MAD - Mean Absolute Deviation purpose :implementation of MAD Mean Absolute Deviation in pinescript
implementation by : patmaba
type : measures of spread
Mean absolute deviation
The mean absolute deviation of a dataset is the average distance between each data point and the mean. It gives us an idea about the variability in a dataset.
Here's how to calculate the median absolute deviation.
Step 1: Calculate the mean.
Step 2: Calculate how far away each data point is from the mean using positive distances. These are called absolute deviations.
Step 3: Add those deviations together.
Step 4: Divide the sum by the number of data points.
Source of MAD:
www.khanacademy.org
Formula :
MAD = ( ∑ |xi−µ| ) / n
where
xi = the value of a data point
|xi − µ| = absolute deviation
µ = mean
n = sample size
Bands
Click VWAP Anchored with Standard Devation BandsSimply use it by clicking on your chart on the places you find important to determine whether you entries or exits look strong or weak.
Flying Dragon Trend IndicatorFlying Dragon Trend Indicator can be used to indicate the trend on all timeframes by finetuning the input settings.
The Flying Dragon Trend family includes both the strategy and the indicator, where the strategy supports of selecting the optimal set of inputs for the indicator in each scenario. Highly recommended to get familiar with the strategy first to get the best out of the indicator.
Flying Dragon Trend plots the trend bands into the ribbon, where the colours indicate the trend of each band. The plotting of the bands can be turned off in the input settings. Based on the user selectable Risk Level the trend pivot indicator is shown for the possible trend pivot when the price crosses the certain moving average line, or at the Lowest risk level all the bands have the same colour. The trend pivot indicator is not shown on the Lowest risk level, but the colour of the trend bands is the indicator instead .
The main idea is to combine two different moving averages to cross each other at the possible trend pivot point, but trying to avoid any short term bounces to affect the trend indication. The ingenuity resides in the combination of selected moving average types, lengths and especially the offsets. The trend bands give visual hint for the user while observing the price interaction with the bands, one could say that when "the Dragon swallows the candles the jaws wide open", then there is high possibility for the pivot. The leading moving average should be fast while the lagging moving average should be, well, lagging behind the leading one. There is Offset selections for each moving average, three for leading one and one for the lagging one, those are where the magic happens. After user has selected preferred moving average types and lengths, by tuning each offset the optimal sweet spot for each timeframe and equity will be found. The default values are good enough starting points for longer (4h and up) timeframes, but shorter timeframes (minutes to hours) require different combination of settings, some hints are provided in tooltips. Basically the slower the "leading" moving average (like HMA75 or HMA115) and quicker the "lagging" moving average (like SMA12 or SMA5) become, the better performance at the Lowest risk level on minute scales. This "reversed" approach at the minute scales is shown also as reversed colour for the "lagging" moving average trend band, which seems to make it work surprisingly well.
The Flying Dragon Trend does not necessarily work well on zig zag and range bounce scenarios without additional finetuning of the input settings to fit the current condition.
Flying Dragon Trend StrategyFlying Dragon Trend Strategy can be used to indicate the trend on all timeframes by finetuning the input settings.
The Flying Dragon Trend family includes both the strategy and the indicator, where the strategy supports of selecting the optimal set of inputs for the indicator in each scenario. Highly recommended to get familiar with the strategy first to get the best out of the indicator.
Flying Dragon Trend plots the trend bands into the ribbon, where the colours indicate the trend of each band. The plotting of the bands can be turned off in the input settings. Based on the user selectable Risk Level the strategy is executed when the price crosses the certain moving average line, or at the Lowest risk level all the bands have the same colour.
The main idea is to combine two different moving averages to cross each other at the possible trend pivot point, but trying to avoid any short term bounces to affect the trend indication. The ingenuity resides in the combination of selected moving average types, lengths and especially the offsets. The trend bands give visual hint for the user while observing the price interaction with the bands, one could say that when "the Dragon swallows the candles the jaws wide open", then there is high possibility for the pivot. The leading moving average should be fast while the lagging moving average should be, well, lagging behind the leading one. There is Offset selections for each moving average, three for leading one and one for the lagging one, those are where the magic happens. After user has selected preferred moving average types and lengths, by tuning each offset the optimal sweet spot for each timeframe and equity will be found. The default values are good enough starting points for longer (4h and up) timeframes, but shorter timeframes (minutes to hours) require different combination of settings, some hints are provided in tooltips. Basically the slower the "leading" moving average (like HMA75 or HMA115) and quicker the "lagging" moving average (like SMA12 or SMA5) become, the better performance at the Lowest risk level on minute scales. This "reversed" approach at the minute scales is shown also as reversed colour for the "lagging" moving average trend band, which seems to make it work surprisingly well.
