• Korea Real Estate Review
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• v.28 no.4
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• pp.75-88
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• 2018

The purpose of this study is to analyze the effect of the spread on housing mortgage loans. In particular, this study analyzes how the spread has a decisive effect on housing mortgage loans when a structural change occurs in the spread. For the sake of empirical analysis, this study utilizes the housing mortgage loan, housing mortgage loan interest rate, COFIX interest rate, and spread. The period of analysis is from December 2010 to December 2017. Results of the analysis show that there is a statistically significant structural change in the spread and housing mortgage loans (May and June 2015, respectively). It is estimated that the structural change in the spread has an influence on the structural change in housing mortgage loans. In addition, the effect of the spread on housing mortgage loans is larger than the effect of the COFIX interest rate and the housing mortgage loan interest rate. This indicates that the adjustment of the spread is a significant burden on housing mortgage loans. As economic uncertainties both internally and externally are increasing, pressure on interest rate hikes is also increasing. Considering these circumstances, interest rate hikes will be inevitable in the future. If the base interest rate and the spread increase simultaneously at Korea's current economic level, it will obviously lead to an economic recession as the burden on the repayment of principal and interest of housing mortgage loans will increase. Therefore, it is imperative that financial authorities prepare institutional arrangements in order to protect financial consumers by preventing arbitrary calculation of the spread, which would not be objective and would not be transparent from the banks.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.197-203
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• 2014

This study deals with a comparative analysis on reverse mortgage loans and mortgage loans in order to pave a path for activation of real estate financing. The fact-revealing analysis was conducted through surveys based on theoretical consideration and advanced researches, which has drawn a range of findings. As the results of this study, the important findings concerning the improvement on the activation of practical housing reverse mortgages are applicable to all real estate, diversifying the tax benefits, and deregulation of 1 house, etc. and findings concerning the improvement to activate mortgage loans are diversifying types of interest rates, diversifying types of repayment, tax benefits for less than 15 years maturity period, and granting benefits(low interest rates, higher loan limits) to low-income households, etc. This study has a significance for providing basic materials in order to accomplish advanced finance policies along with social welfare services as suggesting measures to improve and activate real estate financing through the findings out of the fact-revealing analysis conducted as above.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.81-95
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• 2023

The emergence of Security Token has revolutionized the way assets are traded, bringing efficiency, transparency, and accessibility to the market. However, the Real Estate Security Token market faces challenges, particularly in terms of liquidity. The CMTO(Collateralized Mortgage Token Obligation) model addresses this issue by introducing a novel approach that combines the benefits of NFT(Non-Fungible Token), STO(Security Token Offering), and CMO(Collateralized Mortgage Obligation) techniques to enhance liquidity and promote investment in Real Estate Security Token. The CMTO framework functions by allowing DABS token investors to leverage their tokens as collateral for loans. These token-collateralized loans are pooled together and form the basis for issuing Sequential CMO named CMTO. The CMTO represent a diversified portfolio of token-collateralized loans, providing investors with options based on their financial goals and risk preferences. By implementing CMTO, the Real Estate Security Token market can overcome liquidity challenges, attract a broader range of investors, and unlock the full potential of digital assets in the real estate industry.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.32-40
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• 2010

Recent periodical boom and burst of house price have made mortgage lending issues become the main public interest in Korean real estate market. However, because mortgage-lending issues had not been discussed until then, housing market forecasting associated with mortgage lending has been difficult while using an empirical approach. Thus, comprehensive and systematic approach is required as well as validity of mortgage lending policies should be evaluated. In this regard, this research conducts a sensitivity analysis to validate the proposed policies and estimates the effects of current policies on LTV and DTI ratios with a comparison of another policies scenario. A causal loop and sensitivity analysis using system dynamics confirmed that LTV and DTI regulation is strong clout to housing market. However, to prevent transfer of potential mortgage borrowers to nonmonetary institutions, regulations in loans of nonmonetary institutions should be practiced in accompaniment with regulations of primary lending agencies.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.605-616
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• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1015-1022
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• 2009

Currently, Korean real estate market has experienced cooling down of the business because of the global economic crisis which resulted from the subprime mortgage lending practice. In response, the Korean government has enforced various policies at the base of deregulating real estate speculation, such as increasing Loan to value ratio (LTV) in order to stimulate housing demand and supply. However, these policies seemed to result in deep confusion in the Korean housing market. Furthermore, analysis for housing market forecasting, especially international financial crisis on Korean real estate market, has been partial and fragmentary, therefore comprehensive solution and systematical approach is required to analyze the real estate and real estate financial market including causal nexus between market determining factors. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing Korean Real Estate and Mortgage market dynamics models based on fundamental principles of housing market determined by supply and demand. We also find the impact of deregulation policies focusing on mortgage loan which is the main factors of policies.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.83-89
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• 2022

This study analyzed the effect of bank loans on housing prices, classified bank loans into bank total loans, household loans, and real estate mortgage loans, and analyzed housing prices by dividing them into national-level, regional-level, and Seoul-level housing prices. The main analysis results are as follows. First, it was found that the increase in total bank loans significantly increased housing prices across the national-level, regional-level and Seoul-level. Second, it was found that household loans had a positive effect on regional-level housing prices, but were not statistically significant. In addition, the effect of bank loans on regional-level housing prices was found to be relatively small compared to the effect on national-level housing prices. Third, it was found that there was a difference in the effect of bank loans on regional-level housing prices and Seoul-level housing prices. Fourth, inflation and bank total loans had a significant positive effect on regional-level housing prices with a lag in the first quarter, and short-term interest rates had a significant negative effect on Seoul-level housing prices with a lag in the first quarter. Overall, it was found that the effect of bank loans on housing prices had a positive effect about twice that of Seoul-level rather than regional-level.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.4
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• pp.5-13
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• 2014

This study contributes to addressing the problem of an aging population by providing important information that determines feasible monthly payments for the clients of Chinese reverse mortgage products and by promoting the implementation of reverse mortgages in China. The variables used in this study include mean values obtained from time series data, of the rate of increase of housing prices, and the probability value, interest rate, and mortality rate obtained through the geometric Brownian motion (GBM). For mortality rates, China Life Insurance female mortality rates (2000-2003) were used. This study aims to apply the main variables that affect reverse mortgage products in a monthly payment model based on Chinese financial market conditions, and determine loan values. In this study, Shanghai's reverse mortgage monthly payments, by age levels, were calculated through the loan-to-value (LTV) and payment (PMT) methods to evaluate the value of the reverse mortgages. Based on the optimal combination of the three factors of payment amount, loan interest rates, and the level of acceptance of prices, efforts must be made to extract the best value for the elderly. Only in this way can the interests of both lenders and borrowers be protected, by increasing the market share and economies of scale of the reverse mortgage industry and effectively improving the living standards of the elderly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.265-272
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• 2019

In this study, we conducted a prediction study to qualitatively identify the continuous growth rate that causes problems every year for deposit bank mortgage loans, identify the characteristic factors that could once again stabilize, and come up with measures for future quantitative analysis of mortgage loans and growth trends. Based on data analysis using the R program, which is widely used for big data analysis, the parameters of ARIMA model (0.1,1)(0.1,1)[12] were found to be most suitable. In these indicators, estimates over the next five years (60 months) increased 4.5% on average. However, this has limitations that do not reflect socio-environmental factors, which require further study of these limitations.