Rolling Volatility Indicator
Description :
The Rolling Volatility indicator calculates the volatility of an asset's price movements over a specified period. It measures the degree of variation in the price series over time, providing insights into the market's potential for price fluctuations.
This indicator utilizes a rolling window approach, computing the volatility by analyzing the logarithmic returns of the asset's price. The user-defined length parameter determines the timeframe for the volatility calculation.
How to Use :
Adjust the "Length" parameter to set the rolling window period for volatility calculation.
Ajust "trading_days" for the sampling period, this is the total number of trading days (usually 252 days for stocks and 365 for crypto)
Higher values for the length parameter will result in a smoother, longer-term view of volatility, while lower values will provide a more reactive, shorter-term perspective.
Volatility levels can assist in identifying periods of increased market activity or potential price changes. Higher volatility may suggest increased risk and potential opportunities, while lower volatility might indicate periods of reduced market activity.
Key Features :
Customizable length parameter for adjusting the calculation period and trading days such that it can also be applied to stock market or any markets.
Visual representation of volatility with a plotted line on the chart.
The Rolling Volatility indicator can be a valuable tool for traders and analysts seeking insights into market volatility trends, aiding in decision-making processes and risk management strategies.
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MacroTrend VisionThe "MacroTrend Vision" indicator is crafted with a singular goal – to provide traders with a quick and insightful snapshot of a country's global index. Seamlessly combining macroeconomic and technical perspectives, this tool is designed for those seeking a straightforward yet comprehensive overview. Let's explore the key features that make the "MacroTrend Vision" a valuable asset for traders looking to grasp both the big-picture economic context and technical nuances.
1. Long-Term Vision with Weekly Periods:
Gain a genuine long-term perspective with the ability to process 2500 weekly periods. This feature ensures a holistic understanding of global indices from both macroeconomic and technical viewpoints.
2. Composite Leading Indicator (CLI) Conditions:
Integrate both macroeconomic trends and technical signals through Composite Leading Indicator (CLI) conditions derived from the Relative Strength Index (RSI), offering a comprehensive outlook for informed decision-making.
3. Deviation Bands for Volatility Analysis:
Refine market analysis with strategically integrated deviation bands (0.2 and 0.4) based on smoothed linear regression. Anticipate volatility and potential trend shifts, aligning macro and technical insights.
4. Logarithmic Scale Transformation:
Enhance precision in understanding price movements with a logarithmic scale transformation, especially beneficial for assets with exponential growth patterns.
5. Separated Window for Easy Navigation:
Streamline your analysis with a user-friendly design – a separated window allowing easy navigation through different symbols without altering indicator settings.
6. Alert System for CLI Conditions:
Stay informed about critical shifts with an alert system for both long and close conditions based on the RSI of the CLI. Even during periods of limited chart monitoring, this feature keeps you connected to macroeconomic and technical changes.
In essence, the "MacroTrend Vision" is your go-to tool for a balanced view, simplifying the complexities of global indices with a blend of macroeconomic insights and technical clarity.
Range Detector [LuxAlgo]The Range Detector indicator aims to detect and highlight intervals where prices are ranging. The extremities of the ranges are highlighted in real-time, with breakouts being indicated by the color changes of the extremities.
🔶 USAGE
Ranging prices are defined by a period of stationarity, that is where prices move within a specific range.
Detecting ranging markets is a common task performed manually by traders. Price breaking one of the extremities of a range can be indicative of a new trend, with an uptrend if price breaks the upper range extremity, and a downtrend if price breaks the lower range extremity.
Ranges are highlighted as zones and are set retrospectively, that is the starting point of a range is offset in the past. The exact moment a range is detected is highlighted by a gray background color. The average between the maximum/minimum of a zone is also highlighted as a dotted line and is also set retrospectively.
The range extremities are set in real-time, blue extremities indicate the range extremities were not broken, green extremities indicate that price broke the upper range extremity, while red extremities indicate price broke the lower range extremity.
Extremities are extended until a new range is detected, allowing past ranges extremities can be used as future support/resistances.
🔶 DETAILS
The detection algorithm used to detect ranges tests if all the prices within a user-set window are all within two extremities. These extremities are determined by the mean of the detection window plus/minus an ATR value.
When a new range is detected, the script checks if this new range overlaps with a previously detected range, if this is the case, both ranges are merged into one; updating the extremities of the previous range.
This can be observed with the real-time extremities changing within a highlighted zone.
🔶 SETTINGS
Minimum Range Length: Minimum amount of bars needed to detect a range.
Range Width: Multiplicative factor for the ATR used to detect new ranges. Lower values detect ranges with a lower width. Using higher values might return false positives.
ATR Length: ATR length used to determine the range width.
Histogram-based price zonesThis indicator provides a new approach to creating price zones that can be used as support and resistance. The approach does not use pivot points or Fibonacci levels. Instead, it uses the frequency of occurence of local maxima and minima to determine zones of interest where price often changed direction.
The algorithm is as follows:
- Gather price data from the last Lookback trading periods
- Calculate rolling minima and rolling maxima along the price points with window size Window size
- Build a histogram from the rolling extrema which are binned into different zones. The number of bins and therefore the width of a zone can be adjusted with the parameter Zone width factor
- Select only the top fullest bins. The number of bins selected for plotting can be controlled with Zone multiplier
The result are a number of boxes that appear on the chart which mark levels of interest to watch for. You can combine multiple instances of this indicator on different settings to find zones that are very relevant.
Shown as an example is the Nasdaq 100 futures ( NQ1! ) on the D timeframe with levels built from the last 100 periods with default settings. The boxes are the only output of the indicator, no signals are created.
Supertrend Targets [ChartPrime]The Supertrend Targets indicator combines the concepts of trend-following with dynamic volatility-based target levels. It takes core simple and classical concepts and provides actionable insights. The core of this indicator revolves around the "Supertrend" algorithm, which essentially uses the Average True Range (ATR) and a multiplier to determine if the price of a financial instrument is in an uptrend or downtrend. The indicator generates various plot points on the trading chart, which traders can use to make informed trading decisions.
Users can set several input parameters such as the source price, custom levels, multiplier scale, length of the average true range, and the window length. Traders can also opt to enable a table that shows numeric target data by percentiles, risk ratio, take profit and stop loss points.
