• Journal of Digital Convergence
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• v.15 no.11
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• pp.113-120
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• 2017

The purpose of this study is to analyze how the relative proportion of retention between real estate for business and investment real estate among the real estate held by corporations has been changed after and before the Financial Crisis as well as whether there has been any difference between KOSPI and KOSDAQ listed companies in terms of their share of the real estate. The increasing pattern of real estate owned by KOSDAQ were similar to the KOSPI companies except for investment properties during the Financial Crisis. The proportion of real estate owned by KOSPI had been lower than that of KOSDAQ companies in both investment and business real estate before the Financial Crisis. However, during the period of the Financial Crisis, the proportion of real estate for business held by KOSPI firms was higher than that of KOSDAQ firms. Furthermore, the portion of investment of real estate owned by KOSPI has remained higher than that of KOSDAQ after the Financial Crisis period and the recent period. Based on the results of this analysis, how the relevance of the change of portion between real estate for business and investment real estate affects management performance will be figured out in the future studies.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.175-182
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• 2021

Focusing on the recently announced "KOSPI 200 ESG Index," this study intends to examine whether the "KOSPI 200 ESG Index" has any relevance to stock prices. Specifically, it was empirically analyzed whether companies included in the KOSPI 200 ESG index showed average abnormal return and cumulative average abnormal return of stock prices due to incorporation into the index. As for the research method, the case study was conducted using the return by the market model using the coefficient estimated by the OLS for the normal expected return. The study results are summarized as follows. First, the initial incorporation of a company into the KOSPI 200 ESG index showed significant positive(+) average abnormal return and cumulative average abnormal return. Second, the incorporation of a company into the KOSPI 200 ESG index showed significant positive(+) average abnormal return and cumulative average abnormal return. Through this study, it was confirmed that investors in the market are aware of ESG indicators as non-financial information, not just financial information. In addition, it can be said that the contribution of this study to the fact that investors perceive ESG index as information for investment. This study differs in that it uses the latest ESG index, but at the same time, it has limitations in that the study period is short and the study sample is limited.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.353-361
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• 2018

The purpose of this study is to analyze how Corporate Real Estate Ratio affects Firm's Value for KOSPI Companies and KOSDAQ Companies. The period of analysis is the period of the Financial Crisis (2007-2008), the period immediately after the Financial Crisis (2009-2011), and the period following the introduction of IFRS (2012-2016). The samples of 2761 KOSPI Companies years and 3719 KOSDAQ Companies years are used in this study. The result of Regression Analysis shows that the higher Corporate Real Estate Ratio is, the more negative Firm's Value is. In the comparison of markets, both KOSPI Companies and KOSDAQ Companies had no statistically significant effects during the Financial Crisis. Although KOSDAQ Companies had a greater negative effect on the Firm's Value than KOSPI Companies right after the Financial Crisis, KOSPI Companies have had a greater negative influence on the Firm's Value than KOSDAQ Companies since the introduction of IFRS. Therefore, each corporation should pay more attention to identifying the appropriate amount of their Corporate Real Estate Ratio and should continue to analyze and make decisions on the most efficient use of real estate which is owned by each company. This study shows speciality in dividing into three period, such as the period of the Financial Crisis, the period immediately after the Financial Crisis, and the period following the introduction of IFRS and comparing the degree of influence on the KOSPI Companies and KOSDAQ Companies for the each period. I hope to study the factors that affect the company's real estate policy.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.525-537
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• 2016

The paper considers a hybrid model to analyze and forecast time series data based on an empirical mode decomposition (EMD) that accommodates complex characteristics of time series such as nonstationarity and nonlinearity. We aggregate IMFs using the concept of cumulative energy to improve the interpretability of intrinsic mode functions (IMFs) from EMD. We forecast aggregated IMFs and residue with a hybrid model that combines the ARIMA model and an exponential smoothing method (ETS). The proposed method is applied to forecast KOSPI time series and is compared to traditional forecast models. Aggregated IMFs and residue provide a convenience to interpret the short, medium and long term dynamics of the KOSPI. It is also observed that the hybrid model with ARIMA and ETS is superior to traditional and other types of hybrid models.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.235-244
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• 2013

In this study, we propose a new trading strategy by using a trading volume index in KOSPI200 futures market. Many studies have been conducted with respect to the relationship between volume and price, but none of them is clearly concluded. This study analyzes the economic usefulness of investment strategy, using volume index. This analysis shows that the trading volume is a preceding index. This paper contains two objectives. The first objective is to make an index using Correlated Volume Index (CVI) and second objective is to find an appropriate timing to buy or sell the Kospi200 future index. The results of this study proved the importance of the proposed model in KOSPI200 futures market, and it will help many investors to make the right investment decision.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1449-1466
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• 2014

In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

• Journal of Korean Association for Spatial Structures
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• v.19 no.3
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• pp.61-68
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• 2019

A tensegrity module structure is suitable type for spatial structures. Because the tensegrity is composed of set of discontinuous compressive elements (struts) floating within a net of continuous tensile elements (cables), the system can provide the basis for lightweight and strong. However, despite the advantages of tensegrities, design and fabrication of the systems have difficulty because of form-finding methods, pin-connection and the control of prestress. In this paper, the new pin-connection method was invented to make the tensegrity module. The production process and practical implementation of uniformly compressed the tensegrity structures by using a UTM are described. Experiments showed the mechanical response and failure aspects of the tensegrity system.

• Proceedings of the KAIS Fall Conference
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• 2011.05b
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• pp.765-768
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• 2011

최근 건설경기의 난국 속에서 많은 건설기업들이 경영상의 어려움에 처해 있다. 본 연구에서는 코스피 코스닥 상장 건설기업들을 대상으로 ANP와 DEA 결합 모델을 이용하여 기업의 경영 효율성 분석을 실시한다. DEA 모형에 쓰이는 투입 및 산출 요소의 결정은 ANP 모형의 중요도 분석을 통하여 결정함으로써 기존의 방법보다 효율성 분석 결과의 신뢰도를 제고하였는데, 효율성 분석결과 비효율적 그룹에 대해서는 효율적 그룹으로의 이동을 위한 벤치마킹 대상과 개선을 위한 효율성 수치를 제공한다. 또한 연구의 결과로 나온 기업별 효율성과 주가와의 상관관계를 분석한다. 본 연구에서는 코스피 상장 건설기업 36곳과 코스닥에 상장된 건설기업 21곳인 총57개 기업을 대상으로 기업의 효율성을 평가하였는데, 효율성 분석결과 CCR 효율성이 1인 기업은 4개 기업, BCC 효율성이 1인 기업은 7개 기업, 규모의 효율성이 1인 기업은 4개 기업 이었으며 각각의 효율적 그룹군 기업과 주가와의 상관관계는 CCR, BCC 모형 모두에서 0.7 이상의 강한 양의 상관관계를 나타냈다.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.23-29
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• 2017

Due to the success of Wealthfront, Betterment, etc., there is a growing interest in RoboAdvisor that is an automated asset allocation methodology globally. RoboAdvisor minimizes human involvement in managing assets, thereby reducing the costs of using services and eliminating human psychological factors. In this paper, we developed a predictive model for the KOSPI 200 Futures Index using deep learning, in order to replace the existing technical analysis technique. And the proposed model confirmed that When the KOSPI 200 Gift Index is small, it can be used to predict direction and price of index. In combination with the existing technical analysis, It is confirmed that the proposed models combining with existing technical analyses and can be applied to the RoboAdvisor Service in the future.