Machine Learning RSI [BackQuant]Machine Learning RSI
The Machine Learning RSI is a cutting-edge trading indicator that combines the power of Relative Strength Index (RSI) with Machine Learning (ML) clustering techniques to dynamically determine overbought and oversold thresholds. This advanced indicator adapts to market conditions in real-time, offering traders a robust tool for identifying optimal entry and exit points with increased precision.
Core Concept: Relative Strength Index (RSI)
The RSI is a well-known momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Typically, RSI values above 70 are considered overbought, and values below 30 are considered oversold. However, static thresholds may not be effective in all market conditions.
This script enhances the RSI by integrating a dynamic thresholding system powered by Machine Learning clustering, allowing it to adapt thresholds based on historical RSI behavior and market context.
Machine Learning Clustering for Dynamic Thresholds
The Machine Learning (ML) component uses clustering to calculate dynamic thresholds for overbought and oversold levels. Instead of relying on fixed RSI levels, this indicator clusters historical RSI values into three groups using a percentile-based initialization and iterative optimization:
Cluster 1: Represents lower RSI values (typically associated with oversold conditions).
Cluster 2: Represents mid-range RSI values.
Cluster 3: Represents higher RSI values (typically associated with overbought conditions).
Dynamic thresholds are determined as follows:
Long Threshold: The upper centroid value of Cluster 3.
Short Threshold: The lower centroid value of Cluster 1.
This approach ensures that the indicator adapts to the current market regime, providing more accurate signals in volatile or trending conditions.
Smoothing Options for RSI
To further enhance the effectiveness of the RSI, this script allows traders to apply various smoothing methods to the RSI calculation, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Hull Moving Average (HMA)
Linear Regression (LINREG)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Adaptive Linear Moving Average (ALMA)
T3 Moving Average
Traders can select their preferred smoothing method and adjust the smoothing period to suit their trading style and market conditions. The option to smooth the RSI reduces noise and makes the indicator more reliable for detecting trends and reversals.
Long and Short Signals
The indicator generates long and short signals based on the relationship between the RSI value and the dynamic thresholds:
Long Signals: Triggered when the RSI crosses above the long threshold, signaling bullish momentum.
Short Signals: Triggered when the RSI falls below the short threshold, signaling bearish momentum.
These signals are dynamically adjusted to reflect real-time market conditions, making them more robust than static RSI signals.
Visualization and Clustering Insights
The Machine Learning RSI provides an intuitive and visually rich interface, including:
RSI Line: Plotted in real-time, color-coded based on its position relative to the dynamic thresholds (green for long, red for short, gray for neutral).
Dynamic Threshold Lines: The script plots the long and short thresholds calculated by the ML clustering process, providing a clear visual reference for overbought and oversold levels.
Cluster Plots: Each RSI cluster is displayed with distinct colors (green, orange, and red) to give traders insights into how RSI values are grouped and how the dynamic thresholds are derived.
Customization Options
The Machine Learning RSI is highly customizable, allowing traders to tailor the indicator to their preferences:
RSI Settings : Adjust the RSI length, source price, and smoothing method to match your trading strategy.
Threshold Settings : Define the range and step size for clustering thresholds, allowing you to fine-tune the clustering process.
Optimization Settings : Control the performance memory, maximum clustering steps, and maximum data points for ML calculations to ensure optimal performance.
UI Settings : Customize the appearance of the RSI plot, dynamic thresholds, and cluster plots. Traders can also enable or disable candle coloring based on trend direction.
Alerts and Automation
To assist traders in staying on top of market movements, the script includes alert conditions for key events:
Long Signal: When the RSI crosses above the long threshold.
Short Signal: When the RSI crosses below the short threshold.
These alerts can be configured to notify traders in real-time, enabling timely decisions without constant chart monitoring.
Trading Applications
The Machine Learning RSI is versatile and can be applied to various trading strategies, including:
Trend Following: By dynamically adjusting thresholds, this indicator is effective in identifying and following trends in real-time.
Reversal Trading: The ML clustering process helps identify extreme RSI levels, offering reliable signals for reversals.
Range-Bound Trading: The dynamic thresholds adapt to market conditions, making the indicator suitable for trading in sideways markets where static thresholds often fail.
Final Thoughts
The Machine Learning RSI represents a significant advancement in RSI-based trading indicators. By integrating Machine Learning clustering techniques, this script overcomes the limitations of static thresholds, providing dynamic, adaptive signals that respond to market conditions in real-time. With its robust visualization, customizable settings, and alert capabilities, this indicator is a powerful tool for traders seeking to enhance their momentum analysis and improve decision-making.
As always, thorough backtesting and integration into a broader trading strategy are recommended to maximize the effectiveness!
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Easy CotHow to Use the Commitment of Traders (COT) Report for Market Analysis
The Commitment of Traders (COT) report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that breaks down the open interest in various futures markets. It categorizes traders into three main groups: Commercials, Non-Commercials, and Retail Traders (Non-Reportable positions). Understanding and analyzing the COT report can provide insights into market sentiment and potential reversals, especially in commodity, currency, and stock index futures.
Key Components of the COT Report
Commercials (Hedgers)
These are entities involved in the production or consumption of the underlying asset. For example, oil producers might hedge by selling oil futures to lock in prices, while airlines might buy futures to hedge against rising prices.
Commercials typically act as hedgers, so their positions can indicate the need for protection rather than speculative intent. Because they are less price-sensitive, their positions are usually opposite to the trend near market reversals.
Non-Commercials (Large Speculators)
This group includes hedge funds, asset managers, and large traders who take speculative positions to profit from price movements.
Non-Commercials are often trend-followers, meaning they increase long positions in an uptrend and short positions in a downtrend. When Non-Commercials become extremely bullish or bearish, it may signal a potential market reversal.
Retail Traders (Non-Reportable Positions)
These are smaller individual traders whose positions are too small to be reported individually.
Retail traders tend to be less experienced and are often on the wrong side of major market moves, so extreme positions by retail traders can sometimes signal a market turning point.
How to Interpret the COT Data
1. Identify Extreme Positions
Extreme Long or Short Positions: When a group reaches a historically extreme level of long or short positions, it often signals a potential reversal. For instance, if Non-Commercials are overwhelmingly long, it may indicate that the uptrend is overextended, and a reversal could be near.
