Designed to work best with Decision Support System developed inside Lazy Trading Project
https://vladdsm.github.io/myblog_attempt/topics/lazy%20trading/
Model-based trading robot. Main features are listed below:
- Does not require optimization of parameters
- Learns from past trading experience
- Able to read Market Type
- Able to log Market Type status to the file
- Works with Reinforcement Learning Policy to identify which market type is more suitable to trade in
- IMPORTANT: Setup Environmental Variables to syncronize and use scripts inside the repository
This EA is deprecated.
It was previously explained in the Udemy course
Developing Self Learning Trading Robot
This repository is to keep existing EA working on 28 currencies and forcedly trained with kNN methods used code from here
Original code: Stat_Euclidean_Metric.mq4
Repository will not be maintained or even be deleted in the future.
- Go to Tester and set up parameter Base = True.
- Select large amount of time period and start trades simulation.
- Then change parameter Base = False.
- Run simulation again
Finally in order to use in trading mode move files from /tester folder to the /Files folder
- Check which systems require optimization in the folder 'TEST' see file 're-train'
- Write down magic numbers and corresponding currency pair
- Select robot FALCON_A in Terminal 2 strategy tester
- Select M15, Open Prices, Spread 3
- set up date to be | Start: Today - 2month; End: Today
- during 'optimization' set max 25 trades, lots = 0.01, Base = True
- set up magic number to the one selected in the table (see point 2)
- press start in the tester to generate trades
- repeat steps 7 - 8 for all magic numbers in the table
- execute script _CopyDATFilesToProd.bat to copy generated files to the T1, T3, T4...
- Make sure that platforms/computer are restarted
Use on your own risk: past performance is no guarantee of the future results!