• The Journal of the Korea Contents Association
• /
• v.19 no.7
• /
• pp.36-46
• /
• 2019

If stock market is efficient, any well-devised trading rule can't consistently outperform the average stock market returns. This study aims to verify whether the strategy based on bid-ask volume information can beat the stock market. I suggested a day trading strategy using order imbalance indicator and empirically analyzed its profitability with the KOSPI 200 index futures data from 2001 to 2018. Entry rules are as follows: If BSI is over 50%, enter buy order, otherwise enter sell order, assuming that stock price rises after BSI is over 50% and stock price falls after BSI is less than 50%. The empirical results showed that the suggested trading strategy generated very high trading profit, that is, its annual return runs to minimum 71% per annum even after the transaction costs. The profit was generated consistently during 18 years. This study also improved the suggested trading strategy applying the genetic algorithm, which may help the market practitioners who trade the KOSPI 200 index futures.

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

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.4
• /
• pp.819-829
• /
• 2017

The aim of this study is to analyze intraday price momentum. When price trends are formed, price momentum is the phenomenon that future prices tend to follow the trend. When the market opened and closed, a U-shaped trading volume pattern in which the trading volume was concentrated was observed. In this paper, we defined price momentum as the 10 minute trend after market opening is maintained until the end of market. The strategy is to determine buying and selling in accordance with the price change in the initial 10 minutes and liquidating at closing price. In this study, the strategy was empirically analyzed by using minute data, and it showed effectiveness, indicating the presence of an intraday price momentum. A pattern in which returns are increasing at an early stage is called a J-shaped pattern. If the J-shaped pattern occurs, we have found that the price momentum phenomenon tends to be stronger than otherwise. The DTW algorithm, which is well known in the field of pattern recognition, was used for J-shaped pattern recognition and the algorithm was effective in predicting intraday price movements. This study showed that intraday price momentum exists in the KOSPI200 futures market.

• Communications for Statistical Applications and Methods
• /
• v.17 no.2
• /
• pp.293-308
• /
• 2010

In this paper, we examine the forecasting KOSPI 200 realized volatility by volatility measurements. The empirical investigation for KOSPI 200 daily returns is done during the period from 3 January 2003 to 29 June 2007. Since Korea Exchange(KRX) will launch VKOSPI futures contract in 2010, forecasting VKOSPI can be an important issue. So we analyze which volatility measurements forecast VKOSPI better. To test this hypothesis, we use 5-minute interval returns to measure realized volatilities. Also, we propose a new methodology that reflects the synchronized bidding and simultaneously takes it account the difference between overnight volatility and intra-daily volatility. The t-test and F-test show that our new realized volatility is not only different from the realized volatility by a conventional method at less than 0.01% significance level, also more stable in summary statistics. We use the correlation analysis, regression analysis, cross validation test to investigate the forecast performance. The empirical result shows that the realized volatility we propose is better than other volatilities, including historical volatility, implied volatility, and convention realized volatility, for forecasting VKOSPI. Also, the regression analysis on the predictive abilities for realized volatility, which is measured by our new methodology and conventional one, shows that VKOSPI is an efficient estimator compared to historical volatility and CRR implied volatility.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.2
• /
• pp.281-292
• /
• 2014

As the importance of algorithm trading is getting stronger, researches for artificial intelligence (AI) based trading strategy is also being more important. However, there are not enough studies about using more than two AI methodologies in one trading system. The main aim of this study is development of algorithm trading strategy based on the rough set theory that is one of rule-based AI methodologies. Especially, this study used genetic algorithm for optimizing profit of rough set based strategy rule. The most important contribution of this study is proposing efficient convergence of two different AI methodology in algorithm trading system. Target of purposed trading system is KOPSI200 futures market. In empirical study, we prove that purposed trading system earns significant profit from 2009 to 2012. Moreover, our system is evaluated higher shape ratio than buy-and-hold strategy.

