Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
Centered Oscillators
Median Momentum with Buy/Sell Signals and Bar ColorMomentum Calculation:
Momentum is calculated as the difference between the current close price and the close price momentum_length periods ago: momentum = close - close .
Highest and Lowest Momentum:
The highest and lowest momentum values over the specified length are calculated.
Median Momentum:
The median momentum is calculated as the average of the highest and lowest momentum values.
Color Setting:
medianColor is set based on whether the momentum is above, below, or equal to the median momentum.
barColor is set similarly for bar coloring.
Plotting:
The script plots the median momentum and the actual momentum values.
Buy and sell signals are generated when momentum crosses over or under the median momentum.
The script also plots the buy and sell signals with arrows on the chart.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
ADX-DI - Made EasyThis indicator is a visually improved version of ADX. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the ADX direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation and divergences.
Please note that the divergences on ADX are just experimental and are based on calculations, so there is no guarantee the direction will change.
MMI (Multi.Index.Indicator)Multi-Index Momentum Indicator (MMI)
The Multi-Index Momentum Indicator (MMI) is a custom TradingView Pine Script indicator designed to calculate and display the momentum difference between the base and quote indexes of various currency pairs. This indicator helps traders identify the relative strength or weakness of a currency pair by comparing the momentum of its base and quote indexes.
Features:
Currency Pair Detection: The indicator automatically detects the currency pair of the current chart and selects the appropriate base and quote indexes for that pair.
Index Data Retrieval: It fetches the closing prices of the base and quote indexes for the specified timeframe.
Momentum Calculation:
The indicator calculates the 14-period momentum for both the base and quote indexes and then computes the momentum difference.
Visual Representation: The momentum difference is plotted on the chart as a colored line. If the momentum difference is positive, the line is green; if negative, the line is red.
Data Availability Check:
The script checks if the index data is available. If any index data is missing, the script displays a red label on the chart indicating which index data is missing.
Zero Line: A horizontal line at the zero level is plotted for reference.
Supported Currency Pairs and Their Indexes:
USDJPY: Base Index - DXY, Quote Index - JPYX
EURUSD: Base Index - EXY, Quote Index - DXY
GBPUSD: Base Index - BXY, Quote Index - DXY
AUDUSD: Base Index - AXY, Quote Index - DXY
USDCHF: Base Index - DXY, Quote Index - SXY
USDCAD: Base Index - DXY, Quote Index - CXY
GBPJPY: Base Index - BXY, Quote Index - JPYX
CME Gap Oscillator [CryptoSea]Introducing the CME Gap Oscillator , a pioneering tool designed to illuminate the significance of market gaps through the lens of the Chicago Mercantile Exchange (CME). By leveraging gap sizes in relation to the Average True Range (ATR), this indicator offers a unique perspective on market dynamics, particularly around the critical weekly close periods.
Key Features
Gap Measurement : At its core, the CME Oscillator quantifies the size of weekend gaps in the context of the market's volatility, using the ATR to standardize this measurement.
Dynamic Levels : Incorporating a dynamic extreme level calculation, the tool adapts to current market conditions, providing real-time insights into significant gap sizes and their implications.
Band Analysis : Through the introduction of upper and lower bands, based on standard deviations, traders can visually assess the oscillator's position relative to typical market ranges.
Enhanced Insights : A built-in table tracks the frequency of the oscillator's breaches beyond these bands within the latest CME week, offering a snapshot of recent market extremities.
Settings & Customisation
ATR-Based Measurement : Choose to measure gap sizes directly or in terms of ATR for a volatility-adjusted view.
Band Period Adjustability : Tailor the oscillator's sensitivity by modifying the band calculation period.
Dynamic Level Multipliers : Adjust the multiplier for dynamic levels to suit your analysis needs.
Visual Preferences : Customise the oscillator, bands, and table visuals, including color schemes and line styles.
In the example below, it demonstrates that the CME will want to return to the 0 value, this would be considered a reset or gap fill.
Application & Strategy
Deploy the CME Oscillator to enhance your market analysis
Market Sentiment : Gauge weekend market sentiment shifts through gap analysis, refining your strategy for the week ahead.
Volatility Insights : Use the oscillator's ATR-based measurements to understand the volatility context of gaps, aiding in risk management.
Trend Identification : Identify potential trend continuations or reversals based on the frequency and magnitude of gaps exceeding dynamic levels.
The CME Oscillator stands out as a strategic tool for traders focusing on gap analysis and volatility assessment. By offering a detailed breakdown of market gaps in relation to volatility, it empowers users with actionable insights, enabling more informed trading decisions across a range of markets and timeframes.
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
WaveTrend Oscillator PlusThe WaveTrend based on “Enhanced WaveTrend” of EliCobra. The WaveTrend Oscillator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. This indicator introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
The following indicators were added:
⎆⎆ Squeeze Momentum Indicator
⎆⎆ Elliott Wave Oscillator
⎆⎆ Expert Trend Locator
Multiple Non-Linear Regression [ChartPrime]This Pine Script indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices. Here's a breakdown of its components and functionalities:
Inputs:
Users can adjust several parameters:
Normalization Data Length: Length of data used for normalization.
