Measuring the efficiency of the intraday forex market with a universal data compression algorithm

Armin Shmilovici, Yoav Kahiri, Irad Ben-Gal, Shmuel Hauser

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


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.

Original languageEnglish
Pages (from-to)131-154
Number of pages24
JournalComputational Economics
Issue number2
StatePublished - 1 Jan 2009


  • Efficient Market Hypothesis
  • Forex Intra-day trading
  • Universal prediction
  • Variable Order Markov

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications


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