Yesterday's High v.17.07Yesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of INJ, a 12% Take-Profit and a 1.5% Stop-Loss were set, with an activated trailing-stop percentage, TRL 1 and OFF 0.5.
To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name: Yesterday's High Breakout - Trend Follower Strategy
Author: @tumiza999
Category: Trend Follower, Breakout of Yesterday's High.
Operating mode: Spot or Futures (only long).
Trade duration: Intraday.
Timeframe: 30M, 1H, 2H, 4H
Market: Crypto
Suggested usage: Short-term trading, when the market is in trend and it is showing high volatility.
Entry: When there is a breakout of Yesterday's High.
Exit: Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration:
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting:
⁃ Exchange: BINANCE
⁃ Pair: INJUSDT
⁃ Timeframe: 4H
- Treshold: 1
- Gap%: 1
- SL: 1.5
- TP:12
- TRL: 1
- OFF-TRL: 0.5
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits: LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer: Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
在腳本中搜尋"N+credit最新动态"
Price Legs: Average Heights; 'Smart ATR'Price Legs: Average Heights; 'Smart ATR'. Consol Range Gauge
~~ Indicator to show small and large price legs (based on short and long input pivot lengths), and calculating the average heights of these price legs; counting legs from user-input start time ~~
//Premise: Wanted to use this as something like a 'Smart ATR': where the average/typical range of a distinct & dynamic price leg could be calculated based on a user-input time interval (as opposed to standard ATR, which is simply the average range over a consistent repeating period, with no regard to market structure). My instinct is that this would be most useful for consolidated periods & range trading: giving the trader an idea of what the typical size of a price leg might be in the current market state (hence in the title, Consol Range gauge)
//Features & User inputs:
-Start time: confirm input when loading indicator by clicking on the chart. Then drag the vertical line to change start time easily.
-Large Legs (toggle on/off) and user-input pivot lookback/lookforward length (larger => larger legs)
-Small Legs (toggle on/off) and user-input pivot lookback/lookforward length (smaller => smaller legs)
-Display Stats table: toggle on/off: simple view- shows the averages of large (up & down), small (up & down), and combined (for each).
-Extended stats table: toggle on/off option to show the averages of the last 3 legs of each category (up/down/large/small/combined)
-Toggle on/off Time & Price chart text labels of price legs (time in mins/hours/days; price in $ or pips; auto assigned based on asset)
-Table position: user choice.
//Notes & tips:
-Using custom start time along with replay mode, you can select any arbitrary chunk of price for the purpose of backtesting.
-Play around with the pivot lookback lengths to find price legs most suitable to the current market regime (consolidating/trending; high volatility/ low volatility)
-Single bar price legs will never be counted: they must be at least 2 bars from H>>L or L>>H.
//Credits: Thanks to @crypto_juju for the idea of applying statistics to this simple price leg indicator.
Simple View: showing only the full averages (counting from Start time):
View showing ONLY the large legs, with Time & Price labels toggled ON:
VolatilityIndicatorsLibrary "VolatilityIndicators"
This is a library of Volatility Indicators .
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the parameters and sources, not being restricted to just the closing price.
@Thanks and credits:
1. Dynamic Zones: Leo Zamansky, Ph.D., and David Stendahl
2. Deviation: Karl Pearson (code by TradingView)
3. Variance: Ronald Fisher (code by TradingView)
4. Z-score: Veronique Valcu (code by HPotter)
5. Standard deviation: Ronald Fisher (code by TradingView)
6. ATR (Average True Range): J. Welles Wilder (code by TradingView)
7. ATRP (Average True Range Percent): millerrh
8. Historical Volatility: HPotter
9. Min-Max Scale Normalization: gorx1
10. Mean Normalization: gorx1
11. Standardization: gorx1
12. Scaling to unit length: gorx1
13. LS Volatility Index: Alexandre Wolwacz (Stormer), Fabrício Lorenz, Fábio Figueiredo (Vlad) (code by me)
14. Bollinger Bands: John Bollinger (code by TradingView)
15. Bollinger Bands %: John Bollinger (code by TradingView)
16. Bollinger Bands Width: John Bollinger (code by TradingView)
dev(source, length, anotherSource)
Deviation. Measure the difference between a source in relation to another source
Parameters:
source (float)
length (simple int) : (int) Sequential period to calculate the deviation
anotherSource (float) : (float) Source to compare
Returns: (float) Bollinger Bands Width
variance(src, mean, length, biased, degreesOfFreedom)
Variance. A statistical measurement of the spread between numbers in a data set. More specifically,
variance measures how far each number in the set is from the mean (average), and thus from every other number in the set.
Variance is often depicted by this symbol: σ2. It is used by both analysts and traders to determine volatility and market security.
Parameters:
src (float) : (float) Source to calculate variance
mean (float) : (float) Mean (Moving average)
length (simple int) : (int) The sequential period to calcule the variance (number of values in data set)
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length. Only applies when biased parameter is defined as true.
Returns: (float) Standard deviation
stDev(src, length, mean, biased, degreesOfFreedom)
Measure the Standard deviation from a source in relation to it's moving average.
In this implementation, you pass the average as a parameter, allowing a more personalized calculation.
Parameters:
src (float) : (float) Source to calculate standard deviation
length (simple int) : (int) The sequential period to calcule the standard deviation
mean (float) : (float) Moving average.
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Standard deviation
zscore(src, mean, length, biased, degreesOfFreedom)
Z-Score. A z-score is a statistical measurement that indicates how many standard deviations a data point is from
the mean of a data set. It is also known as a standard score. The formula for calculating a z-score is (x - μ) / σ,
where x is the individual data point, μ is the mean of the data set, and σ is the standard deviation of the data set.
Z-scores are useful in identifying outliers or extreme values in a data set. A positive z-score indicates that the
data point is above the mean, while a negative z-score indicates that the data point is below the mean. A z-score of
0 indicates that the data point is equal to the mean.
Z-scores are often used in hypothesis testing and determining confidence intervals. They can also be used to compare
data sets with different units or scales, as the z-score standardizes the data. Overall, z-scores provide a way to
measure the relative position of a data point in a data
Parameters:
src (float) : (float) Source to calculate z-score
mean (float) : (float) Moving average.
length (simple int) : (int) The sequential period to calcule the standard deviation
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Z-score
atr(source, length)
ATR: Average True Range. Customized version with source parameter.
