• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.730-736
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• 2011

In this paper, we designed the models for pattern classification which can reflect the latest trend in time series. It has been shown that fusion models based on statistical and AI methods are superior to traditional ones for the pattern classification model supporting decision making. Especially, the hit rates of pattern classification models combined with fuzzy theory are relatively increased. The statistical SVM models combined with fuzzy membership function, or the models combining neural network and FCM has shown good performance. BPN, PNN, FNN, FCM, SVM, FSVM, Decision Tree, Time Series Analysis, and Regression Analysis were used for pattern classification models in the experiments of this paper. The economical indices DB with time series properties of the financial market(Korea, KOSPI200 DB) and the electrocardiogram DB of arrhythmia patients in hospital emergencies(USA, MIT-BIH DB) were used for data base.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.51-58
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• 2024

This paper examines the differences between the Korean and American stock markets using the Kospi and S&P 500 indices and discusses policy implications through them. To this end, in addition to the existing time series analysis method, a deep learning method was used to compare markets, and the comparison was made in terms of stock price forecasting ability and data generation ability. In monthly data, the difference between time series was not large, and in daily data, the difference in terms of stability was weak, and there was no significant difference in predictive power or simulation data generation. As shown in the results of this study, if there is not much difference in market price movement patterns between Korea and the United States, tax benefits for long-term stocks investment will be effective against the side effects of short selling.

• Management & Information Systems Review
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• v.26
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• pp.293-309
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• 2008

This study examined the market efficiency of korea stock market by comparing variance ratios(VR) of stock groups which is sorted by market capitalization. We compute variance ratios of KOSPI large capitalization, midium capitalization, and small capitalization for 546 trading days from 2006/01/02 to 2008/04/15. For our study, we also use high frequency data that is; intra-day 1 minute data. The characteristics of variance ratios of stock groups by market capitalization as follows: From 1 to 5 minute interval, variance ratios of three stock group increase far from zero(0). The longer time interval, the more variance ratios decrease, but only large capitalization converge on around zero. This means that the market of large capitalization is more efficient compare to other stock groups. The entire sample period can be divided two sub-period because the impact of sub prime crisis arised from U.S.A. influences Korea stock market. Before sub prime crisis, the VRs of mid cap and small cap do not converge on around zero except large cap although the time interval is longer. After sub prime crisis, the VRs of three stock groups decrease when time interval is longer, but only large cap converge on around zero. We conclude that large cap is more efficient than other stock groups in Korea Stock Market.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.441-450
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• 2014

The stock market is constantly changing and sometimes the stock prices unaccountably plummet or surge. So, the stock market is recognized as a complex system and the change on the stock prices is unpredictable. Recently, many researchers try to understand the stock market as the network among individual stocks and to find a clue about the change of the stock prices from big data being created in real time from Internet. We focus on the correlation between the stock prices and the human interactions in Internet especially in the stock message boards. To uncover this correlation, we collected and investigated the articles concerning with 57 target companies, members of KOSPI200. From the analysis result, we found that there is no significant correlation between the stock prices and the article volume, but the strength of correlation between the article volume and the stock prices is relevant to the stock return. We propose a new method for recommending stock portfolio base on the result of our analysis. According to the simulated investment test using the article data from the stock message boards in 'Daum' portal site, the returns of our portfolio is about 1.55% per month, which is about 0.72% and 1.21% higher than that of the Markowitz's efficient portfolio and that of the KOSPI average respectively. Also, the case using the data from 'Naver' portal site, the stock returns of our proposed portfolio is about 0.90%, which is 0.35%, 0.40%, and 0.58% higher than those of our previous portfolio, Markowitz's efficient portfolio, and KOSPI average respectively. This study presents that collective human behavior on Internet stock message board can be much helpful to understand the stock market and the correlation between the stock price and the collective human behavior can be used to invest in stocks.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.63-94
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• 2013

