Data compression techniques for stock market prediction
Publication
, Journal Article
Azhar, S; Badros, GJ; Glodjo, A; Kao, MY; Reif, JH
Published in: Proceedings of the Data Compression Conference
January 1, 1994
This paper presents advanced data compression techniques for predicting stock markets behavior under widely accepted market models in finance. Our techniques are applicable to technical analysis, portfolio theory, and nonlinear market models. We find that lossy and lossless compression techniques are well suited for predicting stock prices as well as market modes such as strong trends and major adjustments. We also present novel applications of multispectral compression techniques to portfolio theory, correlation of similar stocks, effects of interest rates, transaction costs and taxes.
Duke Scholars
Published In
Proceedings of the Data Compression Conference
Publication Date
January 1, 1994
Start / End Page
72 / 82
Citation
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Azhar, S., Badros, G. J., Glodjo, A., Kao, M. Y., & Reif, J. H. (1994). Data compression techniques for stock market prediction. Proceedings of the Data Compression Conference, 72–82.
Azhar, S., G. J. Badros, A. Glodjo, M. Y. Kao, and J. H. Reif. “Data compression techniques for stock market prediction.” Proceedings of the Data Compression Conference, January 1, 1994, 72–82.
Azhar S, Badros GJ, Glodjo A, Kao MY, Reif JH. Data compression techniques for stock market prediction. Proceedings of the Data Compression Conference. 1994 Jan 1;72–82.
Azhar, S., et al. “Data compression techniques for stock market prediction.” Proceedings of the Data Compression Conference, Jan. 1994, pp. 72–82.
Azhar S, Badros GJ, Glodjo A, Kao MY, Reif JH. Data compression techniques for stock market prediction. Proceedings of the Data Compression Conference. 1994 Jan 1;72–82.
Published In
Proceedings of the Data Compression Conference
Publication Date
January 1, 1994
Start / End Page
72 / 82