Using a Stochastic Complexity Measure to Check the Efficient Market Hypothesis

Computational Economics

Volumn 22, Issue 2-3, 2003, Pages 273-284

  Shmilovici, Armin ^a   Alon Brimer, Yael ^a   Hauser, Shmuel ^a  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

context tree; stochastic complexity; the Efficient Market Hypothesis

Indexed keywords

EID: 84867924938     PISSN: 09277099     EISSN: 15729974     Source Type: Journal    
DOI: 10.1023/A:1026198216929     Document Type: Article

References (13)

1. Alon-Brimer, Y. (2002). Measuring the efficiency of the Israeli stock market by the context tree model. M. A. dissertation (in Hebrew), School of Management, Ben-Gurion University, Israel.
2. Chen, S.-H. and Tan, C.-W. (1999). Estimating the complexity function of financial time series: an estimation based on predictive stochastic complexity. Proc. of the 5th Int. Conference of the Society for Computational Economics, Boston, June 24-26.
3. Chen, S.-H. and Tan, C.-W. (1996). Measuring randomness by Rissanen's stochastic complexity: applications to the financial data. In D. L. Dowe, K. B. Korb and J. J. Oliver (eds.), Information, Statistics and Induction in Science, World Scientific, Singapore.
4. Fama, E. F. (1991). Efficient capital markets: II. Journal of Finance, 46, 1575-1611.
5. Feder, M., Merhav, N. and Gutman, M. (1992). Universal prediction of individual sequences. IEEE Transactions on Information Theory, 38(4), 1258-1270.
6. Hellstrom, T. and Holmstrom, K. (1998). Predicting the stock market. Technical Report Ima-TOM-1997-07, Umea University, Sweden. Available on the web.
7. Merhav, N. and Feder, M. (1998). Universal prediction. Invited Paper, Special Commemorative issue of the IEEE Transactions on Information Theory, celebrating 50 years of Information Theory, IT-44, pp. 2124-2147.
8. Rissanen, J. (1983). A universal data compression system. IEEE Transactions on Information Theory, 29(5), 656-664.
9. Rissanen, J. (1989). Stochastic Complexity in Statistical Inquiry. World Scientific, Singapore.
10. Weinberger, M., Rissanen, J. and Feder, M. (1995). A universal finite memory source. IEEE Transactions on Information Theory, 41(3), 643-653.
11. Willems, F. M. J., Shtarkov, Y. M. and Tjalkens, T. J. (1995). The context-tree weighting method: Basic properties. IEEE Trans. on Information Theory, 41(3), 653-664.
12. Willems, F. M. J., Shtarkov, Y. M. and Tjalkens, T. J. (1997). Reflections on the prize paper 'The context-tree weighting method: Basic properties'. In Newsletters of the IEEE.
13. Ziv, J. (2001). A universal prediction lemma and applications to universal data compression and prediction. IEEE Transactions on Information Theory, 47(4), 1528-1532.