• International journal of advanced smart convergence
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• v.12 no.4
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• pp.111-118
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• 2023

In the ever-changing landscape of finance, the fusion of artificial intelligence (AI)and pair trading strategies has captured the interest of investors and institutions alike. In the context of supervised machine learning, crafting precise and accurate labels is crucial, as it remains a top priority to empower AI models to surpass traditional pair trading methods. However, prevailing labeling techniques in the financial sector predominantly concentrate on individual assets, posing a challenge in aligning with pair trading strategies. To address this issue, we propose an inventive approach that melds the Triple Barrier Labeling technique with pair trading, optimizing the resultant labels through genetic algorithms. Rigorous backtesting on cryptocurrency datasets illustrates that our proposed labeling method excels over traditional pair trading methods and corresponding buy-and-hold strategies in both profitability and risk control. This pioneering method offers a novel perspective on trading strategies and risk management within the financial domain, laying a robust groundwork for further enhancing the precision and reliability of pair trading strategies utilizing AI models.

• 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.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.3
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• pp.13-24
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• 2017

This paper aims to implement "structural changes detection procedure" in pairs trading algorithm and to show that the proposed approach outperforms the extant pair trading algorithm. Structural changes in pairs trading are defined in terms of changes in cointegrating factors and broken cointegration relationship. These changes are designed to test extant structural changes and unit root test methodologies. The simulation finds that expanding the changes in structure, increasing the mean reverting process of spread, and extending the consecutive days of broken cointegration will increase the performances of the proposed algorithm. Empirical study results are also consistent those of the simulation studies. The proposed algorithm outperforms the extant algorithm relative to risk and return given that the cumulative profit/loss has a significant upward-slope with minimal variance.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.271-278
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• 2017

There has been an influx of traders and researchers eager to gain a better understanding of the market due to the rapid growth of the FOREX market. Traders with varying degree of experience are also often inundated with information, analysis methods as well as trading rules when making a trading decision on buying/selling a currency exchange pair. Thus, this paper reviews the current computational tools and analysis methods used within the FOREX trading community and proposes the development of a web-based trading platform with e-learning features to support beginners. Novice traders could also benefit from the use of the proposed e-learning trading platform as it helps them gain valuable knowledge and navigate the FOREX market in real-time. Even experienced traders would find it useful as the platform could be used for actual trading and acts as a reference point to understand the reasoning behind the certain technical analysis implementation that are still unclear to them.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.557-564
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• 2014

In general, board games are just want to buy a pair of board games to play, but in recent years, a new type of the game - Trading card game (TCG) by the vast number of players, Trading card game with its own custom personal hand gameplay and diversified combination tactics when the game is won a high popularity. And there are a few long Trading card game popularity will continue on to now, the growing popularity of such as the board game market needs will continue to continue.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.545-546
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• 2021

최근 주식시장의 관심이 급격하게 높아지고 있으며, 코로나 19의 영향으로 신규 투자가 더욱더 늘어나고 있다. 하지만 개인의 투자자의 경우 기관보다 취득할 수 있는 정보의 양이 제한적이고 정보의 취득 시점이 늦기 때문에 개인의 투자자는 정보를 주관적으로 판단할 수밖에 없는 문제점이 있다. 따라서 본 논문에서는 주식매매의 객관적인 판단을 위하여 페어 트레이딩 기반 빅데이터 분석을 이용하여 주식 매매 시기를 사용자에게 알려주는 알림 시스템을 제안한다. 주식 매매 시기 알림 시스템을 적용할 때 사용자에게 객관적인 주식 매매 시기를 알려주어 투자 손해를 줄일 수 있을 것으로 기대한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.348-353
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• 2013

Recently, control theory including stochastic optimal control and various machine-learning-based artificial intelligence methods have become major tools in the field of financial engineering. In this paper, we briefly review some recent papers utilizing stochastic optimal control theory in the fields of the pair trading for mean-reverting markets and the trend-following strategy, and consider a couple of strategies utilizing both stochastic optimal control theory and machine learning methods to acquire more flexible and accessible tools. Illustrative simulations show that the considered strategies can yield encouraging results when applied to a set of real financial market data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.1
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• pp.3-13
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• 2004

E-Commerce is suddenly spreading in a daily life. A rights trading system is a system that circulates digital-tickets such as plane tickets, software license, coupon. There are two main approaches so far account-based and smart-card based systems. The NTT Proposed FlexToken, a new smart card based copy prevention scheme for digital rights. They Proposed using pseudonymous self certified keys of Petersen and Horster in order to ensure anonymity of users. However. Petersen and Holster's scheme should register a pseudonymous key pair at TTP (One-time) every time so that users create the signature which is satisfied with unlinkability property In this paper, we propose a new anonymous rights trading system using group signature. This paper has a meaning having applied to digital rights trading system an efficient smart card based group signature.

• Management Science and Financial Engineering
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• v.20 no.1
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• pp.11-16
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• 2014

Extending from Grossman and Stiglitz (1980), we provide an asset pricing model of a synchronously traded cross-listed pair under information asymmetry. Following Garbade and Silber (1983), the model further embraces multi-market price discovery in a dynamic framework. The implications are as follows: The price sensitivity of holdings is higher for informed traders than for uninformed traders; the largest cross-border price spread occurs in the absence of arbitrageurs; price discovery is more likely in markets with a larger population of informed traders; and parity convergence accelerates with a higher price elasticity of demand of arbitrageurs.