Divergence Detector [TradingFinder] RSI + MACD + AO Oscillator 🔵 Introduction
🟣 Understanding Divergence
As mentioned, divergence occurs in technical analysis when a stock's price behaves contrary to indicators on the price chart. Divergence can signify either a reversal of the stock's trend or a continuation of the previous trend correction.
Divergences can act as reversal patterns or continuation patterns. Moreover, divergences can be utilized to identify potential support and resistance levels.
For instance, when an indicator is trending upwards and positive, but the price is declining and trending downwards, divergence occurs. Divergence in a stock indicates trader indecision in buying and selling and warns traders to reconsider their decisions regarding buying or holding the stock.
Divergence aids analysts in identifying critical price points. In indicator divergences, it serves as a potent signal in the realm of technical analysis.
🟣 Types of Divergence
1.Regular Divergence
o Positive Regular Divergence (RD+)
o Negative Regular Divergence (RD-)
2.Hidden Divergence
o Positive Hidden Divergence (HD+)
o Negative Hidden Divergence (HD-)
3.Time Divergence
Key Note : This indicator is specifically designed to identify "Regular Divergence" only. Therefore, the following explanation pertains to this type of divergence.
🔵 Regular Divergence/Convergence
Regular Divergence(Convergence) occurs due to conflicting behavior between the indicator and the price chart, typically at the end of a trend. Recognizing Regular Divergence suggests an anticipation of a trend reversal or a pattern resembling a reversal.
🟣 Positive Regular Divergence (RD+)
In contrast to negative divergence, positive Regular Divergence occurs at the end of a downtrend and between two price lows. It manifests when the price forms a new low on the price chart, but the indicator fails to recognize it.
Positive Regular Divergence indicates strong buying pressure and weak selling pressure. Following the identification of positive divergence on the chart, one can anticipate a price increase for the examined stock.
🟣 Negative Regular Divergence (RD-)
This type of Regular Divergence emerges between two price highs during an uptrend. A new high is formed on the price chart, but the indicator fails to acknowledge it. This scenario indicates negative Regular Divergence.
The likelihood of a subsequent market downturn is high. Negative divergence signifies strong selling pressure and weak buying pressure, suggesting an unfavorable future for the stock.
🔵 How to use
By utilizing the "Fractal Period" input, you can specify your desired periods for identifying divergences.
Additionally, through the "Divergence Detect Method" feature, you can choose which oscillators (MACD, RSI, or AO) to base divergence identification on.
Divergence in MACD Oscillator :
Divergence in the MACD indicator occurs when the price chart and the MACD line form a noticeable opposing pattern, meaning the price moves contrary to the MACD line. In this scenario, one expects a reversal in price direction.
Divergence in RSI Oscillator :
If divergence occurs during a downtrend on the price chart (two consecutive lows, with the second low being lower) and on the corresponding RSI point (two consecutive lows, with the second low being higher), it signifies positive Regular Divergence and implies a buying signal.
Conversely, if divergence occurs during an uptrend on the price chart (two consecutive highs, with the second high being higher) and on the corresponding RSI point (two consecutive highs, with the second high being lower), it indicates negative Regular Divergence, signaling a selling opportunity.
Divergence in AO Oscillator :
The AO indicator calculates histograms similar to the AO base. It calculates the difference between the simple moving averages of 5 and 34 periods based on the median of each bar. Then, it plots the bars based on the difference.
It then compares the histograms to detect peaks and troughs in the AO histograms and compares the identified peaks and troughs to the price. Whenever divergence is detected, it plots lines and arrows.
🔵 Table
The table contains information on the functional features of this oscillator that you can utilize. Four categories of information are presented in the table: "Exist," "Consecutive," "Divergence Quality," and "Change Phase Indicator."
Exist :
If divergence exists, you'll see "+" in this row.
Consecutive :
Divergences may occur consecutively. If same-type divergences form within short intervals, you can observe the count in this row.
Divergence Quality : Based on the number of consecutive divergences, their quality can be evaluated. If one divergence exists, its quality is considered "Normal." If two divergences exist, the quality is "Good," and if three or more divergences exist, the quality is considered "Strong."
Change Phase Indicator : If a phase change occurs between two oscillation peaks formed based on divergence, this change is identified and displayed in this row.
M-oscillator
TradeTale Reversal Alert 🚀This script explains how RSI Oscillator along with Bollinger Bands & Moving Average can be used to catch "Reversal Points".
What is an Oscillator:-
An oscillator is a technical analysis tool that constructs high and low bands between two extreme values and then builds a trend indicator that fluctuates within these bounds. Traders use the trend indicator to discover short-term overbought or oversold conditions. RSI with MA is used along with minor calculations (maths) in this Oscillator for generating Long and Short signals.
RSI:-
RSI is a momentum oscillator which measures the speed and change of price movements. RSI moves up and down (oscillates) between ZERO and 100. Generally RSI above 70 is considered overbought and below 30 is considered oversold. Some traders may use a setting of 20 and 80 for oversold and overbought conditions respectively. Some traders may use a setting of 10 and 90 for oversold and overbought conditions respectively. However this may reduce the number of signals. 10 to 30 is shown as bullish zone and 70 to 90 is shown as bearish zone in this Oscillator.
Calculation:-
There are three basic components in the RSI - Avg Gain, Avg Loss & RS.
Avg Gain = Average of Upward Price Change
Avg Loss = Average of Downward Price Change
RS = (Avg Gain)/(Avg Loss)
RSI = 100 – (100 / (1 +RS ))
First Calculation:-
RSI calculation is based on default 14 periods.
Average gain and Average loss are simple 14 period averages.
Average Loss equals the sum of the losses divided by 14 for the first calculation.
Average Gain equals the sum of the Gains divided by 14 for the first calculation.
First Average Gain = Sum of Gains over the past 14 periods / 14.
First Average Loss = Sum of Losses over the past 14 periods / 14.
The formula uses a positive value for the average loss.
RS values are smoothed after the first calculation.
Second Calculation:-
Subsequent calculations multiply the prior value by 13, add the most recent value, and divide the total by 14.
Average Gain = / 14.
Average Loss = / 14.
if
Average Loss = 0, RSI = 100 (means there were no losses to measure).
Average Gain = 0, RSI = 0 (means there were no gains to measure).
Moving Average (MA):-
A moving average (MA) is used in technical analysis, used to help smooth out price data by creating a constantly updated average price. A rising moving average indicates that the security is in an uptrend, while a declining moving average indicates a downtrend.
Bollinger Bands (BB):–
It is consists of a Moving Average line and two standard deviation lines that are plotted above and below the moving average line. The moving average periods & standard deviation can be adjust according to the preference. Bollinger Bands help traders to identify the volatility and potential price range of security.
Logic of this indicator:-
RSI is an oscillator that fluctuates between zero and 100 which makes it easy to use for many traders. Its easy to identify extremes because RSI is range-bound.
Bollinger Band Upper and Lower Bands are used to identify Overbought & Oversold points Respectively. Price crossover of these Upper & Lower Bands used to calculate Reversal Points.
BB, RSI and MA calculations along with maths is used to generate signals.
Rocket signal in is Long Signal and also exit Short signal. (Bullish Entry/Exit)
Bear signal is Short Signal and also exit Long signal. (Bearish Entry/Exit)
But remember that RSI works best in range bound market and is less trustworthy in trending markets. (caution)
A new trader need to be cautious because during strong trends in the market/security, RSI may remain in overbought (70 to 90) or oversold (10 to 30) for extended periods.
Also Bollinger Bands here are used to calculate range reversal, So is less trustworthy in trending markets. (caution)
Chart Timeframe:-
This Indicator works on all timeframes.
Traders should set stop loss and take profit levels as per risk reward ratio.
Note:
Don't confuse RSI and relative strength. RSI is changes in the price momentum of a security.
whereas relative strength compares the price performance of two or more securities.
Like other technical indicators, This indicator also is not a holy grail. It can only assist you in building a good strategy. You can only succeed with proper position sizing, risk management and following correct trading Psychology (No overtrade, No greed, No revenge trade etc).
