Indicators Combination Framework v3 IND [DTU]Hello All,
This script is a framework to analyze and see the results by combine selected indicators for (long, short, longexit, shortexit) conditions.
I was designed this for beginners and users to facilitate to see effects of the technical indicators combinations on the chart WITH NO CODE
You can improve your strategies according the results of this system by connecting the framework to a strategy framework/template such as Pinecoder, Benson, daveatt or custom.
This is enhanced version of my previous indicator "Indicators & Conditions Test Framework "
Currently there are 93 indicators (23 newly added) connected over library. You can also import an External Indicator or add Custom indicator (In the source)
It is possible to change it from Indicator to strategy (simple one) by just remarking strategy parts in the source code and see real time profit of your combinations
Feel free to change or use it in your source
Special thanks goes to Pine wizards: Trading view (built-in Indicators), @Rodrigo, @midtownsk8rguy, @Lazybear, @Daveatt and others for their open source codes and contributions
SIMPLE USAGE
1. SETTING: Show Alerts= True (To see your entries and Exists)
2. Define your Indicators (ex: INDICATOR1: ema(close,14), INDICATOR2: ema(close,21), INDICATOR3: ema(close,200)
3. Define Your Combinations for long & Short Conditions
a. For Long: (INDICATOR1 crossover INDICATOR2) AND (INDICATOR3 < close)
b. For Short: (INDICATOR1 crossunder INDICATOR2) AND (INDICATOR3 > close)
4. Select Strategy/template (Import strategy to chart) that you export your signals from the list
5. Analyze the best profit by changing Indicators values
SOME INDICATORS DETAILS
Each Indicator includes:
- Factorization : Converting the selected indicator to Double, triple Quadruple such as EMA to DEMA, TEMA QEMA
- Log : Simple or log10 can be used for calculation on function entries
- Plot Type : You can overlay the indicator on the chart (such ema) or you can use stochastic/Percentrank approach to display in the variable hlines range
- Extended Parametes : You can use default parameters or you can use extended (P1,P2) parameters regarding to indicator type and your choice
- Color : You can define indicator color and line properties
- Smooth : you can enable swma smooth
- indicators : you can select one of the 93 function like ema(),rsi().. to define your indicator
- Source : you can select from already defined indicators (IND1-4), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
CONDITION DETAILS
- There are are 4 type of conditions, long entry, short entry, long exit, short exit.
- Each condition are built up from 4 combinations that joined with "AND" & "OR" operators
- You can see the results by enabling show alerts check box
- If you only wants to enter long entry and long exit, just fill these conditions
- If "close on opposite" checkbox selected on settings, long entry will be closed on short entry and vice versa
COMBINATIONS DETAILS
- There are 4 combinations that joined with "AND" & "OR" operators for each condition
- combinations are built up from compare 1st entry with 2nd one by using operator
- 1st and 2nd entries includes already defined indicators (IND1-5), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
- Operators are comparison values such as >,<, crossover,...
- 2nd entry include "VALUE" parameter that will use to compare 1st indicator with value area
- If 2nd indicator selected different than "VALUE", value are will mean previous value of the selection. (ex: value area= 2, 2nd entry=close, means close )
- Selecting "NONE" for the 1st entry will disable calculation of current and following combinations
JOINS DETAILS
- Each combination will join wiht the following one with the JOIN (AND, OR) operator (if the following one is not equal "NONE")
CUSTOM INDICATOR
- Custom Indicator defines harcoded in the source code.
- You can call it with "CUST" in the Indicator definition source or combination entries source
- You can change or implement your custom indicator by updating the source code
EXTERNAL INDICATOR
- You can import an external indicator by selecting it from the ext source.
- External Indicator should be already imported to the chart and it have an plot function to output its signal
EXPORTING SIGNAL
- You can export your result to an already defined strategy template such as Pine coders, Benson, Daveatt Strategy templates
- Or you can define your custom export for other future strategy templates
ALERTS
- By enabling show alerts checkbox, you can see long entry exits on the bottom, and short entry exits aon the top of the chart
ADDITIONAL INFO
- You can see all off the inputs descriptions in the tooltips. (You can also see the previous version for details)
- Availability to set start, end dates
- Minimize repainting by using security function options (Secure, Semi Secure, Repaint)
- Availability of use timeframes
-
Version 3 INDICATORS LIST (More to be added):
▼▼▼ OVERLAY INDICATORS ▼▼▼
alma(src,len,offset=0.85,sigma=6).-------Arnaud Legoux Moving Average
ama(src,len,fast=14,slow=100).-----------Adjusted Moving Average
accdist().-------------------------------Accumulation/distribution index.
cma(src,len).----------------------------Corrective Moving average
dema(src,len).---------------------------Double EMA (Same as EMA with 2 factor)
ema(src,len).----------------------------Exponential Moving Average
gmma(src,len).---------------------------Geometric Mean Moving Average
highest(src,len).------------------------Highest value for a given number of bars back.
hl2ma(src,len).--------------------------higest lowest moving average
hma(src,len).----------------------------Hull Moving Average.
lagAdapt(src,len,perclen=5,fperc=50).----Ehlers Adaptive Laguerre filter
lagAdaptV(src,len,perclen=5,fperc=50).---Ehlers Adaptive Laguerre filter variation
laguerre(src,len).-----------------------Ehlers Laguerre filter
lesrcp(src,len).-------------------------lowest exponential esrcpanding moving line
lexp(src,len).---------------------------lowest exponential expanding moving line
linreg(src,len,loffset=1).---------------Linear regression
lowest(src,len).-------------------------Lovest value for a given number of bars back.
mcginley(src, len.-----------------------McGinley Dynamic adjusts for market speed shifts, which sets it apart from other moving averages, in addition to providing clear moving average lines
percntl(src,len).------------------------percentile nearest rank. Calculates percentile using method of Nearest Rank.
percntli(src,len).-----------------------percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
previous(src,len).-----------------------Previous n (len) value of the source
pivothigh(src,BarsLeft=len,BarsRight=2).-Previous pivot high. src=src, BarsLeft=len, BarsRight=p1=2
pivotlow(src,BarsLeft=len,BarsRight=2).--Previous pivot low. src=src, BarsLeft=len, BarsRight=p1=2
rema(src,len).---------------------------Range EMA (REMA)
rma(src,len).----------------------------Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sar(start=len, inc=0.02, max=0.02).------Parabolic SAR (parabolic stop and reverse) is a method to find potential reversals in the market price direction of traded goods.start=len, inc=p1, max=p2. ex: sar(0.02, 0.02, 0.02)
sma(src,len).----------------------------Smoothed Moving Average
smma(src,len).---------------------------Smoothed Moving Average
super2(src,len).-------------------------Ehlers super smoother, 2 pole
super3(src,len).-------------------------Ehlers super smoother, 3 pole
supertrend(src,len,period=3).------------Supertrend indicator
swma(src,len).---------------------------Sine-Weighted Moving Average
tema(src,len).---------------------------Triple EMA (Same as EMA with 3 factor)
tma(src,len).----------------------------Triangular Moving Average
vida(src,len).---------------------------Variable Index Dynamic Average
vwma(src,len).---------------------------Volume Weigted Moving Average
volstop(src,len,atrfactor=2).------------Volatility Stop is a technical indicator that is used by traders to help place effective stop-losses. atrfactor=p1
wma(src,len).----------------------------Weigted Moving Average
vwap(src_).------------------------------Volume Weighted Average Price (VWAP) is used to measure the average price weighted by volume
▼▼▼ NON OVERLAY INDICATORS ▼▼
adx(dilen=len, adxlen=14, adxtype=0).----adx. The Average Directional Index (ADX) is a used to determine the strength of a trend. len=>dilen, p1=adxlen (default=14), p2=adxtype 0:ADX, 1:+DI, 2:-DI (def:0)
angle(src,len).--------------------------angle of the series (Use its Input as another indicator output)
aroon(len,dir=0).------------------------aroon indicator. Aroons major function is to identify new trends as they happen.p1 = dir: 0=mid (default), 1=upper, 2=lower
atr(src,len).----------------------------average true range. RMA of true range.
