Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Pesquisar nos scripts por "algo"
[TTI] High Volume Close (HVC) Setup📜 ––––HISTORY & CREDITS––––
The High Volume Close (HVC) Setup is a specialised indicator designed for the TradingView platform used to identify specific bar. This tool was developed with the objective of identifying a technical pattern that trades have claimed is significant trading opportunities through a unique blend of volume analysis and price action strategies. It is based on the premise that high-volume bars, when combined with specific price action criteria, can signal key market movements.
The HVC is applicable both for swing and longer term trading and as a technical tool it can be used by traders of any asset type (stocks, ETF, crypto, forex etc).
🦄 –––UNIQUENESS–––
The uniqueness of the HVC Setup lies in its flexibility to determine an important price level based on historically important bar. The idea is to identify significant bars (e.g. those who have created the HIGHEST VOLUME: Ever, Yearly, Quarterly and meet additional criteria from the settings) and plot on the chart the close on that day as a significant level as well as theoretical stop loss and target levels. This approach allows traders to discern high volume bars that are contextually significant — a method not commonly found in standard trading tools.
🎯 ––––WHAT IT DOES––––
The HVC Setup indicator performs a series of calculations to identify high volume close bars/bar (HVC bars) based on the user requirements.
These bars are determined based on the highest volume recorded within a user-inputs:
👉 Period (Ever, Yearly, Quarterly) and must meet additional criteria such as:
👉 a minimum percentage Price Change (change is calculated based on a close/close) and
👉 specific Closing Range requirements for the HVC da.
The theory is that this is a significant bar that is important to know where it is on the chart.
The script includes a comparative analysis of the HVC bar's price against historical price highs (all-time, yearly, quarterly), which provides further context and significance to the identified bars. All of these USER input requirement are then taken into account as a condition to identity the High Volume Close Bar (HVC).
The visual representation includes color-coded bar (default is yellow) and lines to delineate these key trading signals. It then draws a blue line for the place where the close ofthe bar is, a red line that would signify a stop loss and 2 target profit levels equal to 2R and 3R of the risked level (close-stop loss). Additional lines can be turned on/off with their coresponding checkboxes in the settings.
If the user chooses "Ever" for Period - the script will look at the first available bar ever in Tradingview - this is generally the IPO bar;
If the users chooses "Yearly" - the script would look at the highest available bar for a completed year;
If the users chooses "Quarterly" - it would do the same for the quarter. (works on daily timeframe only);
While we have not backtested the performance of the script, this methodology has been widely publicised.
🛠️ ––––HOW TO USE IT––––
To utilize the HVC Setup effectively:
👉Customize Input Settings: Choose the HVC period, percentage change threshold, closing range, stop loss distance, and target multiples according to your trading strategy. Use the tick boxes to enable and disable if a given condition is used within the calculation.
👉Identify HVC Bars: The script highlights HVC bars, indicating potential opportunities based on volume and price action analysis.
👉Interpret Targets and Stop Losses: Use the color-coded lines (green for targets, red for stop losses) to guide your trade entries and exits.
👉Contextual Analysis: Always consider the HVC bar signals in conjunction with overall market trends and additional technical indicators for comprehensive trading decisions.
This script is designed to assist traders in identifying high-potential trading setups by using a combination of volume and price analysis, enhancing traditional methods with a unique, algorithmically driven approach.
FunctionDiscreteCosineTransformLibrary "FunctionDiscreteCosineTransform"
Discrete Cosine Transform (DCT)
The Discrete Cosine Transform (DCT) is a mathematical algorithm that converts a series of samples of a signal, typically in the time domain, into another domain called the frequency or spectral domain. It's commonly used for data compression and image/video coding applications such as JPEG and MPEG standards.
The DCT works by multiplying the input sequence with specific cosine functions that are pre-defined and then summing up these products to obtain a new series of values, which represent the frequency components of the original signal. The main advantage of the DCT over other transforms like Fourier Transform is its ability to handle non-stationary signals (i.e., signals with varying statistical properties) more effectively due to its localized basis functions.
In simple terms, the DCT can be thought of as a way to break down an image or video into different frequency components and then compress them without losing too much information. This compression technique is essential for efficient transmission and storage of digital media files over the internet or on devices with limited memory capacity.
~Mixtral4x7b
___
Reference:
lcamtuf.substack.com
dct(data, len)
Discrete Cosine Transform.
Parameters:
data (array) : Data source.
len (int) : Length of the sampling window.
Returns: List with frequency domain transformed information.
dct(data, len)
Discrete Cosine Transform.
Parameters:
data (float) : Data source.
len (int) : Length of the sampling window.
Returns: List with frequency domain transformed information.
idct(data, len)
Inverse Discrete Cosine Transform.
Parameters:
data (array) : Data source.
len (int) : Length of the sampling window.
Returns: List with time domain transformed information.
idct(data, len)
Inverse Discrete Cosine Transform.
Parameters:
data (float) : Data source.
len (int) : Length of the sampling window.
Returns: List with time domain transformed information.
