• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.807-809
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• 2010

글로벌 금융위기를 거치면서 각국의 증시가 같은 방향으로 움직이는 동조화 현상이 뚜렷이 나타나고 있다. 주가 동조화 현상은 주로 시계열 분석 기법을 적용하여 연구가 이루어져 왔는데, 본 연구에서는 네트워크 분석 기법을 적용하고자 한다. 시가 총액이 큰 주요 국가들의 대표적 주가 지수들을 대상으로 상관계수를 구하고, 이러한 상관계수를 가중치로 설정하여 구성한 네트워크를 분석한다.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.101-113
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• 2003

Quasi likelihood estimators defined by Wedderburn are derived for several nonlinear time series models. And also, the least squared estimator and Quasi-likelihood estimator are compared in sense of asymptotic relative efficiency at those models. Finally, we apply these estimations to a real data on exchanging rate and stock market prices.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.7 no.2
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• pp.13-22
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• 2003

Simulations on the nonlinear partial differential equation derived from Black-Scholes equation with transaction costs are performed. These numerical experiments using finite element methods are applied to KOSPI200 in 2002 and the option prices obtained with transaction costs are closer to the real prices in market than the prices used in Korea Stock Exchange.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.

• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.842-864
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• 2006

This paper deals with an empirical study to statistically analyse various financial performances of the selected IPO firms using their investments on research and development(R&D) as an independent variables. The major results of statistical analyses have come up with the followings: 1) The regression analyses for change in average annual total market stock value/total assets over that of R&D expenditures showed the positive relationship, However, those of sales volume and net assets per share showed negative without statistical significances. 2) The statistical analyses in effect of the 3-year average total market stock value/total assets over the 3-year average R&D expenditures resulted in the positive coefficients what are statistically significant at 95% level. 3) Another statistical analysis showed that the financial performances of the IPO finns with deferred assets were better than those of the firms without them. In sum, the degree of investment on R&D by the IPO firms are expected to positively affect their financial performances except the Finns without having proper original technologies.

• Journal of the Korea Furniture Society
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• v.29 no.1
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• pp.40-48
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• 2018

This study analyzes the contribution of hanok that construction in reducing greenhouse gas (GHG) emissions in Korea by calculating the carbon storage of hanoks and comparing it to different housing types in Korea. The hanok is a traditional Korean house. And it were first designed and built in the $14^{th}$ century during thd Joseon Dynasty. According to our results, the number of hanoks in 2016 was approximately 547,085 which was accounting for 7.8% of the total construction market, This study found Gyeongbuk with 95,083, Jeonnam with 88,981, Gyeongnam with 76,388 and Seoul with 43,519 hanoks. According to the GHG Inventory Report for 2016, Korea's total annual GHG emissions amounted to 650 million $tCO_2$, with the carbon stocks in hanoks amounting to 19.2 million $tCO_2$. This accounts for 2.8% of Korea's total GHG emissions and 46.1% of the carbon absorbed by forests. Our results show that hanoks store four times more carbon than light-frame-wood-houses, and 15 times more carbon than concrete-reinforced and steel-frame houses. The main factors causing the hanok industry slowdown are the high construction costs, lack of government support, and insufficient knowledge of hanok architecture. Therefore, to further increase the carbon stock of hanok, more research is needed to improve the technical use of wood and reduce construction of the hanok and prepare legal and institutional arrangements related to hanok industry.

• Information Systems Review
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• v.25 no.4
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• pp.183-204
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• 2023

Due to the COVID-19 pandemic, lots of occasions need to be held in online environment. This is the reason why "Metaverse" gets lots of attention in 2021. A number of companies made announcements on Metaverse, and this situation also boomed stock market. This paper investigates the relationship between Metaverse initiatives and business value of the firm (i.e., stock prices). We examine this relationship by using event study method with Lexis-Nexis News data from 2019 to 2021. The results indicate that Metaverse initiatives significantly impact positive influence on firm's value. In the technological perspective, technical factors affect more positive market returns, including Metaverse enablers (e.g., NFT, VR devices, digital twin) and common infrastructure (e.g., semiconductor, AI, cloud), and especially virtual environment was emphasized. Additionally, in the strategical perspective, radical innovation (e.g., pivoting, acquisition) impact more positive market return rather than incremental innovation (e.g., partnership, investment). Also, firms from non-service industries can achieve benefits from Metaverse initiatives rather than service industry in some degree.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.374-384
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• 2014

In this paper, characteristics of transactions by investors were examined based on the relationship between South Korea's stock market trends and the amount of net purchasing by investors. The study period is from January of 2004 to December of 2011, a total 1,991 days on 96 months. Data used for correlation and regression analysis include the value of the KOSPI index at the end of each month, the monthly net purchase amount of each of the groups, as well the daily volume, the daily price. In this study, the long-term phase of the market divided by refining. and each of the investment position of invest group was investigated. As a result, foreign investors are a net selling position when market was rising phase of the tertiary. And private investors were a net short positions when the market was decline phase of the tertiary. Regardless of the flow changes, the private investors had opposite position to the flow of the mark, also they had opposite position to the position of the foreign investors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.1-12
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• 2024

This paper aims to examine the effectiveness of Restricted Stock Units (RSUs) in attracting and retaining top talent for startups and venture companies in the context of their implementation in July 2024. The study investigates whether RSUs align with their original intent and identifies additional measures to enhance their effectiveness. Additionally, the paper explores strategies to actively adopt and revitalize RSUs in the business field from the perspectives of experts representing key market participants within the early-stage startup ecosystem in Korea. The study employs a three-pronged approach. First, a pre-study examines how RSUs overcome the limitations of existing stock compensation schemes, the benefits they offer, and the key conditions for ensuring market-friendly effectiveness. Second, experts involved in the RSU bill's early stages identify five issues that need to be addressed to ensure the bill's market-friendly effectiveness: RSU vesting conditions, RSU vesting targets, RSU vesting scope, RSU vesting timing, and RSU vesting-related tax benefits. Third, the study conducts an FGI with experts representing key market players in the early-stage startup ecosystem to examine the effectiveness and activation measures of the proposed RSU scheme, RSU adoption within the early-stage startup ecosystem minimizing conflict of interests with existing shareholders such as venture capital investor. Finally, experts emphasize the importance of clearly defining and communicating RSU benefits to businesses for effective RSU activation. This study's significance lies in its derivation of various insights from FGI research on the effective adoption and activation of RSUs within the early-stage startup ecosystem. Moreover, it is expected to provide a methodology for gauging opinion-gathering procedures for new bills introduced to foster startup and venture company growth.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1327-1336
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• 2017

In this study, the problems in the short term stock market forecasting are analyzed and the feasibility of the ARIMA method and the backpropagation neural network is discussed. Neural network and genetic algorithm in short term stock forecasting is also examined. Since the backpropagation algorithm often falls into the local minima trap, we optimized the backpropagation neural network and established a genetic algorithm based on backpropagation neural network for forecasting model in order to achieve high forecasting accuracy. The experiments adopted the korea composite stock price index series to make prediction and provided corresponding error analysis. The results show that the genetic algorithm based on backpropagation neural network model proposed in this study has a significant improvement in stock price index series forecasting accuracy.