Package: portfolioBacktest
Title: Automated Backtesting of Portfolios over Multiple Datasets
Version: 0.4.1
Date: 2022-04-22
Description: Automated backtesting of multiple portfolios over multiple
datasets of stock prices in a rolling-window fashion. Intended for
researchers and practitioners to backtest a set of different portfolios,
as well as by a course instructor to assess the students in their portfolio
design in a fully automated and convenient manner, with results conveniently
formatted in tables and plots. Each portfolio design is easily defined as a
function that takes as input a window of the stock prices and outputs the
portfolio weights. Multiple portfolios can be easily specified as a list
of functions or as files in a folder. Multiple datasets can be conveniently
extracted randomly from different markets, different time periods, and
different subsets of the stock universe. The results can be later assessed
and ranked with tables based on a number of performance criteria (e.g.,
expected return, volatility, Sharpe ratio, drawdown, turnover rate, return
on investment, computational time, etc.), as well as plotted in a number of
ways with nice barplots and boxplots.
Authors@R: c(
person(c("Daniel", "P."), "Palomar", role = c("cre", "aut"), email = "daniel.p.palomar@gmail.com"),
person("Rui", "Zhou", role =  "aut", email = "rzhouae@connect.ust.hk")
)
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>
URL: https://CRAN.R-project.org/package=portfolioBacktest,
https://github.com/dppalomar/portfolioBacktest
BugReports: https://github.com/dppalomar/portfolioBacktest/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: digest, evaluate, ggplot2, pbapply, PerformanceAnalytics,
parallel, quadprog, quantmod, R.utils, rlang, stats, utils,
xts, zoo
Suggests: CVXR, DT, ggfortify, gridExtra, knitr, prettydoc, readtext,
rmarkdown, R.rsp, scales, stringi, testthat
VignetteBuilder: knitr, rmarkdown, R.rsp
NeedsCompilation: no
Packaged: 2022-04-22 02:21:55 UTC; palomar
Author: Daniel P. Palomar [cre, aut],
Rui Zhou [aut]
Repository: CRAN
Date/Publication: 2022-04-22 08:30:09 UTC