본 연구는 변동성지수를 발표하고 있는 8개 국가들의 데이터를 이용하여 각 국가별 변동성지수와 주가지수 사이의 상호관계를 살펴봄으로써 변동성지수가 종합주가지수에 대한 방향 지표로써 의미 있는지를 살펴보고 국내 시장의 특징을 다른 국가들과 대비하여 비교분석 하였다. 분석 방법으로는 VAR 모형을 기반으로 한 그랜저 인과관계, 충격반응함수, 분산분해분석을 실시하였으며, 분석결과를 요약하면 다음과 같다. 첫째, 그랜저 인과관계 검정에서는 미국, 독일, 한국의 경우, 변수들 사이의 선, 후행 관계는 존재하지 않는 것으로 밝혀졌으나, 프랑스의 경우는 변동성지수가 종합주가지수를 일방적으로 선행한다는 것을 확인하였다. 반대로, 네덜란드, 스위스, 일본의 경우, 변동성지수가 종합주가지수를 선행하는 것이 아니라, 오히려 종합주가지수가 변동성 지수의 원인변수인 것으로 밝혀졌으며 마지막으로 영국의 VFTSE와 FTSE는 두 변수간의 상호 선도-지연관계가 존재함이 확인됨으로써 국가마다 상이한 결과차이를 보이는 것으로 나타났다. 둘째, 충격반응함수분석결과에서는 모든 국가들의 종합주가지수의 한 단위 충격에 대해 변동성지수는 크게 반응하지 않는 것으로 나타남에 반해, 변동성지수 표준편차 한 단위 충격에 대해서는 종합주가지수가 1기간(1일) 강한 음(-)의 반응을 보이는 것으로 나타나 변동성지수의 충격이 종합주가지수에 일방적으로 영향을 주는 것으로 확인되었으며 모든 국가별 분석에서도 일관된 결과가 도출되었다. 마지막으로, 분산분해 분석을 실시한 결과, 종합주가지수는 변동성지수에 크게 영향을 미치지 못하는 것으로 나타났으나 변동성지수는 모든 국가에서 50%이상 종합주가지수 변화에 대한 설명력을 가지는 것을 확인하였다. 본 연구의 검정 결과를 종합적으로 판단할 때, 변동성지수와 종합주가지수 사이에는 음(-)의 상관관계가 존재하며 변동성지수는 종합주가지수에 선행한다고 할 수 있다. 본 연구결과는 기관 및 개인투자자들의 투자전략 수립 및 리스크관리에 조금이나마 도움이 될 것이라 판단되며 변동성지수와 종합주가지수사이의 관계에 대한 지속적인 연구가 진행되어야 한다는 학문적 시사점을 제공하고 있다.
The advancement of the global financial market and the development of information and communication technology have led to the activation of the derivatives market. Also, the emergence of a number of derivatives has played a key role in the development of the financial market. Representatively, according to the desire of investors to manage volatility as well as future movements of investment assets, they are traded by developing a volatility index and volatility index futures in a number of advanced countries, starting with the US VIX. The volatility index is an index that reflects market expectations for volatility over the next 30 days of the stock index option. As the option market becomes more active, the volatility index has more predictive power over the stock index. This study investigates the interrelation between the volatility index and the stock price index of each country using data from eight countries that have published the volatility index. The purpose of this study is to confirm whether (1) Does the volatility index have predictive power against the composite stock price index? (2) If the volatility index has a predictive power against the stock price index, how much time difference does it have? (3) Lastly, how much influence it has. We use Grander causality, impulse response function, and variance decomposition analysis based on VAR model after examining the stationary of time series data. The results of the analysis are as follows. First, in the Granger causality test, there is no lead-lag relationship between the volatility index and the composite stock index of the US, Germany, and Korea. However, in France, it is confirmed that the volatility index unidirectionally leads the composite stock price index. On the contrary, in the Netherlands, Switzerland, and Japan, the volatility index does not lead the composite stock price index, but rather the composite stock price index one-sidedly leads the volatility index. Lastly, in the UK, there is a mutual lead-lag relationship between the volatility index, VFTSE, and the composite stock price index, FTSE. Thus, the analysis of Granger causality test shows different results in each country. Second, in the impact response function analysis, the volatility index did not show a large response to the standard deviations unit shock of the all stock indexes of all countries. However, for the standard deviations per unit of volatility index, the composite stock price index showed a strong negative response for one period. This results confirm that the impact of the volatility index unilaterally affects the KOSPI, and consistent results are obtained in all country analyzes. Third, the results of the variance decomposition analysis show that the composite stock index does not have a significant effect on the volatility index, but the volatility index has explanatory power on the change in the stock price index over 50% in all countries. In conclusion, there is a negative correlation between the volatility index and the composite stock price index, and the volatility index leads the composite stock price index. All results of this study will be helpful for the institutional and individual investors to establish investment strategies and risk management and provide implications for the ongoing research on the relationship between the volatility index and the stock price index. Previous studies that have examined the correlation between the volatility index and the composite stock price index were based on volatility data before the publication of the VKOSPI and were based on the results of the time when the volatility index was not included in the upward trend such as the sub-prime mortgage and the EU fiscal crisis. It is concluded that the results of this study are in contradiction with the results of the study. In addition, this study is an empirical study that examines the relationship between the volatility index and the representative stock price index for each country. Some studies have predicted the random distribution of information, investing behavior of irrational investors, and inefficiency of the market, but it is necessary to conduct detailed research on the exact cause.