awesome(fast=len=5,slow=34,type=0).------Awesome Oscilator is an indicator used to measure market momentum. defaults : fast=len= 5, p1=slow=34, p2=type: 0=Awesome, 1=difference
bbr(src,len,mult=1).---------------------bollinger %%
bbw(src,len,mult=2).---------------------Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci(src,len).----------------------------commodity channel index
cctbbo(src,len).-------------------------CCT Bollinger Band Oscilator
change(src,len).-------------------------A.K.A. Momentum. Difference between current value and previous, source - source . is most commonly referred to as a rate and measures the acceleration of the price and/or volume of a security
cmf(len=20).-----------------------------Chaikin Money Flow Indicator used to measure Money Flow Volume over a set period of time. Default use is len=20
cmo(src,len).----------------------------Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog(src,len).----------------------------The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
copcurve(src,len).-----------------------Coppock Curve. was originally developed by Edwin Sedge Coppock (Barrons Magazine, October 1962).
correl(src,len).-------------------------Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count(src,len).--------------------------green avg - red avg
cti(src,len).----------------------------Ehler s Correlation Trend Indicator by
dev(src,len).----------------------------ta.dev() Measure of difference between the series and its ta.sma
dpo(len).--------------------------------Detrended Price OScilator is used to remove trend from price.
efi(len).--------------------------------Elders Force Index (EFI) measures the power behind a price movement using price and volume.
eom(len=14,div=10000).-------------------Ease of Movement.It is designed to measure the relationship between price and volume.p1 = div: 10000= (default)
falling(src,len).------------------------ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
fisher(len).-----------------------------Fisher Transform is a technical indicator that converts price to Gaussian normal distribution and signals when prices move significantly by referencing recent price data
histvol(len).----------------------------Historical volatility is a statistical measure used to analyze the general dispersion of security or market index returns for a specified period of time.
kcr(src,len,mult=2).---------------------Keltner Channels Range
kcw(src,len,mult=2).---------------------ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
klinger(type=len).-----------------------Klinger oscillator aims to identify money flow’s long-term trend. type=len: 0:Oscilator 1:signal
macd(src,len).---------------------------MACD (Moving Average Convergence/Divergence)
mfi(src,len).----------------------------Money Flow Index s a tool used for measuring buying and selling pressure
msi(len=10).-----------------------------Mass Index (def=10) is used to examine the differences between high and low stock prices over a specific period of time
nvi().-----------------------------------Negative Volume Index
obv().-----------------------------------On Balance Volume
pvi().-----------------------------------Positive Volume Index
pvt().-----------------------------------Price Volume Trend
ranges(src,upper=len, lower=-5).---------ranges of the source. src=src, upper=len, v1:lower=upper . returns: -1 source=upper otherwise 0
rising(src,len).-------------------------ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc(src,len).----------------------------Rate of Change
rsi(src,len).----------------------------Relative strength Index
rvi(src,len).----------------------------The Relative Volatility Index (RVI) is calculated much like the RSI, although it uses high and low price standard deviation instead of the RSI’s method of absolute change in price.
smi_osc(src,len,fast=5, slow=34).--------smi Oscillator
smi_sig(src,len,fast=5, slow=34).--------smi Signal
stc(src,len,fast=23,slow=50).------------Schaff Trend Cycle (STC) detects up and down trends long before the MACD. Code imported from
stdev(src,len).--------------------------Standart deviation
trix(src,len) .--------------------------the rate of change of a triple exponentially smoothed moving average.
tsi(src,len).----------------------------The True Strength Index indicator is a momentum oscillator designed to detect, confirm or visualize the strength of a trend.
ultimateOsc(len.-------------------------Ultimate Oscillator indicator (UO) indicator is a technical analysis tool used to measure momentum across three varying timeframes
variance(src,len).-----------------------ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
willprc(src,len).------------------------Williams %R
wad().-----------------------------------Williams Accumulation/Distribution.
wvad().----------------------------------Williams Variable Accumulation/Distribution.
HISTORY
v3.01
ADD: 23 new indicators added to indicators list from the library. Current Total number of Indicators are 93. (to be continued to adding)
ADD: 2 more Parameters (P1,P2) for indicator calculation added. Par:(Use Defaults) uses only indicator(Source, Length) with library's default parameters. Par:(Use Extra Parameters P1,P2) use indicator(Source,Length,p1,p2) with additional parameters if indicator needs.
ADD: log calculation (simple, log10) option added on indicator function entries
ADD: New Output Signals added for compatibility on exporting condition signals to different Strategy templates.
ADD: Alerts Added according to conditions results
UPD: Indicator source inputs now display with indicators descriptions
UPD: Most off the source code rearranged and some functions moved to the new library. Now system work like a little bit frontend/backend
UPD: Performance improvement made on factorization and other source code
UPD: Input GUI rearranged
UPD: Tooltips corrected
REM: Extended indicators removed
UPD: IND1-IND4 added to indicator data source. Now it is possible to create new indicators with the previously defined indicators value. ex: IND1=ema(close,14) and IND2=rsi(IND1,20) means IND2=rsi(ema(close,14),20)
UPD: Custom Indicator (CUST) added to indicator data source and Combination Indicator source.
UPD: Volume added to indicator data source and Combination Indicator source.
REM: Custom indicators removed and only one custom indicator left
REM: Plot Type "Org. Range (-1,1)" removed
UPD: angle, rising, falling type operators moved to indicator library
在腳本中搜尋"curve"
Indicator Functions with Factor and HeikinAshiHello all,
This indicator returns below selected indicators values with entered parameters.
Also you can add factorization, functions candles, function HeikinAshi and more to the plot.
VERSION:
Version 1: returns series only source and Length with already defined default values
Version 2: returns series with source, Length, p1 and p2 parameters according to the indicator definition (ex: )
PARAMETERS p1 p2
for defining multi arguments (See indicators list) indicator input value usable with verison=V2 selected.. ex: for alma( src , len ,offset=0.85,sigma=6), set source=source, len=length, p1=0.85 an p2=6
FACTOR:
Add double triple, Quadruple factors to selected indicator (like converting EMA to 2-DEMA, 3-TEMA, 4-QEMA...)