THIS INDICATOR IS FOR EDUCATIONAL PURPOSE AND PAPER TRADING ONLY. YOU MAY PAPER TRADE TO GAIN CONFIDENCE AND BUILD FURTHER ON THESE. PLEASE CONSULT YOUR FINANCIAL ADVISOR BEFORE INVESTING. WE ARE NOT SEBI REGISTERED.
Hope you all like it
happy learning.
Trend: SMA with ATR Bands and EMA [Oxyge]Brief introduction:
Easy to use trend indicator to help find entry positions
How it works:
1, short-term trend judgment: EMA is greatly influenced by short-term trends, so it is very good to use it as a tool for judging short-term trends. At the same time, the filtering function has been added:
Long: green
Short: red
No direction: blue
2, the general trend judgment: the use of 30SMA as the default trend line, while increasing the ATR band to increase the scope of judgment.
How do I use (assuming it is now a period of long market):
1, first look at the 30SMA and ATR band, if the slope is positive (> 45 °), then ready to go long!
2. When price comes to the ATR band, the ATR band is my point of interest
3. Wait for a test of the ATR band: the EMA turns green, which means that the short-term trend is already nice and long.
4. Stop Loss Placement: Stop Loss is placed at the most recent low.
Closing
Enjoy it!
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简单介绍：
简单易用的趋势指标，帮助寻找进场位置
它怎么工作：
1、短期趋势判断：EMA受短期趋势影响很大，因此把它作为判断短期趋势的工具非常好用。同时增加了过滤功能：
多头：绿色
空头：红色
无方向：蓝色
2、大趋势判断：使用30SMA作为默认趋势线，同时增加ATR带增加判断范围。
我是如何使用的（假设是现在是一段多头行情）：
1、先看30SMA和ATR带，如果斜率为正（>45°），那么准备做多
2、当价格来到ATR带时，ATR带是我的感兴趣的点
3、等待一次对于ATR带的测试：EMA变成绿色，代表短期已经是不错的多头趋势
4、止损放置：止损放置在最近的低点
结束
请享受它
Adaptive Schaff Trend Cycle (STC) [AlgoAlpha]Introducing the Adaptive Schaff Trend Cycle by AlgoAlpha: Elevate Your Trading Strategies 🚀
Discover precision and adaptability with the Adaptive Schaff Trend Cycle 🎯, meticulously crafted for traders seeking an edge in the markets. This advanced tool integrates sophisticated algorithms to offer clear insights and real-time analytics 📈.
Key Features:
⚙️Adaptive Signal Processing: Utilizes evolving calculations to adjust to market changes, offering highly responsive signals.
🔍Enhanced MACD Analysis: Innovates on the traditional MACD, providing new insights into market dynamics through an adaptive lens.
🎨Customizable Visual Experience: Features customizable up and down colors for tailored chart analysis.
🔔Real-Time Alerts: Stay informed with instant alerts on indicator changes.
Quick Guide to Using the Adaptive STC Indicator
1. 🔧 Adding the Indicator: Search for "Adaptive Schaff Trend Cycle (STC) " within TradingView's Indicators & Strategies and apply it to your chart. Customize the settings according to your trading style for optimum results.
2.👀 Market Analysis: Monitor the STC and Histogram values closely. The indicator's color gradients provide a visual representation of momentum shifts, helping you to identify trends more clearly.
3. 🚨 Set Alerts: Enable alerts for specific conditions like significant moves up or down, or when the histogram crosses zero. This feature ensures you never miss a potential trading opportunity.
How It Works:
The Adaptive Schaff Trend Cycle by AlgoAlpha introduces a dynamic approach to market analysis, refining traditional indicators through adaptive logic to align with fluctuating market conditions. Here's a concise overview of its operation:
🔄 Adaptive MACD Adjustment: The foundation of the indicator is an enhanced MACD calculation, which dynamically adjusts its parameters based on real-time market trends and momentum. This algorithmic adjustment aims to ensure the MACD's responsiveness to market changes, adapting its sensitivity to offer timely insights .
🌟 Integration of Schaff Trend Cycle (STC): After adjusting the MACD, the indicator calculates STC values to provide a smoothed representation of market trends. By normalizing and smoothing the MACD values on a scale from 0 to 100, the STC method helps in identifying market phases with a clear visualization. The smoothing process is designed to mitigate noise and focus on significant market movements .
📊 Visualization and Alerts: To aid in the interpretation of these insights, the Adaptive Schaff Trend Cycle employs color gradients and customizable visual settings to indicate momentum shifts. These visual cues, combined with alert functionalities, are structured to assist traders in monitoring market developments, enabling them to make informed decisions based on the presented data .
🛠️The Adaptive Schaff Trend Cycle thus merges adaptive MACD adjustments with STC methodology, supported by visual and alert features, to create a tool aimed at enhancing market analysis. By focusing on adaptability and current market conditions, it provides a nuanced view of market trends, intended to support traders in their decision-making processes without promising predictive accuracy or reliability .
LSMA Z-Score [BackQuant]LSMA Z-Score
Main Features and Use in the Trading Strategy
- The indicator normalizes the LSMA into a detrended Z-Score, creating an oscillator with standard deviation levels to indicate trend strength.
- Adaptive coloring highlights the rate of change and potential reversals, with different colors for positive and negative changes above and below the midline.
- Extreme levels with adaptive coloring indicate the probability of a reversion, providing strategic entry or exit points.
- Alert conditions for crossing the midline or significant shifts in trend direction enhance its utility within a trading strategy.
1. What is an LSMA?
The Least Squares Moving Average (LSMA) is a technical indicator that smoothens price data to help identify trends. It uses the least squares regression method to fit a straight line through the selected price points over a specified period. This approach minimizes the sum of the squares of the distances between the line and the price points, providing a more statistically grounded moving average that can adapt more smoothly to price changes.
2. What is a Z-Score?
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values, measured in terms of standard deviations from the mean. If a Z-Score is 0, it indicates that the data point's score is identical to the mean score. A Z-Score helps in understanding if a data point is typical for a given data set or if it is atypical. In finance, a Z-Score is often used to measure how far a piece of data is from the average of a set, which can be helpful in identifying outliers or unusual data points.
3. Why Turning LSMA into a Z-Score is Innovative and Its Benefits
Converting LSMA into a Z-Score is innovative because it combines the trend identification capabilities of the LSMA with the statistical significance testing of Z-Scores. This transformation normalizes the LSMA, creating a detrended oscillator that oscillates around a mean (zero line), with standard deviation levels to show trend strength. This method offers several benefits:
Enhanced Trend Detection:
- By normalizing the LSMA, traders can more easily identify when the price is deviating significantly from its trend, which can signal potential trading opportunities.
Standardization:
- The Z-Score transformation allows for comparisons across different assets or time frames, as the score is standardized.
Objective Measurement of Trend Strength:
- The use of standard deviation levels provides an objective measure of trend strength and volatility.
4. How It Can Be Used in the Context of a Trading System
This indicator can serve as a versatile tool within a trading system for a range of things:
Trend Confirmation:
- A positive Z-Score can confirm an uptrend, while a negative Z-Score can confirm a downtrend, providing traders with signals to enter or exit trades.
Oversold/Overbought Conditions:
- Extreme Z-Score levels can indicate overbought or oversold conditions, suggesting potential reversals or pullbacks.
Volatility Assessment:
- The standard deviation levels can help traders assess market volatility, with wider bands indicating higher volatility.
5. How It Can Be Used for Trend Following
For trend following strategies, this indicator can be particularly useful:
Trend Strength Indicator:
- By monitoring the Z-Score's distance from zero, traders can gauge the strength of the current trend, with larger absolute values indicating stronger trends.
Directional Bias:
- Positive Z-Scores can be used to establish a bullish bias, while negative Z-Scores can establish a bearish bias, guiding trend following entries and exits.
Color-Coding for Trend Changes :
- The adaptive coloring of the indicator based on the rate of change and extreme levels provides visual cues for potential trend reversals or continuations.