Parameters:
source (float) : (float) Source
length (simple int) : (int) Length (number of bars back)
Returns: (float) ATR
atrp(length, sourceP)
ATRP (Average True Range Percent)
Parameters:
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
atrp(source, length, sourceP)
ATRP (Average True Range Percent). Customized version with source parameter.
Parameters:
source (float) : (float) Source for ATR
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
historicalVolatility(lengthATR, lengthHist)
Historical Volatility
Parameters:
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
historicalVolatility(source, lengthATR, lengthHist)
Historical Volatility
Parameters:
source (float) : (float) Source for ATR
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
minMaxNormalization(src, numbars)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
minMaxNormalization(src, numbars, minimumLimit, maximumLimit)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
In this implementation, the user explicitly provides the desired minimum (min) and maximum (max) values for the scale,
rather than using the minimum and maximum values from the data.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
minimumLimit (simple float) : (float) Minimum value to scale
maximumLimit (simple float) : (float) Maximum value to scale
Returns: (float) Normalized value
meanNormalization(src, numbars, mean)
Mean Normalization
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
mean (float) : (float) Mean of source
Returns: (float) Normalized value
standardization(src, mean, stDev)
Standardization (Z-score Normalization). How "outside the mean" values relate to the standard deviation (ratio between first and second)
Parameters:
src (float) : (float) Source to normalize
mean (float) : (float) Mean of source
stDev (float) : (float) Standard Deviation
Returns: (float) Normalized value
scalingToUnitLength(src, numbars)
Scaling to unit length
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
lsVolatilityIndex(movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int) : (float) Length for normalization
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
lsVolatilityIndex(sourcePrice, movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
sourcePrice (float) : (float) Source for measure the distance
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int)
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
bollingerBands(src, length, mult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) A tuple of Bollinger Bands, where index 1=basis; 2=basis+dev; 3=basis-dev; and dev=multiplier*stdev
bollingerBands(src, length, aMult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Also, various multipliers can be passed, thus getting more bands (instead of just 2).
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) An array of multiplies used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands, where:
index 1=basis; 2=basis+dev1; 3=basis-dev1; 4=basis+dev2, 5=basis-dev2, 6=basis+dev2, 7=basis-dev2, Nup=basis+devN, Nlow=basis-devN
and dev1, dev2, devN are ```multiplier N * stdev```
bollingerBandsB(src, length, mult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation:
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands %B
bollingerBandsB(src, length, aMult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands %B. The number of results in this array is equal the numbers of multipliers passed via parameter.
bollingerBandsW(src, length, mult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation:
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands Width
bollingerBandsW(src, length, aMult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands Width. The number of results in this array is equal the numbers of multipliers passed via parameter.
dinamicZone(source, sampleLength, pcntAbove, pcntBelow)
Get Dynamic Zones
Parameters:
source (float) : (float) Source
sampleLength (simple int) : (int) Sample Length
pcntAbove (simple float) : (float) Calculates the top of the dynamic zone, considering that the maximum values are above x% of the sample
pcntBelow (simple float) : (float) Calculates the bottom of the dynamic zone, considering that the minimum values are below x% of the sample
Returns: A tuple with 3 series of values: (1) Upper Line of Dynamic Zone;
(2) Lower Line of Dynamic Zone; (3) Center of Dynamic Zone (x = 50%)
Examples:
Momentum PlayTraders always need a confirmation of momentum in price action to ride the swings.
Momentum Play Indicator consists of the below:
Bullish Conditions :
1)EMA 8 above EMA 34 and rising
2)Candle close above 5 candle high
3) RSI above 60
4) Volume above 5 candles avg. volume
5) ADX above 20
Bearish Conditions :
1)EMA 8 below EMA 34 and falling
2)Candle close below 5 candle low
3) RSI below 40
4) Volume above 5 candles avg. volume
5) ADX above 20
Traders can change the inputs as per their liking to adjust as per their comfortable timeframe.
Credits: Special Thanks to Mr. DTBHAT for sharing the above conditions.
Financial Data Spreadsheet [By MUQWISHI]The Financial Data Spreadsheet indicator displays tables in the form of a spreadsheet containing a set of selected financial performances of a company within the most recent reported period. Analyzing Financial data is one of the classic methods to evaluate whether the company’s stock price is overvalued or undervalued based on its income statement, balance sheet, and cash flow statement. This indicator might be practical to investors to collect needed data of a company to analyze and compare it with other companies on a TradingView chart or print it in spreadsheet form.
█ OVERVIEW
█ BEST PRACTICES
Due to strict limitations on calling request.financial() function, I tried to develop the table with the best ways to be more dynamic to move and the ability to join multiple tables into a spreadsheet. Users can add up to 20 instruments and 2 financial metrics per table. However, it’s possible to add many tables with other financial metrics, then connect them to the main table.
Credits: The idea of joining multiple tables inspired by @QuantNomad Screener for 40+ instruments
█ INDICATOR SETTINGS
1- Moving Table toward right-left up-down from its origin.
2- Hiding Column Title checkmark. Useful for adding a joined table underneath with additional instruments.
3- Hiding Instruments Title checkmark. Useful for adding a joined table on the right with other financial metrics.
4- Shade Alternate Rows checkmark. I believe it’ll make the table easier to read.
5- Selecting Financial Period. (Year, Quarter).
6- Entering a currency.
7- Choosing a financial ID for each column. There’re over 200 financial IDs. Source: What financial data is available in Pine? — TradingView
8- Optional to highlight values in between.
9- Entering the ticker’s symbol with the ability to activate/deactivate.
█ TIP
For best technical performance, use the indicator in a 1D timeframe.
Please let me know if you have any questions.
Thank you.
[Pt] TICK + Heikin Ashi RSI IndicatorThis indicator combines NYSE TICK and RSI to aim to provide a view of NYSE market trend strength.
What is TICK
NYSE TICK, also known as the TICK index, is a technical analysis indicator that shows the number of stocks on the New York Stock Exchange (NYSE) that are trading on an uptick or a downtick in a particular period of time. The TICK index is calculated by subtracting the number of stocks trading on a downtick from the number of stocks trading on an uptick. A reading of +1000 on the TICK index, for example, would indicate that there are 1000 more stocks trading on an uptick than on a downtick. The TICK index is often used as a measure of market sentiment, as it can provide insight into whether there is more buying or selling pressure in the market at a given time. A high TICK index reading may suggest that there is strong buying pressure, while a low TICK index reading may indicate that there is more selling pressure in the market.