Contrarian Indicator: Since Retail Traders are often on the wrong side, you may look for signals where they are extremely long or short, indicating a possible reversal in the opposite direction.
2. Look for Divergences
Divergence Between Groups: If Non-Commercials (speculators) and Retail Traders are moving in opposite directions, it could indicate that a trend is losing momentum and a reversal is possible.
Commercials vs. Non-Commercials: Commercials are often positioned opposite to Non-Commercials. If there’s a divergence where Non-Commercials are highly bullish, but Commercials are increasingly bearish, it might suggest a coming reversal.
3. Trend Confirmation and Reversal Signals
Trend Confirmation: If both Non-Commercials and Retail Traders are aligned in one direction, it might confirm the trend. However, keep in mind that such alignment may signal the later stages of a trend.
Reversal Signals: Look for signs when Non-Commercials are reaching a peak in one direction while Retail Traders peak in the opposite. Such situations can often indicate that the current trend is close to exhaustion.
Using the COT Report in Trading Strategies
Contrarian Trading Strategy
Extreme Positions as Reversal Signals: Use COT data to identify extreme positions. For instance, if Non-Commercials have a very high long position in a commodity, it might suggest that a bullish trend is overextended and a bearish reversal could be near.
Retail Trader Extremes: If Retail Traders are heavily long or short, consider taking the opposite position once you have additional confirmation signals (e.g., technical indicators).
Following the Trend with Large Speculators
Non-Commercials tend to be trend-followers, so if you see them increasingly long (or short) on an asset, it could be a signal to follow the trend until extreme levels are reached.
Using Divergences for Entry and Exit Points
Entry: If Non-Commercials are long, but Retail Traders are heavily short, consider entering a long position as it may confirm the trend.
Exit: If Non-Commercials begin to reduce their positions while Retail Traders increase theirs, it might be time to consider exiting, as the trend could be losing momentum.
Weighted CG Oscillator with ATRATR-Weighted CG Oscillator
The ATR-Weighted CG Oscillator is an enhanced version of the Center of Gravity (CG) Oscillator, originally developed by John Ehlers . By adding the Average True Range (ATR) to dynamically adjust the oscillator’s values based on market volatility, this indicator aims to make trend signals more responsive to price changes, offering an adaptive tool for trend analysis.
Functionality Overview :
The CG Oscillator, a classic trend-following indicator, has been modified here to incorporate the ATR for improved context and adaptability in different market conditions. The indicator calculates the CG Oscillator and scales it by dividing the ATR by the closing price to normalize for volatility. This creates a “weighted” CG Oscillator that generates more contextually relevant signals. A colored line shows green for long signals (above the long threshold), red for short signals (below the short threshold), and gray for neutral conditions.
Input Parameters :
CGO Length : Sets the period of the CG Oscillator calculation.
ATR Length : Determines the period of the ATR calculation. Longer periods smooth out the volatility impact.
Long Threshold : The threshold that triggers a long signal; a long (green) signal occurs when the weighted CG Oscillator crosses above this level.
Short Threshold : The threshold that triggers a short signal; a short (red) signal occurs when the weighted CG Oscillator crosses below this level.
Source : Specifies the data source for CG Oscillator calculations, with the default set to the closing price.
Recommended Use :
This indicator is designed to be an adaptive tool, not your sole resource. To ensure its effectiveness, it’s essential to backtest the indicator on your chosen asset over your preferred timeframe. Market dynamics vary, so testing the indicator’s parameters—especially the thresholds—will allow you to find the settings that best suit your strategy. While the default values work well for some scenarios, customizing the settings will help align the indicator with your unique trading style and the asset’s characteristics.
Momentum TrackerTo screen for momentum movers, one can filter for stocks that have made a noticeable move over a set period—this initial move defines the momentum or swing move. From this list of candidates, we can create a watchlist by selecting those showing a momentum pause, such as a pullback or consolidation, which later could set up for a continuation.
This Momentum Tracker Indicator serves as a study tool to visualize when stocks historically met these momentum conditions. It marks on the chart where a stock would have appeared on the screener, allowing us to review past momentum patterns and screener requirements.
Indicator Calculation
Bullish Momentum: Price is above the lowest point within the lookback period by the specified threshold percentage.
Bearish Momentum: Price is below the highest point within the lookback period by the specified threshold percentage.
The tool is customizable in terms of lookback period and percentage threshold to accommodate different trading styles and timeframes, allowing us to set criteria that align with specific hold times and momentum requirements.
William Fractals + SignalsWilliams Fractals + Trading Signals
This indicator identifies Williams Fractals and generates trading signals based on price sweeps of these fractal levels.
Williams Fractals are specific candlestick patterns that identify potential market turning points. Each fractal requires a minimum of 5 bars (2 before, 1 center, 2 after), though this indicator allows you to customize the number of bars checked.
Up Fractal (High Point) forms when you have a center bar whose HIGH is higher than the highs of 'n' bars before and after it. For example, with n=2, you'd see a pattern where the center bar's high is higher than 2 bars before and 2 bars after it. The indicator also recognizes patterns where up to 4 bars after the center can have equal highs before requiring a lower high.
Down Fractal (Low Point) forms when you have a center bar whose LOW is lower than the lows of 'n' bars before and after it. For example, with n=2, you'd see a pattern where the center bar's low is lower than 2 bars before and 2 bars after it. The indicator also recognizes patterns where up to 4 bars after the center can have equal lows before requiring a higher low.
Trading Signals:
The indicator generates signals when price "sweeps" these fractal levels:
Buy Signal (Green Triangle) triggers when price sweeps a down fractal. This requires price to go BELOW the down fractal's low level and then CLOSE ABOVE it . This pattern often indicates a failed breakdown and potential reversal upward.
Sell Signal (Red Triangle) triggers when price sweeps an up fractal. This requires price to go ABOVE the up fractal's high level and then CLOSE BELOW it. This pattern often indicates a failed breakout and potential reversal downward.
Customizable Settings:
1. Periods (default: 10) - How many bars to check before and after the center bar (minimum value: 2)
2. Maximum Stored Fractals (default: 1) - How many fractal levels to keep in memory. Older levels are removed when this limit is reached to prevent excessive signals and maintain indicator performance.