The generated plots and fills on the chart represent various levels of potential gains and drawdowns, acting as potential targets for taking profit or stopping losses. These include the 25th, 50th, 75th, 90th, and 100th percentiles, which are adjustable by scale. There are also plots for average gain and drawdown levels, enhanced by standard deviation curves if enabled.
The Supertrend line indicators are color-coded for ease of understanding: blue for bullish performance and orange for bearish performance. The "Center Line" represents the point at which traders might consider entering a position.
Lastly, the script presents a summary table (when enabled) at the right side of the chart displaying numeric data of the plotted targets. This data provides additional insights on the risk-reward balance for each percentile, helping traders to execute their strategies more effectively.
Here's a comprehensive breakdown of its functionalities and features:
Inputs:
Source: Determines the price series type (e.g., Close, Open, High, Low, etc.).
Show Trailing Stop: Option to display the trailing stop on the chart.
Levels: Sets the number of target levels you want to display. Can range from -5 to 5.
Scale: A scaling factor for adjusting targets, can be between 1 to 100.
Window Length: Length for the target computation, determines how many bars will be considered.
Unique: Ensures every data point used in calculations is unique.
Multiplier: Multiplier for the ATR (Average True Range) to compute the SuperTrend.
ATR Length: Period for the ATR computation.
Custom Level: Allows users to set their own levels using various statistics like Average, Average + STDEV, Percentile, or can be disabled.
Percent Rank: Determines the percentile rank for targeting.
Enable Table: Enables or disables a table display.
Methods:
Flag: Identifies bullish and bearish trend reversals.
Target Percent: Determines the expected price movement (both gains and drawdowns) based on historical trend reversals.
Value Percent: Computes the percentage difference between the current price and the entry price during trend reversals.
Plots:
Multiple target lines are plotted on the chart to visualize potential gain and drawdown levels. These levels are adjusted based on user settings. Additionally, the main Supertrend line is plotted to indicate the prevailing trend direction.
Gain Levels: Target levels which show potential upside from the current price.
Drawdown Levels: Target levels which represent potential downside from the current price.
SuperTrend Line: A line that adjusts based on price volatility and trend direction, acting as a dynamic support or resistance.
In conclusion, the "Supertrend Targets " indicator is a powerful tool that combines the principle of trend-following with dynamic targets, providing traders with insights into potential future price movements. The range of customization options allows traders to adapt the indicator to different trading strategies and market conditions.
RiskToolsLibrary "RiskTools"
Provides functions for calculating risk metrics
pctDrop(start, result)
Calculates what is the percentage drop from a reference price
Parameters:
start (float) : Starting price before the drop occurred
result (float) : Resulting price to which the percentage drop occurred
Returns: Percentage drop from "start" to "result"
priceBeforeDrop(pctDrop, result)
Calculates a starting price given a resulting price and a percentage drop to that price
Parameters:
pctDrop (float) : Percentage drop
result (float) : Resulting price to which the percentage drop occurred
Returns: The starting price from which a percentage drop "pctDrop" gave a "result"
dropzone(price, masource, malength, window, zonesize)
Calculates drop zone as an integer representing some multiple of the "zoning size"
Parameters:
price (float) : The current price from which you want to calculate the drop zone
masource (float) : The source series used in the SMA calculation from which the floor price is determined
malength (simple int) : The length used in the SMA calculation from which the floor price is determined
window (simple int) : The lookback period from which to calculate the floor price
zonesize (simple int)
Returns: The zone identifier as a multiple of the zone size. A value of zero or less is translated to the first zone.
OBV Oscillator Volume FilterOBV Oscillator Volume Filter
Introduction
The On-Balance Volume (OBV) is a widely-used technical indicator that aims to relate price and volume in trading. Price and volume are two of the most basic and yet crucial concepts in price movement. Together, they can reveal a lot about the instruments trends and the market's sentiment. This On Balance Volume (OBV) Oscillator incorporates enhanced features like a volume filter using a rolling window to detect outliers in accumulated volume, making it an advanced and more refined version of the standard OBV.
Interpreting the OBV Indicator
The primary function of the OBV is to accumulate volume. In simpler terms:
When the market closes higher than the previous candle, all of that candle's volume is considered 'up-volume'.
Conversely, when the market closes lower than the previous day, all of that candle's volume is considered 'down-volume'.
A rising OBV suggests that volume is being accumulated, indicating bullish market sentiment. A declining OBV, on the other hand, points to a bearish sentiment.
Features of the Script
1. Moving Averages Selection:
The script provides users with the option to select among six types of moving averages (EMA, DEMA, TEMA, SMA, WMA, HMA) to calculate the OBV. This feature offers flexibility and enables traders to choose an MA type they're most comfortable with or find the most effective.
2. Smoothing Option:
To reduce the inherent noise in the indicator, there's an option to apply smoothing. It uses a Simple Moving Average (SMA) to produce a clearer signal, making it easier for traders to interpret and respond to. If you don't want to use smoothing, just simply change the input length of smoothing to 1 in the settings.
3. Outlier Detection:
One of the standout features is the use of a rolling window to detect volume outliers. This ensures that the OBV only reacts to significant volume changes and isn't overly influenced by random spikes or drops. The volume filter is calculated based on a % of the highest OBV volume of X number of bars back. Users can adjust the time (# bars) and the sensitivity (%) of the volume filter. A longer timeperiode (# bars) and a higher % (sensitivity) in the settings result to less signals presented by the indicator.
4. Divergence Detection:
The script automatically highlights both regular and hidden divergences on the chart. Divergences can be a powerful signal of potential price reversals. This feature aids traders in spotting potential buy or sell opportunities based on divergences between price and OBV.
Regular Bullish Divergence: When the price makes lower lows, but the OBV makes higher lows.
Hidden Bullish Divergence: When the price makes higher lows, but the OBV makes lower lows.
Regular Bearish Divergence: When the price makes higher highs, but the OBV makes lower highs.
Hidden Bearish Divergence: When the price makes lower highs, but the OBV makes higher highs.
5. Alerts for Trend Reversals:
The script incorporates alerts that notify traders when the OBV indicates potential trend reversals. This feature can be instrumental in catching early entries or exits.
