• 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.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• 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 Convergence for Information Technology
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• v.11 no.9
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• pp.84-93
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• 2021

The purpose of this study is to analyze whether the spread of COVID-19 infectious diseases acts as a fear to investors and affects the direction and volatility of stock returns. The investor fear index was proposed using the domestic confirmed patient information of COVID-19, and the influence on stock prices was empirically analyzed. The direction and volatility models of stock prices used the Granger causality and GARCH models, respectively. The results of empirical analysis using the KOSPI index from February 20, 2020 to June 30, 2021 are as follows: First, the COVID-19 fear index showed causality to future stock prices. Second, the COVID-19 fear index has a negative effect on the volatility of KOSPI index returns. In future studies, it is necessary to document the cause by using individual business performance and stock price instead of the stock index.

• Journal of Distribution Science
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• v.21 no.9
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• pp.103-114
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• 2023

Purpose: This paper aims to assess psychological heuristics' effectiveness on cumulative returns after significant stock price changes. Specifically, it compares availability and anchoring heuristics' empirical validity due to conflicting stock return predictions. Research Design, Data, and Methodology: This paper analyzes stock price changes of Korean distribution industry stocks in the KOSPI market from January 2004 to July 2022, where daily fluctuations exceed 10%. It evaluates availability heuristics using daily KOSPI index changes and tests anchoring heuristics using 52-week high and low stock prices as reference points. Results: As a result of the empirical analysis, stock price reversals did not consistently appear alongside changes in the daily KOSPI index. By contrast, stock price drifts consistently appeared around the 52-week highest stock price and 52-week lowest stock price. The result of the multiple regression analysis which controlled for both company-specific and event-specific variables supported the anchoring heuristics. Conclusions: For stocks related to the Korean distribution industry in the KOSPI market, the anchoring heuristics theory provides a consistent explanation for stock returns after large-scale stock price fluctuations that initially appear to be random movements.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.219-234
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• 2010

In index investing according to KOSPI, we estimate Value at Risk(VaR) from the extreme losses of the daily returns which are obtained from KOSPI. To this end, we apply Block Maxima(BM) model which is one of the useful models in the extreme value theory. We also estimate the extremal index to consider the dependency in the occurrence of extreme losses. From the back-testing based on the failure rate method, we can see that the model is adaptable for the VaR estimation. We also compare this model with the GARCH model which is commonly used for the VaR estimation. Back-testing says that there is no meaningful difference between the two models if we assume that the conditional returns follow the t-distribution. However, the estimated VaR based on GARCH model is sensitive to the extreme losses occurred near the epoch of estimation, while that on BM model is not. Thus, estimating the VaR based on GARCH model is preferred for the short-term prediction. However, for the long-term prediction, BM model is better.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.23-29
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• 2017

Due to the success of Wealthfront, Betterment, etc., there is a growing interest in RoboAdvisor that is an automated asset allocation methodology globally. RoboAdvisor minimizes human involvement in managing assets, thereby reducing the costs of using services and eliminating human psychological factors. In this paper, we developed a predictive model for the KOSPI 200 Futures Index using deep learning, in order to replace the existing technical analysis technique. And the proposed model confirmed that When the KOSPI 200 Gift Index is small, it can be used to predict direction and price of index. In combination with the existing technical analysis, It is confirmed that the proposed models combining with existing technical analyses and can be applied to the RoboAdvisor Service in the future.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.31-41
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• 2004

This study analyzes the structure of the variations In the domestic bank earnings and examines their dynamic features by estimating the short-run response and the long-run adjustment Process after the changes in financial market variables. A system of the equations for the bank stock price index and KOSPI is formulated to utilize the whole information in the market and simultaneously estimated to identify the relationships between the market variables and the bank earnings. Since the bank stock price is found to be responsive to changes in none of the market variables in the short run, while being relatively responsive to dollar exchange rate and business state, It implies that a good economic conditions and a stable foreign exchange rate should be maintained to Improve the level of the stock price In the long run. In addition, the dynamic structure of the responses of the bank stock price index and KOSPI to the initial changes in the market variable are compared and anlayzed. The response of the bank stock price appears to take much longer in adjusting to the long-run eouilibrium level than that of KOSPI. As a result, the cumulative response of the bank stock price index over time is found much bigger than that of HOSPI.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2030-2032
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• 2001

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock, or other economic markets. Most previous experiments used multilayer perceptrons(MLP) for stock market forecasting. The Kospi 200 Index is modeled using different neural networks and fuzzy system predictions. In this paper, a multilayer perceptron architecture, a dynamic polynomial neural network(DPNN) and a fuzzy system are used to predict the Kospi 200 index. The results of prediction is compared with the root mean squared error(RMSE) and the scatter plot. Results show that both networks can be trained to predict the index. And the fuzzy system is performing slightly better than DPNN and MLP.