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.
Original language | English |
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Pages (from-to) | 131-154 |
Number of pages | 24 |
Journal | Computational Economics |
Volume | 33 |
Issue number | 2 |
DOIs | |
State | Published - 1 Jan 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