• Management & Information Systems Review
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• v.32 no.3
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• pp.285-297
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• 2013

In this study, price discovery among the KOSPI200 markets(KOSPI200 spot, KOSPI200 Futures and The ETFs) is investigated using the vector error correction model(VECM). The main findings are as follows. KODEX200(KOSEF200), KOSPI200 spot and Futures are cointegrated in most cases. Daily data from KODEX200(KOSEF200), KOSPI200 spot and KOSPI200 futures show that the movements of the three markets are interrelated. Specially, KODEX200 contains the most information, followed by the KOSPI200 spot and futures markets. KODEX200 contribute to the price discovery process. Namely KODEX200 plays a more dominant role in price discovery than the KOSPI200 spot and futures.

• Management & Information Systems Review
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• v.31 no.4
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• pp.287-307
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• 2012

We empirically examine the price discovery dynamics among the VKOSPI, the KOSPI200 spot, and the KOSPI200 futures markets. The analysis employs the vector-autoregression, Granger causality, impulse response function, and variance decomposition using both daily data from 2009. 04. 13 to 2011. 12. 30 and 1 minute data from the bull market, bear market, and the flat period. The main results are as follows; First, the lead lag relationships between KOSPI200 spot(futures) yield VKOSPI returns could not be found from the daily data analysis. But KOSPI200 spot(futures) have a predictive power for VKOSPI from 1 minute data. Especially KOSPI200 spot(futures) and VKOSPI show the bi-directional effects to each other during the return rising period Second, We chose the VAR(1) the model in daily data but adopt the VAR(3) model in the one minute data to determine the lead lag time. We know that there is predictability during the very short period Third, Spot returns and futures returns makes no difference in daily data results. According to the one minite data results, VKOSPI returns have a predictive power for KOSPI200 spot return, but have no predictive power for KOSPI200 futures return.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.905-914
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• 2014

In this study, we examine hedging effectiveness of KODEX200 ETF and KOSPI200 futures with respect to KOSPI200 spot or KODEX200 ETF using naive, the risk-minimization models and the VECM. The sample period covers from January 5. 2010 to October 31. 2013. Daily prices of the KOSPI200 spot, KOSPI200 futures and KODEX200 were used in this study. The results are summarized ans follows. First, this study show that there is cointegration relationship among KOSPI200 spot, futures and KODEX200 ETF market. Second, there is no significant difference in hedging performance among the models. Finally, hedged position of KOSPI200 cash(unhedged position)-KODEX200 ETF(hedge vehicle) or KODEX200 ETF-KOSPI200 futures seems to improve hedging performance compared to KOSPI200 cash-KOSPI200 futures. This implies that the portfolio managers may be encouraged to use the former than the latter.

• Management & Information Systems Review
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• v.35 no.2
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• pp.1-12
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• 2016

In this study, price discovery between the KOSPI200 spot, and leveraged ETFs(Leveraged KODEX, Leveraged TIGER, Leveraged KStar) is investigated using the vector error correction model(VECM). The main findings are as follows. Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot are cointegrated in most cases. There is no interrelations between the movement of Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot markets in case of daily data. Namely, in daily data, Leveraged KODEX(Leveraged TIGER, Leveraged KStar) doesn't plays more dominant role in price discovery than the KOSPI200 spot.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.191-212
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• 2003

Recently, there is a growing body of literature that suggests that information inefficiency is one of the causes of the asymmetric volatility. If this explanation for the asymmetric volatility is appropriate, then innovations, such as the introduction of futures, may be expected to impact the asymmetric volatility of stock market. As transaction costs and margin requirements in the futures market are lower than those in the spot market, new information is transmitted to futures prices more quickly and affects spot prices through arbitrage trading with spots. Also, the merit of the futures market may attract noise traders away from the spot market to the futures market. This study examines the impact of futures on the asymmetry of stock market volatility. If the asymmetric volatility is significant lower post-futures and exist in the futures market, it has validity that the asymmetric volatility is caused by information inefficiency in the spot market. The data examined are daily logarithmic returns on KOSPI 200 stock price index from January 4, 1993 to December 26, 2000. To examine the existence of the asymmetric volatility in the futures market, logarithmic returns on KOSPI 200 futures are used from May 4, 1996 to December 26, 2000. We used a conditional mode of TGARCH(threshold GARCH) of Glosten, Jagannathan and Runkel(1993). Pre-futures the spot market exhibits significant asymmetric responses of volatility to news and post-futures asymmetries are significantly lower, irrespective of bear market and bull market. The results suggest that the introduction of stock index futures has an effect on the asymmetric volatility of the spot market and are inconsistent with leverage being the sole explanation of asymmetry. However, it is found that the volatility of futures is not so asymmetric as expected.