Disclaimer
It's crucial to understand that no single indicator should be used in isolation. To increase the probability of making accurate market predictions, always use the OBV Oscillator in conjunction with other indicators and tools. Remember that all trading involves risk, and it's possible to lose your invested capital. Always seek advice from a financial advisor before making any trading decisions. By enhancing the OBV with features like the volume filter, multiple MA types, smoothing, and divergence detection, this script becomes a potent tool in a trader's arsenal. Use it wisely, and always ensure to maintain proper risk management.
Candles In Row (Expo)█ Overview
The Candles In Row (Expo) indicator is a powerful tool designed to track and visualize sequences of consecutive candlesticks in a price chart. Whether you're looking to gauge momentum or determine the prevailing trend, this indicator offers versatile functionality tailored to the needs of active traders. The Candles In Row indicator can be an integral part of a multi-timeframe trading strategy, allowing traders to understand market momentum, and set trading bias. By recognizing the patterns and likelihood of future price movements, traders can make more informed decisions and align their trades with the overall market direction.
█ How to use
The indicator enhances traders' understanding of the consecutive candle patterns, helping them to uncover trends and momentum. Consecutive candles in the same direction may indicate a strong trend. The Candles In Row indicator can be an essential tool for traders employing a multiple timeframes strategy.
Analyzing a Higher Timeframe:
Understanding Momentum: By analyzing consecutive green or red candles in a higher timeframe, traders can identify the prevailing momentum in the market. A series of green candles would suggest an upward trend, while a series of red candles would indicate a downward trend.
Predicting Next Candle: The indicator's predictive feature calculates the likelihood of the next candle being green or red based on historical patterns. This probability helps traders gauge the potential continuation of the trend.
Setting the Trading Bias: If the likelihood of the next candle being green is high, the trader may decide to focus on long (buy) opportunities. Conversely, if the likelihood of the next candle being red is high, the trader may look for short (sell) opportunities.
In this example, we are using the Heikin Ashi candles.
Moving to a Lower Timeframe:
Finding Entry Points: Once the trading bias is set based on the higher timeframe analysis, traders can switch to a lower timeframe to look for entry points in the direction of the bias. For example, if the higher timeframe suggests a high likelihood of a green candle, traders may look for buy opportunities in the lower timeframe.
Combining Timeframes for a Comprehensive Strategy:
Confirmation and Alignment: By analyzing the higher timeframe and confirming the direction in the lower timeframe, traders can ensure that they are trading in alignment with the broader trend.
Avoiding False Signals: By using a higher timeframe to set the trading bias and a lower timeframe to find entries, traders can avoid false signals and whipsaws that might be present in a single timeframe analysis.
█ Settings
Price Input Selection: Choose between regular open and close prices or Heikin Ashi candles as the basis for calculation.
Data Window Control: Decide between displaying the full data window or only the active data. You can also enable a counter that keeps track of the number of candles.
Alert Configuration: Set the desired number and color of consecutive candles that must occur in a row to trigger an alert.
Table Display Customization: Customize the location and size of the display table according to your preferences.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
AI Trend Navigator [K-Neighbor]█ Overview
In the evolving landscape of trading and investment, the demand for sophisticated and reliable tools is ever-growing. The AI Trend Navigator is an indicator designed to meet this demand, providing valuable insights into market trends and potential future price movements. The AI Trend Navigator indicator is designed to predict market trends using the k-Nearest Neighbors (KNN) classifier.
By intelligently analyzing recent price actions and emphasizing similar values, it helps traders to navigate complex market conditions with confidence. It provides an advanced way to analyze trends, offering potentially more accurate predictions compared to simpler trend-following methods.
█ Calculations
KNN Moving Average Calculation: The core of the algorithm is a KNN Moving Average that computes the mean of the 'k' closest values to a target within a specified window size. It does this by iterating through the window, calculating the absolute differences between the target and each value, and then finding the mean of the closest values. The target and value are selected based on user preferences (e.g., using the VWAP or Volatility as a target).
KNN Classifier Function: This function applies the k-nearest neighbor algorithm to classify the price action into positive, negative, or neutral trends. It looks at the nearest 'k' bars, calculates the Euclidean distance between them, and categorizes them based on the relative movement. It then returns the prediction based on the highest count of positive, negative, or neutral categories.
█ How to use
Traders can use this indicator to identify potential trend directions in different markets.
Spotting Trends: Traders can use the KNN Moving Average to identify the underlying trend of an asset. By focusing on the k closest values, this component of the indicator offers a clearer view of the trend direction, filtering out market noise.
Trend Confirmation: The KNN Classifier component can confirm existing trends by predicting the future price direction. By aligning predictions with current trends, traders can gain more confidence in their trading decisions.
█ Settings
PriceValue: This determines the type of price input used for distance calculation in the KNN algorithm.
hl2: Uses the average of the high and low prices.
VWAP: Uses the Volume Weighted Average Price.
VWAP: Uses the Volume Weighted Average Price.
Effect: Changing this input will modify the reference values used in the KNN classification, potentially altering the predictions.
TargetValue: This sets the target variable that the KNN classification will attempt to predict.
Price Action: Uses the moving average of the closing price.
VWAP: Uses the Volume Weighted Average Price.
Volatility: Uses the Average True Range (ATR).
Effect: Selecting different targets will affect what the KNN is trying to predict, altering the nature and intent of the predictions.
Number of Closest Values: Defines how many closest values will be considered when calculating the mean for the KNN Moving Average.
Effect: Increasing this value makes the algorithm consider more nearest neighbors, smoothing the indicator and potentially making it less reactive. Decreasing this value may make the indicator more sensitive but possibly more prone to noise.
Neighbors: This sets the number of neighbors that will be considered for the KNN Classifier part of the algorithm.
Effect: Adjusting the number of neighbors affects the sensitivity and smoothness of the KNN classifier.
Smoothing Period: Defines the smoothing period for the moving average used in the KNN classifier.
Effect: Increasing this value would make the KNN Moving Average smoother, potentially reducing noise. Decreasing it would make the indicator more reactive but possibly more prone to false signals.
█ What is K-Nearest Neighbors (K-NN) algorithm?
