Depth Trend Indicator - RSIDepth Trend Indicator - RSI
This indicator is designed to identify trends and gauge pullback strength by combining the power of RSI and moving averages with a depth-weighted calculation. The script was created by me, Nathan Farmer and is based on a multi-step process to determine trend strength and direction, adjusted by a "depth" factor for more accurate signal analysis.
How It Works
Trend Definition Using RSI: The RSI Moving Average ( rsiMa ) is calculated to assess the current trend, using customizable parameters for the RSI Period and MA Period .
Trends are defined as follows:
Uptrend : RSI MA > Critical RSI Value
Downtrend : RSI MA < Critical RSI Value
Pullback Depth Calculation: To measure pullback strength relative to the current trend, the indicator calculates a Depth Percentage . This is defined as the portion of the gap between the moving average and the price covered by a pullback.
Depth-Weighted RSI Calculation: The Depth Percentage is then applied as a weighting factor on the RSI Moving Average , giving us a Weighted RSI line that adjusts to the depth of pullbacks. This line is rather noisy, and as such we take a moving average to smooth out some of the noise.
Key Parameters
RSI Period : The period for RSI calculation.
MA Period : The moving average period applied to RSI.
Price MA Period : Determines the SMA period for price, used to calculate pullback depth.
Smoothing Length : Length of smoothing applied to the weighted RSI, creating a more stable signal.
RSI Critical Value : The critical value (level) used in determining whether we're in an uptrend or a downtrend.
Depth Critical Value : The critical value (level) used in determining whether or not the depth weighted value confirms the state of a trend.
Notes:
As always, backtest this indicator and modify the parameters as needed for your specific asset, over your specific timeframe. I chose these defaults as they worked well on the assets I look at, but it is likely you tend to look at a different group of assets over a different timeframe than what I do.
Large pullbacks can create large downward spikes in the weighted line. This isn't graphically pleasing, but I have tested it with various methods of normalization and smoothing and found the simple smoothing used in the indicator to be best despite this.
Weighted
Fibonacci ATR Fusion - Strategy [presentTrading]Open-script again! This time is also an ATR-related strategy. Enjoy! :)
If you have any questions, let me know, and I'll help make this as effective as possible.
█ Introduction and How It Is Different
The Fibonacci ATR Fusion Strategy is an advanced trading approach that uniquely integrates Fibonacci-based weighted averages with the Average True Range (ATR) to identify and capitalize on significant market trends.
Unlike traditional strategies that rely on single indicators or static parameters, this method combines multiple timeframes and dynamic volatility measurements to enhance precision and adaptability. Additionally, it features a 4-step Take Profit (TP) mechanism, allowing for systematic profit-taking at various levels, which optimizes both risk management and return potential in long and short market positions.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The Fibonacci ATR Fusion Strategy utilizes a combination of technical indicators and weighted averages to determine optimal entry and exit points. Below is a breakdown of its key components and operational logic.
🔶 1. Enhanced True Range Calculation
The strategy begins by calculating the True Range (TR) to measure market volatility accurately.
TR = max(High - Low, abs(High - Previous Close), abs(Low - Previous Close))
High and Low: Highest and lowest prices of the current trading period.
Previous Close: Closing price of the preceding trading period.
max: Selects the largest value among the three calculations to account for gaps and limit movements.
🔶 2. Buying Pressure (BP) Calculation
Buying Pressure (BP) quantifies the extent to which buyers are driving the price upwards within a period.
BP = Close - True Low
Close: Current period's closing price.
True Low: The lower boundary determined in the True Range calculation.
🔶 3. Ratio Calculation for Different Periods
To assess the strength of buying pressure relative to volatility, the strategy calculates a ratio over various Fibonacci-based timeframes.
Ratio = 100 * (Sum of BP over n periods) / (Sum of TR over n periods)
n: Length of the period (e.g., 8, 13, 21, 34, 55).
Sum of BP: Cumulative Buying Pressure over n periods.
Sum of TR: Cumulative True Range over n periods.
This ratio normalizes buying pressure, making it comparable across different timeframes.
🔶 4. Weighted Average Calculation
The strategy employs a weighted average of ratios from multiple Fibonacci-based periods to smooth out signals and enhance trend detection.
Weighted Avg = (w1 * Ratio_p1 + w2 * Ratio_p2 + w3 * Ratio_p3 + w4 * Ratio_p4 + Ratio_p5) / (w1 + w2 + w3 + w4 + 1)
w1, w2, w3, w4: Weights assigned to each ratio period.
Ratio_p1 to Ratio_p5: Ratios calculated for periods p1 to p5 (e.g., 8, 13, 21, 34, 55).
This weighted approach emphasizes shorter periods more heavily, capturing recent market dynamics while still considering longer-term trends.
🔶 5. Simple Moving Average (SMA) of Weighted Average
To further smooth the weighted average and reduce noise, a Simple Moving Average (SMA) is applied.
Weighted Avg SMA = SMA(Weighted Avg, m)
- m: SMA period (e.g., 3).
This smoothed line serves as the primary signal generator for trade entries and exits.
🔶 6. Trading Condition Thresholds
The strategy defines specific threshold values to determine optimal entry and exit points based on crossovers and crossunders of the SMA.
Long Condition = Crossover(Weighted Avg SMA, Long Entry Threshold)
Short Condition = Crossunder(Weighted Avg SMA, Short Entry Threshold)
Long Exit = Crossunder(Weighted Avg SMA, Long Exit Threshold)
Short Exit = Crossover(Weighted Avg SMA, Short Exit Threshold)
Long Entry Threshold (T_LE): Level at which a long position is triggered.
Short Entry Threshold (T_SE): Level at which a short position is triggered.
Long Exit Threshold (T_LX): Level at which a long position is exited.
Short Exit Threshold (T_SX): Level at which a short position is exited.
These conditions ensure that trades are only executed when clear trends are identified, enhancing the strategy's reliability.
Previous local performance
🔶 7. ATR-Based Take Profit Mechanism
When enabled, the strategy employs a 4-step Take Profit system to systematically secure profits as the trade moves in the desired direction.
TP Price_1 Long = Entry Price + (TP1ATR * ATR Value)
TP Price_2 Long = Entry Price + (TP2ATR * ATR Value)
TP Price_3 Long = Entry Price + (TP3ATR * ATR Value)
TP Price_1 Short = Entry Price - (TP1ATR * ATR Value)
TP Price_2 Short = Entry Price - (TP2ATR * ATR Value)
TP Price_3 Short = Entry Price - (TP3ATR * ATR Value)
- ATR Value: Calculated using ATR over a specified period (e.g., 14).
- TPxATR: User-defined multipliers for each take profit level.
- TPx_percent: Percentage of the position to exit at each TP level.
This multi-tiered exit strategy allows for partial position closures, optimizing profit capture while maintaining exposure to potential further gains.
