.
Projected Volatility: Provides options for projecting future volatility based on the optimized GARCH model.
User-friendly Visualization: Displays the oscillator with clear overbought and oversold levels.
Concepts Underlying the Calculations
The indicator leverages the GARCH model, which is widely used in financial time series analysis to model volatility clustering. The GARCH model considers past variances and returns to predict future volatility. This indicator dynamically adjusts the p and q parameters of the GARCH model within a specified range to find the optimal fit, minimizing the sum of squared errors (SSE).
How It Works
Data Preparation: Calculates the logarithmic returns and lagged variances from the price data.
SSE Optimization: Iterates through different p and q values to find the best GARCH parameters that minimize the SSE.
GARCH Calculation: Uses the optimized parameters to calculate the GARCH-based volatility.
Normalization: Normalizes the calculated volatility to a 0-100 range to form an oscillator.
Visualization: Plots the oscillator with overbought (70) and oversold (30) levels for easy interpretation.
How Traders Can Use It
Volatility Analysis: Identify periods of high and low volatility to adjust trading strategies accordingly.
Overbought/Oversold Conditions: Use the oscillator levels to identify potential reversal points in the market.
Risk Management: Incorporate volatility measures into risk management strategies to avoid trades during highly volatile periods.
Projection: Use the projected volatility feature to anticipate future market conditions.
Example Usage Instructions
Add the Indicator: Apply the "Auto Fitting GARCH Oscillator" to your chart from the Pine Script editor or TradingView library.
Customize Parameters: Adjust the maxP and maxQ values to set the range for GARCH model optimization.
Select Data Type: Choose between "Projected Variance in %" or "Projected Deviation in %" based on your analysis preference.
Set Projection Periods: Use the perForward input to specify how many periods forward you want to project the volatility.
Interpret the Oscillator: Observe the oscillator line and the overbought/oversold levels to make informed trading decisions.
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.
Fisher Transform on RSIOverview
The Fisher Transform on RSI indicator combines the Relative Strength Index (RSI) with the Fisher Transform to offer a refined tool for identifying market turning points and trends. By applying the Fisher Transform to the RSI, this indicator converts RSI values into a Gaussian normal distribution, enhancing the precision of detecting overbought and oversold conditions. This method provides a clearer and more accurate identification of potential market reversals than the standard RSI.
Key/Unique Features
Fisher Transform Applied to RSI : Transforms RSI values into a Gaussian normal distribution, improving the detection of overbought and oversold conditions.
Smoothing : Applies additional smoothing to the Fisher Transform, reducing noise and providing clearer signals.
Signal Line : Includes a signal line to identify crossover points, indicating potential buy or sell signals.
Custom Alerts : Built-in alert conditions for bullish and bearish crossovers, keeping traders informed of significant market movements.
Visual Enhancements : Background color changes based on crossover conditions, offering immediate visual cues for potential trading opportunities.
How It Works
RSI Calculation : The indicator calculates the Relative Strength Index (RSI) based on the selected source and period length.
Normalization : The RSI values are normalized to fit within a range of -1 to 1, which is essential for the Fisher Transform.
Fisher Transform : The normalized RSI values undergo the Fisher Transform, converting them into a Gaussian normal distribution.
Smoothing : The transformed values are smoothed using a simple moving average to reduce noise and provide more reliable signals.
Signal Line : A signal line, which is a simple moving average of the smoothed Fisher Transform, is plotted to identify crossover points.
Alerts and Visuals : Custom alert conditions are set for bullish and bearish crossovers, and the background color changes to indicate these conditions.
Usage Instructions
Trend Identification : Use the Fisher Transform on RSI to identify overbought and oversold conditions with enhanced precision, aiding in spotting potential trend reversals.
Trade Signals : Monitor the crossovers between the smoothed Fisher Transform and the signal line. A bullish crossover suggests a potential buying opportunity, while a bearish crossover indicates a potential selling opportunity.
Alerts : Set custom alerts based on the built-in conditions to receive notifications when important crossover events occur, ensuring you never miss a trading opportunity.