1-Original
2-Double
3-Triple
4-Quadruple
LOG
Log: Use log, log10 on function entries
PLOTTING:
PType: Plotting type of the function on the screen
Original :use original values
Org. Range (-1,1): usable for indicators between range -1 and 1
Stochastic: Convert indicator values by using stochastic calculation between -1 & 1. (use AT/% length to better view)
PercentRank: Convert indicator values by using Percent Rank calculation between -1 & 1. (use AT/% length to better view)
ST/%: length for plotting Type for stochastic and Percent Rank options
Smooth: Use SWMA for smoothing the function
DISPLAY TYPES
Plot Candles: Display the selected indicator as candle by implementing values
Plot Ind: Display result of indicator with selected source
HeikinAshi: Display Selected indicator candles with Heikin Ashi calculation
INDICATOR LIST:
hide = 'DONT DISPLAY', //Dont display & calculate the indicator. (For my framework usage)
alma = 'alma( src , len ,offset=0.85,sigma=6)', // Arnaud Legoux Moving Average
ama = 'ama( src , len ,fast=14,slow=100)', //Adjusted Moving Average
acdst = 'accdist()', // Accumulation/distribution index.
cma = 'cma( src , len )', //Corrective Moving average
dema = 'dema( src , len )', // Double EMA (Same as EMA with 2 factor)
ema = 'ema( src , len )', // Exponential Moving Average
gmma = 'gmma( src , len )', //Geometric Mean Moving Average
hghst = 'highest( src , len )', //Highest value for a given number of bars back.
hl2ma = 'hl2ma( src , len )', //higest lowest moving average
hma = 'hma( src , len )', // Hull Moving Average .
lgAdt = 'lagAdapt( src , len ,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter
lgAdV = 'lagAdaptV( src , len ,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter variation
lguer = 'laguerre( src , len )', //Ehler's Laguerre filter
lsrcp = 'lesrcp( src , len )', //lowest exponential esrcpanding moving line
lexp = 'lexp( src , len )', //lowest exponential expanding moving line
linrg = 'linreg( src , len ,loffset=1)', // Linear regression
lowst = 'lowest( src , len )', //Lovest value for a given number of bars back.
pcnl = 'percntl( src , len )', //percentile nearest rank. Calculates percentile using method of Nearest Rank.
pcnli = 'percntli( src , len )', //percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
rema = 'rema( src , len )', //Range EMA (REMA)
rma = 'rma( src , len )', //Moving average used in RSI . It is the exponentially weighted moving average with alpha = 1 / length.
sma = 'sma( src , len )', // Smoothed Moving Average
smma = 'smma( src , len )', // Smoothed Moving Average
supr2 = 'super2( src , len )', //Ehler's super smoother, 2 pole
supr3 = 'super3( src , len )', //Ehler's super smoother, 3 pole
strnd = 'supertrend( src , len ,period=3)', //Supertrend indicator
swma = 'swma( src , len )', //Sine-Weighted Moving Average
tema = 'tema( src , len )', // Triple EMA (Same as EMA with 3 factor)
tma = 'tma( src , len )', //Triangular Moving Average
vida = 'vida( src , len )', // Variable Index Dynamic Average
vwma = 'vwma( src , len )', // Volume Weigted Moving Average
wma = 'wma( src , len )', //Weigted Moving Average
angle = 'angle( src , len )', //angle of the series (Use its Input as another indicator output)
atr = 'atr( src , len )', // average true range . RMA of true range.
bbr = 'bbr( src , len ,mult=1)', // bollinger %%
bbw = 'bbw( src , len ,mult=2)', // Bollinger Bands Width . The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci = 'cci( src , len )', // commodity channel index
cctbb = 'cctbbo( src , len )', // CCT Bollinger Band Oscilator
chng = 'change( src , len )', //Difference between current value and previous, source - source.
cmo = 'cmo( src , len )', // Chande Momentum Oscillator . Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog = 'cog( src , len )', //The cog (center of gravity ) is an indicator based on statistics and the Fibonacci golden ratio.
cpcrv = 'copcurve( src , len )', // Coppock Curve. was originally developed by Edwin "Sedge" Coppock (Barron's Magazine, October 1962).
corrl = 'correl( src , len )', // Correlation coefficient . Describes the degree to which two series tend to deviate from their ta. sma values.
count = 'count( src , len )', //green avg - red avg
dev = 'dev( src , len )', //ta.dev() Measure of difference between the series and it's ta. sma
fall = 'falling( src , len )', //ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
kcr = 'kcr( src , len ,mult=2)', // Keltner Channels Range
kcw = 'kcw( src , len ,mult=2)', //ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
macd = 'macd( src , len )', // macd
mfi = 'mfi( src , len )', // Money Flow Index
nvi = 'nvi()', // Negative Volume Index
obv = 'obv()', // On Balance Volume
pvi = 'pvi()', // Positive Volume Index
pvt = 'pvt()', // Price Volume Trend
rise = 'rising( src , len )', //ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc = 'roc( src , len )', // Rate of Change
rsi = 'rsi( src , len )', // Relative strength Index
smosc = 'smi_osc( src , len ,fast=5, slow=34)', //smi Oscillator
smsig = 'smi_sig( src , len ,fast=5, slow=34)', //smi Signal
stdev = 'stdev( src , len )', //Standart deviation
trix = 'trix( src , len )' , //the rate of change of a triple exponentially smoothed moving average .
tsi = 'tsi( src , len )', //True Strength Index
vari = 'variance( src , len )', //ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta. sma ), and it informally measures how far a set of numbers are spread out from their mean.
wilpc = 'willprc( src , len )', // Williams %R
wad = 'wad()', // Williams Accumulation/Distribution .
wvad = 'wvad()' //Williams Variable Accumulation/Distribution
I will update the indicator list when I will update the library
Thanks to tradingview, @RodrigoKazuma for their open source indicators
lib_Indicators_v2_DTULibrary "lib_Indicators_v2_DTU"
This library functions returns included Moving averages, indicators with factorization, functions candles, function heikinashi and more.
Created it to feed as backend of my indicator/strategy "Indicators & Combinations Framework Advanced v2 " that will be released ASAP.
This is replacement of my previous indicator (lib_indicators_DT)
I will add an indicator example which will use this indicator named as "lib_indicators_v2_DTU example" to help the usage of this library
Additionally library will be updated with more indicators in the future
NOTES:
Indicator functions returns only one series :-(
plotcandle function returns candle series
INDICATOR LIST:
hide = 'DONT DISPLAY', //Dont display & calculate the indicator. (For my framework usage)
alma = 'alma(src,len,offset=0.85,sigma=6)', //Arnaud Legoux Moving Average
ama = 'ama(src,len,fast=14,slow=100)', //Adjusted Moving Average
acdst = 'accdist()', //Accumulation/distribution index.
cma = 'cma(src,len)', //Corrective Moving average
dema = 'dema(src,len)', //Double EMA (Same as EMA with 2 factor)
ema = 'ema(src,len)', //Exponential Moving Average
gmma = 'gmma(src,len)', //Geometric Mean Moving Average
hghst = 'highest(src,len)', //Highest value for a given number of bars back.
hl2ma = 'hl2ma(src,len)', //higest lowest moving average
hma = 'hma(src,len)', //Hull Moving Average.