At its core, the K-NN algorithm recognizes patterns within market data and analyzes the relationships and similarities between data points. By considering the 'K' most similar instances (or neighbors) within a dataset, it predicts future price movements based on historical trends. The K-Nearest Neighbors (K-NN) algorithm is a type of instance-based or non-generalizing learning. While K-NN is considered a relatively simple machine-learning technique, it falls under the AI umbrella.
We can classify the K-Nearest Neighbors (K-NN) algorithm as a form of artificial intelligence (AI), and here's why:
Machine Learning Component: K-NN is a type of machine learning algorithm, and machine learning is a subset of AI. Machine learning is about building algorithms that allow computers to learn from and make predictions or decisions based on data. Since K-NN falls under this category, it is aligned with the principles of AI.
Instance-Based Learning: K-NN is an instance-based learning algorithm. This means that it makes decisions based on the entire training dataset rather than deriving a discriminative function from the dataset. It looks at the 'K' most similar instances (neighbors) when making a prediction, hence adapting to new information if the dataset changes. This adaptability is a hallmark of intelligent systems.
Pattern Recognition: The core of K-NN's functionality is recognizing patterns within data. It identifies relationships and similarities between data points, something akin to human pattern recognition, a key aspect of intelligence.
Classification and Regression: K-NN can be used for both classification and regression tasks, two fundamental problems in machine learning and AI. The indicator code is used for trend classification, a predictive task that aligns with the goals of AI.
Simplicity Doesn't Exclude AI: While K-NN is often considered a simpler algorithm compared to deep learning models, simplicity does not exclude something from being AI. Many AI systems are built on simple rules and can be combined or scaled to create complex behavior.
No Explicit Model Building: Unlike traditional statistical methods, K-NN does not build an explicit model during training. Instead, it waits until a prediction is required and then looks at the 'K' nearest neighbors from the training data to make that prediction. This lazy learning approach is another aspect of machine learning, part of the broader AI field.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
CandlestickPatternsLibrary "CandlestickPatterns"
This library provides a wide range of candlestick patterns, and available for user to call each pattern individually. It's a comprehensive and common tool designed for traders seeking to raise their technical analysis, and it may help users identify key turning of price action in financial instruments. Credit to public technical “*All Candlestick Patterns*” indicator.
abandonedBaby(order, d1)
The "Abandoned Baby" candlestick pattern is a bullish/bearish pattern consists of three candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
darkCloudCover(c1, n)
The "Dark Cloud Cover" is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
doji(d0)
The "Doji" is neither bullish or bearish consists of one candles.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
dojiStar(order, c1, n, d0)
The "Doji Star" is a bullish/bearish pattern consists of two candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear" .
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
downsideTasukiGap(c2, c1, n)
The "Downside Tasuki Gap" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
dragonflyDoji(d0)
The "Dragon Fly Doji" is a bullish pattern consists of one candle.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
engulfing(order, c1, c0, n)
The "Engulfing" is a bullish/bearish pattern consists of two candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningDojiStar(c2, c0, d1, n)
The "Evening Doji Star" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningStar(c2, c1, c0, n)
The "Evening Star" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
fallingThreeMethods(c4, c3, c2, c1, c0, n)
The "Falling Three Methods" is a bearish pattern consists of five candles.
Parameters:
c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
c3 (simple bool) : (simple bool) 4th candle ago body must be lower than average. Optional argument, default is true.
c2 (simple bool) : (simple bool) 3rd candle ago body must be lower than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) 2nd candle ago body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
Returns: (bool)
fallingWindow()
The "Falling Window" is a bearish pattern consists of two candles.
gravestoneDoji(d0)
The "Gravestone Doji" is a bearish pattern consists of one candle.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
hammer(c0, n)
The "Hammer" is a bullish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
hangingMan(c0, n)
The "Hanging Man" is a bearish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
haramiCross(order, c1, n)
The "Harami Cross" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear".
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
harami(order, c1, c0, n)
The "Harami" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear"
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
invertedHammer(c0, n)
The "Inverted Hammer" is a bullish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
kicking(order, c1, c0, n)
The "Kicking" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear"
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
longLowerShadow(l0)
The "Long Lower Shadow" candlestick pattern is a bullish pattern consists of one candles.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 75.
longUpperShadow(u0)
The "Long Upper Shadow" candlestick pattern is a bearish pattern consists of one candles.
Parameters:
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 75.
marubozuBlack(c0, n)
The "Marubozu Black" candlestick pattern is a bearish pattern consists of one candles.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
marubozuWhite(c0, n)
The "Marubozu White" candlestick pattern is a bullish pattern consists of one candles.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningDojiStar(c2, d1, c0, n)
The "Morning Doji Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningStar(c2, c1, c0, n)
The "Morning Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
onNeck(c1, c0, n)
The "On Neck" candlestick pattern is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
piercing(c1, n)
The "Piercing" candlestick pattern is a bullish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingThreeMethods(c4, c3, c2, c1, c0, n)
The "Rising Three Methods" candlestick pattern is a bullish pattern consists of five candles.
Parameters:
c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
c3 (simple bool) : (simple bool) 4th candle ago body must be Lower than average. Optional argument, default is true.
c2 (simple bool) : (simple bool) 3rd candle ago body must be Lower than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) 2nd candle ago body must be Lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingWindow()
The "Rising Window" candlestick pattern is a bullish pattern consists of two candle.
shootingStar(c0, n)
The "Shooting Star" candlestick pattern is a bearish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
spinningTopBlack(l0, u0)
The "Spinning Top Black" is neither bullish or bearish.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
spinningTopWhite(l0, u0)
The "Spinning Top White" is neither bullish or bearish.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
threeBlackCrows(c2, c1, c0, n)
The "Three Black Crows" candlestick pattern is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
threeWhiteSoldiers(c2, c1, c0, n)
The "Three White Soldiers" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
triStar(order, d2, d1, d0)
The "Tri Star" candlestick pattern is a bullish/bearish pattern consists of three candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
d2 (simple float) : (simple float) Before previous candle's body percentage out of candle range. Optional argument, default is 5.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
tweezerBottom(c1, n)
The "Tweezer Bottom" candlestick pattern is a bullish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
tweezerTop(c1, n)
The "Tweezer Top" candlestick pattern is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
upsideTasukiGap(c2, c1, n)
The "Tri Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before Previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
Range Projections [TFO]The purpose of this indicator is to see how often price reached certain standard deviations from a selected time range. The inspiration for this was to study ICT (Inner Circle Trader) concepts regarding the Central Bank Dealer’s Range (CBDR), which is 2:00 pm - 8:00 pm New York local time according to ICT Core Content. However, the idea and data collection could certainly be applied to any range of time.