Learning Rate: Rate at which the algorithm learns from errors.
Smooth?: Option to smooth the output.
Smooth Length: Length of smoothing if enabled.
Define start coefficients: Initial coefficients for the regression equation.
Data Normalization:
The script normalizes input data to a range between 0 and 1 using the highest and lowest values within a specified length.
Non-linear Regression:
It calculates the regression equation using the input coefficients and normalized data. The equation used is a weighted sum of the independent variables, with coefficients adjusted iteratively using gradient descent to minimize errors.
Error Calculation:
The script computes the error between the actual and predicted values.
Gradient Descent: The coefficients are updated iteratively using gradient descent to minimize the error.
// Compute the predicted values using the non-linear regression function
predictedValues = nonLinearRegression(x_1, x_2, x_3, x_4, b1, b2, b3, b4)
// Compute the error
error = errorModule(initial_val, predictedValues)
// Update the coefficients using gradient descent
b1 := b1 - (learningRate * (error * x_1))
b2 := b2 - (learningRate * (error * x_2))
b3 := b3 - (learningRate * (error * x_3))
b4 := b4 - (learningRate * (error * x_4))
Visualization:
Plotting of normalized input data (close, open, high, low).
The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line.
Plotting of the regression line.
Color gradient on the regression line based on its value and bar colors.
Display of normalized input data and predicted value in a table.
Signals for crossovers with a midline (0.5).
Interpretation:
Users can interpret the regression line and its crossovers with the midline (0.5) as signals for potential buy or sell opportunities.
This indicator helps users analyze the relationship between multiple variables and make trading decisions based on the regression analysis. Adjusting the coefficients and parameters can fine-tune the model's performance according to specific market conditions.
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
=========================================================================
فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Kalman Volume Filter [ChartPrime]The "Kalman Volume Filter" , aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:
Settings:
Users can adjust various parameters to customize the indicator according to their preferences:
Volume Length: Defines the length of the volume period used in calculations.
Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
Signal Line Length: Sets the length of the signal line used for identifying trends.
Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
Source: Allows users to select the price source for volume calculations.
Volume Zone Oscillator (VZO):
Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
Utilizes a volume direction measurement over a specified period to compute the oscillator value.
Normalizes the oscillator value to improve comparability across different securities or timeframes.
// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
Volume_Direction = get_src > get_src ? volume : -volume
VZO_volume = ta.hma(Volume_Direction, length)
Total_volume = ta.hma(volume, length)
VZO = VZO_volume / (Total_volume)
VZO := (VZO - 0) / ta.stdev(VZO, 200)
VZO
Kalman Filter:
Applies a Kalman filter to smooth out the VZO values and reduce noise.
Utilizes a stabilization coefficient (k) to control the degree of smoothing.
Generates a filtered output representing the underlying volume trend.
// KALMAN FILTER
series float M_n = 0.0 // - the resulting value of the current calculation
series float A_n = VZO // - the initial value of the current measurement
series float M_n_1 = nz(M_n ) // - the resulting value of the previous calculation
float k = input.float(0.06) // - stabilization coefficient
// Kalman Filter Formula
kalm(k)=>
k * A_n + (1 - k) * M_n_1
Volume Visualization:
Displays the volume histogram, with color intensity indicating the strength of volume movements.
Adjusts bar colors based on volume bursts to highlight significant changes in volume.
Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.
Plotting:
Plots the Kalman Volume Filter line and a signal line for visual analysis.
Utilizes different colors and fills to distinguish between rising and falling trends.
Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.
VWAP DivergenceThe "VWAP Divergence" indicator leverages the VWAP Rolling indicator available in TradingView's library to analyze price and volume dynamics. This custom indicator calculates a rolling VWAP (Volume Weighted Average Price) and compares it with a Simple Moving Average (SMA) over a specified historical period.
Advantages:
1. Accurate VWAP Calculation: The VWAP Rolling indicator computes a VWAP that dynamically adjusts based on recent price and volume data. VWAP is a vital metric used by traders to understand the average price at which a security has traded, factoring in volume.
2. SMA Comparison: By contrasting the rolling VWAP from the VWAP Rolling indicator with an SMA of the same length, the indicator highlights potential divergences. This comparison can reveal shifts in market sentiment.
3. Divergence Identification: The primary purpose of this indicator is to detect divergences between the rolling VWAP from VWAP Rolling and the SMA. Divergence occurs when the rolling VWAP significantly differs from the SMA, indicating potential changes in market dynamics.
Interpretation:
1. Positive Oscillator Values: A positive oscillator (difference between rolling VWAP and SMA) suggests that the rolling VWAP, derived from the VWAP Rolling indicator, is above the SMA. This could indicate strong buying interest or accumulation.
