Abstract
This paper presents a method of portfolio selection for reducing co-related risks. Differing from the Markowitz’s mean-variance framework, we use the joint probability of co-movement of multi-assets (JPCM) as a measure of risks, and under the condition of minimizing the JPCM, we pinpoint the optimal portfolio by optimizing the JPCM matrix of paired assets. At the same time, we use the shape parameter of generalized error distribution (GED) to measure the tail shapes of different portfolios. The empirical results for China’s stock market show that the JPCM portfolios significantly outperform naive-diversified portfolios (1/N-rule) and minimum-variance (MV) in terms of the tail shape of portfolio distribution.
Highlights
Differing from the Markowitz’s mean-variance framework, we use the joint probability of co-movement of multi-assets (JPCM) as a measure of risks, and under the condition of minimizing the JPCM, we pinpoint the optimal portfolio by optimizing the JPCM matrix of paired assets
Portfolio selection and optimization has been a fundamental problem in finance ever since Markowitz laid down the ground-breaking work that formed the foundation of what is popularly known as Modern Portfolio Theory [1]
When optimizing JPCM matrix during two periods, we set the same risk aversion coefficient α to 0.001 (α = 0.001), calculated the JPCM matrix, optimized the weight of portfolios according to Equation (12)
Summary
Portfolio selection and optimization has been a fundamental problem in finance ever since Markowitz laid down the ground-breaking work that formed the foundation of what is popularly known as Modern Portfolio Theory [1]. Markowitz posed the mean-variance analysis by solving a quadratic optimization problem. This approach has had a profound impact on the financial economics and is a milestone of modern finance. There are documented facts that the Markowitz portfolio is very sensitive to errors in the estimates of the inputs. The allocation vector that we get based on the empirical data can be very different from the allocation vector we want based on the theoretical inputs [2]
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