다양한 위험측정 모형을 이용한 최적자산 배분모형의 성과 비교 - 섹터 ETF상품을 이용한 실증분석
The Selection of Appropriate Risk Measuring Method in terms of the performance of the optimal asset allocation model - Empirical Analysis Using Sector ETFs in Korea Stock Market
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초록
최적 자산배분에서는 Markowitz(1952)의 평균-분산 모형 이후 많은 연구들이 진행되어 왔다. 특히 포트폴리오의 위험 측정에 관한 연구가 다양하게 발전해왔다. 본 논문은 분산 외에 LPM, CLPM, VaR, CVaR, minimax 등 다양한 위험지표를 이용하였을 경우 및 상관관계를 추정해야할 경우 표준분산공분산행렬과 DCC-MGARCH를 이용해 추정한 시간가변적 분산공분산행렬을 이용하였을 경우 달라지는 자산배분에 따른 포트폴리오의 성과를 위험대비 수익률의 측면에서 실증적으로 분석하였다. 2008.1.2.~2013.3.29의 기간에 대한 분석결과, 전기간에서 LPM, CLPM 등이 위험대비 수익률 측면에서 우수한 성과를 보여주었으나, 시장상황에 따른 국면별로는 다른 위험지표가 더 나은 성과를 보이기도 했으며, 분산 이외의 다양한 위험지표를 활용하여 섹터ETF를 운영할 경우 KOSPI지수에 비하여 위험대비 성과가 높음을 알수 있었다.
Abstract
Since Markowitz (1952) of the mean-variance model, there are many studies have been conducted in the field of the optimal asset allocation. In particular, the study of portfolio risk measures have been developed in various ways. This paper made a comparative study LPM, CLPM, VaR, CVaR, minimax in addition to variance of the returns and compared the performance of portfolio about each risk indicators in terms of return on the risk. When the variance-covariance matrix is needed to use for optimal asset allocation, we estimated both the standard variance-covariance matrix and the DCC-MGARCH to use necessary risk indicators. And we compared the result of all kind of test in terms of return on the risk. In a variety of market conditions, LPM, CLPM against other risk indicators show better performance in terms of return on risk. Optimized portfolio of sector ETFs using variance as well as various risk indicators, shows higher performance than KOSPI index always.
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