Fuzzy logic-based portfolio selection with particle filtering and anomaly detection
نویسندگان
چکیده
This paper proposes a new knowledge-based system (KBS) featuring fuzzy logic (FL) 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. The candidates consist of various portfolios based on multiple time-series models estimated by a particle filter with anomaly detectors. In an out-of-sample numerical experiment with a dataset of international financial assets, we demonstrate our KBS successfully generates a series of selected portfolios with satisfactory investment records.
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عنوان ژورنال:
- Knowl.-Based Syst.
دوره 131 شماره
صفحات -
تاریخ انتشار 2017