Visual Representation of Mean-Variance-Skewness Model- An Empirical Study

• Main Authors: Miao-Yun Wei, 魏妙芸
• Other Authors: 巫亮全
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5230023%22.&searchmode=basic

碩士 === 國立中興大學 === 科技管理研究所 === 107 === The use of a mean-variance-skewness model in portfolio performance has increasingly been the object of studies on mathematical guidance in recent years. However, there are few specific methods in empirical studies. The purpose of this paper focuses on the practical research and visualization results in the mean-variance-skewness model. This study demonstrates that there will be portfolio options conditional on mean-variance-skewness than conditional on mean-variance. The paper studies a mean-variance-skewness model in the Standard & Poor’s 500(S&P 500) Stock Index log-return. To begin with, the study generates random asset weight combinations. Then, calculating weights to estimate the proportion of each company stock in the S&P 500 Index. In addition, computing means, standard deviations, and skewness of portfolio return according to weights. Last but not least, the study visualizes data generated by the 3-dimension chart. Furthermore, this research visualizes to reveal projections results. The study examine the influence on mean-variance by means of comparing different points. According to the weights assets allocations indicate that there is more risk diversification based on the mean-variance-skewness model than based on the mean-variance model. These results have implications for empirical research of mean-variance-skewness model and data visualization.