2 Moving Averages | Trend FollowingThe trading system is a trend-following strategy based on two moving averages (MA) and Parabolic SAR (PSAR) indicators.
How it works:
The strategy uses two moving averages: a fast MA and a slow MA.
It checks for a bullish trend when the fast MA is above the slow MA and the current price is above the fast MA.
It checks for a bearish trend when the fast MA is below the slow MA and the current price is below the fast MA.
The Parabolic SAR (PSAR) indicator is used for additional trend confirmation.
Long and short positions can be turned on or off based on user input.
The strategy incorporates risk management with stop-loss orders based on the Average True Range (ATR).
Users can filter the backtest date range and display various indicators.
The strategy is designed to work with the date range filter, risk management, and user-defined positions.
Features:
Trend-following strategy.
Two customizable moving averages.
Parabolic SAR for trend confirmation.
User-defined risk management with stop-loss based on ATR.
Backtest date range filter.
Flexibility to enable or disable long and short positions.
This trading system provides a comprehensive approach to trend-following and risk management, making it suitable for traders looking to capture trends with controlled risk.
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TableLibrary "Table"
This library provides an easy way to convert arrays and matrixes of data into tables. There are a few different implementations of each function so you can get more or less control over the appearance of the tables. The basic rule of thumb is that all matrix rows must have the same number of columns, and if you are providing multiple arrays/matrixes to specify additional colors (background/text), they must have the same number of rows/columns as the data array. Finally, you do have the option of spanning cells across rows or columns with some special syntax in the data cell. Look at the examples to see how the arrays and matrixes need to be built before they can be used by the functions.
floatArrayToCellArray(floatArray)
Helper function that converts a float array to a Cell array so it can be rendered with the fromArray function
Parameters:
floatArray (float ) : (array) the float array to convert to a Cell array.
Returns: array The Cell array to return.
stringArrayToCellArray(stringArray)
Helper function that converts a string array to a Cell array so it can be rendered with the fromArray function
Parameters:
stringArray (string ) : (array) the array to convert to a Cell array.
Returns: array The Cell array to return.
floatMatrixToCellMatrix(floatMatrix)
Helper function that converts a float matrix to a Cell matrix so it can be rendered with the fromMatrix function
Parameters:
floatMatrix (matrix) : (matrix) the float matrix to convert to a string matrix.
Returns: matrix The Cell matrix to render.
stringMatrixToCellMatrix(stringMatrix)
Helper function that converts a string matrix to a Cell matrix so it can be rendered with the fromMatrix function
Parameters:
stringMatrix (matrix) : (matrix) the string matrix to convert to a Cell matrix.
Returns: matrix The Cell matrix to return.
fromMatrix(CellMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Takes a CellMatrix and renders it as a table.
Parameters:
CellMatrix (matrix) : (matrix) The Cells to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromMatrix(dataMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Renders a float matrix as a table.
Parameters:
dataMatrix (matrix) : (matrix_float) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromMatrix(dataMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Renders a string matrix as a table.
Parameters:
dataMatrix (matrix) : (matrix_string) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a Cell array as a table.
Parameters:
dataArray (Cell ) : (array) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a string array as a table.
Parameters:
dataArray (string ) : (array_string) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a float array as a table.
Parameters:
dataArray (float ) : (array_float) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
debug(message, position)
Renders a debug message in a table at the desired location on screen.
Parameters:
message (string) : (string) The message to render.
position (string) : (string) Optional. The position of the debug message. Defaults to position.middle_right.
Cell
Type for each cell's content and appearance
Fields:
content (series string)
bgColor (series color)
textColor (series color)
align (series string)
colspan (series int)
rowspan (series int)
UtilsLibrary "Utils"
A collection of convenience and helper functions for indicator and library authors on TradingView
formatNumber(num)
My version of format number that doesn't have so many decimal places...
Parameters:
num (float) : (float) the number to be formatted
Returns: (string) The formatted number
getDateString(timestamp)
Convenience function returns timestamp in yyyy/MM/dd format.
Parameters:
timestamp (int) : (int) The timestamp to stringify
Returns: (int) The date string
getDateTimeString(timestamp)
Convenience function returns timestamp in yyyy/MM/dd hh:mm format.
Parameters:
timestamp (int) : (int) The timestamp to stringify
Returns: (int) The date string
getInsideBarCount()
Gets the number of inside bars for the current chart. Can also be passed to request.security to get the same for different timeframes.
Returns: (int) The # of inside bars on the chart right now.
getLabelStyleFromString(styleString, acceptGivenIfNoMatch)
Tradingview doesn't give you a nice way to put the label styles into a dropdown for configuration settings. So, I specify them in the following format: . This function takes care of converting those custom strings back to the ones expected by tradingview scripts.
Parameters:
styleString (string)
acceptGivenIfNoMatch (bool) : (bool) If no match for styleString is found and this is true, the function will return styleString, otherwise it will return tradingview's preferred default
Returns: (string) The string expected by tradingview functions
getTime(hourNumber, minuteNumber)
Given an hour number and minute number, adds them together and returns the sum. To be used by getLevelBetweenTimes when fetching specific price levels during a time window on the day.
Parameters:
hourNumber (int) : (int) The hour number
minuteNumber (int) : (int) The minute number
Returns: (int) The sum of all the minutes
getHighAndLowBetweenTimes(start, end)
Given a start and end time, returns the high or low price during that time window.
Parameters:
start (int) : The timestamp to start with (# of seconds)
end (int) : The timestamp to end with (# of seconds)
Returns: (float) The high or low value
getPremarketHighsAndLows()
Returns an expression that can be used by request.security to fetch the premarket high & low levels in a tuple.
Returns: (tuple)
getAfterHoursHighsAndLows()
Returns an expression that can be used by request.security to fetch the after hours high & low levels in a tuple.
Returns: (tuple)
getOvernightHighsAndLows()
Returns an expression that can be used by request.security to fetch the overnight high & low levels in a tuple.
