Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
스크립트에서 "top"에 대해 찾기
JordanSwindenLibraryLibrary "JordanSwindenLibrary"
TODO: add library description here
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
getPipSize(multiplier)
Calculates the pip size of the current market
Parameters:
multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)
Returns: The pip size for the current market
truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places
Parameters:
number (float) : The number to truncate
decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to
Returns: The given number truncated to the given decimalPlaces
toWhole(number)
Converts pips into whole numbers
Parameters:
number (float) : The pip number to convert into a whole number
Returns: The converted number
toPips(number)
Converts whole numbers back into pips
Parameters:
number (float) : The whole number to convert into pips
Returns: The converted number
getPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period
Parameters:
value1 (float) : The first value to reference
value2 (float) : The second value to reference
lookback (int) : The lookback period to analyze
Returns: The percent change over the two values and lookback period
random(minRange, maxRange)
Wichmann–Hill Pseudo-Random Number Generator
Parameters:
minRange (float) : The smallest possible number (default: 0)
maxRange (float) : The largest possible number (default: 1)
Returns: A random number between minRange and maxRange
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
getMA(length, maType)
Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)
Parameters:
length (simple int) : The MA period
maType (string) : The type of MA
Returns: A moving average with the given parameters
barsAboveMA(lookback, ma)
Counts how many candles are above the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to check
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(lookback, ma)
Counts how many candles are below the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently (based on closing prices)
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many times price recently crossed the EMA (based on closing prices)
getPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
lookback (int) : The lookback period to look back over
direction (int) : The color of the bar to count (1 = Green, -1 = Red)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)
bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bullish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bearish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
isInsideBar()
Detects inside bars
Returns: Returns true if the current bar is an inside bar
isOutsideBar()
Detects outside bars
Returns: Returns true if the current bar is an outside bar
barInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls within the given time session
barOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls outside the given time session
dateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range
Parameters:
startTime (int) : The UNIX date timestamp to begin searching from
endTime (int) : the UNIX date timestamp to stop searching from
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze
Parameters:
monday (bool) : Should the script analyze this day? (true/false)
tuesday (bool) : Should the script analyze this day? (true/false)
wednesday (bool) : Should the script analyze this day? (true/false)
thursday (bool) : Should the script analyze this day? (true/false)
friday (bool) : Should the script analyze this day? (true/false)
saturday (bool) : Should the script analyze this day? (true/false)
sunday (bool) : Should the script analyze this day? (true/false)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(atrValue, maxSize)
Parameters:
atrValue (float)
maxSize (float)
tradeCount()
Calculate total trade count
Returns: Total closed trade count
isLong()
Check if we're currently in a long trade
Returns: True if our position size is positive
isShort()
Check if we're currently in a short trade
Returns: True if our position size is negative
isFlat()
Check if we're currentlyflat
Returns: True if our position size is zero
wonTrade()
Check if this bar falls after a winning trade
Returns: True if we just won a trade
lostTrade()
Check if this bar falls after a losing trade
Returns: True if we just lost a trade
maxDrawdownRealized()
Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
totalPipReturn()
Gets the total amount of pips won/lost (as a whole number)
Returns: Total amount of pips won/lost (as a whole number)
longWinCount()
Count how many winning long trades we've had
Returns: Long win count
shortWinCount()
Count how many winning short trades we've had
Returns: Short win count
longLossCount()
Count how many losing long trades we've had
Returns: Long loss count
shortLossCount()
Count how many losing short trades we've had
Returns: Short loss count
breakEvenCount(allowanceTicks)
Count how many break-even trades we've had
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even count
longCount()
Count how many long trades we've taken
Returns: Long trade count
shortCount()
Count how many short trades we've taken
Returns: Short trade count
longWinPercent()
Calculate win rate of long trades
Returns: Long win rate (0-100)
shortWinPercent()
Calculate win rate of short trades
Returns: Short win rate (0-100)
breakEvenPercent(allowanceTicks)
Calculate break even rate of all trades
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even win rate (0-100)
averageRR()
Calculate average risk:reward
Returns: Average winning trade divided by average losing trade
unitsToLots(units)
(Forex) Convert the given unit count to lots (multiples of 100,000)
Parameters:
units (float) : The units to convert into lots
Returns: Units converted to nearest lot size (as float)
getFxPositionSize(balance, risk, stopLossPips, fxRate, lots)
(Forex) Calculate fixed-fractional position size based on given parameters
Parameters:
balance (float) : The account balance
risk (float) : The % risk (whole number)
stopLossPips (float) : Pip distance to base risk on
fxRate (float) : The conversion currency rate (more info below in library documentation)
lots (bool) : Whether or not to return the position size in lots rather than units (true by default)
Returns: Units/lots to enter into "qty=" parameter of strategy entry function
EXAMPLE USAGE:
string conversionCurrencyPair = (strategy.account_currency == syminfo.currency ? syminfo.tickerid : strategy.account_currency + syminfo.currency)
float fx_rate = request.security(conversionCurrencyPair, timeframe.period, close )
if (longCondition)
strategy.entry("Long", strategy.long, qty=zen.getFxPositionSize(strategy.equity, 1, stopLossPipsWholeNumber, fx_rate, true))
skipTradeMonteCarlo(chance, debug)
Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation
Parameters:
chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)
debug (bool) : Whether or not to display a label informing of the trade skip
Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks)
fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)
This updates the given table's cell with the given values
Parameters:
tableID (table) : The table ID to update
column (int) : The column to update
row (int) : The row to update
title (string) : The title of this cell
value (string) : The value of this cell
bgcolor (color) : The background color of this cell
txtcolor (color) : The text color of this cell
tooltip (string)
Returns: Nothing.
Digital Clock with Market Status and AlertsDigital Clock with Market Status and Alerts - 日本語解説は下記
Overview:
The Digital Clock with Market Status and Alerts indicator is designed to display the current time in various global time zones while also providing the status of major financial markets such as Tokyo, London, and New York. This indicator helps traders monitor the open and close times of different markets and alerts them when a market opens. Customizable options are provided for table positioning, background, text colors, and font size.
Key Features:
Real-Time Digital Clock: The indicator shows the current time in your selected time zone (Asia/Tokyo, America/New_York, Europe/London, Australia/Sydney). The time updates in real-time and includes hours, minutes, and seconds, providing a convenient and accurate way to monitor time across different trading sessions.
Global Market Status: Displays the open or closed status of major financial markets.
・Tokyo Market: Open from 9:00 AM to 3:00 PM (JST).
・London Market: Open from 16:00 to 24:00 during summer time and from 17:00 to 1:00 during winter time (JST).
・New York Market: Open from 21:00 to 5:00 during summer time and from 22:00 to 6:00 during winter time (JST).
Customizable Display:
・Background Color: The indicator allows you to set the background color for the clock display, while the leftmost empty cell can be independently customized with its own background color for table alignment.
・Clock and Market Status Colors: Separate color options are available for the clock text, market status during open, and market status during closed periods.
・Text Size: You can adjust the size of the text (small, normal, large) to fit your preferences.
・Table Position: You can position the digital clock and market status table in different locations on the chart: top left, top center, top right, bottom left, bottom center, and bottom right.
Alerts for Market Opening: The indicator will trigger alerts when a market (Tokyo, London, or New York) opens, notifying traders in real-time. This can help ensure that you don't miss any important market openings.
How to Use:
Setup:
Apply the Indicator: Add the Digital Clock with Market Status and Alerts indicator to your chart. Customize the time zone, text size, background colors, and table position based on your preferences.
Monitor Market Status: Watch the market status displayed for Tokyo, London, and New York to keep track of market openings and closings in real-time.
Receive Alerts: The indicator provides built-in alerts for market openings, helping you stay informed when a key market opens for trading.
Time Monitoring:
・Real-Time Clock: The current time is displayed with hours, minutes, and seconds for accurate tracking. The clock updates every second and reflects the selected time zone.
・Global Time Zones: Choose your desired time zone (Tokyo, New York, London, Sydney) to monitor the time most relevant to your trading strategy.
Market Status:
・Tokyo Market: The status will display "Tokyo OPEN" when the Tokyo market is active, and "Tokyo CLOSED" when it is outside of trading hours.
・London Market: Similarly, the indicator will show "London OPEN" or "London CLOSED" depending on whether the London market is currently active.
・New York Market: The New York market status follows the same structure, showing "NY OPEN" or "NY CLOSED."
Customization:
・Table Positioning: Easily move the table to the desired location on the chart to avoid overlap with other chart elements. The leftmost empty cell helps with alignment.
・Text and Background Color: Adjust the text and background colors to suit your personal preferences. You can also set independent colors for open and closed market statuses to easily distinguish between them.
Cautions and Disclaimer:
・Indicator Modifications: This indicator may be updated without prior notice, which could change or remove certain features.
・Trade Responsibility: This indicator is a tool to assist your trading, but responsibility for all trades remains with you. No guarantee of profit or success is implied, and losses can occur. Use it alongside your own analysis and strategy.
Digital Clock with Market Status and Alerts - 解説と使い方
概要:
Digital Clock with Market Status and Alerts インジケーターは、さまざまな世界のタイムゾーンで現在の時刻を表示し、東京、ロンドン、ニューヨークなどの主要な金融市場のステータスを提供します。このインジケーターにより、複数の市場のオープンおよびクローズ時間をリアルタイムで監視でき、市場がオープンする際にアラートを受け取ることができます。テーブルの位置、背景色、テキストカラー、フォントサイズなどのカスタマイズが可能です。
主な機能:
リアルタイムデジタル時計: 選択したタイムゾーン（東京、ニューヨーク、ロンドン、シドニー）の現在時刻を表示します。リアルタイムで更新され、時間、分、秒を正確に表示します。
世界の市場ステータス: 主要な金融市場のオープン/クローズ状況を表示します。
・東京市場: 午前9時～午後3時（日本時間）。
・ロンドン市場: 夏時間では16時～24時、冬時間では17時～1時（日本時間）。
・ニューヨーク市場: 夏時間では21時～5時、冬時間では22時～6時（日本時間）。
カスタマイズ可能な表示設定:
・背景色: 時計表示の背景色を設定できます。また、テーブルの左側に空白のセルを配置し、独立した背景色を設定することでテーブルの配置調整が可能です。
・時計と市場ステータスの色: 時計テキスト、オープン市場、クローズ市場の色を個別に設定できます。
・テキストサイズ: 小、標準、大から選択し、テキストサイズをカスタマイズ可能です。
・テーブル位置: デジタル時計と市場ステータスのテーブルをチャートのさまざまな場所（左上、中央上、右上、左下、中央下、右下）に配置できます。
市場オープン時のアラート: 市場（東京、ロンドン、ニューヨーク）がオープンするときにアラートを発し、リアルタイムで通知されます。これにより、重要な市場のオープン時間を逃さないようサポートします。
使い方:
セットアップ:
インジケーターを適用: チャートに「Digital Clock with Market Status and Alerts」インジケーターを追加し、タイムゾーン、テキストサイズ、背景色、テーブル位置を好みに応じてカスタマイズします。
市場ステータスを確認: 東京、ロンドン、ニューヨークの市場ステータスをリアルタイムで表示し、オープン/クローズ時間を把握できます。
アラートを受け取る: 市場オープン時のアラート機能により、重要な市場のオープンを見逃さないように通知が届きます。
時間管理:
・リアルタイム時計: 現在の時刻が秒単位で表示され、選択したタイムゾーンに基づいて正確に追跡できます。
・グローバルタイムゾーン: 東京、ニューヨーク、ロンドン、シドニーなど、トレードに関連するタイムゾーンを選択して監視できます。
市場ステータス:
・東京市場: 東京市場が開いていると「Tokyo OPEN」と表示され、閉じている場合は「Tokyo CLOSED」と表示されます。
・ロンドン市場: 同様に、「London OPEN」または「London CLOSED」が表示され、ロンドン市場のステータスを確認できます。
・ニューヨーク市場: ニューヨーク市場も「NY OPEN」または「NY CLOSED」で現在の状況が表示されます。
カスタマイズ:
・テーブル位置の調整: テーブルの位置を簡単に調整し、チャート上の他の要素と重ならないように配置できます。左側の空白セルで位置調整が可能です。
・テキストと背景色のカスタマイズ: テキストと背景の色を自分の好みに合わせて調整できます。また、オープン時とクローズ時の市場ステータスを区別するため、独立した色設定が可能です。
注意事項と免責事項:
・インジケーターの変更: このインジケーターは、予告なく変更や機能の削除が行われる場合があります。
・トレード責任: このインジケーターはトレードをサポートするツールであり、トレードに関する全責任はご自身にあります。利益を保証するものではなく、損失が発生する可能性があります。自分の分析や戦略と組み合わせて使用してください。
Composite Momentum█ Introduction
The Composite Momentum Indicator is a tool we came across that we found to be useful at detecting implied tops and bottoms within quick market cycles. Its approach to analyzing momentum through a combination of moving averages and summation techniques makes it a useful addition to the range of available indicators on TradingView.
