Neutral State Stochastic Oscillator {DCAquant}Neutral State Stochastic Oscillator {DCAquant}
The Neutral State Stochastic Oscillator {DCAquant} is an enhanced version of the classic Stochastic Oscillator. This iteration aims to refine the detection of neutral market states — periods where the market is neither overbought nor oversold — potentially signaling a period of consolidation or equilibrium before the next significant price move.
Key Features:
Advanced Oscillator Analysis: It extends the traditional use of the Stochastic Oscillator by identifying a neutral zone, which may signal a pause in market momentum.
Customizable Sensitivity: Users can adjust parameters such as K and D periods, Smooth K, and neutral zone thresholds to tailor the indicator to their trading style.
Neutral Zone Detection: This tool is especially adept at pinpointing where the %K and %D lines converge within a specific threshold, marking a neutral state.
How it Works:
%K and %D Calculation: The indicator calculates the Stochastic %K and %D lines over user-defined periods, smoothing %K for clearer signals.
Neutral Zone Threshold: A threshold defines how close %K and %D lines should be to each other to qualify as a neutral state, offering a refined perspective on market momentum.
Visual Contrast: The indicator employs a distinct color scheme to distinguish between neutral (gray), bullish (%K>%D in aqua), and bearish (%K<%D in fuchsia) market conditions, directly on the price chart.
Visual Indicators and Interpretation:
Neutral Market Condition: A gray background indicates a neutral state where %K and %D are close, suggesting a balanced market awaiting new forces to define the trend.
Market Extremes: Aqua and fuchsia backgrounds highlight when the market is exiting the neutral zone, potentially signaling the start of an uptrend or downtrend.
Strategic Application:
Consolidation and Breakout Identification: This tool helps in identifying consolidation zones which could lead to potential breakouts or breakdowns, aiding in strategic entry and exit decisions.
Multifaceted Market Analysis: By revealing neutral market states, it serves as a vital component in a comprehensive trading strategy, augmenting the insights provided by other technical indicators.
Customization and Usage:
Flexible for Various Markets: The Neutral State Stochastic Oscillator {DCAquant} is adaptable for a variety of markets, whether you're trading cryptocurrencies, stocks, forex, or commodities.
Confirmatory Tool: It acts as an excellent confirmatory tool when used with price action analysis, other oscillators, or trend indicators, ensuring a well-rounded analytical approach.
Disclaimer and User Guidance:
The Neutral State Stochastic Oscillator {DCAquant} is a sophisticated trading tool designed for informative purposes. Traders are advised to use it in conjunction with a robust risk management strategy and not as a standalone decision-making tool. As with all trading indicators, success cannot be guaranteed, and it is recommended that traders perform their due diligence before executing trades based on signals from this or any other analytical tool.
Cerca negli script per "indicators"
Yeong RRGThe code outlines a trading strategy that leverages Relative Strength (RS) and Rate of Change (RoC) to make trading decisions. Here's a detailed breakdown of the tactic described by the code:
Ticker and Period Selection: The strategy begins by selecting a stock ticker symbol and defining a period (len) for the calculations, which defaults to 14 but can be adjusted by the user.
Stock and Index Data Retrieval: It fetches the closing price (stock_close) of the chosen stock and calculates its 25-period exponential moving average (stock_ema). Additionally, it retrieves the closing price of the S&P 500 Index (index_close), used as a benchmark for calculating Relative Strength.
Relative Strength Calculation: The Relative Strength (rs) is computed by dividing the stock's closing price by the index's closing price, then multiplying by 100 to scale the result. This metric is used to assess the stock's performance relative to the broader market.
Moving RS Ratio and Rate of Change: The strategy calculates a Simple Moving Average (sma) of the RS over the specified period to get the RS Ratio (rs_ratio). It then computes the Rate of Change (roc) of this RS Ratio over the same period to get the RM Ratio (rm_ratio).
Normalization: The RS Ratio and RM Ratio are normalized using a formula that adjusts their values based on the mean and standard deviation of their respective series over the specified window. This normalization process helps in standardizing the indicators, making them easier to interpret and compare.
Indicator Plotting: The normalized RS Ratio (jdk_rs_ratio) and RM Ratio (jdk_rm_ratio) are plotted on the chart with different colors for visual analysis. A horizontal line (hline) at 100 serves as a reference point, indicating a neutral level for the indicators.
State Color Logic: The script includes a logic to determine the state color (statecolor) based on the previous state color and the current values of jdk_rs_ratio and jdk_rm_ratio. This color coding is intended to visually represent different market states: green for bullish, red for bearish, yellow for hold, and blue for watch conditions.
Signal Generation: The strategy generates buy, sell, hold, and watch signals based on the state color and the indicators' values relative to 100. For example, a buy signal is generated when both jdk_rs_ratio and jdk_rm_ratio are above 100, and the background color is set to green to reflect this bullish condition.
Trade Execution: Finally, the strategy executes trades based on the generated signals. A "BUY" trade is entered when a buy signal is present, and it is closed when a sell signal occurs.
Overall, the strategy uses a combination of RS and RoC indicators, normalized for better comparison, to identify potential buy and sell opportunities based on the stock's performance relative to the market and its momentum.
Divergence Indicator [Trendoscope®]🎲 New Divergence Indicator by Trendoscope
Our latest Divergence Indicator revolutionizes the way traders identify market trends and potential reversals. Built upon the robust foundation of the Zigzag Trend Divergence Detector and inline with our recent implementation of the Divergence Goggles indicator, this tool is designed to be intuitive yet powerful, making it an essential addition to any trader's toolkit.
We received several queries on extending the Divergence Goggles to last N bars instead of using an interactive widget. Though it is possible, we thought the better approach is to enable the indicator to use any oscillator and trend indicator in order to define the divergence.
🎯 Key Features
Flexible Oscillator Integration : Choose from a wide range of built-in oscillators or import your own, including options like the innovative Multiband Oscillator. This versatility extends to using volume indicators like OBV for divergence calculations, broadening the scope of analysis.
Trend Identification Versatility : Utilize built-in methods like Zigzag and MA Difference, or integrate external trend indicators. Our system adapts to various methods, ensuring you have the right tools for precise trend identification.
Customizable Zigzag Sensitivity : Adjust the Zigzag based on your chosen oscillator's sensitivity to ensure divergence lines are accurate and visually coherent.
Repainting vs. Delayed Signals : Tailor the indicator to your strategy by choosing between immediate repainting signals and slightly delayed but more stable signals.
🎯 Understanding Divergence: Key Rules
Bullish Divergence
Happens only in downtrend
Observed on Pivot Lows
Price makes lower low whereas oscillator makes higher low, indicating weakness and possible reversal
Bearish Divergence
Happens only in uptrend
Observed on Pivot Highs
Price makes higher high whereas oscillator makes lower high, indicating weakness and possible reversal
Bullish Hidden Divergence
Happens only in uptrend
Observed on Pivot Lows
Price makes higher low, whereas indicator makes lower low due to price consolidation. In bullish trend, this is considered as bullish as the price gets a breather and get ready to surge further.
Bearish Hidden Divergence
Happens only in downtrend
Observed on Pivot Highs
Price makes lower high whereas oscillator makes higher high due to price consolidation. In bearish trend, this is considered as bearish as the price gets a breather and get ready to fall further.
