BlackCompositIndicator4OverlayThis is not new indicator.
// Candle Patterns Indicator created by Robert N. 030715
// Volume Indicator @author LazyBear
// Updated and translated by Blyayshman
Это не новый индикатор - это компиляция нескольких для удобства одновременного отображения и экономии разрешенных индикаторов.
Эта версия для отображения на главном экране, вместе с графиком.
Можно отобразить до 4-х MA, 2-х EMA и анализатор паттернов японских свечей.
Пожелания и предложения приветствуются.
Cari dalam skrip untuk "bollingerband"
Bollinger Awesome Alert R1 by JustUncleLThis indicator is an implementation of the Bollinger Band and Awesome Oscillator Scalping system.
This technique is for those who want the most simple method that is very effective. It is BEST traded during the busiest trading hours, 3am to 12am EST NY time. This method doesn't work in sideways markets, only in volatile trending markets.
Time Frames: 1, 5, 10, 15 ,30 min.
Currency pairs: majors.
Other Chart indicators:
Add Awesome Oscillator.
Optionally Add Squeeze Indicator.
Here's the strategy:
Going LONG:
Enter a long position when the black 3 EMA has crossed up through the Bollinger red middle band MA. At the same time, the Awesome should be approaching or crossing it's zeroline, going up. This is indicated by "Buy" alert.
Going SHORT:
Enter a short position when the black 3 EMA has crossed down through the Bollinger red middle band MA. At the same time, the Awesome should be approaching or crossing it's zero line, going down. This is indicated by the "Sell" Alert.
Take profit:
10-20 pips depending on pair or When Awesome Oscillator turns a different colour.
HINTS: Best trades tend to occur when price reversing bounce off outer band and outside the Optional Bollinger Squeeze indication.
Hidden Gap`s VSA Volume If Volume is less then the previous 20 intervals, Volume is gray.
If Volume is greater then the previous 40 intervals, Volume is black.
If Volume is less then the previous 2 intervals, Volume is purple.
If Volume is less then the previous, Volume is red.
If Volume is greater then the previous, Volume is blue.
Other - white.
You can add on the indicator a 2.5 Standart Deviation of a 20 period
Bollinger Band Shifted 3 periods forward.
Single SMA cross with BB StrategyThis is a light weight code and strategy. I tuned it for NZDUSD on a 15 min chart. NZDUSD is a slow moving low volatility pair. A single SMA cross over + crossing a .9 BB + the single SMA is increasing. I will be manually trading this with alerts and once I have LUA down I will set it free with FXCM and see what it can do on it own.
** I use BB as a means of seeing momentum to continue gaining not as a reversal signal.
Please contact me with issues/questions
Bollinger Band and Moving Average v0.1 by JustUncleLThis is another Bollinger Band strategy+indicator in my series of Bollinger based setups. This one is seems to work best with 5min charts and 20 to 30min expiry. The strategy follows variation of a Bollinger band + Moving Averages
reversal strategy, it uses the 2 moving averages mainly to determine market direction.
%BsAn indicator with 10 configurable %B lines for identifying trends, overbought and oversold conditions, and reversal points. %B is a linear representation of a securities relationship to the Upper and Lower Bollinger Bands. The best opportunities arise when a security is oversold in a bullish trend and overbought in a bearish trend. The longer %B trend-lines in this indicator are very useful for major reversals. They can be used to indicate the high or low of the day on a 1-minute chart or show a multi-year reversal point.
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Kay_BBandsV3This is the 3rd version of Kay_BBands.
When +DI (Directional Index ) is above -DI , then Upper band will be visible and vice-versa.
This is when the ADX is above the threshold. 28 is the default in this version. I found its more appealing in 5M time frame.
BLUE - ADX under 10
GREEN - Uptrend, ADX over 10
RED - Downtrend, ADX over 10
Use it with another band with setting 20, 0.6 deviation. Prices keeping above or below the 2nd bands upper or lower bounds shows trending conditions.
I didn't know how to update the old script so published it again.
Changes - :
1) Updated default settings for the indicator
2) ADX setting are now DI (28), ADX (10), adx level to check is 10.
3) IMPORTANT one - When DI is up/down, lower/upper band will also have color (more visible that way.)
Play around the settings.. It really eliminates extra indicator checking visually... Please like if you think idea is good.