█ How It Works
This indicator operates by calculating the difference between two moving averages—one fast and one slow, which can be customized by the user. The difference between these two averages is then expressed as a percentage of the fast moving average, forming the core momentum value which is then smoothed with an Exponential Moving Average is applied. The smoothed momentum is then compared across periods to identify directional changes in direction
Furthermore, the script calculates the absolute differences between consecutive momentum values. These differences are used to determine periods of momentum acceleration or deceleration, aiming to establish potential reversals.
In addition to tracking momentum changes, the indicator sums positive and negative momentum changes separately over a user-defined period. This summation is intended to provide a clearer picture of the prevailing market bias—whether it’s leaning towards strength or weakness.
Finally, the summed-up values are normalized to a percentage scale. This normalization helps in identifying potential tops and bottoms by comparing the relative strength of the momentum within a given cycle.
█ Usage
This indicator is primarily useful for traders who focus on detecting quick cycle tops and bottoms. It provides a view of momentum shifts that can signal these extremes, though it’s important to use it in conjunction with other tools and market analysis techniques. Given its ability to highlight potential reversals, it may be of interest to those who seek to understand short-term market dynamics.
█ Disclaimer
This script was discovered without any information about its author or original intent but was nonetheless ported from its original format that is available publicly. It’s provided here for educational purposes and should not be considered a guaranteed method for market analysis. Users are encouraged to test and understand the indicator thoroughly before applying it in real trading scenarios.
StyleLibraryLibrary "StyleLibrary"
A small library of Pine Script functions that return built-in style variables.
method sizeStyle(size)
Takes a `string` that returns the corresponding built-in size style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
size (string) : A `string` representing a built-in size style: `"Tiny"`, `"Small"`, `"Normal"`, `"Large"`,
`"Huge"`, `"Auto"`.
Returns: The respective built-in size style variable.
method sizeStyle(size)
Takes a `sizeStyle` that returns the corresponding built-in size style variable.
Namespace types: series sizeStyle
Parameters:
size (series sizeStyle) : A `sizeStyle` representing a built-in size style variable.
Returns: The respective built-in size style variable.
method lineStyle(style)
Takes a `string` that returns the corresponding built-in line style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
style (string) : A `string` representing a built-in line style: `"Dashed"`, `"Dotted"`, `"Solid"`.
Returns: The respective built-in line style variable.
method lineStyle(style)
Takes a `lineStyle` that returns the corresponding built-in line style variable.
Namespace types: series lineStyle
Parameters:
style (series lineStyle) : A `lineStyle` representing a built-in line style variable.
Returns: The respective built-in line style variable.
method labelStyle(style)
Takes a `string` that returns the corresponding built-in label style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
style (string) : A `string` representing a built-in label style:
`"Arrow Down"`, `"Arrow Up"`, `"Circle"`, `"Cross"`, `"Diamond"`, `"Flag"`,
`"Label Center"`, `"Label Down"`, `"Label Left"`, `"Label Lower Left"`,
`"Label Lower Right"`, `"Label Right"`, `"Label Up"`, `"Label Upper Left"`,
`"Label Upper Right"`, `"None"`, `"Square"`, `"Text Outline"`, `"Triangle Down"`,
`"Triangle Up"`, `"XCross"`.
Returns: The respective built-in label style variable.
method labelStyle(style)
Takes a `labelStyle` that returns the corresponding built-in label style variable.
Namespace types: series labelStyle
Parameters:
style (series labelStyle) : A `labelStyle` representing a built-in label style variable.
Returns: The respective built-in label style variable.
method fontStyle(font)
Takes a `string` that returns the corresponding built-in font style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
font (string) : A `string` representing a built-in font style: `"Default"`, `"Monospace"`.
Returns: The respective built-in font style variable.
method positionStyle(position)
Takes a `string` that returns the corresponding built-in position style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
position (string) : A `string` representing a built-in position style:
`"Bottom Center", `"Bottom Left", `"Bottom Right", `"Middle Center", `"Middle Left",
`"Middle Right", `"Top Center", `"Top Left", `"Top Right".
Returns: The respective built-in position style variable.
method displayStyle(display)
Takes a `simple string` that returns the corresponding built-in display style variable.
Namespace types: simple string, input string, const string
Parameters:
display (simple string) : A `simple string` representing a built-in display style: `"All"`, `"Data Window"`,
`"None"`, `"Pane"`, `"Price Scale"`, `"Status Line"`.
Returns: The respective built-in display style variable.
Magic Linear Regression Channel [MW]Introduction
The Magic Linear Regression Channel indicator provides users with a way to quickly include a linear regression channel ANYWHERE on their chart, in order to find channel breakouts and bounces within any time period. It uses a novel method that allows users to adjust the start and end period of the regression channel in order to quickly make adjustments faster, with fewer steps, and with more precision than with any other linear regression channel tool. It includes Fibonacci bands AND a horizontal mode in order for users to quickly define significant price levels based on the high, low, open, and close prices defined by the start period.
Settings
Start Time: This is initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
End time: This is also initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
Horizontal Line: This forces the baseline to be horizontal. The band distance is defined by the maximum price distance from the band.
Horizontal Line Type: This snaps the horizontal line to the close, high, low, or open price. Or, it can also use a regression calculation for the selected time period to define the y-position of the line.
Extend Line N Bars: How many bars to the left in which to extend the baseline and bands.
Show Baseline ONLY!!: Removes all lines except the baseline and it’s extension.
Add Half Band: Includes a band that is half the distance between the baseline and the top and bottom bands
Add Outer Fibonacci Band: Includes a band that is 1.618 (phi) times the default band distance
Add Inner Fibonacci Band - Upper: Includes a band that is 0.618 (1/phi) times the default band distance
Add Inner Fibonacci Band - Lower: Includes a band that is 0.382 (1 - 1/phi) times the default band distance
Calculations
This indicator uses the least squares approach for generating a straight regression line, which can be reviewed at Wikipedia’s “Simple Linear Regression” page. It sums all of the x-values, and y-values, as well as the sum of the product of corresponding x and y values, and the sum of the squares of the x-values. These values are used to calculate the slope and intercept using the following equations:
slope = (n * sum_xy - sum_x * sum_y) / (n * sum_xx - sum_x * sum_x)
And
intercept = (sum_y - slope * sum_x) / n
The slope and intercept are then used to generate the baseline and the corresponding bands using the user-selected offsets.
How to Use
When the Magic Linear Regression Channel indicator is first added to the chart, there will be a blue prompt behind the “Indicators, Metrics & Strategies” window. Close the window, then select a START POINT by clicking at a desired location on the chart. Next, you will be prompted to select an END POINT. The end point MUST be placed after the START POINT. At this time a channel will be generated. Once you’ve selected the START POINT and END POINT, you can adjust them by dragging them anywhere on the chart. Each adjustment will generate a new channel making it easier for you to quickly visualize and recognize any channel exits and bounces.
The Magic Linear Regression Channel indicator works great at identifying wave patterns. Place the start line at a top or bottom pivot point. Place the end line at the next respective top or bottom pivot. This will give you a complete wave form to work with. When price reaches a band and rejects, it can be a strong indication that price may move back to one of the bands in the channel. If price exits the channel with volume that supports the exit, it may be an indication of a breakout.
You can also use the horizontal mode to identify key levels, then add Fibonacci bands based on regression calculations for the given time period to provide more meaningful areas of support and resistance.
Other Usage Notes and Limitations
Occasionally, off-by-1 errors appear which makes the extended lines protrude at a slightly incorrect angle. This is a known bug and will be addressed in the next release.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Advanced Keltner Channel/Oscillator [MyTradingCoder]This indicator combines a traditional Keltner Channel overlay with an oscillator, providing a comprehensive view of price action, trend, and momentum. The core of this indicator is its advanced ATR calculation, which uses statistical methods to provide a more robust measure of volatility.
Starting with the overlay component, the center line is created using a biquad low-pass filter applied to the chosen price source. This provides a smoother representation of price than a simple moving average. The upper and lower channel lines are then calculated using the statistically derived ATR, with an additional set of mid-lines between the center and outer lines. This creates a more nuanced view of price action within the channel.
The color coding of the center line provides an immediate visual cue of the current price momentum. As the price moves up relative to the ATR, the line shifts towards the bullish color, and vice versa for downward moves. This color gradient allows for quick assessment of the current market sentiment.
The oscillator component transforms the channel into a different perspective. It takes the price's position within the channel and maps it to either a normalized -100 to +100 scale or displays it in price units, depending on your settings. This oscillator essentially shows where the current price is in relation to the channel boundaries.
The oscillator includes two key lines: the main oscillator line and a signal line. The main line represents the current position within the channel, smoothed by an exponential moving average (EMA). The signal line is a further smoothed version of the oscillator line. The interaction between these two lines can provide trading signals, similar to how MACD is often used.
When the oscillator line crosses above the signal line, it might indicate bullish momentum, especially if this occurs in the lower half of the oscillator range. Conversely, the oscillator line crossing below the signal line could signal bearish momentum, particularly if it happens in the upper half of the range.