2. Negative Oscillator Values: Conversely, a negative oscillator value indicates that the rolling VWAP is below the SMA. This might signal selling pressure or distribution.
3. Divergence Signals: Significant divergences between the rolling VWAP (from VWAP Rolling) and SMA can indicate shifts in market sentiment. For instance, a rising rolling VWAP diverging upwards from the SMA might suggest increasing bullish sentiment.
4. Confirmation with Price Movements: Traders often use these divergences alongside price action to confirm potential trend reversals or continuations.
Implementation:
1. Length Parameter: Adjust the Length input to modify the lookback period for computing both the rolling VWAP from VWAP Rolling and the SMA. A longer period provides a broader view of market sentiment, while a shorter period is more sensitive to recent price movements.
2. Visualization: The indicator plots the VWAP SMA Oscillator, which visually represents the difference (oscillator) between the rolling VWAP (from VWAP Rolling) and SMA over time.
3. Zero Line: The zero line (gray line) serves as a reference point. Oscillator values crossing above or below this line can be interpreted as bullish or bearish signals, respectively.
4. Contextual Analysis: Interpret signals from this indicator in conjunction with broader market conditions and other technical indicators to make informed trading decisions.
This indicator, utilizing the VWAP Rolling component, is valuable for traders seeking insights into the relationship between volume-weighted price levels and traditional moving averages, aiding in the identification of potential trading opportunities based on market dynamics.
MACD 4C with DivergenceMACD 4C Indicator with Divergence
This indicator, named MACD 4C, enhances the traditional MACD (Moving Average Convergence Divergence) by providing a visually intuitive representation with four distinct colors for the histogram bars. It offers a clear interpretation of market momentum and potential trend reversals.
Key Features:
Customizable Parameters: Users can adjust the fast and slow moving average periods along with the signal smoothing parameter to tailor the indicator to their preferred trading style and market conditions.
Four-color Histogram: The histogram bars are color-coded for easy interpretation. Lime and green bars indicate increasing bullish momentum, while maroon and red bars signify increasing bearish momentum.
Bullish and Bearish Divergence Detection: The indicator identifies bullish and bearish divergences between the MACD histogram and price action. Bullish divergence occurs when the price makes a lower low while the MACD histogram forms a higher low, indicating potential bullish reversal. Conversely, bearish divergence occurs when the price makes a higher high while the MACD histogram forms a lower high, suggesting a potential bearish reversal.
How to Use:
Trend Confirmation: Monitor the color of the histogram bars. A series of green (or lime) bars suggests a strengthening bullish trend, while a series of red (or maroon) bars indicates a strengthening bearish trend.
Divergence Identification: Watch for divergences between the MACD histogram and price action. Bullish divergence may signal a potential bullish reversal, while bearish divergence may indicate a potential bearish reversal. These signals can be used in conjunction with other technical analysis tools to confirm trade entries and exits.
The MACD 4C indicator was developed by user vkno422 You can find the original author and their work on their TradingView profile: www.tradingview.com
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
MomentumQ OscillatorDescription of the MomentumQ Oscillator
The MomentumQ Oscillator is a refined technical analysis tool designed to assist traders in identifying market trends and potential reversal points with greater precision. This indicator combines the concepts of MACD and Kaufman's Adaptive Moving Average (KAMA) to create a powerful synergy in trend detection and volatility assessment.
Key Features:
Enhanced MACD Analysis: Utilizes a dynamic scaling factor that adapts the MACD readings to always fall between -100 and 100, ensuring consistent sensitivity across different market conditions.
Adaptive Moving Average: Integrates Kaufman's Adaptive Moving Average, which adjusts more quickly to market volatility compared to traditional moving averages. This feature allows for more responsive trend detection and potential entry/exit signals.
Signal Strength Indicators: Provides visual cues on the chart to denote the strength of buy and sell signals, aiding traders in decision-making based on the robustness of the signal.
Dynamic Sensitivity: Users can adjust the sensitivity of the signals to match their trading style, enhancing the versatility of the indicator across various time frames and market conditions.
Usage:
This tool is invaluable for traders who require precise, adaptive, and visually intuitive indicators. It is suitable for those focusing on medium to long-term trading strategies, as it excels in smoothing out price noise and highlighting core trends.
How It Works:
The MomentumQ Oscillator measures the distance between the current price and the adaptive moving average, normalizing this distance and comparing it against historical standards to project potential market movements. Buy and sell signals are enhanced by a dynamic percentage input, allowing traders to tailor the indicator's reactivity to their risk tolerance.
Please Note:
This indicator does not guarantee future profits and should be used as part of a diversified trading strategy. Past performance is not indicative of future results. Trading involves risk, and it is recommended to consult with a financial advisor if you are unsure about trading online.