• Korean Business Review
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• v.16
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• pp.145-168
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• 2003

This study is mainly aimed at analyzing the influence of the divergency(mispricing) between KOSPI 200 theoretical prices and its real prices of KOSPI 200 spot index, considering the existence of arbitrage opportunity from the mispricing. The data in this study are the daily prices of 1262 days, from 3 May 1996 to 14 December 2000. The results of our empirical study represent that the real prices in KOSPI 200 Stock Index Futures are continuously undervalued relative to their corresponding theoretical prices. Our study reconfirms the results from previous studies conducted at the domestic and overseas markets. We conclude that the undervaluation, especially in the market opening period, could come from fear of investors, whose experiences in the stock index futures market are limited, chiefly because of loss and uncertainty of prediction toward interest rates and dividends. Our study also represents that KOSPI 200 index shows more volatilities during days with mispricing relative to days without mispricing.

• The Korean Journal of Financial Management
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• v.17 no.1
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• pp.227-251
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• 2000

한국시장에서 KOSPI 200 현물과 KOSPI 200 주가지수 선물간의 선 후행성을 실증적으로 분석하기 위하여 1998년 8월부터 1999년 10월까지 KOSPI 200 지수와 유동성이 가장 높은 최근 월물 가격의 5분 간격 자료를 이용하였다. 현 선물 가격의 안정성(stationarity)을 검증한 이후 공적분(cointegration)을 통하여 유도된 오차수정모형(Error Correction Model) 인과관계 회귀식을 GMM(Generalized Method of Moments)으로 추정하여 현 선물간의 선 후행성을 분석하고, 그 원인을 빈번하지 않는 거래(infrequent trading) 문제, 공매의 제약 문제, 거래 활발성의 강도 차이 문제 등의 측면에서 분석하였다. 그 결과 한국시장에서 현 선물간에는 쌍방의 인과 관계가 존재하지만 현물이 선물을 선행하는 정도는 아주 미약하였다. 반면에 선물은 현물을 약 30분 정도 선행하였다. 본 연구의 검증기간과 이용된 자료 내에서 현물이 선물에 대하여 후행하는 주된 원인은 현물시장에 존재하는 공매의 제약과 선물에 비하여 상대적으로 저조한 거래 활발성 때문인 것으로 나타났다. 왜냐하면 현물시장에서 공매가 상대적으로 어려운 시장하락시기에 선물의 선행정도가 통계적으로 유의적이었고, 현물과 선물의 거래가 활발한 시기에는 상호간에 선 후행성이 없었지만 현물의 거래가 비 활발할 경우 선물의 선행이 유의적이었기 때문이다.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.243-266
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• 2006

This paper tests cross hedging performance of the KOSPI 200 stock index futures to hedge the downside risk of the KOSPI, KOSPI 200 and KOSDAQ50 spot market. For this purpose we introduce the minimum variance hedge model, bivariate GARCH(1,1) and EGARCH(1,1) model as hedge models. The main results are as follows; First, we find that the direct hedge performance of KOSPI 200 index futures is better than those of indirect hedge performance. second, in case or cross hedge performance the hedge effect of KOSPI 200 stock index futures market against KOSPI 200 stock index spot market is relatively better than those of KOSPI 200 index futures against KOSPI and KOSDAQ spot position. Third, for the out-sample, hedging effectiveness of the risk-minimization with constant hedge ratios is higher than those of the time varying bivariate GARCH(1,1) and EGARCH(1,1) model. In conclusion, investors are encouraged to use simple risk-minimization model rather than the time varying hedge models like GARCH and EGARCH model to hedge the position of the Korean stock index cash markets.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1449-1466
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• 2014

In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

• The Korean Journal of Financial Management
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• v.16 no.1
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• pp.223-243
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• 1999

포트폴리오의 위험을 통제하거나 감소시키기 위해서 헤저들은 최적헤지비율을 추정하여야 하는데, 최적헤지비율의 추정치는 사용하는 모형에 따라 많은 차이를 보인다. 전통적인 회귀분석모형에 의하여 추정된 최적헤지비율은 시계열자료의 불안정성(nonstationary) 등으로 인하여 잘못될 가능성이 많으며, 잘못 추정된 헤지비율을 그대로 이용할 경우 현물포트폴리오의 시장위험을 최소화시키지 못하고 헤징비용을 증가시키는 결과를 초래한다. 시계열자료의 불안정성으로 말미암아 야기되는 문제점들을 개선할 수 있는 모형으로서 오차 수정모형(Error Correction Model : ECM)이 널리 이용되고 있다. 본 연구는 ECM을 사용하여 추정된 최적헤지비율과 전통적 회귀분석모형을 사용하여 추정한 최적헤지비율을 비교하여 어떤 모형으로 추정한 헤지비율이 더 정확한지를 평가하는데 목적을 두고 있다. 즉, 본 연구는 KOSPI 200 현 선물지수 자료를 대상으로 ECM과 전통적 회귀분석모형에 의한 최적헤지비율을 추정하고 각 모형의 설명력과 예측력을 비교하고자 한다. 실증분석 결과, KOSPI 200 현물지수와 KOSPI 200 선물지수간에는 공적분 관계가 존재하며, ECM과 전통적 회귀분석모형을 이용하여 추정한 최적헤지비율의 크기는 서로 다르며, ECM을 이용할 때 모형의 설명력이 조금 더 높게 나타났으며, 예측력도 ECM이 좀더 우월한 것으로 나타났다.