Visual Cues : Utilize the background color changes to quickly identify bullish (green) and bearish (red) conditions, providing immediate visual feedback on market sentiment.
Complementary Analysis : Combine this indicator with other technical analysis tools and indicators to enhance your overall trading strategy and make more informed decisions.
Visible Range Support and Resistance [AlgoAlpha]🌟 Introducing the Visible Range Support and Resistance 🌟
Discover key support and resistance levels with the innovative "Visible Range Support and Resistance" indicator by AlgoAlpha! 🚀📈 This advanced tool dynamically identifies significant price zones based on the visible range of your chart, providing traders with crucial insights for making informed decisions.
Key Features:
Dynamic support and resistance levels based on visible chart range 📏
User-defined resolution for tailored analysis 🎯
Clear visual representation of significant key zones 🖼️
Easy integration with any trading strategy 💼
How to Use:
🛠 Add the Indicator : Add the indicator to favourites. Adjust settings like resolution and horizontal extension to suit your trading style.
📊 Market Analysis : Identify key support and resistance zones based on the highlighted areas. These zones indicate significant price levels where the market may react.
How it Works:
The indicator segments the price range into user-defined resolutions, analyzing the highest and lowest points to establish boundaries. It calculates the frequency of price action within these segments, highlighting key levels where price movements are least concentrated (areas where price tends to pivot). Customizable settings like resolution and horizontal extension allow for tailored analysis, while the intuitive visual representation makes it easy to spot potential support and resistance zones directly on your chart.
By leveraging this indicator, you can gain deeper insights into market dynamics and improve your trading strategy with data driven support and resistance analysis. Happy trading! 💹✨
ATR Gerchik LightAverage True Range ( ATR ) is a technical analysis indicator that measures volatility in the market. ATR is a moving average of the true range over a period of time.
ATR calculation procedure:
1. Determine the true maximum - this is the highest of the current maximum and yesterday's closing price of the day.
2. Determine the true minimum - this is the smallest of the current minimum and yesterday's closing price.
3. Determine the true range - this is the distance between the true maximum and minimum.
4. We exclude extremely large candles (> x2 ATR) and extremely small ones (< 0.5 ATR) from the obtained true ranges.
5. We calculate the average for the selected period based on the remaining range.
6. We calculate the percentage of the current True Range relative to the average ATR value for the previous period.
Description:
If you analyze it yourself, you will see that 75-80% of the time, the instrument moves only 1 ATR per day. You must understand that if an instrument has, for example, moved 80% of its daily range, it is not advisable to purchase it. This is comparable to a car's fuel tank: if the tank is almost empty, the car won't go far. Most indicators that calculate ATR include anomalous candles, which give unreliable results and lead to incorrect decisions. Because of this, many traders prefer to calculate ATR on their own.
However, the Gerchik ATR indicator accounts for anomalous candles and filters out extremely large candles (> 2x ATR) and extremely small ones (< 0.5x ATR). Additionally, this indicator immediately shows the consumed “fuel” of the instrument as a percentage, so you don't have to calculate the distance traveled yourself. This allows you to make quick, informed decisions. If we see that the tank is almost empty, it is logical not to get into that car today. When building any strategy, you must rely on the average movement.
Key Features:
Anomalous Candle Filtering: Excludes extremely large and small candles to provide more reliable ATR values.
Consumed Fuel Indicator: Shows the percentage of the ATR consumed, helping traders quickly assess the remaining potential movement.
Daily Timeframe Focus: Designed specifically for use on daily charts for accurate long-term analysis.
Practical Applications:
Entry and Exit Points: Use the ATR to determine optimal entry and exit points by assessing market volatility and potential price movement.
Stop-Loss Placement: Calculate stop-loss levels based on ATR to ensure they are placed at appropriate distances, accounting for current market volatility.
Trend Confirmation: Use the percentage of ATR consumed to confirm the strength of a trend and decide whether to enter or exit trades.
Examples of Use:
Trend Following: During strong trends, ATR helps identify periods of increased volatility, signaling potential breakouts or reversals.
Range Trading: In ranging markets, ATR can highlight periods of low volatility, indicating consolidation and potential breakout zones.
