Abstract
The objective of on-line portfolio selection is to design provably good algorithms with respect to some on-line or offline benchmark. Existing algorithms do not consider ‘trading risk’. We present a novel risk-adjusted portfolio selection algorithm (RAPS). RAPS incorporates the ‘trading risk’ in terms of the maximum possible loss. We show that RAPS performs provably ‘as well as’ the Universal Portfolio (UP) [4] in the worst-case. We empirically evaluate RAPS on historical NYSE data. Results show that RAPS is able to beat BCRP as well as several ‘follow-the-winner’ algorithms from the literature, including UP. We conclude that RAPS outperforms in case the assets in the portfolio follow a positive trend.
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© 2014 Springer International Publishing Switzerland
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Dochow, R., Mohr, E., Schmidt, G. (2014). Risk-Adjusted On-line Portfolio Selection. In: Huisman, D., Louwerse, I., Wagelmans, A. (eds) Operations Research Proceedings 2013. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-07001-8_16
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DOI: https://doi.org/10.1007/978-3-319-07001-8_16
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