The Flying Dragon Trend does not necessarily work well on zig zag and range bounce scenarios without additional finetuning of the input settings to fit the current condition.
Strategy direction selector by DashTrader.
Trop BandsTrop Bands is a tool that uses an exponential moving average (EMA) as its central trendline and upper and lower bands to identify potential buying and selling opportunities in the market. The bands are calculated based on recent moves away from the EMA, and they are plotted around the central trendline to provide a visual representation of market trends and conditions. When the price moves outside of these bands, it can be seen as a signal that the security is overbought or oversold and may be ready for a reversal, just like Bollinger Bands.
In addition to providing signals when the price moves outside of the bands, the indicator can also show triangles outside/inside the bands. These triangles are based on the Demand Index developed by James Sibbet and are intended to provide additional confirmation of potential trading opportunities. They can be used in conjunction with other technical analysis tools to help identifying potential trading opportunities in the market.
Correlated ATR Bands | AdulariHow do I use it?
Never use this indicator as standalone trading signal, it should be used as confluence.
It is highly recommended to use this indicator on the 15m timeframe and above, try experimenting with the inverse feature and multipliers as well.
When the price is above the moving average this shows the bullish trend is strong.
When the price is below the moving average this shows the bearish trend is strong.
When the moving average is purple, the trend is bullish , when it is gray, the trend is bearish.
When price is above the upper band this may indicate a bearish reversal.
When price is below the lower band this may indicate a bullish reversal.
Features:
Purple line for bullish trend and gray line for bearish trend.
Custom formula combining an ATR and Hull MA to clearly indicate trend strength and direction.
Unique approach to moving averages and bands by taking the average of 2 types of MA's combined with custom ATR's, then multiplying these by correlation factors.
Bands to indicate possible trend reversals when price crosses them.
How does it work?
1 — ATR value is calculated, then the correlation between the source and ATR is calculated.
2 — Final value is calculated using the following formula:
correlation * atr + (1 - correlation) * nz(atr , atr)
3 — Moving average is calculated with the following formula:
ta.hma((1-(correlation/100*(1+weight/10)))*(ta.sma(source+value, smoothing)+ta.sma(source-value,smoothing))/2,flength)
4 — Bands calculation using multipliers.
[EDU] RSI Momentum BandsRSI Momentum Bands serve a purpose to find best RSI momentum for entering a trade.
Indicator is built simply:
1st RSI MA is smoothed RSI by little period, 2nd RSI MA is smoothed RSI by a bigger period.
Then we calculate standard deviation from the 2nd MA and make upper and lower band.
The rules for trades are simple:
When RSI is above higher band - Buy ;
When RSI is below lower band - Sell .
The indicator is for educational purposes only to present trades a momentum bands concepts, widely used across professionals.
Hope you will find it helpful.
Take your profits!
- Tarasenko Fyodor
Extended Recursive Bands StrategyThe original indicator was created by alexgrover .
All credit goes to alexgrover for creating the indicator that this strategy uses.
This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet.
The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended".
The Indicator
The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often.
In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Added logic:
We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance.
Strategy Long conditions:
1 — Price low is below the the lower band.
2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached.
Strategy Short conditions:
1 — Price high is above the upper band.
2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached.
Strategy Properties:
We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers.
MTF MA Ribbon and Bands + BB, Gaussian F. and R. VWAP with StDev█ Multi Timeframe Moving Average Ribbon and Bands + Bollinger Bands, Gaussian Filter and Rolling Volume Weighted Average Price with Standard Deviation Bands
Up to 9 moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines, colors and background fill are customizable too.
This script can also display:
Moving Average Bands
Bollinger Bands
Gaussian Filter
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Gaussian Filter
Gaussian filter can be used for smoothing.
It rejects high frequencies (fast movements) better than an EMA and has lower lag.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve.
In the case of low-pass filters, only the upper half of the curve describes the filter.