This study aims to understand the long-run movement of volatility in Korean stock market by decomposing stock volatility into the long-lived and the short-lived components. In addition, I analyze how the low-frequency movement of stock market volatility is related to changes in macroeconomic conditions. The volatility decomposition is made based on the GARCH-MIDAS model, in which the long-lived volatility is constructed based on the combination of realized volatilities (RVs). The results show that the long-lived volatility contains information of up to 3~4 years of past RVs. In addition, the changes in the long-lived volatility can explain about two thirds of volatility changes in the Korean stock market from 1994 to 2009. Meanwhile, the low-frequency movement in the market volatility can be related to changes in macroeconomic conditions. The analysis shows that the stock market volatility appears to be countercyclical while showing a positive correlation with the inflation. In addition, the stock market volatility tends to rise as macroeconomic uncertainty increases. These results imply that macroeconomic policies aiming at economic stabilization could contribute to reduction in the stock market volatility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.480-488
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• 2016

As the subprime mortgage crisis spread globally, it depressed not only the financial market, but also the construction business in Korea. In fact, according to CERIK, the BSI of the construction businesses plunged from 80 points in December 2006 to 14.6 points in November 2008, and the extent of the depression in the housing sector was particularly serious. In this respect, this paper analyzes the influence of the financial market fluctuation on the housing market before and after the Global Financial Crisis using VECM. The periods from January 2000 to December 2007 and January 2008 to October 2015, before and after the financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, when the economy is good, the Gangnam housing market is an attractive one for investment. However, when it is depressed, the Gangnam housing market changes in response to the macroeconomic fluctuations. Second, the Gangbuk and Gangnam housing markets showed different responses to fluctuations in the financial market. Third, when the economy is bad, the effect of low interest rates is limited, due to the housing market risk.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.212-223
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• 2016

The purpose of this study is to verify information spillover effects using returns of macroeconomic variables and hotel leisure stock index daily data from January 4, 2000 to December 30, 2015. The findings and implications of the research can be summarized as follows. First, based on time-varying AR(1)-GARCH(1,1) models no evidence of statistically significant conditional mean and volatility spillover effects from returns of macroeconomic variables on the hotel leisure stock index was observed. In addition, no evidence of price volatility spillover from macroeconomic variables on the hotel leisure market was observed. Second, it was discovered that there exists a significantly negative relationship between the return of ER and hotel leisure stock prices, but a positive relationship between the KOSPI and hotel leisure stock prices. Finally, the study also found that was a significantly positive relationship between the volatility of DUB and hotel leisure market, and an adversely negative relationship between the volatility of ER and hotel leisure market. The results of this study are expected to contribute by providing useful information for investment strategies, as well as for risk management for investors and managers.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.37-47
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• 2011

Stock price index option market has various investment strategies that have been developed. Specially, arbitrage strategies are very important to be efficient in option market. The purpose of this study is to improve profit using rough set and Box spread by using past option trading data. Option trading data was based on an actual stock exchange market tick data ranging from 2001 to 2006. Validation process was carried out by transferring the tick data into one-minute intervals. Box spread arbitrage strategies is low risk but low profit. It can be accomplished by back-testing of the existing strategy of the past data and by using rough set, which limit the time line of dealing. This study can make more stable profits with lower risk if control the strategy that can produces a higher profit module compared to that of the same level of risk.

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

• Management & Information Systems Review
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• v.31 no.3
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• pp.21-46
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• 2012

This paper attempts to offer an effective strategy of hedge fund based on trade probability control in the futures market. By using various technical indicators, we create an association rule and transforms it into a trading rule to be used as an investment strategy. Association rules are made by the combination of various technical indicators and the range of individual indicator value. Adjustments of trade probabilities are performed by depending on the rule combinations and it can be utilized to establish an effective investment strategy onto the risk management. In order to demonstrate the superiority of the investment strategy proposed, we analyzed a profitability using the futures index based on KOSPI200. Experiments results show that our proposed strategy could effectively manage and response the dynamics investment risks.