• The Korean Journal of Financial Management
• /
• v.22 no.1
• /
• pp.71-91
• /
• 2005

The object or this paper is to analyze the rollover effect on KOSPI 200 index option prices. Especially we analyze the implied volatilities of the options that became the near maturity options as the old one expired. For this analysis, a panel data of KOSPI 200 Index Option Prices from year 1999 to year 2001 were used, and following results were obtained. First, after controlling for the underlying index returns, strike prices and other pricing factors, the call option prices tend to decrease while the put option prices tend to increase during the week of expiry. Second, if one concentrates on the daily price changes, call option prices tend to go up on Thursday (as the old options expire), and then experience a price decrease on the following day, while the reverse is true for the put options. These results imply that the option prices are affected by some of the market micro-structure effects such as whether the option is the near maturity option. We conjecture that the reason for this is related to the undervaluation of KOSPI 200 futures. The results from this paper have implications on the timing of option trades. If one wants to buy put options, and/or sell call options, he has better off by executing his intended trades before the old options expire. On the other hand, if one wants to buy call options, and/or sell put options, hi has better off by executing his intended trades after the expiry.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.1
• /
• pp.189-195
• /
• 2014

In this research, we investigate the relationship between volatility and the trading volumes of trader types in the KOSPI 200 index stock market, futures market, and options market. Three types of investors are considered: individual, institutional, and foreign investors. The empirical results show that the volatility of the stock market and futures market are affected by the transaction information from another market. This means that there exists the cross-market effect of trading volume to explain volatility. It turns out that the option market volatility is not explained by any trading volume of trader types. This is because the option market volatility, VKOSPI, is the volatility index that reflects traders' expectation on one month ahead underlying volatility. Third, individual investors tend to increase volatilities, whereas institutions and foreign investors tend to stabilize volatilities. These results can be used in the areas of investment strategies, risk management, and financial market stability.

• The Korean Journal of Applied Statistics
• /
• v.23 no.5
• /
• pp.823-834
• /
• 2010

Stock markets perpetually accumulate information. During trading hours the price instantaneously reacts to new information, but accumulated overnight information reacts simultaneously on the opening price. This can create opening price uctuations. This study explores the overnight information e ects on intra-da stock market volatility. GARCH models and the VKOSPI model are provided. Empirical data includes daily opening and closing prices of the KOSPI 200 index and the VKOSPI from March $3^{rd}$ 2008 to June $22^{th}$ 2010. Empirical results show that the VKOSPI signi cantly decrease during trading time when positiv overnight information moves the Korean stock upward. This study provides useful information to investors since the Korea Exchange plans to introduce a futures market for the VKOSPI soon.

• Korean Business Review
• /
• v.18 no.1
• /
• pp.43-57
• /
• 2005

This paper investigate to test the validity of the basic assumptions of strategic trading models with the broker and informed trader using daily closing data of KOSPI 200 stock index futures for the year 2001-2003. Major results are summarized as follows: (i) For these years, while foreign investors and brokerage companies traded for the directions consistent with the model, brokerage companies and individual investors traded for inconsistent directions. (ii) Cross correlation function (CCF) analysis shows no systematic dependency in the trading between all three participants(foreign investor, brokerage companies and individual investors) for these years. (iii) Chi-square validity test for the 30 days of the largest unexpected trading volume shows some systematic dependency in the trading between three participants for these years. Finally, some limitations of this paper and direction for further research were suggested.

• The Korean Journal of Financial Management
• /
• v.25 no.2
• /
• pp.165-190
• /
• 2008

The degree of informational asymmetry relating to the expiration of index derivatives is usually increased as an expiration day of index derivatives approaches. The increase in the degree of informational asymmetry may have some effects on trading behavior of investors. To examine what the effects look like, 'life cycle of index derivatives' in this study is defined as three adjacent periods around expiration day: pre-expiration period(a week before the expiration day), post-expiration period(a week after the expiration day), and remaining period. It is inspected whether stock investor's trading behavior is changed according to the life cycle of KOSPI200 derivatives and what the reason of the changing behavior is. We have four results. First, trading behavior of each investor group is categorized into three patterns: ㄱ-pattern, L-pattern and U-pattern. The level of trading activity is low for pre-expiration period and normal for other periods in the ㄱ-pattern. L-pattern means that the level of trading activity is high for post-expiration period and normal for other periods. In the U-pattern, the trading activity is reduced for remaining period compared to other periods. Second, individual investors have ㄱ-pattern of trading large stocks according to the life cycle of KOSPI200 index futures while they show U-pattern according to the life cycle of KOSPI200 index options. Their trading behavior is consistent with the prediction of Foster and Viswanathan(1990)'s model for strategic liquidity investors. Third, trading pattern of foreign investors in relation to life cycle of index derivatives is partially explained by the model, but trading pattern of institutional investors has nothing to do with the predictions of the model.