JFE (version 2.5.6)

BurkeRatio: Burke ratio of the return distribution

Description

To calculate Burke ratio we take the difference between the portfolio return and the risk free rate and we divide it by the square root of the sum of the square of the drawdowns. To calculate the modified Burke ratio we just multiply the Burke ratio by the square root of the number of datas.

Usage

BurkeRatio(R, Rf = 0, modified = FALSE)

Arguments

R

an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns

Rf

the risk free rate

modified

a boolean to decide which ratio to calculate between Burke ratio and modified Burke ratio.

Author

Ho Tsung-wu <[e-mail]>, College of Management, National Taiwan Normal University.

Details

$$Burke Ratio = \frac{r_P - r_F}{\sqrt{\sum^{d}_{t=1}{D_t}^2}}$$

$$Modified Burke Ratio = \frac{r_P - r_F}{\sqrt{\sum^{d}_{t=1}\frac{{D_t}^2}{n}}}$$

where \(n\) is the number of observations of the entire series, \(d\) is number of drawdowns, \(r_P\) is the portfolio return, \(r_F\) is the risk free rate and \(D_t\) the \(t^{th}\) drawdown.

References

Carl Bacon, Practical portfolio performance measurement and attribution, second edition 2008 p.90-91.
See aslo package PerformanceAnalytics.

Examples

  data(assetReturns)
	assetReturns=assetReturns["2011::2018"] #short sample for fast example
  BurkeRatio(assetReturns,Rf=0)