🎯 Visual Insights: Divergence and Hidden Divergence
For a clearer understanding, refer to our visual guides:
🎲 Using the Divergence Indicator: A Step-by-Step Guide
🎯 Step 1 - Selecting the Oscillator
Customize your analysis by choosing from a variety of oscillators or importing your preferred one. Options are available to select a range of built-in oscillators and the loopback length. However, if the oscillator that user want to use is not in the list, they can simply load the oscillator from the indicator library and use it as an external signal.
In our current example, we are using a custom oscillator called - Multiband Oscillator
This also means, the indicator option is not limited to oscillators. Users can even make use of volume indicators such as OBV for the calculation of divergence.
🎯 Step 2 - Choosing the Trend Identification Method
Select from our built-in methods or integrate an external indicator to accurately identify market trends. Trend is one of the key parameters of divergence type identification. Trend can be identified mathematically by various methods. Some of them are as simple as above or below 200 moving average and some can follow trend based indicators such as supertrend and others can be very complex.
To cater for a wider audience, here too we have provided the option to use an external trend indicator. The simple condition for the external trend indicator is that it should return positive value for uptrend and negative value for downtrend.
Other than that, we also have 2 built in trend identification methods.
Zigzag - The trend is defined by the starting pivot of divergence line. If the starting pivot is Higher High or Higher Low, then it is considered uptrend. And if the starting pivot is either Lower Low or Lower High, then we consider it as downtrend.
MA Difference - In this case, the difference between the moving average of pivots joining the divergence line will determine the trend. It is considered uptrend if the moving average increased from starting pivot to ending pivot of the divergence line, and it is considered downtrend if the moving average decreased from starting pivot to the ending pivot of the divergence line.
🎯 Step 3 - Adjusting Zigzag Sensitivity
Fine-tune the Zigzag to match the oscillator's sensitivity, ensuring divergence lines are accurate and visually coherent.
🎯 Step 4 - Managing Repainting
Understand the implications of repainting in the last pivot of the Zigzag and choose between immediate or delayed signals based on your trading strategy. The last pivot of the zigzag repaint by design. This is not necessarily a bad thing. Users can just choose not to use the last pivot, but instead use the last but one for all the calculations. But, this also means, the signals will be delayed.
Indicator provides option to use repainting signal vs delayed signal. If you select the repaint option, the signals are shown immediately as and when they occur. But, there is a possibility that these signals change when the new price candles change zigzag pivot.
If you chose not to select the repaint option, then the divergence signals may lag by a few bars.
SuperTrend ToolkitThe SuperTrend Toolkit (Super Kit) introduces a versatile approach to trend analysis by extending the application of the SuperTrend indicator to a wide array of @TradingView's built-in or Community Scripts . This tool facilitates the integration of the SuperTrend algorithm with various indicators, including oscillators, moving averages, overlays, and channels.
Methodology:
The SuperTrend, at its core, calculates a trend-following indicator based on the Average-True-Range (ATR) and price action. It creates dynamic support and resistance levels, adjusting to changing market conditions, and aiding in trend identification.
pine_st(simple float factor = 3., simple int length = 10) =>
float atr = ta.atr(length)
float up = hl2 + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = hl2 - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
@TradingView's native SuperTrend lacks the flexibility to incorporate different price sources into its calculation.
Community scripts, addressed the limitation by implementing the option to input different price sources, for example, one of the most popular publications, @KivancOzbilgic's SuperTrend script.
In May 2023, @TradingView introduced an update allowing the passing of another indicator's plot as a source value via the input.source() function. However, the built-in ta.atr function still relied on the chart's price data, limiting the formerly mentioned scripts to the chart's price data alone.
Unique Approach -
This script addresses the aforementioned limitations by processing the data differently.
Firstly we create a User-Defined-Type (UDT) replicating a bar's open, high, low, close (OHLC) values.
type bar
float o = open
float h = high
float l = low
float c = close
We then use this type to store the external input data.
src = input.source(close, "External Source")
bar b = bar.new(
nz(src ) , open 𝘷𝘢𝘭𝘶𝘦
math.max(nz(src ), src), high 𝘷𝘢𝘭𝘶𝘦
math.min(nz(src ), src), low 𝘷𝘢𝘭𝘶𝘦
src ) close 𝘷𝘢𝘭𝘶𝘦
Finally, we pass the data into our custom built SuperTrend with ATR functions to derive the external source's version of the SuperTrend indicator.
supertrend st = b.st(mlt, len)
- Setup Guide -
Utility and Use Cases:
Universal Compatibility - Apply SuperTrend to any built-in indicator or script, expanding its use beyond traditional price data.
- A simple example on one of my own public scripts -
Trend Analysis - Gain additional trend insights into otherwise mainly mean reverting or volume indicators.
- Alerts Setup Guide -
The Super Kit empowers traders and analysts with a tool that adapts the robust SuperTrend algorithm to a myriad of indicators, allowing comprehensive trend analysis and strategy development.
savitzkyGolay, KAMA, HPOverview
This trading indicator integrates three distinct analytical tools: the Savitzky-Golay Filter, Kaufman Adaptive Moving Average (KAMA), and Hodrick-Prescott (HP) Filter. It is designed to provide a comprehensive analysis of market trends and potential trading signals.
Components
Hodrick-Prescott (HP) Filter
Purpose: Smooths out the price data to identify the underlying trend.
Parameters: Lambda: Controls the smoothness. Range: 50 to 1600.
Impact of Parameters:
Increasing Lambda: This makes the trend line more responsive to short-term market fluctuations, suitable for short-term analysis. A higher Lambda value decreases the degree of smoothing, making the trend line follow recent market movements more closely.
Decreasing Lambda: A lower Lambda value makes the trend line smoother and less responsive to short-term market fluctuations, ideal for longer-term trend analysis. Decreasing Lambda increases the degree of smoothing, thereby filtering out minor market movements and focusing more on the long-term trend.
Kaufman Adaptive Moving Average (KAMA):
Purpose: An adaptive moving average that adjusts to price volatility.
Parameters: Length, Fast Length, Slow Length: Define the sensitivity and adaptiveness of KAMA.
Impact of Parameters:
Adjusting Length affects the base period for efficiency ratio, altering the overall sensitivity.
Fast Length and Slow Length control the speed of KAMA’s adaptation. A smaller Fast Length makes KAMA more sensitive to price changes, while a larger Slow Length makes it less sensitive.
Savitzky-Golay Filter:
Purpose: Smooths the price data using polynomial regression.
Parameters: Window Size: Determines the size of the moving window (7, 9, 11, 15, 21).
Impact of Parameters:
A larger Window Size results in a smoother curve, which is more effective for identifying long-term trends but can delay reaction to recent market changes.
A smaller Window Size makes the curve more responsive to short-term price movements, suitable for short-term trading strategies.
General Impact of Parameters
Adjusting these parameters can significantly alter the signals generated by the indicator. Users should fine-tune these settings based on their trading style, the characteristics of the traded asset, and market conditions to optimize the indicator's performance.
Signal Logic
Buy Signal: The trend from the HP filter is below both the KAMA and the Savitzky-Golay SMA, and none of these indicators are flat.
