A Multi Criteria Decision Making Approach To Rank Alternative Investment Indices Based On Their Performance

Abstract

The selection of the ideal Alternative Investment product has been a major challenge for all investors across the world. This is because of the dynamic ever-changing financial market and the complex trade-offs between risk and return. This complexity comes from the diverse characteristics of alternative investments, where products offering high returns often come with increased volatility, while safer options provide relatively lower returns. Hence, we have adopted a Multi-Criteria Decision-Making (MCDM) model to identify the optimal investment product.  

In this study, we analyse the performance of eight alternative investment products (AIPs) — including S&P 500, Hedge Funds, Venture Capital, Private Equity, US Government Bonds, MSCI Emerging Markets, FTSE EPRA/NAREIT, and S&P GSCI Commodity — using three widely accepted MCDM methods: COPRAS (Complex Proportional Assessment), SAW (Simple Additive Weighting), and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The decision matrix incorporates critical performance metrics such as Standard Deviation, Mean Return, Skewness, Kurtosis, Beta, Sharpe Ratio, Sortino Ratio, and Calmar Ratio. 

To assign weights to these criteria we used the Analytic Hierarchy Process (AHP) to ensure a balanced evaluation. The rankings generated by these methods are often a little different, that is why we used a hybrid-ranking approach through Spearman’s Rank Correlation to consolidate the final rankings. 

Our findings indicate that Hedge Funds and Venture Capital emerge as the most attractive options for investors seeking high returns, while US Government Bonds and FTSE EPRA/NAREIT provide safer alternatives with lower volatility. This MCDM framework offers investors a systematic and efficient method to evaluate and rank AIPs to make informed decisions in this complex financial landscape.