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.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
CoT artificial by Oster and Freundl (CoF)Overview:
CoF , short for "CoT artificial by Oster and Freundl", presents a novel approach to market analysis, inspired by the traditional Commitments of Traders (CoT) Index . Based on the artificial CoT calculation according to Freundl and Oster (explained below), this indicator provides traders with a versatile tool applicable across various markets, including individual stocks. Unlike its predecessor, CoF offers flexibility in its application, accommodating traders with different investment horizons, whether they operate on weekly, daily, hourly, or even minute candlesticks. By adjusting the period length in the settings, users can fine-tune the sensitivity of CoF to capture buy or sell signals, albeit with differing signal qualities. Additionally, CoF is equipped with alert functionalities, enhancing its usability for traders seeking timely market insights.
Sophisticated Calculation Methodology:
CoF derives its insights from a sophisticated calculation methodology, leveraging price range and price movement metrics to assess market dynamics. The indicator computes the ratio between the moving averages of price movement and price range over a specified period. This ratio, once normalized and scaled to a 0-100 range , provides traders with a quantifiable measure of market sentiment. Notably, CoF's calculation method, while nuanced, ensures accessibility and usability for traders seeking actionable insights without delving into complex mathematical formulations.
Interpretation:
CoF-Index, represented on the chart, offers traders insights into market sentiment dynamics . Values below the sell threshold indicate potential selling pressure, triggering sell alerts to alert traders to potential downturns. Conversely, values exceeding the buy threshold signal buying opportunities, prompting buy alerts for traders to capitalize on potential market upswings. By aligning these interpretations with the trader's investment strategy, CoF aids in decision-making processes, offering nuanced perspectives on market movements.
Dynamic Color Coding for Visual Clarity:
To enhance user experience and facilitate quick decision-making, CoF incorporates dynamic color coding . Market conditions favoring selling are denoted by red hues, while those conducive to buying are highlighted in green. Neutral conditions, indicative of balanced market sentiment, are represented in neutral colors. This intuitive visual feedback enables traders to swiftly identify market opportunities and risks, empowering them to make informed trading decisions.
Customizable Parameters for Tailored Analysis:
Acknowledging the diverse trading preferences and strategies of its users, CoF offers customizable parameters . Traders can adjust the period length to fine-tune the indicator's sensitivity to their desired level, balancing the frequency and quality of signals according to their trading objectives. Additionally, CoF's alert functionalities allow traders to set personalized thresholds, aligning with their risk tolerance and market outlook.
Conclusion:
In conclusion, CoF emerges as a valuable addition to the trader's toolkit, offering a versatile and accessible approach to market analysis. Built upon a foundation of sophisticated calculation methodologies, CoF provides traders with actionable insights into market sentiment across various timeframes and asset classes . Its intuitive visualizations, coupled with customizable parameters and alert functionalities, empower traders to navigate dynamic market conditions with confidence. Importantly, the CoF index offers traders the flexibility to employ a synthetically calculated method, inspired by the classic CoT-Index, regardless of market or investment horizon . Whether you're a seasoned investor or a novice trader, CoF equips you with the tools needed to stay ahead in today's competitive markets.
Z Score & Trend FollowingIntroduction:
The Z Score & Trend Following indicator is a tool used in financial markets to assess the standard deviation of a data point from its mean value over a specified period. It calculates the Z score, which is a measure of how many standard deviations an element is from the mean. This indicator also incorporates trend-following characteristics, allowing traders to visualize trends based on the Z score.
Indicator Parameters:
Standard Deviation Length: Determines the length of the standard deviation calculation.
Average Length: Specifies the length of the moving average used for the mean calculation.
Calculation Type: Allows users to choose between different types of moving averages (SMA, EMA, WMA, VMA, TMA).
Standard Deviations: Sets the number of standard deviations to be used for trend analysis.
Bar Color: Option to enable or disable bar coloring based on trend conditions.
Calculations:
Z Score Calculation: The Z score is calculated as the difference between the source data point and the moving average divided by the standard deviation.
zscore = (src - (getMA(src, length))) / ta.stdev(src, slength)
Plots:
Z Score Plot: Plots the Z score values, typically in green.
Inverted Z Score Plot: Plots the inverted Z score values (multiplied by -1), typically in red.
Lines:
Zero Line: A horizontal dotted line indicating zero.
Upper Threshold Line: A dotted line representing the upper threshold defined by the number of standard deviations.
Lower Threshold Line: A dotted line representing the lower threshold defined by the negative number of standard deviations.
Bar Color:
The bar color changes based on the Z score values and the predefined standard deviation thresholds. Green bars indicate values above the upper threshold, red bars indicate values below the lower threshold, lime bars indicate positive Z scores, and maroon bars indicate negative Z scores. Neutral values are represented by black bars.
Conclusion:
The Z Score & Trend Following indicator combines the statistical concept of Z score with trend-following characteristics to provide traders with insights into market trends and potential reversal points. By visualizing Z scores alongside trend analysis, traders can make more informed decisions regarding market entry and exit points.
ka66: Externally-Sourced MACDThis indicator generalises the idea of MACD to take any arbitrary series available on the chart, using input.source values .
To provide an overview of the MACD indicator:
You have two EMAs, one with a faster period, usually 12, another with a slower period, usually 26.
You calculate a MACD line, by doing (fastEMA - slowEMA)
You then calculate a Signal Line by taking a moving average of the MACD line over some period.
With this indicator, you can analyse momentum between any 2 series (not just EMAs), they could be raw close prices, other moving averages on the chart including specialised ones, that most MACD implementations won't provide a facility for, for example Kaufman Moving Average.
The chart shows this indicator sourcing 2 inputs from the chart:
A Hull Moving Average as the fast series
And a Simple Moving Average as the slow series
It then calculates the MACD (Series1 - Series2), and a Signal line from the resulting MACD.
A signal series is still calculated manually by the indicator, and thus will be restricted to the provided moving average options (this indicator provides a few like EMA, SMA, Hull, and so on).
Uses of this indicator are essentially what you will use a MACD for:
Evaluate momentum of a strength.
Crossover Signals: MACD vs. Signal, MACD vs. Zero Line, MACD Histogram gradation.
Evaluate overbought/oversold conditions.
As a low-resolution view to confirm price action.
Divergences
FSVZO {DCAquant}The Fourier Smoothed Volume Zone Oscillator (FSVZO) is an innovative technical indicator that leverages complex mathematical models to provide a multifaceted view of market dynamics. Designed as a closed-source script for TradingView, FSVZO employs Fourier analysis and the Augmented Dickey-Fuller (ADF) test to help traders identify and capitalize on potential market trends and reversals.
Key Features:
ADF Test Integration: Employs the statistical power of the ADF test to identify the stationarity within a time series, which can be pivotal for recognizing trend changes.
Advanced Mathematical Operations: Incorporates sophisticated computations like matrix manipulation and QR decomposition to refine the accuracy of market signals.
Fourier Transform Analysis: Utilizes Fourier Transform to distill market movements into a spectral view, revealing underlying cyclical patterns.
Dynamic Trend Visualization: Clearly marks trend shifts on the chart, assisting traders in visualizing and interpreting changes in market momentum.
Color-Coded Signals: Features dynamic color-coding that alerts traders to bullish (aqua) and bearish (fuchsia) market phases based on the oscillator's movement.
Interpretation and Usage:
Overbought/Oversold Conditions: The indicator demarcates overbought and oversold zones, which can signal potential reversals when the FSVZO line crosses these thresholds.
Directional Bias: A cross above or below the zero line indicates potential bullish or bearish trends, respectively, offering clear buy/sell signals.
Multi-Timeframe Analysis: The FSVZO's versatility allows for its application across different timeframes, providing consistent analysis from macro to micro perspectives.
Customization and Flexibility:
Traders can tailor the FSVZO settings to fit their unique trading approach, adjusting parameters like lookback periods and calculation sources for a personalized experience.
How to Use FSVZO {DCAquant} for Market Analysis:
The FSVZO {DCAquant} serves as a multi-dimensional tool that can enhance your trading strategy. Here's how to integrate it into your market analysis for spotting potential trend reversals and other trading signals:
Identify Market Phases:
Bullish Phases: Watch for the FSVZO line to turn aqua and move upward, particularly after being in an oversold region or crossing above the zero line.
Bearish Phases: Look for the FSVZO line to turn fuchsia and trend downward, especially if it descends from an overbought area or drops below the zero threshold.
