國立政治大學統計學系
學 術 演 講
主講人：林良靖 教授 (國立成功大學統計學系)學 術 演 講
題 目：LIMOS – LightGBM Interval Merton’s One-period-portfolio Selection
時 間：民國114年2月17日 (星期一) 下午1：30
地 點：國立政治大學逸仙樓050101教室
摘 要：
The modern portfolio theory can assist us in allocating wealth to risky and risk-free assets reasonably by using some statistical methods. In this study, we will focus on evolving Merton’s portfolio problem. Instead of the conventional parameter estimations based on only the closing prices, we include the opening, high, low, and closing prices to enlarge the database as much as possible to make the parameter estimations much more accurate. Furthermore, the covariances are estimated using the bivariate symbolic interval-valued variables under a copula function. In addition, we use the LightGBM to predict the transaction directions in which the prices and many statistics are included in the features. In real data analysis, we demonstrate the usefulness of combining the aforementioned methods by showing the portfolio profits of selecting 10 stocks in 2018 and 2019. The results particularly show the superiority of the proposed strategy over the conventional method: the profits are almost positive and have around 50% to 117% annually.
Keywords: LightGBM; Merton’s portfolio problem; Symbolic interval-valued estimation.