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portfolioBacktest  

Automated Backtesting of Portfolios over Multiple Datasets
View on CRAN: Click here


Download and install portfolioBacktest package within the R console
Install from CRAN:
install.packages("portfolioBacktest")

Install from Github:
library("remotes")
install_github("cran/portfolioBacktest")

Install by package version:
library("remotes")
install_version("portfolioBacktest", "0.4.1")



Attach the package and use:
library("portfolioBacktest")
Maintained by
Daniel P. Palomar
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-19
Latest Update: 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.
How to cite:
Daniel P. Palomar (2019). portfolioBacktest: Automated Backtesting of Portfolios over Multiple Datasets. R package version 0.4.1, https://cran.r-project.org/web/packages/portfolioBacktest. Accessed 05 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:43), 0.1.0 (2019-06-19 13:40), 0.1.1 (2019-07-06 00:10), 0.2.0 (2019-08-23 15:00), 0.2.1 (2019-10-07 17:20), 0.2.2 (2020-08-03 12:50), 0.2.3 (2021-01-12 09:50), 0.3.0 (2021-09-21 15:10), 0.3.1 (2021-10-17 22:00), 0.4.1 (2022-04-22 10:30)
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