█ Trade Direction
The Fibonacci ATR Fusion Strategy is designed to operate in both long and short market conditions, providing flexibility to traders in varying market environments.
Long Trades: Initiated when the SMA of the weighted average crosses above the Long Entry Threshold (T_LE), indicating strong upward momentum.
Short Trades: Initiated when the SMA of the weighted average crosses below the Short Entry Threshold (T_SE), signaling robust downward momentum.
Additionally, the strategy can be configured to trade exclusively in one direction—Long, Short, or Both—based on the trader’s preference and market analysis.
█ Usage
Implementing the Fibonacci ATR Fusion Strategy involves several steps to ensure it aligns with your trading objectives and market conditions.
1. Configure Strategy Parameters:
- Trading Direction: Choose between Long, Short, or Both based on your market outlook.
- Trading Condition Thresholds: Set the Long Entry, Short Entry, Long Exit, and Short Exit thresholds to define when to enter and exit trades.
2. Set Take Profit Levels (if enabled):
- ATR Multipliers: Define how many ATRs away from the entry price each take profit level is set.
- Take Profit Percentages: Allocate what percentage of the position to close at each TP level.
3. Apply to Desired Chart:
- Add the strategy to the chart of the asset you wish to trade.
- Observe the plotted Fibonacci ATR and SMA Fibonacci ATR indicators for visual confirmation.
4. Monitor and Adjust:
- Regularly review the strategy’s performance through backtesting.
- Adjust the input parameters based on historical performance and changing market dynamics.
5. Risk Management:
- Ensure that the sum of take profit percentages does not exceed 100% to avoid over-closing positions.
- Utilize the ATR-based TP levels to adapt to varying market volatilities, maintaining a balanced risk-reward ratio.
█ Default Settings
Understanding the default settings is crucial for optimizing the Fibonacci ATR Fusion Strategy's performance. Here's a precise and simple overview of the key parameters and their effects:
🔶 Key Parameters and Their Effects
1. Trading Direction (`tradingDirection`)
- Default: Both
- Effect: Determines whether the strategy takes both long and short positions or restricts to one direction. Selecting Both allows maximum flexibility, while Long or Short can be used for directional bias.
2. Trading Condition Thresholds
Long Entry (long_entry_threshold = 58.0): Higher values reduce false positives but may miss trades.
Short Entry (short_entry_threshold = 42.0): Lower values capture early short trends but may increase false signals.
Long Exit (long_exit_threshold = 42.0): Exits long positions early, securing profits but potentially cutting trends short.
Short Exit (short_exit_threshold = 58.0): Delays short exits to capture favorable movements, avoiding premature exits.
3. Take Profit Configuration (`useTakeProfit` = false)
- Effect: When enabled, the strategy employs a 4-step TP mechanism to secure profits at multiple levels. By default, it is disabled to allow users to opt-in based on their trading style.
4. ATR-Based Take Profit Multipliers
TP1 (tp1ATR = 3.0): Sets the first TP at 3 ATRs for initial profit capture.
TP2 (tp2ATR = 8.0): Targets larger trends, though less likely to be reached.
TP3 (tp3ATR = 14.0): Optimizes for extreme price moves, seldom triggered.
5. Take Profit Percentages
TP Level 1 (tp1_percent = 12%): Secures 12% at the first TP.
TP Level 2 (tp2_percent = 12%): Exits another 12% at the second TP.
TP Level 3 (tp3_percent = 12%): Closes an additional 12% at the third TP.
6. Weighted Average Parameters
Ratio Periods: Fibonacci-based intervals (8, 13, 21, 34, 55) balance responsiveness.
Weights: Emphasizes recent data for timely responses to market trends.
SMA Period (weighted_avg_sma_period = 3): Smoothens data with minimal lag, balancing noise reduction and responsiveness.
7. ATR Period (`atrPeriod` = 14)
Effect: Sets the ATR calculation length, impacting TP sensitivity to volatility.
🔶 Impact on Performance
- Sensitivity and Responsiveness:
- Shorter Ratio Periods and Higher Weights: Make the weighted average more responsive to recent price changes, allowing quicker trade entries and exits but increasing the likelihood of false signals.
- Longer Ratio Periods and Lower Weights: Provide smoother signals with fewer false positives but may delay trade entries, potentially missing out on significant price moves.
- Profit Taking:
- ATR Multipliers: Higher multipliers set take profit levels further away, targeting larger price movements but reducing the probability of reaching these levels.
- Fixed Percentages: Allocating equal percentages at each TP level ensures consistent profit realization and risk management, preventing overexposure.
- Trade Direction Control:
- Selecting Specific Directions: Restricting trades to Long or Short can align the strategy with market trends or personal biases, potentially enhancing performance in trending markets.
- Risk Management:
- Take Profit Percentages: Dividing the position into smaller percentages at multiple TP levels helps lock in profits progressively, reducing risk and allowing the remaining position to ride further trends.
- Market Adaptability:
- Weighted Averages and ATR: By combining multiple timeframes and adjusting to volatility, the strategy adapts to different market conditions, maintaining effectiveness across various asset classes and timeframes.
---
If you want to know more about ATR, can also check "SuperATR 7-Step Profit".
Enjoy trading.
Dynamic Sentiment RSI [UAlgo]The Dynamic Sentiment RSI is a technical analysis tool that combines the classic RSI (Relative Strength Index) concept with dynamic sentiment analysis, offering traders enhanced insights into market conditions. Unlike the traditional RSI, this indicator integrates volume weighting, sentiment factors, and smoothing features to provide a more nuanced view of momentum and potential market reversals. It is designed to assist traders in detecting overbought/oversold conditions, momentum shifts, and to generate potential buy or sell signals using crossover and crossunder techniques. By dynamically adjusting based on sentiment and volume factors, this RSI offers better adaptability to varying market conditions, making it suitable for different trading styles and timeframes.
This tool is particularly helpful for traders who wish to explore not only price movement but also the underlying market sentiment, offering a more comprehensive approach to momentum analysis. The sentiment factor amplifies the RSI's sensitivity to price shifts, making it easier to detect early signals of market reversals or the continuation of a trend.
🔶 Key Features
Dynamic Sentiment Calculation: The indicator incorporates a "Sentiment Factor" that adjusts the RSI length dynamically based on a multiplier, helping traders better understand market sentiment at different time intervals.
Volume Weighting: When enabled, the RSI calculations are weighted by volume, allowing traders to give more importance to price movements with higher trading volume, which may provide more accurate signals.
Smoothing Feature: A customizable smoothing period is applied to the RSI to help filter out noise and make the signal smoother. This feature is particularly useful for traders who prefer to focus on long-term trends while minimizing false signals.
Step Size Customization: A "Step Size" input allows users to round the sentiment RSI to predefined intervals, making the results easier to interpret and act upon. This feature allows you to focus on significant sentiment changes and ignore minor fluctuations.
Crossover/Crossunder Alerts: The indicator includes crossover and crossunder signals on the zero-line, helping traders identify potential buy and sell opportunities as the smoothed RSI crosses these levels.