The oscillator's position relative to its own range is also informative. Values near the top of the range (close to 100 if normalized) suggest that price is near the upper Keltner Channel band, indicating potential overbought conditions. Values near the bottom of the range (close to -100 if normalized) suggest proximity to the lower band, potentially indicating oversold conditions.
One of the strengths of this indicator is how the overlay and oscillator work together. For example, if the price is touching the upper band on the overlay, you'd see the oscillator at or near its maximum value. This confluence of signals can provide stronger evidence of overbought conditions. Similarly, the oscillator hitting extremes can draw your attention to price action at the channel boundaries on the overlay.
The mid-lines on both the overlay and oscillator provide additional nuance. On the overlay, price action between the mid-line and outer line might suggest strong but not extreme momentum. On the oscillator, this would correspond to readings in the outer quartiles of the range.
The customizable visual settings allow you to adjust the indicator to your preferences. The glow effects and color coding can make it easier to quickly interpret the current market conditions at a glance.
Overlay Component:
The overlay displays Keltner Channel bands dynamically adapting to market conditions, providing clear visual cues for potential trend reversals, breakouts, and overbought/oversold zones.
The center line is a biquad low-pass filter applied to the chosen price source.
Upper and lower channel lines are calculated using a statistically derived ATR.
Includes mid-lines between the center and outer channel lines.
Color-coded based on price movement relative to the ATR.
Oscillator Component:
The oscillator component complements the overlay, highlighting momentum and potential turning points.
Normalized values make it easy to compare across different assets and timeframes.
Signal line crossovers generate potential buy/sell signals.
Advanced ATR Calculation:
Uses a unique method to compute ATR, incorporating concepts like root mean square (RMS) and z-score clamping.
Provides both an average and mode-based ATR value.
Customizable Visual Settings:
Adjustable colors for bullish and bearish moves, oscillator lines, and channel components.
Options for line width, transparency, and glow effects.
Ability to display overlay, oscillator, or both simultaneously.
Flexible Parameters:
Customizable inputs for channel width multiplier, ATR period, smoothing factors, and oscillator settings.
Adjustable Q factor for the biquad filter.
Key Advantages:
Advanced ATR Calculation: Utilizes a statistical method to generate ATR, ensuring greater responsiveness and accuracy in volatile markets.
Overlay and Oscillator: Provides a comprehensive view of price action, combining trend and momentum analysis.
Customizable: Adjust settings to fine-tune the indicator to your specific needs and trading style.
Visually Appealing: Clear and concise design for easy interpretation.
The ATR (Average True Range) in this indicator is derived using a sophisticated statistical method that differs from the traditional ATR calculation. It begins by calculating the True Range (TR) as the difference between the high and low of each bar. Instead of a simple moving average, it computes the Root Mean Square (RMS) of the TR over the specified period, giving more weight to larger price movements. The indicator then calculates a Z-score by dividing the TR by the RMS, which standardizes the TR relative to recent volatility. This Z-score is clamped to a maximum value (10 in this case) to prevent extreme outliers from skewing the results, and then rounded to a specified number of decimal places (2 in this script).
These rounded Z-scores are collected in an array, keeping track of how many times each value occurs. From this array, two key values are derived: the mode, which is the most frequently occurring Z-score, and the average, which is the weighted average of all Z-scores. These values are then scaled back to price units by multiplying by the RMS.
Now, let's examine how these values are used in the indicator. For the Keltner Channel lines, the mid lines (top and bottom) use the mode of the ATR, representing the most common volatility state. The max lines (top and bottom) use the average of the ATR, incorporating all volatility states, including less common but larger moves. By using the mode for the mid lines and the average for the max lines, the indicator provides a nuanced view of volatility. The mid lines represent the "typical" market state, while the max lines account for less frequent but significant price movements.
For the color coding of the center line, the mode of the ATR is used to normalize the price movement. The script calculates the difference between the current price and the price 'degree' bars ago (default is 2), and then divides this difference by the mode of the ATR. The resulting value is passed through an arctangent function and scaled to a 0-1 range. This scaled value is used to create a color gradient between the bearish and bullish colors.
Using the mode of the ATR for this color coding ensures that the color changes are based on the most typical volatility state of the market. This means that the color will change more quickly in low volatility environments and more slowly in high volatility environments, providing a consistent visual representation of price momentum relative to current market conditions.
Using a good IIR (Infinite Impulse Response) low-pass filter, such as the biquad filter implemented in this indicator, offers significant advantages over simpler moving averages like the EMA (Exponential Moving Average) or other basic moving averages.
At its core, an EMA is indeed a simple, single-pole IIR filter, but it has limitations in terms of its frequency response and phase delay characteristics. The biquad filter, on the other hand, is a two-pole, two-zero filter that provides superior control over the frequency response curve. This allows for a much sharper cutoff between the passband and stopband, meaning it can more effectively separate the signal (in this case, the underlying price trend) from the noise (short-term price fluctuations).
The improved frequency response of a well-designed biquad filter means it can achieve a better balance between smoothness and responsiveness. While an EMA might need a longer period to sufficiently smooth out price noise, potentially leading to more lag, a biquad filter can achieve similar or better smoothing with less lag. This is crucial in financial markets where timely information is vital for making trading decisions.
Moreover, the biquad filter allows for independent control of the cutoff frequency and the Q factor. The Q factor, in particular, is a powerful parameter that affects the filter's resonance at the cutoff frequency. By adjusting the Q factor, users can fine-tune the filter's behavior to suit different market conditions or trading styles. This level of control is simply not available with basic moving averages.
Another advantage of the biquad filter is its superior phase response. In the context of financial data, this translates to more consistent lag across different frequency components of the price action. This can lead to more reliable signals, especially when it comes to identifying trend changes or price reversals.
The computational efficiency of biquad filters is also worth noting. Despite their more complex mathematical foundation, biquad filters can be implemented very efficiently, often requiring only a few operations per sample. This makes them suitable for real-time applications and high-frequency trading scenarios.
Furthermore, the use of a more sophisticated filter like the biquad can help in reducing false signals. The improved noise rejection capabilities mean that minor price fluctuations are less likely to cause unnecessary crossovers or indicator movements, potentially leading to fewer false breakouts or reversal signals.
In the specific context of a Keltner Channel, using a biquad filter for the center line can provide a more stable and reliable basis for the entire indicator. It can help in better defining the overall trend, which is crucial since the Keltner Channel is often used for trend-following strategies. The smoother, yet more responsive center line can lead to more accurate channel boundaries, potentially improving the reliability of overbought/oversold signals and breakout indications.
In conclusion, this advanced Keltner Channel indicator represents a significant evolution in technical analysis tools, combining the power of traditional Keltner Channels with modern statistical methods and signal processing techniques. By integrating a sophisticated ATR calculation, a biquad low-pass filter, and a complementary oscillator component, this indicator offers traders a comprehensive and nuanced view of market dynamics.
The indicator's strength lies in its ability to adapt to varying market conditions, providing clear visual cues for trend identification, momentum assessment, and potential reversal points. The use of statistically derived ATR values for channel construction and the implementation of a biquad filter for the center line result in a more responsive and accurate representation of price action compared to traditional methods.
Furthermore, the dual nature of this indicator – functioning as both an overlay and an oscillator – allows traders to simultaneously analyze price trends and momentum from different perspectives. This multifaceted approach can lead to more informed decision-making and potentially more reliable trading signals.
The high degree of customization available in the indicator's settings enables traders to fine-tune its performance to suit their specific trading styles and market preferences. From adjustable visual elements to flexible parameter inputs, users can optimize the indicator for various trading scenarios and time frames.
Ultimately, while no indicator can predict market movements with certainty, this advanced Keltner Channel provides traders with a powerful tool for market analysis. By offering a more sophisticated approach to measuring volatility, trend, and momentum, it equips traders with valuable insights to navigate the complex world of financial markets. As with any trading tool, it should be used in conjunction with other forms of analysis and within a well-defined risk management framework to maximize its potential benefits.
Tether Ratio ChannelTether Ratio Channel is an on-chain metric that tracks the ebb & flow of the ratio of BTC market cap / stablecoin market cap.
This ratio is relevant to traders, as it tends to lead total crypto market cap's short to medium term trend, and has for many years.
The ratio's most straightforwards visualization may be Stablecoin Supply Oscillator , a legacy on-chain metric that captures the ratio but isn't useful on its own as a trading tool.
Tether Ratio Channel builds on top of Stablecoin Supply Oscillator, to create a new metric that's:
Signal-generating , with clear entry & exit signals
Unambiguous , so use is mechanical
Optimized , with the intent to generate signals as close as possible to BTC local tops & bottoms
Normalized across its history , so each signal has a rich uniform history & context
METRIC CONSTRUCTION
Tether Ratio Channel is a higher timeframe RSI of Stablecoin Supply Oscillator, bound inside a bollinger band channel, normalized and smoothed for optimal signal clarity.
Instead of chart price as the source, the metric uses a proxy for stablecoin market cap:
(USDT + USDC + DAI) divided by BTC mkt cap
But it's named for Tether specifically, because USDT just completely dominates the asset class.
Default settings are very close to the on-chain metric original, but not identical. Settings are adjustable in the metric inputs.
VERTICAL LOCATION IN THE CHANNEL
The lower the yellow print is on the metric's Y-axis, the more upside potential total crypto market cap typically has.
The higher the yellow print is on the metric's Y-axis, the more downside risk most crypto assets typically have.
SWING TRADE SIGNALS
Tether Ratio Channel is signal-generating, a simple cross of the metric (the yellow line) and its weighted moving average (the white line) is the signal.
A bullish cross below the green horizontal target is a high conviction buy signal
A bullish cross above the green target is a lower conviction buy signal, but historically still tends to make for a good entry
Any bearish cross is typically a good time to take profits
Any bearish cross above 55 (on the metric's Y axis) tends to coincide with BTC local tops
Buy signals are visualized with a green vertical, and a background fill that persists until the next sell signal
High conviction buy signals (below the green line) also print an arrow, if enabled.
Background fills and arrow prints will only appear if the chart timeframe is equal to or lower than the 8H chart. (Or whatever the metric's timeframe input is set to, if the user changes default settings).
Qty CalculatorThis Pine Script indicator, titled "Qty Calculator," is a customizable tool designed to assist traders in managing their trades by calculating key metrics related to risk management. It takes into account your total capital, entry price, stop-loss level, and desired risk percentage to provide a comprehensive overview of potential trade outcomes.
Key Features:
User Inputs:
Total Capital: The total amount of money available for trading.
Entry Price: The price at which the trader enters the trade.
Stop Loss: The price level at which the trade will automatically close to prevent further losses.
Risk Percentage: The percentage of the total capital that the trader is willing to risk on a single trade.
Customizable Table:
Position: The indicator allows you to choose the position of the table on the chart, with options including top-left, top-center, top-right, bottom-left, bottom-center, and bottom-right.
Size: You can adjust the number of rows and columns in the table to fit your needs.
Risk Management Calculations:
Difference Calculation: The difference between the entry price and the stop-loss level.
Risk Per Trade: Calculated as a percentage of your total capital.