Important Notes:
• The indicator checks the actual HIGH and LOW prices of each bar, not just closing prices
• Fractal levels are automatically removed after generating a signal to prevent repeated triggers
• Signals are only generated on bar close to avoid false triggers
• Alerts include the ticker symbol and the exact price level where the sweep occurred
Common Use Cases:
• Identifying potential reversal points
• Finding stop-hunt levels where price might reverse
• Setting stop-loss levels above up fractals or below down fractals
• Trading failed breakouts/breakdowns at fractal levels
Enhanced Keltner TrendThe Enhanced Keltner Trend (EKT) indicator builds on the classic Keltner Channel, using volatility to define potential trend channels around a central moving average. It combines customizable volatility measures moving average, giving traders flexibility to adapt the trend channel to various market conditions.
How It Works?
MA Calculation:
A user-defined moving average forms the central line (or price basis) of the Keltner Channel.
Channel Width:
The width of the Keltner Channel depends on market volatility.
You can choose between two methods for measuring the volatility:
ATR-based Width: Uses the Average True Range (ATR) with customizable periods and multipliers.
Price Range Width: Uses the high and low price range over a defined period.
Trend Signal:
The trend is evaluated by price in relation to the Keltner Channel:
Bullish Trend (Blue Line): When the price crosses above the upper band, it signals upward momentum.
Bearish Trend (Orange Line): When the price crosses below the lower band, it signals downward momentum.
What Is Unique?
This Enhanced version of the Keltner Trend is for investors who want to have more control over the Keltner's channels calculation, so they can calibrate it to provide them more alpha when combined with other Technical Indicators.
Use ATR: Gives the user the choice to use the ATR for the channel width calculation, or use the default High - Low over specified period.
ATR Period: Users can modify ATR length to calculate the channels width (Volatility).
ATR Multiplier: Users can fine-tune how much of the volatility they want to factor into the channels, providing more control over the final calculation.
MA Period: Smoothing period for the Moving Averages.
MA Type: Choosing from different Moving Averages types providing different smoothing types.
Setting Alerts:
Built-in alerts for trend detection:
Bullish Trend: When price crosses the upper band, it signals a Bullish Signal (Blue Color)
Bearish Trend: When price crosses the lower band, it signals a Bearish Signal (Orange Color)
Credits to @jaggedsoft , it's a modified version of his.
Auto Fibonacci ModePurpose of the Code:
This Pine Script™ code defines an indicator called "Auto Fibonacci Mode" that automatically plots Fibonacci retracement and extension levels based on recent price data, providing traders with reference levels for potential support and resistance. It also offers an "Auto" mode that determines levels based on the selected moving average type (e.g., EMA, SMA) for added flexibility in trend identification.
Key Components and Functionalities:
Inputs:
lookback (Lookback): Determines how many bars back to look when identifying the highest and lowest prices.
reverse: Reverses the direction of Fibonacci calculations, which is helpful for analyzing both uptrends and downtrends.
auto: When enabled, this option automatically adjusts Fibonacci levels based on a moving average.
mod: Allows the user to select a specific moving average type (EMA, SMA, RMA, HMA, or WMA) for use in "Auto" mode.
Label and Color Options: Customize the display of Fibonacci labels, colors, and whether to show the highest and lowest levels on the chart.
Fibonacci Levels:
Sixteen Fibonacci levels are configurable in the input options, allowing users to choose traditional retracement levels (e.g., 0.236, 0.5, 1.618) as well as custom levels.
These levels are calculated dynamically and adjusted based on the highest and lowest price range within the lookback period.
Calculation of Direction and Fibonacci Levels:
Moving Average Direction: Using the specified moving average, the code evaluates the price direction to determine the trend (upward or downward). This direction can be reversed if the user selects the reverse option.
Fibonacci Level Calculation: Each level is computed based on the highest and lowest prices over the lookback range and adjusted according to the selected trend direction and moving average type.
Plotting Fibonacci Levels:
The script generates lines on the chart to represent each Fibonacci level, with customizable gradient colors.
Labels displaying level values and prices can be enabled, providing easy identification of each level on the chart.
Additional Lines:
Lines representing the highest and lowest prices within the lookback range can also be displayed, highlighting recent support and resistance levels for added context.
Usage:
The Auto Fibonacci Mode indicator is designed for traders interested in Fibonacci retracement and extension levels, particularly those seeking automatic trend detection based on moving averages.
This indicator enables:
Automatic adjustment of Fibonacci levels based on selected moving average type.
Quick visualization of support and resistance areas without manual adjustments.
Analysis flexibility with customizable levels and color gradients for easier trend and reversal identification.
This tool is valuable for traders who rely on Fibonacci analysis and moving averages as part of their technical analysis strategy.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Economic Seasons [Daveatt]Ever wondered what season your economy is in?
Just like Mother Nature has her four seasons, the economy cycles through its own seasons! This indicator helps you visualize where we are in the economic cycle by tracking two key metrics:
📊 What We're Tracking:
1. Interest Rates (USIRYY) - The yearly change in interest rates
2. Inflation Rate (USINTR) - The rate at which prices are rising
The magic happens when we normalize these values (fancy math that makes the numbers play nice together) and compare them to their recent averages. We use a lookback period to calculate the standard deviation and determine if we're seeing higher or lower than normal readings.
🔄 The Four Economic Seasons & Investment Strategy:
1. 🌸 Goldilocks (↑Growth, ↓Inflation)
"Not too hot, not too cold" - The economy is growing steadily without overheating.
BEST TIME TO: Buy growth stocks, technology, consumer discretionary
WHY: Companies can grow earnings in this ideal environment of low rates and stable prices
2. 🌞 Reflation (↑Growth, ↑Inflation)
"Party time... but watch your wallet!" - The economy is heating up.
BEST TIME TO: Buy commodities, banking stocks, real estate
WHY: These sectors thrive when inflation rises alongside growth
3. 🌡️ Inflation (↓Growth, ↑Inflation)
"Ouch, my purchasing power!" - Growth slows while prices keep rising.
BEST TIME TO: Rotate into value stocks, consumer staples, healthcare
WHY: These defensive sectors maintain pricing power during inflationary periods
4. ❄️ Deflation (↓Growth, ↓Inflation)
"Winter is here" - Both growth and inflation are falling.