Sell Signal: The trend from the HP filter is above both the KAMA and the Savitzky-Golay SMA, and none of these indicators are flat.
Usage
Due to the combination of smoothing algorithms and adaptability, this indicator is highly effective at identifying emerging trends for both initiating long and short positions.
IMPORTANT : Although the code and user settings incorporate measures to limit false signals due to lateral (sideways) movement, they do not completely eliminate such occurrences. Users are strongly advised to avoid signals that emerge during simultaneous lateral movements of all three indicators.
Despite the indicator's success in historical data analysis using its signals alone, it is highly recommended to use this code in combination with other indicators, patterns, and zones. This is particularly important for determining exit points from positions, which can significantly enhance trading results.
Limitations and Recommendations
The indicator has shown excellent performance on the weekly time frame (TF) with the following settings:
Savitzky-Golay (SG): 11
Hodrick-Prescott (HP): 100
Kaufman Adaptive Moving Average (KAMA): 20, 2, 30
For the monthly TF, the recommended settings are:
SG: 15
HP: 100
KAMA: 30, 2, 35
Note: The monthly TF is quite variable. With these settings, there may be fewer signals, but they tend to be more relevant for long-term investors. Based on a sample of 40 different stocks from various countries and sectors, most exhibited an average trade return in the thousands of percent.
It's important to note that while these settings have been successful in past performance, market conditions vary and past performance is not indicative of future results. Users are encouraged to experiment with these settings and adjust them according to their individual needs and market analysis.
As this is my first developed trading indicator, I am very open to and appreciative of any suggestions or comments. Your feedback is invaluable in helping me refine and improve this tool. Please feel free to share your experiences, insights, or any recommendations you may have.
Blockchain FundamentalThis indicator is made for traders to harness fundamental blockchain data for better decision-making. Unlike traditional tools, this indicator doesn't depend on standard technical indicators. It offers a novel perspective by focusing on core blockchain metrics like capitalization, miner activity, and other intrinsic data elements. I've designed a distinct scoring logic, exclusive to BF, ensuring it's user-friendly and provides actionable insights for traders at all levels.
Mainly created for Bitcoin , but can be applied to any other crypto assets in cost of losing some metrics in the analysis.
Ethereum chart:
Features:
Customizable Moving Averages:
Choose from an array of moving averages, with the flexibility to adjust the length for a tailored analysis, aiding in pinpointing asset trends.
Blockchain Metrics Integration:
Incorporates a range of blockchain metrics such as Market Cap to Realised Cap ratio, Spent Output Profit Ratio, ATH Drawdown, and more.
Blockchain Metrics Evaluation:
Each metric can be toggled on/off to customize the analysis. Using default settings, traders can use all of the metrics combined.
Every metric is essentially evaluated on a scale from -100 to 100 and then combined with others. If any metric is uncertain about its direction (equals to 0), then the score of it is not accounted in a final calculation.
Kalman Filter:
This indicator offers the option to apply a Kalman filter to the signals, enhancing the smoothness and accuracy of the indicator’s output. This is my approach to mitigate the noise in the final output.
Signal Oscillator:
Displays the aggregated score of all selected blockchain metrics.
Offers visual signals with adjustable upper and lower bounds for easy interpretation based on particular asset observation.
Visual Elements:
Signal Oscillator:
A visual representation of the aggregated blockchain fundamental score.
(White line for a raw calculation, orange line for kalman-filtered one)
Signal Counter:
Displays the count of metrics currently being considered in the fundamental score calculation. (grey line at the middle of an indicator)
Buy/Sell Signal Coloring:
The background color changes to indicate potential buying or selling opportunities based on user-defined bounds.
Usage:
Analysis:
Use the signal oscillator to identify potential market tops and bottoms based on blockchain fundamental data.
Adjust the bounds to customize the sensitivity of buy/sell signals.
Customization:
Enable/disable specific blockchain metrics to tailor the indicator to your analytical needs.
Adjust the moving average type and length for better analysis.
Integration:
Combine with other technical indicators to create a comprehensive trading strategy.
Utilize in conjunction with volume and price action analysis for enhanced decision-making. Every output could be used in traders custom strategies and indicators.
Alxuse MACD for tutorialAll abilities of MACD, moreover :
Drawing upper band and lower band & the ability to change values, change colors, turn on/off show.
Crossing MACD line and SIGNAL line in multi timeframe & there are symbols (Circles) with green color (Buy) and red color (Sell) & the ability to change colors, turn on/off show.
Crossing MACD line and SIGNAL line in multi timeframe according to the values of upper band and lower band & there are symbols (Triangles) with green color (Long) and red color (Short) & the ability to change colors, turn on/off show.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
MACD (Moving Average Convergence/Divergence)
Definition
MACD is an extremely popular indicator used in technical analysis. MACD can be used to identify aspects of a security's overall trend. Most notably these aspects are momentum, as well as trend direction and duration. What makes MACD so informative is that it is actually the combination of two different types of indicators. First, MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
MACD Line is a result of taking a longer term EMA and subtracting it from a shorter term EMA.The most commonly used values are 26 days for the longer term EMA and 12 days for the shorter term EMA, but it is the trader's choice.
The Signal Line.
The Signal Line is an EMA of the MACD Line described in Component 1. The trader can choose what period length EMA to use for the Signal Line however 9 is the most common.
The MACD Histogram.
As time advances, the difference between the MACD Line and Signal Line will continually differ. The MACD histogram takes that difference and plots it into an easily readable histogram. The difference between the two lines oscillates around a Zero Line.
A general interpretation of MACD is that when MACD is positive and the histogram value is increasing, then upside momentum is increasing. When MACD is negative and the histogram value is decreasing, then downside momentum is increasing.
What to look for
The MACD indicator is typically good for identifying three types of basic signals; Signal Line Crossovers, Zero Line Crossovers, and Divergence.
SIGNAL LINE CROSSOVERS
A Signal Line Crossover is the most common signal produced by the MACD. First one must consider that the Signal Line is essentially an indicator of an indicator. The Signal Line is calculating the Moving Average of the MACD Line. Therefore the Signal Line lags behind the MACD line. That being said, on the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move.
The strength of the move is what determines the duration of Signal Line Crossover. Understanding and being able to analyze move strength, as well as being able to recognize false signals, is a skill that comes with experience.
The first type of Signal Line Crossover to examine is the Bullish Signal Line Crossover. Bullish Signal Line Crossovers occur when the MACD Line crosses above the Signal Line.
The second type of Signal Line Crossover to examine is the Bearish Signal Line Crossover. Bearish Signal Line Crossovers occur when the MACD Line crosses below the Signal Line.
Zero line crossovers
Zero Line Crossovers have a very similar premise to Signal Line Crossovers. Instead of crossing the Signal Line, Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0).
The first type of Zero Line Crossover to examine is the Bullish Zero Line Crossover. Bullish Zero Line Crossovers occur when the MACD Line crosses above the Zero Line and go from negative to positive.
The second type of Zero Line Crossover to examine is the Bearish Zero Line Crossover. Bearish Zero Line Crossovers occur when the MACD Line crosses below the Zero Line and go from positive to negative.
Divergence
Divergence is another signal created by the MACD. Simply put, divergence is when the MACD and actual price are not in agreement.