lgAdt = 'lagAdapt(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter
lgAdV = 'lagAdaptV(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter variation
lguer = 'laguerre(src,len)', //Ehler's Laguerre filter
lsrcp = 'lesrcp(src,len)', //lowest exponential esrcpanding moving line
lexp = 'lexp(src,len)', //lowest exponential expanding moving line
linrg = 'linreg(src,len,loffset=1)', //Linear regression
lowst = 'lowest(src,len)', //Lovest value for a given number of bars back.
pcnl = 'percntl(src,len)', //percentile nearest rank. Calculates percentile using method of Nearest Rank.
pcnli = 'percntli(src,len)', //percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
rema = 'rema(src,len)', //Range EMA (REMA)
rma = 'rma(src,len)', //Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sma = 'sma(src,len)', //Smoothed Moving Average
smma = 'smma(src,len)', //Smoothed Moving Average
supr2 = 'super2(src,len)', //Ehler's super smoother, 2 pole
supr3 = 'super3(src,len)', //Ehler's super smoother, 3 pole
strnd = 'supertrend(src,len,period=3)', //Supertrend indicator
swma = 'swma(src,len)', //Sine-Weighted Moving Average
tema = 'tema(src,len)', //Triple EMA (Same as EMA with 3 factor)
tma = 'tma(src,len)', //Triangular Moving Average
vida = 'vida(src,len)', //Variable Index Dynamic Average
vwma = 'vwma(src,len)', //Volume Weigted Moving Average
wma = 'wma(src,len)', //Weigted Moving Average
angle = 'angle(src,len)', //angle of the series (Use its Input as another indicator output)
atr = 'atr(src,len)', //average true range. RMA of true range.
bbr = 'bbr(src,len,mult=1)', //bollinger %%
bbw = 'bbw(src,len,mult=2)', //Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci = 'cci(src,len)', //commodity channel index
cctbb = 'cctbbo(src,len)', //CCT Bollinger Band Oscilator
chng = 'change(src,len)', //Difference between current value and previous, source - source .
cmo = 'cmo(src,len)', //Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog = 'cog(src,len)', //The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
cpcrv = 'copcurve(src,len)', //Coppock Curve. was originally developed by Edwin "Sedge" Coppock (Barron's Magazine, October 1962).
corrl = 'correl(src,len)', //Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count = 'count(src,len)', //green avg - red avg
dev = 'dev(src,len)', //ta.dev() Measure of difference between the series and it's ta.sma
fall = 'falling(src,len)', //ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
kcr = 'kcr(src,len,mult=2)', //Keltner Channels Range
kcw = 'kcw(src,len,mult=2)', //ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
macd = 'macd(src,len)', //macd
mfi = 'mfi(src,len)', //Money Flow Index
nvi = 'nvi()', //Negative Volume Index
obv = 'obv()', //On Balance Volume
pvi = 'pvi()', //Positive Volume Index
pvt = 'pvt()', //Price Volume Trend
rise = 'rising(src,len)', //ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc = 'roc(src,len)', //Rate of Change
rsi = 'rsi(src,len)', //Relative strength Index
smosc = 'smi_osc(src,len,fast=5, slow=34)', //smi Oscillator
smsig = 'smi_sig(src,len,fast=5, slow=34)', //smi Signal
stdev = 'stdev(src,len)', //Standart deviation
trix = 'trix(src,len)' , //the rate of change of a triple exponentially smoothed moving average.
tsi = 'tsi(src,len)', //True Strength Index
vari = 'variance(src,len)', //ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
wilpc = 'willprc(src,len)', //Williams %R
wad = 'wad()', //Williams Accumulation/Distribution.
wvad = 'wvad()' //Williams Variable Accumulation/Distribution.
}
f_func(string, float, simple, float, float, float, simple) f_func Return selected indicator value with different parameters. New version. Use extra parameters for available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
Returns: float Return calculated indicator value
fn_heikin(float, float, float, float) fn_heikin Return given src data (open, high,low,close) as heikin ashi candle values
Parameters:
float : o_ open value
float : h_ high value
float : l_ low value
float : c_ close value
Returns: float heikin ashi open, high,low,close vlues that will be used with plotcandle
fn_plotFunction(float, string, simple, bool) fn_plotFunction Return input src data with different plotting options
Parameters:
float : src_ indicator src_data or any other series.....
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
Returns: float
fn_funcPlotV2(string, float, simple, float, float, float, simple, string, simple, bool, bool) fn_funcPlotV2 Return selected indicator value with different parameters. New version. Use extra parameters fora available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return calculated indicator value
fn_factor(string, float, simple, float, float, float, simple, simple, string, simple, bool, bool) fn_factor Return selected indicator's factorization with given arguments
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
simple : int fact_ Add double triple, Quatr factor to selected indicator (like converting EMA to 2-DEMA, 3-TEMA, 4-QEMA...)
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return result of the function
fn_plotCandles(string, simple, float, float, float, simple, string, simple, bool, bool, bool) fn_plotCandles Return selected indicator's candle values with different parameters also heikinashi is available
Parameters:
string : FuncType_ indicator from the indicator list
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
bool : plotheikin_ Use Heikin Ashi on Plot
Returns: float
RSI Multi TF strategy
The RSI is a very popular indicator that follows price activity.
It calculates an average of the positive net changes, and an average
of the negative net changes in the most recent bars, and it determines
the ratio between these averages. The result is expressed as a number
between 0 and 100. Commonly it is said that if the RSI has a low value,
for example, 30 or under, the symbol is oversold. And if the RSI has a
high value, 70 for example, the symbol is overbought.
Plots 3 RSI (Weekly, Daily, 4h) at the same time, regardless of the Chart Timeframe.
Highlights in green (or red) if all RSI is oversold (or overbought).
Can trigger custom oversold and overbought alerts when all 3 lines grey(4h), yellow(weekly), and red(daily) go in the oversold or overbought zone. The strongest the curves break the barrier the strongest the alert (vertical red and green bars) shows.
HiLo IndicatorNYSE:SPCE
This is an old and simple concept of mine that I am revisiting. It looks similar to the Vortex Indicator but the formulation is different. I was sick and tired of buying late at the top of the peaks, so I wanted to relate the current price to historic highs and lows (you can change how far you want to go back Time Length = tl). The functions are incredible simple:
lo = close -lowest(close,tl)
hi = highest(close,tl) -close
This generates a weaving pattern that shows bullish (lo>hi) and bearish (lo<hi) zones. WMA's (Fast and Long which can be changed and I have the defaults set kind or high) are used to smooth the functions. Only the long is shown for the "hi" function to keep the plot cleaner. I used crossover points of the "lo" WMA curves to specify places of possible bearish "turn around" points and bullish "entry" points. Alerts can set set for these along with the main crossovers where the plots cross bullish (green) and bearish (red). It seems to be a really good companion to popular buy/sell indicators like the Supertrend.
Hope you like it and let me know if there are any questions.
REAL MARKET RATESBased on near and long term eurodollar yield curve. Attempts to indicate, through a spread median, how major players may position themselves in the near future.
Standard Error of the Estimate -Jon Andersen- V2Original implementation idea of bands by:
Traders issue: Stocks & Commodities V. 14:9 (375-379):
Standard Error Bands by Jon Andersen
Standard Error Bands are quite different than Bollinger's.
First, they are bands constructed around a linear regression curve.