BEST TIME TO: Focus on quality bonds, cash positions, and dividend aristocrats
WHY: Capital preservation becomes key; high-quality fixed income provides safety
🎯 Strategic Trading Points:
- BUY AGGRESSIVELY: During late Deflation/early Goldilocks (the spring thaw)
- HOLD & ACCUMULATE: Throughout Goldilocks and early Reflation
- START TAKING PROFITS: During late Reflation/early Inflation
- DEFENSIVE POSITIONING: Throughout Inflation and Deflation
⚠️ Warning Signs to Watch:
- Goldilocks → Reflation: Time to reduce growth stock exposure
- Reflation → Inflation: Begin rotating into defensive sectors
- Inflation → Deflation: Quality becomes crucial
- Deflation → Goldilocks: Start building new positions
The blue dot shows you where we are right now in this cycle.
The red arrows in the middle remind us that this is a continuous cycle - one season flows into the next, just like in nature!
💡 Pro Tip: The transitions between seasons often provide the best opportunities - but also the highest risks. Use additional indicators and fundamental analysis to confirm these shifts.
Remember: Just like you wouldn't wear a winter coat in summer, you shouldn't use a Goldilocks strategy during Inflation! Time your trades with the seasons. 🎯
Happy Trading! 📈
Mins Before Market Close AlertThis script will set an alert X mins before the market closes.
This is meant to be added to daily charts (calculations based off of daily bars).
This script can be useful for sending webhooks before the market closes to close open positions or to open new ones.
Simply add it to your daily chart and set up your desired alert (email, webhook, sound, etc.).
You can also change the chart marker to a different shape, color, or location to your preference.
Enjoy this simple alert!
Buy&Sell Hollow CandlesThe Hollow Candles Script is a type of candlestick analysis script designed to highlight the following:
Purpose of the Script: This script provides the user with buy and sell signals based on candlesticks that show an upward or downward reversal.
Mechanism of the Script: When a hollow (unfilled) red candle appears, it signals a potential entry, provided that this candle is at a low point, following a series of red candles with higher volume than previous days. Similarly, it gives a sell signal when a green candle appears at a peak with high sell volume surpassing that of prior days. However, the appearance of these candles alone should not prompt an immediate buy or sell; you should wait for a confirming candle to validate the signal.
Sideways Movement Caution: If these signals appear during a sideways or flat trend, it is not advisable to proceed with buying or selling.
Chart Insights: The chart demonstrates certain buy and sell operations along with some non-ideal signals where decision-making should be based on fundamental analytical experience.
DOGE MVRV Z-ScoreThe MVRV-Z score is a relative indicator, which is the "circulating market value" of Dogecoin minus the "realized market value", and then standardized by the standard of the circulating market value. The formula is:
MVRV-Z Score = (circulation market capitalization - realized market capitalization) / Standard Deviation (circulation market capitalization)
The "realized market value" is based on the value of transactions on-chain, calculating the sum of the "last movement value" of all Dogecoins on the chain. Therefore, when this indicator is too high, it means that the market value of Dogecoin is overvalued relative to its actual value, which is detrimental to the price of Dogecoin; otherwise, it means that the market value of Dogecoin is undervalued. According to past historical experience, when this indicator is at a historical high, the probability of a downward trend in Dogecoin prices increases, and attention should be paid to the risks of chasing higher prices.
Adaptive Kalman filter - Trend Strength Oscillator (Zeiierman)█ Overview
The Adaptive Kalman Filter - Trend Strength Oscillator by Zeiierman is a sophisticated trend-following indicator that uses advanced mathematical techniques, including vector and matrix operations, to decompose price movements into trend and oscillatory components. Unlike standard indicators, this model assumes that price is driven by two latent (unobservable) factors: a long-term trend and localized oscillations around that trend. Through a dynamic "predict and update" process, the Kalman Filter leverages vectors to adaptively separate these components, extracting a clearer view of market direction and strength.
█ How It Works
This indicator operates on a trend + local change Kalman Filter model. It assumes that price movements consist of two underlying components: a core trend and an oscillatory term, representing smaller price fluctuations around that trend. The Kalman Filter adaptively separates these components by observing the price series over time and performing real-time updates as new data arrives.
Predict and Update Procedure: The Kalman Filter uses an adaptive predict-update cycle to estimate both components. This cycle allows the filter to adjust dynamically as the market evolves, providing a smooth yet responsive signal. The trend component extracted from this process is plotted directly, giving a clear view of the prevailing direction. The oscillatory component indicates the tendency or strength of the trend, reflected in the green/red coloration of the oscillator line.
Trend Strength Calculation: Trend strength is calculated by comparing the current oscillatory value against a configurable number of past values.
█ Three Kalman filter Models
This indicator offers three distinct Kalman filter models, each designed to handle different market conditions:
Standard Model: This is a conventional Kalman Filter, balancing responsiveness and smoothness. It works well across general market conditions.
Volume-Adjusted Model: In this model, the filter’s measurement noise automatically adjusts based on trading volume. Higher volumes indicate more informative price movements, which the filter treats with higher confidence. Conversely, low-volume movements are treated as less informative, adding robustness during low-activity periods.
Parkinson-Adjusted Model: This model adjusts measurement noise based on price volatility. It uses the price range (high-low) to determine the filter’s sensitivity, making it ideal for handling markets with frequent gaps or spikes. The model responds with higher confidence in low-volatility periods and adapts to high-volatility scenarios by treating them with more caution.
█ How to Use
Trend Detection: The oscillator oscillates around zero, with positive values indicating a bullish trend and negative values indicating a bearish trend. The further the oscillator moves from zero, the stronger the trend. The Kalman filter trend line on the chart can be used in conjunction with the oscillator to determine the market's trend direction.
Trend Reversals: The blue areas in the oscillator suggest potential trend reversals, helping traders identify emerging market shifts. These areas can also indicate a potential pullback within the prevailing trend.
Overbought/Oversold: The thresholds, such as 70 and -70, help identify extreme conditions. When the oscillator reaches these levels, it suggests that the trend may be overextended, possibly signaling an upcoming reversal.
█ Settings
Process Noise 1: Controls the primary level of uncertainty in the Kalman filter model. Higher values make the filter more responsive to recent price changes, but may also increase susceptibility to random noise.
Process Noise 2: This secondary noise setting works with Process Noise 1 to adjust the model's adaptability. Together, these settings manage the uncertainty in the filter's internal model, allowing for finely-tuned adjustments to smoothness versus responsiveness.
