PCAVaR {Dowd} | R Documentation |

## Estimates VaR by principal components analysis

### Description

Estimates the VaR of a multi position portfolio by principal components analysis, using chosen number of principal components and a specified confidence level or range of confidence levels.

### Usage

```
PCAVaR(Ra, position.data, number.of.principal.components, cl)
```

### Arguments

`Ra` |
Matrix return data set where each row is interpreted as a set of daily observations, and each column as the returns to each position in a portfolio |

`position.data` |
Position-size vector, giving amount invested in each position |

`number.of.principal.components` |
Chosen number of principal components |

`cl` |
Chosen confidence level |

### Value

VaR

### Author(s)

Dinesh Acharya

### References

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

### Examples

```
# Computes PCA VaR
Ra <- matrix(rnorm(4*6),4,6)
position.data <- rnorm(6)
PCAVaR(Ra, position.data, 2, .95)
```

[Package

*Dowd*version 0.12 Index]