An Application of the Smart Beta Portfolio Model: An Empirical Study in Indonesia Stock Exchange

Abstract Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009–2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

摘要 股价波动会对投资者收益产生影响，在这场引发股市震荡的大流行病背景下尤为如此。受此影响，投资者更倾向于将资金转向更为稳健的投资组合。有鉴于此，本研究采用智能贝塔（smart beta）并结合其他方法构建高效投资组合模型，以得到一种可快速预测个股投资收益的方法。智能贝塔（smart beta）是一种通过考量投资者预设的收益与风险水平，快速且简洁地筛选出可纳入投资组合标的的方法。智能贝塔投资组合具备高效性，因其可跟踪基准指数，并采用主动型投资组合经理所使用的同类技术进行优化。本研究以2009年至2019年印度尼西亚证券交易所上市的100只低波动个股数据为基础，结合逻辑回归方法构建了高效投资组合模型。研究结论表明，高效投资组合由一组具备进取性且交易活跃的个股构成，可在长期周期内的既定风险水平下实现最优收益。此外，采用智能贝塔、贝塔（beta）、阿尔法（alpha）以及个股特征变量构建的投资组合选择模型，是一种可在调整风险水平的前提下快速预测收益率的简洁模型，能够帮助投资者预判风险并降低个股选择失误率。