The indicator offers a clear visual display with multiple color-coded lines and areas:
Sentiment RSI: Plotted as an area chart, color-coded based on sentiment strength.
Raw RSI: A purple line representing the raw adjusted RSI.
Smoothed RSI: A dynamic line, color-coded aqua or orange based on its position relative to the zero line.
Buy/Sell Signals: Triangle shapes are plotted at crossovers and crossunders, providing clear entry and exit points.
🔶 Interpreting the Indicator
Sentiment RSI
-This line represents the sentiment-adjusted RSI, where the higher the value, the stronger the bullish sentiment, and the lower the value, the stronger the bearish sentiment. It is rounded to step intervals, making it easier to detect significant shifts in sentiment.
- A positive sentiment RSI (above 0) suggests bullish market conditions, while a negative sentiment RSI (below 0) suggests bearish conditions.
Smoothed RSI
The smoothed RSI helps reduce noise and shows the trend more clearly.
Crossovers of the zero line are significant:
- Crossover above zero: Indicates that bullish momentum is building, potentially signaling a buying opportunity.
- Crossunder below zero: Signals a shift towards bearish momentum, potentially indicating a sell signal.
Traders should look for these crossovers in conjunction with other signals for more accurate entry/exit points.
Raw RSI (Adjusted)
The raw adjusted RSI offers a less smoothed, more responsive version of the RSI. While it may be noisier, it provides early signals of market reversals and trends.
Crossover/Crossunder Signals
- When the smoothed RSI crosses above the zero line, a "Signal Up" triangle appears, indicating a potential buying opportunity.
- When the smoothed RSI crosses below the zero line, a "Signal Down" triangle appears, signaling a potential sell opportunity.
These signals help traders time their entries and exits by identifying momentum shifts.
Volume Weighting (Optional)
- If volume weighting is enabled, the RSI will give more weight to periods of higher trading volume, making the signals more reliable when the market is highly active.
Strong Up/Down Levels (40/-40)
- These dotted lines represent extreme sentiment levels. When the sentiment RSI reaches 40 or -40, the market may be nearing an overbought or oversold condition, respectively. This could be a signal for traders to prepare for potential reversals or shifts in momentum.
By combining the various components of this indicator, traders can gain a comprehensive view of market sentiment and price action, helping them make more informed trading decisions. The combination of sentiment factors, volume weighting, and smoothing makes this indicator highly flexible and suitable for a variety of trading strategies.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Pulse Oscillator [UAlgo]The "Pulse Oscillator " is a trading tool designed to capture market momentum and trend changes by combining the strengths of multiple well-known technical indicators. By integrating the RSI (Relative Strength Index), CCI (Commodity Channel Index), and Stochastic Oscillator, this indicator provides traders with a comprehensive view of market conditions, offering both trend filtering and precise buy/sell signals. The oscillator is customizable, allowing users to fine-tune its parameters to match different trading strategies and timeframes. With its built-in smoothing techniques and level adjustments, the Pulse Oscillator aims to be a reliable tool for both trend-following and counter-trend trading strategies.
🔶 Key Features
Multi-Indicator Integration: Combines RSI, CCI, and Stochastic Oscillator to create a weighted momentum oscillator.
Why Use Multi-Indicator Integration?
Script uses Multi-Indicator Integration to combine the strengths of different technical indicators—such as RSI, CCI, and Stochastic Oscillator—into a single tool. This approach helps to reduce the weaknesses of individual indicators, providing a more comprehensive and reliable analysis of market conditions. By integrating multiple indicators, we can generate more accurate signals, filter out noise, and enhance our trading decisions.
Customizable Parameters: Allows users to adjust weights, periods, and smoothing techniques, providing flexibility to adapt the indicator to various market conditions.
Trend Filtering Option: An optional trend filter is available to enhance the accuracy of buy and sell signals, reducing the risk of false signals in choppy markets.
Dynamic Levels: The indicator dynamically calculates multiple levels of support and resistance, adjusting to market conditions with customizable decay factors and offsets.
Visual Clarity: The indicator visually represents different levels and trends with color-coded plots and fills, making it easier for traders to interpret market conditions at a glance.
Alerts: Configurable alerts for buy and sell signals, as well as trend changes, enabling traders to stay informed of key market movements without constant monitoring.
🔶 Interpreting the Indicator
Buy Signal: A buy signal is generated when the Slow Line crosses under the Fast Line during an uptrend or when the trend filter is disabled. This indicates a potential bullish reversal or continuation of an upward trend.
Sell Signal: A sell signal occurs when the Slow Line crosses above the Fast Line during a downtrend or when the trend filter is disabled, signaling a potential bearish reversal or continuation of a downward trend.
Trend Change: The indicator detects trend changes when the Fast Line shifts from increasing to decreasing or vice versa, providing early warning of possible market reversals.
Dynamic Levels: The indicator calculates upper and lower levels based on the Fast Line's values. These levels can be used to identify overbought or oversold conditions and potential areas of support or resistance.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Quadratic Weighted Bands"Quadratic Weighted Bands" (QWB) is designed to identify and visualize market trends and volatility using quadratic weighted filtering techniques. It works by applying quadratic weighting to a selected data source over a specified length, enhancing the sensitivity and responsiveness of the indicator to recent market movements. A major advantage of this indicator is the ability to have a longer lookback period without having too much lag. This results in a smoother output that is still very responsive. Its about twice as fast as a normal average so adjust accordingly.
The indicator is customizable, allowing users to select between the normal Quadratic Weighting (QWF) and Volume Quadratic Weighting (VQWF), choose their data source, adjust the lookback period, and modify the deviation multiplier to fit their analysis needs. Additionally, users can customize the colors of the bands and center line.
The color of the central line changes based on the direction of the trend, as well as having a neutral (ranging) color. This visual aspect makes it easier for traders to quickly see the strength and direction of the market.
Style Select: Choose between "Normal Quadratic Weighting" or "Volume Quadratic Weighting" to adapt the indicator based on volume data or standard price data.
Source: This allows for the selection of the input source for the indicator, such as HL2, ensuring the analysis is aligned with specific trading preferences.
Length: Define the lookback period for the average, with the system automatically utilizing the maximum available length if the specified range exceeds available data, ensuring it always works.
Deviation Length: Optionally adjust the lookback period for calculating deviation, enhancing the indicator's sensitivity and accuracy in identifying market volatility.
Multiplier: Fine tune the deviation multiplier to control the width of the bands, allowing traders to adjust for market volatility and personal risk tolerance.
Top Color: Customize the color of the top band, which also affects the center line's appearance. Adjusting the brightness provides visual clarity and personalization.
Bottom Color: Similarly, select the color for the bottom band, which also influences the center line. The option to adjust brightness ensures the indicator's readability and aesthetic preference.
Neutral Color: Designate a color for indicating a ranging market.
