• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.4
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• pp.363-368
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• 2004

The stocks of listed S&M sized firms in the KoreaStock Exchange(KSE) have been neglected to investors for long time in site of their good performences. The word "Neglected" means that the stocks of listed S&M sized firms in the KSE have fail to acquried liquidity. In the result, Listed S&M sized firms in the KSE have not financed equity by issuing stocks timely in the primary market. This problem has resulted in poor investment to their listed S&M sized firms in the KSE. The possible key to sovlve this problem is in the Institutional Investors, especially to the Pension fund. Korean Institutional Investors have lost their basic roles, that is, final supports to prevent the markets not to demolish. The Acts prventing Pension to invest to the stocks is to change to allowing to invest them in soon. this opportunity is good chance to solve the problems of poor liquidity of stocks of listed S&M sized firms in the KSE.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1431-1436
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• 2018

We study the scaling of the price fluctuation in the Korean housing market. From the numerical analysis, we show that the normalized return distribution of the housing price, P(r), has a fat-tail and is well approximated by a power-law, $P(r){\sim}r^{-({\alpha}+1)}$, with ${\alpha}{\simeq}3$ for the whole data set. However, if we divide the data into groups based on the trading patterns, then the value of ${\alpha}$ for positive tail and negative tail can be different depending on the trading patterns. We also find that the autocorrelation function of the housing price decays much slower than that of the stock exchange markets, which shows a unique feature of the housing market distinguished from the other financial systems.

• The Korean Journal of Financial Studies
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• v.2 no.2
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• pp.221-256
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• 1995

This paper compares the intra-day patterns on the NYSE and AMEX of volatility, trading volume and bid-ask spreads for European and Japanese dually-listed stocks with American stocks of comparable average trading volume and volatility. It is shown that the intra-day patterns for these stocks are remarkably similar even though public information flows differ markedly across these stocks during the trading day. In the early morning, all stocks have higher volatility than later in the day, but this phenomenon is most pronounced for Japanese stocks and affects American stocks the least. We argue that these patterns are consistent with markets reacting to the overnight accumulation of public information but are inconsistent with the view that early morning volatility can be attributed to monopolistic specialist behavior.

• Journal of Distribution Science
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• v.13 no.9
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• pp.5-11
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• 2015

Purpose - The purpose of this research is to provide insights that can be used for deliberate decision making around challenging big data investments by measuring the economic value of such big data implementations. Research design, data, and methodology - We perform empirical research through an event study. To this end, we measure actual abnormal returns of companies that are triggered by their investment announcements in big data, or firm size information, during the three-year research period. The research period targets a timeframe after the introduction of big data at Korean firms listed on the Korea stock markets. Results - Our empirical findings discover that on the event day and the day after, the abnormal returns are significantly positive. In addition, our further examination of firm size impacts on the abnormal returns does not show any evidence of an effect. Conclusions - Our research suggests that an event study can be useful as an alternative means to measure the return on investment (ROI) for big data in order to lessen the difficulties or decision making around big data investments.

• Journal of Arbitration Studies
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• v.12 no.2
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• pp.221-262
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• 2003

In recent years, information technological revolution of using Internet in the Stock Market has shown reconsideration of Securities and Exchange Law. Since the 1998 Taipei Conference, ILA have studied upon it and presented 6th Interim Report during the 2000 London Conference. This paper summarizes a part of the 6th Interim Report. The Internet has created a medium to which traditional principles of jurisdiction may not have full relevance. To understand the jurisdictional issues posed by this new medium, we should first review the traditional principles of jurisdiction under international, U. S. law and Other Countries law. In previous reports, the general principles of jurisdiction in international law have been described. These principles are, however, difficult to apply in the context of Internet and other forms of computerized securities trading. Regulators all over the world are trying to address and solve jurisdictional issues raised by the Internet. The traditional rules of jurisdiction in international law, grounded as they are on a geography-based approach, may be in the process of being undermined by the Internet and other global networks allowing for remote access to information and to markets.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• The Journal of Information Systems
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• v.27 no.1
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• pp.193-224
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• 2018

Purpose Targeting Korean companies listed on Korean securities markets (i.e., KOSPI and KOSDAQ markets), this study aims to shed lights the effects of personal information security breaches on stock prices of information security companies. Interestingly, this study is, to the best of our knowledge, the first to examine the information transfer effect on personal information security breaches of companies. Design / Methodology /Approach To examine the information transfer effect of personal information security breaches, our study employs the event study commonly used in financial studies. To this end, we investigate a variety of events of personal information security breaches of companies listed on the KOPSI stock market and the KOSDAQ market. We collect the total samples of one hundred and twelve with forty seven of events of personal information security breaches by thirty companies and sixty five of information security companies. Findings The principal findings from the empirical study are as follows. First, for companies of personal information security breaches, our event study presents the significantly negative AAR (averaged abnormal return) value on the event day at the 5 % level and the highly significant negative CAAR(cumulative averaged abnormal return) value on the event day and the day after the event day at the 1 % level. The results suggest that personal information breaches significantly contribute to an decrease in value of the information breached companies. The cross sectional regressions in this study estimate the significantly negative coefficient for the ME/BE variable, the proxy for a growth opportunity at the 5 % level. This suggests a reverse relation between the growth opportunity of companies and their value. As for the various samples of the information security companies categorized by physical security, network and system security, security application software, code authentication, system integration, we find the significantly positive AAR on the day after the event day at the 5% level, only for the network and system security-companies. This addresses that the information transfer effect followed by personal information breaches is uniquely observable for companies categorized into network and system companies. The regressions for the network and system companies estimate the significantly positive coefficient for the NS dummy variable (i.e., the dummy of the network and system security companies) at the standard level. This allows us to identify appropriate times needed to make the information transfer effect realized from personal information breached companies to information security companies.

• International Area Studies Review
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• v.12 no.3
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• pp.195-216
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• 2008

It is generally accepted that the momentum strategies are effective in the short-term, and the contrarian strategies are profitable in the long run in major stock markets in the world. In Korean market, however, the contrarian is considered effective investment strategy both in the short- and long-term. We investigate whether this is true after 1999, and try to find out the reasons for this phenomena. We found that the contrarian strategies are still effective. Foreign investors showed consistent investment behavior both in Korean and abroad: they followed momentum in the short-tem, and contrarian in the longer-term. The individual investors, who are thought to be noise trader, showed different behavior. They followed contrarian strategies both in the short-and long-term. The reason that the contrarian is observed in Korean market regardless of the investment horizon is thought to be the irrtional behavior of individual investors.