Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection

Masafumi Nakano, Akihiko Takahashi and Soichiro Takahashi
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Masafumi Nakano: Graduate School of Economics, The University of Tokyo
Akihiko Takahashi: Faculty of Economics, The University of Tokyo
Soichiro Takahashi: Graduate School of Economics, The University of Tokyo

No CIRJE-F-1037, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: This paper proposes a new fuzzy logic (FL)-based expert system with particle filtering and anomaly detection to create high-performance investment portfolios. In particular, our FL system selects a portfolio with fine risk-return profiles from a number of candidates by integrating multilateral performance measures including Sharpe, Sortino and Sterling ratios. The candidates consist of various mean-variance portfolios with multiple time-series models estimated by a particle filter and anomaly detectors. In an out-of-sample numerical experiment with a dataset of international financial assets, we demonstrates our expert system successfully generates a series of mean-variance portfolios with satisfactory investment records.

Pages: 19 pages
Date: 2017-02
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Citations: View citations in EconPapers (18)

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