Returns: (tuple)
getNonRthHighsAndLows()
Returns an expression that can be used by request.security to fetch the high & low levels for premarket, after hours and overnight in a tuple.
Returns: (tuple)
getLineStyleFromString(styleString, acceptGivenIfNoMatch)
Tradingview doesn't give you a nice way to put the line styles into a dropdown for configuration settings. So, I specify them in the following format: . This function takes care of converting those custom strings back to the ones expected by tradingview scripts.
Parameters:
styleString (string) : (string) Plain english (or TV Standard) version of the style string
acceptGivenIfNoMatch (bool) : (bool) If no match for styleString is found and this is true, the function will return styleString, otherwise it will return tradingview's preferred default
Returns: (string) The string expected by tradingview functions
getPercentFromPrice(price)
Get the % the current price is away from the given price.
Parameters:
price (float)
Returns: (float) The % the current price is away from the given price.
getPositionFromString(position)
Tradingview doesn't give you a nice way to put the positions into a dropdown for configuration settings. So, I specify them in the following format: . This function takes care of converting those custom strings back to the ones expected by tradingview scripts.
Parameters:
position (string) : (string) Plain english position string
Returns: (string) The string expected by tradingview functions
getTimeframeOfChart()
Get the timeframe of the current chart for display
Returns: (string) The string of the current chart timeframe
getTimeNowPlusOffset(candleOffset)
Helper function for drawings that use xloc.bar_time to help you know the time offset if you want to place the end of the drawing out into the future. This determines the time-size of one candle and then returns a time n candleOffsets into the future.
Parameters:
candleOffset (int) : (int) The number of items to find singular/plural for.
Returns: (int) The future time
getVolumeBetweenTimes(start, end)
Given a start and end time, returns the sum of all volume across bars during that time window.
Parameters:
start (int) : The timestamp to start with (# of seconds)
end (int) : The timestamp to end with (# of seconds)
Returns: (float) The volume
isToday()
Returns true if the current bar occurs on today's date.
Returns: (bool) True if current bar is today
padLabelString(labelText, labelStyle)
Pads a label string so that it appears properly in or not in a label. When label.style_none is used, this will make sure it is left-aligned instead of center-aligned. When any other type is used, it adds a single space to the right so there is padding against the right end of the label.
Parameters:
labelText (string) : (string) The string to be padded
labelStyle (string) : (string) The style of the label being padded for.
Returns: (string) The padded string
plural(num, singular, plural)
Helps format a string for plural/singular. By default, if you only provide num, it will just return "s" for plural and nothing for singular (eg. plural(numberOfCats)). But you can optionally specify the full singular/plural words for more complicated nomenclature (eg. plural(numberOfBenches, 'bench', 'benches'))
Parameters:
num (int) : (int) The number of items to find singular/plural for.
singular (string) : (string) The string to return if num is singular. Defaults to an empty string.
plural (string) : (string) The string to return if num is plural. Defaults to 's' so you can just add 's' to the end of a word.
Returns: (string) The singular or plural provided strings depending on the num provided.
timeframeInSeconds(timeframe)
Get the # of seconds in a given timeframe. Tradingview's timeframe.in_seconds() expects a simple string, and we often need to use series string, so this is an alternative to get you the value you need.
Parameters:
timeframe (string)
Returns: (int) The number of secondsof that timeframe
timeframeToString(tf)
Convert a timeframe string to a consistent standard.
Parameters:
tf (string) : (string) The timeframe string to convert
Returns: (string) The standard format for the string, or the unchanged value if it is unknown.
AR Forecast Scatterplot [SS]This is a showcase indicator of my recently released SPTS library (the partner of the SPTS indicator).
This is just to show some of the practical applications of the boring statistical functions contained within the library/SPTS indicator :-).
This is an autoregressive (AR), scatter plot forecaster. What this means is it tags a lag of 1, performs an autoregressive assessment over the desired training time, then uses what it learns over that training time to forecast the likely outcome.
Its not a machine learning (I am in the process of creating one like this, but it is taking quite some time to complete), but the model needs to learn to plan the statistical coefficients that will best mimic the current trend.
As of its current state, this actually surpassed my own expectations. I can show you some QQQ examples:
Example #1:
Prediction:
Actual:
Example #2:
Prediction:
Actual:
Pretty nuts, eh?
Statistics, I'm telling you, its the answer haha.
So how do we determine the train time?
Because this is not using machine learning to control for over/under representation of datasize (again, I am making a version that does this, but its a slow process), some quick tips at determine appropriate train time is to use the Tradingview Regression tool:
When you set the parameters to align with the current, strongest trend, it is more reliable.
You will see, that it acutally is forecasting a move back to the exact top of this trend, that is because it is using the same processes as the linear regression trend on Tradingview.
You can use a bar counter indicator ( such as mine available here ) to calculate the number or bars back for your model training.
You can verify that these parameters are appropriate by looking at the Model Data table (which can be toggled on and off). You want to see both a high correlation and a high R2 value.
Quick note on colour:
Green = represents the upper confidence predictions (best case scenario)
Blue = represents the most likely result
red = represents that lower confidence (not as best case scenario)
Hope you enjoy!
Safe trades everyone!
Enhanced TrixThe Enhanced Trix Confluence Oscillator involves utilizing two core components: a slow line and a difference histogram based on a shorter length. Another key aspect is the indicator using the DEMA for greater speed while the triple smoothing still provides accuracy which makes this different from the original indicator. This approach aims to rely on principles of both momentum and divergence.
The ETC aims to filter out market noise to reveal the core trend direction in both the short and medium term. A slow line is calculated using a longer time period with the double exponential moving average, which makes it less responsive to short-term price fluctuations and better at capturing longer-term momentum. It's best used to identify divergences with the asset's price, signaling potential reversals. The difference histogram serves as a more sensitive indicator for trade timing once further calibrated. It's calculated by taking the difference between the displayed length and a shorter period using the same calculation. This histogram also operates as a rate of change like the TRIX.
