![]() ![]() See function CalculateReturns for calculating returns from prices, and be aware that the zoo library’s aggregate function has methods for tseries and zoo timeseries data classes to rationally coerce irregular data into regular data of the correct periodicity. Many library functions will work with regular data at different scales (e.g., daily, weekly, etc.) or irregular return data as well. Similar data could be constructed using mymanagers=read.csv("/path/to/file/mymanagers.csv", row.names=1), where the first column contains dates in the YYYY-MM-DD format.Ī quick sidenote: this library is applicable to return (rather than price) data, and has been tested mostly on a monthly scale. Monthly returns for all series end in December 2006 and begin at different periods starting from January 1996. As you can see, managers is a data frame that contains columns of monthly returns for six hypothetical asset managers (HAM1 through HAM6), the EDHEC Long-Short Equity hedge fund index, the S&P 500 total returns, and total return series for the US Treasury 10-year bond and 3-month bill. Other examples are available in the help pages of the functions described in the main page of PerformanceAnalytics.įirst we load the data used in all of the examples that follow. These examples are not intended to be complete, but they should provide an indication of the kinds of analysis that can be done. We focus on the graphs and tables, but comment on some other metrics along the way. This vignette provides a demonstration of some of the capabilities of PerformanceAnalytics. Our hope is that using such tools to uncover information and ask better questions will, in turn, create a more informed investor and help them ask better quality decisions. But what this library aspires to do is help the decision-maker accrete evidence organized to answer a specific question that is pertinent to the decision at hand. Investments must be made in context of investment objectives. There is no magic bullet here – there won’t be one right answer delivered in these metrics and charts. Our goal for PerformanceAnalytics is to make it simple for someone to ask and answer questions about performance and risk as part of a broader investment decision-making process. In particular, we have focused on functions that have appeared in the academic literature over the past several years, but had no functional equivalent in R. ![]() ![]() PerformanceAnalytics is a library of functions designed for evaluating the performance and risk characteristics of financial assets or funds. ![]()
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