lazytrade: Learn Computer and Data Science using Algorithmic Trading

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.

Version: 0.3.10
Depends: R (≥ 3.4.0)
Imports: readr, stringr, dplyr, lubridate, magrittr, ggplot2, grDevices, h2o, ReinforcementLearning, openssl
Suggests: testthat (≥ 2.1.0), covr
Published: 2020-03-23
Author: Vladimir Zhbanko
Maintainer: Vladimir Zhbanko <vladimir.zhbanko at gmail.com>
BugReports: https://github.com/vzhomeexperiments/lazytrade/issues
License: MIT + file LICENSE
URL: https://vladdsm.github.io/myblog_attempt/topics/lazy%20trading/, https://github.com/vzhomeexperiments/lazytrade
NeedsCompilation: no
Materials: README NEWS
CRAN checks: lazytrade results

Downloads:

Reference manual: lazytrade.pdf
Package source: lazytrade_0.3.10.tar.gz
Windows binaries: r-devel: lazytrade_0.3.10.zip, r-release: lazytrade_0.3.10.zip, r-oldrel: lazytrade_0.3.10.zip
macOS binaries: r-release: lazytrade_0.3.10.tgz, r-oldrel: lazytrade_0.3.10.tgz
Old sources: lazytrade archive

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