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

Authors:
Armin Shmilovici;Yoav Kahiri;Irad Ben-Gal;Shmuel Hauser
Affiliations:
Department of Information Systems, Ben-Gurion University, Beer-Sheva, Israel 84105;School of Management, Ben-Gurion University, Beer-Sheva, Israel 84105;Department of Industrial Engineering, Tel-Aviv University, Ramat-Aviv, Tel-Aviv, Israel 69978;ONO Academic College and School of Management, Ben-Gurion University, Beer-Sheva, Israel 84105
Venue:
Computational Economics
Year:
2009

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Abstract

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.