For example, Bullish Divergence occurs when price records a lower low, but the MACD records a higher low. The movement of price can provide evidence of the current trend, however changes in momentum as evidenced by the MACD can sometimes precede a significant reversal.
Bearish Divergence is, of course, the opposite. Bearish Divergence occurs when price records a higher high while the MACD records a lower high.
Summary
What makes the MACD such a valuable tool for technical analysis is that it is almost like two indicators in one. It can help to identify not just trends, but it can measure momentum as well. It takes two separate lagging indicators and adds the aspect of momentum which is much more active or predictive That kind of versatility is why it has been and is used by trader's and analysts across the entire spectrum of finance.
Despite MACD's obvious attributes, just like with any indicator, the trader or analyst needs to exercise caution. There are just some things that MACD doesn't do well which may tempt a trader regardless. Most notably, traders may be tempted into using MACD as a way to find overbought or oversold conditions. This is not a good idea. Remember, MACD is not bound to a range, so what is considered to be highly positive or negative for one instrument may not translate well to a different instrument.
With sufficient time and experience, almost anybody who wants to analyze chart data should be able to make good use out of the MACD.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Buy/Sell EMA CandleThis indicator is designed to display various technical indicators, candle patterns, and trend directions on a price chart. Let's break down the code and explain its different sections:
Exponential Moving Averages (EMA):
The code calculates and plots five EMAs of different lengths (13, 21, 55, 90, and 200) on the price chart. These EMAs are used to identify trends and potential crossovers.
Engulfing Candle Patterns:
The code identifies and highlights potential bullish and bearish engulfing candle patterns. It checks if the current candle's body size is larger than the combined body sizes of the previous and subsequent four candles. If this condition is met, it marks the pattern on the chart.
s3.tradingview.com
EMA Crossovers:
The code identifies and highlights points where the shorter EMA (ema1) crosses above or below the longer EMA (ema2). It plots circles to indicate these crossover points.
Candle Direction and RSI Trend:
The code determines the trend direction of the last candle based on whether it closed higher or lower than its open price. It also calculates the RSI (Relative Strength Index) and determines its trend direction (overbought, oversold, or neutral) based on predefined thresholds.
s3.tradingview.com
Table Display:
The code creates a table displaying trend directions for different timeframes (monthly, weekly, daily, 4-hour, and 1-hour) for candle direction and RSI trends. The trends are labeled with "L" for long, "S" for short, and "N/A" for not applicable.
High Volume Bars (HVB):
The code identifies and colors bars with above-average volume as either bullish or bearish based on whether the price closed higher or lower than it opened. The color and conditions for high volume bars can be customized.
s3.tradingview.com
Doji Candle Pattern:
The code identifies and marks doji candle patterns, where the open and close prices are very close to each other within a certain percentage of the candle's high-low range.
RSI-Based Candle Coloring:
The code adjusts the color of the candles based on the RSI value. If the RSI value is above the overbought threshold or below the oversold threshold, the candles are colored yellow.
Usage and Interpretation:
Traders can use this indicator to identify potential trend changes based on EMA crossovers and candle patterns like engulfing and doji.
The RSI trend direction can provide additional insight into potential overbought or oversold conditions.
High volume bars can indicate potential price reversals or continuation patterns.
The table provides an overview of trend directions on different timeframes for both candle direction and RSI trends.
Keep in mind that this is a complex indicator with multiple features. Users should carefully evaluate its performance and consider combining it with other indicators and analysis methods for more accurate trading decisions.
The table is designed to provide a consolidated view of trend directions and other indicators across multiple timeframes. It is displayed on the chart and organized into rows and columns. Each row corresponds to a specific aspect of analysis, and each column corresponds to a different timeframe.
Here's a breakdown of the components of the table:
Row 1: Separation.
Row 2 (Header Row): This row contains the headers for the columns. The headers represent the different timeframes being analyzed, such as Monthly (M), Weekly (W), Daily (D), 4-hour (4h), and 1-hour (1h).
Row 3 (Content Row): This row contains labels indicating the types of information being displayed in the columns. The labels include "T" for Trend, "C" for Current Candle, and "R" for RSI Trend.
Row 4 and Onwards: These rows display the actual data for each aspect of analysis across different timeframes.
For each aspect of analysis (Trend, Current Candle, RSI Trend), the corresponding rows display the following information:
Monthly (M): The trend direction for the given aspect on the monthly timeframe.
Weekly (W): The trend direction for the given aspect on the weekly timeframe.
Daily (D): The trend direction for the given aspect on the daily timeframe.
4-hour (4h): The trend direction for the given aspect on the 4-hour timeframe.
1-hour (1h): The trend direction for the given aspect on the 1-hour timeframe.
The trend directions are represented by labels such as "L" for Long, "S" for Short, or "N/A" for Not Applicable.
The table's purpose is to provide a quick overview of trend directions and related information across multiple timeframes, aiding traders in making informed decisions based on the analysis of trend changes and other indicators.
Price and Indicator CorrelationFIRST, CHANGE SOURCE OF INDICATOR FROM CLOSE TO WHATEVER INDICATOR YOU ARE COMPARING TO PRICE!!!!
Confirming Indicator Validity: By calculating the correlation coefficient between the price and a specific indicator, you can assess the degree to which the indicator and price move together. If there is a high positive correlation, it suggests that the indicator tends to move in the same direction as the price, increasing confidence in the indicator's validity. On the other hand, a low or negative correlation may indicate a weaker relationship between the indicator and price, signaling caution in relying solely on that indicator for trading decisions.
Identifying Divergence: Divergence occurs when the price and the indicator move in opposite directions. By monitoring the correlation coefficient, you can identify periods of divergence between the price and the selected indicator. Divergence may signal a potential reversal or significant price move, providing an opportunity to enter or exit trades.
Enhancing Trading Strategies: The correlation coefficient can be used to enhance trading strategies by incorporating the relationship between the price and the indicator. For example, if the correlation coefficient consistently shows a strong positive correlation, you may use the indicator as a confirmation tool for price-based trading signals. Conversely, if the correlation is consistently negative, it may indicate an inverse relationship that could be used for contrarian trading strategies.
Indicator Optimization : The correlation coefficient can help traders compare the effectiveness of different indicators. By calculating the correlation coefficient for multiple indicators against the price, you can identify which indicators have a stronger or weaker relationship with price movements. This information can guide the selection and optimization of indicators in your trading strategy.
Example:
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
TCG AI ToolsIntroduction:
This script is a result of an AI recommended created trading strategy that is design to offer new traders’ easy access to trend information and oversold/overbought conditions. Here we have combined commonly used indicators into a single unique visualization that quickly identifies trend changes and both RSI and Bollinger Band based overbought and oversold conditions, and allows all three indicators to be used simultaneously while taking up limited space on the chart.
The value in combining these three indicators is found in the harmony and clarity they are able to provide new traders. Trend changes can be difficult to identify based solely on candlestick analysis, therefore using the moving averages allows the trader to simplify the process of establishing bullish or bearish trends. Once a trend is established it can be very attractive for new traders to establish entries at the wrong time. For this reason, it is useful to include two different overbought and oversold indicators. The Bollinger Bands are included as one of the methods for establishing extreme prices that often result in reversals, and the relative strength index is similarly utilized as a second means to warn traders of extreme conditions.