The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Made with the help from scripts of: adam24x, VishvaP, loxx and pmk07.
RSI Shadow by TartigradiaHave you ever wondered how much the RSI can vary during an open session? How much wicks can make the RSI overshoots before it retraces for the close?
This indicator plots the RSI shadow, which is the area between the highest and lowest RSI values attained during each open session, from the high/low wick price candle (ie, not the open value).
Technically, we calculate the RSI as usual for all past bars, except for current bar for which we use the high and low values to calculate the RSI Shadow bounds. The invisible PineScript loop then repeats this process for each bar.
In practice, the RSI Shadow provides 2 different informations:
1. This allows to visually represent the variability that historically happened for each bar, which help in better understanding the context at the time and may help predict future similar patterns.
2. The closer the RSI is to one bound, high or low, the more bullish or bearish respectively the price action is. Intuitively, when RSI is close to the high shadow bound, it means that price action is so bullish it often closes in proximity to the highest value attained during the open session, hence very bullish sentiment. And inversely for low and bearish sentiment. To ease visualization of these sentiments, a background highlighting is provided.
The indicator works under all timeframes, but it appears to provide a very reliable information with longer timeframe. The background highlighting showing the bullish/bearish sentiment based on the RSI Shadow appears to indicate crypto market cycles relatively reliably, with 2-3 consecutive bars with the same background color indicating a strong trend.
False positives can be reduced by looking at both the background color and the RSI direction, if both are congruent (ie, both bullish), then the trend indication is good, otherwise the trend indicated by the background color should be disregarded. An option was added to uncolor background if incongruent with RSI's direction.
There is also a "shadow margin" setting that allows to further reduce the number of false positives, at the expense of reduced sensitivity (a margin of 3 seems to eliminate most false positives).
Note: if you need a more complete RSI indicator with overbought/oversold signals, check out RSI+ (alt), which includes all RSI related indicators I make (such as RSI Shadow):
Volume Weighted Reversal BandsThis is a vwap & vwma hybrid with upper & lower deviation bands that provide excellent price channels and reversal areas. It can be used on lower & higher timeframes, just increase the deviation % for higher timeframes. Try out the 1 minute timeframe with .5% deviation for great scalping levels.
Here is the calculation used for the main line.
(VWMA100 + VWMA500 + VWMA1000 + VWAP) / 4
So it combines 3 VWMAs with the VWAP and divides that number by 4 to give us a moving average. Then we add new levels above and below that moving average to get our channels. The channels are separated by the % deviation you choose in the settings. For tighter bands, lower the percentage deviation and for wider bands, increase the percentage deviation.
The fattest line in the middle is the main moving average and you can expect price to regularly return to this level. The thick lines are the main moving average plus or minus the percentage deviation you have set. There are 10 levels in each direction from the main moving average. The is also a thin short term moving average as well with a custom calculation. It takes 4 different length moving averages that are weighted and 4 more that are volume weighted and divides the total by 8.The lines will be green when price is above the line and red when price is below the line. The thin white line is the VWAP on its own.
These lines will act as dynamic support and resistance so you can scalp them back and forth. These levels work so well because they are volume weighted and the algos hedge their positions back and forth constantly.
For best results, use this indicator on tickers with the highest volume and trading action as the price will stick to these levels better when the big money players are hedging. Some great tickers for this indicator are APPL, SPY, BTC, ETH.
All colors and linewidths can be customized in the settings easily as well as turning off the VWAP or short moving average and adjusting the percentage deviation for the channels.
***MARKETS***
This indicator can be used on all markets, including stocks, crypto, futures and forex.
***TIMEFRAMES***
This indicator can be used on all timeframes.
***TIPS***
Try using numerous indicators of ours on your chart for extra confirmation. Our favorites to pair with these bands are the Scalper Ribbon and Trend Friend Signals. The 3 combined give you a lot of extra confirmation on whether the market is going to reverse at these levels.
Parkinson's Historical Volatility Bands [Loxx]Parkinson's Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Parkinson's historical volatility (instead of "regular" Historical Volatility) for bands calculation.
What is Parkinson's Historical Volatility?
The Parkinson's number, or High Low Range Volatility developed by the physicist, Michael Parkinson in 1980, aims to estimate the Volatility of returns for a random walk using the High and Low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval: n = 10, 20, 30, 60, 90, 120, 150, 180 days.