Spotting Potential Reversals:
From Overbought/Oversold Levels: A reversal may be impending when the FSVZO exits the overbought or oversold regions, suggesting a saturation of the prevailing trend.
Pivot Points: The script marks pivot points with labels ("R" for regular and "H" for hidden divergences). These points, combined with divergence patterns, can signal a strong likelihood of a trend reversal.
Utilizing Divergences:
Regular Divergence: Occurs when the price records a higher high or lower low, but the FSVZO does not, indicating a weakening trend.
Hidden Divergence: When the price makes a lower high or higher low, but the FSVZO suggests continued strength, it could be an opportunity to join a trend continuation.
Confirming Trade Entries:
Enter a trade in the direction indicated by the FSVZO trend shift circles and confirm with additional analysis (e.g., candlestick patterns, support/resistance levels).
Setting Exit Points:
Set take-profit levels near identified pivot points or when the FSVZO line reaches the opposite overbought or oversold level.
Use trailing stops following the FSVZO line to capitalize on prolonged trends and protect against sudden reversals.
Multi-Timeframe Confluence:
Apply the FSVZO on multiple timeframes to find confluence. For instance, a bullish signal on both daily and hourly charts could increase the confidence in a long position.
Remember that the FSVZO {DCAquant} is best used as part of a comprehensive trading system. It is essential to consider volume, price action, and market context when interpreting signals. As with any technical tool, confirm FSVZO signals with other analysis methods to increase the probability of successful trades.
Educational Value:
FSVZO {DCAquant} is a powerful educational tool designed to enhance traders' understanding of the markets. It encourages comprehensive analysis and should be used in conjunction with robust risk management strategies.
Disclaimer:
While FSVZO {DCAquant} is developed to inform trading decisions with advanced data analysis, it does not guarantee accurate prediction of future market movements. Traders are advised to use this tool as part of a diversified strategy and perform due diligence before making trading decisions.
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.
RSI-HeatmapThis unique indicator is a comprehensive tool designed for traders seeking to gain an edge in the market. It consists of three main components: a revised RSI, a dynamic heatmap, and an integrated alert system.
1.Modified RSI:
Unlike the traditional RSI that calculates delta as the difference between the current price and the previous price (Δ = {price} - {previous price}), this version computes delta by comparing the current price with the price n periods ago (Δ = {price} - {n-th previous price}). This delta is then smoothed using a Volume Weighted Moving Average (VWMA) with a short length to preserve the RSI's core characteristics while adapting it to capture longer-term momentum shifts more effectively.
2.Heatmap:
The heatmap feature introduces a novel approach to visualize market conditions, with 5 high levels and 5 low levels identified around the current price. When the price crosses these thresholds, the RSI-based heatmap changes colors, ranging from blue (indicative of oversold conditions) to red (signaling overbought conditions). This visual tool helps traders quickly gauge the strength and potential reversal points in the market.
3.Alert:
The Alert system employs MACD (Moving Average Convergence Divergence) and CCI (Commodity Channel Index) indicators to signal potential buy or sell opportunities. It categorizes alerts into four color-coded recommendations:
Green and Lighter Green: Strong buy signal, suggesting favorable conditions for entering buy positions.
Blue and Lighter Blue: Moderate buy signal, indicating less robust but potentially profitable buy conditions.
Red and Lighter Red: Strong sell signal, advising traders to consider taking sell positions.
Orange and Lighter Orange: Moderate sell signal, hinting at sell conditions that are not as compelling as those indicated by red.
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.
OBV 1min Volume SqueezeIn the vast realm of trading strategies, few terms evoke as much intrigue as the word "squeeze." It conjures images of pent-up energy, ready to burst forth in a sudden and decisive move. In this blog post, we'll delve into a new trading idea titled the "OBV 1-Minute Volume Squeeze" which aims to catch bigger market movements by fetching 1 minute OBV data on higher time charts.
The Essence of Squeeze
In trading parlance, a "squeeze" typically denotes a scenario where volatility contracts, and prices consolidate within a narrow range. Translating this concept to volume dynamics, a "volume squeeze" suggests a period of compressed volume activity. It is unclear if the Bulls or the Bears are at winning hand and price is thus consolidating. The script calculates buying and selling pressure by fetching 1 min data. The total volume presure is the sum of absolute values of the buying and selling pressure added up. By deviding the Buying volume by the total volume we know the Buying Pressure.
The trading theory suggest that when the buying pressure exceeds a certain value eg. 50% (default value in the script is 55%) it is likely the trend will continue to go up for a longer period of time. Vice Versa when selling pressure is higher, the trend is likely to continue down. In the script you can adjust the sensitivity in such way a higher "Volume Pressure %" result in less trading signals.
Fetching 1 min data
The OBV is a wonderful indicator to measure the buying and selling pressure. A disadvantage of the script is that the total volume pressure is presented as a positive (buying) or negative value (selling) value in the Oscillator. It does not offset the Bulls power against the Bears power at given time. The script aims to do measure the directional volume power by defining a volume pressure % (oulier value) by fetching 1 min OBV data on higher time frame charts comparing the Bulls power against the Bears Power. The code is included below:
// Fetch Lower Timeframe Data in an array
// nV = ZeroValue, sV = Selling Volume, bV = Buying Volume, tV = Total Volume
= request.security_lower_tf(syminfo.tickerid, '1', )
sum_bV_Lengthbars = array.sum(bV)
sum_sV_Lengthbars = array.sum(sV)
sum_tV_Lengthbars = sum_bV_Lengthbars + sum_sV_Lengthbars // Combine buying and selling volumes to get total volume
// Calculate buying and selling volume as percentage of the total volume, but ensure the denominator isn't zero.
buying_percentage = sum_tV_Lengthbars != 0 ? sum_bV_Lengthbars / sum_tV_Lengthbars * 100 : na
selling_percentage = sum_tV_Lengthbars != 0 ? -(sum_sV_Lengthbars / sum_tV_Lengthbars * 100) : na
OBV Oscillator Explanation
The On Balance Volume (OBV) indicator is a technical analysis tool used to measure buying and selling pressure in the market. It does this by keeping a running total of volume flows. OBV is typically calculated by adding the volume on a candle when the price closes higher than the previous candle's close and subtracting the volume on candles when the price closes lower than the previous candles close. If the price closes unchanged from the previous candle, the volume is not added to or subtracted from the OBV. The OBV can be presented as an oscillator. Positve value is the buying pressure and negative values is the selling pressure. In the settings the OBV is calculated based on 1 min data and comes with the following input options for visualization on the chart:
Higher Time Frame Settings (make sure the HTF is higher than the chart you have open)
Type of MA being: EMA, DEMA, TEMA, SMA, WMA, HMA, McGinley
Volume Pressure % (outlier value)
Length of number of bars (of the choosen HTF settings)
Smoothing of number candles of hte opened timechart. Note that higher number of bars to smoothen the indicator results in less signals, but lag of the indicator increases.
The Oscilator contains 3 main lines which are used to determin the entry signals:
Orange Line = the Outlier value in settings described as "Volume Pressure %"
Green Line = Total Buying Pressure OBV
Red Line = Total Selling Pressure OBV
If the Green or Red line is in between the zero line and the orange line the volume is squeezed and waiting for a directional break out.
If the Green line crosses over the orange line the buying pressure is > 55% and triggers a long entry position (green dot). If the Red line crosses under the orange line the selling pressure is > 55% and triggers an short entry (red dot). In the strategy settings this option is called: "Wait for total volume to increase?".
Alternative Strategy Options
In order to play around with different settings users can opt for two more strategy entry settings, called:
"Wait for total volume to deacrease?" --> Only gives a signal when total volume is declining, but buying or selling pressure maintains and crosses % threshold.
"Wait for Pull Back?" --> After a pullback occured and opposite buy/sell pressure gets lower than threshold (direction is shifting)
Turning on all options will logically result into more signals. Note these strategy ideas are experimental and can best be used in confirmation with other indicators.