The slow line identifies broader trends and divergences, while the difference histogram offers a more granular view.
Triple EMA By Ozy
**Triple EMA By Ozy**
The "Triple EMA By Ozy" is a visual indicator that offers traders a clear and concise view of three exponential moving averages (EMAs) at a glance. This tool combines three common EMAs (20, 50, and 200) and additionally calculates and displays the slope angle of each EMA, allowing for a more precise identification of the current trend's direction and strength.
**Key Features:**
1. **Three EMAs in One Indicator:** The 20, 50, and 200-period EMAs are popular among traders and are crucial for identifying short, medium, and long-term trends.
2. **Slope Angle:** The indicator calculates the slope angle for each EMA, which can be indicative of the trend's strength. A positive angle suggests bullish momentum, while a negative angle indicates bearish momentum.
3. **Clear Visual Indication:** The indicator uses colors to easily distinguish between EMAs and also to identify the direction of the slope angle (green for positive, red for negative).
**How to Use:**
- An increasing angle in the EMA20 may indicate the beginning of a new short-term upward trend.
- A decreasing angle in the EMA200 might signal a long-term downtrend gaining strength.
- Crosses between the EMAs can also be points of interest, like the golden cross (EMA50 crossing above the EMA200) or the death cross (EMA50 crossing below the EMA200).
**Triple EMA By Ozy**
El "Triple EMA By Ozy" es un indicador visual que proporciona a los traders una visión clara y concisa de tres medias móviles exponenciales (EMAs) en un solo vistazo. Esta herramienta combina tres EMAs comunes (20, 50 y 200) y, además, calcula y muestra el ángulo de inclinación de cada EMA para identificar con mayor precisión la dirección y la fuerza de la tendencia actual.
**Características principales:**
1. **Tres EMAs en un solo indicador:** Las EMAs de 20, 50 y 200 períodos son populares entre los traders y son esenciales para identificar tendencias a corto, mediano y largo plazo.
2. **Ángulo de inclinación:** El indicador calcula el ángulo de inclinación de cada EMA, que puede ser un indicativo de la fuerza de la tendencia. Un ángulo positivo sugiere un impulso alcista, mientras que un ángulo negativo indica un impulso bajista.
3. **Indicación visual clara:** El indicador utiliza colores para distinguir fácilmente entre EMAs y también para identificar la dirección del ángulo de inclinación (verde para positivo, rojo para negativo).
**Cómo usar:**
- Un ángulo creciente en la EMA20 puede indicar el comienzo de una nueva tendencia al alza a corto plazo.
- Un ángulo decreciente en la EMA200 puede ser una señal de una tendencia bajista a largo plazo que está ganando fuerza.
- Los cruces entre las EMAs también pueden ser puntos de interés, como el cruce dorado (EMA50 cruza por encima de la EMA200) o el cruce de la muerte (EMA50 cruza por debajo de la EMA200).
Leading Economic Indicator (LEI)The Leading Economic Indicator (LEI) is a groundbreaking technical indicator designed to serve as a comprehensive measure of the prevailing direction of economic trends in the United States. This unique index combines two key economic indicators: the Composite Leading Indicator (CLI) from the Organization for Economic Co-operation and Development (OECD) and the Purchasing Managers' Index (PMI) from the Institute for Supply Management (ISM).
The OECD Composite Leading Indicator (CLI) is a globally recognized indicator that assesses the future direction of economic trends by analyzing various leading economic factors. The ISM PMI, on the other hand, provides insights into the business activities of both the manufacturing and services sectors. LEI merges these critical indicators into a single, holistic indicator that empowers traders and investors to grasp the broader economic outlook and the performance of essential economic sectors simultaneously.
By taking into account the CLI and PMI, LEI offers a distinctive perspective, enabling a more accurate assessment of the potential direction of US financial markets.
Usage:
To utilize LEI effectively, it is recommended to apply it on a monthly timeframe (TF Monthly). This extended timeframe is particularly beneficial for investors with a medium to long-term horizon. By focusing on longer-term trends and market stability, LEI becomes an invaluable tool in your investment strategy.
One of the primary applications of LEI is to gauge the risk of market corrections in US financial markets, including the S&P 500, Nasdaq, and Dow Jones indices. Analysts often observe the crossing of the 5-period Simple Moving Average (SMA) with the 10-period SMA. When the 5-period SMA falls below the 10-period SMA, it serves as a potential warning signal for an impending market correction. This feature provides traders with an opportunity to exercise caution and make well-informed investment decisions.
LEI, with its unique blend of the OECD CLI and ISM PMI, provides a reliable tool for assessing the US economic climate, identifying trends, and making informed decisions in the financial markets. It stands as a reference indicator, capturing the essence of economic trends and providing valuable insights to traders and investors.
Sources:
- OECD Composite Leading Indicator (CLI): www.data.oecd.org
- Purchasing Managers' Index: ISM Report on Business (PMI) www.ismworld.org
Zig-Zag Volume Profile (Bull vs. Bear) [Kioseff Trading]Hello!
Thank you @Pinecoders and @TradingView for putting polylines in production and making this viable!!
This script "Zig Zag Volume Profile" implements the polyline feature for Pine Script!
Features
Volume Profile anchored to zig zag trends
Bull vs Bear profiles!
Delta x price level
Standard POC and value area lines, in addition to separated POCs and value area lines for bull profiles and bear profiles
Up to 9999 profile rows per zigzag trend
Stylistic options for profiles
Configurable zig zag - profiles generated for small to large trends
Polylines!
This script generates Bull vs. Bear volume profiles for zig zag trends!
The zigzag indicator is configurable as normal; minor and major trend volume profiles are calculable. This indicator can be thought of as "Volume Profile/Delta for Trends''.