SH is stock's High price in t day.
SL is stock's Low price in t day.
High/Low Return (xt^HL) is calculated as the natural logarithm of the ratio of a stock's High price to stock's Low price.
Return:
And Parkinson's number: 1 / (4 * math.log(2)) * 252 / n * Σ (n, t =1) {math.log(Ht/Lt)^2}
An important use of the Parkinson's number is the assessment of the distribution prices during the day as well as a better understanding of the market dynamics. Comparing the Parkinson's number and periodically sampled volatility helps traders understand the tendency towards mean reversion in the market as well as the distribution of stop-losses.
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Historical Volatility Bands [Loxx]Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Historical Volatility for bands calculation.
What is Historical Volatility?
Historical Volatility (HV) is a statistical measure of the dispersion of returns for a given security or market index over a given period of time. Generally, this measure is calculated by determining the average deviation from the average price of a financial instrument in the given time period. Using standard deviation is the most common, but not the only, way to calculate Historical Volatility.
The higher the Historical Volatility value, the riskier the security. However, that is not necessarily a bad result as risk works both ways - bullish and bearish, i.e: Historical Volatility is not a directional indicator and should not be used as other directional indicators are used. Use to to determine the rising and falling price change volatility.
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
ATR Trend Bands [Misu]█ This indicator shows an upper and lower band based on price action and ATR (Average True Range)
The average true range (ATR) is a market volatility indicator used in technical analysis.
█ Usages:
The purpose of this indicator is to identify changes in trends and price action.
It is mainly used to identify breaking points and trend reversals.
But it can also be used to show resistance or support levels.
█ Features:
> Buy & Sell Alerts
> Buy & Sell Labels
> Color Bars
> Show Bands
█ Parameters:
Length: Length is used to calculate ATR.
Atr Multiplier: A factor used to balance the impact of the ATR on the Trend Bands calculation.
RSI + MA, LinReg, ZZ (HH HL LH LL), Div, Ichi, MACD and TSI HistRelative Strength Index with Moving Average, Linear Regression, Zig Zag (Highs and Lows), Divergence, Ichimoku Cloud, Moving Average Convergence Divergence and True Strength Index Histogram
This script is based on zdmre's RSI script, I revamped a lot of things and added a few indicators from ParkF's RSI script.
Disable Labels in the Style tab and the histogram if you don't enlarge the indicator and it seems too small.
Look to buy in the oversold area and bounce of the support of the linear regression.
Look to sell in the overbought area and bounce of the resistance of the linear regression.
Look for retracement to the moving average or horizontal lines, and divergences for potential reversal.
RSI
The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements.
Moving Average
Moving Average (MA) is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
Linear Regression
The Linear Regression indicator visualizes the general price trend of a specific part of the chart based on the Linear Regression calculation.
Zig Zag (Highs and Lows)
The Zig Zag indicator is used to identify price trends, and in doing so plots points on the chart to mark whenever prices reverse by a larger percentage point than a predetermined variable or marker.
Divergence
The divergence indicator warns traders and technical analysts of changes in a price trend, oftentimes that it is weakening or changing direction.
Ichimoku Cloud
The Ichimoku Cloud is a package of multiple technical indicators that signal support, resistance, market trend, and market momentum.
MACD and TSI Histogram
MACD can be used to identify aspects of a security's overall trend.
The True Strength Index indicator is a momentum oscillator designed to detect, confirm or visualize the strength of a trend.
VWAP BANDS [qrsq]Description
This indicator is used to find support and resistance utilizing both buying and selling volume. It can be used on lower and higher time frames to understand where price is likely to reject or bounce.
How it works
Instead of calculating the VWAP using the total volume, this script estimates the buying/selling volume and respectively calculates their individual VWAP's. The standard deviations of these are then calculated to create the set of two bands. The top bands being the VWAP from buying volume and bottom bands are from selling volume, with the option to use a double band on either pair.
How to use it
I like to use the bands for LTF scalping as well as HTF swings, I also like to use it alongside my SMA VWAP BANDS.
For scalping:
I tend to use either the 5m or 15m TF
I then set the indicator's TF to 1m
I will take a scalp based on the bands confluence with other PA methods, if price is being either supported or rejected.