Enjoy
Advanced Dynamic Threshold RSI [Elysian_Mind]Advanced Dynamic Threshold RSI Indicator
Overview
The Advanced Dynamic Threshold RSI Indicator is a powerful tool designed for traders seeking a unique approach to RSI-based signals. This indicator combines traditional RSI analysis with dynamic threshold calculation and optional Bollinger Bands to generate weighted buy and sell signals.
Features
Dynamic Thresholds: The indicator calculates dynamic thresholds based on market volatility, providing more adaptive signal generation.
Performance Analysis: Users can evaluate recent price performance to further refine signals. The script calculates the percentage change over a specified lookback period.
Bollinger Bands Integration: Optional integration of Bollinger Bands for additional confirmation and visualization of potential overbought or oversold conditions.
Customizable Settings: Traders can easily customize key parameters, including RSI length, SMA length, lookback bars, threshold multiplier, and Bollinger Bands parameters.
Weighted Signals: The script introduces a unique weighting mechanism for signals, reducing false positives and improving overall reliability.
Underlying Calculations and Methods
1. Dynamic Threshold Calculation:
The heart of the Advanced Dynamic Threshold RSI Indicator lies in its ability to dynamically calculate thresholds based on multiple timeframes. Let's delve into the technical details:
RSI Calculation:
For each specified timeframe (1-hour, 4-hour, 1-day, 1-week), the Relative Strength Index (RSI) is calculated using the standard 14-period formula.
SMA of RSI:
The Simple Moving Average (SMA) is applied to each RSI, resulting in the smoothing of RSI values. This smoothed RSI becomes the basis for dynamic threshold calculations.
Dynamic Adjustment:
The dynamically adjusted threshold for each timeframe is computed by adding a constant value (5 in this case) to the respective SMA of RSI. This dynamic adjustment ensures that the threshold reflects changing market conditions.
2. Weighted Signal System:
To enhance the precision of buy and sell signals, the script introduces a weighted signal system. Here's how it works technically:
Signal Weighting:
The script assigns weights to buy and sell signals based on the crossover and crossunder events between RSI and the dynamically adjusted thresholds. If a crossover event occurs, the weight is set to 2; otherwise, it remains at 1.
Signal Combination:
The weighted buy and sell signals from different timeframes are combined using logical operations. A buy signal is generated if the product of weights from all timeframes is equal to 2, indicating alignment across timeframe.
3. Experimental Enhancements:
The Advanced Dynamic Threshold RSI Indicator incorporates experimental features for educational exploration. While not intended as proven strategies, these features aim to offer users a glimpse into unconventional analysis. Some of these features include Performance Calculation, Volatility Calculation, Dynamic Threshold Calculation Using Volatility, Bollinger Bands Module, Weighted Signal System Incorporating New Features.
3.1 Performance Calculation:
The script calculates the percentage change in the price over a specified lookback period (variable lookbackBars). This provides a measure of recent performance.
pctChange(src, length) =>
change = src - src
pctChange = (change / src ) * 100
recentPerformance1H = pctChange(close, lookbackBars)
recentPerformance4H = pctChange(request.security(syminfo.tickerid, "240", close), lookbackBars)
recentPerformance1D = pctChange(request.security(syminfo.tickerid, "1D", close), lookbackBars)
3.2 Volatility Calculation:
The script computes the standard deviation of the closing price to measure volatility.
volatility1H = ta.stdev(close, 20)
volatility4H = ta.stdev(request.security(syminfo.tickerid, "240", close), 20)
volatility1D = ta.stdev(request.security(syminfo.tickerid, "1D", close), 20)
3.3 Dynamic Threshold Calculation Using Volatility:
The dynamic thresholds for RSI are calculated by adding a multiplier of volatility to 50.
dynamicThreshold1H = 50 + thresholdMultiplier * volatility1H
dynamicThreshold4H = 50 + thresholdMultiplier * volatility4H
dynamicThreshold1D = 50 + thresholdMultiplier * volatility1D
3.4 Bollinger Bands Module:
An additional module for Bollinger Bands is introduced, providing an option to enable or disable it.
// Additional Module: Bollinger Bands
bbLength = input(20, title="Bollinger Bands Length")
bbMultiplier = input(2.0, title="Bollinger Bands Multiplier")
upperBand = ta.sma(close, bbLength) + bbMultiplier * ta.stdev(close, bbLength)
lowerBand = ta.sma(close, bbLength) - bbMultiplier * ta.stdev(close, bbLength)
3.5 Weighted Signal System Incorporating New Features:
Buy and sell signals are generated based on the dynamic threshold, recent performance, and Bollinger Bands.
weightedBuySignal = rsi1H > dynamicThreshold1H and rsi4H > dynamicThreshold4H and rsi1D > dynamicThreshold1D and crossOver1H
weightedSellSignal = rsi1H < dynamicThreshold1H and rsi4H < dynamicThreshold4H and rsi1D < dynamicThreshold1D and crossUnder1H
These features collectively aim to provide users with a more comprehensive view of market dynamics by incorporating recent performance and volatility considerations into the RSI analysis. Users can experiment with these features to explore their impact on signal accuracy and overall indicator performance.
Indicator Placement for Enhanced Visibility
Overview
The design choice to position the "Advanced Dynamic Threshold RSI" indicator both on the main chart and beneath it has been carefully considered to address specific challenges related to visibility and scaling, providing users with an improved analytical experience.
Challenges Faced
1. Differing Scaling of RSI Results:
RSI values for different timeframes (1-hour, 4-hour, and 1-day) often exhibit different scales, especially in markets like gold.
Attempting to display these RSIs on the same chart can lead to visibility issues, as the scaling differences may cause certain RSI lines to appear compressed or nearly invisible.
2. Candlestick Visibility vs. RSI Scaling:
Balancing the visibility of candlestick patterns with that of RSI values posed a unique challenge.
A single pane for both candlesticks and RSIs may compromise the clarity of either, particularly when dealing with assets that exhibit distinct volatility patterns.
Design Solution
Placing the buy/sell signals above/below the candles helps to maintain a clear association between the signals and price movements.
By allocating RSIs beneath the main chart, users can better distinguish and analyze the RSI values without interference from candlestick scaling.
Doubling the scaling of the 1-hour RSI (displayed in blue) addresses visibility concerns and ensures that it remains discernible even when compared to the other two RSIs: 4-hour RSI (orange) and 1-day RSI (green).
Bollinger Bands Module is optional, but is turned on as default. When the module is turned on, the users can see the upper Bollinger Band (green) and lower Bollinger Band (red) on the main chart to gain more insight into price actions of the candles.
User Flexibility
This dual-placement approach offers users the flexibility to choose their preferred visualization:
The main chart provides a comprehensive view of buy/sell signals in relation to candlestick patterns.
The area beneath the chart accommodates a detailed examination of RSI values, each in its own timeframe, without compromising visibility.