By default, I am using -800 and 800 for oversold and overbought levels. These are configurable. Also, this indicator includes TICK divergence signals.
The TICK index is usually very volatile, so this indicator is best suited for lower timeframes, such as 1 to 5 min charts.
Idea of TICK neutral zone
As part of this indicator I've identified what I consider as "neutral" range for the TICK. Based on my own personal experience, the market tends to be in consolidation or choppy in this range. By default, I've defined this range to be -200 to 200. This range is configurable.
Signals
In combination with RSI and Heikin Ashi RSI (HARSI), which help smooths out the RSI values and make it easier to identify trends and potential reversal points, this indicator aims to generate Bullish vs Bearish signals based on the following conditions:
- bullish / bearish HARSI candle
- Inside bar on HARSI candle
- TICK trend (above or below Neutral zone)
- RSI trend (above or below 0, but not overbought or oversold)
- RSI / HARSI convergence and divergence
When all bullish conditions are met, the signal turns bright green. Bright red when all bearish conditions are met. These generated signals aims to provide users easy to read visual cues to help with their trades.
A table is also provided in attempt to identify the trend in real time:
TICK trend:
- Bullish, Extended
- Bullish
- Neutral w/ Bullish bias
- Neutral w/ Bearish bias
- Bearish
- Bearish, Extended
RSI:
- Bullish
- Bearish
Note on scale
This indicator is based on the scale for TICK, hence the RSI and HARSI are scaled. By default, standard overbought RSI value of 70 = 800 on this scale, whereas oversold value of 30 = -800.
Credits:
Heikin Ashi RSI code was borrowed from @JayRogers - Heikin Ashi RSI Oscillator
DOW Theory Price Action Multi-Time FrameThis indicator gives a visual representation of Dow Theory Price action based trend analysis and provides trader a table with 4 different timeframe to align with the trend.
It will help traders identify if it is an ongoing Impulse Wave or a Corrective Wave.
3 rules for Bullish Price Action setup (Uptrend or continuation of existing UpTrend): Denoted by 'U' below the candlestic
HH - Higher High
HL - Higher Low
CAH - Close above prior High
3 rules for Bearish Price Action setup (Downtrend or continuation of existing DownTrend): Denoted by 'D' below the candlestic
LH - Lower High
HL - LowerLow
CAH - Close below prior Low
Exception - Outside Candle: Denoted by 'OC' above the candlestic
Outside reversal is a two-day price pattern that shows when a candle or bar on a candlestick or bar chart falls “outside” of the previous day's candle or bar.
The table posistion can be set be user from the input settings as per his screen setting / resolution.
The trailing line can is also customizable from inputs, recomended value is 3-4.
Ideation Credits: Mr. Vineet Jain
FrizBugLibrary "FrizBug"
Debug Tools | Pinescript Debugging Tool Kit
All in one Debugger - the benefit of wrapper functions to simply wrap variables or outputs and have the code still execute the same. Perfect for Debugging on Pine
str(inp)
Overloaded tostring like Function for all type+including Object Variables will also do arrays and matricies of all Types
Parameters:
inp : All types
Returns: string
print_label(str, x_offset, y, barstate, style, color, textcolor, text_align, size)
Label Helper Function - only needs the Str input to work
Parameters:
str :
x_offset : offset from last bar + or -
y : price of label
barstate : barstate built in variable
style : label style settin7
color : color setting
textcolor : textcolor
text_align : text align setting
size : text_sise
Returns: label
init()
initializes the database arrays
Returns: tuple | 2 matrix (1 matrix is varip(live) the other is reagular var (Bar))
update(log, live, live_console, log_console, live_lbl, log_lbl)
Put at the very end of your code / This updates all of the consoles
Parameters:
log : This matrix is the one used for Bar updates
live : This matrix is the one used for Real Time updates
live_console : on_offs for the consoles and lbls - call in the update function
log_console : on_offs for the consoles and lbls - call in the update function
live_lbl : on_offs for the consoles and lbls - call in the update function
log_lbl : on_offs for the consoles and lbls - call in the update function
Returns: void
log(log, inp, str_label, off, rows, index_cols, bars_back)
Function Will push to the Console offset to the right of Current bar, This is the main Console - it has 2 Feeds left and right (changeable)"
Parameters:
log : Matrix - Log or Live
inp : All types
str_label : (optional) This input will label it on the feed
off : Useful for when you don't want to remove the function"
rows : when printing or logging a matrix this will shorten the output will show last # of rows"
index_cols : When printing or logging a array or matrix this will shorten the array or the columns of a matrix by the #"
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)"
Returns: inp - all types (The log and print functions can be used as wrapper functions see usage below for examples)
Print(log, str_label, off, bars_back)
Function can be used to send information to a label style Console, Can be used as a wrapper function, Similar to str.format use with str()
Parameters:
log :
str_label : (optional) Can be used to label Data sent to the Console
off : Useful for when you don't want to remove the function
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)
Returns: string
print(inp, str_label, off, bars_back)
This Function can be used to send information to a label style Console, Can be used as a wrapper function, Overload print function
Parameters:
inp : All types
str_label : string (optional) Can be used to label Data sent to the Console
off : Useful for when you don't want to remove the function
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)
Returns: inp - all types (The log and print functions can be used as wrapper functions see usage below for examples)
Credits:
@kaigouthro - for the font library
@RicardoSantos - for the concept I used to make this
Thanks!
Use cases at the bottom
DR/IDR V1Defining Range DR and Implied Defining Range IDR for regular Session and overnight Session
This script is showing the IDR and DR for the regular trading session and for the overnight session based on the rules from the creator of the DR/IDR concept.
It works for all major Forex Pairs, BTC, ETH and the US Equity indices. This concept is based on rules and has a 80 % probability to be correct.
It should be applied in the 5 Min. Timeframe.
The timings for the RDR are from 09.30 - 10.30 am New York local time.
The timings for the ODR are from 03.00 - 04.00 am New York local time.
Rules:
1. If price in the 5 Min timeframe closes above the DR high after 10.30 am or 04.00 am then the DR low will be with 80 percent probability the low of the trading session. This is called confirmation.
2. If price in the 5 Min timeframe closes below the DR low after 10.30 am or 04.00 am then the DR high will be with 80 percent probability the high of the trading session. This is called confirmation.
3. If price closes above the IDR high after 10.30 am or 04.00 am it is an early indication that the low of the DR will be the low of the day and vice versa.