For swings:
I tend to use a variety of TFs, including: 30m, 1H, 4H, D
I then set the indicator's TF to "Chart"
I will take a swing based on the bands confluence with other PA methods, if price is being either supported or rejected.
I also tend to use them on perpetual contracts as the volume seems to be more consistent and hence results in more accurate support and resistance.
Pivot-Based Channels & Bands [Misu]█ This Indicator is based on Pivot detection to show bands and channels.
The pivot price is similar to a resistance or support level. If the pivot level is breached, the price should continue in that direction. Or the price could reverse at or near this level.
█ Usages:
Use channels as a support & resistance zone.
Use bands as a support & resistance zone. It is also very powerfull to use it as a breakout.
Use mid bands & mid channels as a trend direction or trade filter as a more usual moving average.
█ Parameters:
Show Pivot Bands: show bands.
Show Pivot Mid Band: show mid bands.
Show Pivot Channels: show channels.
Show Pivot Mid Channel: show mid channels.
Deviation: deviation used to calculate pivot points.
Depth: depth used to calculate pivot points.
MTF EMA Ribbon & Bands + BBMulti Timeframe Exponential Moving Average Ribbon & Bands + Boillinger Bands
I used the script "EMA Ribbon - low clutter, configurable " by adam24x, I made some color change and I added a few indicators (Boillinger Bands, EMA on multi timeframe and EMA bands from "34 EMA Bands " by VishvaP).
The script can display various EMA from the chart's timeframe but also EMA from other timeframes.
Bollinger Bands and EMA bands can also be added to the chart.
Ultimate IndicatorThis is a combination of all the price chart indicators I frequently switch between. It contains my day time highlighter (for day trading), multi-timeframe long-term trend indicator for current commodity in the bottom right, customizable trend EMA which also has multi-timeframe drawing capabilities, VWAP, customizable indicators with separate settings from the trend indicator including: EMA, HL2 over time, Donchian Channels, Keltner Channels, Bollinger Bands, and Super Trend. The settings for these are right below the trend settings and can have their length and multiplier adjusted. All of those also have multi-timeframe capabilities separate from the trend multi-time settings.
The Day Trade Highlight option will draw faint yellow between 9:15-9:25, red between 9:25-9:45, yellow between 9:45-10:05. There will be one white background at 9:30am to show the opening of the market. while the market is open there will be a very faint blue background. For the end of the day there will be yellow between 15:45-15:50, red between 15:50-16:00, and yellow between 16:00-16:05. During the night hours, there is no coloring. The purpose of this highlight is to show the opening / closing times of the market and the hot times for large moves.
The indicators can also be colored in the following ways:
1. Simple = Makes all colors for the indicator Gray
2. Trend = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction.
3. Trend Adv = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction. If there is a short-term up-trend during a long-term down-trend, the Blue will become Navy. If short-term down-trend during long-term up-trend, the Red will be Brown.
4. Squeeze = Compares the Bollinger Bands width to the Keltner Channels width and will color based on relative squeeze of the market: Teal = no squeeze. Yellow = little squeeze. Red = decent squeeze. White = huge squeeze. if you do not understand this one, try drawing the Bollinger Bands while using the Squeeze color option and it should become more apparent how this works. I also recommend leaving the length and multiplier to the default 20 and 2 if using this setting and only changing the timeframe to get longer/shorter lengths as I've seen that changing the length or multiplier can more or less make it not work at all.
Along with the indicator settings are options to draw lines/labels/fills for the indicator. I enjoy having only fills for a cleaner look.
The Labels option will show Buy/Sell signals when the short-term trend flips to agree with the long-term trend.
The Trend Bars option will do the same as the Labels option but instead will color the bars white when a Buy/Sell option is given.
The Range Bars option shows will color a bar white when the Close of a candle is outside of a respective ranging indicator option (Bollinger or Keltner).
The Trend Bars will draw white candles no matter which indicator selection you make (even "Off"). However, Range Bars will only draw white when either Bollinger or Keltner are selected.
The Donchian Channels and Super Trend are trending indicators and should be used during trending markets. I like to use the MACD in conjunction with these indicators for possibly earlier entries.
