2023BCP Business & ManagementOpen access

Portfolio Construction Based on Mean Variance Portfolio Theory

Haokai Yin

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Abstract

Asset allocation is considered an important task and is highly regarded, people are eager to earn attractive profits through the correct allocation of investment assets. In this paper, an optimal portfolio of five stocks under different conditions is constructed to calculate and predict the expected return of this portfolio. When constructing a portfolio with equal weights for different underlying symbols, the Sharpe ratio is 1.14, which means that the portfolio return is higher than the volatility risk. Based on the evaluations, Tesla is more volatile, its yield has risen a lot recently. The efficient frontier is obtained by means of Monte-Carlo concepts with random weights arrangement. The results of two different cases with different optimal conditions are presented. In the end, the conclusion is that choose the portfolio with the largest Sharpe ratio, The risk premium per unit of risk is the highest, and it's worth it. Get a possible optimal investment portfolio by analyzing data, so that people can have a deeper understanding of asset allocation theory. Overall, these results offer new insights on portfolio construction and provide guidelines for construction of portfolio.

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Asset allocation is considered an important task and is highly regarded, people are eager to earn attractive profits through the correct allocation of investment assets. In this paper, an optimal portfolio of five stocks under different conditions is constructed to calculate and predict the expected return of this portfolio. When constructing a portfolio with equal weights for different underlying symbols, the Sharpe ratio is 1.14, which means that the portfolio return is higher than the volatility risk. Based on the evaluations, Tesla is more volatile, its yield has risen a lot recently. The efficient frontier is obtained by means of Monte-Carlo concepts with random weights arrangement. The results of two different cases with different optimal conditions are presented. In the end, the conclusion is that choose the portfolio with the largest Sharpe ratio, The risk premium per unit of risk is the highest, and it's worth it. Get a possible optimal investment portfolio by analyzing data, so that people can have a deeper understanding of asset allocation theory. Overall, these results offer new insights on portfolio construction and provide guidelines for construction of portfolio.

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Available abstract

Asset allocation is considered an important task and is highly regarded, people are eager to earn attractive profits through the correct allocation of investment assets. In this paper, an optimal portfolio of five stocks under different conditions is constructed to calculate and predict the expected return of this portfolio. When constructing a portfolio with equal weights for different underlying symbols, the Sharpe ratio is 1.14, which means that the portfolio return is higher than the volatility risk. Based on the evaluations, Tesla is more volatile, its yield has risen a lot recently. The efficient frontier is obtained by means of Monte-Carlo concepts with random weights arrangement. The results of two different cases with different optimal conditions are presented. In the end, the conclusion is that choose the portfolio with the largest Sharpe ratio, The risk premium per unit of risk is the highest, and it's worth it. Get a possible optimal investment portfolio by analyzing data, so that people can have a deeper understanding of asset allocation theory. Overall, these results offer new insights on portfolio construction and provide guidelines for construction of portfolio.

Key concepts: Portfolio, Efficient frontier, Post-modern portfolio theory, Black–Litterman model, Modern portfolio theory, Sharpe ratio, Portfolio optimization, Rate of return on a portfolio

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