The main settings of this indicator are session time, range type, and the standard deviation filter. The session time is the window of price that will be utilized for range projections. The range type can be either body or wick (on the current timeframe). The standard deviation filter is used to eliminate sessions whose ranges (from high to low) are greater than the desired/input number of standard deviations from all available session ranges.
In this example, the time range is set to 16:00 - 20:00, or the time between the New York session close and the Asia session open. Our standard deviations are set to 1, 2, 2.5, and 4. Now, by taking this session’s price range and extrapolating these extensions from the initial range, we can use these levels to see if and how price interacts with them before the next 16:00 - 20:00 session.
Furthermore, we can enable the Data Table to analyze how often price trades to these levels for the sessions that are deemed valid (determined by the standard deviation filter). This time our standard deviations are set to 1, 2, 3, and 4.
This concept can theoretically be applied to any window of time. ICT has mentioned that, in instances where the CBDR is too large, the Asia range may be used instead. We can observe that the indicator behaves the same way when we change the session to the Asia range, 20:00 - 00:00.
Intraday Intensity ModesIntraday Intensity Index was created by David Bostian and its use was later featured by John Bollinger in his book "Bollinger on Bollinger Bands" . It is categorically a volume indicator and considered to be a useful tool for analyzing supply and demand dynamics in the market. By measuring the level of buying and selling pressure within a given trading session it attempts to provide insights into the strength of market participants' interest and their aggressiveness in executing trades throughout the day. It can be used in conjunction with Bollinger Bands® or other envelope type indicators as a complimentary indicator to aid in trying to identify potential turning points or trends.
Intraday intensity is calculated based upon the relationship between the price change and the volume of shares traded during each daily interval. It aims to capture the level of buying or selling activity relative to the overall volume. A high intraday intensity value suggests a higher level of buying or selling pressure, indicating a more active and potentially volatile market. Conversely, a low intraday intensity value indicates less pronounced trading activity and a potentially quieter market. Overall, intraday intensity provides a concise description of the intensity of trading activity during a particular trading session, giving traders an additional perspective on market dynamics. Note that because the calculation uses volume this indicator will only work on symbols where volume is available.
While there are pre-existing versions within community scripts, none were found to have applied the calculations necessary for the various modes that are presented within this version, which are believed to be operating in the manner originally intended when first described by Bostian and again later by Bollinger. When operating in default modes on daily or lower chart timeframes the logic used within this script tracks the intraday high, low, close and volume for the day with each progressing intraday bar.
The BB indicator was included on the top main chart to help illustrate example usage as described below. The Intraday Intensity Modes indicator is pictured operating in three different modes beneath the main chart:
• The top pane beneath the main chart shows the indicator operating as a normalized 21 day II% oscillator. A potential use while in this mode would be to look for positive values as potential confirmation of strength when price tags the upper or lower Bollinger bands, and to look for negative values as potential confirmation of weakness when price tags the upper or lower Bollinger bands.
• The middle pane shows the indicator operating as an "open ended" cumulative sum of II. A potential use while in this mode would be to look for convergence or divergence of trend when price is making new highs or lows, or while price is walking the upper or lower Bollinger bands.
• The bottom pane shows the indicator operating in standard III mode, which provides independent values per session.
Indicator Settings: Inputs tab:
Osc Length : Set to 1 disables oscillation, values greater than 1 enables oscillation for II% (Intraday Intensity percent) mode.
Tootip : Hover mouse over (i) to show recommended example Settings for various modes.
Cumulative : When enabled values are cumulatively summed for the entire chart and indicator operates in II mode.
Normalized : When enabled a rolling window of Osc Length values are summed and normalized to the rolling window's volume.
Intrabar : When enabled price range and volume are evaluated for intensity per bar instead of per day which is a departure from the original
concept. Whenever this setting is enabled the indicator should be regarded as operating in an experimental mode.
Colors For Up Down : Sets the plot colors used, may be overridden in Settings:Style tab.
Styles / Width : Sets the plot style and width used, may be overridden in Settings:Style tab.
This indicator is designed to work with any chart timeframe, with the understanding that when used on timeframes higher than daily the indicator becomes "IntraPeriod" intensity, for example on weekly bars it would be "IntraWeek" intensity. On Daily or lower timeframes the indicator operates as "IntraDay" intensity and is being updated on each bar as each day progresses. If the experimental setting Intrabar is enabled then the indicator operates as "IntraBar" intensity and is no longer constrained to daily or higher evaluations, for example with Intrabar enabled on a 4H timeframe the indicator would operate as "Intra4H" intensity.
NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
MA Correlation CoefficientThis script helps you visualize the correlation between the price of an asset and 4 moving averages of your choice. This indicator can help you identify trendy markets as well as trend-shifts.
Disclaimer
Bear in mind that there is always some lag when using Moving-Averages, hence the purpose of this indicator is as a trend identification tool rather than an entry-exit strategy.
Working Principle
The basic idea behind this indicator is the following:
In a trendy market you will find high correlation between price and all kinds of Moving-Averages. This works both ways, no matter bull or bear trend.
In sideways markets you might find a mix of correlations accross timeframes (2018) or high correlation with Low-Timeframe averages and low correlation with High-Timeframe averages (2021/2022).
Trend shifts might be characterised by a 'staircase' type of correlation (yellow), where the asset regains correlation with higher timeframe averages
Indicator Options
1. Source : data used for indicator calculation
1. Correlation Window : size of moving window for correlation calculation
2. Average Type :
Simple-Moving-Average (SMA)
Exponential-Moving-Average (EMA)
Hull-Moving-Average (HMA)
Volume-Weighted-Moving-Average (VWMA)
3. Lookback : number of past candles to calculate average
4. Gradient : modify gradient colors. colors relate to correlation values.
Plot Explanation
The indicator plots, using colors, the correlation of the asset with 4 averages. For every candle, 4 correlation values are generated, corresponding to 4 colors. These 4 colors are stacked one on top of the other generating the patterns explained above. These patterns may help you identify what kind of market you're in.