Moving Average Filter (HTF)
The Oscillator has a horizontal line at the bottom. The line is green when the moving average is in a uptrend and red when the moving average is in a downtrend. The MA Filter comes with the following settings:
Higher Time Frame Setting
Type of MA being: EMA, DEMA, TEMA, SMA, WMA, HMA, McGinley
Length of number of bars (of the choosen HTF settings)
At last I hope you like this volume trading idea and if you have any comments let me know!
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
Kalman Filtered RSI Oscillator [BackQuant]Kalman Filtered RSI Oscillator
The Kalman Filtered RSI Oscillator is BackQuants new free indicator designed for traders seeking an advanced, empirical approach to trend detection and momentum analysis. By integrating the robustness of a Kalman filter with the adaptability of the Relative Strength Index (RSI), this tool offers a sophisticated method to capture market dynamics. This indicator is crafted to provide a clearer, more responsive insight into price trends and momentum shifts, enabling traders to make informed decisions in fast-moving markets.
Core Principles
Kalman Filter Dynamics:
At its core, the Kalman Filtered RSI Oscillator leverages the Kalman filter, renowned for its efficiency in predicting the state of linear dynamic systems amidst uncertainties. By applying it to the RSI calculation, the tool adeptly filters out market noise, offering a smoothed price source that forms the basis for more accurate momentum analysis. The inclusion of customizable parameters like process noise, measurement noise, and filter order allows traders to fine-tune the filter’s sensitivity to market changes, making it a versatile tool for various trading environments.
RSI Adaptation:
The RSI is a widely used momentum oscillator that measures the speed and change of price movements. By integrating the RSI with the Kalman filter, the oscillator not only identifies the prevailing trend but also provides a smoothed representation of momentum. This synergy enhances the indicator's ability to signal potential reversals and trend continuations with a higher degree of reliability.
Advanced Smoothing Techniques:
The indicator further offers an optional smoothing feature for the RSI, employing a selection of moving averages (HMA, THMA, EHMA, SMA, EMA, WMA, TEMA, VWMA) for traders seeking to reduce volatility and refine signal clarity. This advanced smoothing mechanism is pivotal for traders looking to mitigate the effects of short-term price fluctuations on the RSI's accuracy.
Empirical Significance:
Empirically, the Kalman Filtered RSI Oscillator stands out for its dynamic adjustment to market conditions. Unlike static indicators, the Kalman filter continuously updates its estimates based on incoming price data, making it inherently more responsive to new market information. This dynamic adaptation, combined with the RSI's momentum analysis, offers a powerful approach to understanding market trends and momentum with a depth not available in traditional indicators.
Trend Identification and Momentum Analysis:
Traders can use the Kalman Filtered RSI Oscillator to identify strong trends and momentum shifts. The color-coded RSI columns provide immediate visual cues on the market's direction and strength, aiding in quick decision-making.
Optimal for Various Market Conditions:
The flexibility in tuning the Kalman filter parameters makes this indicator suitable for a wide range of assets and market conditions, from volatile to stable markets. Traders can adjust the settings based on empirical testing to find the optimal configuration for their trading strategy.
Complementary to Other Analytical Tools:
While powerful on its own, the Kalman Filtered RSI Oscillator is best used in conjunction with other analytical tools and indicators. Combining it with volume analysis, price action patterns, or other trend-following indicators can provide a comprehensive view of the market, allowing for more nuanced and informed trading decisions.
The Kalman Filtered RSI Oscillator is a groundbreaking tool that marries empirical precision with advanced trend analysis techniques. Its innovative use of the Kalman filter to enhance the RSI's performance offers traders an unparalleled ability to navigate the complexities of modern financial markets. Whether you're a novice looking to refine your trading approach or a seasoned professional seeking advanced analytical tools, the Kalman Filtered RSI Oscillator represents a significant step forward in technical analysis capabilities.
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
Fourier Adjusted Volume Zone Oscillator [BackQuant]Fourier Adjusted Volume Zone Oscillator
Welcome to BackQuant's FSVZO, Primarily we decided to combine the Fourier analysis to a leading indicator concept. Since in concept it can be beneficial.
We also decided to add in the momentum velocity indicator as a point of confluence.
Which will be discussed later in how it can be used in a trading system. For now onto the boring stuff, please read all of this and enjoy!
Fourier ? What and Why:
Fourier transforms are a mathematical technique used for transforming signals between time and frequency domains. In the context of financial markets, this allows analysts to deconstruct price movements into constituent sinusoidal waves. By isolating these waves, traders can identify the dominant market cycles and trends hidden within the 'noise' of short-term price fluctuations.
Empirical Evidence and Benefits:
Cycle Identification: Empirical studies have shown that markets exhibit cyclical behaviors due to various economic, geopolitical, and psychological factors. Fourier filtering helps in pinpointing these cycles, even in seemingly random market movements.
Trend Detection: By highlighting dominant frequencies, traders can more accurately determine the prevailing trend direction, aiding in trend-following or contrarian strategies.
Volatility Clarity: Filtering out noise enhances the visibility of true market volatility, crucial for risk management and strategy adjustment.
Why the Volume Zone Oscillator (VZO) and Origins + Advantages:
The VZO was developed by Walid Khalil and David Steckler and introduced in the "Stocks & Commodities" magazine in 2009. It integrates volume with price movements to gauge the flow of buying and selling pressure. Unlike traditional volume indicators that solely quantify trading volume, the VZO interprets volume's impact on price direction, offering insights into the strength or weakness of a price trend.
Empirical Evidence and Benefits:
Market Sentiment: Volume is a key indicator of market sentiment. High volume accompanying price movements indicates strong sentiment, whereas low volume suggests a lack of conviction. The VZO makes this analysis quantifiable.
Overbought/Oversold Conditions: By quantifying where the current volume-weighted price is within its range, the VZO helps identify potential reversals, providing actionable signals for entering or exiting trades.
Trend Confirmation: The VZO's ability to confirm price trends with volume adds an extra layer of validation to trading signals, reducing the likelihood of false breakouts or breakdowns.
Why we Decided to Combine Them
The integration of Fourier filtering with the VZO offers a comprehensive view of the market by combining the geometric clarity of price movements with the psychological insights provided by volume analysis. This synergy allows for a more nuanced understanding of market dynamics.
Enhanced Signal Accuracy: The combination reduces the chances of false signals. Fourier filtering's trend and cycle identification, combined with the VZO's volume-based confirmation, can significantly enhance trading decision accuracy.
Market Turns and Continuations: Fourier analysis can indicate potential turning points or continuation patterns, which, when confirmed with volume analysis through the VZO, provides a robust signal for traders to act upon.
Adaptability: Both tools adapt well to various market conditions, making this combination versatile across different trading instruments and timeframes.
Empirical Evidence:
While specific empirical studies directly analyzing the combined effectiveness of Fourier filtering and VZO might be scarce, the foundational research supporting each method individually provides strong evidence of their validity. Academic and practical applications in financial markets have demonstrated the value of both Fourier analysis for cycle detection and volume-based oscillators like the VZO for assessing market strength and sentiment. Together, they offer a compelling toolkit for traders aiming to refine their market analysis and strategy execution.
USER INPUTS
Momentum Velocity Group
Show Confluence Momentum Velocity?: This toggle allows users to decide whether they want to display the momentum velocity indicator on their chart. It's designed to show the momentum of price movements, potentially indicating acceleration or deceleration in price trends.
Calculation Source: This setting lets users select the price data used for calculating the momentum velocity. Common options include the close, open, high, low, or an average of these prices. The choice depends on what aspect of price action the trader wishes to analyze.
Lookback Period: Determines the number of bars used to calculate the momentum. A longer period may smooth out the indicator, reducing sensitivity to recent price changes, while a shorter period may make the indicator more responsive to new information.
Use Adaptive Filtering?: Enables the use of adaptive filtering for the momentum calculation. This feature adjusts the indicator's sensitivity based on recent market volatility, potentially improving the indicator's responsiveness to market changes.
Adaptive Lookback Period: Specifies the period for the adaptive filter. This setting fine-tunes how rapidly the filter adjusts to changes in market conditions.
FSVZO Group
Show FSVZO?: This input controls whether the Fourier Smoothed Volume Zone Oscillator is displayed on the chart. It's the main feature of the script, combining Fourier analysis with volume data to provide insights into market dynamics.