The chosen design optimizes visibility and usability, addressing the unique challenges posed by differing RSI scales and ensuring users can make informed decisions based on both price action and RSI dynamics.
Usage
Installation
To ensure you receive updates and enhancements seamlessly, follow these steps:
Open the TradingView platform.
Navigate to the "Indicators" tab in the top menu.
Click on "Community Scripts" and search for "Advanced Dynamic Threshold RSI Indicator."
Select the indicator from the search results and click on it to add to your chart.
This ensures that any future updates to the indicator can be easily applied, keeping you up-to-date with the latest features and improvements.
Review Code
Open TradingView and navigate to the Pine Editor.
Copy the provided script.
Paste the script into the Pine Editor.
Click "Add to Chart."
Configuration
The indicator offers several customizable settings:
RSI Length: Defines the length of the RSI calculation.
SMA Length: Sets the length of the SMA applied to the RSI.
Lookback Bars: Determines the number of bars used for recent performance analysis.
Threshold Multiplier: Adjusts the multiplier for dynamic threshold calculation.
Enable Bollinger Bands: Allows users to enable or disable Bollinger Bands integration.
Interpreting Signals
Buy Signal: Generated when RSI values are above dynamic thresholds and a crossover occurs.
Sell Signal: Generated when RSI values are below dynamic thresholds and a crossunder occurs.
Additional Information
The indicator plots scaled RSI lines for 1-hour, 4-hour, and 1-day timeframes.
Users can experiment with additional modules, such as machine-learning simulation, dynamic real-life improvements, or experimental signal filtering, depending on personal preferences.
Conclusion
The Advanced Dynamic Threshold RSI Indicator provides traders with a sophisticated tool for RSI-based analysis, offering a unique combination of dynamic thresholds, performance analysis, and optional Bollinger Bands integration. Traders can customize settings and experiment with additional modules to tailor the indicator to their trading strategy.
Disclaimer: Use of the Advanced Dynamic Threshold RSI Indicator
The Advanced Dynamic Threshold RSI Indicator is provided for educational and experimental purposes only. The indicator is not intended to be used as financial or investment advice. Trading and investing in financial markets involve risk, and past performance is not indicative of future results.
The creator of this indicator is not a financial advisor, and the use of this indicator does not guarantee profitability or specific trading outcomes. Users are encouraged to conduct their own research and analysis and, if necessary, consult with a qualified financial professional before making any investment decisions.
It is important to recognize that all trading involves risk, and users should only trade with capital that they can afford to lose. The Advanced Dynamic Threshold RSI Indicator is an experimental tool that may not be suitable for all individuals, and its effectiveness may vary under different market conditions.
By using this indicator, you acknowledge that you are doing so at your own risk and discretion. The creator of this indicator shall not be held responsible for any financial losses or damages incurred as a result of using the indicator.
Kind regards,
Ely
Fibonacci Bollinger Volume Weighted DeviationDiscover market dynamics with the 'Fibonacci Bollinger Volume Weighted Deviation' indicator – a unique tool blending Fibonacci ratios, Bollinger Bands, and volume-weighted analysis. Ideal for spotting overbought/oversold conditions and potential market turnarounds, this indicator is a must-have for traders seeking nuanced insights into price behavior and volatility.
Description:
"The 'Fibonacci Bollinger Volume Weighted Deviation' indicator presents a novel approach to market trend analysis by integrating Fibonacci ratios with the classic concept of Bollinger Bands. Designed for traders who incorporate Fibonacci levels in their market analysis, this indicator adapts Bollinger Bands to a user-defined Fibonacci ratio. It creates dynamic upper and lower bands around a Simple Moving Average (SMA), offering insights into price deviations and potential overbought or oversold market states.
Incorporating volume data, this indicator provides a volume-weighted perspective of price deviations. This feature is crucial in gauging the market sentiment, as significant volumes linked with price deviations can signal strong market moves. By plotting these deviations and emphasizing those that significantly diverge from the volume-weighted average, it aids in pinpointing potential turning points or key support and resistance zones.
Versatile in nature, the 'Fibonacci Bollinger Volume Weighted Deviation' indicator is adaptable to various trading styles and market conditions. It proves especially valuable in markets where Fibonacci levels are a key factor. Traders can explore long positions when prices fall below the lower band and consider short positions when prices breach the upper band. The addition of volume-weighted deviation analysis refines these trading signals, offering a more sophisticated and nuanced decision-making process for entries and exits.
As a standalone tool or in conjunction with other technical instruments, this indicator is an invaluable addition to any technical analyst's toolkit. It not only enhances traditional Fibonacci and Bollinger Band methodologies but also integrates volume analysis to provide a comprehensive view of market trends and movements."
Advanced Weighted Residual Arbitrage AnalyzerThe Advanced Weighted Residual Arbitrage Analyzer is a sophisticated tool designed for traders aiming to exploit price deviations between various asset pairs. By examining the differences in normalized price relations and their weighted residuals, this indicator provides insights into potential arbitrage opportunities in the market.
Key Features:
Multiple Relation Analysis: Analyze up to five different asset relations simultaneously, offering a comprehensive view of potential arbitrage setups.
Normalization Functions: Choose from a variety of normalization techniques like SMA, EMA, WMA, and HMA to ensure accurate comparisons between different price series.
Dynamic Weighting: Residuals are weighted based on their correlation, ensuring that stronger correlations have a more pronounced impact on the analysis. Weighting can be adjusted using several functions including square, sigmoid, and logistic.
Regression Flexibility: Incorporate linear, polynomial, or robust regression to calculate residuals, tailoring the analysis to different market conditions.
Customizable Display: Decide which plots to display for clarity and focus, including normalized relations, weighted residuals, and the difference between the screen relation and the average weighted residual.
Usage Guidelines:
Configure the asset pairs you wish to analyze using the Symbol Relations group in the settings.
Adjust the normalization, volatility, regression, and weighting functions based on your preference and the specific characteristics of the asset pairs.
Monitor the weighted residuals for deviations from the mean. Larger deviations suggest stronger arbitrage opportunities.
Use the difference plot (between the screen relation and average weighted residual) as a quick visual cue for potential trade setups. When this plot deviates significantly from zero, it indicates a possible arbitrage opportunity.
Regularly update and adjust the parameters to account for changing market conditions and ensure the most accurate analysis.
In the Advanced Weighted Residual Arbitrage Analyzer , the value set in Alert Threshold plays a crucial role in delineating a normalized band. This band serves as a guide to identify significant deviations and potential trading opportunities.
When we observe the plots of the green line and the purple line, the Alert Threshold provides a boundary for these plots. The following points explain the significance:
Breach of the Band: When either the green or purple line crosses above or below the Alert Threshold , it indicates a significant deviation from the mean. This breach can be interpreted as a potential trading signal, suggesting a possible arbitrage opportunity.
Convergence to the Mean: If the green line converges with the purple line , it denotes that the price relation has reverted to its mean. This convergence typically suggests that the arbitrage opportunity has been exhausted, and the market dynamics are returning to equilibrium.
