# Realized Covariance: Two Timescales

### Description

Realized Covariance using a generalization of the popular two timescale variance method.

### Usage

1 | ```
rc.timescale(x, y, period, align.by="seconds", align.period = 1, adj.type = "classic", cts = TRUE, makeReturns = FALSE, ...)
``` |

### Arguments

`x` |
Tick data in xts object. |

`y` |
Tick data in xts object. |

`period` |
Sampling period |

`align.by` |
Align the tick data to seconds|minutes|hours |

`align.period` |
Align the tick data to this many [seconds|minutes|hours] |

`cts` |
Create calendar time sampling if a non realizedObject is passed |

`makeReturns` |
Prices are passed make them into log returns |

`adj.type` |
"classic", "adj" or "aa" |

`...` |
... |

### Details

Realized Covariance using two timescale method.

### Value

Realized covariance using two timescale method

### Author(s)

Scott Payseur <spayseur@u.washington.edu>

### References

L. Zhang, P.A Mykland, and Y. Ait-Sahalia. A tale of two time scales: Determining integrated volatility
with noisy high-frequency data. *Journal of the American Statistical Association*, 2005.

Michiel de Pooter, Martin Martens, and Dick van Dijk. Predicting the daily covariance matrix for sp100
stocks using intraday data - but which frequency to use? *Working Paper*, October 2005.

### See Also

`rv.timescale`

, `rRealizedVariance`

### Examples

1 2 3 4 |