Calculation Source for FSVZO: Similar to the momentum velocity calculation source, this setting allows users to choose the price data (close, open, high, low, or an average) that will be used for FSVZO calculations.
Calculation Period: Defines the length of the window for Fourier analysis and VZO calculation. This period can affect the sensitivity and smoothing of the indicator.
Show FSVZO Band Filler? (Ribbon): When enabled, this feature displays a filled area or ribbon on the chart, making it easier to visualize the oscillator's movement and trends.
Show FSVZO Moving Average (Ema)?: This toggle allows the display of an Exponential Moving Average (EMA) of the FSVZO, which can help smooth out its movements and provide a clearer trend direction.
MA Period: Specifies the length of the moving average applied to the FSVZO. Adjusting this period can affect the smoothness and lag of the trend indication.
Smooth VZO (Reduces noise, but increases its accuracy): Enables smoothing of the Volume Zone Oscillator to reduce noise and potentially increase the accuracy of its signals.
Smooth Period: Defines the smoothing period for the VZO, affecting how much noise reduction is applied.
UI Settings Group
Show Static Overbought and Oversold Levels?: Enables the display of predetermined levels that indicate overbought or oversold conditions, helping traders identify potential reversal points.
Show Adaptive Levels?: Allows the use of dynamic, market-condition-adjusted levels for overbought and oversold indicators, offering a more nuanced view of market extremes.
Show Detected Trend Shifts?: This setting controls the display of markers or indications when the script detects potential shifts in market trends, based on the oscillator's movements.
Trendshift Shader?: When enabled, this feature visually highlights areas on the chart where trend shifts are detected, improving the visibility of these important signals.
DIVERGENCES Group
Show Detected Divergences?: This option toggles the display of divergences between price action and the oscillator, which can signal potential reversals.
Use extra filtering when detecting divergences?: Enables additional criteria for identifying divergences, potentially improving the reliability of these signals.
Paint bars when Divergences are detected?: This feature changes the color of price bars when divergences are identified, making them stand out on the chart.
How to calculate divergences: Allows users to choose the method for calculating divergences, affecting the sensitivity and types of divergences that are identified.
Only calculate divergences on values absolutely greater than this: Sets a threshold for divergence calculation, focusing on more significant divergences and reducing noise.
Each input is designed to offer flexibility and control to the user, enabling a highly customizable experience tailored to individual trading strategies and market conditions.
How Can it Be Used in a Trading System
There are a few key ways it can be used, the main way is going to be the trend of the band/ ribbon. As that denotes the primary trend. Thus, if it were to trend up and reach the static overbought zone, there is a high probability of a reversion. This will also work well when it is in an extreme zone and there is a divergence.
Other ways of using it, it taking profit when there is an extreme background hue. Or potentially starting to get ready to buy on a higher timeframe if there is a extreme oversold background hue.
For more clear trends out of the FSVZO you may choose to use the moving average crossing the midline in confluence with the momentum velocity.
Please use with caution, nothing BackQuant or associated entities do are financial advice. please do not use this or any other indicator alone, they are not meant to be used in isolation.
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.
This is using the Midline Crossover of the FSVZO:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
GKD-C Voss Predictive Filter [Loxx]The Giga Kaleidoscope GKD-C Voss Predictive Filter is a confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C Voss Predictive Filter
Featured in John Ehlers' article from August 2019 issue of Technical Analysis of Stocks & Commodities magazine, the Voss predictive filter could help signal cyclic turning points by minimizing group and phase delays, thus reducing lag.
The Voss Predictive Filter operates through a unique approach that enhances its ability to predict market movements by effectively reducing lag, which is common in many traditional trading indicators. At its core, the filter applies advanced mathematical techniques to smooth market data and identify significant price trends and cycles. This process involves adjusting to the market's cyclic components, enabling the filter to anticipate turning points with greater accuracy.
One of the key aspects of the Voss Predictive Filter is its ability to minimize both group and phase delays. Group delay refers to the lag between an input signal (such as market price data) entering the filter and the corresponding output being produced. Phase delay, on the other hand, relates to the shift in phase of the input signal's frequency components as they pass through the filter. By reducing these delays, the filter can provide more timely signals for entering or exiting trades.
The filter's predictive capacity comes from its sophisticated algorithm, which dynamically adjusts based on the analyzed market data, allowing it to remain sensitive to changes in market conditions. This dynamic adjustment is crucial for maintaining the filter's effectiveness in different market environments and for various financial instruments.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
Trend ScopeIntroduction:
The Trend Scope presents a cutting-edge approach to technical analysis, offering traders a distinctive perspective on market momentum through dynamic visualization. This innovative indicator harmoniously blends the momentum-based Rate of Change (RoC) with the smoothing precision of a Butterworth filter and the clarity of a Fisher Transform, all encapsulated within an intuitive color-coded environment.
How Trend Scope Works:
The Trend Scope operates on a multi-faceted computational framework:
1. Rate of Change (RoC): The core of Trend Scope, RoC, measures the velocity of price movements, providing an initial momentum footprint that is both raw and telling.
2. Butterworth Filter: To refine the momentum signal and strip away the erratic noise of the market, we introduce the Butterworth filter. Celebrated for its flat frequency response, it ensures the retention of the signal's integrity with minimal lag.
3. Fisher Transform: To further distill the signal, the Fisher Transform is applied. It recalibrates the smoothed data to fit within specified bounds, thus accentuating the extremities of price actions where potential reversals might loom.
4. Adaptive Color Bands: The centerpiece of the Trend Scope's visual prowess lies in its adaptive color bands. These bands stretch over the momentum landscape, painted in vivid reds and greens based on the directional bias of the smoothed RoC. Intensity varies with momentum strength, offering an immediate, graphical representation of market trends.
Why Trend Scope Stands Out:
In the crowded realm of market indicators, Trend Scope distinguishes itself with its visual-forward approach and adaptive nuances. The intensity-adapting bands offer an instant read on the market's pulse—brighter shades signal stronger momentum, while muted tones suggest caution.
Key Features:
- Momentum Intensity Bands: Instead of mere lines, the Trend Scope deploys color bands that dynamically adapt in opacity to reflect the strength of the trend, making it easier for traders to spot significant movements at a glance.
- Volatility-Sensitive Smoothing: By leveraging the Butterworth filter, the Trend Scope finely tunes the noise reduction process in sync with the asset's natural volatility, ensuring the trends are not only smooth but also relevant.
- Sharper Reversal Signals: The Fisher Transform sharpens the ability to spot potential turning points, providing a statistical edge in anticipating market movements.
- Customizable Parameters: The Trend Scope is fully customizable, allowing traders to calibrate the indicator to the unique demands of different assets and market conditions.
Momentum Concepts [AlgoAlpha]🚀 Introducing the Momentum Concepts™ , a robust multi-layered momentum analysis tool developed by AlgoAlpha . This All-in-One indicator offers a comprehensive approach to understanding market momentum, empowering traders with hyper customizable features to tailor their analysis to their specific trading strategies.
Designed with efficiency and compactness in mind, the script shows momentum regimes on three time horizons: The short-term ( Fast Oscillator ), medium-term ( Scalper's Momentum ) and long-term ( Momentum Impulse Oscillator and Hidden Liquidity Flow ). Additionally, the script also includes reversal signals for traders who prefer to trade contrarian/mean-reversion strategies. By utilizing a blend of advanced algorithms and customizable parameters, Momentum Concepts™ provides traders with a vast array of trading strategies ranging from high frequency scalping to timing better entries on long-term swing and investing positions.
Let's delve into the key features and functionalities of this versatile indicator:
🎯Key Features (summary):
Customizable Fast Oscillator: Tailor the fast oscillator to your preferences with adjustable settings for type, source, trend identification(signal processing) method, length, and more.
Divergence Detection: Identify potential trend reversals with ease using built-in divergence detection for both bullish and bearish signals.
Momentum Impulse Oscillator: Gain deeper insights into trending/ranging markets and underlying market bias with a dedicated oscillator, featuring adjustable trend impulse thresholds.
