• KDI Journal of Economic Policy
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• v.25 no.2
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• pp.137-170
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• 2003

Despite the great success of the derivatives market, several concerns were expressed regarding the additional volatilitystemming from program trading during the expiration of derivatives. This paper examines the impact of the expiration of the KOSPI 200 index derivatives on cash market of Korea Stock Exchange(KSE). The KOSPI 200 index derivatives market has a unique settlement price determination process. The settlement price for the expiration of derivatives is determined by call auction during the last 10 minutes after the trades for matured derivatives are finalized. We analyze typical expiration day effects such as price, volatility, and volume effects. With high frequency data, we find that there are strong expiration day effects in the KSE and try to interpret the results with the unique settlement procedures of the KOSPI 200 cash and derivatives markets.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.175-182
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• 2021

Focusing on the recently announced "KOSPI 200 ESG Index," this study intends to examine whether the "KOSPI 200 ESG Index" has any relevance to stock prices. Specifically, it was empirically analyzed whether companies included in the KOSPI 200 ESG index showed average abnormal return and cumulative average abnormal return of stock prices due to incorporation into the index. As for the research method, the case study was conducted using the return by the market model using the coefficient estimated by the OLS for the normal expected return. The study results are summarized as follows. First, the initial incorporation of a company into the KOSPI 200 ESG index showed significant positive(+) average abnormal return and cumulative average abnormal return. Second, the incorporation of a company into the KOSPI 200 ESG index showed significant positive(+) average abnormal return and cumulative average abnormal return. Through this study, it was confirmed that investors in the market are aware of ESG indicators as non-financial information, not just financial information. In addition, it can be said that the contribution of this study to the fact that investors perceive ESG index as information for investment. This study differs in that it uses the latest ESG index, but at the same time, it has limitations in that the study period is short and the study sample is limited.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.151-162
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• 2010

Recent developments in financial market liberalization and information technology are accelerating the interdependence of national stock markets. This study explores the information spillover effect of the US stock market on the overnight and daytime returns of the Korean stock market. We develop a profitable intra-day trading strategy based on the information spillover effect. Our study provides several important conclusions. First, an information spillover effect still exists from the overnight US stock market to the current Korean stock market. Second, Korean investors overreact to both good and bad news overnight from the US. Therefore, there are significant price reversals in the KOSPI 200 index futures prices from market open to market close. Third, the overreaction effect is different between weekdays and weekends. Finally, the suggested intra-day trading system based on the documented overreaction hypothesis is profitable.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.65-94
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• 2009

The event of change in KOSPI 200 Index composition is one of the main subjects for the test of EMH. According to EMH, when a certain event is not related with firm's fundamental value, stock price should not change after the announcement of news. This hypothesis leads us to the conclusion of horizontal demand curve of stock. This logic was questioned by Shleifer(1986) and argued that downward sloping demand curve hypothesis was supported. But Harris and Gruel(1986) found a different empirical evidence that price reversal occurs in the long run, which is called price pressure hypothesis. They argued that short term price effect by large block trading (price pressure) is offset in the long run because these event is unrelated to fundamental value. Therefor, they argued that EMH can not be rejected in the long run. Until now, there are two empirical studies with Korean market data in this area. Using a data with same time period of $1996{\sim}1999$, Kweon and Park(2000) and Ahn and Park(2005) showed that stock price or beta is not significantly affected by change in index composition. This study retested this event expanding sample period from 1996 to 2006, and analyzed why this event was considered an uninformative events in the preceding studies. We analyzed a market impact by separating samples according to firm size and market condition. In case of newly enlisted firm, we found the evidence supporting price pressure hypothesis on average. However, we found the long run price effect in the sample of large firms under bearish markets. At the same time, we know that the number of samples under the category of large firms under bearish markets is relatively small, which drives the same result of supporting the hypothesis that change in index composition is a non-informative event on average. Also, the long run price effect of large size firms under bearish markets was supported by the analyses using trading volumes. On the other hand, in case of delisting from the index, we found the long run price effect but that was not supported by trading volume analyses.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.461-475
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• 2021

Hidden Markov model (HMM) is a statistical model in which the system consists of two elements, hidden states and observable results. HMM has been actively used in various fields, especially for time series data in the financial sector, since it has a variety of mathematical structures. Based on the HMM theory, this research is intended to apply the domestic KOSPI200 stock index as well as the prediction of global stock indexes such as NIKKEI225, HSI, S&P500 and FTSE100. In addition, we would like to compare and examine the differences in results between the HMM and support vector regression (SVR), which is frequently used to predict the stock price, due to recent developments in the artificial intelligence sector.

• 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.

• 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 Korea Convergence Society
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• v.8 no.5
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• pp.213-221
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• 2017

This study empirically investigates the relation between information quality measured by accruals quality and the KOSPI200 index rebalancing. The accruals quality is used for the proxy of information quality and is estimated by employing the Francis et al. (2005) model. The result shows that there is a statistically significant difference between additions group and deletions group. The average information quality of deletions group is substantially lower than that of additions group. In addition, the regression analysis shows that the relationship between accruals quality and a dummy variable for changes in the KOSPI200 index composition is negative and statistically significant. This result implies that additions to the KOSPI200 stock index improves information quality and relieves the information risk of firm which results in the amelioration of information asymmetry. On the other hand, deletions from the KOSPI200 index result in the deterioration of information quality. These results are consistent with Merton (1987).

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.6-172
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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. The results show that the fuzzy system is performing slightly better than DPNN and MLP. We can develop the desired fuzzy system by learning methods ...

• 한국산학경영학회:학술대회논문집
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• 2006.12a
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• pp.107-120
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• 2006

This thesis examines the relationship between the trading volume and price return in the korean stock Index Futures until June 2005. First, the volume of KOSPI200 futures doesn't play a primary role with the clear explanation of return model. Second, an unexpected volume shocks are negatively associated with the return in case of the KOSPI200 futures, but it is a meaningless relation in the KOSDAQ50 futures. In the case of open interest, it's difficult to find any mean in a both futures. Third, The changes in the trading volumes by foreign investors are positively associated with the return and the volatility, but individuals and domestic commercial investors are negatively associated with the return. This empirical result seems that foreign investors are initiatively trading the korean stock index futures, individuals and domestic commercial investors follow the lead made by foreign investors.