Credits:
This script imports the recently published (VisibleChart) library containing functions that return values calculated from the range of visible bars on the chart.
bmistiaen helped me a lot with this script. Thank you a lot.
Crypto and FX PSCA simple tool to calculate crypto position size and FX lot size.
How to use:
1. Use TradingView measurement tool or position tool to know how wide is your stop loss.
2. Set the equity and risk parameters.
2. For crypto, input the PERCENTAGE in stop loss;
For FX, input the PIPS.
3. Position size will be displayed in the panel.
Notes:
>Position size is in USDT for Cryptocurrencies
>Lot size for forex.
Forex contract size is your account type set by the broker:
Standard = 100,000 units = ~$10/pip
Mini = 10,000 units = ~$1/pip
Micro = 1,000 units = ~$0.10/pip
Nano = 100 units = ~$0. 01/pip
Credits:
trananhvu149
hanabil
Rainbow ChannelI have designed this indicator with the idea of staying focused on the price during the corresponding trend, for this I have built a rainbow channel
The upper part of the channel is painted in colors during the uptrend, at this time the lower part turns gray to focus only on the longs signals
The lower part of the channel is painted in colors during the downtrend, at this time the upper part turns gray to focus only on the shorts signals
The signals are followed by a mark that indicates when to close that trade.
The indicator works with all timeframes, I use it on the 1 hour chart and I do the trades in 1 minute.
CREDITS:
- @DonovanWall for his study "Gaussian Channel " included in this script
- @Alex Orekhov (everget) for his study "HalfTrend" included in this script
Volume Oscillator RefurbishedThis is an experimental version of Volume Oscillator.
For more information about Volume Oscillator, please access the link below:
www.tradingview.com
Objective
The script presented here provides some improvements over the original indicator, namely:
Show multiple moving averages;
Color the bars according to the direction of the averages;
Color the bars when reaching predefined limits.
Below is the print comparing with the original indicator:
Thanks and credits:
Volume Oscillator: TradingView
Moving Averages: PineCoders, CrackingCryptocurrency, MightyZinger, Alex Orekhov (everget), alexgrover, paragjyoti2012, Franklin Moormann (cheatcountry)
Nifty - Gap up Screener
Sample Stock Screener NSE is used to identify the list of Gap up Stocks from provided list. Modify script for other conditions
original credits: achalmeena ( )
Dual Fibonacci Zones & Ranged Vol DCA Study - R3c0nTraderWhat does this do?
This signal script (aka Study) was created so it could be used with the corresponding strategy "Dual Fibonacci Zone & Ranged Vol DCA Strategy - R3c0nTrader" to create the buy and sell signals for 3Commas bots.
How to Use
Configure the study to match your settings you have set in the strategy. This script comes with an buy and sell alert conditions built-in. Just click to add alert and select Buy or Sell and paste in your bot messages.
Credits:
Thank you "EvoCrypto" for granting me permission to use "Ranged Volume" to create this study
Thank you "eykpunter" for granting me permission to use "Fibonacci Zones" to create this study
Dual Fibonacci Zone & Ranged Vol DCA Strategy - R3c0nTraderWhat does this do?
This is for educational purposes and allows one to backtest two Fibonacci Zones simultaneously. This also includes an option for Ranged Volume as a parameter.
Pre-requisites:
First off, this is a Long only strategy as I wrote it with DCA in mind. It cannot be used for shorting. Shorting defeats the purpose of a DCA bot which has a goal that is Long a position not Short a position. If you want to short, there are plenty of free scripts out there that do this.
You must have some base knowledge or experience with Fibonacci trading, understanding what is ADX, +DI (and -DI), etc.
You can use this script without a 3Commas account and see how 3Commas DCA Bot would perform. However, I highly recommend inexperienced uses get a free account and going through the tutorials, FAQ's and knowledgebase. This would give you a base understanding of the settings you will see in this strategy and why you will need to know them. Only then should you try testing this strategy with a paper bot.
Background
After I had created and released "Fibonacci Zone DCA Strategy", I began expanding and testing other ideas.
The first idea was to add Ranged Volume to the Fibonacci Zone DCA strategy which I wanted for providing further confirmation before entering a trade. The second idea was to add a second Fibonacci Zone that was just as configurable as the first Fibonacci Zone. I managed to add both and they can be easily enabled or disabled via the strategy settings menu.
Things Got Real Interesting
Things got real interesting when I started testing strategies with two Fibonacci zones. Here's a quick list of what I found I was able to do:
Mix and match exit strategies. I could set the Fib-1 zone strategy to exit with a take profit % and separately set the Fib-2 zone strategy to exit when the price crosses the top-high fib border
Trade the trend. A common phrase amongst traders is "the Trend is your friend" and with the help of an additional Fib Zone, I was able to trade the trend more often by using two different Fib Zone strategies which if configured properly can shorten time to re-deploy capital, increase number of closed trades, and in some cases increase net profit.
Trade both bull market uptrends and bear market downtrends in the same strategy. I found I could configure one Fib Zone strategy to be really good in uptrends and another Fib Zone strategy to be really good in downtrends. In some cases, with both Fib Zone strategies enabled together in a single strategy I got better results than if the strategies were backtested separately.
There are many other trade strategies I am finding with this. One could be to trade a convergence or divergence of the two different Fib Zones. This could possibly be achieved by setting one strategy to have different Fibonacci length.
Credits:
Thank you "EvoCrypto" for granting me permission to use "Ranged Volume" to create this strategy
Thank you "eykpunter" for granting me permission to use "Fibonacci Zones" to create this strategy
Thank you "junyou0424" for granting me permission to use "DCA Bot with SuperTrend Emulator" which I used for adding bot inputs, calculations, and strategy
Follow The Ranging Hull - studyFollow the Ranging hull - Study is a scalping indicator based off momentum and trend
It indicates the current momentum, and shows the momentum and true strength of a higher timeframe through a status window.
Credits:
Hull Suite by InSilico www.tradingview.com
Range Filter Buy and Sell 5 min www.tradingview.com
Follow Line Indicator by Dreadblitz www.tradingview.com
TSI by Everget www.tradingview.com
Ranged Volume DCA Strategy - R3c0nTraderUpdate: Republishing this as Public Open-Source script.
Credits:
Thank you "EvoCrypto" for granting me permission to use "Ranged Volume" to create this strategy.
Thank you "junyou0424" for granting me permission to use "DCA Bot with SuperTrend Emulator" which I used for adding bot inputs, calculations, and strategy
What does this do?
