• Korean Journal of Construction Engineering and Management
• /
• v.6 no.3 s.25
• /
• pp.144-155
• /
• 2005

Since 1950s, the Korean housing market has continually experienced the chronicle lack of housing stock because of lower housing investment in comparison with a population explosion, prompt urbanization and rapid restructuring of family. The Korean housing market have thus been driven not by the pricing model by housing demand-supply chain but by the Korean housing policies focusing on the increase of housing supply and the living stability of the middle or low-income bracket. After all, repetitive economic vicious circle of housing price and the increase of unsold apartments aggravated the malfunction of the Korean housing market. Meanwhile, the Korean construction firms have exacerbated their profitability. Such terrible situations are mainly triggered by the Korean construction firms that weighed on the short-term profits and quick response of the government policy alterations rather than the prospect of housing market Therefore, this research focusing on the dynamics of housing market identified and classified the demand and supply elements that consist not only of housing system structures but also of the environmental elements that affect the structures. Based on the system thinking and traditional theory of consumer's choice, the interactions of these elements were constructed as a causal loop diagram that explains the mutual influences among housing subsystems with feedback loops. This paper describes and discusses about the causes of the dynamic changes in the Korean housing market. This study would help housing suppliers, including housing developers, construction firms, etc., to form a more comprehensive understanding on the fundamental issues that constitute the Korean housing market and thereby increasing their long term as well as minimizing the risk involved in the housing supply businesses.

• The Korean Journal of Financial Management
• /
• v.22 no.2
• /
• pp.189-212
• /
• 2005

This study examines the interactions between KTB spot and futures markets using the daily prices from March 4, 2002 to January 31, 2005. We use Granger causality test, impulse Response Analysis and Variance Decomposition through vector autoregressive analysis (VAR). However, considering the long-term relationships between the level variables of KTB spot and futures, we introduced Vector Error Correction Model. The main results are as follows. According to the results of Granger-causality test and impulse response analysis, we find that the yields of KTB forward have a great influence on the change of KTB spot but not vice versa. In terms of volatility analysis, there is no inter-dependence between KTB forward and spot markets. In the variance decomposition analysis we find that the short-term KTB forward has much more impact on the KTB spot market than the long-term KTB forward does. We think these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management and international portfolio management.

• Korean journal of communication and information
• /
• v.46
• /
• pp.387-419
• /
• 2009

The concept of strategic group is defined as an aggregate of corporations utilizing similar strategies with similar resources. It becomes a kinds of contact point in the middle of corporation and industry between the industrial organization theory and the strategic management theory. This study tried to apply the strategic group model, which has been a main theory in the management studies, to program providing industry in Korea. This study shed lights upon research problems such as number of strategic groups, differences of strategic variables among the groups, finally differential performances according to strategic groups. 40 commercial broadcasting companies were analyzed to find answers. 9 strategic groups were drawn as a result of cluster analysis. Major variables which contribute to making groups were operating efficiency(4.05), pricing(3.83), size(number of system operator, 3.56), reliance on license revenue(2.58), horizontal integration(number of sister networks, 2.16) in order. An analysis of variance between performance variables has shown statistical significance regarding total net revenue per subscriber, however, insignificances statistically in regards to ratio of operating profit to net sales, cash Abstracts 687 flow ratio. Some studies in the past insisted that history variable played an important role to classifying strategic groups. However, this study found that the history didn't exert significant influence on either the group classification itself or performance.

• Korean Journal of Construction Engineering and Management
• /
• v.19 no.4
• /
• pp.102-110
• /
• 2018

The study analyzed the effects of the floor plan characteristics on the apartment price under the national housing size in 3 Gangnam districts for decades, the primary apartment markets in Korea. The analysis showed that the storage spaces such as kitchen, warehouses and dressage rooms have a positive effect on the price. Especially, the highly opened space with three-side open plan and the one with the unified type of livingroom, diningroom and kitchen have shown the strong effect on the price. For the kitchen spaces, the I-shaped kitchen tends to be more expensive while a centered living room has a positive effect on the price. These findings have an academic significance as the direct effects of plan characteristics on price has been examined unlike prior research focused on the analysis of trend, basic statistics, and satisfaction level. It is noteworthy that these research finding has identified the productive implication for the future floor plan design and pricing and also be implemented in the purchasing decision making by buyers in the housing market.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1215-1227
• /
• 2021

Surface reflectance, as a product of the absolute atmospheric correction process of low-orbit satellite imagery, is the basic data required for accurate vegetation analysis. The Commission on Earth Observation Satellite (CEOS) has conducted research and guidance to produce analysis-ready data (ARD) on surface reflectance products for immediate use by users. However, this trend is still in the early stages of research dealing with ARD for high-resolution multispectral images such as KOMPSAT-3A and CAS-500, as it targets medium- to low-resolution satellite images. This study first summarizes the types of distribution of ARD data according to existing cases. The link between Open Data Cube (ODC), the cloud-based satellite image application platforms, and ARD data was also explained. As a result, we present practical ARD deployment steps for high-resolution satellite images and several types of application models in the conceptual level for high-resolution satellite images deployed in ODC and cloud environments. In addition, data pricing policies, accuracy quality issue, platform applicability, cloud environment issues, and international cooperation regarding the proposed implementation and application model were discussed. International organizations related to Earth observation satellites, such as Group on Earth Observations (GEO) and Committee on Earth Observation Satellites (CEOS), are continuing to develop system technologies and standards for the spread of ARD and ODC, and these achievements are expanding to the private sector. Therefore, a satellite-holder country looking for worldwide markets for satellite images must develop a strategy to respond to this international trend.

