• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.63-79
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• 2022

Recently, various studies have been conducted on stock price prediction using machine learning and deep learning techniques. Among these studies, the latest studies have attempted to predict stock prices using limit order books, which contain buy and sell order information of stocks. However, most of the studies using limit order books consider only the trend of limit order books over the most recent period of a specified length, and few studies consider both the medium and short term trends of limit order books. Therefore, in this paper, we propose a deep learning-based prediction model that predicts stock price more accurately by considering both the medium and short term trends of limit order books. Moreover, the proposed model considers news headlines during the same period to reflect the qualitative status of the company in the stock price prediction. The proposed model extracts the features of changes in limit order books with CNNs and the features of news headlines using Word2vec, and combines these information to predict whether a particular company's stock will rise or fall the next day. We conducted experiments to predict the daily stock price fluctuations of five stocks (Amazon, Apple, Facebook, Google, Tesla) with the proposed model using the real NASDAQ limit order book data and news headline data, and the proposed model improved the accuracy by up to 17.66%p and the average by 14.47%p on average. In addition, we conducted a simulated investment with the proposed model and earned a minimum of $492.46 and a maximum of $2,840.93 depending on the stock for 21 business days.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.63-79
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• 2011

In this research, we have investigated the impact of servitization on firm value focused on Fortune 500 company's alliance announcement. The Firms are categorized to understand the impact of servitization and productization. The data includes Fortune 500 companies (2009, USA). Samples used for the hypothesis tests consist of 1,057 American companies that are opened on NYSE and NASDAQ, for the years 1990 through 2010. We test four research hypotheses based upon the various theoretical perspectives in servitization. The market is selective in reacting to alliance category; service company ${\rightarrow}$ manufacturing company, service company ${\rightarrow}$ service company. The findings show that alliance is significant between service company and manufacturing company. Also, the result shows significant relationship inter-service company's alliance. We have a significant relationship between company's alliance announcement and the market value of firms and shows significant AR in financial performance. Finally, this study presents implications for manufacturing companies that pursue service-led expansion as a strategic approach and are seeking to improve market value through alliance, partnership and cooperation. Continual effort must be placed to sustain market value of the firms.

• The Journal of Industrial Distribution & Business
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• v.4 no.2
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• pp.13-19
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• 2013

Purpose - The paper tested the relationship between the stock markets of the Middle East and the USA with the oil price and US dollar index as threshold variables. Research design, data, and methodology - The stock price indices of the USA, the Middle East (Abu Dhabi, Jordan), WTI spot crude oil price, and US dollar index were daily returns in the research period from May 21, 2001 to August 9, 2012. Following Hansen (1999), the panel threshold regression model was used. Results - With the US dollar index as the threshold variable, a negative relationship existed between the stock price indices of Jordan and the USA but no significant result was found between the stock price indices of Abu Dhabi and the USA. Conclusions - The USA is an economic power today:even if it has a closer relationship with the US stock market, the dynamic US economy can learn about subsequent developments and plan in advance. Conversely, if it has an estranged relationship with the US stock market, thinking in a different direction and different investment strategies will achieve good results.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.369-376
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• 2013

Finance Information System is critical national infrastructure. Therefore it is important to select variables of defect causal factor for the system defect management effectively. We research and analyze detected errors in A Company's Finance Information System for three years. In the result of research and analysis, we have selected 9 variables of defect factor: the trading volume, the fluctuation of KOSDAQ index, and the number of public announcements, etc. Then we have assumed that these variables affect real system errors and analyzed correlation between the hypothesis and the detected system errors. After analyzing, we have extracted the trading volume, the number of orders and fills, changing tasks, and the fluctuations of NASDAQ index as valid variables of defect factor. These variables are proposed for failure prediction model as the variables to manage defects in the finance information system afterward.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.103-126
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• 2017

By the means of pervasiveness of ICT, ICT firms in the dynamic competition try to get the competitive advantage through the combination with the other industrial technologies and the firms in other industries also seek innovations in this way. To ICT suppliers, the application industries were completely different before but if ICT is applied to that industries once, the convergence phenomenon could occur as a part of an ICT industry. So, this research focuses the causality between ICT supplier's behavior and technological convergence according to the research question about what should ICT firms do for ICT convergence. We observed technological changes in the automotive industry through the Nasdaq listed firms' patent activities of 10-year period from the perspective of evolutionary theory. As a result, while the innovativeness of technological trials by ICT suppliers enhances the possibility of technological convergence, diversity of those can reduce the emergence of ICT convergence. This implies that ICT firms should focus specialized technologies for convergence rather than various technological options for the uncertain future.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.223-228
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• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.181-200
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• 2003

Comovement of international stock market prices has been lately a major controversy in the global stock market. This paper explores whether the common trend has really existed among the US, Japan and Korea's stock markets using the econometric techniques such as VAR, VECM as applied. Pair of indices from the exchange market and the over-the-counter market in each country has been tested, and the exchange market only has been turned out that the common trend existed. The dynamic analyses using the Granger causality test, impulse response function, and the forecast error decomposition have followed to show that the US stock market has played some important role in the Korea and Japan's market in the exchange as well as in the OTC market. The results of the paper imply that the more careful investigation with respect to the co-integration may be necessary in the global market integration studies.

• The Journal of Small Business Innovation
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• v.19 no.3
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• pp.17-42
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• 2016

Financial Accounting Standards Board (FASB) Interpretation No. 48 (FIN 48), Accounting for Uncertainty in Income Taxes: An interpretation of FASB Statement No. 109, requires firms to evaluate uncertain tax positions and disclose information on their liabilities for these positions, unrecognized tax benefits (UTBs). We analyze the FIN 48 disclosures for calendar-year-end Korean companies listed on NYSE and NASDAQ and examine the Korean firms' tax aggressiveness utilizing the UTBs. The results suggest that stock exchange and firm size do not play a role in the Korean firms' tax aggressiveness, contrary to the matched U.S. firms and that the Korean firm in the miscellaneous retail industry is more tax aggressive than the firms in the communications, depository institutions and business services. In addition, we find evidence that the Korean firms are less tax aggressive than the matched U.S. firms. We also examine the Korean firms' tax avoidance tendencies using other measures of avoidance, leading to mixed results. Finally, we examine the association between the UTBs and other measures of tax avoidance and find a significant and negative association between the UTBs and the long-run cash effective tax rate.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.