Alpha & BetaAlpha & Beta Indicators for Portfolio Performance
β = Σ Correlation (RP, RM) * (σP/σM)
α P = E(RP) –
Where,
RP = Portfolio Return (or Investment Return)
RM = Market Return (or Benchmark Index)
RF = Risk-Free Rate
How to use the Indicator
RM = SPX (Default)
The Market Return for the indicator has the options of $SPX, $NDX, or $DJI (S&P 500, Nasdaq 100, Dow 30)
RF = FRED: DTB3
The Risk-Free Rate in the Indicator is set to the 3-Month Treasury Bill: Secondary Market Rate
The Default Timeframe is 1260 or 5-Years (252 Trading Days in One Year)
RP = The symbol you enter
HOWEVER , you can determine your portfolio value by following the following directions below.
Note: I am currently working on an indicator that will allow you to insert the weights of your positions.
Complete Portfolio Analysis Directions
You will first need...
a) spreadsheet application - Google Sheets is Free, but Microsoft Excel will convert ticker symbols to Stocks and Retrieve Data.
b) your current stock tickers, quantity of shares, and last price information
In the spreadsheet,
In the first column list the stock tickers...
AMZN
AAPL
TSLA
In the second column list the quantity of shares you own...
5
10
0.20
In the third column insert the last price
Excel: Three tickers will automatically give you the option to "Convert to Stocks",
after conversion, click once on cell and click the small tab in the upper right-hand of the highlighted cell.
Click the tab and a menu pops up
Find "Price", "Price Extended-Hours", or "Previous Close"...
$3,284.72
$497.48
$2,049.98
Next, multiply the number of shares by the price (Stock Market Value)
Excel: in fourth column type "=(B1*C1)", "=(B2*C2)", "=(B3*C3)"...
= $16,423.60
= $4,974.80
= $410.00
add the three calculated numbers together or click "ΣAutoSum" (Portfolio Market Value)
= $21,808.40
Last, divide the market value of AMZN ($16,423.60) by the Portfolio Market Value ($21,808.40) for each of the stocks.
= 0.7531
= 0.2281
= 0.0188
These values are the weight of the stock in your portfolio.
Go back to TradingView
Enter into the "search box" the following...
AMZN*0.7531 + AAPL*0.2281 + TSLA*0.0188
and click Enter
Now you can use the "Alpha & Beta" Indicator to analyze your entire portfolio!
Cerca negli script per "spx"
Carl's BOTTOM DETECTOR: Williams %R + normalized ATRThis script is based on Williams %r and normalized ATR.
When William%R indicates extreme oversold conditions
and the ATR indicates extreme volatility at the same time,
then it prints an arrow below the candle.
It is based on the concept that swing lows and market bottoms
are characterized by extreme oversold momentum and
extreme volatility.
The highest tf's like the daily, show you perfect market bottoms for btc.
If you zoom in it's still good to find swing highs and lows, if necessary
you can tweak the settings.
Next to that I added grey, red, and green vertical bands to the chart.
This is based on the VIX, the SPX volatility index.
Whenever the volatility of the S&P500 crosses above a specific level
it prints a colored background band behind the candle.
Grey means high volatility, red extreme volatility (like in the covid
crisis and 2008 crisis), and green means the same as grey, but indicates
it came after a red zone and could mean strong bullish bounce momentum.
You can tweak the thresholds for the grey/green and read areas.
Sto RSI and kijun-sen line to determine and follow the trend This script uses 25-75 treshold of stochastic RSI with the help of kijun-sen as confirmation, to find entry points to any trend either newly developed or an established one. I just realized it on the 1 hour SPX chart. Sure it can be used on other symbols. Crossing above/below 25/75 line of sto RSI is considered as buy/sell signal. Signals are evaluated whether price be above/below kijun-sen line. If a sell signal below kijun-sen is generated it is a continuation signal for downtrend, otherwise it is a countertrend signal (maybe a signal for a new downtrend). A countertrend signal must be evaluated carefully and only accepted in the right side of kijun-sen. e.g entering a sell signal generated above kijun-sen should be accepted only below the kijun-sen, vice-versa.