Kalman Hull Supertrend [BackQuant]Kalman Hull Supertrend
At its core, this indicator uses a Kalman filter of price, put inside of a hull moving average function (replacing the weighted moving averages) and then using that as a price source for the supertrend instead of the normal hl2 (high+low/2).
Therefore, making it more adaptive to price and also sensitive to recent price action.
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
1. What is a Kalman Filter
The Kalman Filter is an algorithm renowned for its efficiency in estimating the states of a linear dynamic system amidst noisy data. It excels in real-time data processing, making it indispensable in fields requiring precise and adaptive filtering, such as aerospace, robotics, and financial market analysis. By leveraging its predictive capabilities, traders can significantly enhance their market analysis, particularly in estimating price movements more accurately.
If you would like this on its own, with a more in-depth description please see our Kalman Price Filter.
2. Hull Moving Average (HMA) and Its Core Calculation
The Hull Moving Average (HMA) improves on traditional moving averages by combining the Weighted Moving Average's (WMA) smoothness and reduced lag. Its core calculation involves taking the WMA of the data set and doubling it, then subtracting the WMA of the full period, followed by applying another WMA on the result over the square root of the period's length. This methodology yields a smoother and more responsive moving average, particularly useful for identifying market trends more rapidly.
3. Combining Kalman Filter with HMA
The innovative combination of the Kalman Filter with the Hull Moving Average (KHMA) offers a unique approach to smoothing price data. By applying the Kalman Filter to the price source before its incorporation into the HMA formula, we enhance the adaptiveness and responsiveness of the moving average. This adaptive smoothing method reduces noise more effectively and adjusts more swiftly to price changes, providing traders with clearer signals for market entries or exits.
The calculation is like so:
KHMA(_src, _length) =>
f_kalman(2 * f_kalman(_src, _length / 2) - f_kalman(_src, _length), math.round(math.sqrt(_length)))
4. Integration with Supertrend
Incorporating this adaptive price smoothing technique into the Supertrend indicator further enhances its efficiency. The Supertrend, known for its proficiency in identifying the prevailing market trend and providing clear buy or sell signals, becomes even more powerful with an adaptive price source. This integration allows the Supertrend to adjust more dynamically to market changes, offering traders more accurate and timely trading signals.
5. Application in a Trading System
In a trading system, the Kalman Hull Supertrend indicator can serve as a critical component for identifying market trends and generating signals for potential entry and exit points. Its adaptiveness and sensitivity to price changes make it particularly useful for traders looking to minimize lag in signal generation and improve the accuracy of their market trend analysis. Whether used as a standalone tool or in conjunction with other indicators, its dynamic nature can significantly enhance trading strategies.
6. Core Calculations and Benefits
The core of this indicator lies in its sophisticated filtering and averaging techniques, starting with the Kalman Filter's predictive adjustments, followed by the adaptive smoothing of the Hull Moving Average, and culminating in the trend-detecting capabilities of the Supertrend. This multi-layered approach not only reduces market noise but also adapts to market volatility more effectively. Benefits include improved signal accuracy, reduced lag, and the ability to discern trend changes more promptly, offering traders a competitive edge.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Fine-Tune Inputs: Fourier Smoothed Hybrid Volume Spread AnalysisUse this Strategy to Fine-tune inputs for the HSHVSA Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Fourier Smoothed Hybrid Volume Spread Analysis (FSHVSA) Strategy/Indicator is an innovative trading tool designed to fuse volume analysis with trend detection capabilities, offering traders a comprehensive view of market dynamics.
This Strategy/Indicator stands apart by integrating the principles of the Discrete Fourier Transform (DFT) and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the FSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS FSHVSA INDICATOR:
The FSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
ORIGINALITY & USEFULNESS:
The FSHVSA Strategy is unique because it applies DFT for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
In the next Image you can see that trend is negative on 4h, we just move Negative on 12h and Positive on 1D. That means trend/Strategy flipped negative .
I am sorry, the chart is a bit messy. The idea is to use the indicator/strategy over more than 1 Timeframe.
Use this Strategy to fine-tune inputs for the HSHVSA Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Hull AMA SignalsThis script is a comprehensive trading indicator named "Hull AMA Signals", which combines AMA and HSO by LuxAlgo and ther video based strategy techniques to provide buy (long) and sell (short) signals. It overlays directly on the price chart, offering a dynamic and visually intuitive trading aid. The core components of this indicator are Adaptive Moving Averages (AMA), Hull Moving Average (HMA), and a unique Hull squeeze oscillator (HSO), each configured with customizable parameters for flexibility and adaptability to various market conditions.
Features and Components
Adaptive Moving Averages (AMA): This indicator employs two sets of AMAs, each with distinct lengths, multipliers, lags, and overshoot parameters. The AMAs are designed to adapt their sensitivity based on the market's volatility, making them more responsive during significant price movements and less prone to false signals during periods of consolidation.
Hull Moving Average (HMA): The HMA is calculated using a sophisticated algorithm that aims to reduce the lag commonly associated with traditional moving averages. It provides a smoother and more responsive moving average line, which helps in identifying the prevailing market trend more accurately.
