Cross-Correlation Measures in the High-Frequency Domain
19 Pages Posted: 9 Nov 2005
Date Written: October 28, 2005
Abstract
On a high-frequency scale, financial time series are not homogeneous, therefore standard correlation measures can not be directly applied to the raw data. To deal with this problem the time series have to be either homogenized through interpolation or methods that can handle raw non-synchronous time series need to be employed. This paper compares two traditional methods that use interpolation with an alternative method applied directly to the actual time series. The three methods are tested on simulated data and actual trades time series. The temporal evolution of the correlation matrix is revealed through the analysis of the full correlation matrix and of the Minimum Spanning Tree representation. To perform the analysis we implement several measures from the theory of random weighted networks.
Keywords: High-Frequency Correlation, Fourier method, Epps Effect, Minimum Spanning Tree, random networks
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Modeling and Forecasting Realized Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
Modeling and Forecasting Realized Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
The Distribution of Realized Exchange Rate Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
The Distribution of Exchange Rate Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
The Distribution of Exchange Rate Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
The Distribution of Stock Return Volatility
By Torben G. Andersen, Tim Bollerslev, ...
-
By Torben G. Andersen, Tim Bollerslev, ...
-
Range-Based Estimation of Stochastic Volatility Models
By Sassan Alizadeh, Michael W. Brandt, ...
-
By Torben G. Andersen, Tim Bollerslev, ...
-
By Torben G. Andersen, Tim Bollerslev, ...