Asset MaxGain MinLoss Tracker [CHE]Asset MaxGain MinLoss Tracker – Your Tool to Discover the Best Trading Opportunities
Introduction
Hello dear traders,
Today, I'd like to introduce you to a fantastic tool: the Asset MaxGain MinLoss Tracker . This indicator is designed to help you identify the best trading opportunities in the market by analyzing the maximum gain and adjusted maximum loss potentials of various assets.
Why Use This Indicator?
1. Time-Saving Analysis
Instead of spending hours sifting through different charts, this indicator provides you with key metrics for up to 10 assets at a glance.
2. Compare Multiple Assets Simultaneously
Monitor and compare multiple assets to discover which ones offer the highest profit potential and the lowest risk of loss.
3. Customizable Settings
Adjust the observation period and select the assets you want to analyze according to your trading strategy.
4. Clear Visual Representation
Data is presented in an easy-to-read table directly on your chart, highlighting assets with the highest maximum gain and the lowest adjusted maximum loss.
How to Use It in Everyday Trading
Step 1: Setting Up the Indicator
Select Your Assets: Choose up to 10 assets you wish to track. These can be cryptocurrencies, stocks, forex pairs, etc.
Configure the Trading Period Length: Set the number of bars (candles) over which you want to calculate the maximum gain and adjusted maximum loss. This allows you to tailor the analysis to your preferred time frame, whether it's short-term trading or long-term investing.
Step 2: Interpreting the Results
Maximum Gain (%): This value shows the potential upside of each asset over the selected period. A higher percentage indicates a greater potential for profit if the asset's price moves upward.
Adjusted Maximum Loss (%): This figure represents the potential downside risk, adjusted to give a more accurate reflection of loss potential. A lower percentage means less risk of significant loss.
Category Highlighting: Assets are categorized based on their performance:
High Gain & Low Loss: Assets that have both the highest max gain and the lowest adjusted max loss.
High Gain: Assets with the highest max gain.
Low Loss: Assets with the lowest adjusted max loss.
Step 3: Making Trading Decisions
Identify Opportunities: Focus on assets categorized as High Gain & Low Loss for the most favorable risk-to-reward scenarios.
Risk Management: Use the adjusted maximum loss to assess and mitigate potential risks associated with each asset.
Portfolio Diversification: Allocate your investments across assets with varying levels of gain and loss potentials to diversify your portfolio effectively.
Practical Example
Imagine you're monitoring the following assets:
Asset 1: BTCUSD
Asset 2: ETHUSD
Asset 3: ADAUSD
Asset 4: XRPUSD
After applying the indicator:
BTCUSD shows a high maximum gain but also a high adjusted maximum loss.
ETHUSD has both a high maximum gain and a low adjusted maximum loss, categorizing it as High Gain & Low Loss.
ADAUSD indicates a low maximum gain but the lowest adjusted maximum loss.
XRPUSD reflects moderate values in both categories.
Decision Making:
Primary Focus: ETHUSD may be your top choice due to its high reward and lower risk.
Risk-Averse Option: ADAUSD could be considered if you prioritize minimizing losses.
Balanced Approach: Diversify by investing in both ETHUSD and ADAUSD.
Understanding the Core Functionality
While you don't need to delve deep into the code to use the indicator effectively, understanding its core function can enhance your confidence in the tool.
The Main Function: Calculating Max Gain and Adjusted Max Loss
The heart of the indicator is a function that calculates two critical metrics for each asset:
Maximum Gain (sym_MaxGain):
Purpose: Measures the highest potential profit over the selected period.
How It Works: It finds the lowest price (sym_minlow) within the period and calculates the percentage increase to the current high price. This shows how much you could have gained if you bought at the lowest point.
Adjusted Maximum Loss (sym_AdjustedMaxLoss):
Purpose: Provides an adjusted measure of the potential loss, giving a more realistic risk assessment.
How It Works: It identifies the highest price (sym_maxhigh) within the period and calculates the percentage decrease to the current low price. This value is adjusted to account for the diminishing impact as losses approach 100%.
Simplified Explanation of the Function
Data Retrieval: For each asset (sym), the function retrieves the high and low prices over the specified timeframe.
Calculations:
Find Highest and Lowest Prices: Determines sym_maxhigh and sym_minlow within the tracking period.
Compute Max Gain: Calculates the potential gain from sym_minlow to the current high.
Compute Max Loss: Calculates the potential loss from sym_maxhigh to the current low.
Adjust Max Loss: Adjusts the max loss calculation to prevent distortion as losses near 100%.
Output: Returns both sym_MaxGain and sym_AdjustedMaxLoss for further analysis.
Benefits of Understanding the Function
Transparency: Knowing how these values are calculated can increase your trust in the indicator's outputs.
Customization: If you're familiar with coding, you might tailor the function to suit specific trading strategies.
Enhanced Analysis: Understanding the underlying calculations allows you to interpret the results more effectively, aiding in better decision-making.
Conclusion
The Asset MaxGain MinLoss Tracker is a powerful tool that can significantly enhance your trading efficiency and effectiveness by:
Providing Quick Insights: Save time by getting immediate access to essential performance metrics of multiple assets.
Assisting in Risk Management: Use the adjusted maximum loss to understand and mitigate potential risks.
Supporting Strategic Decisions: Identify assets with the best risk-to-reward ratios to optimize your trading strategy.
Take advantage of this indicator to elevate your trading game and make more informed decisions with confidence.
Thank you for your time, and happy trading!
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
This indicator is inspired by the "Max Gain" indicator. A special thanks to Skipper86 for his relentless effort, creativity, and contributions to the TradingView community, which served as a foundation for this work.
Indicators and strategies
Portfolio [Afnan]🚀 Portfolio - Advanced Portfolio Management Indicator 📊
A game-changing portfolio management tool designed to help traders stay on top of their positions and manage risk efficiently. This indicator combines detailed tracking, real-time analytics, and visual clarity to ensure traders are well-equipped for the dynamic world of financial markets.
📈 Key Features 💡
Track up to 14 positions with ease
Real-time Profit & Loss (P&L) updates and risk metrics
Visual representation of entry, stop-loss (SL), and target levels
Alerts for stop-loss breaches and target achievements
Comprehensive portfolio summaries for quick analysis
Customizable options to suit individual trading styles
🔍 Main Components ⚙️
📊 1. Position Tracking
Detailed position data: entry, stop-loss, target levels, and more
Real-time risk-reward ratios
Insights into position size and exposure percentages
Continuous updates on P&L in real-time
📉 2. Visual Indicators
Clear visual markers for entry, SL, and target prices
Price labels with detailed percentage changes
Indicators that show the current position's market status
💼 3. Portfolio Summary
Aggregate account values and exposure
Summarized P&L metrics across all positions
Risk management insights for better decision-making
Daily performance tracking to evaluate strategies
⚠️ 4. Alert System
Instant notifications for stop-loss breaches
Alerts when target prices are hit
Alerts operate for the current chart symbol
⚡ Customization Options 🎨
Show or hide specific data columns
Adjust the table's position and size for better visibility
Personalize color schemes and text styles
Switch between full portfolio view and single symbol focus
📱 How to Use 📝
Input your positions in the indicator's settings
Enable or disable specific positions dynamically
Customize display preferences to your liking
Set up alerts for proactive risk management
Monitor all your trading activities in one comprehensive dashboard
📌 Important Notes ℹ️
Compatible with any trading symbol
Updates seamlessly during market hours
Alerts are specific to the currently active chart symbol
Maximum capacity: 14 simultaneous positions
Created by: @AfnanTAjuddin
⚠️ Disclaimer ⚠️
This indicator is a tool for informational purposes only. Ensure all calculations are verified and consult a financial professional before making investment decisions.