Second, the bands are based on two standard errors above and below this regression line.
The error bands measure the standard error of the estimate around the linear regression line.
Therefore, as a price series follows the course of the regression line the bands will narrow , showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands .
Thanks to the work of @glaz & @XeL_arjona
In this version you can change the type of moving averages and the source of the bands.
Add a few studies of @dgtrd
1- ADX Colored Directional Movement Line
Directional Movement (DMI) (created by J. Welles Wilder ) consists of the Average Directional Index ( ADX ), to define whether or not there is a trend present, and Plus Directional Indicator (+D I) and Minus Directional Indicator (-D I) serve the purpose of determining trend direction
ADX Colored Directional Movement Line is custom interpretation of Directional Movement (DMI) with aim to present all 3 DMI indicator components with SINGLE line and ability to be added on top of the price chart (main chart)
How to interpret :
* triangle shapes:
▲- bullish : diplus >= diminus
▼- bearish : diplus < diminus
* colors:
green - bullish trend : adx >= strongTrend and di+ > di-
red - bearish trend : adx >= strongTrend and di+ < di-
gray - no trend : weekTrend < adx < strongTrend
yellow - week trend : adx < weekTrend
* color density:
darker : adx growing
lighter : adx falling
2- Volatility Colored Price/MA Line
Custom interpretation of the idea “Prices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement”. Further details can be found under study “Price Distance to its MA by DGT”
How to interpret :
-▲ – Bullish , Price Action above Moving Average
-▼ – Bearish , Price Action below Moving Average
-Gray/Black - Low Volatility
-Green/Red – Price Action in Threshold Bands
-Dark Green/Red – Price Action Exceeds Threshold Bands
3- Volume Weighted Bar s
Volume Weighted Bars, a study of Kıvanç Özbilgiç, aims to present whether volume supports price movements. Volume Weighted Bars are calculated based on volume moving average.
How to interpret :
-Volume high above the volume moving average be displayed with red/green colors
-Average volume values will remain as they are and
-Volume low below the volume moving average will be indicated with darker colors
4- Fear & Greed index value, using technical anlysis approach calculated based on :
⮩1 - Price Momentum : Price Distance to its Moving Average
⮩2 - Strenght : Rate of Return, price movement over a period of time
⮩3 - Money Flow : Chaikin Money Flow, quantify changes in buying and selling pressure. CMF calculations is based on Accumulation/Distribution
⮩4 - Market Volatility : CBOE Volatility Index ( VIX ), the Volatility Index, or VIX , is a real-time market index that represents the market's expectation. It provides a measure of market risk and investors' sentiments
⮩5 -Safe Haven Demand: in this study GOLD demand is assumed
M8 BUY @ END OF DAYI've read a couple of times at a couple of different places that most of the move in the market happens after hours, meaning during non-standard trading hours.
After-market and pre-market hours and have seen data presented showing that systems which bought just before end normal market hours and sold the next morning had really amazing resutls.
But when testing those I found the results to be quite poor compared to the pretty graphs I saw, and after much tweaking and trying different ideas I gave up on the idea until I recently decided to try a new position management system.
The System
Buys at the end of the trading day before the close
Sells the next morning at the open IF THE CLOSE OF THE CURRENT BAR IS HIGHER THAN THE ENTRY PRICE
When the current price is not higher, the system will keep the position open until it EITHER gets stops out or closes on profit <<< this is WHY it has the high win %
The system has a high win ratio because it will keep that one position open until it either reaches profit or stops out
This "system" of waiting, and keeping the trade open, actually turned out to be a fantastic way to kind of put the complete trading strategy in a kind of limbo mode. It either waits for market failure or for a profit.
I don't really care about win % at all, almost always high win % ratio systems are just nonsense. What I look for is a PF -- profit factor of 1.5 or above, and a relatively smooth equity curve. -- This has both.
The Stop Loss setting is set @ .95, meaning a 5% stop loss. The Red Line on the chart is the stop loss line.
There is no set profit target -- it simply takes what the market gives.
Non-Repainting System
This does use a 200D Simple Moving Average as a filter. Like a Green Light / Red Light traffic light, the system will only trade long when the price is above its 200 Moving average.
Here is the code: "F1 = close > sma(security(syminfo.tickerid, "D", close ), MarketFilterLen) // HIGH OF OLD DATA -- SO NO REPAINTING"
I use "close ", so that's data from two days ago, it's fixed, confirmed, non-repainting data from the higher timeframe.
-- I would only suggest using this on direction tickers like SPY, QQQ, SSO, TQQQ, market sectors with additional filters in place.
Six Moving Averages Study (use as a manual strategy indicator)I made this based on a really interesting conversation I had with a good friend of mine who ran a long/short hedge fund for seven years and worked at a major hedge fund as a manager for 20 years before that. This is an unconventional approach and I would not recommend it for bots, but it has worked unbelievably well for me over the last few weeks in a mixed market.
The first thing to know is that this indicator is supposed to work on a one minute chart and not a one hour, but TradingView will not allow 1m indicators to be published so we have to work around that a little bit. This is an ultra fast day trading strategy so be prepared for a wild ride if you use it on crypto like I do! Make sure you use it on a one minute chart.
The idea here is that you get six SMA curves which are:
1m 50 period
1m 100 period
1m 200 period
5m 50 period
5m 100 period
5m 200 period
The 1m 50 period is a little thicker because it's the most important MA in this algo. As price golden crosses each line it becomes a stronger buy signal, with added weight on the 1m 50 period MA. If price crosses all six I consider it a strong buy signal though your mileage may vary.
*** NOTE *** The screenshot is from a 1h chart which again, is not the correct way to use this. PLEASE don't use it on a one hour chart.
{Gunzo} Trend Sniper (WMA with coefficient)Trend Sniper is a trend-following indicator that sticks closer to the trend than others moving averages as it is using an upgraded weighted moving average implementation.
OVERVIEW :
It is typical to use a moving average indicator (SMA, EMA, WMA or TMA) to identify the trend of an asset. Standard moving averages indicators smooth the price and doesn’t stick very closely to the actual price, showing potential lagging information.
CALCULATION :
In order to have a trendline that sticks to the price, we are going to use a weighted moving average as it puts more weight on recent candles and less on past candles. The weight is usually calculated using the distance from current candle to the other candles used in the calculation. We have the following formula for the standard calculation as implemented in TradingView :
WMA_standard = (Price1 * Weight1 + …… + PriceN * WeightN)) / (Weight1 + …… + WeightN)
This “Trend Sniper” indicator uses an additional coefficient to alter even more the weight of each candle.
WMA_with_coefficient = (Price1 * (Weight1 - Coefficient) + …… + PriceN * (WeightN - Coefficient)) / ((Weight1 - Coefficient) + …… + (WeightN - Coefficient))
SETTINGS :
MA source : Source used for moving average calculation (ex : “close”)
MA length : Length of the moving average. Higher values will give a smoother line, lower values will give a more reactive line.
Use extra smoothing : Enable/disable usage of a EMA to extra smooth the line curve. If activated the indicator may be lagging, but it will also avoid many false buy/sell signals.
MA extra smoothing length : Length of the moving average of the extra smoothing.
Change candle colors : Enable/disable painting the candles of the chart with the colors of the weighted moving average.