• Asia Marketing Journal
• /
• v.16 no.2
• /
• pp.39-57
• /
• 2014

There has been recognition of the increasing importance of cooperation as an element of marketing strategy. Such cooperation is confined to four levels based on product development, sales promotion, pricing arrangements, and place (or distribution) mechanisms as the usual marketing 4Ps mixed (Varadarajan 1986). At present, however, little is known about the nature of tie-in promotion as a cooperative sales promotion comparing three other levels. The primary goal of this study is to examine the effect of consumer - tie-in promotion relationship on loyalty. The construct of consumer - tie-in promotion relationship is based on the previous research on consumer-brand relationship. In addition, this study divides the concept of loyalty into host brand loyalty and partner brand loyalty to reflect the characteristics of tie-in promotion including program in order to determine the effect of the consumer - tie-in promotion relationship on loyalty. The results showed that the three dimensions of the consumer - tie-in promotion relationship (i.e., commitment, intimacy, and interdependence) had significantly positive effect on program loyalty. The effect of program loyalty is significantly on both host and partner brand loyalty. This study empirically tested the relationships among consumer - tie-in promotion relationship, program loyalty, host brand loyalty, and partner brand loyalty, and then compared with the difference in the suggested model for the target customers and non-target customers. As a result, for target customers, intimacy and interdependence among dimensions of consumer - tie-in promotion relationship had significantly positive influence on program loyalty. In case of non-target customers, however, commitment and interdependence among dimensions of consumer - tie-in promotion relationship had significantly positive influence on program loyalty. Also, program loyalty had significantly positive impact on host brand loyalty and partner brand loyalty in both target and non-target customers. This study has significance in that it addresses the need to identify research and academic implications by analyzing the consumer - tie-in promotion relationship to determine the relationship between tie-in promotion and loyalty, which has not been clearly described by previous studies. Furthermore, this study builds a foundation for firms and managers actively using tie-in promotion to establish tie-in promotion strategies that can maximize loyalty for both host and partner brands from the consumers' point of view.

• Land and Housing Review
• /
• v.14 no.4
• /
• pp.63-76
• /
• 2023

Investors should understand and actively consider factors like location, future value, policies, pricing, market trends, and their income, as these elements can shift with changing local, social, economic, and policy environments. This study seeks to clarify the impact of investment factors on the performance and reinvestment intentions of Sejong City investors by surveying those who have invested in real estate. This study employs a structural equation model with confirmatory factor analysis, focusing on four aspects: value, economic and policy, psychological, and financial. We find that the investment value factor has the largest impact on investment performance, indicating that investors prioritize the investment value of real estate in Sejong City. In addition, factors increasing asset value and expected satisfaction were significant, indicating that real estate investment in Sejong City yields high returns and investor satisfaction. with a positive outlook for future reinvestment.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• The Korean Journal of Financial Management
• /
• v.21 no.2
• /
• pp.125-151
• /
• 2004

This study tests the price discovery from US Treasury bond markets to Korean bond markets using the daily returns of Korean bond data (CD, 3-year T-note, 5-year T-note, 5-year corporate note) and US treasury bond markets (3-month T-bill, 5-year T-note 10-year T-bond) from July 1, 1998 to December 31, 2003. For further research, we divide full data into two sub-samples on the basis of the start-up of bond valuation system in Korean bond market July 1, 2000, employing uni-variate AR(1)-GARCH(1,1)-M model. The main results are as follows. First the volatility spillover effects from US Treasury bond markets (3-month T-bill, 5-year T-note, 10-year T-bond) to Korean Treasury and Corporate bond markets (CD, 3-year T-note, 5-year T-note, 5-year corporate note) are significantly found at 1% confidence level. Second, the price discovery function from US bond markets to Korean bond markets in the sub-data of the pre-bond valuation system exists much stronger and more persistent than those of the post-bond valuation system. In particular, the role of 10-year T-bond compared with 3-month T-bill and 5-year T-note is outstanding. We imply these findings result from the international capital market integration which is accelerated by the broad opening of Korean capital market after 1997 Korean currency crisis and the development of telecommunication skill. In addition, these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management, and international portfolio management.

• Journal of Technology Innovation
• /
• v.17 no.2
• /
• pp.55-80
• /
• 2009

Technology innovation activity plays a pivotal role in constructing the entrance barrier for other firms and making process improvement and new product. and these activities give a profit increase and growth to firms. Thus, technology innovation activity can reduce the default risk of firms. However, technology innovation activity can also increase the firm's default risk because technology innovation activity requires too much investment of the firm's resources and has the uncertainty on success. The purpose of this study is to examine the effect of technology innovation activity on the default risk of firms. This study's sample consists of manufacturing firms listed on the Korea Securities Market and The Kosdaq Market from January 1,2000 to December 31, 2008. This study makes use of R&D intensity as an proxy variable of technology innovation activity. The default probability which proxies the default risk of firms is measured by the Merton's(l974) debt pricing model. The main empirical results are as follows. First, from the empirical results, it is found that technology innovation activity has a negative and significant effect on the default risk of firms independent of the Korea Securities Market and Kosdaq Market. In other words, technology innovation activity reduces the default risk of firms. Second, technology innovation activity reduces the default risk of firms independent of firm size, firm age, and credit score. Third, the results of robust analysis also show that technology innovation activity is the important factor which decreases the default risk of firms. These results imply that a manager must show continuous interest and investment in technology innovation activity of one's firm. And a policymaker also need design an economic policy to promote the technology innovation activity of firms.