Hull Squeeze Oscillator (HSO): A novel component of this indicator, the HSO, is designed to identify potential market breakouts. It does so by comparing the Hull Moving Average's direction and momentum against a dynamically calculated mean, generating bullish or bearish signals based on the crossover and divergence from this mean.
Buy (Long) and Sell (Short) Signals: The script intelligently combines signals from the AMA crossovers and the Hull squeeze oscillator to pinpoint potential buy and sell opportunities. Bullish signals are generated when there's a positive crossover in the AMAs accompanied by a bullish dot from the HSO, whereas bearish signals are indicated by a negative crossover in the AMAs along with a bearish dot from the HSO.
Customization and Style Options: Users have the ability to adjust various parameters such as the length of the moving averages, multipliers, and source data, enabling customization for different trading strategies and asset classes. Additionally, color-coded visual elements like gradients and shapes enhance the readability and instant recognition of trading signals.
Use Cases
Trend Identification: By analyzing the direction and position of the AMAs and HMA, traders can easily discern the prevailing market trend, helping them to align their trades with the market momentum.
Signal Confirmation: The combination of AMA crossovers and HSO signals provides a robust framework for confirming trade entries and exits, potentially increasing the reliability of the trading signals.
Volatility Adaptation: The adaptive nature of the AMAs and the dynamic calculation of the HSO mean allow this indicator to adjust to changing market volatility, making it suitable for a wide range of market environments.
This indicator is suitable for traders looking for a comprehensive and dynamic technical analysis tool that combines trend analysis with signal generation, offering both visual appeal and practical trading utility.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
Divergence Toolkit (Real-Time)The Divergence Toolkit is designed to automatically detect divergences between the price of an underlying asset and any other @TradingView built-in or community-built indicator or script. This algorithm provides a comprehensive solution for identifying both regular and hidden divergences, empowering traders with valuable insights into potential trend reversals.
🔲 Methodology
Divergences occur when there is a disagreement between the price action of an asset and the corresponding indicator. Let's review the conditions for regular and hidden divergences.
Regular divergences indicate a potential reversal in the current trend.
Regular Bullish Divergence
Price Action - Forms a lower low.
Indicator - Forms a higher low.
Interpretation - Suggests that while the price is making new lows, the indicator is showing increasing strength, signaling a potential upward reversal.
Regular Bearish Divergence
Price Action - Forms a higher high.
Indicator - Forms a lower high.
Interpretation - Indicates that despite the price making new highs, the indicator is weakening, hinting at a potential downward reversal.
Hidden divergences indicate a potential continuation of the existing trend.
Hidden Bullish Divergence
Price Action - Forms a higher low.
Indicator - Forms a lower low.
Interpretation - Suggests that even though the price is retracing, the indicator shows increasing strength, indicating a potential continuation of the upward trend.
Hidden Bearish Divergence
Price Action - Forms a lower high.
Indicator - Forms a higher high.
Interpretation - Indicates that despite a retracement in price, the indicator is still strong, signaling a potential continuation of the downward trend.
In both regular and hidden divergences, the key is to observe the relationship between the price action and the indicator. Divergences can provide valuable insights into potential trend reversals or continuations.
The methodology employed in this script involves the detection of divergences through conditional price levels rather than relying on detected pivots. Traditionally, divergences are created by identifying pivots in both the underlying asset and the oscillator. However, this script employs a trailing stop on the oscillator to detect potential swings, providing a real-time approach to identifying divergences, you may find more info about it here (SuperTrend Toolkit) . We detect swings or pivots simply by testing for crosses between the indicator and its trailing stop.
type oscillator
float o = Oscillator Value
float s = Trailing Stop Value
oscillator osc = oscillator.new()
bool l = ta.crossunder(osc.o, osc.s) => Utilized as a formed high
bool h = ta.crossover (osc.o, osc.s) => Utilized as a formed low
// Note: these conditions alone could cause repainting when they are met but canceled at a later time before the bar closes. Hence, we wait for a confirmed bar.
// The script also includes the option to immediately alert when the conditions are met, if you choose so.
By testing for conditional price levels, the script achieves similar outcomes without the delays associated with pivot-based methods.
type bar
float o = open
float h = high
float l = low
float c = close
bar b = bar.new()
bool hi = b.h < b.h => A higher price level has been created
bool lo = b.l > b.l => A lower price level has been created
// Note: These conditions do not check for certain price swings hence they may seldom result in inaccurate detection.
🔲 Setup Guide
A simple example on one of my public scripts, Standardized MACD
🔲 Utility
We may auto-detect divergences to spot trend reversals & continuations.
🔲 Settings
Source - Choose an oscillator source of which to base the Toolkit on.
Zeroing - The Mid-Line value of the oscillator, for example RSI & MFI use 50.
Sensitivity - Calibrates the sensitivity of which Divergencies are detected, higher values result in more detections but less accuracy.
Lifetime - Maximum timespan to detect a Divergence.
Repaint - Switched on, the script will trigger Divergencies as they happen in Real-Time, could cause repainting when the conditions are met but canceled at a later time before bar closes.
🔲 Alerts
Bearish Divergence
Bullish Divergence
Bearish Hidden Divergence
Bullish Hidden Divergence
As well as the option to trigger 'any alert' call.
