policy_tr_systDF

Table with Market Types and sample of actual policy for those states

datasets

Provide sets of functions and methods to learn and practice data science using idea of algorithmic trading.
Main goal is to process information within "Decision Support System" to come up with analysis or predictions.
There are several utilities such as dynamic and adaptive risk management using reinforcement learning
and even functions to generate predictions of price changes using pattern recognition deep regression learning.
Summary of Methods used: Awesome H2O tutorials: <https://github.com/h2oai/awesome-h2o>,
Market Type research of Van Tharp Institute: <https://www.vantharp.com/>,
Reinforcement Learning R package: <https://CRAN.R-project.org/package=ReinforcementLearning>.

Vladimir Zhbanko

lazytrade

Learn Computer and Data Science using Algorithmic Trading

policy_tr_systDF function

A dataframe with 2 columns:<dl class="dl-horizontal">
 <dt>MarketType</dt><dd>Current Market Type status</dd>
 <dt>Policy</dt><dd>Policy choice</dd>
</dl>

Format

Table with Market Types and sample of actual policy for those states — policy_tr_systDF

A dataframe with 2 columns:<dl class='dl-horizontal'>
 <dt>MarketType</dt><dd>Current Market Type status</dd>
 <dt>Policy</dt><dd>Policy choice</dd>
</dl>

policy_tr_systDF: Table with Market Types and sample of actual policy for those states

Description

Usage

Arguments

Format