Display buy/sell signals : Display buy/sell signals (circles) when the moving average is changing direction
VISUALIZATIONS :
This indicator has 3 possible visualizations :
Moving Average line : the line represents the weighted moving average that is following the price of the asset, when the line goes up we are in a uptrend (green line) when the line goes down we are in a downtrend (red line).
Candle coloring : the color of the moving average line can be applied to the candles of the chart for better readability.
Signals : Buy/Sell signals can be displayed at the bottom of the chart
USAGE :
This indicator can help analyze the trend directional changes :
First of all, if the moving average line is under the price (or above the price), then we can assume that the uptrend is strong (or downtrend is strong).
If the current candle crosses the moving average line, it is the first sign that the trend is weakening and possibly starting to revert.
If the weighted moving average is changing direction, then the trend change is confirmed and the color of the line changes
Market Maker BalanceWhere is the market maker in his cycle of building longs or shorts? When is that big drop or big pump coming?
This is a simple and unexpectedly powerful indicator that shows you an estimate of the market maker's position over the last 200 candles. It works on any timeframe.
How does it work?
It combines a simple 10-candle Price Volume Support Resistance Analysis metric of climactic and rising volume. That volume is combined to create a bullish and bearish balance over a period of 200 candles. The curves are smoothed out with a 10 period EMA.
The MMB (Marker Maker Balance) oscillator is the resulting bearish volume - bullish volume, which shows us THEIR position balance.
Indications:
when shorts are increasing (further below 0), we are in a bullish trend -- you should be taking profit on longs
when shorts are flat or decreasing, the trend is due for a reversal -- you should be closing longs and looking to short
when shorts cross 0 to long, the trend is reversing down -- you should be in a short position by now
when longs are increasing, we are in a bearish trend -- you should be taking profits on your shorts
when longs are flat or decreasing, the trend is due for a reversal -- you should be closing your shorts
For extra information, there are also the separate lines for rising and climactic volume to give you early indications of reversal or change in Market Maker behaviour. You can disable them in the Style settings, but they can be a useful early indicator that the current trend is losing strength when rising volume overtakes climax volume (MM's no longer moving out of zones higher/lower).
Ways to use this indicator are quite simple and eerily accurate:
for short term gains, do the opposite of MMs: long when MM are opening more shorts, short when they are opening more longs
for huge positions, mimic the MM position: build long positions / close shorts when MMB is rising, build shorts / close longs when MMB is falling or crosses above 0 (be careful with leverage, begin on 1x leverage)
Note: the results of this indicator will be different for each exchange, because of their different trading volumes per candle. It's advisable to use it for the exchange you're trading on or use a chart that averages all exchanges for that asset, like INDEX:BTCUSD.
For those of you who use the Backtesting & Trading Engine by PineCoders, the BTE Signal plot generates long and short entries as well as filter states. Use this plot as the source for BTE.
Shout out to @infernixx for PVSRA calculations in his awesome Traders Reality indicator, the code of which I shamelessly ripped off and edited for this indicator.
Leave comments below if you want something added.
Ethereum Logarithmic Growth Curves & ZonesThis script was modified to fit ethereum logarithmic pricing action.
LV Cop&RMA w HeikinA buy signal is generated when the indicator turns upwards from previous indicator level.
A sell signal is generated when the indicator turns downwards from previous indicator level.
The indicator is trend-following, and based on averages, so by its nature it doesn't pick a bottom, but rather shows when a rally has started.
It is designed for daily period use.
Frequent buy/sell signals can occur on low and high levels.
It is designed with the mentality of Coppock curve. Rma is used instead of Wma and Heikin-Ashi closing price is used instead of standard closing price.
Moving Regression Prediction BandsIntroducing the Moving Regression Prediction Bands indicator.
Here I aimed to combine the principles of traditional band indicators (such as Bollinger Bands), regression channel and outlier detection methods. Its upper and lower bands define an interval in which the current price was expected to fall with a prescribed probability, as predicted by the previous-step result of the local polynomial regression (for the original Moving Regression script, see link below).
Algorithm
1. At every time step, the script performs local polynomial regression of the sample data within the lookback window specified by the Length input parameter.
2. The fitted polynomial is used to construct the Moving Regression time series as well as to extrapolate data, that is, to predict the next data point ( MRPrediction ).
3. The accuracy of local interpolation is estimated by means of the root-mean-square error ( RMSE ), that is, the deviation between the fitted polynomial and the observed values.
4. The MRPrediction and RMSE values calculated for the previous bar are then used to build the upper and lower bands , which I define as follows:
Upper Band = MRPrediction_prev + Multiplier *( RMSE_prev )
Lower Band = MRPrediction_prev - Multiplier *( RMSE_prev )
Here the Multiplier is a user-defined parameter that should be interpreted as a quantile in the standard normal distribution (the default value of 2.0 roughly corresponds to the 95% prediction interval).
To visualize the central line , the script offers the following options:
Previous-Period MR Prediction: MRPrediction_prev time series from the above equation.
MR: Conventional Moving Regression time series.
Ribbon: “Previous-Period MR Prediction” and “MR” curves plotted together and colored according to their relative value (green if MR > Previous MR Prediction; red otherwise).
Usage
My original idea was to use the band breakouts as potential trading signals. For example, the price crossing above the upper band is a bullish signal , being a potential sign that price is gaining momentum and is out of a previously predicted trend. The exit signal could be the crossing under the lower band or under the central line.
However, be aware that it is an experimental indicator, so you might fin some better strategies.
Feel free to play around!
[blackcat] L2 Ehlers RSI with NETLevel: 2
Background
John F. Ehlers introuced RSI with Noise Elimination Technology (NET) in Dec, 2020.
Function
Many indicators produce more or less noisy output, resulting in false or delayed signals. Dr. Ehlers proposed “Noise Elimination Technology,” in Dec, 2020. He introduces using a Kendall correlation to reduce indicator noise and provide better clarification of the indicator direction. This approach attempts to reduce noise without using smoothing filters, which tend to introduce indicator lag and therefore, delayed decisions. With this script, I use his “MyRSI” indicator, which he introduced in his May 2018 article in S&C, by adding some Tradingview pine v4 code for the noise elimination technology. The indicator plots the MyRSI value as well as the value after applying NET to MyRSI. This de-noising technology uses the Kendall correlation of the indicator with a rising slope. Compared with a lowpass filter, this method does not delay the signals.
The technology appears to work well in this example for removing the noise. But note that the NET function is not meant as a replacement of a lowpass or smoothing filter; its output is always in the -1 to +1 range, so it can be used for de-noising oscillators, but not, for instance, to generate a smoothed version of the price curve.
Key Signal
NET --> Ehlers RSI with NET fast line
Trigger --> Ehlers RSI with NET slow line
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 99th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Trend ChannelMarket engineers can use channels to find out when a market has entered an undervalued or overvalued zone. Purchases and sales take place in these zones. Professionals use trending channels to find out when the market has overtaken itself and where it is likely to reverse.
Upper channel line = EMA + EMA x channel coefficient
Lower channel line = EMA - EMA x channel coefficient
The topline reflects the bulls' strength in raising prices above the average value consensus. This line marks the normal limit of optimism in the market.
