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Portfolio
HF-MaxScore-Portfolio - Hesitant Fuzzy Maximum-Score Portfolio Selection (Zhou-Xu 2018)
Hesitant fuzzy portfolio selection model for general investors. Maximises the aggregated score s(⊗_i w_i h_i) of the hesitant fuzzy portfolio, where ⊗_i w_i h_i is the HFE-power-weighted combination of per-stock aggregated HFEs. Output is optimal investment weight vector W = (w_1,...,w_n) summing to 1. Equivalent to the hesitant fuzzy version of Markowitz's maximum-return portfolio (no risk constraint).
Zhou, W., Xu, Z.2018doi:10.1016/j.knosys.2017.12.020 ↗
Overview
HF-MaxScore-Portfolio is suitable for general investors who want maximum expected return without an explicit risk constraint. It replaces the need for historical return/variance data with subjective HFE evaluations from domain experts. The output is not a ranking but an investment proportion vector - a higher w_i means more capital allocated to stock i.
- Data
- Hesitant
- Weights
- Derived internally, no weight source needed
Edge cases and pitfalls
The HFE power-weighted combination ⊗_i w_i h_i can produce exponentially many elements (Π_i |h_i| values) - computational cost grows with HFE cardinality and number of stocks.
Without a deviation/risk constraint, the model may concentrate all weight on one stock (corner solution) - this is mathematically correct but economically undesirable.
Score s(h) only measures central tendency; for tail-risk-aware investors, use HF-TradeOff-Portfolio or EHVaR instead.
How to cite
Zhou, W.; Xu, Z. (2018). Portfolio selection and risk investment under the hesitant fuzzy environment. Knowledge-Based Systems. https://doi.org/10.1016/j.knosys.2017.12.020
System ID, as it appears in reports and the API
HF-MAXSCORE-PORT