Up to 9999 volume profile levels (price levels) can be calculated for each profile, thanks to the new polyline feature, allowing for less aggregation / more precision of volume at price and volume delta.
Zig Zag Bull Vs Bear Profiles
The image above shows primary functionality!
Green profiles = buying volume
Red profiles = selling volume
Profiles are generated for each trend identified by the zigzag indicator.
The image above shows the indicator calculating volume delta for specific price blocks on the profile. Aggregate volume delta for the identified trend is displayed over the profile!
The image above shows Bull Profile POC lines and value area lines. Bear Profile POC lines and value area lines are also shown!
All colors and transparencies are configurable to the user's liking :D
Additionally, you can select to have the profiles drawn on contrasting sides. Bull Profile on left and Bear Profile on right.
For a more traditional look - you can select to draw the Bull & Bear profiles on the same x-point.
The indicator is robust enough to calculate on "long zig zags" and "short zig zags"; curved profiles can also be used!
The image above exemplifies usage of the indicator!
Bull & Bear volume profiles are calculated for trends on the 30-second timeframe.
The image above shows a more "utilitarian" presentation of the profiles. Once more, line and linefill colors/transparencies are all customizable; the indicator can look however you would like it to!
The image above shows key levels, the Bull vs. Bear profile, and volume delta for the current trend!
That's about it :D
This indicator is part of a series titled "Bull vs. Bear" - a suite of profile-like indicators I will be releasing over coming days. Thanks for checking this out!
Of course, a big thank you to @RicardoSantos for his MathOperator library that I use in every script.
If you have any suggestions please feel free to share!
Moving Average TransformThe MAT is essentially a different kind of smoothed moving average. It is made to filter out data sets that deviate from the specified absolute threshold and the result becomes a smoothing function. The goal here, inspired by time series analysis within mathematical study, is to eliminate data anomalies and generate a more accurate trendline.
Functionality:
This script calculates a filtered average by:
Determining the mean of the entire data series.
Initializing sum and count variables.
Iterating through the data to filter values that deviate from the mean beyond the threshold.
Calculating a filtered mean based on the filtered data.
The filtered mean is then passed through a moving average function, where various types of moving averages like SMA, EMA, DEMA, TEMA, and ALMA can be applied. Some popular averages such as the HMA were omitted due to their heavy dependency on weighing specific data points.
Some information from "Time Series Analysis" regarding deviations
Definition of Anomaly: An anomaly or outlier is a data point that differs significantly from other observations in the dataset. It can be caused by various reasons such as measurement errors, data entry errors, or genuine extreme observations.
Impact on Mean: The mean (or average) of a dataset is calculated by summing all the values and dividing by the number of values. Since the mean is sensitive to extreme values, even a single outlier can significantly skew the mean.
Example: Consider a simple time series dataset: . The value "150" is an anomaly in this context. If we calculate the mean with this outlier, it is (10 + 12 + 11 + 9 + 150) / 5 = 38.4. However, if we exclude the outlier, the mean becomes (10 + 12 + 11 + 9) / 4 = 10.5. The presence of the outlier has substantially increased the mean.
Accuracy and Representativeness: While the mean calculated without outliers might be more "accurate" in the sense of being more representative of the central tendency of the bulk of the data, it's essential to note that anomalies might convey important information about the system being studied. Blindly removing or ignoring them might lead to overlooking significant events or phenomena.
Approaches to Handle Anomalies?
Detection and Removal
Robust Statistics
Transformation
Supertrend Forecast - vanAmsenHello everyone!
I am thrilled to present the "vanAmsen - Supertrend Forecast", an advanced tool that marries the simplicity of the Supertrend with comprehensive statistical insights.
Before we dive into the functionalities of this indicator, it's essential to understand its foundation and theory.
The Theory:
What exactly is the Supertrend?
The Supertrend, at its core, is a momentum oscillator. It's a tool that provides buy and sell signals based on the prevailing market trend. The underlying principle is straightforward: by analyzing average price data and volatility over a period, the Supertrend gives us a line that represents the trend direction.
However, trading isn't just about identifying trends; it's about understanding their strength, potential profitability, and historical accuracy. This is where statistics come into play. By incorporating statistical analysis into the Supertrend, we can gain deeper insights into the market's behavior.
Description:
The "vanAmsen - Supertrend Forecast" isn't just another Supertrend indicator. It's a comprehensive tool designed to offer traders a holistic view of market trends, backed by robust statistical analysis.
Key Features:
- Supertrend Line: A visual representation of the current market direction.
- Win Rate & Expected Return: Delve into the historical accuracy and profitability of the prevailing trend.
- Average Percentage Change: Understand the average price fluctuation for both winning and losing trends.
- Forecast Lines: Project future price movements based on historical data, providing a roadmap for potential scenarios.
- Interactive Table: A concise table in the top right, offering a snapshot of all vital metrics at a glance.
Usage:
- The bullish Supertrend line adopts an Aqua hue, indicating potential upward momentum.
- In contrast, the bearish line is painted in Orange, suggesting potential downtrends.
- Customize your chart by toggling labels, tables, and lines according to preference.
Recommendation:
The "vanAmsen - Supertrend Forecast" is undoubtedly a powerful tool in a trader's arsenal. However, it's imperative to combine it with other technical analysis tools and sound risk management practices. It's always prudent to backtest strategies with historical data before embarking on live trading.
syminfo tableThis is nothing special, and it is not an indicator for investments.
I build this for my programming layout, so I can see all the output of the syminfo command.
Simply put...
It shows the commands on the left side,
and related outputs are on the right side.
BB Support & ResistanceChoosing support and resistance can be time consuming and subjective. Personally, I don't want to spend too much time manually marking up charts. Credit to video I saw, forget the producer, that demonstrated how multi-time frame Bollinger Bands can act as support and resistance. I suggest reading up on Bollinger Bands (en.wikipedia.org) and how to trade them. This indicator draws support and resistance lines based on Bollinger Bands on three time frames. You can select 1 or all three time frames to display on your chart. Enjoy.
Drawdown Dynamics IndicatorDescription :
The Drawdown Dynamics Indicator is a straightforward tool that offers insights into three critical aspects of an asset’s financial performance: Total Max Drawdown, Rolling Period Max Drawdown, and Current Max Drawdown. Inside of the indicator, you can select to view either the rolling period max drawdown or the all-time max drawdown. This is represented by the gray line. The blue line represents the asset's current drawdown.
Rolling Period Max Drawdown is more about a snapshot view, highlighting the maximum loss from a peak to a trough for an adjustable rolling time frame. This is a feature not available with other indicators that exist on TradingView.
Total Max Drawdown gives a broad view, showcasing the all-time deepest decline in an asset’s value.
Current Max Drawdown offers a live update, focusing on the asset's present phase and how it's performing in real-time.
Practical Uses :
The utility of this indicator becomes evident when you start exploring the risks and performance metrics of assets. A notable use of this indicator is in comparing the drawdowns of a trading strategy against the inherent drawdowns of an asset. It helps in painting a clearer picture of risk and performance of both the asset and the strategy.
Risk Understanding : By comparing the strategy drawdown to the asset drawdown, traders get to understand if the risk they’re taking aligns with the asset’s natural risk behavior.
Evaluating Strategy’s Strength : If a strategy can weather the storms of the asset's natural drawdown phases and come out relatively unscathed, it can speak to its strength.
Performance Comparison : It also acts as a benchmark tool. Traders can pit different strategies against each other, using the asset’s drawdown as a baseline, to see which one manages risks better.
Disclaimer : This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Dynamic Sine Wave The Dynamic Sine Wave is designed to calculate a sine wave that reflects the oscillations between the highest high and lowest low points over a specified period, providing traders with a unique perspective on market trends.
Why a Sine Wave is Relevant:
A sine wave is relevant in this context because it is a mathematical function that represents periodic oscillations, making it suitable for capturing the cyclic nature of price movements in financial markets.
By using a sine wave, this indicator highlights the repetitive patterns of price highs and lows over a specified period, which can assist traders in identifying potential trend reversals or continuations.
The sine wave's amplitude and frequency are adjusted based on the highest high and lowest low points, ensuring that it adapts to market volatility and provides a dynamic representation of price action.
Overall, the "Dynamic Sine Wave" indicator offers a unique perspective on market dynamics, helping traders make informed decisions by visualizing the ebb and flow of prices.
Multiperiod Volume Pressure Indicator
Description:
The Volume Pressure Indicator is a powerful tool designed to assess market sentiment based on a combination of price and volume data. By analyzing buy and sell pressure within specific lookback periods, this indicator provides valuable insights into the intensity of market buying and selling activities. Traders can use this information to make informed decisions, especially during periods of price consolidation or trend reversal.
Key Features:
- **Multi-Period Analysis:** Utilizes multiple lookback periods (1, 2, and 4) to calculate buy and sell pressures, offering a nuanced view of market dynamics over different timeframes.
- **Pressure Calculation:** Computes buy and sell pressures based on price range and closing values, providing a comprehensive understanding of market participant behavior.
- **Color-Coded Bars:** Visualizes market sentiment by coloring bars according to the number of positive (buy pressure > sell pressure) periods observed within the specified lookback periods.
How to Use:
- **Color Coding:** Green bars represent periods where buy pressure dominates, indicating potential buying interest. Yellow bars suggest a balance between buy and sell pressures. Red bars signal periods dominated by sell pressure, indicating potential selling interest.
- **Lookback Periods:** Shorter lookback periods (e.g., 1) offer insights into immediate market sentiment, while longer periods (e.g., 4) provide a broader perspective. Analyzing multiple periods can help traders confirm trends and anticipate reversals.
Customization:
- **Lookback Periods:** Adjust the length of the lookback periods (1, 2, and 4) to match your trading style and timeframe preferences.
Disclaimer:
Trading involves risk, and past performance is not indicative of future results. Always conduct thorough analysis and apply proper risk management techniques before making trading decisions.
Usage Scenarios:
- **Trend Confirmation:** Use the indicator to confirm the strength of an ongoing trend. Consistent green bars can validate a bullish trend, while red bars may confirm a bearish trend.
- **Reversal Signals:** Look for transitions in bar colors to identify potential trend reversals. A shift from green to yellow/red or vice versa can indicate changing market sentiment.
- **Divergence Analysis:** Compare price movements with the indicator's bar colors. Divergence between price trends and bar colors may signal upcoming price movements.
DMI Based Overbought/Oversold SignalsDescription:
The Directional Movement Index (DMI) with Bollinger Bands and Moving Averages is a comprehensive technical analysis tool designed to assist traders in identifying potential market trends and reversal points. This indicator combines the power of DMI, Bollinger Bands, and Moving Averages to offer insights into market strength, volatility, and potential entry/exit points.
Key Features:
- **DMI Analysis:** Utilizes the DMI to evaluate the strength of bullish and bearish trends, aiding in trend identification and momentum assessment.
- **Bollinger Bands:** Implements Bollinger Bands on both +DI and -DI, enabling traders to gauge price volatility and potential overbought/oversold conditions.
- **Moving Averages Confirmation:** Utilizes Moving Averages for both +DI and -DI, confirming trend signals and providing additional context for trade decisions.
- **Color-Coded Signals:** Displays red boxes for potential bearish signals and green boxes for potential bullish signals, enhancing visual clarity.
How to Use:
- **DMI Signals:** Red boxes indicate potential bearish signals, suggesting caution or potential short opportunities. Green boxes suggest potential bullish signals, indicating possible long opportunities.
- **Volatility Assessment:** Bollinger Bands expansion (price moving away from the center line) can indicate increased volatility, potentially signaling significant price movements.
- **Trend Confirmation:** Moving Averages confirm the strength of the trend. When +DI or -DI is above its respective upper Bollinger Band and the Moving Average is also above, the trend is considered strong.
Customization:
- **DI Length:** Adjust the length of the Directional Index (DI) to fine-tune the sensitivity of trend signals.
- **Bollinger Bands Length:** Modify the length of Bollinger Bands to control the indicator's responsiveness to price volatility.
- **Bollinger Bands Multiplier:** Adjust the multiplier to widen or narrow the Bollinger Bands, affecting the sensitivity of overbought/oversold signals.
- **Moving Average Length:** Define the length of Moving Averages for additional confirmation of trend signals.
Disclaimer:
Trading involves risk, and past performance is not indicative of future results. Always conduct thorough analysis and apply proper risk management techniques before making trading decisions.
DMI Based Consolidation InidcatorDescription:
The Consolidation Indicator (DMI + MA) combines the power of the Directional Movement Index (DMI) and Moving Averages (MA) to help traders identify both trends and consolidation phases in the market. This versatile indicator provides valuable insights into the market's behavior, making it an essential tool for traders seeking to optimize their strategies.
Key Features:
- **Directional Movement Analysis:** Utilizes the DMI to assess the strength of bullish and bearish trends, helping traders identify trend direction and momentum.
- **Moving Average Confirmation:** Integrates Moving Averages to confirm trend signals, enhancing the reliability of trend identification.
- **Trend and Consolidation Recognition:** Displays +DI and -DI trends with color-coded boxes, allowing traders to distinguish between bullish, bearish trends, and consolidation phases.
How to Use:
- **Trend Identification:** +DI Trend box (green) indicates a bullish trend, suggesting potential buying opportunities. -DI Trend box (red) signifies a bearish trend, indicating potential selling opportunities.
- **Consolidation Phase:** When both boxes are white, the market is in a consolidation phase. During consolidation, prices often move within a range. Traders may consider range-bound strategies or wait for a clear trend signal.
Customization:
- **ADX Smoothing:** Adjust the ADX smoothing factor (lensig) to fine-tune the sensitivity of trend signals.
- **DI Length:** Set the length of the Directional Index (DI) to control the responsiveness of the indicator to price changes.
- **Moving Average Length:** Define the length of the Moving Averages for additional confirmation of trend signals.
- **Moving Average Type:** Choose from SMA, EMA, WMA, or VWMA to customize the Moving Averages based on your trading preferences.
Disclaimer:
Trading involves risk, and past performance is not indicative of future results. Always perform your analysis and consider risk management strategies before making trading decisions.
Support Resistance with Touch HighlightDescription:
Support Resistance with Touch Highlight is a powerful technical analysis tool designed to help traders identify key support and resistance levels in the market. Unlike traditional support and resistance indicators, this indicator utilizes a unique approach by considering multiple periods simultaneously, enhancing its accuracy and reliability.
Key Features:
- **Multi-Period Analysis:** The indicator analyzes multiple user-defined periods, allowing for a comprehensive view of support and resistance levels.
- **Average Calculation:** It calculates the average of the highest and lowest prices within the specified periods, providing a balanced representation of support and resistance zones.
- **Dynamic Highlighting:** Bars touching the support or resistance lines are highlighted, aiding traders in spotting potential reversal points.
- **Alert System:** Set custom alerts to be notified when the price touches the support or resistance lines, enabling timely decision-making.
Why It's Superior:
1. **Accuracy Through Multiple Periods:** By considering multiple periods, the indicator provides a more accurate depiction of support and resistance levels, minimizing false signals.
2. **Dynamic Highlighting:** The indicator dynamically highlights relevant bars, making it easy for traders to identify significant price interactions with support and resistance zones.
3. **Customizable Alerts:** Tailor alerts to your trading strategy, ensuring you never miss crucial market movements.
How to Use:
- **Support Zones:** Prices often bounce off the support line. Look for buying opportunities when the price touches or approaches the green support line.
- **Resistance Zones:** Prices tend to reverse near the resistance line. Consider selling or tightening stops when the price touches or nears the red resistance line.
Disclaimer:
Trading involves risk, and past performance is not indicative of future results. Always perform your analysis and consider risk management strategies before making trading decisions.
Breakout mode patterns [yohtza]This indicator detects three kinds of price action patterns:
ii - consecutive inside bars ( high and low inside of the previous bar), triangle on a lower timeframe
oo - consecutive outside bars ( high above the high of the previous bar and the low below the low of the previous bar), expanding triangle on a lower timeframe
ioi - inside outside inside, diamond pattern on a lower timeframe
Traders that trade these patterns are entering on breakouts above/below .When they appear in a trending market, they are good setups for both continuation and reversal swing trades. When they appear in ranging market, they are not nearly as powerful since most breakouts fail in this context. To achieve the highest probability, it is best to trade in the direction of the trend on the last bar in the pattern with a stop loss on the other side and going for a reward that is at least twice the risk.
Seasonality and Presidential cycleAn incredibly useful indicator that shows seasonality and presidential cycles by indices, stocks and industries. Just type in a ticker and trade according to seasonal patterns
Blue line - seasonality excluding presidential cycles
Green line - seasonality taking into account presidential cycles
*Seasonal patterns over the last 10 years
This indicator uses the request.seed() function.
Requests data from a GitHub repository maintained by our team and returns it as a series.
Pine Seeds is a service to import custom data and access it via TradingView.
Use TradingView as frontend and use a GitHub repository as backend.
github.com
...
Rus: Невероятно полезный индикатор, который показывает сезонность и президентские циклы по индексам, акциям и отраслям. Просто вбейте тикер и торгуйте согласно сезонным паттернам
Синяя линия - сезонность без учета президентских циклов
Зеленая линия - сезонность с учетом президентских циклов
*Сезонные паттерны за последние 10 лет
MTF ATR Reversal Levels (Open Source)
This is an open source version of the original I posted a couple of years ago.... Multitple TimeFrame Swingarm system borrowing from the Blackflag FTS indicator.
This throws up 5 resolutions of ATR thresholds, only showing the current bar level using a horizontal line across the full chart. I don't like the historical information charted, just need to know the current level for my trading purposes.
It will also give Sell/Buy alerts when the closing price exceeds one of those thresholds... essentially confirmation of a trend reversal.
On the primary resolution (defaulted to the current timeframe of the chart) it can show the fibonacci reversal levels using the ATR levels for that time resolution. This is if for the current trend.
I find it useful, so I thought I would share. Like all indicators, it'll work as long as you stick with a system, and let it work. :)
Market Internals (TICK, ADD, VOLD, TRIN, VIX)OVERVIEW
This script allows you to perform data transformations on Market Internals, across exchanges, and specify signal parameters, to more easily identify sentiment extremes.
Notable transformations include:
1. Cumulative session values
2. Directional bull-bear Ratios and Percent Differences
3. Data Normalization
4. Noise Reduction
This kind of data interaction is very useful for understanding the relationship between two mutually exclusive metrics, which is the essence of Market Internals: Up vs. Down. Even so, they are not possible with symbol expressions alone. And the kind of symbol expression needed to produce baseline data that can be reliably transformed is opaque to most traders, made worse by the fact that prerequisite symbol expressions themselves are not uniform across symbols. It's very nuanced, and if this last bit was confusing … exactly.
All this to say, rather than forcing that burden onto you, I've baked the baseline symbol expressions into the indicator so: 1) the transform functions consistently ingest the baseline data in the correct format and 2) you don't have to spend time trying to figure it all out. Trading is hard. There's no need to make it harder.
INPUTS
Indicator
Allows you to specify the base Market Internal and Exchange data to use. The list of Market Internals is simplified to their fundamental representation (TICK, ADD, VOLD, TRIN, VIX, ABVD, TKCD), and the list of Exchange data is limited to the most common (NYSE, NASDAQ, All US Stocks). There are also options for basic exchange combinations (Sum or Average of NYSE & NASDAQ).
Mode
Short for "Plot Mode", this is where you specify the bars style (Candles, Bars, Line, Circles, Columns) and the source value (used for single value plots and plot color changes).
Scale
This is the first and second data transformation grouped together. The default is to show the origin data as it might appear on a chart. You can then specify if each bar should retain it's unique value (Bar Value) or be added to a running total (Cumulative). You can also specify if you would like the data to remain unaltered (Raw) or converted to a directional ratio (Ratio) or a percentage (Percent Diff). These options determine the scale of the plot.
Both Ratio and Percent Diff. convert a given symbol into a positive or negative number, where positive numbers are bullish and negative numbers are bearish.
Ratio will divide Bull values by Bear values, then further divide -1 by the quotient if it is less than 1. For example, if "0.5" was the quotient, the Ratio would be "-2".
Percent Diff. subtracts Bear values from Bull values, then divides that difference by the sum of Bull and Bear values multiplied by 100. If a Bull value was "3" and Bear value was "7", the difference would be "-4", the sum would be "10", and the Percent Diff. would be "-40", as the difference is both bearish and 40% of total.
Ratio Norm. Threshold
This is the third data transformation . While quotients can be less than 1, directional ratios are never less than 1. This can lead to barcode-like artifacts as plots transition between positive and negative values, visually suggesting the change is much larger than it actually is. Normalizing the data can resolve this artifact, but undermines the utility of ratios. If, however, only some of the data is normalized, the artifact can be resolved without jeopardizing its contextual usefulness.
The utility of ratios is how quickly they communicate proportional differences. For example, if one side is twice as big as the other, "2" communicates this efficiently. This necessarily means the numerical value of ratios is worth preserving. Also, below a certain threshold, the utility of ratios is diminished. For example, an equal distribution being represented as 0, 1, 1:1, 50/50, etc. are all equally useful. Thus, there is a threshold, above which we want values to be exact, and below which the utility of linear visual continuity is more important. This setting accounts for that threshold.
When this setting is enabled, a ratio will be normalized to 0 when 1:1, scaled linearly toward the specified threshold when greater than 1:1, and then retain its exact value when the threshold is crossed. For example, with a threshold of "2", 1:1 = 0, 1.5:1 = 1, 2:1 = 2, 3:1 = 3, etc.
With all this in mind, most traders will want to set the ratios threshold at a level where accuracy becomes more important than visual continuity. If this level is unknown, "2" is a good baseline.
Reset cumulative total with each new session
Cumulative totals can be retained indefinitely or be reset each session. When enabled, each session has its own cumulative total. When disabled, the cumulative total is maintained indefinitely.
Show Signal Ranges
Because everything in this script is designed to make identifying sentiment extremes easier, an obvious inclusion would be to not only display ranges that are considered extreme for each Market Internal, but to also change the color of the plot when it is within, or beyond, that range. That is exactly what this setting does.
Override Max & Min
While the min-max signal levels have reasonable defaults for each symbol and transformation type, the Override Max and Override Min options allow you to … (wait for it) … override the max … and min … signal levels. This may be useful should you find a different level to be more suitable for your exact configuration.
Reduce Noise
This is the fourth data transformation . While the previous Ratio Norm. Threshold linearly stretches values between a threshold and 0, this setting will exponentially squash values closer to 0 if below the lower signal level.
The purpose of this is to compress data below the signal range, then amplify it as it approaches the signal level. If we are trying to identify extremes (the signal), minimizing values that are not extreme (the noise) can help us visually focus on what matters.
Always keep both signal zones visible
Some traders like to zoom in close to the bars. Others prefer to keep a wider focus. For those that like to zoom in, if both signals were always visible, the bar values can appear squashed and difficult to discern. For those that keep a wider focus, if both signals were not always visible, it's possible to lose context if a signal zone is vertically beyond the pane. This setting allows you to decide which scenario is best for you.
Plot Colors
These define the default color, within signal color, and beyond signal color for Bullish and Bearish directions.
Plot colors should be relative to zero
When enabled, the plot will inherit Bullish colors when above zero and Bearish colors when below zero. When disabled and Directional Colors are enabled (below), the plot will inherit the default Bullish color when rising, and the default Bearish color when falling. Otherwise, the plot will use the default Bullish color for all directions.
Directional colors
When the plot colors should be relative to zero (above), this changes the opacity of a bars color if moving toward zero, where "100" percent is the full value of the original color and "0" is transparent. When the plot colors are NOT relative to zero, the plot will inherit Bullish colors when rising and Bearish colors when falling.
Differentiate RTH from ETH
Market Internal data is typically only available during regular trading hours. When this setting is enabled, the background color of the indicator will change as a reminder that data is not available outside regular trading hours (RTH), if the chart is showing electronic trading hours (ETH).
Show zero line
Similar to always keeping signal zones visible (further up), some traders prefer zooming in while others prefer a wider context. This setting allows you to specify the visibility of the zero line to best suit your trading style.
Linear Regression
Polynomial regressions are great for capturing non-linear patterns in data. TradingView offers a "linear regression curve", which this script is using as a substitute. If you're unfamiliar with either term, think of this like a better moving average.
Symbol
While the Market Internal symbol will display in the status line of the indicator, the status line can be small and require more than a quick glance to read properly. Enabling this setting allows you to specify if / where / how the symbol should display on the indicator to make distinguishing between Market Internals more efficient.
Speaking of symbols, this indicator is designed for, and limited to, the following …
TICK - The TICK subtracts the total number of stocks making a downtick from the total number of stocks making an uptick.
ADD - The Advance Decline Difference subtracts the total number of stocks below yesterdays close from the total number of stocks above yesterdays close.
VOLD - The Volume Difference subtracts the total declining volume from the total advancing volume.
TRIN - The Arms Index (aka. Trading Index) divides the ratio of Advancing Stocks / Volume by the ratio of Declining Stocks / Volume. Given the inverse correlation of this index to market movement, when transforming it to a Ratio or Percent Diff., its values are inverted to preserve the bull-bear sentiment of the transformations.
VIX - The CBOE Volatility Index is derived from SPX index option prices, generating a 30-day forward projection of volatility. Given the inverse correlation of this index to market movement, when transforming it to a Ratio or Percent Diff., its values are inverted and normalized to the sessions first bar to preserve the bull-bear sentiment of the transformations. Note: If you do not have a Cboe CGIF subscription , VIX data will be delayed and plot unexpectedly.
ABVD - The Above VWAP Difference is an unofficial index measuring all stocks above VWAP as a percent difference. For the purposes of this indicator (and brevity), TradingViews PCTABOVEVWAP has has been shortened to simply be ABVD.
TKCD - The Tick Cumulative Difference is an unofficial index that subtracts the total number of market downticks from the total number of market upticks. Where "the TICK" (further up) is a measurement of stocks ticking up and down, TKCD is a measurement of the ticks themselves. For the purposes of this indicator (and brevity), TradingViews UPTKS and DNTKS symbols have been shorted to simply be TKCD.
INSPIRATION
I recently made an indicator automatically identifying / drawing daily percentage levels , based on 4 assumptions. One of these assumptions is about trend days. While trend days do not represent the majority of days, they can have big moves worth understanding, for both capitalization and risk mitigation.
To this end, I discovered:
• Article by Linda Bradford Raschke about Capturing Trend Days.
• Video of Garrett Drinon about Trend Day Trading.
• Videos of Ryan Trost about How To Use ADD and TICK.
• Article by Jason Ruchel about Overview of Key Market Internals.
• Including links to resources outside of TradingView violates the House Rules, but they're not hard to find, if interested.
These discoveries inspired me adopt the underlying symbols in my own trading. I also found myself wanting to make using them easier, the net result being this script.
While coding everything, I also discovered a few symbols I believe warrant serious consideration. Specifically the Percent Above VWAP symbols and the Up Ticks / Down Ticks symbols (referenced as ABVD and TKCD in this indicator, for brevity). I found transforming ABVD or TKCD into a Ratio or Percent Diff. to be an incredibly useful and worthy inclusion.
ABVD is a Market Breadth cousin to Brian Shannon's work, and TKCD is like the 3rd dimension of the TICKs geometry. Enjoy.
MTF Breakout/RetestIntroducing the MTF (Multi Timeframe) Breakout and Retest Indicator:
This indicator is designed to enhance your trading strategy by providing a clear view of support and resistance levels across multiple timeframes. What this simply means is that you can input your levels, and be on a lower timeframe such as the 1 minute timeframe, and are able to see when your support or resistance level has a breakout
📈 Short Trade Breakout Condition:
- Definition: A short breakout occurs when a candle closes below your specified support level on any chosen timeframe.
- Confirmation: It confirms as a valid short signal when a second candle closes below the support level without retesting.
- Visual Clarity: The indicator highlights the timeframe in which this breakout has occurred.
(Long conditions are same but reversed, and will be displayed in color green)
📊 Multi-Timeframe Insights:
- Scope: You can analyze support and resistance levels across various timeframes, including 5, 15, 30, and 60 minutes, while trading on a lower timeframe like 1 minute.
🎨 Dynamic Color-Coding:
- Visual Signaling: The indicator employs color-coding to visually signal breakout events. When a short breakout occurs on any timeframe the timeframe color will highlight red, and vice versa for long will highlight green. The physical line will change color based on the current timeframe you are viewing
- Real-Time Tracking: Colors reset when a level is retested, helping you track market sentiment in real-time.
🪙 Need Your Help
- I am still very much new to coding, and this code is clearly not optimized well. This code was mainly the based idea, and over the next coming months I will be working to enhance the code but I need tradingview help. If you are a coder and see a way to optimize this code please please let me know :)
