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Woehrmann, Peter; Hens, Thorsten (2007). Strategic asset allocation and market timing: a reinforcement learning approach. Computational Economics, 29(3-4):369-381.
We apply the recurrent reinforcement learning method of Moody, Wu, Liao, and Saffell (1998) in the context of the strategic asset allocation computed for sample data from US, UK, Germany, and Japan. It is found that the optimal asset allocation deviates substantially from the fixed-mix rule. The investor actively times the market and he is able to outperform it consistently over the almost two decades we analyze.
| Item Type: | Journal Article, refereed, original work |
|---|---|
| Communities & Collections: | 03 Faculty of Economics > Department of Finance |
| Dewey Decimal Classification: | 330 Economics |
| Scopus Subject Areas: | Social Sciences & Humanities > Economics, Econometrics and Finance (miscellaneous)
Physical Sciences > Computer Science Applications |
| Scope: | Discipline-based scholarship (basic research) |
| Language: | English |
| Date: | 1 May 2007 |
| Deposited On: | 17 Jul 2014 10:25 |
| Last Modified: | 03 Aug 2024 03:30 |
| Publisher: | Springer |
| ISSN: | 0927-7099 |
| OA Status: | Green |
| Publisher DOI: | https://doi.org/10.1007/s10614-006-9064-0 |
| Official URL: | http://link.springer.com/article/10.1007/s10614-006-9064-0 |
| Other Identification Number: | merlin-id:3559 |
Woehrmann, Peter