Risk Levels: The indicator evaluates multiple risk levels (0.10%, 0.25%, 0.50%, 1.00%) and calculates the quantity, capital per trade, percentage of total capital, and the risk amount associated with each level.
R-Multiples Calculation:
The indicator calculates potential profit levels at 2x, 3x, 4x, and 5x the risk (R-Multiples), showing the potential gains if the trade moves in your favor by these multiples.
Table Display:
The table includes the following columns:
CapRisk%: Displays the risk percentage.
Qty: The quantity of the asset you should trade.
Cap/Trade: The capital allocated per trade.
%OfCapital: The percentage of total capital used in the trade.
Risk Amount: The monetary risk taken on each trade.
R Gains: Displays potential gains at different R-Multiples.
This indicator is particularly useful for traders who prioritize risk management and want to ensure that their trades are aligned with their capital and risk tolerance. By providing a clear and customizable table of critical metrics, it helps traders make informed decisions and better manage their trading strategies.
NEXT BAR PercentagesNEXT BAR Percentages Indicator
This Pine Script code implements the "NEXT BAR Percentages" indicator, designed to analyze and display percentage changes between consecutive bars on a TradingView chart. The script provides valuable insights into how percentage changes in price behave after significant price movements, aiding traders in identifying potential trends or reversals.
Key Features:
Percentage Change Calculations :
Close-to-Close : Calculates the percentage change between the close of the current bar and the close of the previous bar.
High-to-Close : Calculates the percentage change between the high of the current bar and the close of the previous bar.
Low-to-Close : Calculates the percentage change between the low of the current bar and the close of the previous bar.
High-to-Close (Wick) : Computes the percentage change from the close to the high of the current bar.
Low-to-Close (Wick) : Computes the percentage change from the close to the low of the current bar.
Dynamic Table Display :
Creates a table on the chart to display various statistics related to percentage changes.
The table position is customizable, with options including "Top Left," "Middle Left," "Bottom Left," "Top Right," "Middle Right," "Bottom Right," "Top Center," "Middle Center," and "Bottom Center."
Count and Average Calculations :
High POS/NEG Counts : Counts occurrences of significant positive and negative percentage changes based on user-defined thresholds.
High POS/NEG Average : Computes the average percentage change following high positive and negative percentage changes.
Next Bar Statistics : Provides statistics on the percentage change of the next bar following identified significant price movements.
Visual Indicators :
Labels : Plots arrows on the chart when a high positive or high negative percentage change is detected, visually highlighting these events.
Customizable Input Parameters :
Adjust the thresholds for identifying high positive and negative percentage changes ( highpos, highposEnd, highneg, highnegEnd ).
Specify the start date for analysis ( teststartdate ), allowing for focused period analysis.
Usage:
Traders : Gain insights into price behavior following significant movements to make informed trading decisions.
Analysis : Customizable parameters and visual indicators enable detailed analysis of price action and trend identification.
Enhance your chart analysis with this indicator for a clear, data-driven view of percentage changes and their implications for future price movements.
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
PubLibCandleTrendLibrary "PubLibCandleTrend"
candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development
chh()
candle higher high condition
Returns: bool
chl()
candle higher low condition
Returns: bool
clh()
candle lower high condition
Returns: bool
cll()
candle lower low condition
Returns: bool
cdt()
candle double top condition
Returns: bool
cdb()
candle double bottom condition
Returns: bool
gc()
green candle condition
Returns: bool
gchh()
green candle higher high condition
Returns: bool
gchl()
green candle higher low condition
Returns: bool
gclh()
green candle lower high condition
Returns: bool
gcll()
green candle lower low condition
Returns: bool
gcdt()
green candle double top condition
Returns: bool
gcdb()
green candle double bottom condition
Returns: bool
rc()
red candle condition
Returns: bool
rchh()
red candle higher high condition
Returns: bool
rchl()
red candle higher low condition
Returns: bool
rclh()
red candle lower high condition
Returns: bool
rcll()
red candle lower low condition
Returns: bool
rcdt()
red candle double top condition
Returns: bool
rcdb()
red candle double bottom condition
Returns: bool
chh_1p()
1-part candle higher high condition
Returns: bool
chh_2p()
2-part candle higher high condition
Returns: bool
chh_3p()
3-part candle higher high condition
Returns: bool
chh_4p()
4-part candle higher high condition
Returns: bool
chh_5p()
5-part candle higher high condition
Returns: bool
chh_6p()
6-part candle higher high condition
Returns: bool
chh_7p()
7-part candle higher high condition
Returns: bool
chh_8p()
8-part candle higher high condition
Returns: bool
chh_9p()
9-part candle higher high condition
Returns: bool
chh_10p()
10-part candle higher high condition
Returns: bool
chh_11p()
11-part candle higher high condition
Returns: bool
chh_12p()
12-part candle higher high condition
Returns: bool
chh_13p()
13-part candle higher high condition
Returns: bool
chh_14p()
14-part candle higher high condition
Returns: bool
chh_15p()
15-part candle higher high condition
Returns: bool
chh_16p()
16-part candle higher high condition
Returns: bool
chh_17p()
17-part candle higher high condition
Returns: bool
chh_18p()
18-part candle higher high condition
Returns: bool
chh_19p()
19-part candle higher high condition
Returns: bool
chh_20p()
20-part candle higher high condition
Returns: bool
chh_21p()
21-part candle higher high condition
Returns: bool
chh_22p()
22-part candle higher high condition
Returns: bool
chh_23p()
23-part candle higher high condition
Returns: bool
chh_24p()
24-part candle higher high condition
Returns: bool
chh_25p()
25-part candle higher high condition
Returns: bool
chh_26p()
26-part candle higher high condition
Returns: bool
chh_27p()
27-part candle higher high condition
Returns: bool
chh_28p()
28-part candle higher high condition
Returns: bool
chh_29p()
29-part candle higher high condition
Returns: bool
chh_30p()
30-part candle higher high condition
Returns: bool
chl_1p()
1-part candle higher low condition
Returns: bool
chl_2p()
2-part candle higher low condition
Returns: bool
chl_3p()
3-part candle higher low condition
Returns: bool
chl_4p()
4-part candle higher low condition
Returns: bool
chl_5p()
5-part candle higher low condition
Returns: bool
chl_6p()
6-part candle higher low condition
Returns: bool
chl_7p()
7-part candle higher low condition
Returns: bool
chl_8p()
8-part candle higher low condition
Returns: bool
chl_9p()
9-part candle higher low condition
Returns: bool
chl_10p()
10-part candle higher low condition
Returns: bool
chl_11p()
11-part candle higher low condition
Returns: bool
chl_12p()
12-part candle higher low condition
Returns: bool
chl_13p()
13-part candle higher low condition
Returns: bool
chl_14p()
14-part candle higher low condition
Returns: bool
chl_15p()
15-part candle higher low condition
Returns: bool
chl_16p()
16-part candle higher low condition
Returns: bool
chl_17p()
17-part candle higher low condition
Returns: bool
chl_18p()
18-part candle higher low condition
Returns: bool
chl_19p()
19-part candle higher low condition
Returns: bool
chl_20p()
20-part candle higher low condition
Returns: bool
chl_21p()
21-part candle higher low condition
Returns: bool
chl_22p()
22-part candle higher low condition
Returns: bool
chl_23p()
23-part candle higher low condition
Returns: bool
chl_24p()
24-part candle higher low condition
Returns: bool
chl_25p()
25-part candle higher low condition
Returns: bool
chl_26p()
26-part candle higher low condition
Returns: bool
chl_27p()
27-part candle higher low condition
Returns: bool
chl_28p()
28-part candle higher low condition
Returns: bool
chl_29p()
29-part candle higher low condition
Returns: bool
chl_30p()
30-part candle higher low condition
Returns: bool
clh_1p()
1-part candle lower high condition
Returns: bool
clh_2p()
2-part candle lower high condition
Returns: bool
clh_3p()
3-part candle lower high condition
Returns: bool
clh_4p()
4-part candle lower high condition
Returns: bool
clh_5p()
5-part candle lower high condition
Returns: bool
clh_6p()
6-part candle lower high condition
Returns: bool
clh_7p()
7-part candle lower high condition
Returns: bool
clh_8p()
8-part candle lower high condition
Returns: bool
clh_9p()
9-part candle lower high condition
Returns: bool
clh_10p()
10-part candle lower high condition
Returns: bool
clh_11p()
11-part candle lower high condition
Returns: bool
clh_12p()
12-part candle lower high condition
Returns: bool
clh_13p()
13-part candle lower high condition
Returns: bool
clh_14p()
14-part candle lower high condition
Returns: bool
clh_15p()
15-part candle lower high condition
Returns: bool
clh_16p()
16-part candle lower high condition
Returns: bool
clh_17p()
17-part candle lower high condition
Returns: bool
clh_18p()
18-part candle lower high condition
Returns: bool
clh_19p()
19-part candle lower high condition
Returns: bool
clh_20p()
20-part candle lower high condition
Returns: bool
clh_21p()
21-part candle lower high condition
Returns: bool
clh_22p()
22-part candle lower high condition
Returns: bool
clh_23p()
23-part candle lower high condition
Returns: bool
clh_24p()
24-part candle lower high condition
Returns: bool
clh_25p()
25-part candle lower high condition
Returns: bool
clh_26p()
26-part candle lower high condition
Returns: bool
clh_27p()
27-part candle lower high condition
Returns: bool
clh_28p()
28-part candle lower high condition
Returns: bool
clh_29p()
29-part candle lower high condition
Returns: bool
clh_30p()
30-part candle lower high condition
Returns: bool
cll_1p()
1-part candle lower low condition
Returns: bool
cll_2p()
2-part candle lower low condition
Returns: bool
cll_3p()
3-part candle lower low condition
Returns: bool
cll_4p()
4-part candle lower low condition
Returns: bool
cll_5p()
5-part candle lower low condition
Returns: bool
cll_6p()
6-part candle lower low condition
Returns: bool
cll_7p()
7-part candle lower low condition
Returns: bool
cll_8p()
8-part candle lower low condition
Returns: bool
cll_9p()
9-part candle lower low condition
Returns: bool
cll_10p()
10-part candle lower low condition
Returns: bool
