The study aims to address the limitations of modern portfolio theory (MPT) in asset selection by developing a risk-centric, multi-criteria decision-making approach. By incorporating additional risks such as fat-tail risk and skewness, as well as investor preferences and macroeconomic factors, the study offers an improved and pragmatic framework for asset selection in real-world financial markets.
The study employs a fuzzy multi-criteria decision-making methodology, using the Choquet integral to evaluate assets across eight global markets. It combines quantitative criteria (return, risk) with qualitative factors (investor preferences, macroeconomic conditions). Investor profiles are developed, and fuzzy trapezoidal numbers are used to quantify linguistic evaluations. The study tests six different investor profiles, ranking assets based on each profile's unique risk-return preferences, demonstrating the method's adaptability to varied investment strategies.
We find that the proposed approach augments MPT by accommodating heterogeneous investor preferences and incorporating non-conventional risks. Different investor profiles result in varied optimal asset allocations, suggesting that a sole focus on risk-return measures may not be sufficient and that integrating behavioral and macroeconomic factors leads to more personalized and effective investment strategies.
The study offers practical implications for financial institutions, particularly in improving investor profiling and aligning asset recommendations with individual preferences. This approach enhances personalized wealth management and aids in regulatory compliance, offering a robust framework for portfolio strategies that can adapt to market changes and diverse investor behaviors.
This study offers a novel contribution to asset selection by integrating a fuzzy multi-criteria decision-making model that accounts for investor heterogeneity, nonconventional risks (skewness and kurtosis) and macroeconomic factors. Unlike traditional models that rely solely on risk-return trade-offs, this approach provides a more holistic and practical solution, aligning investment strategies with real-world investor preferences.
This study significantly contributes to the purpose of multi-dimensional decision making by advancing a behavioral concept called “suitability modeling.”
A model has been proposed based on fuzzy Choquet integral methodology for asset selection to address the limitations of modern portfolio theory.
The model considers idiosyncratic characteristics of financial assets, heterogeneous personal and behavioral preferences of individual investors and the interdependencies among choice variables.
Fat tail and skewness risk in addition to the conventional risk measures of Modern Portfolio Theory are investigated.
Heterogeneous risk profiles of investors with considerably different sensitivities/preferences toward the risk, return and other decision variables have been simulated.
