### Abstract

The portfolio beta β_{p} is quite an important coefficient in modern portfolio theory since it efficiently measures portfolio volatility relative to the benchmark index or the capital market. β_{p} is usually employed for portfolio evaluation or prediction but scarcely for portfolio construction process. The main objective of this paper is to propose a portfolio algorithm that engages β_{p} in its portfolio construction process and studies its strengths. Our portfolio algorithm termed as β-G portfolio algorithm selects stocks based on their market capitalization and optimizes them in terms of the standard deviation of β_{p}. The optimizing process or finding optimal weights is done by the genetic algorithm. Our major findings on β-G portfolio algorithm are: (i) its performance depends on market volatility, i.e. it is expected to work well for a stable market whether it is bullish or bearish (ii) it tends to register outstanding performance for short-term applications.

Original language | English |
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Pages (from-to) | 527-534 |

Number of pages | 8 |

Journal | Expert Systems with Applications |

Volume | 30 |

Issue number | 3 |

DOIs | |

Publication status | Published - 2006 Apr 1 |

### All Science Journal Classification (ASJC) codes

- Engineering(all)
- Computer Science Applications
- Artificial Intelligence

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## Cite this

*Expert Systems with Applications*,

*30*(3), 527-534. https://doi.org/10.1016/j.eswa.2005.10.010