Scalper's Momentum: Utilize a specialized momentum indicator designed for scalping strategies, featuring agility in signal detection with noise reduction and customizable smoothing parameters.
Hidden Liquidity Flow Analysis: Assess hidden liquidity flows within the market, highlighting excess liquidity and potential squeeze situations.
Trend Confluence Indicator: Evaluate the overall momentum direction with dynamically colored zones, aggregating signals from Momentum Concepts™ components for a holistic view.
User-Friendly Interface: The indicator is presented in a clear and intuitive manner, making it accessible for traders of all experience levels.
All-Rounded Alerts: The indicator comes with a comprehensive alerts extension in a separate script, allowing you to stay informed of important market movements even when away from your trading platform.
🎯Key Features (in-depth):
The Fast Oscillator within Momentum Concepts™ comprises four components designed to provide insights into short-term momentum dynamics:
🔱Price Volume Swings :
This confirmation component uses our proprietary Price Volume Algorithm to analyze price action and volume to identify buying and selling pressure, aiding traders in spotting short-term swings for potential trading opportunities.
⚜️Price Volume Waves :
This leading component also uses our proprietary Price Volume Algorithm but differs from the Price Volume Swings by capturing dominant wave patterns instead. This indicator breaks down price and volume data into a wave-like plot which enables leading insights into market momentum due to the relatively predicable nature of sine-like waves. Leading components such as this and the Alpha Wave are best used with other confirmation components within the Momentum Concepts™ .
🌊Alpha Wave :
The Alpha Wave is a leading non-volume alternative to the Price Volume Waves . It reflects market momentum by analyzing price action only instead of using volume data, resulting in a normalized wave-like plot similar to that of the Price Volume Waves , offering a leading perspective on potential market momentum shifts. Leading components such as this and the Price Volume Waves are best used with other confirmation components within the Momentum Concepts™ .
🐲Dragon RSI :
The Dragon RSI is a confirmation component that determines market momentum by analyzing the directional movement of the Relative Strength Index (RSI). By doing so, users are able to visually identify the current short term trend of the market as well as identify overbought and oversold conditions.
Reversal Signals :
All the Fast Oscillator components come with reversal signals that are based on the respective components being either oversold or overbought.
Divergences :
All the Fast Oscillator components come with bullish and bearish divergences. Divergences within the Fast Oscillator components of Momentum Concepts ™ offer crucial signals for trend shifts. 🔱 Price Volume Swings and ⚜️ Price Volume Waves detect weakening buying or selling pressure, signalling potential reversals or continuations. 🌊 Alpha Wave and 🐲 Dragon RSI identify divergences between momentum and price, aiding traders in anticipating market movements. Leveraging these divergences enhances analysis, aiding traders in formulating meaningful analysis.
Customizable Signal Processing Methods :
All the Fast Oscillator components come with customizable signal processing methods to identify trends on the Fast Oscillator , they include (but not limited to) methods such as Heiken Ashi, and a vast selection of Moving Averages.
Diminishing Momentum Warning :
All the Fast Oscillator components come with a diminishing momentum warning that represents a reducing momentum on the Fast Oscillator . This can act as a take profit signal or as a precautionary warning that the price is about to change direction soon even though the Fast Oscillator has not detected it yet.
Dynamically Colored Reversal Zones :
Last but not least, the dynamic coloring of the reversal zones for Fast Oscillator can be customised based on either the reversal probability of the Fast Oscillator or based on the overall trend confluence of all the components within the Momentum Concepts™ indicator.
The Momentum Impulse Oscillator in Momentum Concepts™ offers crucial insights into long-term momentum trends, aiding traders in identifying the underlying momentum regime and differentiating between trending and consolidating markets.
Underlying Momentum Bias
By default, the Momentum Impulse Oscillator is set to show the longer term trend of price action, this can be used to set the directional bias for the markets and prevent users from trading against the trend.
Trending/Ranging Detection
The Momentum Impulse Oscillator comes with the option to enable trending thresholds, when the Momentum Impulse Oscillator is beyond these thresholds, it indicates a trending market, when Momentum Impulse Oscillator is within the thresholds, it indicates a consolidating/ranging market.
The Scalper's Momentum within Momentum Concepts™ furnishes traders with nuanced signals ideal for short to medium-term trading strategies. It efficiently displays both the medium-term momentum and any emerging divergences towards the opposing direction.
Medium-Term Momentum
The Scalper's Momentum is designed to fill the analysis gap between the Fast Oscillator and the Momentum Impulse Oscillator . Showing momentum insights over the medium-term.
Momentum Convergence-Divergence
The Scalper's Momentum is also capable of showing momentum convergences and divergences, which can be used as take-profit and/or confirmation signals to other components within Momentum Concepts™ .
The Hidden Liquidity Flow component of Momentum Concepts™ is designed to uncover underlying liquidity dynamics. This feature enables traders to anticipate potential price movements based on changes in liquidity flow, enhancing their ability to make informed trading decisions.
Underlying Liquidity Dynamics
The Hidden Liquidity Flow shows the underlying liquidity flow of the market, a positive liquidity flow indicates that liquidity is entering the market and increasing the probability of bullish price action, the opposite is true for negative liquidity flows.
Excess Liquidity Flow
The Hidden Liquidity Flow also indicates when there is an abnormal amount of liquidity flowing through the market, this can indicate the potential for volatility and explosive price action.
🎯Usage Examples:
Now that we have gone through the components and features of Momentum Concepts™ in detail, we'll walk you through the usage examples and strategies that you can utilise to navigate the markets.
Scalping
Using the Scalper's Momentum and the Fast Oscillator as an example, users can first use the Scalper's Momentum as a directional bias and the Fast Oscillator as a means of timing a more precise entry. Take profits can be based on either the Diminishing Momentum Warnings or the Fast Oscillator flipping signals or the Scalper's Momentum flipping signals.
Buying the Dip/Shorting the Pump
Using the Momentum Impulse Oscillator and the Fast Oscillator as an example, users will need to first determine the underlying trend with the Momentum Impulse Oscillator , after which they can use the Fast Oscillator for entry signals into the trend. Take profits can be based on either the Diminishing Momentum Warnings or the Fast Oscillator flipping signals
Reversal Trading
Using the Momentum Impulse Oscillator on a timeframe roughly 3-4 times greater than the chart's timeframe and the Fast Oscillator as an example, users will need to first ensure that the Momentum Impulse Oscillator signals a ranging market on a higher timeframe, divergence signals from the Fast Oscillator can then be used as entries. Take profits can be based on either the Diminishing Momentum Warnings or the Fast Oscillator flipping signals or the Fast Oscillator reaching the zero line.
(These are just examples for reference, the Momentum Concepts™ offers significantly more possibilities for customisation and fine tuning of your trading strategy.)
🎯Conclusion:
In conclusion, Momentum Concepts™ stands as a versatile and powerful tool for traders seeking to decode the intricacies of market momentum across multiple time horizons. With its comprehensive suite of customizable features, including the Fast Oscillator , Scalper's Momentum , Momentum Impulse Oscillator , and Hidden Liquidity Flow , traders can gain deep insights into market dynamics and make well-informed trading decisions. Whether executing high-frequency scalping strategies or timing entries for longer-term positions, Momentum Concepts™ equips traders with the tools they need to navigate diverse market conditions with confidence. By harnessing the power of momentum analysis, this indicator empowers traders to stay ahead of the curve and capitalize on emerging opportunities in the ever-evolving financial markets.
Multi-Spectral RSI Deviations [AlgoAlpha]🌌 Multi-Spectral RSI Deviations by AlgoAlpha - Dive into Market Dynamics! 🌠
Dive deep into the essence of market trends with our 🚀 Multi-Spectral RSI Deviations indicator, a comprehensive tool designed by AlgoAlpha to enhance your trading strategy. By harnessing the power of multiple RSI lengths and innovative smoothing techniques, this indicator offers a unique perspective on market momentum and potential reversals.
🔍 Key Features:
🎨 Customizable up and down colors for immediate trend recognition.
🔢 Three RSI lengths for multi-layered market analysis.
🔄 Various Moving Average (MA) types including SMA, EMA, and more for tailored smoothing.