cll_11p()
11-part candle lower low condition
Returns: bool
cll_12p()
12-part candle lower low condition
Returns: bool
cll_13p()
13-part candle lower low condition
Returns: bool
cll_14p()
14-part candle lower low condition
Returns: bool
cll_15p()
15-part candle lower low condition
Returns: bool
cll_16p()
16-part candle lower low condition
Returns: bool
cll_17p()
17-part candle lower low condition
Returns: bool
cll_18p()
18-part candle lower low condition
Returns: bool
cll_19p()
19-part candle lower low condition
Returns: bool
cll_20p()
20-part candle lower low condition
Returns: bool
cll_21p()
21-part candle lower low condition
Returns: bool
cll_22p()
22-part candle lower low condition
Returns: bool
cll_23p()
23-part candle lower low condition
Returns: bool
cll_24p()
24-part candle lower low condition
Returns: bool
cll_25p()
25-part candle lower low condition
Returns: bool
cll_26p()
26-part candle lower low condition
Returns: bool
cll_27p()
27-part candle lower low condition
Returns: bool
cll_28p()
28-part candle lower low condition
Returns: bool
cll_29p()
29-part candle lower low condition
Returns: bool
cll_30p()
30-part candle lower low condition
Returns: bool
gc_1p()
1-part green candle condition
Returns: bool
gc_2p()
2-part green candle condition
Returns: bool
gc_3p()
3-part green candle condition
Returns: bool
gc_4p()
4-part green candle condition
Returns: bool
gc_5p()
5-part green candle condition
Returns: bool
gc_6p()
6-part green candle condition
Returns: bool
gc_7p()
7-part green candle condition
Returns: bool
gc_8p()
8-part green candle condition
Returns: bool
gc_9p()
9-part green candle condition
Returns: bool
gc_10p()
10-part green candle condition
Returns: bool
gc_11p()
11-part green candle condition
Returns: bool
gc_12p()
12-part green candle condition
Returns: bool
gc_13p()
13-part green candle condition
Returns: bool
gc_14p()
14-part green candle condition
Returns: bool
gc_15p()
15-part green candle condition
Returns: bool
gc_16p()
16-part green candle condition
Returns: bool
gc_17p()
17-part green candle condition
Returns: bool
gc_18p()
18-part green candle condition
Returns: bool
gc_19p()
19-part green candle condition
Returns: bool
gc_20p()
20-part green candle condition
Returns: bool
gc_21p()
21-part green candle condition
Returns: bool
gc_22p()
22-part green candle condition
Returns: bool
gc_23p()
23-part green candle condition
Returns: bool
gc_24p()
24-part green candle condition
Returns: bool
gc_25p()
25-part green candle condition
Returns: bool
gc_26p()
26-part green candle condition
Returns: bool
gc_27p()
27-part green candle condition
Returns: bool
gc_28p()
28-part green candle condition
Returns: bool
gc_29p()
29-part green candle condition
Returns: bool
gc_30p()
30-part green candle condition
Returns: bool
rc_1p()
1-part red candle condition
Returns: bool
rc_2p()
2-part red candle condition
Returns: bool
rc_3p()
3-part red candle condition
Returns: bool
rc_4p()
4-part red candle condition
Returns: bool
rc_5p()
5-part red candle condition
Returns: bool
rc_6p()
6-part red candle condition
Returns: bool
rc_7p()
7-part red candle condition
Returns: bool
rc_8p()
8-part red candle condition
Returns: bool
rc_9p()
9-part red candle condition
Returns: bool
rc_10p()
10-part red candle condition
Returns: bool
rc_11p()
11-part red candle condition
Returns: bool
rc_12p()
12-part red candle condition
Returns: bool
rc_13p()
13-part red candle condition
Returns: bool
rc_14p()
14-part red candle condition
Returns: bool
rc_15p()
15-part red candle condition
Returns: bool
rc_16p()
16-part red candle condition
Returns: bool
rc_17p()
17-part red candle condition
Returns: bool
rc_18p()
18-part red candle condition
Returns: bool
rc_19p()
19-part red candle condition
Returns: bool
rc_20p()
20-part red candle condition
Returns: bool
rc_21p()
21-part red candle condition
Returns: bool
rc_22p()
22-part red candle condition
Returns: bool
rc_23p()
23-part red candle condition
Returns: bool
rc_24p()
24-part red candle condition
Returns: bool
rc_25p()
25-part red candle condition
Returns: bool
rc_26p()
26-part red candle condition
Returns: bool
rc_27p()
27-part red candle condition
Returns: bool
rc_28p()
28-part red candle condition
Returns: bool
rc_29p()
29-part red candle condition
Returns: bool
rc_30p()
30-part red candle condition
Returns: bool
cdut()
candle double uptrend condition
Returns: bool
cddt()
candle double downtrend condition
Returns: bool
cdut_1p()
1-part candle double uptrend condition
Returns: bool
cdut_2p()
2-part candle double uptrend condition
Returns: bool
cdut_3p()
3-part candle double uptrend condition
Returns: bool
cdut_4p()
4-part candle double uptrend condition
Returns: bool
cdut_5p()
5-part candle double uptrend condition
Returns: bool
cdut_6p()
6-part candle double uptrend condition
Returns: bool
cdut_7p()
7-part candle double uptrend condition
Returns: bool
cdut_8p()
8-part candle double uptrend condition
Returns: bool
cdut_9p()
9-part candle double uptrend condition
Returns: bool
cdut_10p()
10-part candle double uptrend condition
Returns: bool
cdut_11p()
11-part candle double uptrend condition
Returns: bool
cdut_12p()
12-part candle double uptrend condition
Returns: bool
cdut_13p()
13-part candle double uptrend condition
Returns: bool
cdut_14p()
14-part candle double uptrend condition
Returns: bool
cdut_15p()
15-part candle double uptrend condition
Returns: bool
cdut_16p()
16-part candle double uptrend condition
Returns: bool
cdut_17p()
17-part candle double uptrend condition
Returns: bool
cdut_18p()
18-part candle double uptrend condition
Returns: bool
cdut_19p()
19-part candle double uptrend condition
Returns: bool
cdut_20p()
20-part candle double uptrend condition
Returns: bool
cdut_21p()
21-part candle double uptrend condition
Returns: bool
cdut_22p()
22-part candle double uptrend condition
Returns: bool
cdut_23p()
23-part candle double uptrend condition
Returns: bool
cdut_24p()
24-part candle double uptrend condition
Returns: bool
cdut_25p()
25-part candle double uptrend condition
Returns: bool
cdut_26p()
26-part candle double uptrend condition
Returns: bool
cdut_27p()
27-part candle double uptrend condition
Returns: bool
cdut_28p()
28-part candle double uptrend condition
Returns: bool
cdut_29p()
29-part candle double uptrend condition
Returns: bool
cdut_30p()
30-part candle double uptrend condition
Returns: bool
cddt_1p()
1-part candle double downtrend condition
Returns: bool
cddt_2p()
2-part candle double downtrend condition
Returns: bool
cddt_3p()
3-part candle double downtrend condition
Returns: bool
cddt_4p()
4-part candle double downtrend condition
Returns: bool
cddt_5p()
5-part candle double downtrend condition
Returns: bool
cddt_6p()
6-part candle double downtrend condition
Returns: bool
cddt_7p()
7-part candle double downtrend condition
Returns: bool
cddt_8p()
8-part candle double downtrend condition
Returns: bool
cddt_9p()
9-part candle double downtrend condition
Returns: bool
cddt_10p()
10-part candle double downtrend condition
Returns: bool
cddt_11p()
11-part candle double downtrend condition
Returns: bool
cddt_12p()
12-part candle double downtrend condition
Returns: bool
cddt_13p()
13-part candle double downtrend condition
Returns: bool
cddt_14p()
14-part candle double downtrend condition
Returns: bool
cddt_15p()
15-part candle double downtrend condition
Returns: bool
cddt_16p()
16-part candle double downtrend condition
Returns: bool
cddt_17p()
17-part candle double downtrend condition
Returns: bool
cddt_18p()
18-part candle double downtrend condition
Returns: bool
cddt_19p()
19-part candle double downtrend condition
Returns: bool
cddt_20p()
20-part candle double downtrend condition
Returns: bool
cddt_21p()
21-part candle double downtrend condition
Returns: bool
cddt_22p()
22-part candle double downtrend condition
Returns: bool
cddt_23p()
23-part candle double downtrend condition
Returns: bool
cddt_24p()
24-part candle double downtrend condition
Returns: bool
cddt_25p()
25-part candle double downtrend condition
Returns: bool
cddt_26p()
26-part candle double downtrend condition
Returns: bool
cddt_27p()
27-part candle double downtrend condition
Returns: bool
cddt_28p()
28-part candle double downtrend condition
Returns: bool
cddt_29p()
29-part candle double downtrend condition
Returns: bool
cddt_30p()
30-part candle double downtrend condition
Returns: bool
ATR Price Range Prediction V.2### ATR Price Range Prediction V.2
This script calculates the expected high and low prices for the current day based on the Average True Range (ATR) and displays the proportion of days where the daily range (high - low) is greater than or equal to the ATR. Additionally, the script provides an option to adjust the size of the text displayed in the top-right corner of the chart.
#### How It Works
1. **ATR Calculation**: The script calculates the ATR for a specified period (`atrPeriod`). ATR is a measure of volatility that represents the average range between the high and low prices over a specified number of periods.
2. **Expected High and Low Calculation**:
- **Expected High**: Calculated by adding the ATR value to the low price of the current day.
- **Expected Low**: Calculated by subtracting the ATR value from the high price of the current day.
3. **Proportion Calculation**: The script calculates the proportion of days where the daily range (high - low) is greater than or equal to the ATR value. This proportion is updated in real-time as new data comes in.
4. **Table Display**: Instead of displaying labels on each candle, the script shows the expected high, expected low, and the calculated proportion in a table located at the top-right corner of the chart. The size of the text in this table can be adjusted using the `Table Size` input.
5. **Color Coding**: The script changes the color of the bars to yellow if the daily range is greater than or equal to the ATR value, making it easy to identify these bars visually.
#### How to Use
- **ATR Period (`atrPeriod`)**: Adjust the period for the ATR calculation using the input parameter. The default value is 14.
- **Table Size (`tableSizeOption`)**: Choose the size of the text displayed in the table. Options include `tiny`, `small`, `normal`, `large`, and `huge`.
- **Expected High and Low**: Use the green and red lines to identify potential target prices or stop-loss levels for your trades. The green line represents the expected high, and the red line represents the expected low.
- **Proportion**: The table in the top-right corner of the chart shows the proportion of days where the daily range is greater than or equal to the ATR value. This can provide insight into the volatility of the asset.
- **Color Coding**: Yellow bars indicate days where the daily range is greater than or equal to the ATR value.