Trade Execution: A trader can consider entering a trade when the lines breach the Alert Threshold . The return of the green line to align closely with the purple line can be seen as a signal to exit the trade, capitalizing on the reversion to the mean.
By monitoring these plots in conjunction with the Alert Threshold , traders can gain insights into market imbalances and exploit potential arbitrage opportunities. The convergence and divergence of these lines, relative to the normalized band, serve as valuable visual cues for trade initiation and termination.
When you're analyzing relations between two symbols (for instance, BINANCE:SANDUSDT/BINANCE:NEARUSDT ), you're essentially looking at the price relationship between the two underlying assets. This relationship provides insights into potential imbalances between the assets, which arbitrage traders can exploit.
Breach of the Lower Band: If the purple line touches or crosses below the lower Alert Threshold , it indicates that the first symbol (in our example, SANDUSDT ) is undervalued relative to the second symbol ( NEARUSDT ). In practical terms:
Action: You would consider buying the first symbol ( SANDUSDT ) and selling the second symbol ( NEARUSDT ).
Rationale: The expectation is that the price of the first symbol will rise, or the price of the second symbol will fall, or both, thereby converging back to their historical mean relationship.
Breach of the Upper Band: Conversely, if the difference plot touches or crosses above the upper Alert Threshold , it suggests that the first symbol is overvalued compared to the second. This implies:
Action: You'd consider selling the first symbol ( SANDUSDT ) and buying the second symbol ( NEARUSDT ).
Rationale: The anticipation here is that the price of the first symbol will decrease, or the price of the second will increase, or both, bringing the relationship back to its historical average.
Convergence to the Mean: As mentioned earlier, when the green line aligns closely with the purple line, it's an indication that the assets have returned to their typical price relationship. This serves as a signal for traders to consider closing out their positions, locking in the gains from the arbitrage opportunity.
It's important to note that when you're trading based on symbol relations, you're essentially betting on the relative performance of the two assets. This strategy, often referred to as "pairs trading," seeks to capitalize on price imbalances between related financial instruments. By taking opposing positions in the two symbols, traders aim to profit from the eventual reversion of the price difference to the mean.
QQE Weighted Oscillator [LuxAlgo]The QQE (Quantitative Qualitative Estimation) Weighted Oscillator improves on its original version by weighting the RSI based on the indications given by the trailing stop, requiring more effort in order for a cross with the trailing stop to occur.
🔶 USAGE
The QQE Weighted Oscillator is comprised of a smoothed RSI oscillator and a trailing stop derived from this same RSI. The oscillator can be used to indicate whether the market is overbought/oversold as well as an early indication of trend reversals thanks to the leading nature of the RSI.
Using higher Factor values will return a longer-term trailing stop.
Like with a regular RSI divergence can be indicative of a reversal.
Further weighting will control how much "effort" is required for the trailing stop to cross the RSI. For example. For example, an RSI above the trailing stop will require a higher degree of negative price variations in order for a potential cross to occur when using higher weights.
This can cause higher weightings to return more cyclical and smoother results.
🔶 SETTINGS
Length: Length of the RSI oscillator.
Factor: Multiplicative factor used for the trailing stop calculation.
Smooth: Degree of smoothness of the RSI oscillator.
Weight: Degree of weighting used for the RSI calculation.
Volume-Weighted Supertrend Strategy [wbburgin]This is a script that can be used as a strategy or a standalone indicator.
The Volume-Weighted Supertrend is a supertrend based on a rolling VWAP, instead of a normal price source. The strategy has two components - a supertrend based off of this VWAP (shown on the chart) and a supertrend from volume itself (not plotted on the chart directly). The supertrend from volume is an example of my "Supertrend Any Source" indicator, where a custom ATR is created from non-OHLC data; this is available as both a separate public script and also in my "wbburgin_utils" library for you to use in your own script creation.
The supertrend from volume acts as a confirmation filter for the VWAP-supertrend shown on-chart. If the volume supertrend is trending up and the VWAP-based supertrend is also trending up, a buy signal is generated. Likewise, if the volume supertrend is trending down and the VWAP-supertrend is trending down, a sell signal is generated. The colors are based off of whether both supertrends are trending up or down: green for both up, blue for only price up, orange for only price down, and red for both down.
The settings enable you to change the volume length and the ATR length separately, as well as the multiplier and the source for the price supertrend. If you load the indicator for the first time and see no entries and exits, this is because "Show Strategy Entries and Exits" is disabled in the settings. This is if you plan on using the strategy as an indicator and don't want to be bothered by the entry and exit symbols on the chart. Additionally, for those who like clean charts (like me), you can turn all the labels off in the settings, as well as the highlighting.
My default strategy settings for the strategy results shown below are as follows: 5% equity per trade, 5 degrees of pyramiding, commissions of 0.08% per trade. This strategy doesn't come with stops yet, so please be aware of that before using it to trade - I highly suggest you create your own stops based off of your R/R ratio and personal risk tolerance. Additionally, it works best on trending assets (b/c of the supertrends) with high volume. This might mean it does not work as well on lower timeframes.
Anchored VWAP Pinch & Handoff, Intervals, and Signals"Anchored VWAP Pinch & Handoff, Intervals, and Signals" is an AVWAP toolbox for those who like to use various VWAP trading techniques. The indicator is currently comprised of the following three sections:
• The Pinch & Handoff section (shown above on chart) allows manually setting an upper and lower AVWAP (Pinch) along with an additional AVWAP (Handoff) by entering dates or by dragging the vertical anchor lines to the desired significant events on chart. Each of these three AVWAPs can also be set to show zones above and/or below by a percentage or standard deviation amount. The theory behind this method is that the upper and lower AVWAPs may act as dynamic support and resistance levels, effectively creating a price range or channel. As price moves between these two VWAP levels, it becomes squeezed or consolidated within that range. Further conjecture is that the longer the price remains within the range of the two anchored VWAP values, the higher the potential for an explosive breakout. Traders using this strategy may interpret the prolonged consolidation as a period of price compression, with the expectation that a significant move in either direction is likely to occur. Traders employing the AVWAP Pinch strategy might look for specific chart patterns or additional confirmation signals to enter a trade. For example, a breakout above the upper anchored VWAP level could trigger a long trade, while a breakdown below the lower anchored VWAP level could signal a short trade. Stop-loss orders and profit targets are typically set based on the trader's risk tolerance and the volatility of the asset. The third AVWAP (Handoff) is typically set after price has broken through the Pinch, and is used as a new level of support or resistance. The "Pinch & Handoff" phrase is believed to have been coined by Brian Shannon, who has popularized this method.
