Published papers

News articles play an important role in financial markets.　This study　analyzes the relationship between news articles and stock price fluctuations using high frequency trading data in Korean stock markets.　Especially, we analyze differences in market reactions according to　languages of news articles. In order to understand the influences of　news articles, this study explores conditions of Long Short Term Memory　(LSTM) models that classify news articles.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2020. In the Initial Public Offering (IPO), many prior studies have discussed underpricing, where the public price is below the initial price. In this study, we propose a novel system for company valuation employing patent document analysis. Specifically, we first extracted patent document data published from 2001 to 2015 and vectorize them through Sparse Composite Document Vectors (SCDV). Similar companies in this study refer to the same industry, products handled, and business scale. However, there are various theories on what should be treated as similar companies. Next, the center of gravity is calculated from the vectorized patent document, and comparable companies are selected by expressing the distance between companies. A detailed analysis is planned for further study.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2020. This study constructed a news article evaluation system that utilizes a language generation model to analyze financial markets. This system enables us to analyze the effect of news articles distributed in financial markets on the stock price of a company. We added the generated news articles as data for analysis through GPT-2 and verified the accuracy of the constructed system. As a result of empirical analyses, we confirmed that the accuracy of the model with the generated news articles improved. More detailed analyses are planned for the future.

© 2019, Springer Nature Switzerland AG. Although industrial classification plays an important role in various contexts, it is rarely questioned. However, as diversification and business transformation are ongoing, it is becoming difficult to recognize company’s real business. Therefore, there is not enough to allocate one type of business class to express the situation of the company, and a new type of industrial classification system is required. Through the analysis, we construct a new industrial classification system with Fuzzy C Means (FCM). This study also confirms the validity of proposed method through composite variance and absolute prediction error (APE). As the result, we present that there is a possibility that we are able to represent one company with overlapping industry, so to speak, assign one company more than two industries.

© 2020, Springer Nature Singapore Pte Ltd. This study focuses on the influence of the market collapse process of financial institutions under financial regulation on financial systems. For this purpose, the authors expand simulation models of systemic risks expressing financial regulation and the financing behavior of financial institutions. Using this model, scenario analysis is performed how the collapse process in the financial system changes due to the balance sheet constraint. Our numerical experiment shows that (1) as the amount of marketable assets is increased, the type of failed process with high occurrence changes, and (2) when there is a balance sheet restriction, the frequency of chain collapse is suppressed.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2020. This paper proposes a formal descriptive model of organizational decision-making called the Managerial Decision-Making Description Model (MDDM). This model introduces visual representations to describe managerial decisions that redefine relationships between their objectives and resources. The MDDM describes various business cases and enables us to compare these decision-making processes. This paper presents the MDDM’s methodologies and describes, and compares, the decision diagrams extracted from actual business cases and organizational agent-based simulation (ABS) logs as virtual business cases.

© 2019, Springer Nature Singapore Pte Ltd. Researchers are aware of the importance of debriefing in gaming. However, there has been little progress in establishing a methodology for evaluating player behavior. Therefore, we propose a framework to support the evaluation of player behavior in business games using computers. Specifically, we introduce a simulation analysis methodology that involves the following steps: (1) constructing an agent-based model based on the subject of the business game and categorizing simulation-logs; and (2) mapping logs of player behavior onto typed results. In this way, the positioning of the player in the overall simulation scenario is visualized, and a range of possible results is presented. Both players and facilitators receive information that is useful for debriefing.

To understand social and organizational phenomena and connect them to the design of a system, an approach to implement an agent-based model and a case study have been proposed. In this study, we propose a methodology that extends the approach to the following two points i.e., 1) analyzing not the micro-level simulation logs themselves but the patterns of micro-level logs and 2) describing the interpretations of the business cases formally by using an abstract description language. To confirm the feasibility of our proposed methodology, an agent-based model that expresses the decision-making process concerning external environment recognition of an organization was established. For systematically analyzing, we generated the simulation logs from the model via many trials by using the random search method comprehensively. Furthermore, we adopt the Managerial Decision-making Description Model as an abstract description language and wrote down two actual business cases with similar themes; a top-down-type decision-making case and a bottom-up-type decision-making case. Moreover, the comparisons of the business cases with similar themes were performed. Hence, this new methodology enables 1) to comprehensively understand the results and processes of the simulation and to discuss the occurrence frequency and 2) to express the simulation logs and actual business cases in the same format by case description language to compare them.

© 2018, Springer International Publishing AG, part of Springer Nature. News is an important source of information for investment decision-making. Many studies analyzing listed companies in the US & Japan have been reported. However, the number of studies focusing on Korean stock markets is limited. This study analyzes the influence of news articles on Korean stock markets with high frequency trading data. Especially, we focus on analyses of the relationship between news articles and financial markets. Furthermore, we also analyze differences in market reactions according to language (English or Korean) of news articles and present three case studies.