This script is mainly used for backtesting a Ranged Volume strategy to see how a 3Commas bot would perform.
I created this script out of necessity and I wanted a way to test a 3Commas DCA bot with a strategy based on “Volume.”
I came across "EvoCrypto’s" "Ranged Volume" study and strategy in TradingView and I liked it. I wanted to configure it so it can be used for DCA bot backtesting. I used parts from "junyou0424’s" "DCA Bot with SuperTrend Emulator" to add the following:
1. The Start Time and End Time
2. Price deviation to open safety orders (%)
3. Target Take Profit (%)
4. Trailing deviation
5. Base Order and Safety Order
6. Safety order volume scale
7. Safety order step scale
8. Max safety orders
In addition to the above, I also added chart indicators for "Take Profit" as well as "Safety Order"
Pre-requisites:
You can use this script without a 3Commas account and see how 3Commas DCA Bot and Ranged Volume strategy would perform vs. a non-DCA strategy. However, I highly recommend signing up for their free account and going through their training. This would give you a base understanding on the settings you will see in this strategy and why you will need to know them.
That said these are the pre-requisites I suggest you have:
1. Base Knowledge of 3Commas DCA bots
2. Base knowledge of settings such as “Max safety trades count”, “safety order volume scale” and “safety order step scale”. If these are alien to you, I suggest you read up on these.
3. Knowledge of setting up a Single-pair 3Commas bot for receiving custom TradingView signal.
4. A paper-bot to test your ideas. (Do not use a real money bot until you have tested it sufficiently with a paper-bot. You alone are responsible for your results!)
5. Add the study I created called "R3c0nTrader’s Ranged Volume Study” which adds a separate chart in its own pane showing the volume spikes. It will also generate the “buy” signals for your bot. NOTE: The study also has the same color scheme as this strategy and having the colors in both the strategy and the study will make things easier to see. If you use EvoCrypto’s Ranged Volume Study instead, just keep in mind that the colors won’t match, and you will have to manually match them.
6. Make your buy signals from your strategy are the same as in your study! To do this, use the same “Volume Range Length” you entered in the STRATEGY and enter that value for the “Volume Range Length” in the STUDY. Also ensure you have the same settings for “Heikin Ashi” (On or Off).
Comparisons of Ranged Volume Strategy vs Ranged Volume DCA Strategy
BTCUSD
Beware of Strategies that claim super high profits. This can easily be done by lowering the initial capital to something unrealistic. If I did that with this strategy and set the initial capital $100 and base order size to $100, I get a net profit of 2,864% which is not realistic.
How to Use
1. On the “Inputs” tab:
a. Set your Start and End Time to backtest against.
b. Set your “Volume Range Length” (number of bars to look back)
c. “Heikin Ashi Colors” – Usually I leave this enabled
d. “Show Bar Colors” – Leave enabled
e. “Show Break-Out” – Leave enabled
f. “Show Range” – Leave enabled
g. Set your other inputs which are those settings you would find in your 3Commas bot that you want to test (e.g., Price deviation to open safety orders, Target Take Profit, Base order, Safety order, etc.).
h. Quick Example for BTCUSD on 2hr chart:
i. Price deviation to open safety orders (%) = 6
ii. Target Take Profit (%) = 14
iii. Trailing deviation = 0
iv. Base order = 100
v. Safety order = 200
vi. Safety order volume scale = 2
vii. Safety order step scale = 1.4
viii. Max safety order = 5
2. On the “Properties” tab, set your initial capital, base currency, etc.
a. Initial capital – Default is 10,000 (Please use realistic values here. The amount here should be able to cover ALL your safety orders if they were triggered. Ideally, you should have funds left over and not use all trade capital.)
b. Base currency – Select your currency
c. Order Size - Not used. Use the “Inputs” tab to change your base order size.
d. Leave “Pyramiding” set to 999. This acts as a ceiling to the “Max safety orders” on the “Inputs” tab. It must always be higher than your “Max safety orders.” For example, if you set your “Max safety orders” to “4” and “Pyramiding” to “4” then it effectively means you have “3” “Max safety orders” and not “4” because it is counting each successive entry including the initial order.
e. “Commission” - Optional
f. “Verify price for limit orders” – Leave at zero. This does not change anything that I can tell.
g. Optional - Enter a value for “Commission”
h. Slippage – Optional. Slippage does not occur in backtesting but does occur in real trading but it can be simulated. Example use case for tracking performance of a real money bot: You enter the start date and time of your bot’s trade into this strategy and you notice some values are a little off due to slippage (average price, take profit, safety orders are not lining up) then you would go back here and increase the slippage until those lines up close enough with your actuals.
i. Margin for long positions – I don’t use this honestly.
j. Margin for short positions – I don’t use this honestly.
k. Recalculate “After order is filled” and “On every tick” – I don’t use this honestly.
3. “Style” tab
a. Ranged Volume Bar Coloring - You must disable bar coloring in any studies you added or this may not work properly
i. Color 0 – Default Yellow; appears when a volume breakout occurs
ii. Color 1 – Default Red; appears when a volume breakdown occurs
iii. Color 2 – Light Blue; appears when Close is higher than the Open
iv. Color 3 – Dark Blue; appears when the Close is lower than the Open
b. Take profit – Default Green; take profit line
c. Safety order – Default Light Blue; safety order line
d. No Safety Orders left – Default Red; when a trade runs out of safety orders, the line turns red and there is no safety orders left underneath to catch any further falling price movements.
e. Avg Position Price – Default Orange; your average position price for any given trade.
f. Take Profit Plot Area – Default Green; creates a highlighted area for your take profit
g. SO Plot Area – Default Light Blue; creates a highlighted area for your safety orders
h. Trades on chart – Show or hide your trades on the chart
i. Signal labels – Show or hide the trade signal labels on the chart
j. Quantity – Show or hide the trade quantity on the chart
Explanation of Chart lines and colors on chart
HighTimeframeSamplingLibrary "HighTimeframeSampling"
Library for sampling high timeframe (HTF) data. Returns an array of historical values, an arbitrary historical value, or the highest/lowest value in a range, spending a single security() call.
An optional pass-through for the chart timeframe is included. Other than that case, the data is fixed and does not alter over the course of the HTF bar. It behaves consistently on historical and elapsed realtime bars.
The first version returns floating-point numbers only. I might extend it if there's interest.