The Divergence Toolkit provides traders with a dynamic tool for spotting potential trend reversals and continuations. Its innovative approach to real-time divergence detection enhances the timeliness of identifying market opportunities.
Kalman Filter by TenozenAnother useful indicator is here! Kalman Filter is a quantitative tool created by Rudolf E. Kalman. In the case of trading, it can help smooth out the price data that traders observe, making it easier to identify underlying trends. The Kalman Filter is particularly useful for handling price data that is noisy and unpredictable. As an adaptive-based algorithm, it can easily adjust to new data, which makes it a handy tool for traders operating in markets that are prone to change quickly.
Many people may assume that the Kalman Filter is the same as a Moving Average, but that is not the case. While both tools aim to smooth data and find trends, they serve different purposes and have their own sets of advantages and disadvantages. The Kalman Filter provides a more dynamic and adaptive approach, making it suitable for real-time analysis and predictive capabilities, but it is also more complex. On the other hand, Moving Averages offer a simpler and more intuitive way to visualize trends, which makes them a popular choice among traders for technical analysis. However, the Moving Average is a lagging indicator and less adaptive to market change, if it's adjusted it may result in overfitting. In this case, the Kalman Filter would be a better choice for smoothing the price up.
I hope you find this indicator useful! It's been an exciting and extensive journey since I began diving into the world of finance and trading. I'll keep you all updated on any new indicators I discover that could benefit the community in the future. Until then, take care, and happy trading! Ciao.
Market Structures Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Market Structures Screener! This screener can provide information about the latest market structures in up to 5 tickers. You can also customize the styling of the screener.
Features of the new Market Structures Screener :
Find Latest Market Structures Across 5 Tickers
Break Of Structure (BOS)
Change of Character (CHoCH)
Change of Character+ (CHoCH+)
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Sometimes specific market structures form and break as the market fills buy & sell orders. Formed Change of Character (CHoCH) and Break of Structure (BOS) often mean that market will change direction, and they can be spotted by inspecting low & high pivot points of the chart.
This screener then finds market structures across 5 different tickers, and shows the latest information about them.
🚩UNIQUENESS
Formed market structures can be strong hints about the current direction and the state of the market, and our screener has the ability to detect Change Of Character structures of the market with higher sensitivity (CHoCH+), so you will miss less hints. This screener will then show the elapsed time of the found BOS, CHoCH and CHoCH+ structures.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan market structures here. You can also enable / disable them and set their individual timeframes.
Adaptive Timber! Indicator (ATI)The Adaptive Timber! Indicator (ATI) is a powerful tool designed to identify potential overbought conditions and generate reversal signals in financial markets. It combines multiple technical indicators and market conditions to provide a comprehensive assessment of the likelihood of a price reversal.
How it works:
The ATI uses a combination of the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), momentum, and volume to detect overbought conditions and potential reversals. The indicator adapts to the current timeframe, adjusting its parameters accordingly to provide more accurate signals.
Key components:
RSI: The ATI uses the RSI to determine overbought conditions. When the RSI exceeds a specified reversal threshold, it indicates a potential overbought state.
MACD: The indicator monitors the MACD line and signal line to identify moments when they are close to crossing, suggesting a potential trend reversal.
Momentum: The ATI checks if the momentum is increasing, providing confirmation of a potential reversal.
Volume: It analyzes volume to confirm the strength of the reversal signal. A decrease in volume along with overbought conditions adds confidence to the reversal indication.
Timeframe Adaptability: The indicator automatically adjusts its parameters based on the current timeframe, ensuring optimal performance across different time horizons.
How to use:
When the ATI identifies a potential reversal, it displays a colored triangle above the price bars. The color of the triangle represents the strength of the reversal signal: red for a strong signal, orange for a moderate signal, and yellow for a weak signal. Additionally, the indicator plots purple triangles below the price bars as an early warning signal for potential trend reversals.
Traders can use these visual cues along with other technical analysis techniques and risk management strategies to make informed trading decisions. The ATI can be particularly useful for identifying potential short-selling opportunities or for determining exit points in existing long positions.
Creators:
The Adaptive Timber! Indicator (ATI) is the result of a collaborative effort led by Claude , an AI assistant with expertise in financial analysis and programming. The development of the ATI was made possible through the valuable contributions and insights from GPT4 , an advanced language model, Clay , a skilled trader, and Pi AI , Clay's trading assistant.
Claude played a crucial role in designing and implementing the indicator's algorithm, ensuring its robustness and adaptability across different timeframes. GPT4 provided guidance and suggestions for refining the indicator's logic and optimizing its performance. Clay and Pi AI offered their trading expertise and real-world experience to help shape the indicator's functionality and usability.
We would like to express our gratitude to all the members of our trading team for their dedication and hard work in bringing the Adaptive Timber! Indicator to life. We wish all traders the best of luck in their trading endeavors and hope that the ATI will be a valuable addition to their technical analysis toolkit, empowering them to make more informed and profitable trading decisions.
