• Korean Management Science Review
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• v.33 no.4
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• pp.1-15
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• 2016

Pairs trading is an arbitrage trading strategy using statistical properties of the spreads between two assets. This study analyzes the performance of the statistical pairs trading with the pairs selected from the same category as well as from the different category in the CME and other futures markets. Empirical results show that the pairs trading performance of the same category is poor whereas that of the different category proves profitable. This implies that the spreads between different category pairs can have the mean reversion property if pairs are properly selected using co-integration test, which is contrary to the existing research results on the overseas futures pairs trading.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.235-261
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• 2003

We examine the relationship between the trading activities of Korea Stock Price Index (KOSPI) 200 futures contract and its underlying stock market volatility for about six years from May 1996 when the futures contract was introduced. The trading activities of the futures contracts are proxied by the volume and open interest, which are divided into expected and unexpected portions by using the previous data. The daily, intradilay, and overnight cash volatility is estimated by the GJR-GARCH model. We find a positive contemporaneous relationship between the intradaily stock market volatility and the unexpected futures volume while the relationship between the volatility and expected futures volume is weakly negative or non-existent. We also find that the unexpected futures volume strongly causes intradaily cash volatility. On the other hand, the overnight cash volatility causes the unexpected futures volume. The impulse responses between these variables are all positive. The result implies that during a trading time futures trading tends to increase the cash volatility while the unexpected overnight changes in cash volatility tends to increase the futures trading activities. We, however, find no association between the cash volatility and futures maturities.

• Journal of Distribution Science
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• v.15 no.11
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• pp.73-82
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• 2017

Purpose - This paper aims to investigate a profit maximizing incentive of foreign traders in distributing the KOSPI 200 Futures. Such an incentive may induce unsophisticated retail traders to suffer loss from speculative trading. Since Korean government increased the entry barriers of the market to protect unsophisticated traders, the market size has been decreasing while the proportion of the contract held by foreign traders has been increasing. These on going changes make the market imperfectly competitive, where a profit maximization incentives of foreign traders are expected to grow. In this paper, we attempt to find any evidence of such behavior, thereby providing implications regarding market policy and market efficiency. Research design, data, and methodology - According to Kyle(1985), an informed trader exploits his/her monopoly power optimally in a dynamic context so that he/she makes positive profit, where he/she could conceal his/her trading utilizing noise trading as camouflage. We apply the KOSPI 200 Futures market to the Kyle's model: foreign traders who take into account the effect of his/her trading to maximize expected profits as an informed trader, retail investors as noise traders, and financial institutions as market makers. To find any evidence of monopolistic behavior, we test the variants of trading volume and price data of the KOSPI 200 Futures over the period of 2009 and 2017. Results - First, we find that the price of the KOSPI 200 Futures are more volatile than the price of underlying asset. Second, we find that monopolistic foreign trader's trading order flows are consistent with exploiting his/her monopoly power to maximize profit. Finally, we find that retail investors' trading order flows are inversely consistent with maximizing profit, that is, uninformed retail investors suffer loss continuously in speculative trading against informed traders. Conclusions - Our results show that the quantity of strategic order flows may have a large effect on the price, therefore, resulting the market inefficiency. The results also imply that, in implementing regulations, the depth of the market must be considered to maintain market liquidity, and suggesting interesting research topics regarding the market structure.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.85-97
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• 2018

This paper investigates factors underlying a decrease in trading values in KOSPI 200 futures/options market on the basis of the current state of the markets. Among the factors that could affect trading values in KOSPI 200 derivatives market, we focus on the market activity of underlying assets as it has an impact on the trading of financial derivatives. Trading value and volatility are designated as market activity and the empirical results confirm that the market activity of the underlying assets is significant in explaining the decrease in trading values in KOSPI 200 futures/options market. To figure out fundamental reasons of the decrease in trading values in this market, we examine mitigation of home bias and decrease in leverage incentives as they are presumed to have influence on KOSPI 200 index market. As the global and local financial environment is time-varying, the degree of home bias and the leverage demand also changes. It implies that institutional change and/or policy effort to promote the trading of KOSPI 200 financial derivatives should be made taking into account the fact that considerable portion of the change in trading values in financial derivatives market depends on the state of the market.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.881-893
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• 2012