🙏 Credits: This library is (yet another) attempt at a solution of the problems in using HTF data that were laid out by Pinecoders - to whom, especially to Luc F, many thanks are due - in "security() revisited" - which I recommend you consult first. Go ahead, I'll wait.
All code is my own.
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WHAT'S THE PROBLEM? OR, WHY NOT JUST USE SECURITY()
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There are many difficulties with using HTF data, and many potential solutions. It's not really possible to convey it only in words: you need to see it on a chart.
Before using this library, please refer to my other HTF library, HighTimeframeTiming: which explains it extensively, compares many different solutions, and demonstrates (what I think are) the advantages of using this very library, namely, that it's stable, accurate, versatile and inexpensive. Then if you agree, come back here and choose your function.
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MOAR EXPLANATION
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🧹 Housekeeping: To see which plot is which, turn line labels on: Settings > Scales > Indicator Name Label. Vertical lines at the top of the chart show the open of a HTF bar: grey for historical and white for real-time bars.
‼ LIMITATIONS: To avoid strange behaviour, use this library on liquid assets and at chart timeframes high enough to reliably produce updates at least once per bar period.
A more conventional and universal limitation is that the library does not offer an unlimited view of historical bars. You need to define upfront how many HTF bars you want to store. Very large numbers might conceivably run into data or performance issues.
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BRING ON THE FUNCTIONS
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@function f_HTF_Value(string _HTF, float _source, int _arrayLength, int _HTF_Offset, bool _useLiveDataOnChartTF=false)
Returns a floating-point number from a higher timeframe, with a historical operator within an abitrary (but limited) number of bars.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't go back further in history than this number of bars (minus one, because the current/most recent available bar is also stored).
@param int _HTF_Offset is the historical operator for the value you want to return. E.g., if you want the most recent fixed close, _source=close and _HTF_Offset = 0. If you want the one before that, _HTF_Offset=1, etc.
The number of HTF bars to look back must be zero or more, and must be one less than the number of bars stored.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches the raw source values from security(){0}.
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@returns a floating-point value that you requested from the higher timeframe.
@function f_HTF_Array(string _HTF, float _source, int _arrayLength, bool _useLiveDataOnChartTF=false, int _startIn, int _endIn)
Returns an array of historical values from a higher timeframe, starting with the current bar. Optionally, returns a slice of the array. The array is in reverse chronological order, i.e., index 0 contains the most recent value.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to keep in the array.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param int _startIn is the array index to begin taking a slice. Must be at least one less than the length of the array; if out of bounds it is corrected to 0.
@param int _endIn is the array index BEFORE WHICH to end the slice. If the ending index of the array slice would take the slice past the end of the array, it is corrected to the end of the array. The ending index of the array slice must be greater than or equal to the starting index. If the end is less than the start, the whole array is returned. If the starting index is the same as the ending index, an empty array is returned. If either the starting or ending index is negative, the entire array is returned (which is the default behaviour; this is effectively a switch to bypass the slicing without taking up an extra parameter).
@returns an array of HTF values.
@function f_HTF_Highest(string _HTF="", float _source, int _arrayLength, bool _useLiveDataOnChartTF=true, int _rangeIn)
Returns the highest value within a range consisting of a given number of bars back from the most recent bar.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't have a range greater than this number.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param _rangeIn is the number of bars to include in the range of bars from which we want to find the highest value. It is NOT the historical operator of the last bar in the range. The range always starts at the current bar. A value of 1 doesn't make much sense but the function will generously return the only value it can anyway. A value less than 1 doesn't make sense and will return an error. A value that is higher than the number of stored values will be corrected to equal the number of stored values.
@returns a floating-point number representing the highest value in the range.
@function f_HTF_Lowest(string _HTF="", float _source, int _arrayLength, bool _useLiveDataOnChartTF=true, int _rangeIn)
Returns the lowest value within a range consisting of a given number of bars back from the most recent bar.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't go back further in history than this number of bars (minus one, because the current/most recent available bar is also stored).
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param _rangeIn is the number of bars to include in the range of bars from which we want to find the highest value. It is NOT the historical operator of the last bar in the range. The range always starts at the current bar. A value of 1 doesn't make much sense but the function will generously return the only value it can anyway. A value less than 1 doesn't make sense and will return an error. A value that is higher than the number of stored values will be corrected to equal the number of stored values.
@returns a floating-point number representing the lowest value in the range.
Follow The Ranging HullThis is a scalping strategy, trying to make quick points based on momentum and trend trading.
Entry Points are when either the range filter or the the following line changes colour. And the Hull is in that same direction.
--The Strategy Only enters on range filter entry point for now.
This Strategy has been tested on the NASDAQ 1 min, And works best with low timeframes.
Set the IsStrategy on the settings to true, to activate the strategy.
Make sure the Dates are correct .
Credits:
Hull Suite by InSilico www.tradingview.com
Range Filter Buy and Sell 5 min www.tradingview.com
Follow Line Indicator by Dreadblitz www.tradingview.com
HighTimeframeTimingLibrary "HighTimeframeTiming"
@description Library for sampling high timeframe (HTF) historical data at an arbitrary number of HTF bars back, using a single security() call.
The data is fixed and does not alter over the course of the HTF bar. It also behaves consistently on historical and elapsed realtime bars.
‼ LIMITATIONS: This library function depends on there being a consistent number of chart timeframe bars within the HTF bar. This is almost always true in 24/7 markets like crypto.
This might not be true if the chart doesn't produce an update when expected, for example because the asset is thinly traded and there is no volume or price update from the feed at that time.
To mitigate this risk, use this function on liquid assets and at chart timeframes high enough to reliably produce updates at least once per bar period.
The consistent ratio of bars might also break down in markets with irregular sessions and hours. I'm not sure if or how one could mitigate this.
Another limitation is that because we're accessing a multiplied number of chart bars, you will run out of chart bars faster than you would HTF bars. This is only a problem if you use a large historical operator.
If you call a function from this library, you should probably reproduce these limitations in your script description.
However, all of this doesn't mean that this function might not still be the best available solution, depending what your needs are.
If a single chart bar is skipped, for example, the calculation will be off by 1 until the next HTF bar opens. This is certainly inconsistent, but potentially still usable.
@function f_offset_synch(float _HTF_X, int _HTF_H, int _openChartBarsIn, bool _updateEarly)
Returns the number of chart bars that you need to go back in order to get a stable HTF value from a given number of HTF bars ago.