🎯 "Stay disciplined, trade smart, and let data guide your decisions." 📊
SnowdexUtilsLibrary "SnowdexUtils"
the various function that often use when create a strategy trading.
f_backtesting_date(train_start_date, train_end_date, test_date, deploy_date)
Backtesting within a specific window based on deployment and testing dates.
Parameters:
train_start_date (int) : the start date for training the strategy.
train_end_date (int) : the end date for training the strategy.
test_date (bool) : if true, backtests within the period from `train_end_date` to the current time.
deploy_date (bool) : if true, the strategy backtests up to the current time.
Returns: given time falls within the specified window for backtesting.
f_init_ma(ma_type, source, length)
Initializes a moving average based on the specified type.
Parameters:
ma_type (simple string) : the type of moving average (e.g., "RMA", "EMA", "SMA", "WMA").
source (float) : the input series for the moving average calculation.
length (simple int) : the length of the moving average window.
Returns: the calculated moving average value.
f_init_tp(side, entry_price, rr, sl_open_position)
Calculates the target profit based on entry price, risk-reward ratio, and stop loss. The formula is `tp = entry price + (rr * (entry price - stop loss))`.
Parameters:
side (bool) : the trading side (true for long, false for short).
entry_price (float) : the entry price of the position.
rr (float) : the risk-reward ratio.
sl_open_position (float) : the stop loss price for the open position.
Returns: the calculated target profit value.
f_round_up(number, decimals)
Rounds up a number to a specified number of decimals.
Parameters:
number (float)
decimals (int)
Returns: The rounded-up number.
f_get_pip_size()
Calculates the pip size for the current instrument.
Returns: Pip size adjusted for Forex instruments or 1 for others.
f_table_get_position(value)
Maps a string to a table position constant.
Parameters:
value (string) : String representing the desired position (e.g., "Top Right").
Returns: The corresponding position constant or `na` for invalid values.
Risk-Reward Labels Minimal with OffsetIndicator Explanation
The indicator “Risk-Reward Labels Minimal with Offset” is designed to assist traders in managing risk and potential rewards. It displays the Stop-Loss (SL) and Take-Profit (TP) levels for both long and short positions based on identified support and resistance levels.
Key Features:
1. Risk-Reward Ratio: Traders can adjust the risk-reward ratio to define the relationship between potential losses and potential gains (e.g., 1:1 or 1:2).
2. Risk Distance: The distance (in pips) is set to determine where to place the SL and TP levels.
3. Labels with Offset: SL and TP labels can be shifted by an offset (bars), allowing for better visualization.
4. Support and Resistance Levels: The indicator dynamically calculates support and resistance. When a support or resistance level is broken, the corresponding labels are deleted.
5. Display in Range Markets: If the market is ranging or lacks a clear trend, both long and short labels are displayed. This allows traders to identify potential entry opportunities in both directions, even when the market is not clearly trending.
6. Deletion Logic: If the price falls below support or rises above resistance, the relevant SL and TP labels are removed. However, in a Range situation, the possibility of seeing both long and short labels remains, increasing flexibility and helping to avoid false signals.
Automatic Fibonacci Levels with EMAAutomatic Fibonacci Levels with EMA
Description:
This script automatically calculates and displays Fibonacci retracement levels based on the highest and lowest prices over a dynamic lookback period. The Fibonacci levels are recalculated on every bar to adapt to price changes, providing an ongoing analysis of key support and resistance areas.
The Fibonacci levels are dynamically colored to reflect the trend direction, determined by the position of the price relative to the Exponential Moving Average (EMA). When the market is in an uptrend (price above EMA), Fibonacci levels are displayed in green, and in a downtrend (price below EMA), they are shown in red. This color coding helps traders quickly identify the current market direction.
Key Features:
Dynamic Fibonacci Levels: Automatically adjusts Fibonacci retracement levels based on recent price action, recalculated with each new bar.
EMA Trend Confirmation: The trend is confirmed by the position of the price relative to the 20-period EMA. Fibonacci levels are color-coded to reflect this trend.
Customizable Lookback Period: Adjust the base lookback period (default 50) and scale it according to your preferred timeframe for more or less sensitivity to recent price action.
Flexible Fibonacci Duration: The Fibonacci levels remain on the chart for a customizable duration (default 2 bars), allowing for visual clarity while adapting to new price action.
Timeframe Scaling: The script automatically adjusts the lookback period based on a scaling factor, making it suitable for different timeframes.
How to Use:
Use the Fibonacci levels to identify potential support and resistance zones based on the market's current price range.
Combine the trend color coding with your own strategy to enhance decision-making, whether for long or short entries.
Adjust the Lookback Period and Fibonacci Duration based on your trading style and timeframe preferences.
This script provides an automatic and customizable way to visualize Fibonacci retracements in a dynamic manner, helping traders make informed decisions based on trend direction and key price levels.
Note: As with any trading tool, always use proper risk management and test the script before using it in live trading.
Order BlockOverview:
The Order Block Indicator is designed to help traders identify key bullish and bearish order blocks on their charts. Order blocks are significant price zones where institutional activity may have occurred, often leading to strong reversals or continuations. This indicator visually highlights these blocks and provides alerts for potential trade opportunities.
Key Features
Bullish Order Blocks (Yellow):
Identifies bullish structures where price signals a potential upward movement.
Highlighted in bright yellow to stand out on your chart.
Bearish Order Blocks (Pink):
Detects bearish structures where price suggests a possible downward movement.
Highlighted in pink for easy identification.
Alerts for Order Blocks:
Sends a notification whenever a bullish or bearish order block is detected.
Keeps you informed of key market zones even when you’re away from the screen.
How It Works
Bullish Order Block Criteria
The last candle (close ) is bullish (close > open).
The second last candle (close ) is bearish (close < open).
The bullish candle’s close is above the high of the bearish candle.
The bearish candle’s close is above the low of the third last candle.
The bearish candle’s low is below the low of the third last candle.
The current candle’s low is above the bearish candle’s high.
