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
在脚本中搜索"GOLD"
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
ADX Heatmap & Di's + Fib Referencial by [JohnnySnow]For quicker and easier interpretation, ADX line is displayed in a heatmap style. The more absolute difference between both DIs, the more intense the color.
Because some people use 20 ADX reference and others use 25 ADX reference to confirm the trend, I just add both as reference lines in a 'golden box'
Additionally, reference lines were added with default values set to Fib levels
RedK Auto-Stepping Ladder TraderThe RedK Auto-Stepping Ladder Trader is an experimental tool to help identify trade entry and exits for various types of trades (Trend / Momentum / Breakout and Swing trades)
The underlying concept here is loosely similar to the SMAC script - in case you'd like to read some of the "script-specific" write-up . I even borrowed some of the SMAC code, but upgraded the script to Pine v5 while working. So i won't repeat write-up here on how the script works - and we'll get right into how to use in trading
How to use / trade the Ladder Trader:
-------------------------------------------------
The idea is to set the auto-stepping ladder to a higher timeframe, the "ladder view" helps simplify the price action to show a clear direction, then use the lower timeframe to find best entries (close or at the ladder line) and exits (on the ATR as TP target)
- Entries should be as close to the ladder line as possible - a trader may decide to have a small margin above or below the ladder line where they set entry limit order
- note that when stepping is enabled, the auto-stepping algo will choose the step value based on the underlying price range and the selected timeframe to move with common trader "mental values" where traders will usually gravitate
- exits can be set using the optional ATR or Pct channels - by default, there's an ATR channel (golden color) for that purpose
Possible usage scenarios of the Ladder Trader:
--------------------------------------------------------------
- Trend / long(er) term: enter position once the ladder line switches to the color corresponding to my desired direction (example: blue for long), and hold all the way until the color changes
- Swing: Take only trades in the direction of the ladder (long with blue, short with orange) - enter at the ladder line value, set TP at the desired ATR, repeat as long as the direction holds
- Feel free to experiment and share back other uses you find. There are so many settings and tweaks provided for flexibility - the downside is this adds a certain level of complexity - however, i hope this will be a valuable tool to add to your trading.
Few Notes:
-----------------------
- The Auto-stepping algo is a bit improved to be more FOREX and Crypto-friendly - i do not trade these instruments myself, but will continue to improve the auto-stepping technique in upcoming updates
- the signal line (hidden by default, and is what causes the ladder to change color) is based on my Compound Ratio Moving Average - since it's the moving average i found to provide best combination of speed and smoothness. It is used as a proxy to the price, to signal when the price is above or below the ladder level - while removing some of the whipsaws if we use the price value directly.
- Broader analysis of price action should still be made using other indicators - and possibly other chart setups - we shouldn't rely on the Ladder Trader signal only - Check for overall momentum, volume movement and market sentiment before using the Ladder Trader
- Also test your settings in PaperMoney - i noticed that different instruments may need different settings (for Ladder Type, Length, Rounding Technique, ATR multiplier..etc) for optimal setup that shows best signals.. Get very familiar with the Ladder Trader and it should hopefully become more helpful to you as a tradiing tool.
Comments and Feedback are welcome. Good luck.
NVTNetwork Value to Transactions Ratio (NVT) is defined as the ratio of market capitalization divided by transacted volume.
NVT Ratio can be thought of as an indicator that measures whether the blockchain network is overvalued or not.
If it is upper than red line, it means overvalued.
NVT Golden Cross targets to generate short or long signals by comparing the short-term trend of NVT and the long-term trend of NVT. If the short-term trend is way greater than the long-term trend is, the network can be interpreted as overpriced and will soon revert to mean value, meaning short signal. Similarly, the opposite case may imply a long signal.
Over the red line is short signal and under the green line is long signal.
You can find divergence in this indicator.
There are two sources
cryptocap
glassnode
SEMA-XSEMA-X (sema cross)
It's a simple EMA cross strategy
Rules of strategy
1. 2 EMA crossing
2. Long (Golden Cross), Short (Dead Cross)
3. Target profit, stop loss setting
You can also get big trend gains if you set a long target price.
* * *
SEMA-X (세마크로스)
간단한 EMA 교차 전략 입니다.
전략의 규칙
1. 2개의 EMA 교차
2. 매수(골든 크로스), 매도(데드 크로스)
3. 목표가, 손절가 설정
목표가를 길게 설정하면 큰 추세 이익도 얻을 수 있습니다.
Fibonacci Toolkit [LuxAlgo]This toolkit aims to display multiple Fibonacci drawing tools including retracements, arcs, circles, fans, timezones and spirals.
Usage
Upon adding the indicator to the chart, users will be prompted to choose a starting point and an ending point for the calculation of the drawing tools.
Users can then navigate to the settings of the toolkit and choose which drawing tool to display using the Fibonacci drop-down menu. Users are also free to change the default Fibonacci ratios used by the indicator from within the settings. Each tool is described below.
Retracements
Fibonacci retracements display multiple levels constructed using the starting price point, ending price point, and multiple Fibonacci ratios. These levels can be used as support and resistance.
Arcs
Fibonacci arcs display multiple semi-circles. Each semi-circle crosses the line connecting the starting & end price point at a certain percentage determined by Fibonacci ratios. These arcs can be used as support and resistance.