Note: The indicator is displayed and works only on the daily timeframe!
The indicator was created according to the instructions, description of the functionality, and strategy of Mr. Gerchik. Thank you so much, Chief!
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Average True Range ( ATR , средний истинный диапазон) – это индикатор технического анализа, который измеряет волатильность на рынке. ATR представляет собой скользящее среднее истинного диапазона за определенный период времени.
Порядок расчета ATR:
1. Определяем истинный максимум – это наивысшее из текущего максимума и вчерашней цены закрытия дня.
2. Определяем истинный минимум – это наименьшее из текущего минимума и вчерашней цены закрытия.
3. Определяем истинный диапазон – это расстояние между истинным максимумом и минимумом.
4. Исключаем из полученных истинных диапазонов экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR).
5. Рассчитываем среднее за выбранный период исходя из оставшегося диапазона.
6 . Рассчитываем процент текущего истинного диапазона (True Range) относительно среднего значения ATR за предыдущий период.
Описание:
Если вы сами проанализируете, то увидите, что 75-80% времени инструмент ходит только 1 ATR. И вы должны понимать, что если инструмент внутри дня прошел, к примеру, 80% своего движения, то этот инструмент больше нельзя покупать. Это можно сравнить с баком машины: если бак почти пустой, машина далеко не уедет. Большинство индикаторов, которые рассчитывают ATR, производят расчет с паранормальными свечами. Это дает недостоверный результат и приводит к неверным решениям. Многие трейдеры из-за этого не используют готовые индикаторы и предпочитают считать ATR самостоятельно. Но индикатор ATR Gerchik учитывает паранормальные свечи и фильтрует экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR). Также этот индикатор сразу показывает израсходованный "бензин" инструмента в процентах. И вам не надо самостоятельно высчитывать пройденный путь. Вы можете быстро принимать правильные решения. Если мы видим, что бак почти пустой, логично не садиться в эту машину сегодня. Когда вы строите какую-то стратегию, вы должны обязательно полагаться на среднестатистическое движение.
Существует много стратегий, завязанных на ATR, которые учитывают волатильность инструмента, запас хода, точки разворота, места выставления стоп-лоссов (SL) и тейк-профитов (TP) и другие факторы. Я не буду останавливаться на них, так как каждый может найти описание этих стратегий и использовать их на свой выбор.
Индикатор отображается и работает только на дневном таймфрейме!
Индикатор создан по наставлениям, описанию функционала и стратегии господина Герчика. Огромное спасибо, Шеф!
Swing Failure Zones and Signals [AlgoAlpha]Elevate your trading strategy with the Swing Failure Zones and Signals indicator by AlgoAlpha! This powerful tool helps you identify potential swing failure zones, offering clear bullish and bearish signals to guide your trading decisions. 📈💡
🎨 Bullish/Bearish Color Customization : Easily set the colors for bullish and bearish signals to match your chart preferences.
🧹 Mitigated Zone Removal : Option to remove mitigated zones from the chart for a cleaner view.
🔍 Range High/Low Lookback : Adjustable lookback period for determining significant highs and lows.
🖌 Dynamic Zone Creation : Automatically draws zones based on swing failure criteria.
🔔 Alert Conditions : Set alerts for both bullish and bearish swing failure conditions to stay informed without constant monitoring.
Quick Guide to Using the Swing Failure Zones and Signals Indicator
🛠 Add the Indicator : Search for "Swing Failure Zones and Signals " in TradingView's Indicators & Strategies. Customize settings like lookback period, colors, and zone removal options to fit your trading style.
📊 Market Analysis : Watch for the appearance of the zones and the directional arrows for potential reversal signals. Use these signals to identify key market entries and exits.
🔔 Alerts : Enable alerts for bullish and bearish swing failure conditions to capture trading opportunities without constant chart monitoring.
