• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.85-107
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• 2006

This paper investigates whether the futures market responds to the news more sensitively and uses more diverse information than the spot market. The sensitivity to the news is measured by the coefficients of the model which regresses the daily changes in the futures prices to the daily changes in the theoretical prices computed from spot prices using the spot-futures parity. The diversity of news is measured by the mean range differences ($\overline{RD}$), mean hi-price differences($\overline{HD}$) and mean low-price differences. The data in this paper is the closing prices of the nearest-to-maturity and the second-nearest-to-maturity contracts of the KOSPI 200 index futures. As the estimates of the relative sensitivity of the futures prices($^{\beta}$) for the whole-period sample are not significantly different from 1, the sensitivity of two markets to the news are not different. However, $\hat{\beta}$ of the most recent period(Nov. 2002 to Dec. 2005) are strongly different from 1. And, in the most recent period, the futures price changes for the good news, which is defined as the price increase of KOSPI of more than 1.5% in a day, show additional sensitivity. Since the mean range different which measures the relative diversity of information used, are not significantly different from 0 for the whole-period and subperiod samples, and this can be interpreted that the futures market does not use more diverse information than the spot market. However, the mean high-price difference, which measures the relative diversity of good news, are significantly different from 0 for the nearest-maturity contracts in the whole-period and subperiod samples. This evidence supports that the futures prices reflects more diverse good news which brings price increase in the market.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.205-229
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• 2004

The deviation from put-call parity condition may affect market prices since it provides an opportunity of arbitrage to many participants. This study uses the KOSPI200 index data and examines the interdependence among spot, futures, and options contracts by examining whether the deviations from the parity have significant roles in price formation. Whenever the parity condition is violated, the deviation tends to affect the prices significantly in most markets. The results show that positive values of deviation are associated with the fall of the prices in the spot and put option contracts and the rise of the call option premiums, thus decreasing the deviations. Also, the decreasing impact of deviations lasts for at Beast an hour in most markets. Futures prices, however, do not show clear relations with the deviations, which suggests the possibility that futures markets lead other markets.

• The Korean Journal of Financial Management
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• v.25 no.3
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• pp.111-130
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• 2008

This paper compares long term equilibrium relation of KOSPI 200 which is underling stock and its futures by using general method fractional cointegration instead of existing integer cointegration. Existence of integer cointegration between two price time series gives much wider information about long term equilibrium relation. These details grasp long term equilibrium relation of two price time series as well as reverting velocity to equilibrium by observing difference coefficient of error term when it renounces from equilibrium relation. The result of this study reveals existence of long term equilibrium relation between KOSPI200 and futures which follow fractional cointegration. Difference coefficient, d, of 'two price time series error term' satisfies 0 < d < 1/2 beside bandwidth parameter, m(173). It means two price time series follow stationary long memory process. This also means impulse effects to balance price of two price time series decrease gently within hyperbolic rate decay. It indicates reverting speed of error term is very low when it bolts from equilibrium. It implies to market maker, who is willing to make excess return with arbitrage trading and hedging risk using underling stock, how invest strategy should be changed. It also insinuates that information transition between KOSPI 200 Index market and futures market does not working efficiently.

• The Korean Journal of Financial Management
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• v.17 no.1
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• pp.253-281
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• 2000