Arbitrage SpreadThis indicator helps to find spreads between cryptocurrencies, assess their correlation, spread, z score and atr z score.
The graphs are plotted as a percentage. Because of the limitation in pine tradingview for 5000 bars a period was introduced (after which a new starting point of the graph construction will be started), if you want it can be disabled
The multiplier parameter affects only the construction of the joint diagram on which z score and atr z score are calculated (construction of the diagram is done by dividing one pair by another and multiplying by the multiplier parameter) is shown with a red line
To create a notification you have to specify the data for parameters other than zero which you want to monitor. For parameters z score and atr z score data are counted in both directions
The data can be tracked via the data window
Link to image of the data window prnt.sc
Scalper's toolkit - ATR WidgetWidget specifically designed for scalping. Many settings to fit the instrument and view preferences to make it fit into your chart window how you like, even on mobile.
** I have 5 other features to add into this in the very near future, as I use this as my primary tool for Risk reward. This script will be updated in the near future as more features are coded into it. See bottom for notes on plans
Features:
Displays a quick view of the ATR value on the chart, in decimal PIPs or directly in Points - a key value for scalping using the DOM for point value settings and one click trading on fast time frames.
Automatic calculation of stop and target distance for a predetermined Risk Reward Ratio (Set with the settings panel), and then also displayed in PIPs or Points for easy use in quick trading.
Works on most all instruments/pairs/cryptos with multiple precision levels for correct values to be shown in the widget.
Fully customizable -
ATR period Base setting, just like a normal ATR indicator
Display in : PIPs or Points
ATR based stop distance, using a multiplier. 2 is the most common multiplier used, and the default setting.
Risk Reward Calculation using the Stop Loss value.
-Quickly helps with proper target and stop sizing for the volatility in the price on the current trade entry point.
-Set to any ratio you wish, from 1:0.1 all the way to 1:100 or more, unlimited R ratio settings to fit your strategy and risk tolerances.
Position anywhere on the chart window with 9 preset locations available (Pine script limitation)
Show as a column layout or a row layout
Customize the Size, with 5 preset widget sizes, from tiny to huge (Pine script limitation)
-Mobile Friendly - Tiny or Small may be too small on PC, but can be used for Mobile so the widget does not become too large over the chart.
Custom text, background, and boarder colors
Custom Boarder Size - 0 size is no boarder
Set up:
-Open the settings panel.
First section is the basic settings for the ATR - the length (Default is 14) and to use a PIP value display, or Point value display.
Here you also see a "Precision" Setting. **Because each instrument returns different precision ATR values, it is difficult to determine with code what those values will be ahead of time to do the math in the background. Even some 2 decimal instruments return 5 decimal ATR values, so this setting filters that** Just use the dropdown and choose how many decimal places the instrument has from 2 - 5 decimals
The second section is for risk and reward calculations, and can be disabled if you do not want to see these values.
The first value is the "ATR Multiplier" Typically, a 2x multiplier is used on the ATR to determine how far away to place your stop loss from the entry, placing it out of harm's way from normal market activity.
The second value is the Reward target distance, based from the stop loss size. This quickly calculates your target to match your intended reward ratio, saving some manual work to calculate this by hand every trade.
** Note: because of the math used in the code, you may see odd values on some instruments, like indexes. If you have the precision correct, try changing the "Show in Pips" to "Show in Points", as this may solve the issue.
The last two sections are purely for how the widget looks and how/where it shows on the screen. These can be set however you like. To have no boarder, just set the "Frame size" value to 0.
Additional Updates planned:
Pip value calculation (2 feature uses)
-This will serve 2 purposes. The widget will calculate the value of the trade based on the lot size. It will also have a risk limit, so if the ATR get's too high for the current risk settings, It will show red to warn you of a high risk situation before you trade.
Example, you have a set limit of 3 dollars per trade using .02 lot sizing. If the ATR get's too high, The Stop value will be more risk than you would like to use at that trade sizing. Reduce the trade size, or wait for ATR to come lower.
Purpose 2: lot size calculation, so if you wanted to maximize the use of risk available. If you wanted to risk 600 for example, it would use the ATR you have set for the risk, and determine the proper lot size for the amount of volatility in the market. This way, you Risk Exactly, or as close as possible to 600 for the the current trade conditions.
Extra use for this value: Show the Current trade amounts at risk and for gain in money values on the side of the pip/point value. Know what you're risking and also trading for in monetary value.
ATR candle Comparison- Early momentum Detection (2 feature uses)
Will show an additional section on the bottom of the widget to show how each candle compares to the one before, up to the last 5, and show if ATR went down, up, or stayed the same over the last 5 candles.
Show an additional symbol to indicate the current candle status in comparison to the close of the last candle. Real time of if the ATR is getting larger, smaller, or staying the same.
Spectral Gating (SG)The Spectral Gating (SG) Indicator is a technical analysis tool inspired by music production techniques. It aims to help traders reduce noise in their charts by focusing on the significant frequency components of the data, providing a clearer view of market trends.
By incorporating complex number operations and Fast Fourier Transform (FFT) algorithms, the SG Indicator efficiently processes market data. The indicator transforms input data into the frequency domain and applies a threshold to the power spectrum, filtering out noise and retaining only the frequency components that exceed the threshold.
Key aspects of the Spectral Gating Indicator include:
Adjustable Window Size: Customize the window size (ranging from 2 to 6) to control the amount of data considered during the analysis, giving you the flexibility to adapt the indicator to your trading strategy.
Complex Number Arithmetic: The indicator uses complex number addition, subtraction, and multiplication, as well as radius calculations for accurate data processing.
Iterative FFT and IFFT: The SG Indicator features iterative FFT and Inverse Fast Fourier Transform (IFFT) algorithms for rapid data analysis. The FFT algorithm converts input data into the frequency domain, while the IFFT algorithm restores the filtered data back to the time domain.