How it works
The indicator calculates the direction and length of each candle to identify swing failure points by comparing current high and low prices with those from the lookback period. A bullish swing failure is detected when the current low is lower than the previous low and the close is higher than the previous high, while a bearish swing failure occurs when the current high is higher than the previous high and the close is lower than the previous low. Upon detection, the script creates zones on the chart to indicate these failure points and manages them by removing invalidated zones based on the user's settings. Visual signals are plotted on the chart as arrows, and alerts are set for these conditions to help traders capture potential entry opportunities efficiently.
Enhance your trading edge with this robust tool designed to spotlight critical swing failure points in the market! 💪📈
Percentage GridPercentage Grid Indicator
Description:
The Percentage Grid indicator is designed to assist traders in identifying significant support and resistance levels based on yearly percentage changes. This indicator plots horizontal lines on the chart from the start of the year, allowing you to customize how much percentage each line represents. Currently, you can set up to 5 horizontal lines, each representing a different percentage change from the beginning of the year.
For instance, when applied to the SBI Bank stock, you can customize the lines to display various percentage changes from the start of the year, such as 20%, 25%, and up to 35%, as the SBIN stock is currently trading around these levels. This visualization helps traders to easily identify key levels where price action tends to react, providing valuable insights for making trading decisions.
Principles of Trading Technical Analysis:
The Percentage Grid indicator is grounded in the principle of support and resistance levels, which are fundamental concepts in technical analysis. These levels are specific price points on a chart that tend to act as barriers, preventing the price from getting pushed in a certain direction. The indicator helps in:
Identifying Support Levels: Price levels where a downtrend can be expected to pause due to a concentration of buying interest.
Identifying Resistance Levels: Price levels where an uptrend can be expected to pause due to a concentration of selling interest.
By customizing and plotting percentage-based horizontal lines, the indicator highlights these critical levels based on the percentage change from the start of the year.
How to Use:
Add the Indicator to Your Chart:
Search for "Percentage Grid" in the TradingView indicator library and add it to your chart.
Customize Percentage Levels:
Access the indicator settings to customize the percentage change each line represents.
You can set up to 5 different percentage levels. For example, you can set lines at 20%, 25%, 30%, 35%, and 40%.
Interpret the Grid Lines:
The plotted lines will represent the specified percentage changes from the start of the year.
Use these lines to identify potential support and resistance levels where price action is likely to react.
Practical Application:
Look for price bounces or reversals around these levels, which can indicate strong support or resistance.
Combine the Percentage Grid with other technical analysis tools, such as moving averages or trend lines, to confirm potential trading opportunities.
Example:
In the accompanying screenshot, the Percentage Grid is applied to the SBI Bank stock. The lines are set to display 20%, 25%, 30%, 35%, and 40% changes from the start of the year. Notice how the price action respects these levels, providing clear areas where support and resistance are evident.
By incorporating the Percentage Grid into your trading strategy, you can enhance your ability to identify key price levels and make more informed trading decisions.
Happy Trading!
Advanced Fractal and Hurst IndicatorAdvanced Fractal and Hurst Indicator (AFHI)
Description:
The Advanced Fractal and Hurst Indicator (AFHI) is a custom technical analysis tool designed to identify market trends and potential reversals by leveraging the concepts of Fractal Dimension and the Hurst Exponent . These advanced mathematical concepts provide insights into the complexity and persistence of price movements, making this indicator a powerful addition to any trader's toolkit.
How It Works:
Fractal Dimension (FD) :
The Fractal Dimension measures the complexity of price movements. A higher Fractal Dimension indicates a more complex, choppy market, while a lower value suggests smoother trends.
The FD is calculated using the log difference of price movements over a specified length.
Hurst Exponent (HE) :
The Hurst Exponent indicates the tendency of a time series to either regress to the mean or cluster in a direction. Values below 0.5 indicate a tendency to revert to the mean (mean-reverting), while values above 0.5 suggest a trending market.
The HE is calculated using the rescaled range method, comparing the range of price movements to the standard deviation.
Composite Indicator :
The Composite Indicator combines the smoothed Fractal Dimension and Hurst Exponent to provide a single value indicating market conditions. This is done by normalizing the FD and HE values and combining them into one metric.
A positive Composite Indicator suggests an uptrend, while a negative value indicates a downtrend.