---
### ภาษาไทย
### ATR คาดการณ์ราคาสูงสุดและต่ำสุด พร้อมสัดส่วน
สคริปต์นี้คำนวณราคาสูงสุดและต่ำสุดที่คาดการณ์สำหรับวันปัจจุบันโดยอิงจากค่าเฉลี่ยช่วงที่แท้จริง (ATR) และแสดงสัดส่วนของวันที่ช่วงราคาต่อวัน (สูง - ต่ำ) มากกว่าหรือเท่ากับค่า ATR นอกจากนี้ยังมีตัวเลือกในการปรับขนาดข้อความที่แสดงในกล่องข้อความมุมขวาบนของกราฟ
#### วิธีการทำงาน
1. **การคำนวณ ATR**: สคริปต์คำนวณค่า ATR สำหรับช่วงเวลาที่กำหนด (`atrPeriod`) ATR เป็นมาตรวัดความผันผวนที่แสดงช่วงเฉลี่ยระหว่างราคาสูงสุดและต่ำสุดในช่วงเวลาที่กำหนด
2. **การคำนวณราคาสูงสุดและต่ำสุดที่คาดการณ์**:
- **ราคาสูงสุดที่คาดการณ์**: คำนวณโดยการบวกค่า ATR กับราคาต่ำสุดของวันปัจจุบัน
- **ราคาต่ำสุดที่คาดการณ์**: คำนวณโดยการลบค่า ATR จากราคาสูงสุดของวันปัจจุบัน
3. **การคำนวณสัดส่วน**: สคริปต์คำนวณสัดส่วนของวันที่ช่วงราคาต่อวัน (สูง - ต่ำ) มากกว่าหรือเท่ากับค่า ATR สัดส่วนนี้จะอัปเดตแบบเรียลไทม์เมื่อมีข้อมูลใหม่เข้ามา
4. **การแสดงผลในตาราง**: แทนที่จะแสดงป้ายกำกับบนแท่งเทียนแต่ละแท่ง สคริปต์จะแสดงราคาสูงสุดที่คาดการณ์ ราคาต่ำสุดที่คาดการณ์ และสัดส่วนที่คำนวณในตารางที่มุมขวาบนของกราฟ โดยสามารถปรับขนาดข้อความในตารางได้
5. **การใช้สี**: สคริปต์จะเปลี่ยนสีของแท่งเทียนเป็นสีเหลืองหากช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR ทำให้สามารถระบุแท่งเทียนเหล่านี้ได้ง่ายขึ้น
#### วิธีการใช้งาน
- **ATR Period (`atrPeriod`)**: ปรับช่วงเวลาสำหรับการคำนวณ ATR โดยใช้พารามิเตอร์การป้อนค่า ค่าเริ่มต้นคือ 14
- **Table Size (`tableSizeOption`)**: เลือกขนาดข้อความที่แสดงในตาราง ตัวเลือกได้แก่ `tiny`, `small`, `normal`, `large`, และ `huge`
- **ราคาสูงสุดและต่ำสุดที่คาดการณ์**: ใช้เส้นสีเขียวและสีแดงเพื่อระบุราคาที่เป็นเป้าหมายหรือระดับการหยุดขาดทุนสำหรับการซื้อขายของคุณ เส้นสีเขียวแสดงถึงราคาสูงสุดที่คาดการณ์และเส้นสีแดงแสดงถึงราคาต่ำสุดที่คาดการณ์
- **สัดส่วน**: ตารางที่มุมขวาบนของกราฟแสดงสัดส่วนของวันที่ช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR ซึ่งสามารถให้ข้อมูลเชิงลึกเกี่ยวกับความผันผวนของสินทรัพย์
- **การใช้สี**: แท่งเทียนสีเหลืองบ่งบอกถึงวันที่ช่วงราคาต่อวันมากกว่าหรือเท่ากับค่า ATR
_____
Event on charts**Event on Charts Indicator**
This indicator visually marks significant events on your chart. It is highly customizable, allowing you to activate or deactivate different groups of events and choose whether to display the event text directly on the chart or only when hovered over. Each group of events can be configured with distinct settings such as height mode, color, and label style.
### Key Features:
- **Group Activation:** Enable or disable different groups of events based on your analysis needs.
- **Text Display Options:** Choose to display event texts directly on the chart or only on hover.
- **Customizable Appearance:** Adjust the height mode, offset multiplier, bubble color, text color, and label shape for each group.
- **Predefined Events:** Includes predefined events for major crashes, FED rate changes, SPX tops and bottoms, geopolitical conflicts, economic events, disasters, and significant Bitcoin events.
### Groups Included:
1. **Crash Events:** Marks major market crashes.
2. **FED Rate Events:** Indicates changes in the Federal Reserve rates.
3. **SPX Top Events:** Highlights market tops for the S&P 500.
4. **Geopolitical Conflicts:** Marks significant geopolitical events.
5. **Economic Events:** Highlights important economic events such as bankruptcies and crises.
6. **Disaster and Cyber Events:** Indicates major disasters and cyber attacks.
7. **Bitcoin Events:** Marks significant events in the Bitcoin market.
8. **SPX Bottom Events:** Highlights market bottoms for the S&P 500.
### Usage:
This indicator is useful for traders and analysts who want to keep track of historical events that could impact market behavior. By visualizing these events on the chart, you can better understand market reactions and make informed decisions.
Multi-Chart Widget [LuxAlgo]The Multi-Chart Widget tool is a comprehensive solution crafted for traders and investors looking to analyze multiple financial instruments simultaneously. With the capability to showcase up to three additional charts, users can customize each chart by selecting different financial instruments, and timeframes.
Users can add various widely used technical indicators to the charts such as the relative strength index, Supertrend, moving averages, Bollinger Bands...etc.
🔶 USAGE
The tool offers traders and investors a comprehensive view of multiple charts simultaneously. By displaying up to three additional charts alongside the primary chart, users can analyze assets across different timeframes, compare their performance, and make informed decisions.
Users have the flexibility to choose from various customizable chart types, including the recently added "Volume Candles" option.
This tool allows adding to the chart some of the most widely used technical indicators, such as the Supertrend, Bollinger Bands, and various moving averages.
In addition to the charting capabilities, the tool also features a dynamic statistic panel that provides essential metrics and key insights into the selected assets. Users can track performance indicators such as relative strength, trend, and volatility, enabling them to identify trends, patterns, and trading opportunities efficiently.
🔶 DETAILS
A brief overview of the indicators featured in the statistic panel is given in the sub-section below:
🔹Dual Supertrend
The Dual Supertrend is a modified version of the Supertrend indicator, which is based on the concept of trend following. It generates buy or sell signals by analyzing the asset's price movement. The Dual Supertrend incorporates two Supertrend indicators with different parameters to provide potentially more accurate signals. It helps traders identify trend reversals and establish trend direction in a more responsive manner compared to a single Supertrend.
🔹Relative Strength Index
The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in a market. Traditionally, RSI values above 70 are considered overbought, suggesting that the asset may be due for a reversal or correction, while RSI values below 30 are considered oversold, indicating potential buying opportunities.
🔹Volatility
Volatility in trading refers to the degree of variation or fluctuation in the price of a financial instrument, such as a stock, currency pair, or commodity, over a certain period of time. It is a measure of the speed and magnitude of price changes and reflects the level of uncertainty or risk in the market. High volatility implies that prices are experiencing rapid and significant movements, while low volatility suggests that prices are relatively stable and are not changing much. Traders often use volatility as an indicator to assess the potential risk and return of an investment and to make informed decisions about when to enter or exit trades.
🔹R-Squared (R²)
R-squared, also known as the coefficient of determination, is a statistical measure that indicates the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In other words, it quantifies the goodness of fit of a regression model to the observed data. R-squared values range from %0 to %100, with higher values indicating a better fit of the model to the data. An R-squared of 100% means that all movements of a security are completely explained by movements in the index, while an R-squared value of %0 indicates that the model does not explain any of the variability in the dependent variable.
In simpler terms, in investing, a high R-squared, from 85% to 100%, indicates that the stock’s or fund’s performance moves relatively in line with the index. Conversely, a low R-squared (around 70% or less) indicates that the fund's performance tends to deviate significantly from the movements of the index.
🔶 SETTINGS
🔹Mini Chart(s) Generic Settings
Mini Charts Separator: This option toggles the visibility of the separator lines.
Number Of Bars: Specifies the number of bars to be displayed for each mini chart.
Horizontal Offset: Determines the distance at which the mini charts will be displayed from the primary chart.
🔹Mini Chart Settings: Top - Middle - Bottom
Mini Chart Top/Middle/Bottom: Toggle the visibility of the selected mini chart.
Symbol: Choose the financial instrument to be displayed in the mini chart. If left as an empty string, it will default to the current chart instrument.
Timeframe: This option determines the timeframe used for calculating the mini charts. If a timeframe lower than the chart's timeframe is selected, the calculations will be based on the chart's timeframe.
Chart Type: Selection from various chart types for the mini charts, including candles, volume candles, line, area, columns, high-low, and Heikin Ashi.
Chart Size: Determines the size of the mini chart.
Technical Indicator: Selection from various technical indicators to be displayed on top of the mini charts.
Note : Chart sizing is relative to other mini charts. For example, If all the mini charts are sized to x5 relative to each other, the result will be the same as if they were all sized as x1. This is because the relative proportions between the mini charts remain consistent regardless of their absolute sizes. Therefore, their positions and sizes relative to each other remain unchanged, resulting in the same visual representation despite the differences in absolute scale.
🔹Supertrend Settings
ATR Length: is the lookback length for the ATR calculation.
Factor: is what the ATR is multiplied by to offset the bands from price.
Color: color customization option.
🔹Moving Average Settings
Type: is the type of the moving average, available types of moving averages include SMA (Simple Moving Average), EMA (Exponential Moving Average), RMA (Root Mean Square Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average.
Color: Color customization option.
🔹Bollinger Bands Settings
Basis Type: Determines the type of Moving Average that is applied to the basis plot line.
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average which creates the base for the Upper and Lower Bands.
StdDev: The number of Standard Deviations away from the Moving Average that the Upper and Lower Bands should be.
Color: Color customization options for basis, upper and lower bands.
🔹Mini Chart(s) Panel Settings
Mini Chart(s) Panel: Controls the visibility of the panel containing the mini charts.
Dual Supertrend: Toggles the display of the evaluated dual super trend, based on the super trend settings provided below the option. The definitions for the options are the same as stated above for the super trend.
Relative Strength Index: Toggles the display of the evaluated RSI, based on the source and length settings provided below the option.
Volatility: Toggles the display of the calculated Volatility, based on the length settings provided below the option.
R-Squared: Toggles the display of the calculated R-Squared (R²), based on the length settings provided below the option.
🔶 LIMITATIONS
The tool allows users to display mini charts featuring various types of instruments alongside the primary chart instrument. However, there's a limitation: the selected primary chart instrument must have an ACTIVE market status. Alternatively, if the primary chart instrument is not active, the mini chart instruments must belong to the same exchange and have the same type as the primary chart instrument.
CPR by MTThe CPR indicator, or Central Pivot Range indicator, is a technical analysis tool used in trading to identify potential support and resistance levels based on the price action of a security. Developed by pivot point theory, it is particularly popular among day traders and swing traders. The CPR indicator consists of three lines:
1. **Pivot Point (PP):** This is the central line and is calculated as the average of the high, low, and closing prices from the previous trading period.
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2. **Top Central Pivot (TC):** This is calculated by subtracting the low from the PP and then adding the result to the PP.
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3. **Bottom Central Pivot (BC):** This is calculated by subtracting the high from the PP and then adding the result to the PP.
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### How to Use the CPR Indicator
- **Trend Identification:** A wide CPR range indicates low volatility and a potential sideways or consolidation phase. A narrow CPR range indicates high volatility and a potential strong trending move.
- **Support and Resistance:** The top and bottom central pivots act as immediate resistance and support levels. If the price is above the TC, it indicates a bullish sentiment, while if it is below the BC, it indicates a bearish sentiment.
- **Entry and Exit Points:** Traders use the CPR lines to determine optimal entry and exit points. For example, if the price breaks above the TC and sustains, it may signal a buy opportunity, whereas a drop below the BC may signal a sell opportunity.