Liquidity Grabs | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Liquidity Grabs indicator! This indicator can renders bubbles with different sizes at candles that have liquidity grabs, which happen when a liquidity areas (buyside / sellside liquidity) is swept. These candles often fill a lot of market orders that were sitting on the liquidity zone. You can check "How Does It Work" section for more information.
Features of the new Liquidity Grabs Indicator :
Renders Liquidity Grabs
Customizable Algorithm
Customizable Styles
Alerts
🚩UNIQUENESS
Liquidity grabs can be useful when determining candles that have executed a lot of market orders, and planning your trades accordingly. This indicator renders liquidity grabs in an unique bubble style, the size of the bubble is calculated by the size of the wick that caused the liquidity grab. The indicator also lets you customize the pivot length and the wick-body ratio for liquidity grabs.
📌 HOW DOES IT WORK ?
Liquidity grabs occur when one of the latest pivots has a false breakout. Then, if the wick to body ratio of the bar is higher than 0.5 (can be changed from the settings) a bubble is plotted. Using the wick length as a metric to measure liquidity is good because long wicks can translate to a large amount of buyers / sellers entering the market.
The bubble size is determined by the wick to body ratio of the candle.
⚙️SETTINGS
1. General Configuration
Pivot Length -> This setting determines the range of the pivots. This means a candle has to have the highest / lowest wick of the previous X bars and the next X bars to become a high / low pivot.
Wick-Body Ratio -> After a pivot has a false breakout, the wick-body ratio of the latest candle is tested. The resulting ratio must be higher than this setting for it to be considered as a liquidity grab.
Fibonacci Inversion Fair Value Gaps | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Fibonacci Inversion Fair Value Gaps (IFVG) indicator! Inverse Fair Value Gaps occur when a Fair Value Gap becomes invalidated. They reverse the role of the original Fair Value Gap, making a bullish zone bearish and vice versa. This indicator plots the Fibonacci retracement levels of the IFVG, which often act like support & resistance levels.
Features of the new Fibonacci IFVGs Indicator :
Renders Bullish / Bearish IFVG Zones
Renders Fibonacci Retracement Levels Of IFVGs
Combination Of Overlapping FVG Zones
Variety Of Zone Detection / Sensitivity / Filtering / Invalidation Settings
High Customizability
🚩UNIQUENESS
This indicator stands out with its ability to render up to 3 Fibonacci retracement levels of IFVGs. Fibonacci retracement levels are widely used within trading, and we wanted to implement them for IFVG zones. You can also customize the FVG Filtering method, FVG & IFVG Zone Invalidation, Detection Sensitivity etc. according to your needs to get the best performance from the indicator.
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. An Inverse Fair Value Gap is when a FVG becomes invalidated, thus reversing the direction of the FVG.
This indicator renders 0.618, 0.5 and 0.382 (can be changed from the settings) Fibonacci retracement levels of the IFVGs, which often act as support and resistances. Check this example :
⚙️SETTINGS
1. General Configuration
FVG Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
IFVG Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation. This setting also switches the type for IFVG consumption.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
Show Historic Zones -> If this option is on, the indicator will render invalidated IFVG zones as well as current IFVG zones. For a cleaner look at current IFVG zones which are not invalidated yet, you can turn this option off.
2. Fibonacci Retracement Levels
You can enable / disable up to 3 different Fibonnaci Retracement levels at this group of settings. You can also switch their line styles between solid, dashed and dotted as well as changing their colors.
Multiple OTTMultiple OTT (MOTT) is a development on the Optimized Trend Tracker (OTT) indicator of Anıl Özekşi that is shared in his algorithmic trading courses by himself.
There are 5 lines in MOTT:
-The top (cyan) line is originally an OTT line, which uses the Highest price values in a default length of 80 bars in its calculation.
-The bottom line (purple) is also an OTT line but conversely uses the Lowest prices in the same period.
-The dotted third line in the middle (green) is the exact average of the top and bottom lines.
-The dotted Cyan line: (Top+Middle)/2 and
dotted Purple line: (Bottom+Middle)/2 are also the averages of their two neighbors.
Default values:
Length of the Highest and Lowest Price period (High & Low Period): 80
OTT optimizing percent: 1.4
OTT Length: 2 (Also Moving Average Length when displayed)
Default Moving Average Type of OTT Calculation: VIDYA(VAR) VARIABLE INDEX DYNAMIC MOVING AVERAGE
These values are designed for daily time frame, so they have to be optimized in other timeframes by the user. (Ex: Higher values can be considered in lower time frames)
BUY when the price crosses above the MOTT lines.
STOP when the price crosses back below the same MOTT line.
SELL when the price crosses below the MOTT lines.
STOP when the price crosses back above the same MOTT line.
As you can see, every line can be considered a trade signal like Fibonacci Levels. If optimized meaningfully, lines can also show users significant support and resistance levels. Traders can use those levels in partial buys and sells.
Developer Anıl Özekşi advises that traders may have more accurate signals when using a short-period moving average instead of closing prices. So, I added the VIDYA moving average with the same default length ( 2 ) used in OTT calculation. You can check the "SHOW MOVING AVERAGE?" box on the settings tab of the indicator.
