ארמין שמילוביץ

אקדמי בכיר

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

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

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.

שפת פרסום אנגלית
דפים 131-154
כתב עת Computational Economics
כרך 33
נושא מספר 2
סטטוס פרסום פורסם - 01.01.2009

Keywords

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

ASJC Scopus subject areas

Economics, Econometrics and Finance (miscellaneous)
Computer Science Applications
גישה למסמך
10.1007/s10614-008-9153-3
קבצים וקישורים אחרים
Link to publication in Scopus