### Practical Example
Suppose a stock had a high of $105, a low of $95, and a closing price of $100 on the previous day. The CPR levels for the next day would be calculated as follows:
1. **Pivot Point (PP):**
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2. **Top Central Pivot (TC):**
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3. **Bottom Central Pivot (BC):**
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The levels for the next day would be PP = $100, TC = $110, and BC = $90. Traders would then use these levels to assess potential trading strategies based on where the price moves relative to these levels.
### Conclusion
The CPR indicator is a useful tool for traders looking to understand market conditions and make informed decisions about entry and exit points. Its effectiveness comes from its ability to highlight key price levels derived from historical price data, helping traders predict potential market movements.
colorLabLibrary "colorLab"
The ColorLab library presents an essential solution for color optimization, leveraging color terms and philosophy. Through its capabilities, it furnishes the necessary versatility to attain optimal color representation and coherence by integrating functions.
tint_level(colour, level)
Determines a Tinted color
Parameters:
colour (color) : (series color) Pure color.
level (float) : (series float) Optional argument, default = 50. A level of tent color. 0 is entered color and 100 is white color.
Returns: (series color) A color Computed from a linear "Tint" gradient.
shade_level(colour, level)
Determines a Shaded color.
Parameters:
colour (color) : (series color) Pure color.
level (float) : (series float) Optional argument, default = 50. A level of tent color. 0 is entered color and 100 is Black color.
Returns: (series color) A color Computed from a linear "Shade" gradient.
tone_level(colour, level)
Determines a Tone color.
Parameters:
colour (color) : (series color) Pure color.
level (float) : (series float) Optional argument, default = 50. A level of tent color. 0 is entered color and 100 is Gray color.
Returns: (series color) A color Computed from a linear "Tone" gradient.
lightness_gradient(colour, value, bottom_value, top_value, bottom_lightness, top_lightness)
Determines a color from a "Lightness" gradient, based on the position of an entered value within a defined range.
Parameters:
colour (color) : (series color) Pure color.
value (float) : (series float) Value.
bottom_value (float) : (series float) Bottom Value.
top_value (float) : (series float) Top Value.
bottom_lightness (simple float) : (simple float) Optional argument, default = 70. Lightness Percentage. 100% is lightest and 0% is darkest
top_lightness (simple float) : (simple float) Optional argument, default = 30. Lightness Percentage. 100% is lightest and 0% is darkest
Returns: (series color) A color Computed a the linear "Lightness" gradient.
saturation_gradient(colour, value, bottom_value, top_value, bottom_saturated, top_saturated)
Determines a color from a "Saturation" gradient, based on the position of an entered value within a defined range.
Parameters:
colour (color) : (series color) Pure color.
value (float) : (series float) Value.
bottom_value (float) : (series float) Bottom Value.
top_value (float) : (series float) Top Value.
bottom_saturated (simple float) : (simple float) Optional argument, default = 15. Low Saturated Percentage.
top_saturated (simple float) : (simple float) Optional argument, default = 80. High Saturated Percentage.
Returns: (series color) A color Computed from a linear "Saturation" gradient.
hue_gradient(colour, value, bottom_value, top_value, bottom_hue, top_hue)
Determines a color from a "Hue" gradient, based on the position of an entered value within a defined range.
Parameters:
colour (color) : (series color) Pure color.
value (float) : (series float) Value.
bottom_value (float) : (series float) Bottom Value.
top_value (float) : (series float) Top Value.
bottom_hue (simple float) : (simple float) Optional argument, Default = 0. Low Hue is a degree where value in range 0 to 360 degrees.
top_hue (simple float) : (simple float) Optional argument, default = 300. High Hue is a degree where value in range 0 to 360 degrees.
Returns: (series color) A color Computed from a linear "Saturation" gradient.
opposColor(colour)
Generates the opposite color of inputted color.
Parameters:
colour (color) : (series color) Pure color.
Returns: (series color) An opposite color.
randColor(seed)
Generates a random color.
Parameters:
seed (simple int) : (simple int) Optional argument. With identifying seed, it will generate similar color sequence.
Returns: (series color) A random color.
bk_or_wh(colour, lightness)
Determines a white or back fits with an inputted color.
Parameters:
colour (color) : (series color) Pure color.
lightness (float) : (series float) Optional argument, default = 50. If the lightness percentage of inputted color is higher, the output is white; otherwise, it's black.
Returns: (series color) white or back color.
monochrome(colour, lightness, saturation)
Generates a monochromatic color scheme.
Parameters:
colour (color) : (series color) Pure color.
lightness (float) : (series float) Optional argument, default = NA. To custom Lightness percentage manually, 100% is lightest and 0% is darkest.
saturation (float) : (series float) Optional argument, default = NA. To custom Saturation percentage manually, 100% is highest and 0% is lowest saturated.
Returns: (tuple of two color series) .
complementary(colour)
Generates a complementary color scheme.
Parameters:
colour (color) : (series color) Pure color.
Returns: (tuple of two color series) .
analogous(colour)
Generates an analogous color scheme.
Parameters:
colour (color) : (series color) Pure color.
Returns: (tuple of three color series) .
triadic(colour)
Generates an Triadic color scheme.
Parameters:
colour (color) : (series color) Pure color.
Returns: (tuple of three color series) .
tetradic(colour)
Generates an Tetradic color scheme.
Parameters:
colour (color) : (series color) Main color.
Returns: (tuple of four color series) .
tst_scheme(colour, size, _type)
Generates an array of requested type (tint, shade, or tone) scheme colors.
Parameters:
colour (simple color) : (simple color) Pure color.
size (simple int) : (simple input) Number of elements in color array.
_type (simple string) : (simple string) Type of color scheme, possible input "tint", "shade", and "tone".
Returns: (simple array) An array contains elements of the requested type scheme colors.
lsh_scheme(colour, size, _type, topLevel, botLevel)
Generates an array of requested type (lightness, saturation or hue) scheme colors.
Parameters:
colour (simple color) : (simple color) Pure color.
size (simple int) : (simple input) Number of elements in color array.
_type (simple string) : (simple string) Type of color scheme, possible input "lightness", "saturation" and "hue".
topLevel (simple float) : (simple float) Optional argument, default = NA.
1. if "lightness", in a percentage where value in range 0 to 100, 100% lightest.
2. if "saturation", in a percentage where value in range 0 to 100, 100% highest saturated.
3. if "hue", in a degree where value in range 0 to 360 degrees.
botLevel (simple float) : (simple float) Optional argument, default = NA.
1. if "lightness", in a percentage where value in range 0 to 100, 0% darkest.
2. if "saturation", in a percentage where value in range 0 to 100, 0% lowest saturated.
3. if "hue", in a degree where value in range 0 to 360 degrees.
Returns: (simple array) An array contains elements of the requested type scheme colors.
display_color(colour, location)
Displays color including RGB and HSL.
Parameters:
colour (simple color) : (simple color) Pure color.
location (simple string) : (simple string) Optional argument, default = "top_right". cell location.
Returns: (simple table) A table cell contains RGB and HSL of entered color.
display_scheme(arrayColour, location)
Displays Scheme colors including RGB and HSL.
Parameters:
arrayColour (array)
location (simple string) : (simple string) Optional argument, default = "top_right". cell location.
Returns: (simple table) A table cells contain RGB and HSL of entered color.
[EmreKb] Volume AnalysisI've noticed that many Pine coders calculate buy and sell volumes by considering the volume of a bullish candle as buy volume and the volume of a bearish candle as sell volume. However, I believe this approach isn't very logical, especially for candles with long wicks like pinbars.
Therefore, I've devised a method to calculate the buy and sell volumes of a candle by separately considering the sizes of its top and bottom wicks and its body. I distribute the volume of the candle equally among its top wick, body, and bottom wick sizes. If the candle is bearish, I consider the body volume as sell volume; if bullish, as buy volume. For the top and bottom wick volumes, since there's a two-way movement, I allocate half to buy volume and the other half to sell volume.
This indicator displays the sum of buy and sell volumes retrospectively up to the "lookback" value on the candle. You can set the lookback value to 1 to only visualize the buy and sell volume distribution of a single candle.
If this method has been used by another Pine coder, please inform me!
Volume Delta Candles [LuxAlgo]Volume Delta Candles provides insights about Intrabar trading activity in an easy-to-interpret manner. Lower timeframe or real-time data is used for displaying Volume Delta percentage against the total volume as a coloured bar part.
The script also highlights the intrabar price with the maximum trading activity, as well as complementary information.
🔶 USAGE
The tool focuses on intrabar volume to provide more information about the trading activity associated with a candle, without having to use an external volume indicator.
Each indicator components is further explained below:
🔹 Volume Delta
The volume delta is obtained by the difference between buy volume and sell volume, where buy volume is the volume associated with a bullish intrabar candle, and sell volume with a bearish intrabar candle.
Positive volume delta is displayed with a green candle area, while negative delta is displayed with a red candle area.
🔹 Bar Coloring
The script displays VD as a percentage of the whole, or from the candle half, depending on the setting ' Display '.
Bars can be coloured as follows:
Full (100%) when Display is set at ' Full Bar '
Half (50% or 100% of half a bar) when Display is set at ' Half Bar '
A negative VD (more bearish than bullish volume) will fill the bar from the top (or centre) of the bar towards the bottom, and a positive VD will fill a bar from the bottom (or centre) of the bar towards the top.
A negative VD on a green candle will show a red-coloured VD against a green-bordered candle. On the other hand, a positive VD on a red candle will show a green-coloured VD against a red-bordered candle.
Colours for VD sentiment opposite to the candle sentiment can be set differently if desired.
🔹 Highest Volume Price Level
The script displays a white (black on light mode) line highlighting the intrabar price level with the highest volume.
When ' Show Previous Max Volume Price ' is checked, a white (black on light mode) dot is displayed 1 bar to the right.
🔶 DETAILS
🔹 Tick/LTF data
The above example used Lower TimeFrame (LTF) data.
The following example uses real-time tick data ( Settings -> Data From )
Both options, LTF or tick data, will show a vertical dotted line where the data starts.
🔹 LTF settings
When ' Data from ' LTF is chosen and ' Auto ' enabled, the LTF will be the nearest possible x times smaller TF than the current TF. When 'Premium' is disabled, the minimum TF will always be 1 minute to ensure TradingView plans lower than Premium don't get an error.
Examples with current Daily TF (when Premium is enabled):
500 : 3 minute LTF
1500 (default): 1 minute LTF
5000: 30 seconds LTF (1 minute if Premium is disabled)
🔹 Notes
Different LTFs give different data, which means different results; this doesn't mean it isn't correct; they are just different data sets.
(LTF is displayed at the top right corner)
To ensure maximum visibility of values, we recommend using Bars from the Bar's style menu.