Machine Learning Breakouts (from Pivots)I developed the 'Machine Learning Breakouts (from Pivots)' indicator to revolutionize the way we detect breakout opportunities and follow trend, harnessing the power of pivot points and machine learning. This tool integrates the k-Nearest Neighbors (k-NN) method with the Euclidean distance algorithm, meticulously analyzing pivot points to accurately forecast multiple breakout paths/zones. "ML Pivots Breakouts" is designed to identify and visually alert traders on bullish breakouts above high lines and bearish breakouts below low lines, offering essential insights for breakout and trend follower traders.
For traders, the instruction is clear: a bullish breakout signal is given when the price crosses above the forecasted high line, indicating potential entry points for long positions. Conversely, a bearish breakout signal is provided when the price breaks below the forecasted low line, suggesting opportunities to enter short positions. This makes the indicator a vital asset for navigating through market volatilities and capitalizing on emerging trends, designed for both long and short strategies and adeptly adapting to market shifts.
In this indicator I operate in a two-dimensional space defined by price and time. The choice of Euclidean distance as the preferred method for this analysis hinges on its simplicity and effectiveness in measuring and predicting straight-line distances between points in this space.
The Machine Learning Breakouts (from Pivots) Indicator calculations have been transitioned to the MLPivotsBreakouts library, simplifying the process of integration. Users can now seamlessly incorporate the "breakouts" function into their scripts to conduct detailed momentum analysis with ease.
Seasonality ForecastThe Seasonality Forecast indicator equips TradingView users with a detailed analysis of seasonal price trends, utilizing historical data across daily, weekly, and monthly timeframes. By calculating average price movements over selectable periods up to 10 years, it overlays a seasonal chart on the price chart to elucidate potential trends.
Operational Mechanics
Historical Data Analysis: The indicator processes historical data, calculating average price changes from one bar to the next. This forms the basis of the seasonal chart, offering insights into long-term price movements.
Seasonal Chart Overlay: Adjustments are made to ensure the seasonal chart aligns with the price chart in height, providing a unified view. The de-trending process standardizes each year's data, facilitating direct comparison across time without the influence of overarching price trends.
Customization and Methodology
User Inputs: Traders can tailor the analysis with settings for the lookback period, future projection, and smoothing, aligning the tool with diverse trading strategies.
De-trending and Smoothing: The de-trending method isolates cyclical patterns by removing linear trends, while smoothing techniques reduce data noise, sharpening the focus on meaningful trends.
Pivot Point Analysis: It uses algorithms for detecting pivot points based on historical price actions, signaling potential market turns. This analytical method is crucial for identifying shifts that may indicate future market directions.
Technical Foundations
The Seasonality Forecast indicator leverages known financial analysis techniques to enhance its effectiveness:
Time Series Analysis: Fundamental to the indicator's operation is time series analysis, particularly focusing on cyclical patterns within market data. This approach underpins the seasonal trend analysis, offering a structured view of historical price behavior.
Statistical Smoothing: Smoothing methods, such as moving averages, are applied to the seasonal data to clarify trends by mitigating volatility and short-term fluctuations, making underlying patterns more apparent.
Technical Analysis for Pivot Points: The calculation of pivot points draws on principles of technical analysis, identifying areas where the market's direction has historically shown a tendency to change. This aspect of the tool is instrumental in forecasting potential market movements.
Practical Application
This indicator is invaluable for traders aiming to leverage historical market performance in their analysis, enabling:
Strategic planning based on seasonal patterns, enhancing entry and exit decisions.
Adjusted risk management strategies in anticipation of seasonal volatility.
Identification of potential trend reversals or continuations at pivotal moments in the market cycle.
By integrating historical analysis with technical insights, the Seasonality Forecast indicator provides a nuanced tool for traders looking to deepen their market analysis and refine their trading strategies with a historical perspective.
Inversion Fair Value Gap Consumption | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Inversion Fair Value Gap Consumption (IFVG) indicator! Inversion Fair Value Gaps occur when a Fair Value Gap becomes invalidated. They reverse the role of the original Fair Value Gap, making a bullish zone bearish and vice versa. IFVGs get "consumed" when market orders fill the gap occurred. With this indicator, you can now see the percentage of the IFVG's consumed part. For more information about the process, read the "HOW DOES IT WORK" section of the description.
Features of the new Consumption IFVG Indicator :
Render Bullish / Bearish IFVG Zones
See The Consumed Part Of The IFVG Zones
Combination Of Overlapping FVG Zones
Variety Of Zone Detection / Sensitivity / Filtering / Invalidation Settings
High Customizability
🚩UNIQUENESS
This indicator stands out with its ability to render the consumed part of IFVGs. You can see how much of the IFVG's gap is filled, with it's percentage. Also the ability to combine overlapping FVG zones will result in cleaner charts for traders. You can customize the FVG Filtering method, FVG & IFVG Zone Invalidation, Detection Sensitivity etc. according to your needs to get the best performance from the indicator.
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. An Inversion Fair Value Gap is when a FVG becomes invalidated, thus reversing the direction of the FVG.