Using the Indicator
1. MA10 MA20 Trend Indicator
The large red/green horizontal bar located at the 0 line on the X axis is the trend direction indicator. This visualization compares the 10 and 20 period moving averages to establish trend. When the MA10 is above the MA20 the trend is considered bullish and supportive of long positions and indicates such by changing the color of the horizontal bar to green. When the MA10 is below MA20 the trend is considered bearish and indicates such by changing the color of the horizontal bar to red. Color changes occur at the moment of a MA crossover/under.
2. Relative Strength Index.
The vertical red and green bars that make up the background of the panel indicate conditions wherein the RSI is considered overbought or oversold. When the vertical bar is red it indicates that RSI is below 30 suggesting that current conditions are oversold and supportive of long entries. When the vertical bar is green it suggests that the current conditions are overbought and are supportive of short entries.
3. Bollinger Band Extremes
Within the horizontal red/green bar there are red and green arrows. These arrows represent periods where the price is exceeding the upper or lower Bollinger bands and indicate overbought/oversold conditions. When a green arrow appears, it indicates that the price has crossed below the lower BB and is supportive of long entries. If a red arrow appears it indicates that the price has crossed above the upper Bollinger band and conditions are supportive of short entries.
Adaptive RSI/Stochastic (ARSIS)As a trader, one of the most important aspects of technical analysis is identifying the dominant cycle of the market. The dominant cycle, also known as the market's "heartbeat," can provide valuable information on the current market trend and potential future price movements. One way to measure the dominant cycle is through the use of the MESA Adaptation - MAMA Cycle function, which is a part of the Dominant Cycle Estimators library.
I have developed an "Adaptive RSI/Stochastic" indicator that incorporates the MAMA Cycle function to provide more accurate and reliable signals. The indicator uses the MAMA Cycle function to calculate the period of the data, which is then used as a parameter in the calculation of the RSI and Stochastic indicators. By adapting the calculation of these indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
The MAMA Cycle function is a powerful tool that utilizes advanced mathematical techniques to accurately calculate the dominant cycle of the market. It takes into account the dynamic nature of the market and adapts the calculation of the period to the current conditions. The result is a more accurate and reliable measurement of the market's dominant cycle, which can be used to improve the performance of other indicators and trading strategies.
In conclusion, the Adaptive RSI/Stochastic indicator that I have developed, which incorporates the MAMA Cycle function, is a valuable tool for any trader looking to improve their technical analysis. By adapting the calculation of the RSI and Stochastic indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
Huge thank you to @lastguru for making this possible!
Key Points of Adjoining Median (KPAM)This indicator shows more reliable overbought & oversold levels buy combing 3 different level-indicators (i.e., indicators showing overbought/oversold levels).
A median is created by adjoining two of them and then it is assisted by a third one.
This reduces noise in calculating entries when using level indicators.
Note: The extra indicator shown is "Bands Bands (BanB)"
----- HOW TO USE IT -----
Use with price-action trading and with indicators showing the overall trend.
See notes in chart for more explanation.
The high and low levels of the RSI are within a range of 2 & -2 respectively.
The high and low levels for the median range from 4 & -4 respectively.
The Discordance shows how certain the level of the median is.
For example, if a part of the Discordance touches a low level while the median is at a higher level, then it usually indicates that the median is about to reverse.
The more Discordance that is visible, the less certain the current trend of the median is.
----- HOW THIS INDICATOR IS ORIGINAL; WHAT IT DOES AND HOW IT DOES IT -----
This indicator has an original, unique ability to reduce noise when comparing overbought and oversold levels.
It does this by first adjoining the Stochastic and the Stochastic RSI. Second, it creates a median from the two.
Third, the median is compared to the RSI on the same scale to assist in deciding where the median is at in relation to itself.
It shows whether the median lows and highs are near overbought or oversold levels.
----- VERSION -----
This is not a variant of the Stochastic, Stochastic RSI, and/or the RSI.
The focus is on the median that is created by an adjoining of the Stochastic and Stochastic RSI.
The Stochastic and Stochastic RSI are needed in order to obtain and plot the Median and the Discordance.
The RSI is plotted on the same scale to serve as the comparison needed to evaluate the Median levels with more visual accuracy.
TriexDev - SuperBuySellTrend (PLUS+)Minimal but powerful.
Have been using this for myself, so thought it would be nice to share publicly. Of course no script is correct 100% of the time, but this is one of if not the best in my basic tools. (This is the expanded/PLUS version)
Github Link for latest/most detailed + tidier documentation
Base Indicator - Script Link
TriexDev - SuperBuySellTrend (SBST+) TradingView Trend Indicator
---
SBST Plus+
Using the "plus" version is optional, if you only want the buy/sell signals - use the "base" version.
## What are vector candles?
Vector Candles (inspired to add from TradersReality/MT4) are candles that are colour coded to indicate higher volumes, and likely flip points / direction changes, or confirmations.
These are based off of PVSRA (Price, Volume, Support, Resistance Analysis).
You can also override the currency that this runs off of, including multiple ones - however adding more may slow things down.
PVSRA - From MT4 source:
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, and bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colours: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colours: Bull bars are blue and bear are blue-violet.
A blue or purple bar can mean the chart has reached a top or bottom.
High volume bars during a movement can indicate a big movement is coming - or a top/bottom if bulls/bears are unable to break that point - or the volume direction has flipped.
This can also just be a healthy short term movement in the opposite direction - but at times sets obvious trend shifts.
## Volume Tracking
You can shift-click any candle to get the volume of that candle (in the pair token/stock), if you click and drag - you will see the volume for that range.
## Bollinger Bands
Bollinger Bands can be enabled in the settings via the toggle.
Bollinger Bands are designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold (bottom lines) or overbought (top lines).
>There are three lines that compose Bollinger Bands: A simple moving average (middle band) and an upper and lower band.
>The upper and lower bands are typically 2 standard deviations +/- from a 20-day simple moving average, but they can be modified.
---
Base Indicator
## What is ATR?
The average true range (ATR) is a technical analysis indicator, which measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following:
- current high - the current low;
- the absolute value of the current high - the previous close;
- and the absolute value of the current low - the previous close.
The ATR is then a moving average, generally using 10/14 days, of the true ranges.
## What does this indicator do?
Uses the ATR and multipliers to help you predict price volatility, ranges and trend direction.
> The buy and sell signals are generated when the indicator starts
plotting either on top of the closing price or below the closing price. A buy signal is generated when the ‘Supertrend’ closes above the price and a sell signal is generated when it closes below the closing price.
> It also suggests that the trend is shifting from descending mode to ascending mode. Contrary to this, when a ‘Supertrend’ closes above the price, it generates a sell signal as the colour of the indicator changes into red.
> A ‘Supertrend’ indicator can be used on equities, futures or forex, or even crypto markets and also on daily, weekly and hourly charts as well, but generally, it will be less effective in a sideways-moving market.
Thanks to KivancOzbilgic who made the original SuperTrend Indicator this was based off
---
## Usage Notes
Two indicators will appear, the default ATR multipliers are already set for what I believe to be perfect for this particular (double indicator) strategy.
If you want to break it yourself (I couldn't find anything that tested more accurately myself), you can do so in the settings once you have added the indicator.
