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Automatic Trading Agent. RMT based Portfolio Theory and Portfolio Selection

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  • Malgorzata Snarska
  • Jakub Krzych

Abstract

Portfolio theory is a very powerful tool in the modern investment theory. It is helpful in estimating risk of an investor's portfolio, which arises from our lack of information, uncertainty and incomplete knowledge of reality, which forbids a perfect prediction of future price changes. Despite of many advantages this tool is not known and is not widely used among investors on Warsaw Stock Exchange. The main reason for abandoning this method is a high level of complexity and immense calculations. The aim of this paper is to introduce an automatic decision - making system, which allows a single investor to use such complex methods of Modern Portfolio Theory (MPT). The key tool in MPT is an analysis of an empirical covariance matrix. This matrix, obtained from historical data is biased by such a high amount of statistical uncertainty, that it can be seen as random. By bringing into practice the ideas of Random Matrix Theory (RMT), the noise is removed or significantly reduced, so the future risk and return are better estimated and controlled. This concepts are applied to the Warsaw Stock Exchange Simulator http://gra.onet.pl. The result of the simulation is 18 % level of gains in comparison for respective 10 % loss of the Warsaw Stock Exchange main index WIG.

Suggested Citation

  • Malgorzata Snarska & Jakub Krzych, 2006. "Automatic Trading Agent. RMT based Portfolio Theory and Portfolio Selection," Papers physics/0608293, arXiv.org.
  • Handle: RePEc:arx:papers:physics/0608293
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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
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    Cited by:

    1. Urbanowicz, Krzysztof & Richmond, Peter & Hołyst, Janusz A., 2007. "Risk evaluation with enhanced covariance matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 468-474.
    2. N. C. Suganya & G. A. Vijayalakshmi Pai, 2010. "Pareto‐archived evolutionary wavelet network for financial constrained portfolio optimization," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(2), pages 59-90, April.

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