These conditions combine to identify strong bullish zones.
Bearish Order Block Criteria
The last candle (close ) is bearish (close < open).
The second last candle (close ) is bullish (close > open).
The bearish candle’s close is below the low of the bullish candle.
The third last candle’s high is above the bullish candle’s close.
The bullish candle’s high is above the high of the third last candle.
The current candle’s high is below the bullish candle’s low.
This logic highlights potential bearish zones.
How to Use It
Add the Indicator to Your Chart:
Use it on any timeframe to spot bullish or bearish order blocks.
Visual Assistance:
Yellow bars indicate bullish order blocks.
Pink bars represent bearish order blocks.
Set Alerts:
Configure alerts to notify you when a bullish or bearish order block appears.
Customization
Colors: Easily change the colors for bullish and bearish order blocks.
Alerts: Adjust alert messages to suit your trading preferences.
Disclaimer:
This indicator is a technical analysis tool and should be used alongside other strategies and market analysis. It does not guarantee profits and carries trading risks. Always trade responsibly.
London/NY Sessions [jpkxyz]London/NY Sessions Indicator Guide
This indicator tracks the forex market's most active trading periods: London session, New York session, and their overlap.
This characteristics of the London and New York trading sessions are well documented and many traders use them as a key element in their trading strategies. It is most relevant in forex trading, however it is to an extend also applicable in cryptocurrencies.
London Session (08:00-16:00 UTC)
Most active trading session (35% of daily forex volume)
Highest trading volume and liquidity
Major price movements and trend development
Significant institutional participation
New York Session (13:00-20:00 UTC)
Second most active trading period
High institutional order flow
Major US economic releases
Significant impact on USD pairs
London/New York Overlap (13:00-16:00 UTC)
The most active period in forex markets:
Maximum market liquidity
Highest daily trading volume
Strong price movements
Tightest spreads
Peak institutional activity
This indicator helps traders:
Visualize key trading sessions
Track session highs and lows
Monitor overlap dynamics
Identify potential support/resistance levels (session highs/lows)
Custom ATR with Paranormal Bar FilterCustom ATR with Paranormal Bar Filter
Description:
This indicator calculates a custom ATR (Average True Range) by filtering out bars with unusually large or small price ranges. It helps provide a more accurate measure of market volatility by ignoring outliers.
How it works:
True Range Calculation:
The price range for each bar is calculated.
Bars with ranges much larger or smaller than typical are excluded.
Filtered ATR:
The ATR is calculated using only the bars that pass the filter.
Current Bar Progress:
Measures how much the current bar has moved compared to the filtered ATR, based on the difference between its opening and closing prices.
Display:
A line represents the filtered ATR.
A table shows the filtered ATR, the current bar's range, and its progress relative to the ATR.
Input Settings:
ATR Period: Number of bars used to calculate the ATR.
Filter Window: Number of recent bars used to determine the typical range.
Filter Threshold: Sensitivity of the filter. A higher value allows more bars to pass.
How to Use:
Monitor Volatility:
Use the filtered ATR to understand market volatility while ignoring unusual price movements.
Track Current Bar Progress:
See how much of the ATR the current bar has completed.
Adjust Filter Settings:
Fine-tune the filter to match your trading timeframe and strategy.
This indicator is designed for traders who want to track market volatility without being misled by extreme outlier bars.
BTC InsightThis script is a comprehensive tool for analyzing Bitcoin's daily price range, trend predictions, and significant volume-based order block levels. It combines multiple technical analysis concepts, including exponential moving averages (EMAs), logarithmic calculations, and custom indicators for advanced forecasting and visualization.
Key Features and Technical Details
1. Exponential Moving Averages (EMAs)
The script calculates two smoothed EMAs:
EMA1 and EMA2 are derived from the logarithmic price of Bitcoin (log(close)).
The smoothing periods and multipliers are user-configurable through inputs:
Smoothed EMA1 Period (default: 728)
Smoothed EMA2 Period (default: 728)
Initial EMA Multipliers (default: 1.0 for EMA1, 5.0 for EMA2)
A time decay factor is applied to the multipliers to adjust sensitivity over time, making the EMAs adaptive to market dynamics.
2. Logarithmic Domain Calculations
The script uses logarithmic transformations to enhance accuracy when dealing with large price changes.
Adjustments to EMAs are made in the logarithmic domain and converted back to the price domain for plotting.
3. EMA Forecasting
The script performs a linear regression analysis over a specified period (728 bars by default) to estimate future price trends for both EMAs.
Slope Adjustments:
RSI (Relative Strength Index) is incorporated to modify the forecast slope dynamically:
RSI > 70: Bearish adjustment (-0.5)
RSI < 30: Bullish adjustment (+0.5)
Forecasts are plotted as dashed lines, projecting future values of EMA1 (green) and EMA2 (red).
4. Order Block Detection
Detects order block levels based on high volume spikes relative to the average volume over a lookback period (default: 100 bars).
A volume multiplier (default: 1.5x) is applied to identify significant volume activity.
Two types of order blocks are identified:
Below EMA1: A price zone where significant buying occurred below EMA1.
Above EMA2: A price zone where significant selling occurred above EMA2.
Order blocks are visualized as shaded rectangles:
Green boxes represent order blocks below EMA1.
Red boxes represent order blocks above EMA2.
5. Customization Inputs
The script allows fine-tuning via the following parameters:
EMA Settings: Periods, multipliers, and time factors for both EMAs.
Volume Analysis Settings: Lookback period and volume multiplier for order block detection.
Order Block Box Settings: Height of the range as a percentage of the detected price.
6. Visualization
EMAs: Two smoothed exponential moving averages are plotted with configurable offsets.
Forecast Lines: Dashed lines project future EMA trends based on regression analysis.
Order Block Boxes: Highlight areas of high volume below EMA1 and above EMA2, indicating potential support or resistance zones.
How It Works in Practice
EMAs and Trend Analysis:
The EMAs represent long-term market trends, adjusted dynamically using custom multipliers and time decay.
The script forecasts the EMAs' future trajectories to anticipate potential price movements.
Order Blocks:
High-volume zones indicate areas where significant market activity occurred, providing insights into potential price reversal points or continuation zones.
RSI Integration:
RSI-based slope adjustment fine-tunes the EMA forecast, adding an extra layer of dynamic market context.
Comprehensive View:
By combining trend forecasts with volume-based zones, the script delivers a robust analysis tool for identifying potential entry/exit points, support/resistance levels, and long-term trend predictions.
Prometheus Markov ChainThe Prometheus Markov Chain Indicator is a custom-built tool designed to predict potential future price movements using a Markov Chain approach. A Markov Chain is a statistical model that assumes the probability of moving to a future state depends solely on the current state. In this indicator, states represent price movement classifications—bullish, bearish, or neutral—and are determined based on historical price changes (percentage returns). The indicator builds a transition matrix to calculate probabilities of transitioning from one state to another, enabling traders to identify patterns and forecast likely price actions.
Core Functionality and Transition Matrix
The transition matrix is the backbone of the Markov Chain. It captures the frequency of transitions between states in the historical price data and normalizes these counts into probabilities. For example, if the price was in a bearish state and transitioned to a bullish state 3 out of 10 times, the probability of transitioning from bearish to bullish would be 0.3. The matrix is created dynamically using the stateFunc function to classify states, which can use either dynamic thresholds (highest and lowest returns over a lookback period) or a user-defined percent return threshold. Below is the snippet that updates the transition matrix:
transitionMatrix = matrix.new(dimension, dimension, 0.0)
for i = 0 to array.size(vec) - 2
fromState = array.get(vec, i)
toState = array.get(vec, i + 1)
transitionMatrix.set(fromState, toState, transitionMatrix.get(fromState, toState) + 1)
for i = 0 to dimension - 1
rowSum = 0.0
for j = 0 to dimension - 1
rowSum += transitionMatrix.get(i, j)
for j = 0 to dimension - 1
prob = transitionMatrix.get(i, j) / rowSum
transitionMatrix.set(i, j, prob)
This snippet iterates through historical price movements, counts state transitions, and then normalizes each row of the matrix so that the sum of probabilities for all possible transitions from a given state equals 1.
How the Indicator Predicts Future States
After constructing the transition matrix, the indicator calculates the current state of the price based on the latest percentage return and then uses the matrix to compute probabilities for transitioning to other states. The state with the highest probability is predicted as the next state, which is displayed on the chart using color-coded labels: green for bullish and red for bearish. The following snippet demonstrates how the current state and predictions are calculated:
current_chng = (close - close ) / close
var int current_state = na
if not use_custom_thresh
highest_chng = ta.highest(current_chng, int(size) * 2)
lowest_chng = ta.lowest(current_chng, int(size) * 2)
current_state := stateFunc(current_chng, highest_chng, lowest_chng)
else
current_state := stateFunc(current_chng, custom_thresh)
predicted_probs = array.new(dimension, 0.0)
for j = 0 to dimension - 1
array.set(predicted_probs, j, transitionMatrix.get(current_state, j))
The indicator evaluates which state has the highest transition probability (highest_prob) and places corresponding labels on the chart. For example, if the next state is predicted to be bullish, a green "Bullish" label is placed below the current bar. This predictive functionality helps traders anticipate potential reversals or continuations in price trends based on historical behavior patterns.
Usage:
Here we see the indicator at work on $PLTR. The states predicted are bullish then bearish. In this example we then see price move in a way that verifies those predictions.
On this 4 Hour NASDAQ:AMZN chart we see predictions play out in a short trade style. States quickly move from one to another but not without giving traders a way to take advantage.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective market state. We encourage any comments about desired updates or criticism!
Previous Candle AverageDescription:
The Previous Candle Average indicator is a powerful tool designed to provide traders with insights into market momentum by visualizing the relationship between the current and previous open levels for a customizable timeframe. This versatile indicator allows you to select from various timeframes, including 1 Month, 1 Week, 1 Day, 8 Hours, 4 Hours, and 1 Hour, making it suitable for different trading strategies, whether you're a swing trader, day trader, or scalper.
The indicator plots the Current Open and Previous Open levels for the selected timeframe and calculates the average value between them. By displaying these critical levels, traders can quickly gauge the current market dynamics relative to the previous period, making it easier to identify support, resistance, or trend continuation.
Key Features:
Custom Timeframe Selection: Easily select the desired timeframe from a variety of options (1M, 1W, 1D, 8H, 4H, 1H) to align with your trading strategy.
Current and Previous Open Levels: The indicator plots both the Current Open and Previous Open levels for the chosen timeframe, providing clear visual guidance on where the market is opening relative to the previous period.
Open Fill with Adjustable Transparency: The area between the Current Open and Previous Open levels is filled with color to represent the relationship between the two. The fill color changes based on whether the Current Open is above or below the Previous Open, with a default 20% opacity for better clarity without overwhelming the chart.
Average Line: The indicator also plots the average value between the Current Open and Previous Open levels, painted by default in a solid white color with a line thickness of 2. This average helps identify potential key levels where the price might react.
Dynamic Coloring: The fill color changes dynamically based on whether the Current Open is higher or lower than the Previous Open, using green to indicate bullish behavior and red for bearish behavior.
How to Use:
The Previous Candle Average indicator can help traders identify the momentum of the market by visually comparing the relationship between consecutive open levels.
Use the Average Line as a reference for potential support or resistance, especially when the market opens near this average.
The Open Fill color can quickly indicate a shift in market sentiment. A green fill suggests that the market is opening stronger than the previous period, while a red fill indicates weakness.
Best Practices:
Combine this indicator with other technical analysis tools, such as trend lines, moving averages, or volume analysis, to confirm potential trading opportunities.
The custom timeframe feature is particularly useful for multi-timeframe analysis. For instance, you can monitor weekly open levels while trading on an hourly chart.
Note: The indicator uses real-time open data and is updated accordingly, ensuring there is no delay or repainting of historical values.
Ideal For:
Traders who want a clear visual representation of market open levels relative to previous periods.
Those who want to identify potential shifts in momentum by comparing open levels across different timeframes.
Traders seeking to add an additional layer of analysis to their existing strategy by incorporating key opening levels and their averages.
ArrayMovingAveragesLibrary "ArrayMovingAverages"
This library adds several moving average methods to arrays, so you can call, eg.:
myArray.ema(3)
method emaArray(id, length)
Calculate Exponential Moving Average (EMA) for Arrays
Namespace types: array
Parameters:
id (array) : (array) Input array
length (int) : (int) Length of the EMA
Returns: (array) Array of EMA values
method ema(id, length)
Get the last value of the EMA array
Namespace types: array
Parameters:
id (array) : (array) Input array
length (int) : (int) Length of the EMA
Returns: (float) Last EMA value or na if empty
method rmaArray(id, length)
Calculate Rolling Moving Average (RMA) for Arrays
Namespace types: array
Parameters:
id (array) : (array) Input array
length (int) : (int) Length of the RMA
Returns: (array) Array of RMA values
method rma(id, length)
Get the last value of the RMA array
Namespace types: array
Parameters:
id (array) : (array) Input array
length (int) : (int) Length of the RMA
Returns: (float) Last RMA value or na if empty
method smaArray(id, windowSize)
Calculate Simple Moving Average (SMA) for Arrays
Namespace types: array
Parameters:
id (array) : (array) Input array
windowSize (int) : (int) Window size for calculation, defaults to array size
Returns: (array) Array of SMA values
method sma(id, windowSize)
Get the last value of the SMA array
Namespace types: array
Parameters:
id (array) : (array) Input array
windowSize (int) : (int) Window size for calculation, defaults to array size
Returns: (float) Last SMA value or na if empty
method wmaArray(id, windowSize)
Calculate Weighted Moving Average (WMA) for Arrays
Namespace types: array
Parameters:
id (array) : (array) Input array
windowSize (int) : (int) Window size for calculation, defaults to array size
Returns: (array) Array of WMA values
method wma(id, windowSize)
Get the last value of the WMA array
Namespace types: array
Parameters:
id (array) : (array) Input array
windowSize (int) : (int) Window size for calculation, defaults to array size
Returns: (float) Last WMA value or na if empty
Crypto Arbitrage Scanner [CryptoSea]Crypto Arbitrage Scanner
The Crypto Arbitrage Scanner is an advanced tool designed to help traders identify arbitrage opportunities across multiple cryptocurrency exchanges. With the ability to compare prices, volumes, and differences in price, this indicator is a must-have for any trader seeking to exploit cross-exchange inefficiencies in real time.
Key Features
Multi-Exchange Price and Volume Comparison: Tracks data from multiple major cryptocurrency exchanges, including BINANCE, COINBASE, KUCOIN, and others, allowing traders to easily compare prices and volume across platforms.
Customizable Difference Metrics: Allows users to toggle between displaying price differences in percentages or absolute dollar values, depending on the preferred metric for arbitrage analysis.
Sorting and Filtering Options: Includes user-defined sorting options to order the data by Price, Volume, or Difference, helping to prioritize potential arbitrage opportunities based on the trader's chosen criteria.
Difference and Volume Thresholds: Users can specify the minimum volume and price difference thresholds, ensuring that only significant arbitrage opportunities are highlighted.
Real-Time Alerts: Built-in alert conditions notify users when arbitrage opportunities exceed their defined price difference thresholds, helping traders respond instantly to market movements.
The Crypto Arb Scanner displays a table of prices, volumes, and price differences across selected exchanges. Each exchange is listed along with the current close price, volume, and the difference in price compared to the average price across all exchanges. Highlighting is used to indicate significant differences that may present arbitrage opportunities.
In the example below, we can see a highlighted opportunity in green showing that the price is below the user inputed thresold.
How it Works
Data Collection: Gathers real-time volume and price data from various exchanges using a streamlined process, allowing for a detailed comparison.
Average Price Calculation: Computes the average price across all valid exchanges to identify where price discrepancies occur, providing a clear picture of arbitrage potential.
Sorting Mechanism: Utilizes custom sorting based on user preferences, making it easy to quickly analyze and identify key opportunities.
Dynamic Highlighting and Alerts: Price differences that exceed user-defined thresholds are highlighted, and alerts can be triggered for these arbitrage opportunities, allowing for a timely response.
Application
Arbitrage Trading: The Crypto Arb Scanner is ideal for traders looking to exploit price differences across exchanges, enabling efficient arbitrage opportunities.
Market Efficiency Analysis: Offers insights into the consistency of prices across exchanges, which can help gauge the efficiency and liquidity of the markets being traded.
Customizable Alerts: Set alerts based on price differences or volume, allowing traders to stay informed about changes without constantly monitoring the markets.
The Crypto Arbitrage Scanner is a powerful addition to any trader's toolkit, offering comprehensive features to detect arbitrage opportunities with confidence. With real-time monitoring, customizable metrics, and a user-friendly interface, this tool allows traders to make informed decisions and capitalize on inefficiencies across exchanges.
Weekly Stacked Daily Changes [LuxAlgo]The Weekly Stacked Daily Changes tool allows traders to compare daily net price changes for each day of the week, stacked by week. It provides a very convenient way to compare daily and weekly volatility at the same time.
🔶 USAGE
The tool requires no configuration and works perfectly out of the box, displaying the net price change for each day of the week as stacked boxes of the appropriate size.
Traders can adjust the width of the columns and the spacing between days and weeks, options to change the color and disable the months and new month lines are also available.
🔹 Bottom Stack Bias
This feature allows traders to compare weekly volatility in two different ways.
With this feature disabled, all weeks use zero as the bottom of the stack, so traders can see at a glance weeks with more volatility and weeks with less volatility.
Enabling this feature will cause the tool to display the stacks with the weekly net price change as the bottom, so if a stack starts below the zero line it means that week has a negative net return, and if it starts above the zero line it means that week has a positive net return.
🔶 SETTINGS
Width: Select the fixed width for each column.
Offset: Choose the fixed width between each column.
Spacing: Select the distance between each day within each column.
🔹 Style
Bottom Stack Bias: Use weekly net price change as the bottom of the stack.
Bullish Change: Color for days with positive net price change
Bearish Change: Color for days with negative net price change
Show Months: Under each week stack, display the month
Show Months Delimiter: Display a line indicating the start of a new month
Drummond Geometry - Pldot and EnvelopeThis Pine Script will:
1.Calculate and display the PL Dot (Price Level Dot), a moving average that reflects short-term market trends.
2.Plot the Envelope Top and Bottom lines based on averages of previous highs and lows, which represent key areas of resistance and support.
Drummond Geometry Overview
Drummond Geometry is a method of market analysis focused on:
PL Dot : Captures market energy and trend direction. It reacts to price deviations and serves as a magnet for price returns, often referred to as a "PL Dot Refresh."
Envelope Theory : Considers price movements as cycles oscillating between the Envelope Top and Bottom. Prices breaking these boundaries often indicate trends, retracements, or exhaustion.
The geometry helps traders visualize energy flows in the market and anticipate directional changes using established support and resistance zones.
Understanding PL Dot and Envelope Top/Bottom
PL Dot:
Formula: Average(Average(H, L, C) of last three bars)
Usage: Indicates short-term trends:
Trend: PL Dot slopes upward or downward.
Congestion: PL Dot moves horizontally.
Envelope Top and Bottom:
Formula:
Top: (11 H1 + 11 H2 + 11 H3) / 3
Bottom: (11 L1 + 11 L2 + 11 L3) / 3
Usage: Acts as dynamic resistance and support:
Price above the top: Indicates strong bullish momentum.
Price below the bottom: Indicates strong bearish momentum.
Advantages of Drummond Geometry
Clarity of Market Flow: Highlights the relationship between price and key levels (PL Dot, Envelope Top/Bottom).
Predictive Power: Suggests possible reversals or continuation based on energy distribution.
Adaptability: Works across multiple time frames and market types (trending, congestion).
Trading Strategy
PL Dot Trades:
Buy: When price returns to the PL Dot in an uptrend.
Sell: When price returns to the PL Dot in a downtrend.
Envelope Trades:
Reversal: Trade counter to price if it breaks and retreats from the Envelope Top/Bottom.
Continuation: Trade in the direction of price if it sustains movement beyond the Envelope Top/Bottom.
Engulfing bar detectorHere’s the updated description with the added step about using Fibonacci levels across timeframes for confirmation:
Liquidity Engulfing Bar Detector
The **Liquidity Engulfing Bar Detector** is a powerful tool designed for traders who want to identify high-probability reversal patterns in the market based on liquidity grabbing and price action. This indicator highlights **Bullish Engulfing** and **Bearish Engulfing** bars that fulfill specific liquidity criteria, helping you spot potential trend reversals and trading opportunities.
**Features**:
1. **Bullish Engulfing Bars**:
- The current candle's low dips below the previous candle's low (grabs liquidity).
- The current candle closes above the previous candle's open.
- A green label is plotted above the engulfing bar for easy identification.
2. **Bearish Engulfing Bars**:
- The current candle's high exceeds the previous candle's high (grabs liquidity).
- The current candle closes below the previous candle's open.
- A red label is plotted below the engulfing bar for clear visibility.
3. **Customizable Alerts**:
- Receive instant notifications via TradingView alerts when a bullish or bearish engulfing pattern is detected.
- Alerts are fully customizable, allowing you to stay updated without actively monitoring the chart.
4. **Visual Markers**:
- Clear and intuitive labels make it easy to spot key patterns directly on your chart.
- Fully integrated with any timeframe and market, ensuring versatility for all trading styles.
---
### **How to Use**:
1. **Add the Indicator**:
- Apply the Liquidity Engulfing Bar Detector to your chart to automatically highlight bullish and bearish engulfing bars.
2. **Enable Alerts**:
- Set up TradingView alerts to get notified of potential setups in real-time.
3. **Analyze with Fibonacci Levels**:
- Draw a Fibonacci retracement tool over the identified engulfing bar, from its low to its high (for bullish patterns) or high to low (for bearish patterns).
- Use the following Fibonacci levels as key zones of interest:
- **0.0 (start)**, **0.25**, **0.5 (midpoint)**, **0.75**, and **1.0 (end)**.
- These levels often act as critical support or resistance zones for price action.
4. **Use Multi-Timeframe Confirmation**:
- Validate zones from higher timeframes using lower timeframe candles:
- **1-minute candles** for confirming zones on the **15-minute chart**.
- **5-minute candles** for confirming zones on the **1-hour chart**.
- **15-minute candles** for confirming zones on the **4-hour chart**.
- This approach ensures precision in your entry points and aligns intraday movements with higher timeframe setups.
5. **Integrate with Your Strategy**:
- Combine the indicator with other tools (e.g., trendlines, moving averages, or volume analysis) for confirmation.
- Use proper risk management to maximize your trading edge.
---
### **Why Use This Indicator?**
Liquidity grabs often signal the participation of major market players, which can lead to significant reversals or continuations. By combining liquidity concepts with engulfing bar patterns and Fibonacci analysis, this indicator helps you:
- Identify key market turning points.
- Improve your entries and exits with multi-timeframe precision.
- Enhance your trading strategy with an edge rooted in smart money concepts.
---
**Note**: This indicator is best used with proper risk management and alongside other technical or fundamental analyses.
---
Let me know if there's anything more you'd like to include!
Equal High and Low FinderThe Matching Close / Equal High Low Finder indicator identifies candles within a specified lookback period that have matching close prices while satisfying specific conditions:
Matching Candle Types:
Only matches bullish candles (close > open) with other bullish candles.
Only matches bearish candles (close < open) with other bearish candles.
Intermediate Candle Condition:
Bullish matches: No intermediate candle between the two matching candles can have a higher close price than the first candle.
Bearish matches: No intermediate candle between the two matching candles can have a lower close price than the first candle.
Gap Between Matches: Ensures at least one intermediate candle exists with a close price different from the matched candles.
Customizable Features:
Adjustable lookback period.
Configurable line style, width, and colors for bullish and bearish matches.
This indicator visually connects the matching candles with lines, offering a clear visual cue for price behavior.
Dix$on's Weighted Volume FlowDixson's Weighted Volume Flow
Dixson's Weighted Volume Flow is a technical indicator designed to analyze and visualize the distribution of buy and sell volume within a given timeframe. It dynamically calculates the proportional allocation of volume based on price action within each bar, providing insights into market sentiment and activity. This indicator displays horizontal volume bars in a separate pane and annotates them with precise volume values.
How It Works
1. Volume Allocation:
- The indicator calculates buy and sell volume using the following formulas:
- Buy Volume = (Close - Low) / (High - Low) Total Volume
- Sell Volume = (High - Close) / (High - Low) Total Volume
- These formulas allocate volume proportionally based on the bar's price range, attributing more volume to buying or selling depending on the relationship between the close, high, and low prices.
2. Dynamic Scaling:
- The buy and sell volumes are scaled relative to their combined total for the period.
- The resulting values determine the length of the horizontal bars, providing a comparative view of buy and sell activity.
3. Bar Visualization:
- Buy Volume Bars: Displayed as green horizontal bars.
- Sell Volume Bars: Displayed as red horizontal bars.
- The lengths of the bars represent the dominance of buy or sell volume, scaled dynamically within the pane.
4. Labels:
- Each bar is annotated with a label showing its calculated buy or sell volume value.
5. Timeframe Adjustment:
- The indicator uses the request.security() function to fetch data from the selected timeframe, allowing users to customize their analysis for intraday, daily, or longer-term trends.
6. Customization Options:
- Enable or disable the indicator using a toggle.
- Adjust colors for the buy/sell bars and text labels to suit your chart theme.
How to Use It
1. Enable the Indicator:
- Activate the indicator using the "Enable/Disable" toggle in the settings.
2. Select a Timeframe:
- Choose the timeframe for analysis (e.g., 1-minute, 1-hour, daily). The indicator fetches volume data specific to the selected timeframe.
3. Interpret the Visualization:
- Compare Bar Lengths:
- Longer buy volume bars (green) indicate stronger buying activity.
- Longer sell volume bars (red) suggest dominant selling pressure.
- Labels:
- Use the labels to view the exact buy and sell volume values for precise analysis.
4. Combine with Other Tools:
- Use the indicator alongside price action analysis, support/resistance levels, or trend indicators to confirm market sentiment and detect potential reversals.
5. Monitor Imbalances:
- Significant disparities between buy and sell volume can signal shifts in market sentiment, such as the end of a trend or the start of a breakout.
Practical Applications
- Trend Confirmation:
- Align the dominance of buy or sell volume with price trends to confirm market direction.
- Reversal Signals:
- Watch for volume imbalances or a sudden shift in the dominance of buy or sell volume to identify potential reversals.
- High-Activity Zones:
- Identify areas with increased volume to anticipate significant price movements or key support/resistance interactions.
Dixson's Weighted Volume Flow provides a clear and systematic way to analyze market activity by visualizing the dynamics of buy and sell volume. It is particularly useful for traders looking to enhance their understanding of volume-based sentiment and its impact on price movements.
hinton_map█ HINTON MAP
This library provides functions to create and display a Hinton Map visualization. A Hinton map uses squares to represent the magnitude and direction of values in a matrix. This library allows you to display multiple ticker/timeframe/indicator combinations on a single chart, using color/boxsize/bnordersize to represent the values used. The values must be from -1.0 to 1.0 in value. 3 different values can be input per square.
Example Usage:
The example below demonstrates how to create a Hinton Map for two symbols (AAPL and MSFT) across three timeframes (1 minute, 5 minutes, and 1 day).
var hintonData = hinton_map.initHintonData(2, 3)
tickers = array.from("AAPL", "MSFT")
timeframes = array.from("1", "5", "1D")
for i = 0 to array.size(tickers) - 1
for j = 0 to array.size(timeframes) - 1
ticker = array.get(tickers, i)
timeframe = array.get(timeframes, j)
= request.security(ticker, timeframe, [close, close , ta.rsi(close, 14)], lookahead = barmerge.lookahead_on)
percent_change = (close_current - close_previous) / close_previous * 100
rsi_deviation = rsi_current - 50
hintonData.unitMatrix.set(i, j, hinton_map.createHintonUnit(
fillValue = percent_change,
borderValue = rsi_deviation,
innerValue = percent_change * rsi_deviation,
boxText = dv.from_string(str.tostring(math.round(percent_change, 2)) + "%"),
tooltipText = dv.from_string(syminfo.ticker + ", " + timeframe + ": " + str.tostring(math.round(percent_change, 2)) + "%, RSI: " + str.tostring(math.round(rsi_current, 2)))
))
hinton_map.drawHintonMap(hintonData)
█ createHintonUnit
Creates a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
Default Value: 0.0
• borderValue
Value to determine the border color hue and width.
Type: float
Default Value: 0.0
• innerValue
Value to determine the inner box color hue.
Type: float
Default Value: 0.0
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
Default Value: na
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
Default Value: na
Returns: HintonUnit
█ initHintonData
Initializes Hinton map data structure.
• rows
Number of rows.
Type: int
• columns
Number of columns.
Type: int
Returns: HintonData
█ drawHintonMap
Draws a Hinton map.
• hintonData
Hinton map data.
Type: HintonData
• unitSize
Size of each unit in bars.
Type: int
Default Value: 10
• borderWidth
Base width of the inner box border.
Type: int
Default Value: 5
• plusHue
Hue value for positive values (0-360).
Type: float
Default Value: 180
• minusHue
Hue value for negative values (0-360).
Type: float
Default Value: -30
█ HintonUnit
Data for a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
• borderValue
Value to determine the border color hue and width.
Type: float
• innerValue
Value to determine the inner box color hue.
Type: float
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
█ HintonData
Structure to store Hinton map data.
• unitMatrix
Matrix of Hinton units.
Type: matrix
• lineMatrix
Matrix of lines.
Type: matrix
• labelMatrix
Matrix of labels.
Type: matrix
• boxMatrix
Matrix of boxes.
Type: matrix
• fillMatrix
Matrix of line fills.
Type: matrix
Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger B# Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands
## Overview
This indicator combines the Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands to create a comprehensive trading system. It provides adaptive trend following capabilities while measuring market volatility and potential reversal points.
## Key Features
- Adaptive moving average that adjusts to market conditions
- Dynamic Bollinger Bands for volatility measurement
- Color-coded KAMA line indicating trend direction
- Integrated buy/sell signals based on multiple confirmations
- Customizable parameters for both KAMA and Bollinger Bands
- Optional bar confirmation wait feature
- Built-in alert conditions for trade signals
## Main Components
### 1. Kaufman Adaptive Moving Average (KAMA)
- Adapts to market volatility using an efficiency ratio
- Changes color based on trend direction (green for uptrend, red for downtrend)
- Adjustable parameters for fine-tuning:
- Base Length: Controls the main calculation period (default: 10)
- Fast EMA Length: For rapid market response (default: 2)
- Slow EMA Length: For stable market conditions (default: 30)
### 2. Bollinger Bands
- Standard deviation-based volatility bands
- Customizable length and standard deviation multiplier
- Includes expansion threshold for volatility measurement
- Components:
- Upper Band: Upper volatility threshold
- Middle Band: Simple moving average
- Lower Band: Lower volatility threshold
## Signal Generation
### Buy Signals
Generated when:
1. KAMA color changes from red to green
2. Price closes above KAMA
3. Price closes above the middle Bollinger Band
4. Signals are marked with:
- Green triangles below the candles
- "B" labels for easy identification
### Sell Signals
Generated when:
1. KAMA color changes from green to red
2. Price closes below KAMA
3. Price closes below the middle Bollinger Band
4. Signals are marked with:
- Red triangles above the candles
- "S" labels for easy identification
## Customizable Parameters
### KAMA Settings
- Base Length (1-50)
- Fast EMA Length (1-10)
- Slow EMA Length (10-50)
- Source Price Selection
- Direction Highlight Toggle
- Bar Confirmation Option
### Bollinger Bands Settings
- Length (default: 20)
- Standard Deviation Multiplier (default: 2.0)
- Expansion Threshold (0.1-3.0)
## Alert Functionality
Built-in alerts for:
- Buy signals with customizable messages
- Sell signals with customizable messages
## Best Practices
### Timeframe Selection
- Works well on multiple timeframes
- Recommended for 15m to 4h charts for optimal signal generation
- Higher timeframes provide more reliable trend signals
### Parameter Optimization
- Adjust KAMA lengths based on trading style:
- Shorter lengths for day trading
- Longer lengths for swing trading
- Fine-tune BB multiplier based on market volatility
- Consider waiting for bar confirmation in volatile markets
### Risk Management
- Use in conjunction with other indicators for confirmation
- Consider market conditions and volatility when trading signals
- Implement proper position sizing and stop-loss levels
## Technical Notes
- Written in Pine Script™ v6
- Overlay indicator (displays on price chart)
- Compatible with all TradingView-supported markets
- Resource-efficient implementation for smooth performance
## Disclaimer
This indicator is provided under the Mozilla Public License 2.0. While it can be a valuable tool for technical analysis, it should not be used as the sole basis for trading decisions. Always combine with proper risk management and additional analysis methods.
Quick scan for signal🙏🏻 Hey TV, this is QSFS, following:
^^ Quick scan for drift (QSFD)
^^ Quick scan for cycles (QSFC)
As mentioned before, ML trading is all about spotting any kind of non-randomness, and this metric (along with 2 previously posted) gonna help ya'll do it fast. This one will show you whether your time series possibly exhibits mean-reverting / consistent / noisy behavior, that can be later confirmed or denied by more sophisticated tools. This metric is O(n) in windowed mode and O(1) if calculated incrementally on each data update, so you can scan Ks of datasets w/o worrying about melting da ice.
^^ windowed mode
Now the post will be divided into several sections, and a couple of things I guess you’ve never seen or thought about in your life:
1) About Efficiency Ratios posted there on TV;
Some of you might say this is the Efficiency Ratio you’ve seen in Perry's book. Firstly, I can assure you that neither me nor Perry, just as X amount of quants all over the world and who knows who else, would say smth like, "I invented it," lol. This is just a thing you R&D when you need it. Secondly, I invite you (and mods & admin as well) to take a lil glimpse at the following screenshot:
^^ not cool...
So basically, all the Efficiency Ratios that were copypasted to our platform suffer the same bug: dudes don’t know how indexing works in Pine Script. I mean, it’s ok, I been doing the same mistakes as well, but loxx, cmon bro, you... If you guys ever read it, the lines 20 and 22 in da code are dedicated to you xD
2) About the metric;
This supports both moving window mode when Length > 0 and all-data expanding window mode when Length < 1, calculating incrementally from the very first data point in the series: O(n) on history, O(1) on live updates.
Now, why do I SQRT transform the result? This is a natural action since the metric (being a ratio in essence) is bounded between 0 and 1, so it can be modeled with a beta distribution. When you SQRT transform it, it still stays beta (think what happens when you apply a square root to 0.01 or 0.99), but it becomes symmetric around its typical value and starts to follow a bell-shaped curve. This can be easily checked with a normality test or by applying a set of percentiles and seeing the distances between them are almost equal.
Then I noticed that on different moving window sizes, the typical value of the metric seems to slide: higher window sizes lead to lower typical values across the moving windows. Turned out this can be modeled the same way confidence intervals are made. Lines 34 and 35 explain it all, I guess. You can see smth alike on an autocorrelogram. These two match the mean & mean + 1 stdev applied to the metric. This way, we’ve just magically received data to estimate alpha and beta parameters of the beta distribution using the method of moments. Having alpha and beta, we can now estimate everything further. Btw, there’s an alternative parameterization for beta distributions based on data length.
Now what you’ll see next is... u guys actually have no idea how deep and unrealistically minimalistic the underlying math principles are here.
I’m sure I’m not the only one in the universe who figured it out, but the thing is, it’s nowhere online or offline. By calculating higher-order moments & combining them, you can find natural adaptive thresholds that can later be used for anomaly detection/control applications for any data. No hardcoded thresholds, purely data-driven. Imma come back to this in one of the next drops, but the truest ones can already see it in this code. This way we get dem thresholds.
Your main thresholds are: basis, upper, and lower deviations. You can follow the common logic I’ve described in my previous scripts on how to use them. You just register an event when the metric goes higher/lower than a certain threshold based on what you’re looking for. Then you take the time series and confirm a certain behavior you were looking for by using an appropriate stat test. Or just run a certain strategy.
To avoid numerous triggers when the metric jitters around a threshold, you can follow this logic: forget about one threshold if touched, until another threshold is touched.
In general, when the metric gets higher than certain thresholds, like upper deviation, it means the signal is stronger than noise. You confirm it with a more sophisticated tool & run momentum strategies if drift is in place, or volatility strategies if there’s no drift in place. Otherwise, you confirm & run ~ mean-reverting strategies, regardless of whether there’s drift or not. Just don’t operate against the trend—hedge otherwise.
3) Flex;
Extension and limit thresholds based on distribution moments gonna be discussed properly later, but now you can see this:
^^ magic
Look at the thresholds—adaptive and dynamic. Do you see any optimizations? No ML, no DL, closed-form solution, but how? Just a formula based on a couple of variables? Maybe it’s just how the Universe works, but how can you know if you don’t understand how fundamentally numbers 3 and 15 are related to the normal distribution? Hm, why do they always say 3 sigmas but can’t say why? Maybe you can be different and say why?
This is the primordial power of statistical modeling.
4) Thanks;
I really wanna dedicate this to Charlotte de Witte & Marion Di Napoli, and their new track "Sanctum." It really gets you connected to the Source—I had it in my soul when I was doing all this ∞
4-Frame Trend CountThis script tracks the current close vs the close from 4 time frames prior to spot a trend reversal after 9 consecutive up or down moves.
Four Supertrend By Baljit AujlaThis Pine Script is an implementation of a "Four Supertrend" indicator by Baljit Aujla. It calculates and plots four Supertrend indicators based on the Average True Range (ATR) method, allowing for different ATR periods and multipliers for each line.
Here is an explanation of the key components:
Inputs
1:- ATR Periods: Four different periods for ATR, adjustable by the user (defaults: 10, 11, 12, 13).
2:- ATR Multipliers: Four different multipliers for the ATR, adjustable by the user (defaults: 1.0, 2.0, 3.0, 4.0).
3:- Source: The data source used for calculation, default is the average of high and low prices (hl2).
4:- Change ATR Calculation Method: Option to switch between the traditional ATR and a simple moving average of true range (SMA of TR).
5:- Signal Display- Options to show buy/sell signals and highlight trends.
Logic:
The script computes four separate Supertrend lines using the ATR method for each line. For each of the four lines, it calculates an uptrend and downtrend threshold, and the trend direction changes when the close price crosses these thresholds.
For each trend line:
1. Uptrend and Downtrend Calculation: The script uses ATR-based bands above and below the price. The uptrend line is calculated by subtracting the ATR multiplied by a given multiplier from the source price, and the downtrend line is calculated by adding the ATR multiplied by a multiplier to the source price.
2. Trend Reversal Logic: The trend switches based on the price action relative to the uptrend and downtrend lines. If the price moves above the downtrend, it signals a switch to an uptrend, and vice versa for a downtrend.
3. Signal Generation: Buy signals occur when the trend changes from negative to positive (down to up), and sell signals occur when the trend changes from positive to negative (up to down).
Plots:
The script plots:
Uptrend and Downtrend Lines: These are visualized as green and red lines for each trend.
Buy/Sell Signals: Small circles are drawn on the chart when a trend change occurs (buy and sell signals).
Trend Highlighting: Background highlighting is applied to show when the market is in an uptrend (green) or downtrend (red).
Alerts:
The script has commented-out alert conditions (alertcondition), which can be enabled to send notifications when a buy or sell signal occurs, or when a trend change happens.
Enhancements:
1. Background Highlighting: This is an option to visually emphasize uptrends and downtrends by filling the background with respective colors.
2. Signal Visibility: You can toggle whether to show the buy/sell signals on the chart.
3. ATR Calculation Method: Option to change the ATR calculation method (using SMA of TR vs the default ATR).
The script is useful for identifying multi-timeframe trends with adjustable parameters and provides both signals and visual markers on the chart to aid in trading decisions.
Issues and Improvements:
The code seems to be truncated, specifically for the last Supertrend line (Line 4). To fully complete the functionality for the fourth line, the logic for up4, down4 and tread4 needs to be finished, similar to the other three lines.
Would you like help finishing the script for the fourth line or improving specific parts of it?