Basic rundown:
- A single Buy/Sell indicator in the dim colour; may be setting a direction change, or just healthy movement.
- When the brighter Buy/Sell indicator appears; it often means that a change in direction (uptrend or downtrend) is confirmed.
---
You can see here, there was a (brighter) green indicator which flipped down then up into a (brighter) red sell indicator which set the downtrend. At the end it looks like it may be starting to break the downtrend - as the price is hitting the trend line. (Would watch for whether it holds above or drops below at that point)
Another example, showing how sometimes it can still be correct but take some time to play out - with some arrow indicators.
Typically I would also look at oscillators, RSI and other things to confirm - but here it held above the trend lines nicely, so it appeared to be rather obvious.
It's worth paying attention to the trend lines and where the candles are sitting.
Once you understand/get a feel for the basics of how it works - it can become a very useful tool in your trading arsenal.
Also works for traditional markets & commodities etc in the same way / using the same ATR multipliers, however of course crypto generally has bigger moves.
---
You can use this and other indicators to confirm likeliness of a direction change prior to the brighter/confirmation one appearing - but just going by the 2nd(brighter) indicators, I have found it to be surprisingly accurate.
Tends to work well on virtually all timeframes, but personally prefer to use it on 5min,15min,1hr, 4hr, daily, weekly. Will still work for shorter/other timeframes, but may be more accurate on mid ones.
---
This will likely be updated as I go / find useful additions that don't convolute things. The base indicator may be updated with some limited / toggle-able features in future also.
Digital Kahler Stochastic [Loxx]Digital Kahler Stochastic is a Digital Kahler filtered Stochastic. This modification significantly reduces noise.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
Calculation
The calculation is simple
Step1: create the CCI
Step 2: Use CCI as Fast MA and smoothed CCI as Slow MA
Step 3: Multiple the Slow and Fast MAs by their respective input ratios, and then divide by their sum. if the result is greater than 0, then the result is 1, if it's less than 0 then the result is -1, then chart the data
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) > 50.0)
temp := 1
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) < 50.0)
temp := -1
Step 4: Profit
Other implementations of Digital Kahler
This is to better understand the process the DK process and it's result, and furthermore, I'm linking these because for many in the Forex community, they see DK filtered indicators as the best implementations of standard indicators.
Digital Kahler MACD
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones
Digital Kahler CCI
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Digital Kahler CCI [Loxx]Digital Kahler CCI is a Digital Kahler filtered CCI. This modification significantly reduces noise.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
Calculation
The calculation is simple
Step1 : create the CCI
Step 2 : Use CCI as Fast MA and smoothed CCI as Slow MA
Step 3 : Multiple the Slow and Fast MAs by their respective input ratios, and then divide by their sum. if the result is greater than 0, then the result is 1, if it's less than 0 then the result is -1, then chart the data
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) > 50.0)
temp := 1
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) < 50.0)
temp := -1
Step 4 : Profit
Other implementations of Digital Kahler
This is to better understand the process the DK process and it's result, and furthermore, I'm linking these because for many in the Forex community, they see DK filtered indicators as the best implementations of standard indicators.
MACD
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones [Loxx]VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones is an RSI indicator with adaptive inputs, Digital Kahler filtering, and Dynamic Zones. This indicator uses a Vertical Horizontal Filter for calculating the adaptive period inputs and allows the user to select from 7 different types of RSI.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
4 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Loxx's Variety RSI
Loxx's Dynamic Zones
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications.
________________________________________________________________
Included moving averages
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA, it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA.
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average (DEMA) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA. It's also considered a leading indicator compared to the EMA, and is best utilized whenever smoothness and speed of reaction to market changes are required.
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA (Simple Moving Average). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA.
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Hull Moving Average - HMA
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points.
IE/2 - Early T3 by Tim Tilson
The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator".
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA (Simple Moving Average) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA (Least Squares Moving Average)
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA. Although it's similar to the Simple Moving Average, the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track price better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average. The Linear Weighted Moving Average calculates the average by assigning different weight to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrows price.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA.
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average (SMA), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen a an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA (Smoothed Moving Average). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA. They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
The TMA and Sine Weighted Moving Average Filter are almost identical at times.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, it's signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers.
Volume Weighted EMA - VEMA
Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements.
Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings.
Zero Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers, as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA, this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
________________________________________________________________
What are Heiken Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following:
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Expanded generic source types:
Close = close
Open = open
High = high
Low = low
Median = hl2
Typical = hlc3
Weighted = hlcc4
Average = ohlc4
Average Median Body = (open+close)/2
Trend Biased = (see code, too complex to explain here)
Trend Biased (extreme) = (see code, too complex to explain here)
Included:
-Toggle bar color on/off
-Toggle signal line on/off
SUPERTREND MIXED ICHI-DMI-DONCHIAN-VOL-GAP-HLBox@RLSUPERTREND MIXED ICHI-DMI-VOL-GAP-HLBox@RL
by RegisL76
This script is based on several trend indicators.
* ICHIMOKU (KINKO HYO)
* DMI (Directional Movement Index)
* SUPERTREND ICHIMOKU + SUPERTREND DMI
* DONCHIAN CANAL Optimized with Colored Bars
* HMA Hull
* Fair Value GAP
* VOLUME/ MA Volume
* PRICE / MA Price
* HHLL BOXES
All these indications are visible simultaneously on a single graph. A data table summarizes all the important information to make a good trade decision.
ICHIMOKU Indicator:
The ICHIMOKU indicator is visualized in the traditional way.
ICHIMOKU standard setting values are respected but modifiable. (Traditional defaults = .
An oriented visual symbol, near the last value, indicates the progression (Ascending, Descending or neutral) of the TENKAN-SEN and the KIJUN-SEN as well as the period used.
The CLOUD (KUMO) and the CHIKOU-SPAN are present and are essential for the complete analysis of the ICHIMOKU.
At the top of the graph are visually represented the crossings of the TENKAN and the KIJUN.
Vertical lines, accompanied by labels, make it possible to quickly visualize the particularities of the ICHIMOKU.
A line displays the current bar.
A line visualizes the end of the CLOUD (KUMO) which is shifted 25 bars into the future.
A line visualizes the end of the chikou-span, which is shifted 25 bars in the past.
DIRECTIONAL MOVEMENT INDEX (DMI) : Treated conventionally : DI+, DI-, ADX and associated with a SUPERTREND DMI.
A visual symbol at the bottom of the graph indicates DI+ and DI- crossings
A line of oriented and colored symbols (DMI Line) at the top of the chart indicates the direction and strength of the trend.
SUPERTREND ICHIMOKU + SUPERTREND DMI :
Trend following by SUPERTREND calculation.
DONCHIAN CHANNEL: Treated conventionally. (And optimized by colored bars when overshooting either up or down.
The lines, high and low of the last values of the channel are represented to quickly visualize the level of the RANGE.
SUPERTREND HMA (HULL) Treated conventionally.
The HMA line visually indicates, according to color and direction, the market trend.
A visual symbol at the bottom of the chart indicates opportunities to sell and buy.
VOLUME:
Calculation of the MOBILE AVERAGE of the volume with comparison of the volume compared to the moving average of the volume.
The indications are colored and commented according to the comparison.
PRICE: Calculation of the MOBILE AVERAGE of the price with comparison of the price compared to the moving average of the price.
