• 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.

• Spatial Information Research
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• v.21 no.6
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• pp.69-80
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• 2013

Our country has made every efforts to develop Real Estate Transaction culture with emphasis on Licensed Realtors by introducing Real Estate Transaction Law in 1983. Also, MOLIT(Ministry of Land, Infrastructure and Transport) designated several organizations including KAR(Korea Association of Realtors) as Real Estate Transaction Information Network Licensees for data credibility enhancement and transaction transparency. Nevertheless, the level of law abiding spirit and transaction culture are still similar to those of the old 'Bokdeokbang' era. The under-developed transaction behaviors prevent the social capital of people's credibility on Licensed Realtors from advancing, and results in the outcomes of unnecessary social cost. That is, very low credibility on the data on Sales Items in the market and the fear of speculative real estate price uprise and market distortions are continuing on. In this context, the purpose of this study is to propose the model of GIS-based Modernized Real Estate Transaction System and its execution policies to support credible Real Estate Information to the general public for efficient transactions in the market. Accordingly, the study aims at contributing to the modernization of Real Estate Transactions, fostering competitiveness of Realtors in the Real Estate Market.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.592-609
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• 2019

This study attempts to expand the leverage cycle theory using the subprime real estate investors. The leverage cycle theory has demonstrated asset price fluctuations irrelevant to changes in fundamentals through the restructuring of transaction composition centered on optimistic buyers. However, it needs to understand how this theory works in the depressed housing market with low-income residential regions to explain the geographic origins of the financial crisis. In the depressed housing market, the subprime real estate investors focused on low-income residential regions. Through this spatial focus, the low-income residential regions solely have real estate investor-oriented composition of new purchase transactions in the depressed housing market. The discovery of the subprime real estate investors as new actors lays the foundation for applying the leverage cycle theory to the depressed housing market which has been a underserved area for capital investment. This attempt illustrates how the geographical reinterpretation of an economic theory reestablishes spatio-temporal context of economic phenomena.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.49-55
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• 2019

This study is on the trend of real estate market using text mining and big data. The data were collected through internet news posted on Naver from August 2016 to August 2017. As a result of TF-IDF analysis, the frequency was high in the order of housing, sale, household, real estate market, and region. Many words related to policies such as loan, government, countermeasures, and regulations were extracted, and the region - related words appeared the most frequently in Seoul. The combination of the words related to the region showed that the frequencies of 'Seoul - Gangnam', 'Seoul - Metropolitan area', 'Gangnam - reconstruction' and 'Seoul - reconstruction' appeared frequently. It can be seen that the people's interest and expectation about the reconstruction of Gangnam area is high.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.3
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• pp.245-262
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• 2007

This paper aims at analyzing the characteristics of performance and asset management system of listed property trusts(LPT) in Australia, and elucidating the implications for Korean real estate indirect investment market. The main results of this paper are as follows. Firstly, LPT have a leading position among the real estate indirect investment systems in Australia, through the rapid growth of market capitalization. Secondly, LPT achieved superior risk adjustment performance than other financial products, and had valid portfolio diversification effect. Thirdly, many LPT have used stapled securities structure as a asset management system, and stapled LPT revealed superior risk adjustment performance than unit LPT. Finally, implications and policy measures such as using the stapled structure and activating the development activities were examined for the development of Korean real estate indirect investment market.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.211-231
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• 2003

In this study, first, current state and future prospects of indirect real estate investment systems after foreign exchange crisis are analyzed, and second, policy alternatives for activating indirect real estate investment markets are examined. After foreign exchange crisis, various indirect real estate investment systems, such as REITs, ABS and CRC, were introduced. Present market size of indirect real estate investment is not larger than expected. The reasons are the problems of incomplete system on the one hand, and real estate market conditions on the other hand. But long term prospects of indirect real estate investment markets may not be pessimistic. Considering the positive effects of indirect real estate investment systems to the real estate and financial markets, policy supports for activating indirect real estate investment market may be needed. The representative alternatives are reconciliation and integration of indirect real estate investment systems, upgrading the infrastructure of real estate industry, and activating the networks between indirect real estate investment markets and related markets such as financial makets, capital markets, restructuring markets.

• The Journal of Society for e-Business Studies
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• v.14 no.3
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• pp.15-37
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• 2009

This study presents a new retrieval system developed to consider various preferential requirements for buyers in the real estate market. The paper analyses essential factors affecting the price of real estate and then a set of factors are classified by region-related factor and individual-related factor. After endowing the buyer's selected factors with weights in the retrieval system, the optimal solutions have been drawn by comparing with the others through an entropy measure of Multi-attribute Decision Making. This retrieval system is applied to the Busan real estate market to estimate the solutions of retrieval. Evaluation results indicate that the retrieval system can provide useful information to analyse the price determination factors of real estate, as well as to save the searching cost of the buyers.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.75-87
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• 2023

We designed to employ an Artificial Intelligence learning model to predict real estate prices and determine the reasons behind their changes, with the goal of using the results as a guide for policy. Numerous studies have already been conducted in an effort to develop a real estate price prediction model. The price prediction power of conventional time series analysis techniques (such as the widely-used ARIMA and VAR models for univariate time series analysis) and the more recently-discussed LSTM techniques is compared and analyzed in this study in order to forecast real estate prices. There is currently a period of rising volatility in the real estate market as a result of both internal and external factors. Predicting the movement of real estate values during times of heightened volatility is more challenging than it is during times of persistent general trends. According to the real estate market cycle, this study focuses on the three times of extreme volatility. It was established that the LSTM, VAR, and ARIMA models have strong predictive capacity by successfully forecasting the trading price index during a period of unusually high volatility. We explores potential synergies between the hybrid artificial intelligence learning model and the conventional statistical prediction model.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.111-124
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• 2011

The apartment' share of the housing has steadily increased and property assets have been valued in importance as the one of asset value. Information retrieval system using internet is particularly active in the real estate market. However, user satisfaction on real estate information system is not very high, and there is a lack of research on real estate retrieval to increasing efficiency until now. This study presents a new knowledge information system developed to consider region-related factor and individual-related factor in the real estate market. In addition it enables a real estate knowledge system to search various preferential requirements for buyers such as school district, living convenience, easy maintenance as well as price. We made a survey of the search condition preference of experts on 30 real estate agents and then analyzed the result using AHP methodology. Furthermore, this research is to build apartment ontology using semantic web technologies to standardize various terminologies of apartment information and to show how it can be used to help buyers find apartments of the interest. After designing architecture of a real estate knowledge information system, this system is applied to the Busan real estate market to estimate the solutions of retrieval through Multi-Attribute Decision Making(MADM). Based on the results of the analysis, we endowed the buyer and expert's selected factors with weights in the system. Evaluation results indicate that this new system is to raise not only the value satisfaction of user, but also make it possible to effectively search and analyze the real estate through entropy analysis of MADM. This new system is to raise not only the value satisfaction of buyer's real estate, but also make it possible to effectively search and analyze the related real estate, consequently saving the searching cost of the buyers.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.73-84
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• 2013

The development of the information on the internet brought a lot of changes in the real estate market. Because the real estate has local distinctiveness and individuality household who want to move must to visit place for housing information. But now household use internet real estate information at every decision-moving step and that is able to reduce not only the cost of real estate information but also social benefit like $CO_2$ emissions reduction effect. In this study, I analyzed the effect of $CO_2$ emissions reduction with Seoul household residential mobility data when household take informations from internet real estate site. As increasing a single family who is good at internet service, the effect of $CO_2$ reduction from the development of the Internet real estate information has more increased.