KC-MACD Entry Master @shrilssThe KC-MACD Entry Master is designed to enhance trading strategies by utilizing Keltner Channels and MACD for dynamic market analysis. This indicator excels in visually identifying market conditions with a sophisticated bar coloring system and an informative MACD Traffic Light feature.
Key Features:
- Dynamic Bar Coloring: The core feature of this indicator is its ability to adjust the color of bars based on their positioning relative to the Keltner Channels and the EMA (Exponential Moving Average). It colors bars lime or red when the closing price is within the Keltner Channels but above or below the EMA, respectively. Additionally, it uses a fuchsia color to indicate breakouts when the price extends beyond the Keltner Channels. This visual aid helps traders quickly identify potential buying or selling opportunities based on market volatility and price action.
- MACD Traffic Light: Positioned at the bottom of the chart, this unique feature displays the histogram color of the MACD, set by default to a 3/10/16 configuration—known as the 3-10 Oscillator. This Traffic Light gives traders an at-a-glance view of the underlying momentum and trend shifts, further aiding in decision-making processes.
- MACD-Based Entry Signals: By calculating the fast and slow moving averages specified by the user, the script determines MACD values and their crossover with a smoothed signal line. Entry points are then highlighted with shapes (e.g., "Buy" or "Sell") plotted on the chart when conditions are met, including alignment with the bar colors for enhanced accuracy.
Dynamic Price Oscillator (Zeiierman)█ Overview
The Dynamic Price Oscillator (DPO) by Zeiierman is designed to gauge the momentum and volatility of asset prices in trading markets. By integrating elements of traditional oscillators with volatility adjustments and Bollinger Bands, the DPO offers a unique approach to understanding market dynamics. This indicator is particularly useful for identifying overbought and oversold conditions, capturing price trends, and detecting potential reversal points.
█ How It Works
The DPO operates by calculating the difference between the current closing price and a moving average of the closing price, adjusted for volatility using the True Range method. This difference is then smoothed over a user-defined period to create the oscillator. Additionally, Bollinger Bands are applied to the oscillator itself, providing visual cues for volatility and potential breakout signals.
█ How to Use
⚪ Trend Confirmation
The DPO can serve as a confirmation tool for existing trends. Traders might look for the oscillator to maintain above or below its mean line to confirm bullish or bearish trends, respectively. A consistent direction in the oscillator's movement alongside price trend can provide additional confidence in the strength and sustainability of the trend.
⚪ Overbought/Oversold Conditions
With the application of Bollinger Bands directly on the oscillator, the DPO can highlight overbought or oversold conditions in a unique manner. When the oscillator moves outside the Bollinger Bands, it signifies an extreme condition.
⚪ Volatility Breakouts
The width of the Bollinger Bands on the oscillator reflects market volatility. Sudden expansions in the bands can indicate a breakout from a consolidation phase, which traders can use to enter trades in the direction of the breakout. Conversely, a contraction suggests a quieter market, which might be a signal for traders to wait or to look for range-bound strategies.
⚪ Momentum Trading
Momentum traders can use the DPO to spot moments when the market momentum is picking up. A sharp move of the oscillator towards either direction, especially when crossing the Bollinger Bands, can indicate the start of a strong price movement.
⚪ Mean Reversion
The DPO is also useful for mean reversion strategies, especially considering its volatility adjustment feature. When the oscillator touches or breaches the Bollinger Bands, it indicates a deviation from the normal price range. Traders might look for opportunities to enter trades anticipating a reversion to the mean.
⚪ Divergence Trading
Divergences between the oscillator and price action can be a powerful signal for reversals. For instance, if the price makes a new high but the oscillator fails to make a corresponding high, it may indicate weakening momentum and a potential reversal. Traders can use these divergence signals to initiate counter-trend moves.
█ Settings
Length: Determines the lookback period for the oscillator and Bollinger Bands calculation. Increasing this value smooths the oscillator and widens the Bollinger Bands, leading to fewer, more significant signals. Decreasing this value makes the oscillator more sensitive to recent price changes, offering more frequent signals but with increased noise.
Smoothing Factor: Adjusts the degree of smoothing applied to the oscillator's calculation. A higher smoothing factor reduces noise, offering clearer trend identification at the cost of signal timeliness. Conversely, a lower smoothing factor increases the oscillator's responsiveness to price movements, which may be useful for short-term trading but at the risk of false signals.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Trend Tide Oscillator [UAlgo]🔶 Description:
The "Trend Tide Oscillator " is a technical analysis tool designed to identify potential trend reversals and overbought/oversold conditions in the market. It calculates an oscillator based on the Commodity Channel Index (CCI) and then applies smoothing techniques to provide a clearer view of market momentum.
🔶 Key Features:
Oscillator Calculation : The indicator calculates an oscillator based on the Commodity Channel Index (CCI), which is a momentum-based oscillator used to identify overbought and oversold conditions.
Smoothing : Smoothing techniques are applied to the oscillator to reduce noise and provide a clearer view of market momentum. This helps traders in identifying trends more effectively.