The indications are colored and commented according to the comparison.
HHLL BOXES:
Visualizes in the form of a box, for a given period, the max high and min low values of the price.
The configuration allows taking into account the high and low wicks of the price or the opening and closing values.
FAIR VALUE GAP :
This indicator displays 'GAP' levels over the current time period and an optional higher time period.
The script takes into account the high/low values of the current bar and compares with the 2 previous bars.
The "gap" is generated from the lack of overlap between these bars. Bearish or bullish gaps are determined by whether the gap is above or below HmaPrice, as they tend to fill, and can be used as targets.
NOTE: FAIR VALUE GAP has no values displayed in the table and/or label.
Important information (DATA) relating to each indicator is displayed in real time in a table and/or a label.
Each information is commented and colored according to direction, value, comparison etc.
Each piece of information indicates the values of the current bar and the previous value (in "FULL" mode).
The other possible modes for viewing the table and/or the label allow a more synthetic view of the information ("CONDENSED" and "MINIMAL" modes).
In order not to overload the vision of the chart too much, the visualization box of the RANGE DONCHIAN, the vertical lines of the shifted marks of the ICHIMOKU, as well as the boxes of the HHLL Boxes indicator are only visualized intermittently (managed by an adjustable time delay ).
The "HISTORICAL INFO READING" configuration parameter set to zero (by default) makes it possible to read all the information of the current bar in progress (Bar #0). All other values allow to read the information of a historical bar. The value 1 reads the information of the bar preceding the current bar (-1). The value 10 makes it possible to read the information of the tenth bar behind (-10) compared to the current bar, etc.
At the bottom of the DATAS table and label, lights, red, green or white indicate quickly summarize the trend from the various indicators.
Each light represents the number of indicators with the same trend at a given time.
Green for a bullish trend, red for a bearish trend and white for a neutral trend.
The conditions for determining a trend are for each indicator:
SUPERTREND ICHIMOHU + DMI: the 2 Super trends together are either bullish or bearish.
Otherwise the signal is neutral.
DMI: 2 main conditions:
BULLISH if DI+ >= DI- and ADX >25.
BEARISH if DI+ < DI- and ADX >25.
NEUTRAL if the 2 conditions are not met.
ICHIMOKU: 3 main conditions:
BULLISH if PRICE above the cloud and TENKAN > KIJUN and GREEN CLOUD AHEAD.
BEARISH if PRICE below the cloud and TENKAN < KIJUN and RED CLOUD AHEAD.
The other additional conditions (Data) complete the analysis and are present for informational purposes of the trend and depend on the context.
DONCHIAN CHANNEL: 1 main condition:
BULLISH: the price has crossed above the HIGH DC line.
BEARISH: the price has gone below the LOW DC line.
NEUTRAL if the price is between the HIGH DC and LOW DC lines
The 2 other complementary conditions (Datas) complete the analysis:
HIGH DC and LOW DC are increasing, falling or stable.
SUPERTREND HMA HULL: The script determines several trend levels:
STRONG BUY, BUY, STRONG SELL, SELL AND NEUTRAL.
VOLUME: 3 trend levels:
VOLUME > MOVING AVERAGE,
VOLUME < MOVING AVERAGE,
VOLUME = MOVING AVERAGE.
PRICE: 3 trend levels:
PRICE > MOVING AVERAGE,
PRICE < MOVING AVERAGE,
PRICE = MOVING AVERAGE.
If you are using this indicator/strategy and you are satisfied with the results, you can possibly make a donation (a coffee, a pizza or more...) via paypal to: lebourg.regis@free.fr.
Thanks in advance !!!
Have good winning Trades.
**************************************************************************************************************************
SUPERTREND MIXED ICHI-DMI-VOL-GAP-HLBox@RL
by RegisL76
Ce script est basé sur plusieurs indicateurs de tendance.
* ICHIMOKU (KINKO HYO)
* DMI (Directional Movement Index)
* SUPERTREND ICHIMOKU + SUPERTREND DMI
* DONCHIAN CANAL Optimized with Colored Bars
* HMA Hull
* Fair Value GAP
* VOLUME/ MA Volume
* PRIX / MA Prix
* HHLL BOXES
Toutes ces indications sont visibles simultanément sur un seul et même graphique.
Un tableau de données récapitule toutes les informations importantes pour prendre une bonne décision de Trade.
I- Indicateur ICHIMOKU :
L’indicateur ICHIMOKU est visualisé de manière traditionnelle
Les valeurs de réglage standard ICHIMOKU sont respectées mais modifiables. (Valeurs traditionnelles par défaut =
Un symbole visuel orienté, à proximité de la dernière valeur, indique la progression (Montant, Descendant ou neutre) de la TENKAN-SEN et de la KIJUN-SEN ainsi que la période utilisée.
Le NUAGE (KUMO) et la CHIKOU-SPAN sont bien présents et sont primordiaux pour l'analyse complète de l'ICHIMOKU.
En haut du graphique sont représentés visuellement les croisements de la TENKAN et de la KIJUN.
Des lignes verticales, accompagnées d'étiquettes, permettent de visualiser rapidement les particularités de l'ICHIMOKU.
Une ligne visualise la barre en cours.
Une ligne visualise l'extrémité du NUAGE (KUMO) qui est décalé de 25 barres dans le futur.
Une ligne visualise l'extrémité de la chikou-span, qui est décalée de 25 barres dans le passé.
II-DIRECTIONAL MOVEMENT INDEX (DMI)
Traité de manière conventionnelle : DI+, DI-, ADX et associé à un SUPERTREND DMI
Un symbole visuel en bas du graphique indique les croisements DI+ et DI-
Une ligne de symboles orientés et colorés (DMI Line) en haut du graphique, indique la direction et la puissance de la tendance.
III SUPERTREND ICHIMOKU + SUPERTREND DMI
Suivi de tendance par calcul SUPERTREND
IV- DONCHIAN CANAL :
Traité de manière conventionnelle.
(Et optimisé par des barres colorées en cas de dépassement soit vers le haut, soit vers le bas.
Les lignes, haute et basse des dernières valeurs du canal sont représentées pour visualiser rapidement la fourchette du RANGE.
V- SUPERTREND HMA (HULL)
Traité de manière conventionnelle.
La ligne HMA indique visuellement, selon la couleur et l'orientation, la tendance du marché.
Un symbole visuel en bas du graphique indique les opportunités de vente et d'achat.
*VI VOLUME :
Calcul de la MOYENNE MOBILE du volume avec comparaison du volume par rapport à la moyenne mobile du volume.
Les indications sont colorées et commentées en fonction de la comparaison.
*VII PRIX :
Calcul de la MOYENNE MOBILE du prix avec comparaison du prix par rapport à la moyenne mobile du prix.
Les indications sont colorées et commentées en fonction de la comparaison.
*VIII HHLL BOXES :
Visualise sous forme de boite, pour une période donnée, les valeurs max hautes et min basses du prix.
La configuration permet de prendre en compte les mèches hautes et basses du prix ou bien les valeurs d'ouverture et de fermeture.
IX - FAIR VALUE GAP
Cet indicateur affiche les niveaux de 'GAP' sur la période temporelle actuelle ET une période temporelle facultative supérieure.