Trend Follow with kijun-sen/tenkan sen for 1 Hour SPX
This script determines, plots and alerts on probable trend initiation and continuation points, using tenkan-sen(conversion line of ichimoku), kijun-sen(baseline of ichimoku) and stochastic RSI, for 1 H SPX.
New long/short trend initiates when prices cross above/below kijun sen. The trend continues when prices cross above/below tenkan-sen or stochastic RSI crosses up/down its signal line, while prices are above/below kijun-sen.
It is good to take partial profit between 10-15 points gain and trail the left with stops below kijun-sen line.
While placing the order, using 2-3 points buffer above/below of signal bars is recommended. Additionally, please be careful about clouds and do not place long/short orders below/above clouds.
Trend Follow with 8/34 EMA and Stoch RSI for 1 Hour SPX
The script determines and plots entry points for 1 hour S&P index using 8/34 emas and stochastic RSI. When 8 ema above/below 34 ema up/down crosses of stochastic RSI are considered as long/short entries. Entry prices should be above/below high/low of the signal bars accordingly. Ichimoku cloud can be used as extra filtering.
LSE_Bitcoin pump and flush at the London SE opening and closingBTC recently decoupled from SPX but now it is using London Exchange opening and closing hour to pump and flush.
Moving Average Speed Can Spot Turns Before They HappenMoving averages are perhaps the most common indicator in the world of technical analysis, highlighting trends over time by smoothing out values.
Because they show direction, moving averages inevitably rise or fall. These changes are often obvious in retrospect, but now they can be spotted as they happen with our MA Speed script.
This indicator calculates one of five kinds of moving averages (including exponential and volume-weighted). Users can set the length (50-day SMA by default). They can even pick whether it calculates based on open, high, low, close, etc. (Close is the default.)
MA Speed plots the simple 1-day percentage change similar to an oscillator at the bottom of the chart, color-coding for positive or negative values.
The chart above applies MA Speed to the S&P 500 . The result is pretty interesting because we can see how its 50-day SMA was falling at 0.67 percent in March, the fastest decline since December 2008. But this month it’s flattened quickly and is on pace to turn higher in the next session or two.
Selectable Ticker DIXWith this script you can select 10 tickers and see the aggregated DIX for them. I have the highest volume equity ETFs as defaults, but one could easily select FAANGM and a few other mega caps and make a FAANGM DIX index by changing the tickers in the settings. One improvement item that I have not gotten around to doing is to create a dollar weighted version of this, similar to the actual Squeezemetrics SPX DIX. This is "equal weighted" To make a dollar weighted version, multiply each by the daily closing price essentially and THEN find the average. It is possible to do I just have not taken the time to do it. It is on the list of things to do. If anyone has a solution PM me and I will add it. Thanks.
Strategy - Bobo Intraday Swing Bot with filtersThis is an adapted version of my swing bot with additional filters that mean it works quite well on lower timeframes like 1min, 5 mins as long as you adjust the setting accordingly (reduce pivot timescale, band width)
Entry conditions are filtered by an invisible trend calculation running in the background so the bot doesn't repeatedly try and fail to fade a strong trend. It has just about everything you should need for basic use, stop losses and targets, automatically close trade at pivot.
I get good results on rangey instruments like major indices such as SPX / ES that kind of thing. Make sure you understand the minmum tick value of an index so the stop setting on the bot work properly
Hope it's useful!
Correlation Coefficient & Coefficient of DeterminationMeasures the correlation between 2 assets, along with the coefficient of determination of the average of 200 candles. By default, 2 correlations are presented but only 1 with a coefficient of determination (default 200).
Default assets are XBTUSD and SPX
A value of 1 for R(200) gives a strong linear correlation between 2 assets
A value of 0 for R(200) suggests no linear correlation
A value of -1 for R(200) suggests a negative linear correlation between 2 assets
A coefficient of determination (R2) of 1 suggests confidence in the variability of the response data around mean.
A coefficient of determination (R2) of 0 suggests no confidence in the variability of the response data around mean.
BAT Multi Anchored VWAPMulti Anchored VWAP which includes:
BTC Key Pivots
SPX Key Pivots
Yearly Opens
5 Adjustable Dates
Works on all assets, unlike some VWAP calculations.