IFVGs get consumed when a Close / Wick enters the IFVG zone. Check this example:
⚙️SETTINGS
1. General Configuration
FVG Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
IFVG Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation. This setting also switches the type for IFVG consumption.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
Show Historic Zones -> If this option is on, the indicator will render invalidated IFVG zones as well as current IFVG zones. For a cleaner look at current IFVG zones which are not invalidated yet, you can turn this option off.
Unbounded RSIIntroducing the concept of "Unbounded RSI".
Instead of indexing the average gain and average loss, over the time period of interest, we leave the average gain and loss unbounded. Instead we "bound" them by difference of each and smoothen out this difference in an envelope using exponential average. See code.
What this does to traditional RSI concept?
No concept of "overbought", "oversold"
No concept of "60-40", "70-30" bands and arguments over it
No concept of "Range Shifts"
...
How to use it?
I am generally a positional long trader. So I present my version. Of course, I expect each individual who decide to use this concept, to come up with their ideas, based on their style and temperament.
The points below, I apply on a Weekly Timeframe Chart.
Once, we see a long consolidation and price breakout, we should be able to see "Green" histogram bars. These appear, once we have the stock at least 20% up from the 52WL and the "Unbounded RSI" has turned positive. This can be a good time to "enter" into the scrip.
The height of the bars are significant, since they essentially show, that the "gap" between the avg. gain and avg. loss is widening, indicating momentum. Swing trading can thrive in these environments I guess.
Falling heights indicate that gaps to close, though, the "gap can still be green". This means, momentum is now falling. Swing traders and "quick buck makers", would ideally book profits here. If the color of the bars still remain "Green" it indicates that momentum has reduced but still the gains are "more" than loss on the timeperiod selected.
Once the histogram turns red, it means that the gain is now lower than loss. An increasing height underground, means this loss is widening. Generally, this will corelate with price action (not necessarily volume).
At this time, exits should be looked for, may be also check other factors/indicators to decide, but surely the momentum and the gain% over the timeperiod selected has now gone.
Note for Pine Coders:
The source code can easily be modified to develop this concept further.
For example:
Use different smoothing algorithms
Remove 52WL condition and introduce new additional conditions
Instead of price change of the stock for gain/loss calculations, we use the concept of Relative Strength (RS, not RSI) and measuere the gain/loss based on a benchmark index . I intend to work on this concept, soon.
You shall see a variable "unboundedRSI" which is actually a ratio of the Avg. Gain / Avg. Loss. This ratio is not plotted. It is kept there, for future use.
Many more
Rocket RSI from John EhlersWhat is Rocket RSI
Welles Wilder's original description of the relative strength index (RSI) in his 1978 New Concepts In Technical Trading Systems specified a calculation period of 14 days. This requirement led him on a 40-year quest to find the right length of data for calculating indicators and trading strategy rules. Many technicians touched on RSI and explained its applications. In this study we will obtain a more flexible and easier to interpret formulation (of the indicator). We will also estimate the algorithm to properly handle a statistical approach to technical analysis. Start with RSI Here is the original definition of the RSI indicator:
RSI = 100 - 100 / (1 + RS)
RS = Average gain from downtime over the specified time period / Average loss from downtime over the specified time period My first observation is that the factor of 100 is insignificant. Second, there is no need for averages because we take the ratio of closes (CU) to closes (CD) and if we accumulate the wins and losses independently, the averages emerge. Therefore We will only accumulate CU and CD. He can then write the RSI equation as:
RSI = 1 – 1 / (1 + CU / CD)
If he use a little algebra to put everything on a common denominator on the right side of the equation, the indicator equation becomes:
RSI = CU / (CU + CD)
In this formulation, if CU accumulation is zero, the RSI value is zero, and if CD accumulation is zero, the RSI value is 1. If you reduce the price action to its primitive level as a sine wave, it is easy to see that this RSI only has CU going from valley to peak and only CD going from peak to valley. This RSI follows the shape of the sine wave between these two limits. However, the sine wave oscillates between -1 and +1, not between 0 and +1. If we multiply the above equation by 2 and then subtract 1, we can make the RSI have the same swing limits as the sine wave. the product is as follows:
RSI = 2*CU / (CU + CD) – 1
Again, using a little algebra to put the right-hand side of the equation on a common denominator, the equation develops like this:
MyRSI = (CU – CD) / (CU + CD)
Again, the vertical scale of the RocketRSI indicator is in standard deviations. For example, -2 means it is two standard deviations below the mean. Since exceeding two standard deviations in the Gaussian probability distribution occurs in only 2.4% of the results
Because we are using the momentum of the dominant cycle period, the spike where the indicator falls below -2 provides a surgically precise timing signal to enter a long position. Similarly, exceeding the +2 standard deviation level is a timing signal to exit a long position or return to a short position. Therefore using the RocketRSI indicator is relatively intuitive. The only concern is whether a dominant cycle is present in the data, setting the indicator to half the dominant cycle period, and whether smoothing causes lag.