Support and Resistance Zones : The indicator plots support and resistance zones based on the highest and lowest values of the oscillator over a specified lookback (default 50) period. These zones can help traders identify potential areas of price reversal. The indicator considers volatility when plotting the support and resistance zones. This aims to create more adaptable levels that account for fluctuating market conditions.
Visualization : The indicator visually represents overbought and oversold conditions with shapes (⚠️), aiding traders in quickly identifying potential entry or exit points.
Customization : Users can adjust parameters such as oscillator length, smoothing, and overbought/oversold levels, support and resistance lookbacks according to their trading preferences.
🔶 Disclaimer :
This indicator is provided for informational and educational purposes only and should not be considered as financial advice. Trading in the financial markets involves risk, and users should conduct their own research and analysis before making any investment decisions.
Trade Scanner Pro [MarketSignalsPro]
█ OVERVIEW
Trade Scanner Pro is a trade signal generator based on my trend following momentum reversal system. It identifies a pullback and then confirms momentum exhaustion which produces a signal appearing as a set of suggested orders (horizontal lines) on the chart. The goal is to help traders capitalize on price momentum while simplifying decision making and offering a way to gauge expectations. It can be used for any market, any time frame and configured for counter trend signals also.
█ CONCEPT
While markets are highly random, especially on smaller time frames, trends do exist.
Trade Scanner Pro offers a visually structured way to align the user
with price momentum that is relevant to the trend. It accomplishes this by incorporating a unique mix of standard technical formulas to identify a pullback followed by a momentum reversal. The process occurs in 3 steps:
1 — Identifying the trend of the current time frame.
2 — Evaluating the retrace in terms of how far it moves away from the typical price.
3 — Confirming price exhaustion by recognizing a reversal in price momentum.
Once the criteria are met, a signal appears as a blue horizontal line. This is the entry price suggestion (see label). Stop and take profit orders are also calculated simultaneously. These appear as a red line and green line respectively with price labels. The stop and take profit orders are based upon an average of previous price ranges and will be relative to the price action on the chosen time frame. The initial reward/risk ratio is set to 1.5:1, and can be changed in the settings menu.
This system can also be adjusted to cater to the experience level of the trader. For example, more advanced traders can select “counter trend” mode which will only show signals on the opposite side of the trend. A trailing stop can be activated to help stay in a trade after reaching the profit level. There is also a “heads up” mode which colors the candles orange which means a signal is more likely to appear over the next couple of candles. More on these features in the next section.
For best results, time frames of 1 minute and above should be considered. The smaller the time frame, the more signals, but also more noise and stop outs. Knowing your
market and the most active time of day is especially important for smaller time frames.
█ FEATURES
The following features can be found in the settings menu of Trade Scanner Pro.
Show Trend:
The initial setting is “on”. This shows the trend label on the upper right corner of the screen. Trend can be either bullish or bearish. At times there will be a “conflict” label that appears below the trend label. Conflict means the trend MAY be in the process of changing. This occurs when price persists against the prevailing trend for a prolonged amount of time.
Counter Trend:
When selected will ignore signals on the side of the trend and show counter trend signals only. If the “heads up” feature is selected, orange candles will only appear for potential counter trend signals.
Trailing Stop:
When selected, a trailing stop order suggestion (orange line) will appear beginning from the stop loss price (red line) after a few closed candles. The trailing stop line will follow the price upon each new close of the candles until it is touched. This serves as a point of reference to capture larger market movements and skew reward/risk favorably over time.
Heads Up:
When selected will paint orange candles when there is a greater chance a signal will appear. For example, in trend mode it will only evaluate signals on the side of the trend. In counter trend mode it will evaluate counter trend signals only. For advanced users, this “pre signal” can offer potential opportunities to enter a trade before the signal appears.
Reward Ratio:
This is the reward part of the reward/risk formula used to establish the take profit suggestion on the chart. Initially it is set at 1.5 which produces a line on the chart at a 1.5:1 ratio. The user can change this setting to better align with their expectations. For example, if a larger market movement is anticipated, 2 can be entered into the input field and will generate a take profit line 2X farther than the stop loss line (2:1 reward/risk).
█ LIMITATIONS
Markets are HIGHLY random, especially on smaller time frames. No system that is based on public domain formulas can be expected to be HIGHLY accurate. It is reasonable to expect a 50% win rate more often than not. Profitability in such systems depends on the reward/risk rather than win rate.
This is a system based on price momentum which means MOMENTUM must be present for best results especially on very short time frames.
While this system helps to reduce the burden of analysis, the user should have some basic familiarity with technical analysis. Basic knowledge can help to better determine a quality signal over noise.
█ RAMBLINGS
The stop loss orders MUST be respected otherwise the user puts their entire account at risk. Signals can appear at price locations where larger magnitude risk is extremely high. Respecting the stop loss suggestions can help to mitigate this risk.