Measurement Noise: Sets the uncertainty in the observed price data. Increasing this value makes the filter rely more on historical data, resulting in smoother but less reactive filtering. Lower values make the filter more responsive but potentially more prone to noise.
O sc Smoothness: Controls the level of smoothing applied to the trend strength oscillator. Higher values result in a smoother oscillator, which may cause slight delays in response. Lower values make the oscillator more reactive to trend changes, useful for capturing quick reversals or volatility within the trend.
Kalman Filter Model: Choose between Standard, Volume-Adjusted, and Parkinson-Adjusted models. Each model adapts the Kalman filter for specific conditions, whether balancing general market data, adjusting based on volume, or refining based on volatility.
Trend Lookback: Defines how far back to look when calculating the trend strength, which impacts the indicator's sensitivity to changes in trend strength. Shorter values make the oscillator more reactive to recent trends, while longer values provide a smoother reading.
Strength Smoothness: Adjusts the level of smoothing applied to the trend strength oscillator. Higher values create a more gradual response, while lower values make the oscillator more sensitive to recent changes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
52 Week High/Low Tracking TableThis Indicator helps the User to Quickly view Current Closing Price Compared to the Mentioned Period High and Low.
"Bars Back" indicate the period you need to look back. In case of Daily charts 260 Bars Back usually indicate 52 Weeks/1 year. This is set a default. But you can change it as well.
The Indicator will show the data for below:-
1) High - Highest Close price for the Mentioned Period
2) % from High - The Percentage difference between the Current Close Price Vs Highest Close price for the Mentioned Period. (-) indicate that the current close price is lesser then then High Price.
3) Low - Lowest Close price for the Mentioned Period
4) % from Low - The Percentage difference between the Current Close Price Vs Highest Close price for the Mentioned Period. (-) indicate that the current close price is lesser then then High Price.
You can add this indicator to Quickly Scan multiple stocks to see were they stand.
Dynamic Time Period CandlesThis indicator gives the dynamic history of the current price over various time frames as a series of candles on the right of the display, with optional lines on the chart, so that you can assess the current trend more easily.
In the library I found lots of indicators that looked at the previous xx time period candle, but they then immediately switched to the new xx time candle when it started to be formed. This indicator looks back at the rolling previous time period. With this indicator, you can clearly see how price has been behaving over time.
IMPORTANT SETUP INFO:
Initially, you must go into the settings and select the timeframe (in minutes) that your chart is displaying. If you don't do this then the indicator will look back the wrong number of candles and give you totally wrong results.
You can then setup how high you want the candle labels to be on the chart.
Then you can select settings for each candle that you want displayed. Anywhere between 1 and 5 different timeframes can be displayed on the chart at once.
I initially published an indicator called 'Dynamic 4-Hour Candle (Accurate Highs and Lows)', but this new indicator is so different that it needs to be forked and published as a separate indicator. The reasons for this are below:
The original indicator only looked at the previous 4 hour time period. This indicator allows the user to select any time period that they choose.
The original indicator only looked at one time period. This indicator allows to select between one and five time periods on the chart at once.
The original indicator did not put lines on the chart to show the lookback period and the highs and lows of that time period. This indicator does both those things.
The name of the original indicator in no way now describes what this new indicator is capable of, and would be very misleading to anyone who came across it. This new indicator has a name that much more accurately reflects what its' purpose and functionality is.
[ AlgoChart ] - Compare MarketIndicator Description:
This indicator allows you to display a second asset, selectable from the input panel, in a separate window. Plotted on the same time scale as the first asset but with a distinct price scale, the indicator enables analysis of the relationships and relative movements of two financial instruments. It’s an ideal tool for understanding whether two assets move in a correlated or divergent manner.
Key Features:
Multi-Asset Comparison: Display two assets simultaneously to compare their trends.
Custom Scale: Each asset uses its own price scale, making comparative analysis easier.
Intuitive Interface: Easily select the second asset through the input panel.
Operational Applications:
Spread Trading: Identify optimal moments to execute spread trades when two highly correlated instruments move in opposite directions.
Supply & Demand: Pinpoint zones of interest on both assets, increasing the validity of support and resistance areas.
Exposure Reduction: Monitor instruments that move similarly to avoid exposing the portfolio in identical directions, thereby reducing the risk of double losses.
Additional Features:
Candle Color Change: When a directional divergence occurs between the two assets, the candles change color to highlight the event.
Customizable Notifications: Receive instant alerts when a divergence occurs, allowing you to act promptly.
Previous Day High and Low Count with Probabilities
Indicator Explanation
This indicator displays the number of days on which the previous day's high or low prices were not reached and calculates probabilities for future price movements based on this information. It stores the high and low values of the last 45 days and checks daily whether these levels were touched. Based on the number of days without touching either the high or the low, the indicator calculates the probability of future price movements in either direction (Up or Down).
The indicator offers customization options for label placement and color on the chart. The counts for the high and low touches, along with the calculated probabilities (in percentages), are displayed as labels on the chart. These labels can be shifted along the X-axis by up to 50 bars and can be customized in color and size. Additionally, the text for the labels can be freely chosen, giving the user improved flexibility and overview.
In summary, this indicator helps to:
- Track how often previous day's high and low levels were not reached.
- Estimate probabilities for future price movements based on this information.
- Customize the chart display for easier interpretation.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Adjustments and Risk Management
This strategy can be adjusted by modifying the probability values, the number of days without a high/low touch, and the lot sizes. Additionally, stop-loss and take-profit levels can be added to further control the risk and secure profits.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Risk Disclaimer
The author of this strategy does not assume any liability for potential losses or gains that may arise from the use of this strategy. Trading involves significant risk, and it is important to only trade with capital that you can afford to lose. The strategy presented is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider seeking advice from a professional financial advisor before making any trading decisions.
MERCURY by DrAbhiramSivprasad"MERCURY by DrAbhiramSivprasad"
Developed from over 10 years of personal trading experience, the Mercury Indicator is a strategic tool designed to enhance accuracy in trading decisions. Think of it as a guiding light—a supportive tool that helps traders refine and build more robust strategies by integrating multiple powerful elements into a single indicator. I’ll be sharing some examples to illustrate how I use this indicator in my own trading journey, highlighting its potential to improve strategy accuracy.
