A Study of Genetic-based Optimization Strategy for Value Averaging Investment
| Autor: | Xsiang-Jui Wu, 吳祥睿 |
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| Rok vydání: | 2013 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 Value averaging is an alternative investment strategy for the well-known dollar cost averaging strategy. The traditional model for value averaging is operated by maintaining a pre-determined level of value-in-asset through periodic investments of fixed time intervals, which appears to be lacking the advantage of explicit market timing for trading. In this thesis we present a dynamic model for value averaging to improve its traditional static version. Our proposed methodology includes two major aspects: (1) we employ various technical indicators for market timing of investment, and (2) we use the class of Genetic Algorithms (GA) to determine optimal entry and exit points of our system. Our empirical results show that the optimization through the GA is effective in generating dynamic value averaging models that outperform the traditional ones. We thus expect this proposed methodology to advance the current state of GA research for investment. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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