국내외 금융시장의 변동성을 이용한 KOSPI200 실현변동성 예측력 향상에 관한 연구

초록

Volatility is one of the important parameters in financial markets. It plays a very important role in asset pricing, risk management, and investment policy. As concerns volatility increase, VIX, an index for volatilities in the US financial markets, was invented in 1993. At first time, the implied volatility had been used to calculate VIX, option prices have been used since September 2003. There have been many research works on whether VIX is the unbiased estimate of the realized volatility. They focus on improving model specifications, finding a better estimation method or relaxing assumptions on model specifications. However, results are not consistent. They cannot lead to the same result. Jorion(1995), Christensen and Prabhala(1998) find that implied volatility has better information contents than historical volatility. Canania and Figlewski(1993) insist that historical volatility is better than implied volatility in terms of information contents and that implied volatility has nothing to do with future realized volatility. Day and Lewis(1992) suggest that any candidate does not perform better than others. Corrado and Miller(2005), Lee and Chung(2006) find that VIX performs well to predict the future realized volatility. Rhee and Hwang(2008) obtain the result that model-free implied volatility(MFIV) has better predictive power for future realized volatility. Eom et al.(2008) calculate the monthly volatility index using KOSPI200 option prices and test the predictive power of the monthly volatility index for the future realized volatility. They find that the volatility index is an unbiased estimator after taking the measurement error or the omitted-variable problem into account, while it’s a biased estimator in general regression test. These results show that the unbiasedness of the volatility index to the actual volatility is not rejected when some econometric issues are considered and that the volatility index has higher predictability power than those of other volatility measures such as past actual volatilities. Yoo and Koh(2009) find out whether the information from foreign capital markets can improve the forecasting power for the realized volatility of KOSPI200 index. The realized volatility is estimated by using both daily return series and 5 minutes intraday data of KOSPI200. The volatilities of S&P100 return series and Won/Dollar exchange rate are considered as the information from foreign capital markets, and the volatility of Korean domestic interest rate is introduced as an additional variable to improve the forecasting power for the realized volatility of KOSPI200 returns. It turns out that those additional variables are statistically significant to improve the predictive power for the realized volatility of KOSPI200. Can the predictability of realized volatility be improved when volatilities of other financial markets are added as explanatory variables? To answer this question, the dependent variable, that is, realized volatility is estimated by using various data sets with different frequencies of day, hour, 30 minutes and 5 minutes. As for explanatory variables, we use both domestic and foreign financial markets variables. For domestic financial market variables, there are volatility of domestic three-month CD rates and volatilities of foreign exchange rates. For foreign financial market variables, there are equity volatilities of U.S., Japan, Hong Kong, and U.K., and volatilities of three-month U.S. treasury rates and three-year U.S. treasury rates. It turns out that VKOSPI is a biased estimator of the corresponding realized volatility. VKOSPI, historical volatility of S&P500, and historical volatility of KOSPI200 explain similarly the realized volatility of KOSPI200 in terms of the explanatory power, that is, . In addition to VKOSPI, volatilities of domestic bond and won/dollar exchange markets have additional minor explanatory power to the realized volatility. One thing interesting is that the volatility of the domestic interest rate market is negatively related to the realized volatility. For volatilities from foreign stock markets, we first use volatility of S&P500 as an explanatory variable and then add volatilities of other foreign equity markets. It turns out that there exists little improvement in . That means that S&P500 has dominant explanatory power to the realized volatility of KOSPI200.

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