Reason behind the combination of emas , cpr and vwap is it provides very good support and resistance in my trading carrier so now i brought them together in one plate
How It Works:
Mercury combines three essential elements—EMA, VWAP, and CPR—each of which plays a vital role in detecting support and resistance:
Exponential Moving Averages (EMAs): Known for their strength in providing dynamic support and resistance levels, EMAs help in identifying trends and shifts in momentum. This indicator includes a dashboard with up to nine customizable EMAs, showing whether each is acting as support or resistance based on real-time price movement.
Volume Weighted Average Price (VWAP): VWAP also provides valuable support and resistance, often regarded as a fair price level by institutional traders. Paired with EMAs, it forms a dual-layered support/resistance system, adding an additional level of confirmation.
Central Pivot Range (CPR): By combining CPR with EMAs and VWAP, Mercury highlights “traffic blocks” in your target journey. This means it identifies zones where price is likely to stall or reverse, providing additional guidance for navigating entries and exits.
Why This Combination Matters:
Using these three tools together gives you a more complete view of the market. VWAP and EMAs offer dynamic trend direction and support/resistance, while CPR pinpoints critical price zones. This combination helps you find high-probability trades, adding clarity to complex market situations and enabling stronger confirmation on trend or reversal decisions.
How to Use:
Trend Confirmation: Check if all EMAs are aligned (green for uptrend, red for downtrend), which is visible in the EMA dashboard. An alignment across VWAP, CPR, and EMAs signifies high confidence in trend direction.
Breakouts & Breakdowns: Mercury has an alert system to signal when a price breakout or breakdown occurs across VWAP, EMA1, and EMA2. This can help in spotting strong directional moves.
Example Application: In my trading, I use Mercury to identify support/resistance zones, confirming trends with EMA/VWAP alignment and using CPR as a checkpoint. I find this especially useful for day trading and swing setups.
Recommended Timeframes:
Day Trading: 5 to 15-minute charts for swift, actionable insights.
Swing Trading: 1-hour or 4-hour charts for broader trend analysis.
Note:
The Mercury Indicator should be used as a supportive tool rather than a standalone strategy, guiding you toward informed decisions in line with your trading style and goals.
EXAMPLE OF TRADE
you can see the cart of XAUUSD on 11th nov 2024
1.SHORT POSITION - TIME FRAME 15 MIN
So here for a short position you need to wait for a breakdown candle which will print in orange post the candle you need to check ema dashboard is completly red that indicates no traffic blocks in your journey to destiny target from ema's and you can take the target from nearest cpr support line
TAKEN IN XAUUSD you can see in chart of XAUUSD on 7th nov
2.LONG POSITION - TIME FRAME 15 MIN -
So here for long position you need to wait for a breakout candle from indicator thats here is blue and check all ema boxes are green and candle body should close above all the 3 lines here it is the both ema 1 and 2 and the vwap line then you can take and entry and your target will be the nearest resistance from the daily cpr
3. STOP LOSS CRITERIA
After the entry any candle close below any of the last line from entry for example we have 3 lines vwap and ema 1 and 2 lines and u have made an entry and the last line before the entry is vwap then if any candle closes below vwap can be considered as stoploss like wise in any lines
The MERCURY indicator is a comprehensive trading tool designed to enhance traders' ability to identify trends, breakouts, and reversals effectively. Created by Dr. Abhiram Sivprasad, this indicator integrates several technical elements, including Central Pivot Range (CPR), EMA crossovers, VWAP levels, and a table-based EMA dashboard, to offer a holistic trading view.
Core Components and Functionality:
Central Pivot Range (CPR):
The CPR in MERCURY provides a central pivot level along with Below Central (BC) and Top Central (TC) pivots. These levels act as potential support and resistance, useful for identifying reversal points and zones where price may consolidate.
Exponential Moving Averages (EMAs):
MERCURY includes up to nine EMAs, with a customizable EMA crossover alert system. This feature enables traders to see shifts in trend direction, especially when shorter EMAs cross longer ones.
VWAP (Volume-Weighted Average Price):
VWAP is incorporated as a dynamic support/resistance level and, combined with EMA crossovers, helps refine entry and exit points for higher probability trades.
Breakout and Breakdown Alerts:
MERCURY monitors conditions for upside and downside breakouts. For an upside breakout, all EMAs turn green and a candle closes above VWAP, EMA1, and EMA2. Similarly, all EMAs turning red, combined with a close below VWAP and EMA1/EMA2, signals a downside breakdown. Continuous alerts are available until the trend shifts.
Real-Time EMA Dashboard:
A table displays each EMA’s relative position (Above or Below), helping traders quickly gauge trend direction. Colors in the table adjust to long/short conditions based on EMA alignment.
Usage Recommendations:
Trend Confirmation:
Use the CPR, EMA alignments, and VWAP to confirm uptrends and downtrends. The table highlights trends, making it easy to spot long or short setups at a glance.
Breakout and Breakdown Alerts:
The alert system is customizable for continuous notifications on critical price levels. When all EMAs align in one direction (green for long, red for short) and the close is above or below VWAP and key EMAs, the indicator confirms a breakout/breakdown.
Adaptable for Different Styles:
Day Trading: Traders can set shorter EMAs for quick insights.
Swing Trading: Longer EMAs combined with CPR offer insights into sustained trends.
Recommended Settings:
Timeframes: MERCURY is suitable for timeframes as low as 5 minutes for intraday traders, up to daily charts for trend analysis.
Symbols: Works across forex, stocks, and crypto. Adjust EMA lengths for asset volatility.
Example Strategy:
Long Entry: When the price crosses above CPR and closes above both EMA1 and EMA2.
Short Entry: When the price falls below CPR with a close below both EMA1 and EMA2.
Pavan CPR Strategy Pavan CPR Strategy (Pine Script)
The Pavan CPR Strategy is a trading system based on the Central Pivot Range (CPR), designed to identify price breakouts and generate long trade signals. This strategy uses key CPR levels (Pivot, Top CPR, and Bottom CPR) calculated from the daily high, low, and close to inform trade decisions. Here's an overview of how the strategy works:
Key Components:
CPR Calculation:
The strategy calculates three critical CPR levels for each trading day:
Pivot (P): The central value, calculated as the average of the high, low, and close prices.
Top Central Pivot (TC): The midpoint of the daily high and low, acting as the resistance level.