@param float _HTF_X is the timeframe multiplier, i.e. how much bigger the selected timeframe is than the chart timeframe. The script shows a way to calculate this using another of my libraries without using up a security() call.
@param int _HTF_H is the historical operator on the HTF, i.e. how many bars back you want to go on the higher timeframe. If omitted, defaults to zero.
@param int _openChartBarsIn is how many chart bars have been opened within the current HTF bar. An example of calculating this is given below.
@param bool _updateEarly defines whether you want to update the value at the closing calculation of the last chart bar in the HTF bar or at the open of the first one.
@returns an integer that you can use as a historical operator to retrieve the value for the appropriate HTF bar.
🙏 Credits: This library is an attempt at a solution of the problems in using HTF data that were laid out by Pinecoders in "security() revisited" -
Thanks are due to the authors of that work for an understanding of HTF issues. In addition, the current script also includes some of its code.
Specifically, this script reuses the main function recommended in "security() revisited", for the purposes of comparison. And it extends that function to access historical data, again just for comparison.
All the rest of the code, and in particular all of the code in the exported function, is my own.
Special thanks to LucF for pointing out the limitations of my approach.
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EXPLANATION
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Problems with live HTF data: Many problems with using live HTF data from security() have been clearly explained by Pinecoders in "security() revisited"
In short, its behaviour is inconsistent between historical and elapsed realtime bars, and it changes in realtime, which can cause calculations and alerts to misbehave.
Various unsatisfactory solutions are discussed in "security() revisited", and understanding that script is a prerequisite to understanding this library.
PineCoders give their own solution, which is to fix the data by essentially using the previous HTF bar's data. Importantly, that solution is consistent between historical and realtime bars.
This library is an attempt to provide an alternative to that solution.
Problems with historical HTF data: In addition to the problems with live HTF data, there are different issues when trying to access historical HTF data.
Why use historical HTF data? Maybe you want to do custom calculations that involve previous HTF bars. Or to use HTF data in a function that has mutable variables and so can't be done in a security() call.
Most obviously, using the historical operator (in this description, represented using { } because the square brackets don't render) on variables already retrieved from a security() call, e.g. HTF_Close{1}, is not very useful:
it retrieves the value from the previous *chart* bar, not the previous HTF bar.
Using {1} directly in the security() call instead does get data from the previous HTF bar, but it behaves inconsistently, as we shall see.
This library addresses these concerns as well.
Housekeeping: To follow what's going on with the example and comparisons, turn line labels on: Settings > Scales > Indicator Name Label.
The following explanation assumes "close" as the source, but you can change it if you want.
To quickly see the difference between historical and realtime bars, set the HTF to something like 3 minutes on a 15s chart.
The bars at the top of the screen show the status. Historical bars are grey, elapsed realtime bars are red, and the realtime bar is green. A white vertical line shows the open of a HTF bar.
A: This library function f_offset_synch(): When supplied with an input offset of 0, it plots a stable value of the close of the *previous* HTF bar. This value is thus safe to use for calculations and alerts.
For a historical operator of {1}, it gives the close of the *last-but-one* bar. Sounds simple enough. Let's look at the other options to see its advantages.
B: Live HTF data: Represented on the line label as "security(){0}". Note: this is the source that f_offset_synch() samples.
The raw HTF data is very different on historical and realtime bars:
+ On historical bars, it uses a flat value from the end of the previous HTF bar. It updates at the close of the HTF bar.
+ On realtime bars, it varies between and within each chart bar.
There might be occasions where you want to use live data, in full knowledge of its drawbacks described above. For example, to show simple live conditions that are reversible after a chart bar close.
This library transforms live data to get the fixed data, thus giving you access to both live and fixed data with only one security() call.
C: Historical data using security(){H}: To see how this behaves, set the {H} value in the settings to 1 and show options A, B, and C.
+ On historical bars, this option matches option A, this library function, exactly. It behaves just like security(){0} but one HTF bar behind, as you would expect.
+ On realtime bars, this option takes the value of security(){0} at the end of a HTF bar, but it takes it from the previous *chart* bar, and then persists that.
The easiest way to see this inconsistency is on the first realtime bar (marked red at the top of the screen). This option suddenly jumps, even if it's in the middle of a HTF bar.
Contrast this with option A, which is always constant, until it updates, once per HTF bar.
D: PineCoders' original function: To see how this behaves, show options A, B, and D. Set the {H} value in the settings to 0, then 1.
The PineCoders' original function (D) and extended function (E) do not have the same limitations as this library, described in the Limitations section.
This option has all of the same advantages that this library function, option A, does, with the following differences:
+ It cannot access historical data. The {H} setting makes no difference.
+ It always updates at the open of the first chart bar in a new HTF bar.
By contrast, this library function, option A, is configured by default to update at the close of the last chart bar in a HTF bar.
This little frontrunning is only a few seconds but could be significant in trading. E.g. on a 1D HTF with a 4H chart, an alert that involves a HTF change set to trigger ON CLOSE would trigger 4 hours later using this method -
but use exactly the same value. It depends on the market and timeframe as to whether you could actually trade this. E.g. at the very end of a tradfi day your order won't get executed.
This behaviour mimics how security() itself updates, as is easy to see on the chart. If you don't want it, just set in_updateEarly to false. Then it matches option D exactly.
E: PineCoders' function, extended to get history: To see how this behaves, show options A and E. Set the {H} value in the settings to 0, then 1.
I modified the original function to be able to get historical values. In all other respects it is the same.
Apart from not having the option to update earlier, the only disadvantage of this method vs this library function is that it requires one security() call for each historical operator.
For example, if you wanted live data, and fixed data, and fixed data one bar back, you would need 3 security() calls. My library function requires just one.
This is the essential tradeoff: extra complexity and less robustness in certain circumstances (the PineCoders function is simple and universal by comparison) for more flexibility with fewer security() calls.
Multi-Timeframe 10XIMPORTANT NOTE:
-> The timeframe for this indicator must be set at 1 minute;
-> If the chart timeframe is higher than 1 minute, the results shown in the table for timeframes lower than the chart will not be correct;
-> Tradingview's own documentation explains this as follows: " It is not recommended to request data of a timeframe lower that the current chart timeframe, for example 1 minute data from a 5 minutes chart. The main problem with such a case is that some part of a 1 minute data will be inevitably lost, as it’s impossible to display it on a 5 minutes chart and not to break the time axis. In such cases the behavior of security can be rather unexpected "; and
-> It is therefore recommended that this indicator is placed in a standalone 1min chart window, and the window resized to only show the table to avoid any issues.