For best results set up notifications to receive a message on your desktop, smart phone or tablet rather than sitting in front of a computer screen waiting for a signal to appear. Keep in mind a 1 minute chart in a single market can produce 5 or 6 signals throughout the entire daily session and NOT all will be profitable. A 1 hour time frame may produce 1 or 2 throughout the day. The larger the time frame the lower frequency of signals.
█ THANKS
Special thanks to Cryptosnagger for
helping me translate my concept into a pine script reality.
UT Bot Stochastic RSIUT Bot Stochastic RSI is a powerful trading tool designed to help traders identify potential buy and sell signals in the market. This indicator combines the Stochastic and RSI (Relative Strength Index) oscillators, two of the most popular and effective technical analysis tools, to provide a comprehensive view of market conditions.
The Stochastic oscillator is a momentum indicator that compares a security's closing price to its price range over a given time period. The RSI, on the other hand, is a momentum oscillator that measures the speed and change of price movements. By combining these two indicators, the UT Bot Stochastic RSI can help traders identify overbought and oversold conditions, as well as potential trend reversals.
The UT Bot Stochastic RSI also includes an ATR (Average True Range) trailing stop, which can be used to set stop-loss levels and manage risk. This feature is particularly useful in volatile markets, where price movements can be large and unpredictable.
In addition to its powerful technical analysis tools, the UT Bot Stochastic RSI also includes a backtesting feature, allowing traders to test their strategies on historical data. This can help traders identify the most effective settings for the indicator and improve their trading performance.
Overall, the UT Bot Stochastic RSI is a versatile and effective tool for traders of all levels, providing valuable insights into market conditions and helping to improve trading decisions
Neutral State MACD {DCAquant}The Neutral State MACD {DCAquant}
The Neutral State MACD {DCAquant} offers a nuanced interpretation of the classic MACD (Moving Average Convergence Divergence) indicator. By focusing on the neutrality of price movements, it serves to identify periods where the market lacks a defined directional bias, often seen as potential phases of accumulation or distribution before a new trend emerges.
Characteristics of the Neutral State MACD {DCAquant}:
Enhanced MACD Formula: Incorporates a neutral zone detection system into the traditional MACD framework to spotlight periods of market equilibrium.
Neutral Zone Threshold: A user-defined parameter that establishes a range within which the MACD and the signal line convergence is considered indicative of a neutral state.
Color-Coded Visualization: Utilizes color variations to illustrate the relationship between the MACD line and the signal line, accentuating the detection of neutral states, bullish crossovers, and bearish crossovers.
Functionality:
MACD and Signal Line Calculation: Employs fast and slow EMA inputs to generate the MACD line, contrasted against a signal line to capture momentum shifts.
Neutral State Detection: Assesses the proximity between the MACD and signal lines relative to the neutral zone threshold, identifying periods where neither bullish nor bearish momentum is dominant.
Background Highlighting: Modifies the chart's background color to reflect the current state of the market—neutral (gray), bullish divergence (teal), or bearish divergence (purple).
Interpretation and Trading Strategy:
Market Phases Identification: Traders can spot periods of equilibrium that may precede significant market moves, aiding in the timing of entry and exit points.
Momentum Analysis: The MACD line's cross above the signal line suggests increasing bullish momentum, whereas a cross below may signal growing bearish momentum.
Trend Confirmation: Acts as a confirmation tool when aligned with trend-following strategies, providing additional validation for trade setups.
Customization and User Guidance:
Adjustable Parameters: Allows for fine-tuning of length settings and the neutral zone threshold to match different trading styles and market conditions.
Complementary Indicator: Can be paired with volume indicators, price action patterns, or other oscillators to form a comprehensive trading system.
Disclaimer:
The Neutral State MACD {DCAquant} is a sophisticated tool meant for educational and strategic development. Traders should integrate it within a broader analytical framework and consider additional market factors. It is not a standalone signal for trades and should be used with caution and proper risk management. Trading decisions should always be made in the context of well-researched strategies and responsible investment practices.
GKD-C Derivative Oscillator [Loxx]The Giga Kaleidoscope GKD-C Derivative Oscillator is a Confirmation module included in AlgxTrading's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C Derivative Oscillator, a brief overview
The Derivative Oscillator is a technical analysis tool used in trading that merges the concepts of the Relative Strength Index (RSI) and the double smoothed moving average. Essentially, it operates by taking the difference between a short-term moving average of the asset's price and a longer-term moving average, which is then double smoothed with exponential moving averages (EMAs). This process refines the RSI, aiming to provide clearer signals regarding the momentum and potential trend reversals of a security's price. The GKD-C Derivative Oscillator produces two types of signals: Zero-line or Signal crosses. (read the sections below to learn how traders can test these different signal types using AlgxTrading's GKD trading system)
GKD-C Derivative Oscillator in Zero-line crosses mode
GKD-C Derivative Oscillator in Signal crosses mode
To explain the features included in the GKD-C Derivative Oscillator , let's first dive into the details of the Giga Kaleidoscope (GKD) Modularized Trading System.
