• 경영과학
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• 제32권4호
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• pp.57-67
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• 2015

It is a familiar Wall Street adage that "It takes volume to make prices move." Numerous researches have found the positive correlation between trading volume and price changes. Recent studies have documented that informed traders have strong influences on stock market prices through their trading with distinctive information power. Ever since 1992 capital market liberalization in Korea, it is said that foreign investors make consistent profits with their superior information and analytical skills. This study aims at whether we can make a profitable trading strategy by using the foreign investors' trading information. We analyse the relation between the KOSPI index returns and the foreign investors trading volume using GARCH models and VAR models. This study suggests the profitable trading strategies based on the documented relation between the foreign investors' trading volume and KOSPI index returns. We simulate the trading system with the real stock market data. The data include the daily KOSPI index returns and foreign investors' trading volume for 2001~2013. We estimate the GARCH and VAR models using 2001~2011 data and simulate the suggested trading system with the remaining out-of-sample data. Empirical results are as follows. First, we found the significant positive relation between the KOSPI index returns and contemporaneous foreign investors' trading volume. Second, we also found the positive relation between the KOSPI index returns and lagged foreign investors' trading volume. But the relation showed no statistical significance. Third, our suggested trading system showed better trading performance than B&H strategy, especially trading system 2. Our results provide good information for uninformed traders in the Korean stock market.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.737-745
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• 2021

This study aims to determine whether there are differences in the average abnormal return, trading volume activity, and trading frequency activity in pharmaceutical stocks before and after the announcement of the first case of the coronavirus (COVID-19) in Indonesia. The sample was selected using a purposive sampling method and collected as many as nine pharmaceutical companies listed on the Indonesia Stock Exchange during 2019-2020. The data used in this study were secondary data in the form of daily data on stock closing prices, Composite Stock Price Index (IHSG), stock volume trading, number of shares outstanding, and stock trading frequency. This study was an event study with an observation period of 14 days, namely seven days before and seven days after the announcement of the coronavirus's first positive case in Indonesia. Hypothesis testing employed the paired sample t-test method. Based on the results, it was found that there was no difference in the average abnormal return of pharmaceutical stocks before and after the announcement of the first case of COVID-19. However, there was a difference in the average trading volume activity and the average trading frequency activity in pharmaceutical stocks before and after the announcement of the first case of COVID-19.

• 한국정보시스템학회지:정보시스템연구
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• 제23권1호
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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.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1099-1106
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• 2006

This study is an analysis of the stock trading value in terms of investor types in the Korean stock market for recent 12 years. We examined the characteristics in stock trading value variation according to each investor type and the interactive relationship in the trading value between types of investors. The results show that the trading value scale of every investor type increases overall while the proportion of the trading value by each investor type in the market exhibits variation. In addition, a statistically significant interactive relationship in the trading value between types of investors exists: the correlations are formed differently before and after events which largely influence the stock market.

• Journal of Information Technology Applications and Management
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• 제21권4호
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• pp.1-13
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• 2014

This study aims to show the risk reduction effects of round-the-clock trading environment. We analyse the trading results of the currency futures contracts in CME Globex which are open 23 hours a day. These include Euro FX, Japanese Yen, Australian Dollar, and British Pound from January 2005 to August 2013. We generate new price series using only daytime prices during about 7-hour period. This hypothetical "G" data series may have greater gap risk than the original "R" data series. Empirical results show the trading risk reduction effects, that is R data series have higher profits and lower risks than G data series.

• 패션비즈니스
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• 제10권1호
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• pp.148-163
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• 2006

The purpose of this study is to examine differences in university students' spatial behavior and time for purchasing weekdays or weekends according to trading areas they use to purchase casual wears. Theoretical background examined trading areas, in Busan, consumers' spatial behavior. An empirical research developed a questionnaire as a measuring tool to conduct a preliminary survey and a main survey. Data collection was implemented with 507 students from four universities in Busan; and for data analysis, descriptive statistics, cross-tabulation analysis, correspondence analysis, and McNemar test were carried out by using the SPSS for Windows 12.0K program. This study obtained the main results as follows: The characteristics of university students' spatial behavior according to trading areas show significant difference in reasons of trading area selection, time slots for visiting. University students who visited the Seomyeon trading area were found to consider comparison-based purchasing and prominence of the trading area, regardless of the time for purchasing weekdays or weekends. As for trading areas around Busan National University, visits were mainly due to accessibility. Students visited trading areas in Nampo-Gwangbok-dong regardless of the time for purchasing in diverse reasons of trading area selection, time slots. As for trading areas around Kyungsung University, students were visited due to accessibility.