✅ Bullish and Bearish divergence plotting for spotting potential reversals.
🕵️♂️ Adjustable divergence sensitivity settings to fine-tune signal detection.
🔔 Built-in alerts for trend shifts and reversal conditions, ensuring you never miss a trading opportunity.
🚀 Quick Guide to Using the Multi-Spectral RSI Deviations Indicator
🛠 Add the Indicator: Search for "Multi-Spectral RSI Deviations" in TradingView's Indicators & Strategies. Adjust the RSI lengths and MA settings to suit your trading strategy.
🔍 Market Analysis: Keep an eye on the color changes for trend direction and use divergence plots to anticipate potential market reversals.
🔔 Alerts Setup: Activate the built-in alerts for trend shifts and reversals to stay ahead of the game without having to constantly monitor the charts.
🧠 How It Works:
At the core of the Multi-Spectral RSI Deviations indicator is its ability to analyze the market through various RSI lengths, providing a comprehensive view of momentum. The indicator calculates the Relative Strength Index (RSI) over three different periods, creating a spectrum of momentum insights. These RSI values are then compared to each other to identify the momentum shifts within the market.
To refine these insights, the differences between these RSI values are smoothed using a selected Moving Average type, such as SMA, EMA, etc., based on user preference. This smoothing process helps in highlighting the overall trend direction and potential reversal points with greater clarity.
Furthermore, the indicator employs a color-coding system, where the plotted line changes color based on the momentum's direction—shifting to an up color for positive momentum and a down color for negative momentum. This visual cue enables traders to quickly discern the market trend at a glance.
Divergences between the price action and the indicator's values are another cornerstone of this tool. By plotting potential bullish and bearish divergences, the indicator provides early signals of possible trend reversals, offering traders a strategic advantage.
Embrace the power of our 🌌 Multi-Spectral RSI Deviations and elevate your trading to stellar heights! 🌠✨
Momentum Velocity [BackQuant]Momentum Velocity
Main Features:
- Momentum Based Oscillator
- Divergences
- Overbought and Oversold Conditions based off a VZO
- Alert Conditions
- Ability to make Adaptive
- Big User input menu for customisation
The Momentum Velocity indicator is based on the principle of momentum , which is a measure of the rate of change or the speed at which prices move over a specified time period. The underlying assumption of momentum trading is that assets that have performed well in the recent past will continue to perform well in the near future, and conversely, assets that have performed poorly will continue to perform poorly. This concept is widely accepted and empirically supported in financial literature, making the Momentum Velocity indicator empirically sound for several reasons:
Empirical Evidence on Momentum
Academic Research: A foundational piece of research that supports the momentum strategy is Jegadeesh and Titman's study, "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," published in the Journal of Finance in 1993. The authors find that strategies which buy stocks that have performed well in the past and sell stocks that have performed poorly generate significantly higher than expected returns over 3- to 12-month holding periods. This study is one of many that empirically validate the momentum effect in stock returns.
Behavioural Finance Theories:
Behavioural finance provides explanations for the momentum effect that go beyond the efficient market hypothesis. Theories such as investor herding, overreaction and under reaction to news, and the disposition effect can cause price trends to continue. The momentum strategy exploits these behavioural biases by assuming that prices will continue to move in their current direction for some time.
Global Evidence:
The momentum effect is not limited to specific markets or asset classes. Studies have documented momentum profits across various countries, markets, and asset types (stocks, bonds, commodities, and currencies). For instance, Asness, Moskowitz, and Pedersen in their paper, "Value and Momentum Everywhere," published in the Journal of Finance in 2013, show that momentum strategies can yield positive returns in different international markets.
Risk Factors:
Some researchers argue that the returns to momentum strategies are compensation for bearing certain risks. However, the empirical evidence suggests that momentum returns are difficult to explain by traditional risk factors alone, adding to the strategy’s attractiveness. The factor model of Carhart (1997), which adds a momentum factor to the Fama and French three-factor model, highlights the importance of momentum as a distinct source of returns.
Empirical Evidence Application
The Momentum Velocity indicator applies these empirical insights by quantitatively measuring the speed and direction of price movements over a given period, adjusting for recent market conditions through adaptive filtering, and normalizing the results to identify potential trading signals. By doing so, it provides traders with a tool that not only captures the essence of the momentum anomaly but also enhances it with modern technical analysis techniques for real-time market application.
Trading Application
Due to the robustness of momentum, traders are able to use this as a confluence metric into their system on any timeframe. Providing robust signals, that by extention are adaptive to the market. This is also further enabled by using adaptive filtering.
Conclusion
In summary, the empirical soundness of the Momentum Velocity indicator is grounded in the well-documented momentum effect observed in financial markets. By leveraging historical price data to predict future price movements, it aligns with both academic research and observed market behavior, making it a potentially valuable tool for traders seeking to exploit momentum-based trading opportunities.
User Inputs:
Calculation Source: Choose the price component (e.g., close) to base calculations on.
Lookback Period: Define the period over which momentum and normalization are calculated.
Use Adaptive Filtering?: Toggle the use of DEMA for more responsive momentum calculation.
Adaptive Lookback Period: Set the period for the adaptive filter when enabled.
Show Momentum Moving Average?: Option to display a moving average of the plotosc for trend smoothing.
MA Period: Specify the period for the momentum moving average.
Show Static High and Low Levels: Display predefined levels indicating extreme momentum thresholds.
Color Bars According to Trend?: Color price bars based on the momentum direction for quick visual reference.
Show Overbought and Oversold Signals: Highlight extreme volume conditions as potential buy/sell signals.
Signal Calculation Period: Set the period for calculating volume-based signals.
Show Detected Divergences?: Enable or disable the visualization of bullish and bearish divergences.
How it can be used in the context of a Trading System
Momentum and momentum divergences are pivotal concepts in trading systems, offering traders insights into the strength and potential reversal points of market trends. Momentum, a measure of the rate of price changes, helps traders identify the velocity of market movements, allowing them to ride the wave of prevailing trends for profits. When momentum divergences occur—where price movement and momentum indicators move in opposite directions—they signal a weakening of the current trend and potential for reversal. Traders can use these signals to adjust their positions, entering or exiting trades based on the anticipation of trend changes. Incorporating momentum and its divergences into a trading system provides a dynamic strategy that leverages the market's natural cycles of trend strength and exhaustion, aiming to capitalize on both continuation and reversal opportunities for enhanced trading outcomes.
We have also added a volume based component for traders to use as a point of confluence. It is shown on the chart giving background hues for overbought and oversold signals.
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
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.
Change in DominanceTitle: Change in Dominance Indicator
Description:
This is a tool designed to gauge the prevailing trend in the cryptocurrency market. By analyzing the Rate of Change (ROC) in percentage terms over the previous 9 bars for BTC Dominance (BTC.D), Ethereum Dominance (ETH.D), Other Altcoins Dominance (OTHER.D), and USDT Dominance (USDT.D).
How It Works:
The indicator calculates the ROC for BTC.D, ETH.D (aggregated as part of the Altcoin market), OTHER.D (also included in the Altcoin calculation), and USDT.D.
Three lines represent the trends for Bitcoin (BTC), Altcoins (ETH and OTHER combined), and USDT respectively:
Green Line: Represents the trend for BTC. A higher green line indicates a dominance of BTC in the market trend, suggesting money flow into Bitcoin.
Silver Line: Indicates the Altcoin trend (combining ETH and OTHER). When the silver line is the highest among the three, it signals that Altcoins are leading the market, which can be considered bullish as it suggests money is flowing into Altcoins.
Red Line: Represents the USDT trend. A dominant red line over others implies a bearish market sentiment, indicating money flow out of cryptocurrencies and into USDT.
Usage Tips:
Altcoin Bullishness: When the silver line is above both the red and green lines, it suggests a bullish trend for Altcoins, indicating that money is flowing into the Altcoin sector of the market.
Market Bearishness: If the red line surpasses the silver and green lines, it could be a signal that investors are moving their funds into USDT, often a sign of bearish market sentiment.
BTC Bullishness: A higher green line compared to the silver and red lines implies that Bitcoin is the dominant force in the market, suggesting a bullish sentiment for BTC.