Spectral Gating: At the heart of the indicator, the spectral gating function applies a threshold to the power spectrum, suppressing frequency components below the threshold. This process helps to enhance the clarity of the data by reducing noise and focusing on the more significant frequency components.
Visualization: The indicator plots the filtered data on the chart with a simple blue line, providing a clean and easily interpretable representation of the results.
Although the Spectral Gating Indicator may not be a one-size-fits-all solution for all trading scenarios, it serves as a valuable tool for traders looking to reduce noise and concentrate on relevant market trends. By incorporating this indicator into your analysis toolkit, you can potentially make more informed trading decisions.
Markdown: The Pine Editor's Hidden Gem💬 Markdown, a markup language
Markdown is a portable, lightweight markup language that can be used for everything whether you're building a website, documentation, or even presentations.
Platforms like Discord, Reddit, and GitHub support Markdown and is the widely go-to option for text formatting due to its simplicity. Pine Script is a language that also utilizes Markdown, specifically in the Pine Editor where it can really be used to some extent.
Since the release of libraries, user-defined types, and methods, Pine Script is entering an age where developers will be highly dependent on libraries due to the capabilities Pine has inherited recently. It would be no surprise if a few people got together and took their time to thoroughly develop an entire project/library centered around improving Pine Script's built-in functions and providing developers with easier ways of achieving things than they thought they could.
As you're all aware, hovering over functions (and more) in the editor pops up a prompt that specifies the parameters, types, and what the function returns. Pine Script uses Markdown for that, so I figured we could go ahead and push that feature to its limits and see what we can do.
Today we'll go over how we can utilize Markdown in Pine Script, and how you can make your library's built-in functions stand out more than they did previously.
For more information, visit www.markdownguide.org
📕 General Notes
Markdown syntax only works on functions and methods.
Using arrays as parameters as of 2/21/2023 breaks the Markdown system.
The prompt window holds a max of 166 characters on one line before overflowing.
There is no limit on how long the prompt window can be.
🔽 Getting Started 🔽
▶️ Headings
If you have experience in HTML, Markdown, or even Microsoft Word then you already have a grasp of how headings work and look.
To simplify it, headings make the given text either massive or tiny depending on how many number symbols are provided.
When defining headings, you must have a space between the number (#) symbol, and the text. This is typical syntax throughout the language.
Pine Script uses bold text by applying (**) for their titles on their built-ins (e.g. @returns) but you could also use heading level 4 (####) and have it look the same.
▶️ Paragraphs & Line Breaks
You may want to provide extensive details and examples relating to one function, in this case, you could create line breaks. Creating line breaks skips to the next line so you can keep things organized as a result.
To achieve a valid line break and create a new paragraph, you must end the line with two or more spaces.
If you want to have an empty line in between, apply a backslash (\).
Backslashes (\) are generally not recommended for every line break. In this case, I only recommend using them for empty lines.
▶️ Text Formatting
Markdown provides text formatting such as bold, italics, and strikethrough.
For bolding text, you can apply open and close (**) or (__).
For italicizing text, you can apply open and close (*) or (_).
For bolding and italicizing text, you can apply open and close (***) or (___).
For s̶t̶r̶i̶k̶e̶t̶h̶r̶o̶u̶g̶h̶, you need to apply open and close (~~).
This was mentioned in the Headers section, but Pine Script's main titles (e.g. @returns or @syntax) use bold (**) by default.
▶️ Blockquotes
Blockquotes in Pine Script can be visualized as a built-in indentation system.
They are declared using greater than (>) and everything will be auto-aligned and indented until closed.
By convention you generally want to include the greater than (>) on every line that's included in the block quote. Even when not needed.
If you would like to indent even more (nested blockquotes), you can apply multiple greater than symbols (>). For example, (>>)
Blockquotes can be closed by ending the next line with only one greater than (>) symbol, or by using a horizontal rule.
▶️ Horizontal Rules
Horizontal rules in Pine Script are what you see at the very top of the prompt in built-ins.
When hovering, you can see the top of the prompt provides a line, and we can actually reproduce these lines.
These are extremely useful for separating information into their own parts and are accessed by applying 3 underscores (___), or 3 asterisks (***).
Horizontal rules were mentioned above, when we were discussing block quotes. These can also be used to close blockquotes as well.
Horizontal rules require a minimum of 3 underscores (___) or 3 asterisks (***).
▶️ Lists
Lists give us a way to structure data in a somewhat neat way. There are multiple ways to start a list, such as
1. First Item (number followed by a period)
- First Item (dash)
+ First Item (plus sign)
* First Item (asterisk)
Using number-based lists provide an ordered list, whereas using (-), (+), or (*) will provide an unordered list (bullet points).
If you want to begin an unordered list with a number that ends with a period, you must use an escape sequence (\) after the number.
Standard indentation (tab-width) list detection isn't supported, so to nest lists you have to use blockquotes (>) which may not look as appealing.
▶️ Code Blocks
Using code blocks allows you to write actual Pine Script code inside the prompt.
It's a game changer that can potentially help people understand how to execute functions quickly.
To use code blocks, apply three 3 open and close backquotes (```). Built-in's use (```pine) but there's no difference when we apply it.
Considering that tab-width indentation isn't detected properly, we can make use of the blockquotes mentioned above.
▶️ Denotation
Denoting can also be seen as highlighting a background layer behind text. They're basically code blocks, but without the "block".
Similar to how code blocks work, we apply one backquote open and close (`).
Make sure to only use this on important keywords. There really isn't a conventional way of applying this.
It's up to you to decide what people should have their eyes tracked onto when they hover over your functions.
If needed, look at how Pine Script's built-in variables and functions utilize this.
▶️ Tables
Tables are possible in Markdown, although they may look a bit different in the Pine Editor.
They are made by separating text with vertical bars (|).
The headers are detected when there is a minimum of one hyphen (-) below them.
You can align text by using a colon as I do in the photo. Hyphens must be connected to the colon in order to display correctly.
Tables aren't ideal to use in the editor but are there if anyone wants to give it a go.
▶️ Links & Images
Markdown supports images and hyperlinks, which means we can also do that here in the Pine Editor. Cool right?