• 지능정보연구
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• 제17권3호
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• pp.187-201
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• 2011

방향성(Direction)과 변동성(Volatility)에 대한 분석은 증권투자를 위한 시장분석의 기초가 된다. 변동성분석이 옵션 투자에서 중요하다면 주식이나 주가지수선물투자는 방향성분석에 의하여 투자성과가 결정된다. 기존의 금융분석에서 기계학습을 이용한 방향성에 대한 연구는 주가나 투자위험의 예측을 중심으로 이루어졌으며, 최근에 와서야 실전투자를 위한 매매시스템(trading system) 개발에 대한 연구가 이루어지고 있다. 인공지능형 주가예측모형에서는 ANN(artificial neural networks), fuzzy system, SVM(Support Vector Machine) 등의 기법이 주로 활용되고 있다. 본 연구에서는 방향성매매를 위한 지능형 기계학습방법 중에서도 패턴인식에서 좋은 성과를 보이고 있는 은닉마코프 모형(Hidden Markov Model)을 이용한다. 실무적으로는 방향성 예측을 위해 주로 주가의 추세분석(Trend Analysis)을 활용한다. 다양한 기술적 지표를 이용한 추세분석에 기반한 시스템트레이딩(System Trading) 기법은 실전투자에서 점차 확대추세에 있다. 본 연구에서는 시스템트레이딩 기법 중 실무에서 많이 이용되는 이동평균교차전략(moving average cross)에 연속 은닉마코프모형을 적용한 지능형 매매시스템을 제안하고, 실제 주가자료를 이용한 시뮬레이션 결과를 제시한다. 세계적 선물시장으로 성장한 KOSPI200 선물시장에서 제안된 매매시스템의 장기간의 투자성과를 분석하기 위하여 지난 21년 동안의 KOSPI200 주가지수자료를 실증 분석하였다. 분석결과는 KOSPI200 주가지수선물의 방향성매매에서 제안된 CHMM기반 지능형 매매시스템이 실전에서 일반적으로 활용되는 시스템트레이딩 기법의 투자성과를 개선할 수 있음을 보여주었다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권3호
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• pp.123-140
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• 2018

Purpose The purpose of this study is to explore the optimal trading frequency which is useful for stock price prediction by using deep learning for charting image data. We also want to identify the appropriate time for accurate forecasting of stock price when performing pattern analysis. Design/methodology/approach In order to find the optimal trading frequency patterns and forecast timings, this study is performed as follows. First, stock price data is collected using OpenAPI provided by Daishin Securities, and candle chart images are created by data frequency and forecasting time. Second, the patterns are generated by the charting images and the learning is performed using the CNN. Finally, we find the optimal trading frequency patterns and forecasting timings. Findings According to the experiment results, this study confirmed that when the 10 minute frequency data is judged to be a decline pattern at previous 1 tick, the accuracy of predicting the market frequency pattern at which the market decreasing is 76%, which is determined by the optimal frequency pattern. In addition, we confirmed that forecasting of the sales frequency pattern at previous 1 tick shows higher accuracy than previous 2 tick and 3 tick.

• 수산경영론집
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• 제32권1호
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• pp.1-14
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• 2001

The research on the price-volume relation in the market is very important because it examines into regular phenomenon revealed by market participants including producers and middlemen. The purpose of this study is to investigate the relationship between price and trading volume in the oyster producing market. In order to accomplish the purpose of this study, the contents of empirical analysis include the time series properties of price and trading volume, the short-term and long-term relationships between price and trading volume, and the determinants of trading volume. The data used in this study correspond to daily price and trading volume covering the time period from January 1998 to April 2001. The empirical results can be summarized as follows : First, price and trading volume follow random walks and they are integrated of order 1. The first difference is necessary for satisfying the stationary conditions. Second, price and trading volume are cointegrated. This long-run relationship is stronger from trading volume to price. Third, error correction model suggests that feedback effect exists in the long-run and that price tends to lead trading volume by about five days in the short run, that is, to be required period by digging, conveying, and peeling oystershell for selling oyster. Fourth, price and price volatility is a determinant of trading volume. In particular, trading volume is a negative function of price. It is believed that the conclusion drawn from this study would provide a useful standard for the policy makers in charge of reducing the oyster price volatility risk caused by trading volume(selling quantities).

• 한국IT서비스학회지
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• 제13권2호
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• pp.151-161
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• 2014

KOSPI 200 index options market has the highest trading volume in the global options markets. The risk and return structure of options contracts are very complex. Volatility complicates options trading because volatility plays a central role in options pricing process. This study develops a trading system for KOSPI 200 index options trading using KOSPI 200 volatility index. We design a database system to handle the complex options information such as price, volume, maturity, strike price, and volatility using Oracle DBMS. We then develop options trading strategies to test how the volatility index is related to the prices of complicated options trading strategies. Back test procedure is presented with PL/SQL of Oracle DBMS. We simulate the suggested trading system using historical data set of KOSPI 200 index options from December 2008 to April 2012.