The Bollinger Bands and Keltner Channel are ranging indicators and should be used during ranging markets. I like to use the RSI in conjunction with these indicators and will use 60/40 for overbought and oversold areas rather than 70/30. During a range, I wait for an overbought or oversold indication and will buy/sell when it crosses back into the middle area and close my position when it touches the opposite band.
I have a MACD/RSI combination indicator if you'd like that as well :D
As always, trade at your own risk. This is not some secret indicator that will 100% win. As always, the trades you see in the picture use a 1:1.5 or 1:2 risk to reward ratio, for today (August 8, 2022) it won 5/6 times with one trade still open at the end of the day. Manage your account correctly and you'll win in the long term. Hit me up with any questions or suggestions. Happy Trading!
MTF VWAP & StDev BandsMulti Timeframe Volume Weighted Average Price with Standard Deviation Bands
I used the script "Koalafied VWAP D/W/M/Q/Y" by Koalafied_3 and made some changes, such as adding more standard deviation bands.
The script can display the daily, weekly, monthly, quarterly and yearly VWAP.
Standard deviation bands values can be changed (default values are 0.618, 1, 1.618, 2, 2.618, 3).
Also the previous standard deviation bands can be displayed.
Value At Risk Channel [AstrideUnicorn]The Value at Risk Channel (VaR Channel) is a trading indicator designed to help traders control the level of risk exposure in their positions. The user can select a time period and a probability value, and the indicator will plot the upper and lower limits that the price can reach during the selected time period with the given probability.
CONCEPTS
The indicator is based on the Value at Risk (VaR) calculation. VaR is an important metric in risk management that quantifies the degree of potential financial loss within a position, portfolio or company over a specific period of time. It is widely used by financial institutions like banks and investment companies to forecast the extent and likelihood of potential losses in their portfolios.
We use the so-called “historical method” to compute VaR. The algorithm looks at the history of past returns and creates a histogram that represents the statistical distribution of past returns. Assuming that the returns follow a normal distribution, one can assign a probability to each value of return. The probability of a specific return value is determined by the distribution percentile to which it belongs.
HOW TO USE
Let’s assume you want to plot the upper and lower limits that price will reach within 4 hours with 5% probability. To do this, go to the indicator Settings tab and set the Timeframe parameter to "4 hours'' and the Probability parameter to 5.0.
You can use the indicator to set your Stop-Loss at the price level where it will trigger with low probability. And what's more, you can measure and control the probability of triggering.
You can also see how likely it is that the price will reach your Take-Profit within a specific period of time. For example, you expect your target level to be reached within a week. To determine this probability, set the Timeframe parameter to "1 week" and adjust the Probability parameter so that the upper or lower limit of your VaR channel is close to your Take-Profit level. The resulting Probability parameter value will show the probability of reaching your target in the expected time.
The indicator can be a useful tool for measuring and managing risk, as well as for developing and fine-tuning trading strategies. If you find other uses for the indicator, feel free to share them in the comments!
SETTINGS
Timeframe - sets the time period, during which the price can reach the upper or lower bound of the VaR channel with the probability, set by the Probability parameter.
Probability - specifies the probability with which the price can reach the upper or lower bound of the VaR channel during the time period specified by the Timeframe parameter.
Window - specifies the length of history (number of historical bars) used for VaR calculation.
DEMA Supertrend Bands [Misu]█ Indicator based on DEMA (Double Exponential Moving Average) & Supertrend to show Bands .
DEMA attempts to remove the inherent lag associated with Moving Averages by placing more weight on recent values.
Supertrend aims to detect price trends, it's also used to set protective stops.
█ Usages:
Combining Dema to calculate Supertrend results in nice lower and upper bands.
This can be used to identify potential supports and resistances and set protective stops.
█ Parameters:
Length DEMA: Double Ema lenght used to calculate DEMA. Dema is used by Supertrend indicator.
Length Atr: Atr lenght used to calculate Atr. Atr is used by Supertrend indicator.
Band Mult: Used to calculate Supertrend Bands width.
█ Other Applications:
The mid band can be used to filter bad signals in the manner of a more classical Moving Average.
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones [Loxx]VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones is an RSI indicator with adaptive inputs, Digital Kahler filtering, and Dynamic Zones. This indicator uses a Vertical Horizontal Filter for calculating the adaptive period inputs and allows the user to select from 7 different types of RSI.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
4 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Loxx's Variety RSI
Loxx's Dynamic Zones
