This study employs several methods to simulate and construct the portfolio from stock indexes of the six Association of Southeast Asian Nations (ASEAN) markets during the period from January 2001 to December 2017, namely, time-varying Copulas; Glosten, Jagannathan and Runkle (GJR); generalised autoregressive conditional heteroskedasticity (GARCH); extreme value theory (EVT); and conditional value at risk (CVaR). Our target is minimising the risk based on CVaR, then achieving the maximal expected return for investors. Our model also sheds further light on the role of the dependence structure among stock indexes by employing elliptical (student t) Copulas, which are incorporated for simulating the optimal portfolios. Our findings suggest that the investor should invest in the optimal portfolio, which lies in the efficiency curve. Hence, the optimal portfolio has similar time-varying characteristics across the dependence of Copulas, as well as confidence levels. The research implications can be employed practically by portfolio managers and individual investors who desire to invest in ASEAN equity markets. Therefore, our findings can draw investors' attention to constructing the portfolio with the dependence level via time-varying Copulas and minimise the risk represented by CVaR rather than traditional variance.

中文翻译：

---

Copulas-GJR-GARCH-EVT-CVAR模型的投资组合优化：来自东盟股票指数的经验证据

本研究采用几种方法从2001年1月至2017年12月的东南亚国家联盟（ASEAN）六个市场的股票指数（即时变的Copulas）中模拟和构建投资组合。Glosten，Jagannathan和Runkle（GJR）；广义自回归条件异方差（GARCH）；极值理论（EVT）；和条件风险价值（CVaR）。我们的目标是基于CVaR将风险降至最低，然后为投资者实现最大的预期收益。我们的模型还通过采用椭圆形（学生t）Copulas（其用于模拟最佳投资组合）进一步阐明了股票指数之间的依存结构的作用。我们的发现表明，投资者应投资于最佳组合，该组合位于效率曲线中。因此，最佳投资组合在Copulas的依赖关系和置信度上具有类似的时变特征。研究意义可以由希望在东盟股票市场上投资的投资组合经理和个人投资者采用。因此，我们的发现可以引起投资者的注意，即通过随时间变化的Copulas构建具有依赖水平的投资组合，并最大限度地降低CVaR代表的风险而不是传统的方差。