Genetic Algorithms: Genesis of Stock Evaluation

Economics WPA Working Paper No. 0404007

17 Pages Posted: 26 Apr 2004

See all articles by Rama Prasad Kanungo

Rama Prasad Kanungo

Newcastle University London; University of Newcastle

Date Written: March 2004

Abstract

The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many optimisation models that have subsequently addressed much of the scepticism. In this paper the author proposes a methodology based on Genetic Algorithms and individual data maximum likelihood estimation using logit model arguing that forecasting discrepancy can be rationalised by combined approximation of both the approaches. Thus this paper offers a methodological overture to further investigate the anomalies surrounding stock market. In the main, this paper attempts to provide a temporal dimension of the methods transposed on recurrent series of data over a fixed window conjecture.

Keywords: Genetic Algorithms, Individual Maximum Likelihood Estimation, Share Price

JEL Classification: C5, C9, C53

Suggested Citation

Kanungo, Rama Prasad, Genetic Algorithms: Genesis of Stock Evaluation (March 2004). Economics WPA Working Paper No. 0404007, Available at SSRN: https://ssrn.com/abstract=535242 or http://dx.doi.org/10.2139/ssrn.535242

Rama Prasad Kanungo (Contact Author)

Newcastle University London ( email )

Middlesex Street
London, E1 7EZ
United Kingdom

University of Newcastle

Middlesex Street
London, E1 7EZ
United Kingdom

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