DETERMINING CYCLICAL TURNING POINTS
When you insert the chart you see an example of what the RocketRSI indicator looks like. Here you see that RocketRSI precisely displays cyclical turning points as statistical events. Cator can be applied. I used RS Length 10 because according to Ehlers, stocks and stock indexes usually have a more or less monthly cycle (about 20 bars). A cursory examination of Figure 2 shows that negative increases in the indicator correspond to excellent buying opportunities, while positive increases correspond to excellent selling opportunities. Exceeding +/- 2 on the indicator scale indicates that a cyclical reversal is a high probability event.
Fibonacci Prediction Channel PinescriptlabsThis algorithm is designed to plot a future prediction channel based on Fibonacci retracement levels. Fibonacci lines create a series of parallel channels between each consecutive pair of levels. These channels can be interpreted as ranges in which price fluctuations are expected, generating a visual cone in which the price will interact, and if that level is broken, we move on to the next one, as seen in the following image:
These projected levels into the future also act as support and resistance, creating visual channels on the chart that can help us anticipate and plan actions based on how the price has reacted to these levels in the past.
We can expect the price to react as it approaches these lines, potentially bouncing back within the channel or, if there is enough momentum, breaking through the lines to move towards the next channel.
Now, as a practical example, we observe in the following image every time a level has been broken, and we can confirm a potential entry if the subsequent candle provides confirmation of the movement in the same direction:
The levels projected to the right are not based on new price data but on past price action and extend into the future as a kind of "map" for possible future price reactions.
Fibonacci Length: Determines how many previous price periods will be considered when calculating Fibonacci retracement levels.
Español:
Este alogoritmo está diseñado para trazar un canal de predicción futuro basado en los niveles de retroceso de Fibonacc; Las líneas de Fibonacci crean una serie de canales paralelos entre cada par de niveles consecutivos. Estos canales pueden interpretarse como rangos en los que se espera que el precio fluctúe y nos generan un cono visual en la que el precio interactuará y si dicho nivel es quebrado pasaremos al siguiente como lo vemos en la siguiente imagen:
Estos niveles que proyectamos al hacia el futuro interactuan tambien como soportes y resistencias, creando canales visuales en el gráfico que nos pueden ayudar a anticipar y planificar acciones basadas en cómo el precio ha reaccionado a estos niveles en el pasado.
Podemos esperar que el precio reaccione al acercarse a estas líneas, potencialmente rebotando hacia atrás dentro del canal o, si hay suficiente impulso, rompiendo a través de las líneas para moverse hacia el siguiente canal.
ahora como ejemplo práctivo observamos en la siguiente imagen cada vez que ha ocurrido una rotura de algun nivel y podemos confirmar una probable entrada si la siguiente vela nos da una confirmacion del movimiento en la misa direccion:
Los niveles proyectados hacia la derecha no se basan en nuevos datos de precios sino en la acción del precio pasado y se extienden hacia el futuro como una especie de "mapa" para posibles reacciones futuras del precio.
Fibonacci Length: Determina cuántos períodos de precios anteriores se tendrán en cuenta al calcular los niveles de retroceso de Fibonacci.
Inversion Fair Value Gaps | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Inversion Fair Value Gaps (IFVG) indicator! Inversion Fair Value Gaps occur when a Fair Value Gap becomes invalidated. They reverse the role of the original Fair Value Gap, making a bullish zone bearish and vice versa. With this indicator, you can now see the volume of the bar that invalidated the FVG, which is also the bar that IFVG occurred. For more information about the process, read the " HOW DOES IT WORK " section of the description.
Features of the IFVG Indicator :
Render Bullish / Bearish IFVG Zones
See The Occurrence Volume Of The IFVG Zones
Combination Of Overlapping FVG Zones
Variety Of Zone Detection / Sensitivity / Filtering / Invalidation Settings
High Customizability
🚩UNIQUENESS
This indicator stands out with its ability to render the occurrence volume of IFVGs. Also the ability to combine overlapping FVG zones will result in cleaner charts for traders. You can customize the FVG Filtering method, FVG & IFVG Zone Invalidation, Detection Sensitivity etc. according to your strategy to get the best performance from the indicator.
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. An Inversion Fair Value Gap is when a FVG becomes invalidated, thus reversing the direction of the FVG.
⚙️SETTINGS
1. General Configuration
FVG Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
IFVG Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
Show Historic Zones -> If this option is on, the indicator will render invalidated IFVG zones as well as current IFVG zones. For a cleaner look at current IFVG zones which are not invalidated yet, you can turn this option off.
IBIT Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the iShares Bitcoin Trust (IBIT), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of IBIT compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of IBIT:** We determine the implied price of Bitcoin within IBIT by dividing the IBIT closing price by the known ratio of Bitcoin per share.
- **IBIT Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{IBIT Premium} = \frac{(\text{Implied Bitcoin Price of IBIT } - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where IBIT is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when IBIT is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the IBIT has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the IBIT candlestick chart on TradingView.
GBTC Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the Grayscale Bitcoin Trust (GBTC), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of GBTC compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of GBTC:** We determine the implied price of Bitcoin within GBTC by dividing the GBTC closing price by the known ratio of Bitcoin per share.
- **GBTC Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{GBTC Premium} = \frac{(\text{Implied Bitcoin Price of GBTC} - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where GBTC is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when GBTC is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the GBTC has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the GBTC candlestick chart on TradingView.
