wrapper function for combining arbitrary function list into a table

Description

This function creates a table of statistics from vectors of functions and labels passed in. The resulting table is formatted such that metrics are calculated separately for each column of returns in the data object.

Assumes an input of period returns. Scale arguements can be used to specify the number of observations during a year (e.g., 12 = monthly returns).

Usage

table.Arbitrary(R, metrics = c("mean", "sd"), metricsNames = c("Average Return", "Standard Deviation"), ...)
statsTable(R, metrics = c("mean", "sd"), metricsNames = c("Average Return", "Standard Deviation"), ...)

Arguments

Details

The idea here is to be able to pass in sets of metrics and values, like:

metrics = c(DownsideDeviation(x,MAR=mean(x)), sd(subset(x,x>0)), sd(subset(x,x<0)), DownsideDeviation(x,MAR=MAR), DownsideDeviation(x,MAR=Rf=0), DownsideDeviation(x,MAR=0),maxDrawdown(x))

metricsNames = c("Semi Deviation", "Gain Deviation", "Loss Deviation", paste("Downside Deviation (MAR=",MAR*scale*100,"%)", sep=""), paste("Downside Deviation (rf=",rf*scale*100,"%)", sep=""), paste("Downside Deviation (0%)", sep=""), "Maximum Drawdown" )

Here's how it's working right now: > table.Arbitrary(monthlyReturns.ts,metrics=c("VaR","mean"), metricsNames=c("modVaR","mean"),p=.95)

           Actual   S&P500TR
modVaR 0.04186461 0.06261451
mean   0.00945000 0.01013684

Passing in two different sets of attributes to the same function doesn't quite work currently. The issue is apparent in: > table.Arbitrary(edhec,metrics=c("VaR", "VaR"), metricsNames=c("Modified VaR","Traditional VaR"), modified=c(TRUE,FALSE))

                Convertible.Arbitrage CTA.Global Distressed.Securities
Modified VaR               0.04081599  0.0456767             0.1074683
Traditional VaR            0.04081599  0.0456767             0.1074683
                Emerging.Markets Equity.Market.Neutral Event.Driven
Modified VaR           0.1858624            0.01680917    0.1162714
Traditional VaR        0.1858624            0.01680917    0.1162714
                Fixed.Income.Arbitrage Global.Macro Long.Short.Equity
Modified VaR                 0.2380379   0.03700478        0.04661244
Traditional VaR              0.2380379   0.03700478        0.04661244
                Merger.Arbitrage Relative.Value Short.Selling Funds.of.Funds
Modified VaR          0.07510643     0.04123920     0.1071894     0.04525633
Traditional VaR       0.07510643     0.04123920     0.1071894     0.04525633

In the case of this example, you would simply call VaR as the second function, like so: > table.Arbitrary(edhec,metrics=c("VaR", "VaR"),metricsNames=c("Modified VaR","Traditional VaR"))

                Convertible.Arbitrage CTA.Global Distressed.Securities
Modified VaR               0.04081599 0.04567670            0.10746831
Traditional VaR            0.02635371 0.04913361            0.03517855
                Emerging.Markets Equity.Market.Neutral Event.Driven
Modified VaR          0.18586240            0.01680917   0.11627142
Traditional VaR       0.07057278            0.01746554   0.03563019
                Fixed.Income.Arbitrage Global.Macro Long.Short.Equity
Modified VaR                0.23803787   0.03700478        0.04661244
Traditional VaR             0.02231236   0.03692096        0.04318713
                Merger.Arbitrage Relative.Value Short.Selling Funds.of.Funds
Modified VaR          0.07510643     0.04123920     0.1071894     0.04525633
Traditional VaR       0.02510709     0.02354012     0.0994635     0.03502065

Author(s)

Peter Carl

Examples

data(edhec)
table.Arbitrary(edhec,metrics=c("VaR", "ES"),metricsNames=c("Modified VaR","Modified Expected Shortfall"))