Kay_BBands v2This is the second version of Kay_BBands. But this is infused with ADX.
When +DI (Directional Index) is above -DI, then Upper band will be visible and vice-versa.
This is when the ADX is above the threshold. 20 is the default but can be set to 25.
When the ADX is below the specified threshold, both bands gets visible, showing no trending conditions.
Use it with another band with setting 20/21, 0.6 deviation. Prices keeping above or below the 2nd bands upper or lower bounds shows trending conditions.
[JR] Multi Bollinger Heat BandsBollinger Bands, with incremented additional outer bands.
Set as you would normally, but with the addition of an incremental value for the added outer bands.
Defaults with Length 20, base multiplier of 2.0, and an Increment value of 0.5 for additional outer bands at 2.5 and 3.0. Adjust values to suite your needs.
All lines and zones have colour and formatting options available - because why not eh?
Fibonnacci Bollinger BandsThis Bollinger Bands with additional Fib levels. Swing Trader Edition :) .. thats all really
Bollinger Band TouchThis script simply colors the background when price hits or exceeds the bollinger bands. Just a nice visual cue.
[RS]Multiple Bollinger Bands Candles V0EXPERIMENTAL: using multiple length bollinger bands to create a better reading of ?price/range? strength?.
• calculates 2 candle plots for upper and lower bands, were the high and low are the extremes of the bands,
open is the previous close of the band and close is the extreme midline.
CapnsBandsV2Here is the 2nd version of CapnsBandsV2 for Mateys... Remind you this a trend indicator NOT a BUY and SELL. Its up to you how you read it. Defaults for Smaller TF like 15Mnts. Enjoy it. :)
BL_MTF River Strategy with TP/SL by Beller
Anyone remember the "Frogger" game where a frog must pass a river ?
This strategy is like a game.
Immagine you that the cyan lines are a River, any time the price can cross up or down this river, you must buy or sell only when the bar are dry..
BUY at highest price of the first bar that is completely dry over the river
SELL at the lowest price of the first bar that is completely dry under the river
Stoploss is placed at the river bands, take profit is placed at 1:1 and 1:2 ratio, a risk money management must be applied.
This strategy can be used with multiple time frame, i'm testing it in 15min,180m and daily base applyed to EURJPY.
It's a game but can produce some money... ;-)
Indicator: MFI or RSI enclosed by Bollinger BandsIndicator allows choosing either MFI or RSI and draws a BB over it to identify oversold / overbought conditions.
Oversold/Overbought breaches are highlighted using different colors for easy identification. Has helped me a lot during sudden pumps to identify the tops, hope you find a use for this.
Trading Strategy based on BB/KC squeeze**** [Edit: New version (v02) posted, see the comments section for the code *****
Simple strategy. You only consider taking a squeeze play when both the upper and lower Bollinger Bands go inside the Keltner Channel. When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and a move is about to take place.
I have added more support indicators -- I highlight the bullish / bearish KC breaches (using GREEN/RED crosses) and a SAR to see where price action is trending.
Appreciate any feedback. Enjoy!
Color codes for v02:
----------------------------
When both the upper and lower Bollinger Bands go inside the Keltner Channel, the squeeze is on and is highlighted in RED.
When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and is highlighted in GREEN.
When one of the Bollinger Bands is out of Keltner Channel, no highlighting is done (this means, the background color shows up, so don't get confused if you have RED/GREEN in your chart's bground :))
Color codes for v01:
----------------------------
When both the upper and lower Bollinger Bands go inside the Keltner Channel, the squeeze is on and is highlighted in YELLOW.
When the Bollinger Bands (BOTH lines) start to come out of the Keltner Channel, the squeeze has been released and is highlighted in BLUE.
VolatilityIndicatorsLibrary "VolatilityIndicators"
This is a library of Volatility Indicators .
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the parameters and sources, not being restricted to just the closing price.