█ Giga Kaleidoscope (GKD) Modularized Trading System
The GKD Trading System is a comprehensive, algorithmic trading framework from AlgxTrading, designed to optimize trading strategies across various market conditions. It employs a modular approach, incorporating elements such as volatility assessment, trend identification through a baseline, multiple confirmation strategies for signal accuracy, and volume analysis. Key components also include specialized strategies for entry and exit, enabling precise trade execution. The system allows for extensive backtesting, providing traders with the ability to evaluate the effectiveness of their strategies using historical data. Aimed at reducing setup time, the GKD system empowers traders to focus more on strategy refinement and execution, leveraging a wide array of technical indicators for informed decision-making.
🔶 Core components of a GKD Algorithmic Trading System
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. The GKD algorithm is built on the principles of trend, momentum, and volatility. There are eight core components in the GKD trading algorithm:
🔹 Volatility - In the GKD trading system, volatility is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. There are 17+ different types of volatility available in the GKD system including Average True Range (ATR), True Range Double (TRD), Close-to-Close, Garman-Klass, and more.
🔹 Baseline (GKD-B) - The baseline is essentially a moving average and is used to determine the overall direction of the market. The baseline in the GKD trading 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 GKD indicators.
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards or price is above the baseline, then only long trades are taken, and if the baseline is sloping downwards or price is below the baseline, then 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.
🔹 Confirmation 1, Confirmation 2, Continuation (GKD-C) - The GKD trading system incorporates technical confirmation indicators for the generation of its primary long and short signals, essential for its operation.
The GKD trading system distinguishes three specific categories. The first category, Confirmation 1 , encompasses technical indicators designed to identify trends and generate explicit trading signals. The second category, Confirmation 2 , a technical indicator used to identify trends; this type of indicator is primarily used to filter the Confirmation 1 indicator signals; however, this type of confirmation indicator also generates signals*. Lastly, the Continuation category includes technical indicators used in conjunction with Confirmation 1 and Confirmation 2 to generate a special type of trading signal called a "Continuation"
In a full GKD trading system all three categories generate signals. (see the section “GKD Trading System Signals” below)
🔹 Volatility/Volume (GKD-V) - Volatility/Volume indicators are used to measure the amount of buying and selling activity in a market. They are based on the trading Volatility/Volume of the market, and can provide information about the strength of the trend. In the GKD trading system, Volatility/Volume indicators are used to confirm trading signals generated by the various other GKD indicators. In the GKD trading system, Volatility is a proxy for Volume and vice versa.
Volatility/Volume indicators 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 GKD-C confirmation and GKD-B baseline indicators.
🔹 Exit (GKD-E) - The exit indicator in the GKD system is an indicator that is deemed effective at identifying optimal exit points. 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.
🔹 Backtest (GKD-BT) - The GKD-BT backtest indicators link all other GKD-C, GKD-B, GKD-E, GKD-V, and GKD-M components together to create a GKD trading system. GKD-BT backtests generate signals (see the section “GKD Trading System Signals” below) from the confluence of various GKD indicators that are imported into the GKD-BT backtest. Backtest types include: GKD-BT solo and full GKD backtest strategies used for a single ticker; GKD-BT optimizers used to optimize a single indicator or the full GKD trading system; GKD-BT Multi-ticker used to backtest a single indicator or the full GKD trading system across up to ten tickers; GKD-BT exotic backtests like CC, Baseline, and Giga Stacks used to test confluence between GKD components to then be injected into a core GKD-BT Multi-ticker backtest or single ticker strategy.
🔹 Metamorphosis (GKD-M) ** - 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, GKD-E, or GKD-V 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.
*(see the section “GKD Trading System Signals” below)
**(not a required component of the GKD algorithm)
🔶 What does the application of the GKD trading system look like?
Example trading system:
Volatility: Average True Range (ATR) (selectable in all backtests and other related GKD indicators)
GKD-B Baseline: GKD-B Multi-Ticker Baseline using Hull Moving Average
GKD-C Confirmation 1 : GKD-C Advance Trend Pressure
GKD-C Confirmation 2: GKD-C Dorsey Inertia
GKD-C Continuation: GKD-C Stochastic of RSX
GKD-V Volatility/Volume: GKD-V Damiani Volatmeter
GKD-E Exit: GKD-E MFI
GKD-BT Backtest: GKD-BT Multi-Ticker Full GKD Backtest
GKD-M Metamorphosis: GKD-M Baseline Optimizer
**all indicators mentioned above are included in the same AlgxTrading package**
Each module is passed to a GKD-BT backtest module. In the backtest module, all components are combined to formulate trading signals and statistical output. This chaining of indicators requires that each module conform to AlgxTrading's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the various indictor types in the GKD algorithm.
