Broad Asset Portfolio Designed Based on the Mean-Variance Model

Abstract

Contemporarily, broad asset class allocation has gradually become an ideal investment strategy for investors and institutions. This paper constructs the optimal asset class allocation and portfolio design with python based on the mean-variance model, using stocks, gold, crude oil, bonds, futures, foreign exchange, funds, commodities, digital currencies and treasury bonds as the main underlying assets. To compare the asset allocation portfolios constructed by different approaches (the equally weighted investment model, the minimum variance model and the maximum Sharpe ratio model), the comparative analysis is implemented in terms of five indicators, including the annualised return, annualised volatility, Sharpe ratio, maximum drawdown and return-to-drawdown ratio. After the comparison, the advantages of the maximum Sharpe ratio model are demonstrated. According to the results, the mean-variance model, as a risk management model from the investor’s perspective, is consistent with the investment logic of investors and financial institutions that it outperforms the traditional minimum variance model and equally weighted model in terms of profitability and risk control. Therefore, the mean-variance model has certain theoretical guidance for broad asset class allocation. Overall, these results shed light on portfolio designed for investments.