• The Intervals section (shown above on chart) is comprised of six periodic AVWAPs which cyclically reset. Their default settings are 1 Day, 2 Days, 1 Week, 1 Month, 1 Quarter, and 1 Year. They each may be set to desired period and when they are enabled the VWAPs whose periods are lower than the current chart timeframe are automatically hidden. For example a 1 Day AVWAP is not useful on a 1 Week chart so it would be hidden from that timeframe. When using AVWAPs from higher timeframes it may be helpful to set your chart to "Scale price chart only". This can be enabled by right clicking on your chart's price column and then left clicking "Scale price chart only" to enable that option.
• The Auto section (shown above on chart) is comprised of two automatic Anchored VWAPs. There are choices for setting anchors automatically based upon Highest Source, Highest Volume, Lowest Source, Lowest Volume, Pivot High, and Pivot Low. Because these two VWAPs work retroactively they are drawn with lines instead of plots. There is currently a limitation of 500 lines that may be drawn at any given time and the logic within this indicator uses a line for every bar of VWAP that is drawn, so if the combined length of both of these VWAPs exceeds 500 bars the earliest lines would disappear. For typical use of looking for the highest high in the last 50 bars or the last fractal this limitation should not be an issue.
---
All of the plots have been titled including hidden plots that are generated for the AVWAP line drawings. All of the various types of AVWAP within the indicator should be available as choices within the Alert creation dialog if use of alerts is desired.
---
NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
Weighted Momentum and Volatility Indicator (WMI)The Weighted Momentum and Volatility Indicator (WMI) is a composite technical analysis tool that combines momentum and volatility to identify potential trend changes in the underlying asset.
The WMI is displayed as an histogram that oscillates around a zero line, with increasing bars indicating a bullish trend and decreasing bars indicating a bearish trend.
The WMI is calculated by combining the Rate of Change (ROC) and Average True Range (ATR) indicators.
The ROC measures the percentage change in price over a set period of time, while the ATR measures the volatility of the asset over the same period.
The WMI is calculated by multiplying the normalized values of the ROC and ATR indicators, with the normalization process being used to adjust the values to a scale between 0 and 1.
Traders and investors can use the WMI to identify potential trend changes in the underlying asset, with increasing bars indicating a bullish trend and decreasing bars indicating a bearish trend.
The WMI can be used in conjunction with other technical analysis tools to develop a comprehensive trading strategy.
Do not hesitate to let me know your comments if you see any improvements to be made :)
Weighted Bollinger Band (+ Logarithmic)ENG)
Weighted BB is more responsive to price changes than original Bollinger Bands.
the calculation formula uses a weighted method based on the current price.
Instead of using a standard deviation, I used a weighted standard deviation that weights the current price, and instead of a simple moving average, I used a weighted moving average.
Also included is a formula to log the Bollinger Bands for users who view charts on a logarithmic scale.
KOR)
원본 볼밴보다 가격변화에 대한 반응성이 높습니다.
계산식에는 현재가격에 가중을 주는 방식을 사용하였습니다.
표준편차를 사용하는 대신 저는 현재가격에 가중을 두는 가중표준편차를 사용하였고, 단순이동평균 대신 가중이동평균을 사용하였습니다.
또한 로그스케일로 차트를 보는 유저를 위해 볼린저밴드를 log화 하는 수식도 포함하였습니다.
Anchored VWAP BandSimple script to anchor vwap to a drag and drop spot on the chart and display it as a band instead of a line.
the AVAP Band displays:
1. The AVWAP using High as the source
2. The AVWAP using OHLC4 as the source
3. The AVWAP using Low as the source
This is just a different way of visualising VWAP from an anchored point in time (Band vs Line)
Tunable SWMADissected the standard SWMA function and added options for user to change just about every part of it. Weights ,Lookback ,Source can all be changed in the settings.
Green is the standard SWMA, Using the Input value selected.(MAs/LRC/VWAP)
Red is the tuned SWMA, with the option of applying a final Output filter (MAs/LRC/VWAP). Uses 8 datapoints instead of 4 for the default.
Customization can really help expand upon the standard SWMA I find. Enjoy tuning to your hearts content
Weighted percentile nearest rankYo, posting it for the whole internet, took the whole day to find / to design the actual working solution for weighted percentile 'nearest rank' algorithm, almost no reliable info online and a lot of library-style/textbook-style solutions that don't provide on real world production level.
The principle:
0) initial data
data = 22, 33, 11, 44, 55
weights = 5 , 3 , 2 , 1 , 4
array(s) size = 5
1) sort data array, apply the sorting pattern to the weights array, resulting:
data = 11, 22, 33, 44, 55
weights = 2 , 5 , 3 , 1 , 4
2) get weights cumsum and sum:
weights = 2, 5, 3 , 1 , 4
weights_cum = 2, 7, 10, 11, 15
weights_sum = 15
3) say we wanna find 50th percentile, get a threshold value:
n = 50
thres = weights_sum / 100 * n
7.5 = 15 / 100 * 50
4) iterate through weights_cum until you find a value that >= the threshold:
for i = 0 to size - 1
2 >= 7.5 ? nah
7 >= 7.5 ? nah
10 >= 7.5 ? aye
5) take the iteration index that resulted "aye", and find the data value with the same index, that's gonna be the resulting percentile.
i = 2
data = 33
This one is not an approximation, not an estimator, it's the actual weighted percentile nearest rank as it is.
I tested the thing extensively and it works perfectly.
For the skeptics, check lines 40, 41, 69 in the code, you can comment/uncomment dem to switch for unit (1) weights, resulting in the usual non-weighted percentile nearest rank that ideally matches the TV's built-in function.
Shoutout for @wallneradam for the sorting function mane
...
Live Long and Prosper
Volume Weighted Exponential Moving AverageThis is a volume weighted exponential moving average. uses exponential weighting and considers volume in the consideration of the average price. This makes for a more accurate "average" than a standard moving average.
VWAP With EMA Overlay (Adjustable Anchor)For those who want the classic Volume Weighted Average Price and Ema on the same overlay.
This script utilizes the same protocols as the VWAP and EMA you currently use. Just frees up an indicator space.
KEEP UP TO DATE
Are you a college student or graduate?
Join College Town Trade discord for helpful community specializing in trading stocks, options, and crypto.
Our staff consists of a group of college students with 10+ years of combined experience. Collectively we have profited and made well above an average yearly salary while being in college. The community aspect is everything and the team always listens and appreciates feedback. We all earn and learn together. There are free trials in place in order for you to see what it’s all about. These are in place so we can gain your trust and show transparency!
I look forward to seeing you in the community
advBtBjDhk
Vix FIX / Stochastic Weights StrategyThis script is based off of Chris Moody's Vix Fix Indicator modified by OskarGallard and BigBitsIO's Stochastic Weights.
This script is a compilation of several different stochastic indicators (and RSI ) where the K value of each indicator is equally weighted. The purpose of the indicator is to combine many indicators together in a fashion that weights them easier. By default, the Stochastic and Stochastic RSI are both enabled - the idea is to speed up the relatively slower Stochastic and to slow down the relatively fast Stochastic RSI . BigBitsIO's Stochastics are also available that can also be added to the weighted calculation. Only the K value is weighted, as the D value is just a moving average of the weighted K.