Le script prend en compte les valeurs haut/bas de la barre actuelle et compare avec les 2 barres précédentes.
Le "gap" est généré à partir du manque de recouvrement entre ces barres.
Les écarts baissiers ou haussiers sont déterminés selon que l'écart est supérieurs ou inférieur à HmaPrice, car ils ont tendance à être comblés, et peuvent être utilisés comme cibles.
NOTA : FAIR VALUE GAP n'a pas de valeurs affichées dans la table et/ou l'étiquette.
Les informations importantes (DATAS) relatives à chaque indicateur sont visualisées en temps réel dans une table et/ou une étiquette.
Chaque information est commentée et colorée en fonction de la direction, de la valeur, de la comparaison etc.
Chaque information indique la valeurs de la barre en cours et la valeur précédente ( en mode "COMPLET").
Les autres modes possibles pour visualiser la table et/ou l'étiquette, permettent une vue plus synthétique des informations (modes "CONDENSÉ" et "MINIMAL").
Afin de ne pas trop surcharger la vision du graphique, la boite de visualisation du RANGE DONCHIAN, les lignes verticales des marques décalées de l'ICHIMOKU, ainsi que les boites de l'indicateur HHLL Boxes ne sont visualisées que de manière intermittente (géré par une temporisation réglable ).
Le paramètre de configuration "HISTORICAL INFO READING" réglé sur zéro (par défaut) permet de lire toutes les informations de la barre actuelle en cours (Barre #0).
Toutes autres valeurs permet de lire les informations d'une barre historique. La valeur 1 permet de lire les informations de la barre précédant la barre en cours (-1).
La valeur 10 permet de lire les information de la dixième barre en arrière (-10) par rapport à la barre en cours, etc.
Dans le bas de la table et de l'étiquette de DATAS, des voyants, rouge, vert ou blanc indique de manière rapide la synthèse de la tendance issue des différents indicateurs.
Chaque voyant représente le nombre d'indicateur ayant la même tendance à un instant donné. Vert pour une tendance Bullish, rouge pour une tendance Bearish et blanc pour une tendance neutre.
Les conditions pour déterminer une tendance sont pour chaque indicateur :
SUPERTREND ICHIMOHU + DMI : les 2 Super trends sont ensemble soit bullish soit Bearish. Sinon le signal est neutre.
DMI : 2 conditions principales :
BULLISH si DI+ >= DI- et ADX >25.
BEARISH si DI+ < DI- et ADX >25.
NEUTRE si les 2 conditions ne sont pas remplies.
ICHIMOKU : 3 conditions principales :
BULLISH si PRIX au dessus du nuage et TENKAN > KIJUN et NUAGE VERT DEVANT.
BEARISH si PRIX en dessous du nuage et TENKAN < KIJUN et NUAGE ROUGE DEVANT.
Les autres conditions complémentaires (Datas) complètent l'analyse et sont présents à titre informatif de la tendance et dépendent du contexte.
CANAL DONCHIAN : 1 condition principale :
BULLISH : le prix est passé au dessus de la ligne HIGH DC.
BEARISH : le prix est passé au dessous de la ligne LOW DC.
NEUTRE si le prix se situe entre les lignes HIGH DC et LOW DC
Les 2 autres conditions complémentaires (Datas) complètent l'analyse : HIGH DC et LOW DC sont croissants, descendants ou stables.
SUPERTREND HMA HULL :
Le script détermine plusieurs niveaux de tendance :
STRONG BUY, BUY, STRONG SELL, SELL ET NEUTRE.
VOLUME : 3 niveaux de tendance :
VOLUME > MOYENNE MOBILE, VOLUME < MOYENNE MOBILE, VOLUME = MOYENNE MOBILE.
PRIX : 3 niveaux de tendance :
PRIX > MOYENNE MOBILE, PRIX < MOYENNE MOBILE, PRIX = MOYENNE MOBILE.
Si vous utilisez cet indicateur/ stratégie et que vous êtes satisfait des résultats,
vous pouvez éventuellement me faire un don (un café, une pizza ou plus ...) via paypal à : lebourg.regis@free.fr.
Merci d'avance !!!
Ayez de bons Trades gagnants.
Jurik CFB Adaptive, Elder Force Index w/ ATR Channels [Loxx]Jurik CFB Adaptive, Elder Force Index w/ ATR Channels is a variation of Elder Force Index that better adapts to trends by calculating dynamic lengths for the traditional Elder Force Index calculation. ATR channels are added to show levels of price extremes or exhaustion of price either up or down. Elder Force Index is typically used for spotting reversals on the weekly timeframe.
What is the Elder Force Index?
Dr. Alexander Elder is one of the contributors to a newer generation of technical indicators. His force index is an oscillator that measures the force, or power, of bulls behind particular market rallies and of bears behind every decline.1
The three key components of the force index are the direction of price change, the extent of the price change, and the trading volume. When the force index is used in conjunction with a moving average, the resulting figure can accurately measure significant changes in the power of bulls and bears.1 In this way, Elder has taken an extremely useful solitary indicator, the moving average, and combined it with his force index for even greater predictive success.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Adaptive Qualitative Quantitative Estimation (QQE) [Loxx]Adaptive QQE is a fixed and cycle adaptive version of the popular Qualitative Quantitative Estimation (QQE) used by forex traders. This indicator includes varoius types of RSI caculations and adaptive cycle measurements to find tune your signal.
Qualitative Quantitative Estimation (QQE):
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index (RSI) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
Wilders' RSI:
The Relative Strength Index ( RSI ) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI , when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
RSX RSI:
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
Rapid RSI:
Rapid RSI Indicator, from Ian Copsey's article in the October 2006 issue of Stocks & Commodities magazine.
RapidRSI resembles Wilder's RSI , but uses a SMA instead of a WilderMA for internal smoothing of price change accumulators.
VHF Adaptive Cycle:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Band-pass Adaptive Cycle:
Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode.
There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility.
We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month.
When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth.
Included:
-Toggle on/off bar coloring
-Customize RSI signal using fixed, VHF Adaptive, and Band-pass Adaptive calculations
-Choose from three different RSI types
Visuals:
-Red/Green line is the moving average of RSI
-Thin white line is the fast trend
-Dotted yellow line is the slow trend
Happy trading!
Template Signal IndicatorThis script is an example on how to create a custom indicator that produce start/end long/short deal signals based on configurable conditions from internal and external indicators.
This indicator can be used as an external indicator to other strategies like "Template Trailing Strategy" that will execute the deals and enter the desired positions based on the signals produced by this script.
Combining this script with the aforementioned strategy (or any other compatible) has the advantage that you can backrest the results of your custom deal conditions. Also additional functionality that is provided by the strategy can be utilized (e.g. Take Profit Targets, Trailing Stop Loss etc.).
In this particular example I combined the RSI and Stoch RSI indicators (internal) with the "Trend Explorer" indicator (external) so it produces buy and sell signals based on the logic I defined in the input tab of this indicator. To combine "indicators on indicators" you need Pro+ TV subscription.
The convention I use to communicate the signals is the following (2 -> enter long, 1 -> exit long, -2 -> enter short, -1 ->exit short). However, this convention is also configurable in the consumer/strategy script "Template Trailing Strategy" so make sure that both script "speak the same language" before procced.