Circles
The Fibonacci circles are similar to the Fibonacci arcs but display a full circle instead. Users can expect the price to bounce off of the circles.
This tool is less commonly used by traders.
Fan
A Fibonacci fan is a tool displaying trendlines all connected to a starting point and extending to a point determined by Fibonacci ratios. These can also be used as support and resistance.
Timezone
Fibonacci timezones return a series of horizontal lines. The distance of the lines increases by a factor given by the numbers in the Fibonacci sequence.
This tool can be useful to highlight points where a trend might reverse assuming that their duration increases over time.
Spiral
The Fibonnaci spiral displays a spiral that grows by a factor given by the golden ratio. This indicator returns a spiral using 7 turns (5 internal) and sets the origin of the spiral to the ending point which is selected by the user. The height of the spiral is based on the price range between the starting point and ending point.
Note that potential display artifacts can be seen when fitting the spiral on stocks and forex pairs.
Scalping Trading System bot Crypto and StocksThis is a trend trading strategy scalping bot that can work with any type of market. However I concluded my tests so far with Crypto, Stocks and Forex, and with optimizations always could be found some profitable settings.
Indicators
SImple Moving Average
Exponential Moving Average
Keltner Channels
MACD Histogram
Stochastics
Rules for entry
long= Close of the candle bigger than both moving averages and close of the candle is between the top and bot levels from Keltner. At the same time the macd histogram is negative and stochastic is below 50.
short= Close of the candle smaller than both moving averages and close of the candle is between the top and bot levels from Keltner. At the same time the macd histogram is positive and stochastic is above 50.
Rules for exit
We exit when we meet an opposite reverse order.
This strategy has no risk management inside, so use it with caution !
MMRIIndicator as described by Greg Mannarino
Greg describes an indicator that takes the Dollar Index multiplied by the US 10 Yield divided by the Golden Ratio. Greg further describes overall levels of market risk and and transitional points for 'risk on' assets
Auto Anchored Volume Weighted Average Price - Custom AVWAP
Based on Brian Shannon's AVWAP - This indicator anchors vwap to the highest high, lowest low and highest volume bar of a user defined lookback period.
In the chart example above on AVAX, the lookback period is set to 90 days
- The blue line depicts AVWAP from the highest bar in in the last 90 dats
- The purple Line is AVWAP from the lowest bar in the last 90 days
- The golden line is AVWAP from the highest volume bar in the last 90 Days
These levels act as a price magnet and strong levels of support and resistance. I use them to identify chart locations for where I want to do business and look for trade setups.
Unlike moving averages, AVWAP will maintain it's chart position no matter the chart resolution. One way to take advantage of this is to wait for price to get to one of these levels, go to lower timeframes and find low risk setups based on your trading strategy.
You can customise the look and feel and which anchors you want displayed. You can use multiple instances with varying lookback periods to display shorter and longer term levels simultaneously
Times and Gold Zonethis indicator is to see all the time sessions but you have another session that you can change the hour to only see the best volatility of the pair you want
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
EMA Magnetic PullColor coded indicator showing the "Magnetic Pull" of a specifed Moving Average. Indicator changes color based on how high price has exceeded the specified moving average. The default moving average is set to 50, but users can define their desired moving average.
Bitcoin Weekly Chart Example:
Gold or White may indicate that an asset is overbought suggesting a trend reversal or corrective pullback in price
Light Blue may indicate that an asset is oversold, suggesting an undervalued condition
[blackcat] L1 Tether LineLevel: 1
Background
Omega Research proposed Tether line in June 2000. I utilized it in fast-slow line form to follow trend.
Function
Due it can provides good support and resistance, using it as "moving average" fast-slow line form can provide very stable golden cross and dead cross signal.
You can adjust parameters to fit for your trading pair and use it and compare it with Supertrend indicator.
Key Signal
Tether_fast --> Tether Fast Line.
Tether_slow --> Tether Slow Line.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
Sideways detection bollinger bandsSideways detection indicator using Bollinger bands .
In this case we take the original ratio between lower and upper and we smooth it even harder in order to get a better idea about the accuracy of the trend.
If the initial ratio is not between 0 and 1 and the smooth ratio is higher than our selected value, we get an idea if we are a in trending market or not.
Of course using it as a standalone has no usage, and it has to be combined with other tools like moving average, oscillators and so on.
IF you have any questions let me know
[blackcat] L1 Joe Sharp More Responsive Moving Average (MMA)Level: 1
Background
Joe Sharp propsed a "More Responsive Moving Averages (MMA)" in Jan, 2000. He describes a modified moving average that greatly diminishes the lag that is typically associated with moving averages. With the formula described in the article, the moving average line is more responsive to changes in the price action.
Function
An MMA indicator to plot the modified moving average is created in this script for application on a chart with fastline and slowline to produce golden crosses and dead crosses. In the pine script below, the calculation for the modified moving average is created in a function called ModifiedMA. This function basically takes care of all the necessary calculations for the modified moving average line. By putting the entire calculation into a function, the modified moving average calculation can be easily referenced by any analysis technique.
Key Signal
ModifiedMA (Price, FastLength) --> ModifiedMA Fast Line.
ModifiedMA (Price, SlowLength) --> ModifiedMA Slow Line.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.