@Thanks and credits:
1. Dynamic Zones: Leo Zamansky, Ph.D., and David Stendahl
2. Deviation: Karl Pearson (code by TradingView)
3. Variance: Ronald Fisher (code by TradingView)
4. Z-score: Veronique Valcu (code by HPotter)
5. Standard deviation: Ronald Fisher (code by TradingView)
6. ATR (Average True Range): J. Welles Wilder (code by TradingView)
7. ATRP (Average True Range Percent): millerrh
8. Historical Volatility: HPotter
9. Min-Max Scale Normalization: gorx1
10. Mean Normalization: gorx1
11. Standardization: gorx1
12. Scaling to unit length: gorx1
13. LS Volatility Index: Alexandre Wolwacz (Stormer), Fabrício Lorenz, Fábio Figueiredo (Vlad) (code by me)
14. Bollinger Bands: John Bollinger (code by TradingView)
15. Bollinger Bands %: John Bollinger (code by TradingView)
16. Bollinger Bands Width: John Bollinger (code by TradingView)
dev(source, length, anotherSource)
Deviation. Measure the difference between a source in relation to another source
Parameters:
source (float)
length (simple int) : (int) Sequential period to calculate the deviation
anotherSource (float) : (float) Source to compare
Returns: (float) Bollinger Bands Width
variance(src, mean, length, biased, degreesOfFreedom)
Variance. A statistical measurement of the spread between numbers in a data set. More specifically,
variance measures how far each number in the set is from the mean (average), and thus from every other number in the set.
Variance is often depicted by this symbol: σ2. It is used by both analysts and traders to determine volatility and market security.
Parameters:
src (float) : (float) Source to calculate variance
mean (float) : (float) Mean (Moving average)
length (simple int) : (int) The sequential period to calcule the variance (number of values in data set)
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length. Only applies when biased parameter is defined as true.
Returns: (float) Standard deviation
stDev(src, length, mean, biased, degreesOfFreedom)
Measure the Standard deviation from a source in relation to it's moving average.
In this implementation, you pass the average as a parameter, allowing a more personalized calculation.
Parameters:
src (float) : (float) Source to calculate standard deviation
length (simple int) : (int) The sequential period to calcule the standard deviation
mean (float) : (float) Moving average.
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Standard deviation
zscore(src, mean, length, biased, degreesOfFreedom)
Z-Score. A z-score is a statistical measurement that indicates how many standard deviations a data point is from
the mean of a data set. It is also known as a standard score. The formula for calculating a z-score is (x - μ) / σ,
where x is the individual data point, μ is the mean of the data set, and σ is the standard deviation of the data set.
Z-scores are useful in identifying outliers or extreme values in a data set. A positive z-score indicates that the
data point is above the mean, while a negative z-score indicates that the data point is below the mean. A z-score of
0 indicates that the data point is equal to the mean.
Z-scores are often used in hypothesis testing and determining confidence intervals. They can also be used to compare
data sets with different units or scales, as the z-score standardizes the data. Overall, z-scores provide a way to
measure the relative position of a data point in a data
Parameters:
src (float) : (float) Source to calculate z-score
mean (float) : (float) Moving average.
length (simple int) : (int) The sequential period to calcule the standard deviation
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Z-score
atr(source, length)
ATR: Average True Range. Customized version with source parameter.
Parameters:
source (float) : (float) Source
length (simple int) : (int) Length (number of bars back)
Returns: (float) ATR
atrp(length, sourceP)
ATRP (Average True Range Percent)
Parameters:
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
atrp(source, length, sourceP)
ATRP (Average True Range Percent). Customized version with source parameter.
Parameters:
source (float) : (float) Source for ATR
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
historicalVolatility(lengthATR, lengthHist)
Historical Volatility
Parameters:
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
historicalVolatility(source, lengthATR, lengthHist)
Historical Volatility
Parameters:
source (float) : (float) Source for ATR
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
minMaxNormalization(src, numbars)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
minMaxNormalization(src, numbars, minimumLimit, maximumLimit)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
In this implementation, the user explicitly provides the desired minimum (min) and maximum (max) values for the scale,
rather than using the minimum and maximum values from the data.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
minimumLimit (simple float) : (float) Minimum value to scale
maximumLimit (simple float) : (float) Maximum value to scale
Returns: (float) Normalized value
meanNormalization(src, numbars, mean)
Mean Normalization
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
mean (float) : (float) Mean of source
Returns: (float) Normalized value
standardization(src, mean, stDev)
Standardization (Z-score Normalization). How "outside the mean" values relate to the standard deviation (ratio between first and second)
Parameters:
src (float) : (float) Source to normalize
mean (float) : (float) Mean of source
stDev (float) : (float) Standard Deviation
Returns: (float) Normalized value
scalingToUnitLength(src, numbars)
Scaling to unit length
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
lsVolatilityIndex(movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int) : (float) Length for normalization
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
lsVolatilityIndex(sourcePrice, movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
sourcePrice (float) : (float) Source for measure the distance
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int)
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
bollingerBands(src, length, mult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) A tuple of Bollinger Bands, where index 1=basis; 2=basis+dev; 3=basis-dev; and dev=multiplier*stdev
bollingerBands(src, length, aMult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Also, various multipliers can be passed, thus getting more bands (instead of just 2).
