Armin Shmilovici Leib

Senior Academic

Using a Stochastic Complexity Measure to Check the Efficient Market Hypothesis

Armin Shmilovici, Yael Alon-Brimer, Shmuel Hauser

The weak form of the Efficient Market Hypothesis (EMH) states that current market price reflects fully the information from past prices and rules out prediction based on price data alone. No recent test of time series of stock returns rejects this weak-form hypothesis. This research offers another test of the weak form of the EHM that leads to different conclusions for some time series.The stochastic complexity of a time series is a measure of the number of bits needed to represent and reproduce the information in the time series. In an efficient market, compression of the time series is not possible, because there are no patterns and the stochastic complexity is high. In this research, Rissanen's context tree algorithm is used to identify recurring patterns in the data, and use them for compression. The weak form of the EMH is tested for 13 international stock indices and for all the stocks that comprise the Tel-Aviv 25 index (TA25), using sliding windows of 50, 75, and 100 consecutive daily returns. Statistically significant compression is detected in ten of the international stock index series. In the aggregate, 60% to 84% of the TA25 stocks tested demonstrate compressibility beyond randomness. This indicates potential market inefficiency.

Publication language English
Pages 273-284
Journal Computational Economics
Volume 22
Issue number 2-3
Publication status Published - 01.12.2003

Keywords

context tree
stochastic complexity
the Efficient Market Hypothesis

ASJC Scopus subject areas

Economics, Econometrics and Finance (miscellaneous)
Computer Science Applications
Access to Document
10.1023/A:1026198216929
Other files and links
Link to publication in Scopus