Smoothing :
Both FD and HE values are smoothed using a simple moving average to reduce noise and provide clearer signals.
Trend Confirmation :
A 50-period moving average (MA) is used to confirm the trend direction. The price being above the MA indicates an uptrend, while below the MA indicates a downtrend.
Background Shading :
The indicator pane is shaded green during uptrend conditions (positive Composite Indicator and price above MA) and red during downtrend conditions (negative Composite Indicator and price below MA).
How Traders Can Use It:
Identifying Trends :
Traders can use the AFHI to identify current market trends. The background shading in the indicator pane provides a visual cue for trend direction, with green indicating an uptrend and red indicating a downtrend.
Trend Confirmation :
The Composite Indicator line, plotted in purple, helps confirm the trend. Positive values suggest a strong uptrend, while negative values indicate a strong downtrend.
Entry and Exit Signals :
Traders can use the transitions of the Composite Indicator and the background shading to time their entry and exit points. For instance, a shift from red to green shading suggests a potential buy opportunity, while a shift from green to red suggests a potential sell opportunity.
Alerts :
The script includes alert conditions that can notify traders when the Composite Indicator signals a new trend direction. Alerts can be set up for both uptrends and downtrends, helping traders stay informed of key market changes.
Strategy Development :
By integrating AFHI into their trading strategies, traders can develop more robust systems that account for market complexity and persistence. The indicator can be used alongside other technical tools to enhance decision-making and improve trade accuracy.
Volume Weighted Relative Strength Index (VWRSI) [AlgoAlpha]Volume Weighted Relative Strength Index 📈✨
The Volume Weighted Relative Strength Index (VWRSI) by AlgoAlpha enhances traditional RSI by incorporating volume weighting, providing a more nuanced view of market strength. It uses custom range detection to measure consolidation strength, applying dynamic scoring to highlight trend phases. The indicator includes customizable moving averages (SMA, EMA, WMA, VWMA) and color-coded visual cues for uptrends and downtrends. Additionally, it marks significant bullish and bearish trend points with symbols, making it easier to identify potential trading opportunities. This powerful tool helps traders make informed decisions by combining volume, price action, and trend analysis.
✨ Key Features :
📊 Volume-Weighted RSI : Combines RSI with volume for better accuracy.
🔄 Range Detection : Identifies consolidation phases.
🎨 Customizable MAs : Choose from various moving averages.
🔔 Alert Capabilities : Set notifications for trend points.
🚀 How to Use :
🛠 Add Indicator : Add the indicator to favorites, and customize the settings to suite your trading style.
📊 Analyze Market : Watch RSI and range score for trends.
🔔 Set Alerts : Get notified of bullish/bearish points.
✨ How It Works :
The Volume Weighted Relative Strength Index (VWRSI) combines traditional RSI with volume weighting to offer a more comprehensive view of market momentum. It calculates the RSI using the closing price, then weights it by volume to enhance the accuracy of the trend analysis. The indicator also includes a custom range detection feature that evaluates consolidation strength by dynamically scoring the RSI over a specified period. This scoring helps identify phases of strong trends and consolidations. Visual elements like color-coded trend fills and symbols for bullish and bearish points make it easier to spot key market movements and potential trading opportunities.
Stay ahead with VWRSI by AlgoAlpha! 📈💡
Multi-Frame Market Sentiment DashboardOverview
This Pine Script™ code generates a "Market Sentiment Dashboard" on TradingView, providing a visual summary of market sentiment across multiple timeframes. This tool aids traders in making informed decisions by displaying real-time sentiment analysis based on Exponential Moving Averages (EMA).
Key Features
Panel Positioning:
Custom Placement: Traders can position the dashboard at the top, middle, or bottom of the chart and align it to the left, center, or right, ensuring optimal integration with other chart elements.
Customizable Colors:
Sentiment Colors: Users can define colors for bullish, bearish, and neutral market conditions, enhancing the dashboard's readability.
Text Color: Customizable text color ensures clarity against various background colors.
Label Size:
Scalable Labels: Adjustable label sizes (from very small to very large) ensure readability across different screen sizes and resolutions.
