Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2020.1842225
nvestment decision making based on the probabilistic hesitant financial data: model and empirical study
Wei Zhou
Man Liu
Zeshui Xu
Marinko Škare
Sažetak
This paper proposes a portfolio selection model from the perspective
of probabilistic hesitant financial data (PHFD). PHFD can be interpreted as the new form of information presentation that is obtained
by transforming real financial data into probabilistic hesitant fuzzy elements. Based on the above data and model, we can derive the optimal investment ratios and give suggestions for investors. Specifically,
this paper first develops a transformation algorithm to transform the
general share returns into PHFD. The transformed data can directly
show all the returns and their occurrence probabilities. Then, the
portfolio selection and risk portfolio selection models based on
PHFD, namely the probabilistic hesitant portfolio selection (PHPS)
model and the risk probabilistic hesitant portfolio selection (RPHPS)
model, are proposed. Furthermore, the investment decision-making
methods are provided to show their practical application in financial
markets. It is pointed out that the PHPS model for general investors
is constructed based on the maximum-score or minimum-deviation
principles to get the optimal investment ratios, and the RPHPS
model provides the optimal investment ratios for three types of risk
investors with the aim of obtaining the maximum return or taking
the minimum risk. Finally, an empirical study based on the real data
of China’s stock markets is shown in detail. The results verify the
effectiveness and practicability of the proposed methods.
Ključne riječi
Probabilistic hesitant financial data; portfolio selection; investment decision making; optimal investment ratio; China’s stock market
Hrčak ID:
301461
URI
Datum izdavanja:
31.12.2021.
Posjeta: 123 *