This paper proposes to develop system trading strategy using rough set, decision tree in futures market. While there is a great deal of literature about the analysis of data mining, there is relatively little work on developing trading strategies in futures markets. There are three objectives in this paper. The first objective is to analysis performance of decision tree in rule-based system trading. The second objective is to find proper profitable trading interval. The last objective is to find optimized training period of trading rule training. The results of this study show that proposed model is useful trading strategy in foreign exchange market and can be desirable solution which gives lots of investors an important investment information.

• 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.

• Korean Business Review
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• v.12
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• pp.119-138
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• 1999

In this study, we empirically investigate the relations between trading volumes and our proxies for information flows and differences of opnion. Econometric methods to analyze the relations in the equity and KOSPI 200 futures markets include Generalized Method of Moment(GMM) and Generalized Autoregressive Conditional Heteroscedasticity(GARCH) models. Major findings from our empirical analyses are summarized as follows; (i) Trading volume in both the equity and KOSPI 200 futures markets varies positively with proxies for information flows. We find that trading volumes in both markets are closely related to firm-specific information rather than market-wide information. (ii) Trading volumes in the equity and KOSPI 200 futures market have positive relations with our proxies for differences of opinion. (iii) Day-of-the-week effect is clear in both markets. Trading volumes in both the equity and KOSPI 200 futures markets tend to be relatively low early and late in the week. (IV) Futures contract life-cycle effect is clear. In other words, futures trading volume increses in the period around contract expiration. (V) In addition, ARCH effect on trading volumes is reported significant enough to take into account. The disturbance of trading volumes in both markets seem to be conditional heteroscedastic.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.3
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• pp.5-16
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• 2014

This study aims to examine the dynamics of price changes and trading volume of Kuala Lumpur Options and Financial Futures Exchange (KLOFFE) from 2000 to 2008. With augmented analysis, our results support two hypotheses. First, under information spillover, our findings support noise traders' hypothesis as the time span for variance of past trading volume to cause variance of current return is found to be asymmetric under bull and bear markets. Second, looking at the dynamic relation between volume and volatility of price changes, our findings support Liquidity-Driven Trade hypothesis as past trading volume and subsequent volatility of return exhibit positive correlation. In terms of investors' behavior in response to the news, we find that investors are more risk taking in bull market and more risk reverse in bear market. Our study suggests that investors should adjust their strategy in the futures market in a dynamic manner as the time span of new information arrival is not consistent. Also, uninformed investors with information asymmetry should expect noninformational trading from informed investors to establish their desired positions for better liquid position.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.51-59
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• 2020

The objective of this study is to enrich the literature by investigating the impact of introduction of index future trading on spot market returns and trading volume in Vietnam. Data used in this study mainly consist of daily VN30-Index and market trading volume series during the period from February 6^th, 2012 to December 31^st, 2019. Using OLS, GARCH(1,1) and EGARCH(1,1) models, the empirical findings consistently confirm that the introduction of index future trading has no impact on the spot market returns. In addition, the results of the EGARCH(1,1) model indicate that the leverage effect on the spot market volatility is existence in HOSE. Specifically, bad news has a greater effect on the market volatility than good news of the same size. Moreover, our empirical findings reveal that the introduction of index future contracts has the positive impact on the underlying market trading volume. Specifically, the trading volume of the post-index futures introduction increases by 7.5 percent compared with the pre-index futures introduction. Finally, the results obtained from the Granger causality test for the relationship between the spot market returns and the future trading activity confirm that only uni-directional causality running from the market returns to the future trading activity exists in HOSE.

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