The Application of genetic algorithms for the selection of WSE companies in Warsaw for the investment portfolio.

B. Basiura, Joanna Motyczyńska
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Abstract

Portfolio analysis is a tool particularly intended for investors. Risk assessment and risk specification make the investor able to properly diversify and offset the portfolio. Broadly speaking, there are multiple tools destined for building up an efficient set of portfolios.One of them is Markowitz’s model theory postulating building up a portfolio determined on the basis of equilibrium between expected profit level as well as accepted level of risk assessment.In the context of this paper, the objective is to shed some light on creating investment portfolios based on either Markowitz's portfolio theory or evolutionary algorithm. The simulation based methods for building up a portfolio of approximately 40-50 companies listed out in the primary marketof the Warsaw Stock Exchange using the selection function proposed in the BA thesis were presented.Portfolio profit values have been evaluated in a dynamically shifted time window. The conducted analysis showed shifts in the economy at certain periods of time. The implemented genetic algorithms smoothly handled the optimization with a relatively short processing time of the task result.
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遗传算法在华沙WSE公司投资组合选择中的应用。
投资组合分析是一种专门为投资者设计的工具。风险评估和风险说明使投资者能够适当地分散和抵消投资组合。广义地说,有多种工具注定要建立一套有效的投资组合。其中之一是马科维茨的模型理论,假设在预期利润水平和可接受的风险评估水平之间的均衡的基础上建立一个投资组合。在本文的背景下,目标是根据马科维茨的投资组合理论或进化算法来创建投资组合。提出了基于模拟的方法,利用BA论文中提出的选择函数,建立了在华沙证券交易所主要市场上市的约40-50家公司的投资组合。投资组合的利润价值在一个动态变化的时间窗口中被评估。所进行的分析显示了经济在某些时期的变化。所实现的遗传算法以较短的任务结果处理时间平稳地处理了优化问题。
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