I've been live trading for a couple of years and in that time i've tried numerous strategies until late last year when i finally developed my own system. Due to my statistics and mathematics backgroung and job experience, I developed a prediction model that eseentailly uses the last 3 years data to predict how the market will move (considering trending and ranging factors as well).
I've backtested the model on 30M, 1HR and 4HR timeframes as well and the results are very encouranging as it has managed to correctly predict the right decision on more than 50% of the time(ranges between 50% to 60%). The prediction model is designed in R programming language and it seems to work best on GBPJPY. After R gives the prediction, i execute the buy or sell order in 4 hour timelines with proper money management in my platform(using Ctrader at the moment).
Ive been trading it on the 4HR chart with a stop loss of 20pips and take profit figure of 45pips and based on my sucess ratio of 55% per month, the results are very encouraging. I chose those 2 figures(stop loss and take profit) based on average pip movt of the GBPJPY for the last 2 years on the 4HR bars (details in attached excel sheet).
I need someone who can help me backtest it on 5 year to 10 year data for 15 mins timeframe as my machine isnt capable of doing it due to processing speed requierements.
I've attached the R script for back testing and the one for live trading as well as a statisctical analysis sheet that displays the back tested data.
Any details on how to fine tune the model are welcome.