Volatitity Bands (STARC) on RSI for reversal warning [beta]Origin : The Indicator uses STARC volatilty bands created by Manning Stoller, based on ATR.
He perfered them to Bollinger because extreme price action never exceeds them.
Her former scholar and now TA Superstar Constance Brown applied them on RSI for getting
very relavant trend reversals. (She only used them in times when "overbought or not" becomes a severe question.
What it does: It delivers a reversal signal after rsi exceeded the bands and - as the bands resume the trend - the rsi fails to test the band once more. This is the moment of a reversal warning.
How to work wit h:
- Take the index of your interest and choose a time horizon one or two scales higher than your usual working horizon .(i.e if you work on Daily choose weekly).
-Scale the upper and the lower band via settings, so that the rsi only in rare cases exceeds or touches the bands. This is to tweak the reversal threshold. (For weekly SPX i am fine with 2.2 and 2.1)
- Find the arrows that mark possible reversals.
- Ready
Note: I called this a beta because i publish it with nearly no practical experience with it , just checked the formal correctness of the code. (Published so fast because it was written during the coronavirus days, for which to handle it might be helpful. )So feedback very welcome.
I took the formula in slight modification from the book "Technical Analysis for the Trading Professional", 2nd edition, by Constance Brown.
"Fun" Note: As you see the script would have warned before the corona selling - if you had used it.
I didn't because bull flags and all predicted nice weather...
Greets and again feedback welcome
yoxxx
SMU Quantum Thermo BallsThis script is the enhanced version of Market Thermometer with one difference. This one has Quantum Thermo balls shooting out of the thermometer tube when overheated. Quantum psychology, Quantum observation, call it what you like
My scripts are designed to beat ALGO, so the behavior of indicators is not like traditional indicators. Don't try to overthink it and compare it to other established functions.
If you knew ALGo as much as I do, then you would also ditch old indicators and design your own weird scripts to match the ALGO's personality. Oh yes, each AlGo for each stock has its own programming personality. Most my scripts are tuned to beat SPX ALGO meniac
Enjoy and think outside the box, the only way to beat the ALGO
Relative Strength(RSMK) + Perks - Markos KatsanosIf you are desperately looking for a novel RSI, this isn't that. This is another lesser known novel species of indicator. Hot off the press, in multiple stunning color schemes, I present my version of "Relative Strength (RSMK)" employing PSv4.0, originally formulated by Markos Katsanos for TASC - March 2020 Traders Tips. This indicator is used to compare performance of an asset to a market index of your choosing. I included the S&P 500 index along side the Dow Jones and the NASDAQ indices selectively by an input() in "Settings". You may comparatively analyze other global market indices by adapting the code, if you are skilled enough in Pine to do so.
With this contribution to the Tradingview community, also included is MY twin algorithmic formulation of "Comparative Relative Strength" as a supplementary companion indicator. They are eerily similar, so I decided to include it. You may easily disable my algorithm within the indicator "Settings". I do hope you may find both of them useful. Configurations are displayed above in multiple scenarios that should be suitable for most traders.
As always, I have included advanced Pine programming techniques that conform to proper "Pine Etiquette". For those of you who are newcomers to Pine Script, this script may also help you understand advanced programming techniques in Pine and how they may be utilized in a most effective manner. Utilizing the "Power of Pine", I included the maximum amount of features I could surmise in an ultra small yet powerful package, being less than a 60 line implementation at initial release.
Unfortunately, there are so many Pine mastery techniques included, I don't have time to write about all of them. I will have to let you discover them for yourself, excluding the following Pine "Tricks and Tips" described next. Of notable mention with this release, I have "overwritten" the Pine built-in function ema(). You may overwrite other built-in functions too. If you weren't aware of this Pine capability, you now know! Just heed caution when doing so to ensure your replacement algorithms are 100% sound. My ema() will also accept a floating point number for the period having ultimate adjustability. Yep, you heard all of that properly. Pine is becoming more impressive than `impressive` was originally thought of...
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND much, much more... You have the source!
The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Grand Trend Forecasting - A Simple And Original Approach Today we'll link time series forecasting with signal processing in order to provide an original and funny trend forecasting method, the post share lot of information, if you just want to see how to use the indicator then go to the section "Using The Indicator".
Time series forecasting is an area dealing with the prediction of future values of a series by using a specific model, the model is the main tool that is used for forecasting, and is often an expression based on a set of predictor terms and parameters, for example the linear regression (model) is a 1st order polynomial (expression) using 2 parameters and a predictor variable ax + b . Today we won't be using the linear regression nor the LSMA.
In time series analysis we can describe the time series with a model, in the case of the closing price a simple model could be as follows :
Price = Trend + Cycles + Noise
The variables of the model are the components, such model is additive since we add the component with each others, we should be familiar with each components of the model, the trend represent a simple long term variation of high amplitude, the cycles are periodic fluctuations centered around 0 of varying period and amplitude, the noise component represent shorter term irregular variations with mean 0.
As a trader we are mostly interested by the cycles and the trend, altho the cycles are relatively more technical to trade and can constitute parasitic fluctuations (think about retracements in a trend affecting your trend indicator, causing potential false signals).
If you are curious, in signal processing combining components has a specific name, "synthesis" , here we are dealing with additive synthesis, other type of synthesis are more specific to audio processing and are relatively more complex, but could be used in technical analysis.
So what to do with our components ? If we want to trade the trend, we should estimate right ? Estimating the trend component involve removing the cycle and noise component from the price, if you have read stuff about filters you should know where i'am going, yep, we should use filters, in the case of keeping the trend we can use a simple moving average of relatively high period, and here we go.
However the lag problem, which is recurrent, come back again, we end up with information easier to interpret (here the trend, which is a simple fluctuation such as a line or other smooth curve) at the cost of decision timing, that is unfortunate but as i said the information, here the moving average output, is relatively simple, and could be easily forecasted right ? If you plot a moving average of high period it would be easier for you to forecast its future values. And thats what we aim to do today, provide an estimate of the trend that should be easy to forecast, and should fit to the price relatively well in order to produce forecast that could determine the position of future closing prices observations.
Estimating And Forecasting The Trend
The parameter of the indicator dealing with the estimation of the trend is length , with higher values of length attenuating the cycle and noise component in the price, note however that high values of length can return a really long term trend unlike a simple moving average, so a small value of length, 14 for example can still produce relatively correct estimate of trend.
here length = 14.
The rough estimate of the trend is t in the code, and is an IIR filter, that is, it is based on recursion. Now i'll pass on the filter design explanation but in short, weights are constants, with higher weights allocated to the previous length values of the filter, you can see on the code that the first part of t is similar to an exponential moving average with :
t(n) = 0.9t(n-length) + 0.1*Price
However while the EMA only use the precedent value for the recursion, here we use the precedent length value, this would just output a noisy and really slow output, therefore in order to create a better fit we add : 0.9*(t(n-length) - t(n-2length)) , and this create the rough trend estimate that you can see in blue. On the parameters, 0.9 is used since it gives the best estimate in my opinion, higher values would create more periodic output and lower values would just create a rougher output.
The blue line still contain a residual of the cycle/noise component, this is why it is smoothed with a simple moving average of period length. If you are curious, a filter estimating the trend but still containing noisy fluctuations is called "Notch" filter, such filter would depending on the cutoff remove/attenuate mid term cyclic fluctuations while preserving the trend and the noise, its the opposite of a bandpass filter.
In order to forecast values, we simply sum our trend estimate with the trend estimate change with period equal to the forecasting horizon period, this is a really really simple forecasting method, but it can produce decent results, it can also allows the forecast to start from the last point of the trend estimate.
Using The Indicator
We explained the length parameter in the precedent section, src is the input series which the trend is estimated, forecast determine the forecasting horizon, recommend values for forecast should be equal to length, length/2 or length*2, altho i strongly recommend length.
here length and forecast are both equal to 14 .
The corrective parameter affect the trend estimate, it reduce the overshoot and can led to a curve that might fit better to the price.
The indicator with the non corrective version above, and the corrective one below.
The source parameter determine the source of the forecast, when "Noisy" is selected the source is the blue line, and produce a noisy forecast, when "Smooth" is selected the source is the moving average of t , this create a smoother forecast.
The width interval control...the width of the intervals, they can be seen above and under the forecast plot, they are constructed by adding/subtracting the forecast with the forecast moving average absolute error with respect to the price. Prediction intervals are often associated with a probability (determining the probability of future values being between the interval) here we can't determine such probability with accuracy, this require (i think) an analysis of the forecasting distribution as well as assumptions on the distribution of the forecasting error.
Finally it is possible to see historical forecasts, that is, forecasts previously generated by checking the "Show Historical Forecasts" option.
Examples
Good forecasts mostly occur when the price is close to the trend estimate, this include the following highlighted periods on AMD 15TF with default settings :
We can see the same thing at the end of EURUSD :
However we can't always obtain suitable fits, here it is isn't sufficient on BTCUSD :
We can see wide intervals, we could change length or use the corrective option to get better results, another option is to use a log scale.
We will end the examples with the log SPX, who posses a linear trend, so for example a linear model such as a linear regression would be really adapted, lets see how the indicator perform :
Not a great fit, we could try to use an higher length value and use "Smooth" :
Most recent fits are quite decent.
Conclusions
A forecasting indicator has been presented in this post. The indicator use an original approach toward estimating the trend component in the closing price. Of course i should have given statistics related to the forecasting error, however such analysis is worth doing with better methods and in more advanced environment allowing for optimization.
But we have learned some stuff related to signal processing as well as time series analysis, seeing a time series as the sum of various components is really helpful when it comes to make sense of chaotic and noisy series and is a basic topic in time series analysis.
You can see that in this new year i work harder on the visual of my indicators without trying to fall in the label addict trap, something that i wasn't really doing before, let me know what do you think of it.
Thanks for reading !
SMU Antimatter CandlesThis script is phycological similar to my Quantum candles series. So it is completely left field and may not suit everyone.
Antimatter Candles push the stock/symbol into negative antimatter universe where up is down and down is up.
In the antimatter universe, when 'actual' index goes up, the antimatter index goes down and vice versa. It means Green in the antimatter universe is behaving like Red and vice versa.
The phycology part is, our mind expects the stocks to go up even though we (bears) want it to come down. So every time you look at a green candle, you re-affirm the market upside move. Those familiar with Quantum Physics know that our mind re-enforces the external reality.
So when media tell us stock will go up, we are being trained (brainwashed) to assume stocks always go up.
For example, say you want to start your trading day and log into TradingView to see your chart. Even if you are bearish, in the back of your mind you expect to see stocks or index such as SPX gone up, and you also expect to see a Green candle melt-up.
So unconsciously, you are promoting the behaviour of Melt-up market. This script does the opposite where if you see a green candles the actual market has gone down. Physiologically speaking, this script de-hypnotise you from media brainwash
The antimatter candles enforce the opposite. When you see a green antimatter candle going up, it is mirroring a Red candle when the price goes down. So if you are a BEARISH on stock, you want to see more green and uptrend in the antimatter universe
To use the script, you need to turn off actual candle and do the opposite to go back to the reality mode.
Kind of like reverse scale with negative numbers and opposite colours.
Candlesticks ANN for Stock Markets TF : 1WHello, this script consists of training candlesticks with Artificial Neural Networks (ANN).
In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs.
The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open)
The outputs are adapted to the current values with a simple forecast code.
Once the OHLC value is found, the exponential moving averages of 5 and 20 periods are used.
Reminder : OHLC = (Open + High + Close + Low ) / 4
First version :
Script is designed for S&P 500 Indices,Funds,ETFs, especially S&P 500 Stocks,and for all liquid Stocks all around the World.
NOTE: This script is only suitable for 1W time-frame for Stocks.
The average training error rates are less than 5 per thousand for each candlestick variable. (Average Error < 0.005 )
I've just finished it and haven't tested it in detail.
So let's use it carefully as a supporter.
Best regards !
ANN Next Coming Candlestick Forecast SPX 1D v1.0WARNING:
Experimental and incomplete.
Script is open to development and will be developed.
This is just version 1.0
STRUCTURE
This script is trained according to the open, close, high and low values of the bars.
It is tried to predict the future values of opening, closing, high and low values.
A few simple codes were used to correlate expectation with current values. (You can see between line 129 - 159 )
Therefore, they are all individually trained.
You can see in functions.
The average training error of each variable is less than 0.011.
NOTE :
This script is designed for experimental use on S & P 500 and connected instruments only on 1-day bars.
The Plotcandle function is inspired by the following script of alexgrover :
Since we estimate the next values, our error rates should be much lower for all candlestick values. This is just first version to show logic.
I will continue to look for other variables to reach average error = 0.001 - 0.005 for each candlestick status.
Feel free to use and improve , this is open-source.
Best regards.
Macroeconomic Artificial Neural Networks
This script was created by training 20 selected macroeconomic data to construct artificial neural networks on the S&P 500 index.
No technical analysis data were used.
The average error rate is 0.01.
In this respect, there is a strong relationship between the index and macroeconomic data.
Although it affects the whole world,I personally recommend using it under the following conditions: S&P 500 and related ETFs in 1W time-frame (TF = 1W SPX500USD, SP1!, SPY, SPX etc. )
Macroeconomic Parameters
Effective Federal Funds Rate (FEDFUNDS)
Initial Claims (ICSA)
Civilian Unemployment Rate (UNRATE)
10 Year Treasury Constant Maturity Rate (DGS10)
Gross Domestic Product , 1 Decimal (GDP)
Trade Weighted US Dollar Index : Major Currencies (DTWEXM)
Consumer Price Index For All Urban Consumers (CPIAUCSL)
M1 Money Stock (M1)
M2 Money Stock (M2)
2 - Year Treasury Constant Maturity Rate (DGS2)
30 Year Treasury Constant Maturity Rate (DGS30)
Industrial Production Index (INDPRO)
5-Year Treasury Constant Maturity Rate (FRED : DGS5)
Light Weight Vehicle Sales: Autos and Light Trucks (ALTSALES)
Civilian Employment Population Ratio (EMRATIO)
Capacity Utilization (TOTAL INDUSTRY) (TCU)
Average (Mean) Duration Of Unemployment (UEMPMEAN)
Manufacturing Employment Index (MAN_EMPL)
Manufacturers' New Orders (NEWORDER)
ISM Manufacturing Index (MAN : PMI)
Artificial Neural Network (ANN) Training Details :
Learning cycles: 16231
AutoSave cycles: 100
Grid
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 998
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls
Learning rate: 0.1000
Momentum: 0.8000 (Optimized)
Target error: 0.0100
Training error: 0.010000
NOTE : Alerts added . The red histogram represents the bear market and the green histogram represents the bull market.
Bars subject to region changes are shown as background colors. (Teal = Bull , Maroon = Bear Market )
I hope it will be useful in your studies and analysis, regards.
Volume Price ROC Tracker and Shadow CandlesWhen price goes up on negative volume, then market is telling there is doubts in investors mind.
The SPX upside recent month was a on. Lower volume so, the rally in my view will not last. Read my articles on current market.
This very simple scripts shows if price drop or gain was on a upside volume or down side. It is a visual track on the candle reflecting the volume ROC overlapped as a price movement on the actual candle. So don't mistake it with a moving average. Red means volume was down even if price has gone up. Basically if a price goes up on a increase ROC volume then you can trust it. Otherwise it is likely that it won't last.
If you can improve on this idea, it would be great. I think there is not enough volume related scripts that diggs a bit deeper to describe the market behaviour in the future. After all all technical analysis are supposed to tell us about future price not just how it was in the past.
TradersAI_UTBotCREDITS to @HPotter for the orginal code.
CREDITS to @Yo_adriiiiaan for recently publishing the UT Bot study based on the original code -
I just added some simple code to turn it into a strategy. Now, anyone can simply add the strategy to their chart to see the backtesting results!
While @Yo_adriiiiaan mentions it works best on a 4-hour timeframe or above, I am happy to share that this seems to be working on a 15-minute chart on e-mini S&P 500 Index (using the KeyValue setting at 10)! You can play around with the different settings, and may be you might discover even better settings.
Hope this helps. Btw, if any of you play with different settings and discover great settings for a specific instrument, please share them with the community here - it will be rewarded back multiple times!