Market Sentiment Calculation:
EMA-Based Sentiment: The dashboard calculates sentiment using a 9-period EMA. If the EMA is higher than two bars ago, the sentiment is bullish; if lower, it's bearish; otherwise, it's neutral.
Multiple Timeframes: Sentiment is calculated for several timeframes: 1 minute, 3 minutes, 5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, and 1 day. This broad analysis provides a comprehensive view of market conditions.
Dynamic Table:
Structured Display: The dashboard uses a table to organize and display sentiment data clearly.
Real-Time Updates: The table updates in real-time, providing traders with up-to-date market information.
How It Works
EMA Calculation: The script requests EMA(9) values for each specified timeframe and compares the current EMA with the EMA from two bars ago to determine market sentiment.
Color Coding: Depending on the sentiment (Bullish, Bearish, or Neutral), the corresponding cell in the table is color-coded using predefined colors.
Table Display: The table displays the timeframe and corresponding sentiment, allowing traders to quickly assess market trends.
Benefits to Traders
Quick Assessment: Traders can quickly evaluate market sentiment across multiple timeframes without switching charts or manually calculating indicators.
Enhanced Visualization: The color-coded sentiment display makes it easy to identify trends at a glance.
Multi-Timeframe Analysis: Provides a broad view of short-term and long-term market trends, helping traders confirm trends and avoid false signals.
This dashboard enhances the overall trading experience by providing a comprehensive, customizable, and easy-to-read summary of market sentiment.
Usage Instructions
Add the Script to Your Chart: Apply the "Market Sentiment Dashboard" indicator to your TradingView chart.
Customize Settings: Adjust the panel position, colors, and label sizes to fit your preferences.
Interpret Sentiment: Use the color-coded table to quickly understand the market sentiment across different timeframes and make informed trading decisions.
sVPSA - standardized Volume Price Spread AnalysisDear Analysts and Traders,
I want to introduce my new indicator - sVPSA - standardized Volume Price Spread Analysis. For me, this script is helpfully in Technical Analysis mainly with Wyckoff and VSA methodologies. Maybe You are in circle of people who used my previous script - normalized Volume Price Spread Analysis. I work with him a lot of time, but I come to a conclusion that I can do better...
Theory concept...
What is a big volume? How big was this spread? It was extreme high or just high? How to do an answer for this and a lot other questions related to this subject? My thoughts was directed to statistics. In my first script I used to x/max normalized data. It was good, but susceptible for high deviation events. So, I choose standardization method with smaller sensitivity on violent events - z-Score standardization Description of z-Score formula:
Z = (x-mean)/standard deviation
Probability of event are descriptive by probability density function - The Normal Distribution.
en.wikipedia.org
en.Wikipedia.org
This is base of script methodology, let’s go deeper in indicator.
X axis is time, date. Y axis is standard deviation. Narrow bar represent price spread, wide one is volume. Colors are corresponding to deviation, blue < sigma, green > sigma, red > 2*sigma and fuchsia > 3*sigma. Appearance is full editable.
Data collection starts from left to right. There is two possibilities to use, constans number of bars or visible data range, also indicator permit to overscore linear regression from data. There is a possibility to set an alert.
Short introduction how put an interpretation on visualized data.
For this example I used constans value of data collection, 52 bars. So, from left I see great, fuchsia volume bar with low spread. This record respond Celsius withdrawals pause. This is bar with the biggest volume on presented chart, more than four sigmas. Spread value is near one sigma. I should consider this via one of Wyckoffs laws - effort vs result. I see a three bars in turn, they tenor tells me that bear market is possible near end. Accumulation structure near new year, spring test and bullish momentum bar near march are approval of this idea. Next high spread bars have volume near mean value. Effort is low but result is great. Interesting is last bar, with -2,8 deviation of volume. I see the lowest volume value on chart, so he’s deviation is strong to negative side. This script require a little of practise and can be a potent tool in Technical Analysis.
If You have a concept how to improve my script or You experience bug, please, send me feedback.
I hope that You consider my work as useful.
I wish You great trades and faultless analysis.
CatTheTrader
