JarqueBeraBacktest {Dowd} | R Documentation |

## Jarque-Bera backtest for normality.

### Description

Jarque-Bera (JB) is a backtest to test whether the skewness and kurtosis of a given sample matches that of normal distribution. JB test statistic is defined as

`JB=\frac{n}{6}\left(s^2+\frac{(k-3)^2}{4}\right)`

where
`n`

is sample size, `s`

and `k`

are coefficients of sample
skewness and kurtosis.

### Usage

```
JarqueBeraBacktest(sample.skewness, sample.kurtosis, n)
```

### Arguments

`sample.skewness` |
Coefficient of Skewness of the sample |

`sample.kurtosis` |
Coefficient of Kurtosis of the sample |

`n` |
Number of observations |

### Value

Probability of null hypothesis H0

### Author(s)

Dinesh Acharya

### References

Dowd, Kevin. Measuring Market Risk, Wiley, 2007.

Jarque, C. M. and Bera, A. K. A test for normality of observations and regression residuals, International Statistical Review, 55(2): 163-172.

### Examples

```
# JB test statistic for sample with 500 observations with sample
# skewness and kurtosis of -0.075 and 2.888
JarqueBeraBacktest(-0.075,2.888,500)
```

[Package

*Dowd*version 0.12 Index]