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Detecting Intraday Periodicities with Application to High Frequency Exchange Rates

Chris Brooks and Melvin J. Hinich
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 55, No. 2 (2006), pp. 241-259
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/3592665
Page Count: 19
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Detecting Intraday Periodicities with Application to High Frequency Exchange Rates
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Abstract

Many recent papers have documented periodicities in returns, return volatility, bid-ask spreads and trading volume, in both equity and foreign exchange markets. We propose and employ a new test for detecting subtle periodicities in time series data based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8-h and 12-h frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule that is based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules can generate returns that are considerably greater than those of a buy-and-hold strategy, although they cannot retain their profitability net of transactions costs. We conjecture that this methodology could constitute an important tool for financial market researchers which will enable them to detect, quantify and rank the various periodic components in financial data better.

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