- Why is this modifed stochastic useful?
- To weight multiple indicators together so that you can attempt to find optimal values shared amongst the indicators. Ex: If Stochastic RSI is 100 and Stochastic is 50, K would be 75 and not particularly high. If you add in a 50 RSI , the K would be 67 in this example. If we weight indicators together that all have a high value they could potentially help find elements that align together to produce a stronger signal.
In this script we have the red "S" triangles which are Exits (overbought stochastic crosses).
Added alerts for stochastic exit signals. Alerts are Pre-Set to only Alert on Bar Close.
The "Williams Vix Fix" is one of the most reliable indicators in history for finding market bottoms. The Vix Fix is simply a code from Larry Williams creating almost identical results for creating the same ability the Vix has to all assets.
The VIX has always been much better at signaling bottoms than tops. Simple reason is when market falls retail traders panic and increase volatility , and professionals come in and capitalize on the situation. At market tops there is no one panicking... just liquidity drying up.
The FE green triangles are "Filtered Entries".
The AE green triangles are "Aggressive Filtered Entries".
Added Alerts to Williams Vix Fix (Aggressive Entry and Filtered Entry). Alerts are Pre-Set to only Alert on Bar Close.
Added "Ehlrers StochCCI" indicator of user @glaz
The Ehlrers StochCCI is a variation of Ehlers Stochastic RSI replaced with CCI.
The John Ehlers' article in August, 2006, "Modeling The Market = Building Trading Strategies," describes a process for extracting trend and cyclic elements from market data, then recombining them for trading purposes. He used the Stochastic RSI denoted the cyclic elements.
Added ability to show Dots when StochCCI Crosses.
Sell: fuchsia dots.
Buy: green dots.
Added alerts for (Buy / Sell) StochCCI. Alerts are Pre-Set to only Alert on Bar Close.
DISCLAIMER: For educational and entertainment purposes only. Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security or investment including all types of crypto. DYOR, TYOB.
HLC True Strength Indicator (with Vix)HLC True Strength Indicator Volume Weighted with Vix Line by SpreadEagle71
This indicator is a True Strength Indicator with Close, High and Low used together, along with the TSI of the Vix.
The white line is the close. The red line is the lows and the blue is the highs. These are also volume-weighted.
How to Interpret:
1. zero line crosses. If SPY/SPX500 crosses the zero line, then its bullish. If the purple Vix line crosses up, watch out because this is bearish.
2. white/blue/red lines cross purple (Vix). If they cross upwards, this is bullish. If downward, this is bearish. Basically, SPX, ES1!, SPY or even DIA can be used. The security and the Vix should travel in opposite directions and cross the zero-line at the same time. But this is not always the case.
3. Black area infills. These are used between the close and the highs (blue) and the lows(red). Close should not be between these in order to have momentum.
4. Close (white line) leads. Close is the last price so it tends to show where the others (highs and lows) are going. If the close is sagging below a high where the blue lines are on top, this could mean that there is a reversal coming. Same holds true for a white line above a "valley" formed by the blue and red lines; it could mean a reversal to the upside soon.
5. The Black Infill areas as a squeeze or contraction/expansion area. The thinner the black infill areas, the more of a momentum "squeeze" could be present. Wide black infill areas mean increased volatility and what may come next is a reversion to the mean for volatility. See TTM Squeeze Indicator or the Squeeze Momentum Indicator (kudos LazyBear).
Lastly, just remember indicators indicate; they are not magic. :)
SpreadEagle71
Relative slopeRelative slope metric
Description:
I was in need to create a simple, naive and elegant metric that was able to tell how strong is the trend in a given rolling window. While abstaining from using more complicated and arguably more precise approaches, I’ve decided to use Linearly Weighted Linear Regression slope for this goal. Outright values are useful, but the problem was that I wasn’t able to use it in comparative analysis, i.e between different assets & different resolutions & different window sizes, because obviously the outputs are scale-variant.
Here is the asset-agnostic, resolution-agnostic and window size agnostic version of the metric.
I made it asset agnostic & resolution agnostic by including spread information to the formula. In our case it's weighted stdev over differenced data (otherwise we contaminate the spread with the trend info). And I made it window size agnostic by adding a non-linear relation of length to the output, so finally it will be aprox in (-1, 1) interval, by taking square root of length, nothing fancy. All these / 2 and * 2 in unexpected places all around the formula help us to return the data to it’s natural scale while keeping the transformations in place.
Peace TV
Weighted Standard Deviation BandsLinearly weighted standard deviations over linearly weighted mean.
The rationale of the study can be deduced from my latest publications where I go deeper into explaining the benefits of linear weighting, but in short, I can remind that by using linear weighting we are able to increase the information gain by communicating the sequential nature of time series to the calculations via linear weighting.
Note, that multiplier parameters can take both negative and positive values resulting in ability to have, for example, 1st and 6th weighted standard deviations higher than the weighted mean.
Despite the modification of the classic standard deviation formula, I assume that mathematical qualities of standard deviation will hold due to the fact we can alternately weight the window itself, and then apply the classic standard deviation over the weighted window. In both cases, the results will be the same.
Aight that was too formal, but your short strangles should be happy
Here is it, for you
StrengthA mathematically elegant, native & modern way how to measure velocity/ strength/ momentum. As you can see it looks like MACD, but !suddenly! has N times shorter code (disregard the functions), and only 1 parameter instead of 3. OMG HOW DID HE DO IT?!?
MACD: "Let's take one filter (1 parameter), than another filter (2 parameters), then let's take dem difference, then let's place another filter over the difference (3rd parameter + introduction of a nested calculation), and let's write a whole book about it, make thousands of multi-hours YouTube videos about it, and let's never mention about the amount of uncertainty being introduced by multiple parameters & introduction of the nested calculation."
Strength: "let's get real, let's drop a weighted linear regression & usual linear regression over the data of the same length, take dem slopes, then make the difference over these slopes, all good. And then share it with people w/o putting an ® sign".
Fyi, regressions were introduced centuries ago, maybe decades idk, the point is long time ago, and computational power enough to calculate what I'm saying is slightly more than required for macd.
Rationale.
Linearly weighted linear regression has steeper slope (W) than the usual linear regression slope (S) due to the fact that the recent datapoints got more weight. This alone is enough of a metric to measure velocity. But still I've recalled macd and decided to make smth like it cuz I knew it'll might make you happy. I realized that S can be used instead of smoothing the W, thus eliminating the nested calculation and keeping entropy & info loss in place. And see, what we get is natural, simple, makes sense and brings flex. I also wanna remind you that by applying regression we maximize the info gain by using all the data in the window, instead of taking difference between the first and the last datapoints.
This script is dedicated to my friend Fabien. Man, you were the light in the darkness in that company. You'll get your alien green Lambo if you'll really want it, no doubts on my side bout that.
Good hunting