Credits:
-> J. Welles Wilder creating the Directional Movement System (DMS) (1978); and
-> John Carter applying the DMS to create the popular Simpler Trading 10X Bars indicator.
Introduction:
Quickly see the quality and strength of a trend based on Directional Movement Index (DMI).
The Average Directional Index (ADX), Minus Directional Indicator (-DI) and Plus Directional Indicator (+DI) represent a group of directional movement indicators that form a trading system developed by Welles Wilder. Although Wilder designed his Directional Movement System with commodities and daily prices in mind, these indicators can also be applied to stocks. Wilder determined directional movement by comparing the difference between two consecutive lows with the difference between their respective highs.
+DI and -DI are derived from smoothed averages of these differences and measure trend direction over time. These two indicators are often collectively referred to as the DMI. ADX is in turn derived from the smoothed averages of the difference between +DI and -DI; it measures the strength of the trend (regardless of direction) over time.
Trade Signals:
-> Green indicates an uptrend i.e. when +DI is above -DI and ADX is greater than 20 - there is more upward pressure than downward pressure in the price;
-> Red indicates a downtrend i.e. when -DI is above +DI and ADX is greater than 20 - there is more downward pressure on the price; and
-> Yellow indicates no strong directional trend and potential for a reversal.
Standalone Indicator:
The 10X Bars version of the indicator can be found here:
DCA Bot IndicatorName: DCA Bot Indicator
Category: Dollar Cost Average.
Operating mode: Alerts at a specific time, day of the week and day of the month.
Trades duration: N/A.
Timeframe: 1H
Suggested usage: long-term investing DCA strategies.
Entry: Only indicates the time and then the day of the week or the day of the month to buy.
Exit: As per long-term Investor’s strategy.
Usage: If you want to perform a Dollar Cost Averaging approach with:
- Daily purchases (at a specific time)
- Weekly purchases (at a specific time and day of the week)
- Monthly purchases (at a specific time and day of the month)
It is then possible to set the alert text with a preferred message or for use with trade automation systems. The green background identify the specific time chosen.
It is possible to identify through the Bias Analyzer the best time for the daily purchase.
Configuration:
- Buy Time: hour you would like to buy, please consider that the script is executed at the end of the defined time, so if you would like to buy at 2, have to put 1.
- Buy only Days of the Week: you can select the day you want.
- Buy only on Day of Month, you can specify a specific day.
Credits:
- dsteaves for inspiration
Multi-Timeframe TTM Squeeze Pro
IMPORTANT NOTE:
-> The timeframe for this indicator must be set at 1 minute;
-> If the chart timeframe is higher than 1 minute, the results shown in the table for timeframes lower than the chart will not be correct;
-> Tradingview's own documentation explains this as follows: " It is not recommended to request data of a timeframe lower that the current chart timeframe, for example 1 minute data from a 5 minutes chart. The main problem with such a case is that some part of a 1 minute data will be inevitably lost, as it’s impossible to display it on a 5 minutes chart and not to break the time axis. In such cases the behavior of security can be rather unexpected "; and
-> It is therefore recommended that this indicator is placed in a standalone 1min chart window, and the window resized to only show the table to avoid any issues.
Credits:
-> John Carter creating the TTM Squeeze and TTM Squeeze Pro
-> Lazybear's original interpretation of the TTM Squeeze: Squeeze Momentum Indicator
-> Makit0's evolution of Lazybear's script to factor in the TTM Squeeze Pro upgrades - Squeeze PRO Arrows
This is my version of their collective works, with amendments primarily to the Squeeze Conditions to more accurately reflect the color coding used by the official TMM Squeeze Pro indicator.
TTM Squeeze Guide
For those unfamiliar with the TTM Squeeze, it is simply a visual way of seeing how Bollinger Bands (standard deviations from a simple moving average ) relate to Keltner Channels ( average true range bands) compared with the momentum of the price action. The concept is that as Bollinger Bands compress within Keltner Channels , price volatility decreases, giving way for a potential explosive price movement up or down.
Differences between the original TTM Squeeze and TTM Squeeze Pro:
-> Both use a 2 standard deviation Bollinger Band ;
-> The original squeeze only used a 1.5 ATR Keltner Channel; and
-> The pro version uses 1.0, 1.5 and 2.0 ATR Keltner Channels .
The pro version therefore helps differentiate between levels of squeeze (compression) as the Bollinger Bands moves through the Keltner Channels i.e. the greater the compression, the more potential for explosive moves - less compression means more squeezing.
The Histogram shows price momentum whereas the colored dots (along the zeroline) show where the Bollinger Bands are in relation to the Keltner Channels:
-> Cyan Bars = positive, increasing momentum;
-> Blue Bars = positive, decreasing momentum (indication of a reversal in price direction);
-> Red Bars = negative, increasing momentum;
-> Yellow Bars = negative, decreasing momentum (indication of a reversal in price direction);
-> Orange Dots = High Compression / large squeeze (One or both of the Bollinger Bands is inside the 1st (1.0 ATR) Keltner Channel);
-> Red Dots = Medium Squeeze (One or both of the Bollinger Bands is inside the 2nd (1.5 ATR) Keltner Channel);
-> Black Dots = Low compression / wide squeeze (One or both of the Bollinger Bands is inside the 3rd (2.0 ATR) Keltner Channels );
-> Green Dots = No Squeeze / Squeeze Fired (One or both of the Bollinger Bands is outside of the 3rd (2.0 ATR) Keltner Channel).
Ideal Scenario:
As the ticker enters the squeeze, black dots would warn of the beginning of a low compression squeeze. As the Bollinger bands continue to constrict within the Keltner Channels , red dots would highlight a medium compression. As the price action and momentum continues to compress an orange dot shows warning of high compression. As price action leaves the squeeze, the coloring would reverse e.g. orange to red to black to green. Any compression squeeze is considered fired at the first green dot that appears.
Note: This is an ideal progression of the different types of squeezes, however any type of squeeze (and color sequence) may appear at anytime, therefore the focus is primarily on the green dots after any type of compression.
Entry and Exit Guide:
-> John Carter recommends entering a position after at least 5 black dots or wait for 1st green dot ; and
-> Exit on second blue or yellow bar or, alternatively, remain in the position after confirming a continuing trend through a separate indicator.
Standalone Indicator:
The indicator (which can be used on any timeframe) can be found here:
