Strategy Myth-Busting #4 - LSMA+HULL Crossover - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our fourth one we are automating is one of the strategies from "I Found The Best 1 Minute Scalping Strategy That Actually Works! ( Beginner Friendly )" from "Trade Domination" who claims to have made 366% profit on the 1 min chart of Solona despite having a 31% win rate in just a few weeks. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on the same symbol ( SOLUSD ), timeframe (1m) with identical instrument settings that "Trade Domination" was demonstrating with. Strategy Busted.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
LSMA
Hull Suite by InSilico
Trading Rules
1 min candles
Stop Loss on recent swing High/Low
1:5 Risk Ratio
Enter Long
LSMA cross above Red Hull Suite line
Price has to be above Hull Suite Line
Enter Short
LSMA crosses under green Hull Suite Line
Price has to be below Hull Suite Line
Least
Weighted Least Squares Moving AverageLinearly Weighted Ordinary Least Squares Moving Regression
aka Weighted Least Squares Moving Average -> WLSMA
^^ called it this way just to for... damn, forgot the word
Totally pwns LSMA for some purposes here's why (just look up):
- 'realistically' the same smoothness;
- less lag;
- less overshoot;
- more or less same computationally intensive.
"Pretty cool, huh?", Bucky Roberts©, thenewboston
Now, would you please (just look down) and see the comparison of impulse & step responses:
Impulse responses
Step responses
Ain't it beautiful?
"Motivation behind the concept & rationale", by gorx1
Many been trippin' applying stats methods that require normally distributed data to time series, hence all these B*ll**** Bands and stuff don't really work as it should, while people blame themselves and buy snake oil seminars bout trading psychology, instead of using proper tools. Price... Neither population nor the samples are neither normally nor log-normally distributed. So we can't use all the stuff if we wanna get better results. I'm not talking bout passing each rolling window to a stat test in order to get the proper descriptor, that's the whole different story.
Instead we can leverage the fact that our data is time-series hence we can apply linear weighting, basically we extract another info component from the data and use it to get better results. Volume, range weighting don't make much sense (saying that based on both common sense and test results). Tick count per bar, that would be nice tho... this is the way to measure "intensity". But we don't have it on TV unfortunately.
Anyways, I'm both unhappy that no1 dropped it before me during all these years so I gotta do it myself, and happy that I can give smth cool to every1
Here is it, for you.
P.S.: the script contains standalone functions to calculate linearly weighted variance, linearly weighted standard deviation, linearly weighted covariance and linearly weighted correlation.
Good hunting
Exponential Least Squares Moving AverageModified LSMA (Least Squares Moving Average) to use exponential rates of growth instead of linear regression. Inputting a number into the confidence interval allows the user to have set percentage of statistical guarantee based on past movement. To set this percentage of guarantee (Default set to 97.5%), refer to the input values below:
0.000 = 50%
0.255 = 60%
0.525 = 70%
0.835 = 80%
1.040 = 85%
1.285 = 90%
1.645 = 95%
1.960 = 97.5%
2.330 = 99%
Forecasting - Least Squares RegressionTested on 5m TF with EURUSD. Settings should be modified appropriately for other TFs, lookbacks and securities. This indicator does not repaint.
