lazytrade (version 0.4.0)

generate_RL_policy_mt: Function performs RL and generates model policy for each Market Type

Description

This function will perform Reinforcement Learning using Trading Data. It will suggest whether or not it is better to keep using trading systems or not. Function is just using results of the past performance to generate the recommendation (not a holy grail).

Usage

generate_RL_policy_mt(x, states, actions, control)

Arguments

x

- Dataframe containing trading data

states

- possible states for Reinforcement Learning

actions

- possible actions

control

- control parameters

Value

Function returns data frame with reinforcement learning model policy

Details

Initial policy is generated using a dummy zero values. This way function starts working directly from the first observation. However policy 'ON' value will only be generated once the Q value is greater than zero

Examples

# NOT RUN {
library(dplyr)
library(ReinforcementLearning)
data(trading_systemDF)
states <- c("BUN", "BUV", "BEN", "BEV", "RAN", "RAV")
actions <- c("ON", "OFF")
control <- list(alpha = 0.7, gamma = 0.3, epsilon = 0.1)
generate_RL_policy_mt(trading_systemDF, states, actions, control)


# }