Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm

Universal compression algorithms can detect recurring patterns in any type of temporal data—including financial data—for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable Order...

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Bibliographic Details
Published in:Computational economics Vol. 33; no. 2; pp. 131 - 154
Main Authors: Shmilovici, Armin, Kahiri, Yoav, Ben-Gal, Irad, Hauser, Shmuel
Format: Journal Article
Language:English
Published: Boston Springer US 01.03.2009
Society for Computational Economics
Springer Nature B.V
Series:Computational Economics
Subjects:
ISSN:0927-7099, 1572-9974
Online Access:Get full text
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Summary:Universal compression algorithms can detect recurring patterns in any type of temporal data—including financial data—for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable Order Markov (VOM) model and use it to test the weak form of the Efficient Market Hypothesis (EMH). The EMH is tested for 12 pairs of international intra-day currency exchange rates for one year series of 1, 5, 10, 15, 20, 25 and 30 min. Statistically significant compression is detected in all the time-series and the high frequency series are also predictable above random. However, the predictability of the model is not sufficient to generate a profitable trading strategy, thus, Forex market turns out to be efficient, at least most of the time.
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ISSN:0927-7099
1572-9974
DOI:10.1007/s10614-008-9153-3