rl_write_control_parameters_mt: Function to find and write the best control parameters.

In lazytrade: Learn Computer and Data Science using Algorithmic Trading

Function to find and write the best control parameters.

Description

This function is supposed to run on a weekly basis. Purpose of this function is to perform RL and trading simulation and find out the best possible control parameters for the RL function.

Usage

rl_write_control_parameters_mt(
  x,
  path_control_files,
  num_trades_to_consider = 100
)

Arguments

x	dataset containing the trading results for one trading robot
path_control_files	path where control parameters will be saved
num_trades_to_consider	number of last trades to use for RL modeling simulations, default value 100

Details

Function is used by the R script Adapt_RL_MT_control.R

Value

Function writes best control parameters to be used by the Reinforcement Learning Function

Author(s)

(C) 2019, 2021 Vladimir Zhbanko

Examples

# test lasts 15 sec:
dir <- normalizePath(tempdir(),winslash = "/")

library(dplyr)
library(readr)
library(ReinforcementLearning)
library(magrittr)
library(lazytrade)
data(trading_systemDF)

# use optimal control parameters found by auxiliary function
rl_write_control_parameters_mt(x = trading_systemDF,
                               path_control_files = dir,
                               num_trades_to_consider = 100)

lazytrade documentation built on Sept. 12, 2024, 9:36 a.m.