• 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.

• 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.

• Journal of Industrial Convergence
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• v.3 no.1
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• pp.3-18
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• 2005

The purpose of this study is to examine the relationship between KOSPI200 Futures and KTB Futures in inter market and intra market. We are focusing on which market would be lead. The empirical results have indicated that there are no lead or lag effect between KOSPI200 Futures and KTB Futures market. But some positive correlation appeared, we used to know negative correlation between stock and bond market, which is a new finding. As a conclusion, the market still have an efficiency with co-movement.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.151-161
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• 2014

KOSPI 200 index options market has the highest trading volume in the global options markets. The risk and return structure of options contracts are very complex. Volatility complicates options trading because volatility plays a central role in options pricing process. This study develops a trading system for KOSPI 200 index options trading using KOSPI 200 volatility index. We design a database system to handle the complex options information such as price, volume, maturity, strike price, and volatility using Oracle DBMS. We then develop options trading strategies to test how the volatility index is related to the prices of complicated options trading strategies. Back test procedure is presented with PL/SQL of Oracle DBMS. We simulate the suggested trading system using historical data set of KOSPI 200 index options from December 2008 to April 2012.

• Management & Information Systems Review
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• v.36 no.3
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• pp.37-49
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• 2017

This study investigates the dynamic relationship between KOSPI200 stock index and stock index futures and stock index option markets which is its derived from KOSPI200 stock index. We use 5-minutes rate of return data from 2012. 06 to 2014. 12. To empirical analysis, this study use autocorrelation and cross-correlation analysis as a preliminary analysis and then following Stoll and Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the stock index and stock index futures and option markets by Newey and West's(1987) Empirical results of our study shows as follows. First, there exist a strong autocorrelation in the KOSPI200 stock index before 10minutes but a very weak autocorrelation in the stock index futures and option markets. Second, there is a strong evidence that stock index future and option markets lead KOSPI200 stock index in the cross-correlation analysis. Third, based on the multiple regression, the stock index futures and option markets lead the stock index prior to 10-15 minutes and weak evidence that the stock index leads the future and option markets. This results show that the market efficient of KOSPI200 stock index market is improved as compared to the early stage of stock index future and option market.

• 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.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.106-120
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• 2000

The purpose of this research is to understand the effects of Quality Management Award on stock prices movement and to examine the comparative advantages of quality award system in Korea and the U.S. This study compares the performances of QM Award companies in the stock market with those of the market index in both countries. We develop Korean Quality Award Index(KQA Index) based on the Baldrige Index of NIST in the U.S. We inspect three studies. Study 1 tests if the performances of MB Award winners and S&P500 index have a difference in the stock market. Study 2 tests if the performances of KQA winners and KOSPI(Korean Composite Stock Price Index) have a difference in the stock market. Study 3 tests if the performances of KQA winners and MB Award winners have a difference in the stock market. From the empirical tests, the performances of KQA winners are superior to those of KOSPI and the performances of MB Award winners are superior to those of S&P500 and the performances of MB Award winners are superior to those of KQA winners.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.117-144
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• 2008

This article examines the information transmission process between the KOSPI 200 futures market and its underlying stock market, using the 10-second quote and trade data. The VAR analysis reveals that quote revisions through limit orders in general lead trades through market orders. In addition, the VAR analysis shows that the futures market tends to lead the stock market in terms of quote revisions and trades, even though the other direction is also observable. Even when we focus on the events causing large movements in quote revisions and trades, those lead and lag relations between those markets and between quote revisions and order imbalances are confirmed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.308-316
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• 2015

The purpose of this study is to verify TOM(turn-of-the-month) effect in the Kosdaq market, and that to compare to TOM effect of KOSPI for supporting degree of identification and to find new features. For this study, as the study basis sample, we used the daily data of the KOSDAQ from January 1996 to December 2013 and verified the TOM effect through yearly, monthly, classification by event as financial crisis, different period of TOM in order to clarify the effect of the KOSPI and KOSDAQ. As a result, We find that the TOM effect in KOSDAQ is always present uniformly in yearly, monthly, event-specific, which unlike TOM period also in KOSPI and generally TOM effect in KOSDAQ market which has larger volatility was appeared more pronouncedly than KOSPI market, and particularly TOM effect of KOSDAQ was larger than that of KOSPI on financial crisis occasion. But TOM effect of KOSDAQ was less stable than KOSPI.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.