The bottom line of the channel reflects the strength of the bears pushing prices below the average consensus of values. This line marks the normal limit of pessimism in the market.
The coefficient is used to correct the distance to the moving average until the channel contains 95% of all prices. Only the tips and the lowest bottoms are allowed to protrude. For these peaks and curves and sideways trends, I have added two more switchable lines to the border lines, with a distance of 23.6% (light blue).
The larger the time frame, the wider the channel.
If you buy near a rising moving average, you take profits near the upper line of the channel.
If you are short near a falling moving average, you should close out near the bottom of the channel.
If the moving average is essentially flat, then you should be long on the bottom of the channel and short on the top of the channel. You realize profits when the prices have returned to their moving average to normal.
Interesting for day traders:
Adjust the moving average so that it has the same slope as the quotes on the hourly chart. With the coefficient you set the distance between the border lines. Perhaps adding the 23.6% lines will help, where the sideways trends are starting. Set the resolution to "1 hour". If you want to trade with these settings in short time units, e.g. in the 3 minute chart or in the 1 minute chart, then you now have target marks and indications in which direction the prices will possibly move when the prices have reached the moving average or one of the border lines.
The text contains excerpts from "Come into my Trading Room" by Dr. Alexander Elder.
The indicator has an additional exponential moving average with adjustable period, adjustable shift and adjustable source for the narrow range of quotations and final determination of direction.
The chart shows how the trend channel and the Fibonacc trading indicator can complement each other.
The text contains excerpts from "Come into my Trading Room" by Dr. Alexander Elder.
Markttechniker können Kanäle verwenden um heraus zu finden, wann ein Markt eine unterbewertete oder überbewertete Zone erreicht hat. An diesen Zonen finden Käufe und Verkäufe statt. Profis benutzen Trendkanäle um herauszufinden, wann der Markt sich selbst überholt hat und wo er wahrscheinlich eine Umkehrbewegung vollziehen wird.
Obere Kanallinie = EMA + EMA x Kanalkoeffizient
Untere Kanallinie = EMA - EMA x Kanalkoeffizient
Die Oberlinie reflektiert die Kraft der Bullen, mit der sie die Kurse über den durchschnittlichen Wertekonsens anheben. Diese Linie kennzeichnet die normale Grenze des Optimismus im Markt.
Die untere Linie des Kanals reflektiert die Kraft der Bären, mit der sie die Kurse unter den durchschnittlichen Wertekonsens drücken. Diese Linie kennzeichnet die normale Grenze des Pessimismus im Markt.
Mit dem Koeffizienten wird der Abstand zum gleitenden Durchschnitt so lange korrigiert, bis der Kanal 95% aller Kurse enthält. Lediglich die Spitzen und die niedrigsten Böden dürfen herausragen. Für diese Spitzen und Bögen und Seitwärtstrends habe ich zu den Grenzlinien zwei weitere zuschaltbare Linien, mit einem Abstand von 23,6%, hinzugefügt (hellblau).
Je größer der Zeitrahmen ist, um so breiter ist der Kanal.
Wenn Sie in der Nähe eines ansteigenden gleitenden Durchschnitts kaufen, nehmen Sie die Gewinne in der Nähe der oberen Grenzlinie des Kanals mit.
Wenn Sie in der Nähe eines fallenden gleitenden Durchschnitts leerverkaufen, sollten Sie in der Nähe der unteren Grenzlinie des Kanals glattstellen.
Wenn der gleitende Durchschnitt im Wesentlichen flach ist, dann sollten Sie an der unteren Kanalbegrenzung eine Long-Position und an der oberen Kanalbegrenzung eine Short-Position einnehmen. Gewinne realisieren Sie jeweils, wenn die Kurse zu ihrem gleitenden Durchschnitt, zur Normalität zurückgekehrt sind.
Für Daytrader interessant:
Stellen Sie den gleitenden Durchschnitt so ein, dass er die gleiche Steigung wie die Notierungen im Stunden-Chart hat. Mit dem Koeffizienten Stellen Sie den Abstand der Grenzlinien ein. Vielleicht hilft die Zuschaltung der 23,6%-Linien, wo die Seitwärtstrends anstoßen. Stellen Sie die Auflösung auf „1 Stunde“. Wenn Sie mit diesen Einstellungen in niedrigen Zeiteinheiten traden wollen, z.B. im 3 Minuten-Chart oder im 1 Minuten-Chart, dann haben Sie jetzt Zielmarken und Hinweise in welche Richtung die Notierungen möglicherweise laufen werden, wenn die Notierungen den gleitenden Durchschnitt oder eine der Grenzlinien erreicht haben.
Der Text enthält Auszüge aus „Come into my Trading Room“ von Dr. Alexander Elder.
Der Indikator besitzt zur engen Umfang der Notierungen und endgültigen Richtungsbestimmung einen zusätzlichen exponentiellen gleitenden Durchschnitt mit einstellbarer Periode, einstellbarer Verschiebung und einstellbarer Quelle.
Der Chart zeigt wie sich Trendkanal und Fibonacc-Trading-Indikator ergänzen könne.
Der Text enthält Auszüge aus „Come into my Trading Room“ von Dr . Alexander Elder.
Combo Backtest 123 Reversal & Kase Dev Stops This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The Kase Dev Stops system finds the optimal statistical balance between letting profits run,
while cutting losses. Kase DevStop seeks an ideal stop level by accounting for volatility (risk),
the variance in volatility (the change in volatility from bar to bar), and volatility skew
(the propensity for volatility to occasionally spike incorrectly).
Kase Dev Stops are set at points at which there is an increasing probability of reversal against
the trend being statistically significant based on the log normal shape of the range curve.
Setting stops will help you take as much risk as necessary to stay in a good position, but not more.
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
WARNING:
- For purpose educate only
- This script to change bars colors.
Cycle Swing MomentumAdaptive Ultra-Smooth Momentum indicator
The Cycle-Swing-Indicator "CSI" provides an optimized "momentum" oscillator based on the current dominant cycle by looking at the swing of the dominant cycle instead of the raw source momentum. Offering the following improvements:
Smoothness
Zero delay
Sharpness at turning points
Robust and adaptable to market conditions
Accurate deviation detection
The following common problems with standard indicators are solved by this indicator:
First, normal indicators introduce a lot of false signals due to their noisy signal line. Second, to compensate for the noise, one would normally try to add some smoothing. But this only results in adding more delay to the indicator, which makes it almost useless. Third, standard indicators require a length adjustment to derive reliable signals. However, you never know how to set the right length.
All three problems described above are solved by the developed adaptive cyclic algorithm.
The above chart shows current Bitcoin 4h data from the last days as of writing with the proposed signal reading for this indicator. The standard momentum indicator is included for comparison.
HOW TO USE
The indicator works without any parameter and can be applied to any chart and any time-frame. It will adapt automatically to the Dominant Cycle and use the dominant cycle of the source data to derive the ultra smooth momentum curve. Adaptive upper/lower bands are included and highlight areas with extreme readings. Automatic divergence detection can be turned off/on.
HOW TO READ
The indicator can be used like any oscillator. In addition, it provides adaptive high and low bands.