Bottom Central Pivot (BC): Derived from the pivot and the top CPR, providing a support level.
The script uses request.security to fetch these CPR values from the daily timeframe, even when applied on intraday charts.
Trade Entry Condition:
A long position is initiated when:
The current price crosses above the Top CPR level (TC).
The previous close was below the Top CPR level, signaling a breakout above a key resistance level.
This condition aims to capture upward momentum as the price breaks above a significant level.
Exit Strategy:
Take Profit: The position is closed with a profit target set 50 points above the entry price.
Stop Loss: A stop loss is placed at the Pivot level to protect against unfavorable price movements.
Visual Reference:
The script plots the three CPR levels on the chart:
Pivot: Blue line.
Top CPR (TC): Green line.
Bottom CPR (BC): Red line.
These plotted levels provide visual guidance for identifying potential support and resistance zones.
Use Case:
The Pavan CPR Strategy is ideal for intraday traders who want to capitalize on price movements and breakouts above critical CPR levels. It provides clear entry and exit signals based on price action and is best used in conjunction with proper risk management.
Note: The strategy is written in Pine Script v5 for use on TradingView, and it is recommended to backtest and optimize it for the asset or market you are trading.
Trend of Multiple Oscillator Dashboard ModifiedDescription: The "Trend of Multiple Oscillator Dashboard Modified" is a powerful Pine Script indicator that provides a dashboard view of various oscillator and trend-following indicators across multiple timeframes. This indicator helps traders to assess trend conditions comprehensively by integrating popular technical indicators, including MACD, EMA, Stochastic, Elliott Wave, DID (Curta, Media, Longa), Price Volume Trend (PVT), Kuskus Trend, and Wave Trend Oscillator. Each indicator’s trend signal (bullish, bearish, or neutral) is displayed in a color-coded dashboard, making it easy to spot the consensus or divergence in trends across different timeframes.
Key Features:
Multi-Timeframe Analysis: Displays trend signals across five predefined timeframes (1, 2, 3, 5, and 10 minutes) for each included indicator.
Customizable Inputs: Allows for customization of key parameters for each oscillator and trend-following indicator.
Trend Interpretation: Each indicator is visually represented with green (bullish), red (bearish), and yellow (neutral) trend markers, making trend identification intuitive and quick.
Trade Condition Controls: Input options for the number of positive and negative conditions needed to trigger entries and exits, allowing users to refine the decision-making criteria.
Delay Management: Options for re-entry conditions based on both price movement (in points) and the minimum number of candles since the last exit, giving users flexibility in managing trade entries.
Usage: This indicator is ideal for traders who rely on multiple oscillators and moving averages to gauge trend direction and strength across timeframes. The dashboard allows users to observe trends at a glance and make informed decisions based on the alignment of various trend indicators. It’s particularly useful in consolidating signals for strategies that require multiple conditions to align before entering or exiting trades.
Note: Ensure that you’re familiar with each oscillator’s functionality, as some indicators like Elliott Wave and Wave Trend are simplified for visual coherence in this dashboard.
Disclaimer: This script is intended for educational and informational purposes only. Use it with caution and adapt it to your specific trading plan.
Developer's Remark: "This indicator's comprehensive design allows traders to filter noise and identify the most robust trends effectively. Use it to visualize trends across timeframes, understand oscillator behavior, and enhance decision-making with a more strategic approach."
GeoMean+The Geometric Moving Average (GMA) with Sigma Bands is a technical indicator that combines trend following and volatility measurement. The blue center line represents the GMA, while the upper and lower bands (light blue) show price volatility using standard deviations (sigma). Traders can use this indicator for both trend following and mean reversion strategies. For trend following, enter long when price crosses above the GMA and short when it crosses below, using the bands as profit targets. For mean reversion, look for buying opportunities when price touches the lower band and selling opportunities at the upper band, with the GMA as your profit target. The indicator includes alerts for band touches and crosses, providing real-time notifications with symbol, timeframe, current price, and band level information. The default 100-period setting works well for daily charts, but can be adjusted shorter (20-50) for intraday trading or longer (200+) for position trading. Wider bands indicate higher volatility (use smaller positions), while narrower bands suggest lower volatility (larger positions possible). For best results, confirm signals with volume and avoid trading against strong trends. Stop losses can be placed beyond the touched band or at the GMA line, depending on your risk tolerance.
Nasan Hull-smoothed envelope The Nasan Hull-Smoothed Envelope indicator is a sophisticated overlay designed to track price movement within an adaptive "envelope." It dynamically adjusts to market volatility and trend strength, using a series of smoothing and volatility-correction techniques. Here's a detailed breakdown of its components, from the input settings to the calculated visual elements:
Inputs
look_back_length (500):
Defines the lookback period for calculating intraday volatility (IDV), smoothing it over time. A higher value means the indicator considers a longer historical range for volatility calculations.
sl (50):
Sets the smoothing length for the Hull Moving Average (HMA). The HMA smooths various lines, creating a balance between sensitivity and stability in trend signals.
mp (1.5):
Multiplier for IDV, scaling the volatility impact on the envelope. A higher multiplier widens the envelope to accommodate higher volatility, while a lower one tightens it.
p (0.625):
Weight factor that determines the balance between extremes (highest high and lowest low) and averages (sma of high and sma of low) in the high/low calculations. A higher p gives more weight to extremes, making the envelope more responsive to abrupt market changes.
Volatility Calculation (IDV)
The Intraday Volatility (IDV) metric represents the average volatility per bar as an exponentially smoothed ratio of the high-low range to the close price. This is calculated over the look_back_length period, providing a base volatility value which is then scaled by mp. The IDV enables the envelope to dynamically widen or narrow with market volatility, making it sensitive to current market conditions.
Composite High and Low Bands
The high and low bands define the upper and lower bounds of the envelope.
High Calculation
a_high:
Uses a multi-period approach to capture the highest highs over several intervals (5, 8, 13, 21, and 34 bars). Averaging these highs provides a more stable reference for the high end of the envelope, capturing both immediate and recent peak values.
b_high:
Computes the average of shorter simple moving averages (5, 8, and 13 bars) of the high prices, smoothing out fluctuations in the recent highs. This generates a balanced view of high price trends.
high_c:
Combines a_high and b_high using the weight p. This blend creates a composite high that balances between recent peaks and smoothed averages, making the upper envelope boundary adaptive to short-term price shifts.
Low Calculation
a_low and b_low:
Similar to the high calculation, these capture extreme lows and smooth low values over the same intervals. This approach creates a stable and adaptive lower bound for the envelope.
low_c:
Combines a_low and b_low using the weight p, resulting in a composite low that adjusts to price fluctuations while maintaining a stable trend line.
Volatility-Adjusted Bands
The final composite high (c_high) and composite low (c_low) bands are adjusted using IDV, which accounts for intraday volatility. When volatility is high, the bands expand; when it’s low, they contract, providing a visual representation of volatility-adjusted price bounds.
Basis Line
The basis line is a Hull Moving Average (HMA) of the average of c_high and c_low. The HMA is known for its smoothness and responsiveness, making the basis line a central trend indicator. The color of the basis line changes:
Green when the basis line is increasing.
Red when the basis line is decreasing.
This color-coded basis line serves as a quick visual reference for trend direction.
Short-Term Trend Strength Block
This component analyzes recent price action to assess short-term bullish and bearish momentum.
Conditions (green, red, green1, red1):
These are binary conditions that categorize price movements as bullish or bearish based on the close compared to the open and the close’s relationship with the exponential moving average (EMA). This separation helps capture different types of strength (above/below EMA) and different bullish or bearish patterns.
Composite Trend Strength Values:
Each of the bullish and bearish counts (above and below the EMA) is normalized, resulting in the following values:
green_EMAup_a and red_EMAup_a for bullish and bearish strength above the EMA.
green_EMAdown_a and red_EMAdown_a for bullish and bearish strength below the EMA.
Trend Strength (t_s):
This calculated metric combines the normalized trend strengths with extra weight to conditions above the EMA, giving more relevance to trends that have momentum behind them.
Enhanced Trend Strength
avg_movement:
Calculates the average absolute price movement over the short_term_length, providing a measurement of recent price activity that scales with volatility.
enhanced_t_s:
Multiplies t_s by avg_movement, creating an enhanced trend strength value that reflects both directional strength and the magnitude of recent price movement.
min and max:
Minimum and maximum percentile thresholds, respectively, based on enhanced_t_s for controlling the color gradient in the fill area.
Fill Area
The fill area between plot_c_high and plot_c_low is color-coded based on the enhanced trend strength (enhanced_t_s):
Gradient color transitions from blue to green based on the strength level, with blue representing weaker trends and green indicating stronger trends.
This visual fill provides an at-a-glance assessment of trend strength across the envelope, with color shifts highlighting momentum shifts.
Summary
The indicator’s purpose is to offer an adaptive price envelope that reflects real-time market volatility and trend strength. Here’s what each component contributes:
Basis Line: A trend-following line in the center that adjusts color based on trend direction.
Envelope (c_high, c_low): Adapts to volatility by expanding and contracting based on IDV, giving traders a responsive view of expected price bounds.
Fill Area: A color-gradient region representing trend strength within the envelope, helping traders easily identify momentum changes.
Overall, this tool helps to identify trend direction, market volatility, and strength of price movements, allowing for more informed decisions based on visual cues around price boundaries and trend momentum.
Kalman Based VWAP [EdgeTerminal]Kalman VWAP is a different take on volume-weighted average price (VWAP) indicator where we enhance the results with Kalman filtering and dynamic wave visualization for a more smooth and improved trend identification and volatility analysis.
A little bit about Kalman Filter:
Kalman filtering (also known as linear quadratic estimation) is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, to produce estimates of unknown variables that tend to be more accurate than those based on a single measurement, by estimating a joint probability distribution over the variables for each time-step. The filter is constructed as a mean squared error minimiser, but an alternative derivation of the filter is also provided showing how the filter relates to maximum likelihood statistics
This indicator combines:
Volume-Weighted Average Price (VWAP) for institutional price levels
Kalman filtering for noise reduction and trend smoothing
Dynamic wave visualization for volatility zones
This creates a robust indicator that helps traders identify trends, support/resistance zones, and potential reversal points with high precision.
What makes this even more special is the fact that we use open price as a data source instead of usual close price. This allows you to tune the indicator more accurately when back testing it and generally get results that are closer to real time market data.
The math:
In case if you're interested in the math of this indicator, the indicator employs a state-space Kalman filter model:
State Equation: x_t = x_{t-1} + w_t
Measurement Equation: z_t = x_t + v_t
x_t is the filtered VWAP state
w_t is process noise ~ N(0, Q)
v_t is measurement noise ~ N(0, R)
z_t is the traditional VWAP measurement
The Kalman filter recursively updates through:
Prediction: x̂_t|t-1 = x̂_{t-1}
Update: x̂_t = x̂_t|t-1 + K_t(z_t - x̂_t|t-1)
Where K_t is the Kalman gain, optimally balancing between prediction and measurement.
Input Parameters
Measurement Noise: Controls signal smoothing (0.0001 to 1.0)
Process Noise: Adjusts trend responsiveness (0.0001 to 1.0)
Wave Size: Multiplier for volatility bands (0.1 to 5.0)
Trend Lookback: Period for trend determination (1 to 100)
Bull/Bear Colors: Customizable color schemes
Application:
I recommend using this along other indicators. This is best used for assets that don't have a close time, such as BTC but can be used with anything as long as the data is there.
With default settings, this works better for swing trades but you can adjust it for day trading as well, by adjusting the lookback and also process noise.
NASI +The NASI + indicator is an advanced adaptation of the classic McClellan Oscillator, a tool widely used to gauge market breadth. It calculates the McClellan Oscillator by measuring the difference between the 19-day and 39-day EMAs of net advancing issues, which are optionally adjusted to account for the relative strength of advancing vs. declining stocks.
To enhance this analysis, NASI + applies the Relative Strength Index (RSI) to the cumulative McClellan Oscillator values, generating a unique momentum-based view of market breadth. Additionally, two extra EMAs—a 10-day and a 4-day EMA—are applied to the RSI, providing further refinement to signals for overbought and oversold conditions.
With NASI +, users benefit from:
-A deeper analysis of market momentum through cumulative breadth data.
-Enhanced sensitivity to trend shifts with the applied RSI and dual EMAs.
-Clear visual cues for overbought and oversold conditions, aiding in intuitive signal identification.