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) An array of multiplies used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands, where:
index 1=basis; 2=basis+dev1; 3=basis-dev1; 4=basis+dev2, 5=basis-dev2, 6=basis+dev2, 7=basis-dev2, Nup=basis+devN, Nlow=basis-devN
and dev1, dev2, devN are ```multiplier N * stdev```
bollingerBandsB(src, length, mult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation:
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands %B
bollingerBandsB(src, length, aMult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands %B. The number of results in this array is equal the numbers of multipliers passed via parameter.
bollingerBandsW(src, length, mult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation:
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands Width
bollingerBandsW(src, length, aMult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands Width. The number of results in this array is equal the numbers of multipliers passed via parameter.
dinamicZone(source, sampleLength, pcntAbove, pcntBelow)
Get Dynamic Zones
Parameters:
source (float) : (float) Source
sampleLength (simple int) : (int) Sample Length
pcntAbove (simple float) : (float) Calculates the top of the dynamic zone, considering that the maximum values are above x% of the sample
pcntBelow (simple float) : (float) Calculates the bottom of the dynamic zone, considering that the minimum values are below x% of the sample
Returns: A tuple with 3 series of values: (1) Upper Line of Dynamic Zone;
(2) Lower Line of Dynamic Zone; (3) Center of Dynamic Zone (x = 50%)
Examples:
K's Volatility BandsVolatility bands come in all shapes and forms contrary to what is believed. Bollinger bands remain the principal indicator in the volatility bands family. K's Volatility bands is an attempt at optimizing the original bands. Below is the method of calculation:
* We must first start by calculating a rolling measure based on the average between the highest high and the lowest low in the last specified lookback window. This will give us a type of moving average that tracks the market price. The specificity here is that when the market does not make higher highs nor lower lows, the line will be flat. A flat line can also be thought of as a magnet of the price as the ranging property could hint to a further sideways movement.
* The K’s volatility bands assume the worst with volatility and thus will take the maximum volatility for a given lookback period. Unlike the Bollinger bands which will take the latest volatility calculation every single step of time, K’s volatility bands will suppose that we must be protected by the maximum of volatility for that period which will give us from time to time stable support and resistance levels.
Therefore, the difference between the Bollinger bands and K's volatility bands are as follows:
* Bollinger Bands' formula calculates a simple moving average on the closing prices while K's volatility bands' formula calculates the average of the highest highs and the lowest lows.
* Bollinger Bands' formula calculates a simple standard deviation on the closing prices while K's volatility bands' formula calculates the highest standard deviation for the lookback period.
Applying the bands is similar to applying any other volatility bands. We can list the typical strategies below:
* The range play strategy : This is the usual reversal strategy where we buy whenever the price hits the lower band and sell short whenever it hits the upper band.
* The band re-entry strategy : This strategy awaits the confirmation that the price has recognized the band and has shaped a reaction around it and has reintegrated the whole envelope. It may be slightly lagging in nature but it may filter out bad trades.
* Following the trend strategy : This is a controversial strategy that is the opposite of the first one. It assumes that whenever the upper band is surpassed, a buy signal is generated and whenever the lower band is broken, a sell signal is generated.
* Combination with other indicators : The bands can be combined with other technical indicators such as the RSI in order to have more confirmation. This is however no guarantee that the signals will improve in quality.
* Specific strategy on K’s volatility bands : This one is similar to the first range play strategy but it adds the extra filter where the trade has a higher conviction if the median line is flat. The reason for this is that a flat line means that no higher highs nor lower lows have been made and therefore, we may be in a sideways market which is a fertile ground for mean-reversion strategies.