If you want to create a hyperlink, surround the displayed text in open and close brackets .
If you want to load a photo into your prompt, it's the same syntax as the hyperlink, except it uses a (!)
See syntax list below.
Here are realistic usage examples. (Snippets from code below)
These follow the same syntax as the built-ins.
I'm not using horizontal rules here, but it's entirely up to you.
▶️ Syntax List
Headings
Level 1: #
Level 2: ##
Level 3: ###
Level 4: ####
Level 5: #####
Level 6: ######
Line Breaks
Text (two spaces)
Text\ (backslash)
Text Formatting
Bold (**)
Italic (**)
Strikethrough (~~)
Blockquotes
Indent (>)
Double Indent (>>)
Triple Indent (>>>) and so on.
Horizontal Rules
(___) or (***)
Lists
Ordered List (1.)
Unordered List (-) or (+) or (*)
Code Blocks
(```) or (```pine)
Denotation
(`)
Tables
(|) and (-) and (:)
Hyperlinks
(URL)
Images
! (URL)
Hope this helps. 👍
Strategy Myth-Busting #23 - 2xEMA+DPO- [MYN]#23 on the Myth-Busting bench, we are automating the "Best Funded Account Trading Strategy (Pass EVERY Challenge!)" strategy from "Trade with Pat" who claims this strategy will pass every trading challenge out there.
This strategy uses 3 open source indicators. 2 EMA's. The first one (Slow) is set to a length of 40 and a fast EMA which is set to 12. This strategy uses the crossover of the fast( 12) EMA over the Slow EMA ( 40 ) as the primary means to enter a long position. The opposite when the fast EMA crosses under the slow EMA as a means to indicate a short position. This strategy uses the DPO (Detrended Price Oscillaor) from the Uptrend Price DPO indicator in the same way we would traditionally use a stochastic or moving average convergence/divergence indicator like the MACD . Basically, the DPO helps evaluate and estimate the length of the price cycle from peak to peek or through to trough and in this strategy confirms entry of a long / short condition complimenting the EMA crossover/crossunders.
And as always, If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
EMA x2 ( 40 and 12)
Untrend Price DPO indicator by jTradeuh
Trading Rules
1 or 4 hour candles
Stop loss at previous highest-high (Short) and lowest-low (Long).
Take Profit 2 - 2.5 the risk
Strategy Template includes open source code from the following:
Performance Summary Dashboard by @VertMT
Time Of Day Window by @ddctv
Monthly Table Performance Dashboard by @QuantNomad
DistributionsLibrary "Distributions"
Library with price distribution zones calculation helpers.
Based on research from "Trading Systems and Methods, 5th Edition" by Perry J. Kaufman
getZones(h, l, c, window)
Returns price distribution zones based on HLC and for some period
Parameters:
h : high price
l : low price
c : close price
window : period to calculate distributions
Returns: tuple of 5 price zones in descent order, from highest to lowest
Moving Average ZonesImagine bollinger bands, but instead with multiple customizable moving averages.
MAZ contains moving averages that act as support and resistance. This can lead to potential use for stop loss and take profit decision-making along with potential signs of reversals.
Features
Areas of Confluence
Display Options
Data Window
Default Settings (with Data Window)
Areas of Confluence
In the photo above, every touch inside a zone increases the brightness of the zone, strengthening the confluence of the zone.
Zones will disappear after a while if no touches have occurred in between a zone within the specified lookback period.
Asymmetric Dispersion High Lowdear fellows,
this indicator is an effort to determine the range where the prices are likely to fall within in the current candle.
how it is calculated
1. obtain
a. gain from the open to the high
b. loss from the open to the low
in the last 20 (by default) candles and
in the last 200 (10*20 by default) candles
2. perform
a. the geometric average (sma of the log returns) over these gains and losses
b. their respective standard deviation
3. plot from the open of each candle
a. the average + 2 standard deviations (2 by default) of the short window size
b. same for the long window size (which is overlapped)
what it shows
1. where the current candle is likely to move with 95% likelyhood
how it can be interpreted
1. a gauge for volatility in the short and long term
2. a visual inbalance between likelyhood to go up or down according to dispersion in relation to current prices or candle open.
3. a confirmation of crossings of, for instance, support and resistances once the cloud is completely above or below.
in regard to bollinger bands (which are and excellent well proven indicator)
1. it segregates upward moves from the downward ones.
2. it is hardly crossed by prices
3. it is centered on the current candle open, instead of the moving average.
we welcome feedback and critic.
best regards and success wishes.
na_skip_highestLibrary "na_skip_highest"
Finds the highest historic value over len bars but skip na valued bars (eg, off days). In other words, this will ensure we find the highest value over len bars with a real value, and if there are any na bars in-between, we skip over but the loop will continue. This allows to mimic calculations on markets with off days (eg, weekends).
na_skip_highest(src, len)
Finds the highest historic value over len bars but skip na valued bars (eg, off days). In other words, this will ensure we find the highest value over len bars with a real value, and if there are any na bars in-between, we skip over but the loop will continue. This allows to mimic calculations on markets with off days (eg, weekends).
Parameters:
src : series float source (eg, close)
len : int length, number of recent bars to consider in the window to find the highest value
Returns: highest float highest value found over the len window
ctndLibrary "ctnd"
Description:
Double precision algorithm to compute the cumulative trivariate normal distribution
found in A.Genz, Numerical computation of rectangular bivariate and trivariate normal
and t probabilities”, Statistics and Computing, 14, (3), 2004. The cumulative trivariate
normal is needed to price window barrier options, see G.F. Armstrong, Valuation formulae
or window barrier options”, Applied Mathematical Finance, 8, 2001.
References:
link.springer.com
www.tandfonline.com
citeseerx.ist.psu.edu
The Complete Guide to Option Pricing Formulas, 2nd ed. (Espen Gaarder Haug)
CTND(LIMIT1, LIMIT2, LIMIT3, SIGMA1, SIGMA2, SIGMA3)
Returns the Cumulative Trivariate Normal Distribution
Parameters:
LIMIT1 : float,
LIMIT2 : float,
LIMIT3 : float,
SIGMA1 : float,
SIGMA2 : float,
SIGMA3 : float,
Returns: float.
