rl_write_control_parameters: 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(
  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_control.R

Value

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

Author(s)

(C) 2019 Vladimir Zhbanko

Examples

dir <- normalizePath(tempdir(),winslash = "/")
#test lasts 15 sec:
library(dplyr)
library(readr)
library(ReinforcementLearning)
library(magrittr)
library(lazytrade)
data(data_trades)
x <- data_trades
rl_write_control_parameters(x = data_trades,
                            path_control_files = dir,
                            num_trades_to_consider = 20)

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