• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.517-524
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• 2020

The study examines factors affecting apartment prices in the real estate market of Ho Chi Minh City, Vietnam. The study uses primary data based on surveys of customers who have traded successfully, and collects transaction data from real estate trading companies that are the top investors in Ho Chi Minh City real estate market. The collected data include 384 observations in a total of 24 districts, detailing that each district surveyed on a minimum of four projects, each project carried out a survey on a minimum of four apartments. The survey collected 339 valid questionnaires for analysis and model testing. This study employs multivariate regression with the data of 339 observations. The research results reveal that five significant factors affect positively the price of apartments in Ho Chi Minh City - apartment area, toilet and bedroom, apartment floor, reference price, and apartment interior. Besides, there are three significant factors affecting negatively the price of apartments - next price trend, distance to city center, and potential building. From the results, the research proposes solutions in the pricing of apartments in the real estate market in Ho Chi Minh City - better information system, a real estate transaction index, and stricter management of small brokerage activities.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2011.04a
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• pp.285-289
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• 2011

he purpose of this study is to assess the effects of real estate policy on apartment price index in Seoul. To meet the research goal, this research reviewed real estate policy of the government from January of 1986 to August of 2010, and then it collected monthly apartment price index in 25 local districts of Seoul from January of 2003 to August of 2010. After 25 districts were grouped into 2 areas (14 districts in Gangnam and 11 districts in Gangbuk), the data of two areas were analyzed by using the SAS program, Cluster analysis with Ward method showed 3 clusters on each area, and with 6 clusters in total, the effects of real estate policy in the period were examined by using residual analysis. The analysis indicated two major shocks (one was from May to October of 2003, and the other was from March of 2006 to January of 2007), and the results showed that the intervention of government in the market had the asymmetric effects in bullish and bearish times. It implies that the market volatility is substantially influenced by irrational sentiments. Thus, it's suggested to devise the consumer sentiment index suitable in real estate market.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.227-234
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• 2006

While most of the real estate information provided on the web is simply based on the information of the properties like addresses, locations, prices etc, this paper suggests methodologies for the development of a total information system of real estate which can provide, in an one-stop mode, value-added real estate information contents. The total information system of real estate designed in this paper includes a geological information system using a GIS, a property information system using photos and videos, a systemized legal consulting system, a web call center where customers can communicate with real estate experties on the web and lastly marketing analyses system using credit card data.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.325-332
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• 2009

The Korean real estate transaction makes a contract after the buying and selling person concerned agreed a business condition. As for vendee, business consists of the method that I issue documents before provision and money left over provision and the registration at the same time, and register a contract deposit in vendor. However, it latent for the real estate transaction various accidents such as fraud from a contract day to time to finish a real estate registration transfer, embezzlement, double contract by the breach of trust. Nevertheless vendee comes to match vendor by an asymmetry of the information one-sidedly to the front completing a registration transfer. I may prevent stellionate by the breach of trust of vendor if I use an ESCROW system in such a responsibility blank state.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.72-80
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• 2016

Re-auction happens when a bid winner defaults on the payment without making second in-line purchase declaration even after determining sales permission. This is a process of selling under the court's authority. Re-auctioning contract price of real estate is largely influenced by the real estate business, real estate value, and the number of bidders. This paper is designed to establish a statistical model that deals with the number of bidders participating especially in apartment re-auctioning. For these, diverse factors are taken into consideration, including ratio of minimum sales value from the point of selling to re-auctioning, number of bidders at the time of selling, investment value of the real estate, and so forth. As an attempt to consider ambiguous and vague factors, this paper presents a comparatively vague concept of real estate and bidders as trapezoid fuzzy number. Two different methods based on the least squares estimation are applied to fuzzy regression model in this paper. The first method is the estimating method applying substitution after obtaining the estimators of regression coefficients, and the other method is to estimate directly from the estimating procedure without substitution. These methods are provided in application for re-auction data, and appropriate performance measure is also provided to compare the accuracies.

• Journal of KIBIM
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• v.11 no.3
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• pp.12-21
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• 2021

Existing real estate markets are monopolized because they are capital intensive and have information asymmetry. However, with the advent of the Fourth Industrial Revolution, technology is converging in various industries based on information technology (IT), and the real estate market is also developing a new field called "PropTech". According to this trend, new PropTech technologies are emerging in various real estate services sectors in Korea, but the electronic contract system, which accounts for the largest portion of the real estate industry, is still cited as a complex identification process and long processing time. Therefore, in this paper, we propose an improvement plan for the current electronic contract system through the introduction of blockchain technology, which is drawing attention with the development of PropTech, and explore the possibility of introduction by producing an experimental model of blockchain-applied electronic contract system in a programming language.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.416-427
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• 2018

As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

• International Area Studies Review
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• v.15 no.1
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• pp.219-240
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• 2011

The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.125-137
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• 2011

This study empirically examined the structural relationships among service quality of internet real estate information web-sites, trust, customer satisfaction and reuse intention. In order to achieve the purpose, survey method was applied using a sample of 293 real estate information web-site users. The results of this study showed that service quality of real estate web-sites had a significant effect on trust and customer satisfaction. And, the trust of web-sites have influenced on customer satisfaction and reuse intention. Finally, the customer satisfaction of estate information web-sites had a significant positive effect on reuse intention.