Forecasting with a Universal Data Compression Algorithm: The Forex Market Case

Armin Shmilovici Leib, Yoav Kahiri, Shmuel Hauser

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We use the context tree algorithm of Rissanen, for compression and prediction of time series. The weak form of 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 minutes. Statistically significant compression is detected in all the time-series, yet, the Forex market turns out to be efficient most of the time, and the short periods of inefficiency are not sufficient generating excess profit.
Original languageEnglish
Title of host publicationInternational Conference of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004)
EditorsTheodore Simos, George Maroulis
Number of pages4
Edition1
StatePublished - 2019

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