mt_import_data

Function imports file from the MetaTrader sandbox. Function performs necessary cleansing of the data column types
<a href="https://lifecycle.r-lib.org/articles/stages.html#stable"><img src="figures/lifecycle-stable.svg?package=lazytrade&version=0.5.4" alt="[Stable]"></a>

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://vantharp.com/>,
Reinforcement Learning R package: <https://CRAN.R-project.org/package=ReinforcementLearning>.

Vladimir Zhbanko

lazytrade

Learn Computer and Data Science using Algorithmic Trading

mt_import_data function

<dl><dt>path_sbxm</dt>
<dd><ul>
<li>String, Path to the sandbox with the log file (master terminal)</li>
</ul></dd>
<dt>system_number</dt>
<dd><ul>
<li>magic number id of the trading system</li>
</ul></dd></dl>

Arguments

Author

Function imports file from the MetaTrader sandbox. Function performs necessary cleansing of the data column types
<a href='https://lifecycle.r-lib.org/articles/stages.html#stable'><img src='figures/lifecycle-stable.svg' alt='[Stable]' /></a>

Import Market Type related Data to R from the Sandbox — mt_import_data

<dl>

<dt>path_sbxm</dt>
<dd><ul>
<li>String, Path to the sandbox with the log file (master terminal)</li>
</ul></dd>


<dt>system_number</dt>
<dd><ul>
<li>magic number id of the trading system</li>
</ul></dd>

</dl>

mt_import_data: Import Market Type related Data to R from the Sandbox

Description

Usage

Value

Arguments

Author

Examples