• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.202-211
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• 2014

Pairs trading is a type of arbitrage investment strategy that buys an underpriced security and simultaneously sells an overpriced security. Since the 1980s, investors have recognized pairs trading as a promising arbitrage strategy that pursues absolute returns rather than relative profits. Thus, individual and institutional traders, as well as hedge fund traders in the financial markets, have an interest in developing a pairs trading strategy. This study proposes pairs trading rules (PTRs) created from a price ratio between securities (i.e., stock index futures) using rough set analysis. The price ratio involves calculating the closing price of one security and dividing it by the closing price of another security and generating Buy or Sell signals according to whether the ratio is increasing or decreasing. In this empirical study, we generate PTRs through rough set analysis applied to various technical indicators derived from the price ratio between KOSPI 200 and S&P 500 index futures. The proposed trading rules for pairs trading indicate high profits in the futures market.

• Korean Management Science Review
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• v.31 no.1
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• pp.49-61
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• 2014

We investigate the hedging effectiveness of incorporating single-stock futures into the corresponding stocks. Investing in only stocks frequently causes too much risk when market volatility suddenly rises. We found that single-stock futures help reduce the variance and risk levels of the corresponding stocks invested. We use daily prices of Korean stocks and their corresponding futures for the time period from December 2009 to August 2013 to test the hedging effect. We also use system trading technique that uses automatic trading program which also has several simulation functions. Moving average strategy, Stochastic's strategy, Larry William's %R strategy have been considered for hedging strategy of the futures. Hedging effectiveness of each strategy was analyzed by percent reduction in the variance between the hedged and the unhedged variance. The results clearly showed that examined hedging strategies reduce price volatility risk compared to unhedged portfolio.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.75-92
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• 2002

This paper is concerned with proposing a new market strategy for the segmented markets of the Internet stock trading. Many companies are providing various services for customers. However, the internet stock trading market is glowing rapidly absorbing a wide variety of customers showing different tastes and demographic information, so that it is necessary for us to investigate specific strategy for the segmented markets. General strategy so far in the Internet stock trading market has been to lower transaction fee according to the market trend. As the advent of rapidly enlarging market, however, more specific strategies need to be suggested for the segmented markets. In this respect, this paper applied a self-organizing map (SOM) to 83 questionnaire data collected from the Internet stock trading market in Korea, and obtained meaningful results.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.133-133
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• 1998

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.123-130
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• 2022

Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.

• The Journal of Information Systems
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• v.23 no.1
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• pp.29-52
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• 2014

As the advance of multi-platform and multi-channel online services, brokerages are now offering three representative online trading systems - HTS(Home Trading Systems), WTS(Web Trading Systems), MTS(Mobile Trading Systems). In this study we investigated and compared the impact of different systems on the performance of brokerages. Using the panel data of 29 brokerages of 4 periods, we empirically tested the impact of online trading systems and the commissions of trading services. We found out that there exist some differences between the impacts of online trading systems based on the platforms. HTS was identified as the main platform for online trading services. However the role of MTS was also significantly identified while WTS showed no significant impact on the brokerage performances. Commission also showed significant negative impact in case of HTS and MTS platforms. Finally, offering MTS was identified as the significant dummy variable influencing the performance of brokerages. The results provides some implication for the multi-platform strategy for online services.

• Knowledge Management Research
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• v.22 no.1
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• pp.21-37
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• 2021

The purpose of this study is to explore financial investment knowledge related to multi-strategy, which is not generally shared. Through case studies, we will share it with the domestic hedge fund market. Since the era of full-fledged private equity hedge funds in Korea opens, many funds are created; however, reality is that there is a lack of diversity in strategies. Initially, it started with a simple stock long/short strategy, and various strategies such as mezzanine and alternative investments are in use but funds using multi-strategy are limited. This study aims to present an empirical application plan for hedge fund management strategies using a case study. It will specifically focus on process of achieving Absolute Return using the Multi Strategy technique actively used in securities firms' Prop Trading. With the results of this study, we intend to contribute to those fund managers and desired researchers who are utilizing multiple strategies in the hedge fund management to pursue Absolute Return and to help them strengthening their financial knowledge and competitiveness.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.225-231
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• 2010

This paper proposes the strategy of ladder trades in a symbol pool and simulates a performance of it on the Multicharts' system trading tool. The ladder trading strategy is based on a multi-entry strategy which is efficient for several symbols. A symbol pool is composed of verified stocks comprising KOSPI200 and 17 symbols are selected for an examination which equity is over 10 billion. From July to December in 2009, optimum parameters are searched and the results are delta is 4% and ladder is 5. When those parameters are adopted, the profit is 1,000,000 won as a single trade and the number of trade is 188. The next study is to modify a ladder shape for increasing probability and to find the difference of optimum parameters according to trading months.