Description Usage Arguments Details Author(s) References Examples

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.

1 | ```
BurkeRatio(R, Rf = 0, modified = FALSE, ...)
``` |

`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. |

`...` |
any other passthru parameters |

*Burke Ratio = (Rp - Rf)
/ (sqrt(sum(t=1..n)(Dt^2)))*

*Modified
Burke Ratio = (Rp - Rf) / (sqrt(sum(t=1..n)(Dt^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.

Matthieu Lestel

Carl Bacon, *Practical portfolio performance
measurement and attribution*, second edition 2008 p.90-91

1 2 3 4 5 6 7 8 9 | ```
data(portfolio_bacon)
print(BurkeRatio(portfolio_bacon[,1])) #expected 0.74
print(BurkeRatio(portfolio_bacon[,1], modified = TRUE)) #expected 3.65
data(managers)
print(BurkeRatio(managers['1996']))
print(BurkeRatio(managers['1996',1]))
print(BurkeRatio(managers['1996'], modified = TRUE))
print(BurkeRatio(managers['1996',1], modified = TRUE))
``` |

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