* Look for turns above the upper/lower bands
* Look for divergences between source and signals line
Further reading/Original source:
The indicator uses the dominant cycle to optimize signal, smoothing and cyclic memory. To get more in-depth information on the Cycle Swing Indicator, please read Chapter 10 "Cycle Swing Indicator: Trading the swing of the dominant cycle" of the book "Decoding the Hidden Market Rhythm, Part 1" available at your favorite book store.
Related ideas:
Please also check the cyclic RSI indicator which also uses cyclic information to improve the signal.
Square Root Moving AverageAbstract
This script computes moving averages which the weighting of the recent quarter takes up about a half weight.
This script also provides their upper bands and lower bands.
You can apply moving average or band strategies with this script.
Introduction
Moving average is a popular indicator which can eliminate market noise and observe trend.
There are several moving average related strategies used by many traders.
The first one is trade when the price is far from moving average.
To measure if the price is far from moving average, traders may need a lower band and an upper band.
Bollinger bands use standard derivation and Keltner channels use average true range.
In up trend, moving average and lower band can be support.
In ranging market, lower band can be support and upper band can be resistance.
In down trend, moving average and upper band can be resistance.
An another group of moving average strategy is comparing short term moving average and long term moving average.
Moving average cross, Awesome oscillators and MACD belong to this group.
The period and weightings of moving averages are also topics.
Period, as known as length, means how many days are computed by moving averages.
Weighting means how much weight the price of a day takes up in moving averages.
For simple moving averages, the weightings of each day are equal.
For most of non-simple moving averages, the weightings of more recent days are higher than the weightings of less recent days.
Many trading courses say the concept of trading strategies is more important than the settings of moving averages.
However, we can observe some characteristics of price movement to design the weightings of moving averages and make them more meaningful.
In this research, we use the observation that when there are no significant events, when the time frame becomes 4 times, the average true range becomes about 2 times.
For example, the average true range in 4-hour chart is about 2 times of the average true range in 1-hour chart; the average true range in 1-hour chart is about 2 times of the average true range in 15-minute chart.
Therefore, the goal of design is making the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
For example, for the 24-day moving average, the weighting of the most recent 6 days is close to the weighting of the rest 18 days.
Computing the weighting
The formula of moving average is
sum ( price of day n * weighting of day n ) / sum ( weighting of day n )
Day 1 is the most recent day and day k+1 is the day before day k.
For more convenient explanation, we don't expect sum ( weighting of day n ) is equal to 1.
To make the weighting of the most recent quarter is close to the weighting of the rest recent three quarters, we have
sum ( weighting of day 4n ) = 2 * sum ( weighting of day n )
If when weighting of day 1 is 1, we have
sum ( weighting of day n ) = sqrt ( n )
weighting of day n = sqrt ( n ) - sqrt ( n-1 )
weighting of day 2 ≒ 1.414 - 1.000 = 0.414
weighting of day 3 ≒ 1.732 - 1.414 = 0.318
weighting of day 4 ≒ 2.000 - 1.732 = 0.268
If we follow this formula, the weighting of day 1 is too strong and the moving average may be not stable.
To reduce the weighting of day 1 and keep the spirit of the formula, we can add a parameter (we call it as x_1w2b).
The formula becomes
weighting of day n = sqrt ( n+x_1w2b ) - sqrt ( n-1+x_1w2b )
if x_1w2b is 0.25, then we have
weighting of day 1 = sqrt(1.25) - sqrt(0.25) ≒ 1.1 - 0.5 = 0.6
weighting of day 2 = sqrt(2.25) - sqrt(1.25) ≒ 1.5 - 1.1 = 0.4
weighting of day 3 = sqrt(3.25) - sqrt(2.25) ≒ 1.8 - 1.5 = 0.3
weighting of day 4 = sqrt(4.25) - sqrt(3.25) ≒ 2.06 - 1.8 = 0.26
weighting of day 5 = sqrt(5.25) - sqrt(4.25) ≒ 2.3 - 2.06 = 0.24
weighting of day 6 = sqrt(6.25) - sqrt(5.25) ≒ 2.5 - 2.3 = 0.2
weighting of day 7 = sqrt(7.25) - sqrt(6.25) ≒ 2.7 - 2.5 = 0.2
What you see and can adjust in this script
This script plots three moving averages described above.
The short term one is default magenta, 6 days and 1 atr.
The middle term one is default yellow, 24 days and 2 atr.
The long term one is default green, 96 days and 4 atr.
I arrange the short term 6 days to make it close to sma(5).
The other twos are arranged according to 4x length and 2x atr.
There are 9 curves plotted by this script. I made the lower bands and the upper bands less clear than moving averages so it is less possible misrecognizing lower or upper bands as moving averages.
x_src : how to compute the reference price of a day, using 1 to 4 of open, high, low and close.
len : how many days are computed by moving averages
atr : how many days are computed by average true range
multi : the distance from the moving average to the lower band and the distance from the moving average to the lower band are equal to multi * average true range.
x_1w2b : adjust this number to avoid the weighting of day 1 from being too strong.
Conclusion
There are moving averages which the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
We can apply strategies based on moving averages. Like most of indicators, oversold does not always means it is an opportunity to buy.
If the short term lower band is close to the middle term moving average or the middle term lower band is close to the long term moving average, it may be potential support value.
References
Computing FIR Filters Using Arrays
How to trade with moving averages : the eight trading signals concluded by Granville
How to trade with Bollinger bands
How to trade with double Bollinger bands
Bitcoin M2 supply adjusted priceThis script plots bitcoin candles adjusted by M2 supply (blue line), helping the trader to obtain insight of new support/resistance levels adjusted by M2 supply.
Note: As it was not possible to make the price adjust automatically by the last M2 value (pinescript limitation, I guess), the input parameter "M2Last" must be updated manually observing the last M2 value in blue curve.
Future Value: Compound Interest with Regular Deposits [racer8]This isn't no ordinary FV equation, this one takes into account regular deposits. I had to derive this equation myself.
This calculator calculates future value based on the following inputs:
- Present value
- Yearly return
- Yearly deposit
- years
Application: Can be used to determine you're future value of your equity curve.
C = c*m^n + a*m*{(m^(n-1)-1)/(m-1)}
C = Future value
c = present value
m = yearly return multiplier
n = years
a = yearly deposit amount
Enjoy :)
Ichimoku Cloud using Tilson T3 SmoothingThe standard Ichimoku Cloud is derived from Donchian Channels and is based on the range of the data set. However the channels are choppy and may not always be easy to read. By using moving averages, similar leading spans can be generated with a smoother outline. The T3 averages further smooths out the curve.
BTC Contango IndexInspired by a Twitter post by Byzantine General:
This is a script that shows the contango between spot and futures prices of Bitcoin to identify overbought and oversold conditions. Contango and backwardation are terms used to define the structure of the forward curve. When a market is in contango, the forward price of a futures contract is higher than the spot price. Conversely, when a market is in backwardation, the forward price of the futures contract is lower than the spot price.
The aggregate prices on top exchanges are taken and then averaged to obtain a Spot Average and a Futures Average. The script then plots (Futures Average/Spot Average) - 1 to illustrate the percent difference (contango) between spot and futures prices of Bitcoin.
When in contango, Bitcoin may be overbought.
When in backwardation, Bitcoin may be oversold.