🔶 SETTINGS
Data from: Lower TimeFrame or real-time Tick data
Resolution: LTF setting
Auto + multiple: Adjusts the initial set resolution
Premium: Enable when your TradingView plan is Premium or higher
🔹 Intrabar Data
Colours
Display: Full/Half bar
Show previous max volume price: White/black dot, showing previous highest volume price level
🔹 Table
Show TF: Show LTF at the top right corner
Colour + table text size
🔹 Details
Show details: label with 'Volume', 'Delta' (VD) and '%'
See USAGE for more information
Periodic Activity Tracker [LuxAlgo]The Periodic Activity Tracker tool periodically tracks the cumulative buy and sell volume in a user-defined period and draws the corresponding matching bars and volume delta for each period.
Users can select a predefined aggregation period from the following options: Hourly, Daily, Weekly, and Monthly.
🔶 USAGE
This tool provides a simple and clear way of analyzing volumes for each aggregated period and is made up of the following elements:
Buy and sell volumes by period as red and green lines with color gradient area
Delta (difference) between buy & sell volume for each period
Buy & sell volume bars for each period
Separator between lines and bars, and period tags below each pair of bars for ease of reading
On the chart above we can see all the elements displayed, the volume level on the lines perfectly matches the volume level on the bars for each period.
In this case, the tool has the default settings so the anchor period is set to Daily and we can see how the period tag (each day of the week) is displayed below each pair of bars.
Users can disable the delta display and adjust the bar size.
🔹 Reading The Tool
In trading, assessing the strength of the bulls (buyers) and bears (sellers) is key to understanding the current trading environment. Which side, if any, has the upper hand? To answer this question, some traders look at volume in relation to price.
This tool provides you with a view of buy volume versus sell volume, allowing you to compare both sides of the market.
As with any volume tool, the key is to understand when the forces of the two groups are balanced or unbalanced.
As we can observe on the chart:
NOV '23: Buy volume greater than sell volume, both moving up close together, flat delta. We can see that the price is in range.
DEC '23: Buy volume bigger than Sell volume, both moving up but with a bigger difference, bigger delta than last month but still flat. We can see the price in the range above last month's range.
JAN '24: Buy and sell volume tied together, no delta whatsoever. We can see the price in range but testing above and below last month's range.
FEB '24: Buy volume explodes higher and sell volume cannot keep up, big growing delta. Price explodes higher above last month's range.
Traders need to understand that there is always an equal number of buyers and sellers in a liquid market, the quality here is how aggressive or passive they are. Who is 'attacking' and who is 'defending', who is using market orders to move prices, and who is using limit orders waiting to be filled?
This tool gives you the following information:
Lines: if the top line is green, the buyers are attacking, if it is red, the sellers are attacking.
Delta: represents the difference in their strength, if it is above 0 the buyers are stronger, if it is below 0 the sellers are stronger.
Bars: help you to see the difference in strength between buyers and sellers for each period at a glance.
🔹 Anchor Period
By default, the tool is set to Hourly. However, users can select from a number of predefined time periods.
Depending on the user's selection, the bars are displayed as follows:
Hourly : hours of the current day
Daily : days of the current week
Weekly : weeks of the current month
Monthly : months of the current year
On the chart above we can see the four periods displayed, starting at the top left and moving clockwise we have hourly, daily, weekly, and monthly.
🔶 DETAILS
🔹 Chart TimeFrame
The chart timeframe has a direct impact on the visualization of the tool, and the user should select a chart timeframe that is compatible with the Anchor period in the tool's settings panel.
For the chart timeframe to be compatible it must be less than the Anchor period parameter. If the user selects an incompatible chart timeframe, a warning message will be displayed.
As a rule of thumb, the smaller the chart timeframe, the more data the tool will collect, returning indications for longer-term price variations.
These are the recommended chart timeframes for each period:
Hourly : 5m charts or lower
Daily : 1H charts or lower
Weekly : 4H charts or lower
Monthly : 1D charts or lower
🔹 Warnings
This chart shows both types of warnings the user may receive
At the top, we can see the warning that is given when the 'Bar Width' parameter exceeds the allowed value.
At the bottom is the incompatible chart timeframe warning, which prompts the user to select a smaller chart timeframe or a larger "Anchor Period" parameter.
🔶 SETTINGS
🔹 Data Gathering
Anchor period: Time period representing each bar: hours of the day, days of the week, weeks of the month, and months of the year. The timeframe of the chart must be less than this parameter, otherwise a warning will be displayed.
🔹 Style
Bars width: Size of each bar, there is a maximum limit so a warning will be displayed if it is reached.
Volume color
Delta: Enable/Disable Delta Area Display
Nightrangers IndicatorDescription
This indicator combines three EMA's, Ichimoku Cloud, RSI and MACD. By combining and modifying their use case this turns into an extremely powerful and accessible indicator for finding long and short position entries, below is a description of how to use this indicator, and what makes it different.
Primary Use case
The three EMA's would be the initial indicators you would be looking at, they are based on the 7d, 25d and 200d MA - Used on their own, they would be worthless, and this is where the Ichimoku Cloud comes into it, I have removed all other aspects of the Ichimoku Cloud and only kept the baseline, combine this with the three MA's and we have a very powerful indicator for finding Long entries, that is used uniquely in a way to which the Ichimoku Cloud is not originally meant to be used for.
An early indication of a LONG entry would be when the 7d MA crosses above the Ichimoku Baseline, through this early indicator, you are able to watch and monitor the chart, you would be waiting to see if the 25d MA then also crosses above the Ichimoku Baseline, This would be the second important indication of a long entry. The 200d MA helps here when making decisions on where to set your own personal take profits - If the Ichimoku baseline, and the MA's are below the 200d MA, you would be expecting a bounce point here, or heavy resistance so the long entry could be over a shorter period, than that if it was above the 200d MA, which is why it is included here, to help make a better informed choice.
The latter is reversed for finding short positions, and entries. This indicator is completely reliant on each other to find the best possible entry/exit by complementing each other, and by using the Ichimoku Baseline on it's own, and not as the Ichimoku Cloud is intended.
Just using these though, is not enough, which is why the RSI and MACD are also combined, once the conditions are met above, You may find that there can be false positives for entries, and this is where the RSI has multiple use cases within this script.
Firstly the backdrop colour will change based on whether the chart is in an uptrend or downtrend, This is a visual indicator provided to work simultaneaously on the chart itself to help identification of entries/exits easier to identify in conjunction with the above.
Secondly, It is used to display in the top right, The current Trend in a text format, as well as if the current chart is in one of three phases, these are Overbrought, Oversold and accumulation.
And finally it will display the current RSI Value on the last candle in a clear to see blue Label, This helps with the visual accessible side, to help you make a more informed choice depending on your own personal tolerance.
This ties into the above Indicators, by combining the information, you would not be looking to take a long, if for example, the RSI showed it was over-brought, and in a downtrend, even if the MA's had crossed above the Baseline, as this would most likely be a fakeout.
However if the Indicators above, showed a potential long, and the backdrop had flipped green, indicating an uptrend, and it was in an accumulation phase, you would consider this position. and this is where the MACD comes into play.
You would use the MACD to see whether or not the Signal line has crossed over the MACD line, and vice versa - However this script uses it to simplify and portray current market sentiment, and visually display by reducing clutter on screen, and making it more accessible.
It is designed to portray an easy to read and understand visual indicator by displaying in the top right simply as Bullish or Bearish, with markers above the candles ( "M" and "MX" ).
The M indicator is to show where the MACD Crosses above the Signal, and if aligned with all the other indicators within the script, shows a very strong confirmation for a buying opportunity, and vice versa for the "MX" indicator if aligned with the other indicators in reverse, provides a very strong confirmation for opening a short position or for selling.
Secondary Use case
By combining the indicators above, the secondary conditions you would be looking for, If you opened a LONG position, would be knowing when to sell, On top of what has been described above already regarding this, you would be looking to start taking profits, when the 7d MA crosses above or across the candles, and looking to close the position, when the 25d MA also crosses above the candles, and respectively, in reverse for closing short positions. This is shown across the charts to be extremely useful, however, combine this with the other indicators, portrayed in an easy to use and understand visual representation, you are now able to make more informed decisions, on whether to close a position or not.
How is it different and not just a mash up
I have combined these indicators to make the world of trading more accessible for everyone regardless of circumstances, by creating an easy to understand visual representation, keeping colours vibrant and easy to stand out, with clear and simple to read text indications. So whether you are a seasoned trader, or just starting out, you can make more informed choices, without the need of learning how to use multiple different indicators, and learning how to combine them all, or if you have difficulties learning, this indicator also simplifies a lot of the more technical intricacies, by still allowing you to make a more informed choice.
Multiple OTTMultiple OTT (MOTT) is a development on the Optimized Trend Tracker (OTT) indicator of Anıl Özekşi that is shared in his algorithmic trading courses by himself.
There are 5 lines in MOTT:
-The top (cyan) line is originally an OTT line, which uses the Highest price values in a default length of 80 bars in its calculation.
-The bottom line (purple) is also an OTT line but conversely uses the Lowest prices in the same period.
-The dotted third line in the middle (green) is the exact average of the top and bottom lines.
-The dotted Cyan line: (Top+Middle)/2 and
dotted Purple line: (Bottom+Middle)/2 are also the averages of their two neighbors.
Default values:
Length of the Highest and Lowest Price period (High & Low Period): 80
OTT optimizing percent: 1.4
OTT Length: 2 (Also Moving Average Length when displayed)
Default Moving Average Type of OTT Calculation: VIDYA(VAR) VARIABLE INDEX DYNAMIC MOVING AVERAGE
These values are designed for daily time frame, so they have to be optimized in other timeframes by the user. (Ex: Higher values can be considered in lower time frames)
BUY when the price crosses above the MOTT lines.
STOP when the price crosses back below the same MOTT line.
SELL when the price crosses below the MOTT lines.
STOP when the price crosses back above the same MOTT line.
As you can see, every line can be considered a trade signal like Fibonacci Levels. If optimized meaningfully, lines can also show users significant support and resistance levels. Traders can use those levels in partial buys and sells.
Developer Anıl Özekşi advises that traders may have more accurate signals when using a short-period moving average instead of closing prices. So, I added the VIDYA moving average with the same default length ( 2 ) used in OTT calculation. You can check the "SHOW MOVING AVERAGE?" box on the settings tab of the indicator.
Quan Channel - Quan DaoI tried several channels, like the supertrend, ATR, Donchian or Bollingers, but they do not seem to fit my needs.
So I created a new channel to PREDICT the next impulse move of a price.
The current value of the top or bottom of the channel is based on 2 previous candles (not the candle itself), and it takes into account:
- The Direction of the previous candles (red or green) and
- The Width of their bodies
In my channel, the top or bottom lines will cover the price movement most of the time. But in some cases, when the price is on a big move, it will go out of the channel. And this is the time we need to consider a buy/sell (or take some profit) as well (not necessarily 100% of the time, though).
Personally, I like to use another oscillator in combination with this channel to predict whether it will reverse after the breakouts or continue to make another peak. If you are a DCA or long-term investor, I guess it would be safe to buy at the blue signals (out of bottom) and take some profits at the orange signals (out of top).
I also added an alert when the price breaks out of the channel for easier tracking.