가격의 일일 등락폭을 상하 일정률로 제한하는 가격제한폭제도는 증거금 제도와 함께 증권시장의 양대 안정장치의 하나이다. KOSPI 200 현 선물시장에서도 가격제한폭 변경이 또KOSPI 200 도입이후 네 번 있었다. 따라서 연구는 가격제한폭의 변경 전후의 KOSPI 200 현 선물지수와 거래량 자료를 대상으로 수익률의 변동성 분석, 거래량 분석, 시장반응을 분석하였다. 본 연구의 실증적 연구결과는 다음과 같다. 첫째, 현물시장만 가격제한폭을 변경한 경우 변경 전후에는 현 선물시장의 수익률변동성에는 변화가 없는 것으로 나타났으나, 현 선물시장의 거래량 변동성 차이는 가격제한폭 변경후에 작은 것으로 분석되었다. VAR 분석에 의하면 변경후가 변경전에 비하여 선물이 현물을 선도하는 시차가 작아진 것으로 나타나 변경후가 더 효율적인 시장임을 알 수 있다. 둘째, 선물시장만 가격제한폭 일부의 제도를 변경한 경우 변경후에 현 선물시장의 수익률변동성과 거래량변동성이 축소된 것으로 나타나 안정적임을 알 수 있다. VAR 분석에 의하면 변경후가 변경전에 비하여 선물이 현물을 선도하는 시차가 작아진 것으로 나타나 변경후가 더 효율적인 시장임을 알 수 있다. 셋째, 현 선물시장이 동시에 제도를 변경한 경우 다음과 같다. 1998년 3월 2일의 경우 선물시장은 수익률 변동성 차이가 없는 것으로 나타났으나, 현물시장은 변경후 수익률의 변동성이 적은 것으로 나타났다. 거래량의 변동성은 현 선물시장에서 변경후가 작은 차이가 있는 것으로 분석되었다. VAR 분석에 의하면 변경후가 변경전에 비하여 선물이 현물을 선도하는 시차가 커진 것으로 나타나 현물시장과 선물시장이 동시에 가격제한폭 확대후에 비효율 적으로 되었다는 의미로 판단된다. 1998년 12월 7일의 경우 변경후에 현 선물시장에서는 수익률 및 거래량의 변동성이 작은 것으로 나타났다. 변경전에는 선물시장에 비해 현물시장의 수익률, 변동성이 높은 것으로 나타났으나, 변경후에는 현물시장에 비해 선물시장의 수익률 변동성이 높은 것으로 나타났다. VAR 분석에 의하면 변경후가 변경전에 비하여 선물이 현물을 선도하는 시차가 다소 커진 것으로 나타나 현물시장과 선물시장이 동시에 가격제한폭 확대후에 비효율적으로 되었다는 의미로 판단된다.

• Journal of the Korea Society of Computer and Information
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• v.7 no.2
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• pp.196-204
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• 2002

This paper examines the price discovery role of the KOSPI 200 futures index for its cash index. It was used the intrady data for KOSPI 200 and futures index from July 1998 to June 2001. The existing Preceding study for KOSPI 200 futures index was used the data of early market installation, but this study is distinguished to use a recent data accompanied with the great volume of transaction and various investors. We established three hypothesis to examine whether there is the price discovery role in the KOPSI 200 futures index and the characteristics of that. First, to examine whether the lead-lag relation is induced by the infrequent trading of component stocks, observations are sorted by the size of the trading volume of cash index. In a low trading volume, the long lead time is reported and the short lead time in a high volume. It is explained that the infrequent trading effect have an influence on the price discovery role. Second, to examine whether the lead-lag relation is different under bad news and good news, observations are sorted by the sign and size of cash index returns. In a bad news the long lead time is reported and the short lead time in a good news. This is explained by the restriction of"short selling" of the cash index Third, we compared estimates of the lead and lag relationships on the expiration day with those on days prior to expiration using a minute-to-minute data. The futures-to-spot lead time on the expiration day was at least as long as other days Prior to expiration, suggesting that "expiration day effects" did not demonstrate a temporal character substantially different form earlier days. Thus, while arbitrage activity may be presumed to be the greatest at expiration, such arbitrage transactions were not sufficiently strong or Pervasive to alter the empirical price relationship for the entire day. for the entire day.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.

• Management & Information Systems Review
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• v.35 no.2
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• pp.273-284
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• 2016

The objective of this study is to analyze the market efficiency in the futures markets. Although many previous studies have investigated market efficiency between spot and futures prices, that with different maturities has not been studied in the futures markets extensively. For our objective, this paper examines KOSPI200 stock index future market with different maturities. We analyze the dynamic serial relationship of the difference of basis between nearest-month contract and next nearest-month contract using dynamic regression analysis suggested by Kawamoto and Hamori(2011) Using the data from 2000. 1 to 2013. 12, the major empirical findings are as follows: First. the mean and standard deviation of basis of next nearest-month contract is bigger than those of nearest-month contract. Second, the t-period basis of nearest-month contract can be explained by (t-1)period basis of that. Third, the basis spread of t-period and (t-1)period have negative affect on the return of underlying assets. This result is very reasonable because two basis spreads are derived from same underlying assets. Finally, basis information of next nearest-month contract can be used for the prediction of nearest-month contract and spot market return.