🔶 GKD Trading System Signals
🔹 Standard Entry requires a sequence of conditions including a confirmation signal from GKD-C, baseline agreement, price criteria related to the Goldie Locks Zone, and concurrence from a second confirmation and volatility/volume indicators.
🔹 1-Candle Standard Entry introduces a two-phase process where initial conditions must be met, followed by a retraction in price and additional confirmations in the subsequent candle, including baseline, confirmations 1 and 2, and volatility/volume criteria.
🔹 Baseline Entry focuses on signals generated by the GKD-B Baseline, requiring agreement from confirmation signals, specific price conditions within the Goldie Locks Zone, and a timing condition related to the confirmation 1 signal.
🔹 1-Candle Baseline Entry mirrors the baseline entry but adds a requirement for a price retraction and subsequent confirmations in the following candle, maintaining the focus on the baseline's guidance.
🔹 Volatility/Volume Entry is predicated on signals from volatility/volume indicators, requiring support from confirmations, price criteria within the Goldie Locks Zone, baseline agreement, and a timing condition for the confirmation 1 signal.
🔹 1-Candle Volatility/Volume Entry adapts the volatility/volume entry to include a phase of initial signal and agreement, followed by a retracement phase that seeks further agreement from the system's components in the subsequent candle.
🔹 Confirmation 2 Entry is based on the second confirmation signal, requiring the first confirmation's agreement, specific price criteria, agreement from volatility/volume indicators, and baseline, with a timing condition for the confirmation 1 signal.
🔹 1-Candle Confirmation 2 Entry adds a retracement requirement to the confirmation 2 entry, necessitating additional agreements from the system's components in the candle following the signal.
🔹 PullBack Entry initiates with a baseline signal and agreement from the first confirmation, with a price condition related to volatility. It then looks for price to return within the Goldie Locks Zone and seeks further agreement from the system's components in the subsequent candle.
🔹 Continuation Entry allows for the continuation of an active position, based on a previously triggered entry strategy. It requires that the baseline hasn't crossed since the initial trigger, alongside ongoing agreements from confirmations and the baseline.
█ GKD-C Derivative Oscillator, a deep dive
Now that you have a basic understanding of the GKD trading system. let's dive deeper into the features included in the GKD-C Derivative Oscillator
🔶 GKD-C Derivative Oscillator Modes aka "Confirmation Type"
The GKD-C Derivative Oscillator has 4 modes: Confirmation for confirmation 1 and 2; Continuation; Multi-ticker for multi-ticker confirmation 1 and 2; and Optimizer.
🔹 Confirmation: When in this mode, the GKD-C Derivative Oscillator generates confirmation 1 and 2 signals. These values can then be exported to a GKD-BT backtest strategy.
Signal Key: L = Long, S = Short
GKD-C Derivative Oscillator in Confirmation mode
Confirmation Exports
GKD-C Derivative Oscillator in attached to a GKD-BT backtest strategy
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
🔹 Continuation: When in this mode, the GKD-C Derivative Oscillator generates continuation signals.
Signal Key: L = Long, S = Short, CL = Continuation Long, CS = Continuation Short
GKD-C Derivative Oscillator in Continuation mode
Continuation Exports
🔹 Multi-ticker: When in this mode, the GKD-C Derivative Oscillator generates multi-ticker confirmation 1 and 2. This mode allows users to generate confirmation 1 and 2, and continuation signals for up to 10 different tickers. These values can then be exported to a GKD-BT Multi-ticker backtest.
Signal Key: L = Long, S = Short
GKD-C Derivative Oscillator in Multi-ticker mode
Multi-ticker Exports
GKD-C Derivative Oscillator attached to the GKD-BT Multi-ticker SCS Backtest
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
🔹 Optimizer: When in this mode, the GKD-C Derivative Oscillator generates optimization signals. These signals allow the user to backtest a range of input values. These values are exported to a GKD-BT optimizer backtest.
Signal Key: L = Long, S = Short
GKD-C Derivative Oscillator in Optimizer mode
Optimizer Inputs and Exports
GKD-C Derivative Oscillator attacked to the GKD-BT Optimizer SCS Backtest
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
█ Conclusion
The GKD-C Derivative Oscillator serves as a multi-modal component of the GKD trading system allowing traders to optimize and backtest acorss a range of input parameters and tickers. These features decrease total build time required to create a custom GKD algorithmic trading system by allowing users to spend more time trading and less time guessing.
█ How to Access
You can see the Author's Instructions below to learn how to get access.
Multi-time Frame Trend DirectionThis is a multi-time frame trend direction indicator. It indicates whether the trend is ascending or descending across multiple time frames: 5M, 15M, 30M, 1H, 4H, and Daily.
The logic is based on the positions of EMA12 and EMA26.
These EMAs are smoothed with an SMA.
Why 12 and 26, and why are they smoothed with 9?
As you might surmise, these parameters are derived from the MACD.
I recommend not altering the parameters, but the choice is yours. Enjoy.
