Compensating asynchrony effects in the calculation of financial correlations
We present a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards smaller return intervals (Epps effect). We show that this statistical effect is a major cause of the Epps effect. Hence, we are able to quantify and to compensate it using only trading prices and trading times.
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- Giovanni Bonanno & Fabrizio Lillo & Rosario N. Mantegna, 2000.
"High-frequency Cross-correlation in a Set of Stocks,"
cond-mat/0009350, arXiv.org, revised Nov 2000.
- G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
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