• Korean Management Science Review
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• v.31 no.1
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• pp.17-26
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• 2014

This study presents a new real estate value analysis model considering the changes in the population structure. We propose a new model that takes advantage of the binomial option model one of the techniques of real options and considers the changes in the population structure. The real estate market price data of Seoul city from year 2001 to 2012 were extracted and the correlation analysis between real estate prices and changes in the population structure was performed. The result shows that they have positive correlation with one year time lag. The coefficient between the real estate prices and demographic changes was estimated using the OLS analysis and included in the traditional binomial option model to calculate the value of the property. It is assumed for the future price prediction that real estate invested in Seoul in January, 2013 will be sold within five years. Analysis result shows that the values of real estate in September of 2013 were predicted as 583.5 million won in the new model and as 582.4 million won in the traditional model. This reflects that the new model considering the change of population change gives better realistic performance than the traditional one.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.96-106
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• 2018

The government adopted activation policy of real estate to overcome low economic growth rate. Real estate activation plan adopted by the government raised credit limit by lowering the regulation, and reduced real estate investment cost by reducing the base rate. Also, delayed transfer tax on multi-house owner to activate real estate investment and resolved purchase right resale. Relief of real estate regulate caused increase of housing sales and price increase, and the real estate market changed to overheating aspect such as premium upon completion of lot sale in a short time. Such market atmosphere greatly increased household debs as owners own houses based on 'financial debt' instead of their income. Since 2017, real estate policy was reinforced to reduce household debts and lending rate was raised due to rise of base rate, accordingly, burden of household debt is expected to increase. This research suggested a plan for the Financial Supervisory Service to efficiently manage the financial world by analyzing the cause and problem of household debs.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.229-236
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• 2021

There has been a lot of research on the real estate market, but a lack of research on the supply and demand of housing supply in each region, reflecting the changes in population growth and supply. It is calculated as the transition probability of the Markov chain model by reflecting the data on the number of houses per 1,000 people in the past 35 years and the forecast data for population change by region, in terms of supply (housing) to demand (population) for factors on the real estate market. According to the calculation results of the real estate market by region, the housing supply to the metropolitan area such as Gyeong-gi, Incheon, and Seoul is expected to be insufficient for a considerable period of time, considering the population changes by region. To stabilize the real estate market, it was confirmed that it was necessary to actively apply the differentiation of housing supply by region. It is meaningful in terms of verifying long term trends in the real estate market by region that reflect the prediction of population change, and it is expected that the methods used in this study will be practical through the analysis results using the historical data.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.41-52
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• 2010

Even though REITs (Real Estate Investment Trusts) are listed on the stock market, REITs have characteristics that allow them to invest in real estate and financing for real estate development. Therefore REITs is related with stock market and construction business and real estate business. Using time-series analysis, this study analyzed REITs in relation to construction businesses, real estate businesses, and the stock market, and derived influence factor of REITs. We used the VAR (vector auto-regression) and the VECM (vector error correction model) for the time-series analysis. This study classified three steps in the analysis. First, we performed the time-series analysis between REITs and construction KOSPI(The Korea composite stock price index) and the result showed that construction KOSPI influenced REITs. Second, we analyzed the relationship between REITs and construction commencement area of the coincident construction composite index, office index and housing price index in real estate business indexes. REITs and the housing price index influence each other, although there is no causal relationship between them. Third, we analyzed the relationship between REITs and the construction permit area of the leading construction composite index. The construction permit area is influenced by REITs, although there is no causal relationship between these two indexes, REITs influenced the stock market and housing price indexes and the construction permit area of the leading composite index in construction businesses, but exerted a relatively small influence in construction starts coincident with the composite office indexes in this study.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1553-1560
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• 2013

This study focused on the residential real estate market, real estate for sale in the course of the bargaining power of buyers in terms of factors to be extracted was determined. In addition to rental housing, including the number of buyers have several alternatives, the more related information, the buyers have advantage over the sellers in the course of the housing sale process. And if the external conditions and the situations between the parties have changed, how much flexibility to respond to changing and the less costs of to changing, the buyers have advantage over the sellers in the course of the housing sale process.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.349-356
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• 2012

Entering the era of globalization, international real estate companies to advance into the country are increasing. And real estate transactions, the need for transparency and reliability are becoming even more. The alternative that real estate transactions in advance to avoid an accident is just an escrow system. Analysing the status and actual conditions of escrow in the country's real estate market and presenting the activation plans are as follows. First, the government should support building bulk service for real estate transactions. Second, tax benefits should be developed.

• Land and Housing Review
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• v.9 no.1
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• pp.1-9
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• 2018

As the government announced Real Estate Policies on August 02, most areas except for Seoul cities face increasing business risks. Moreover, the government control over financial sectors' loan leads to the highly possible contraction of new distribution markets. The market trend could bring about the reduction of new demand in PF (Private Financing) business that large construction companies mainly concentrate on, and even the business already obtained has a high risk of being distributed, which could result in substantially low profitability. The currently unstable financial structure of most construction companies is caused by the hike of the prime cost of foreign plants except for that of a few construction companies. If PF (Private Financing) business also faces a difficult situation in such a financial condition, even large construction companies come to have the high possibility of a deficiency in credit rating. Accordingly, the major business that large construction companies concentrate on needs the sufficient business review. It is desirable to make a bid for business guaranteeing stability rather than business solely in consideration of profitability, when participating in a competition for a new construction contract.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.175-182
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• 2016

In the 21st century knowledge and information society, Electronic Contracts made with the intention of electronic computer information networks are emerging as a new legal problem which can not be solved in the conventional legal system governing contracts. In other words, the indicator's decision determines the effect and formation of the contracts in the face-to-face or written contracts but electronic decision through computer information network is established the working process of electronic signals-electronic contracts are not only difficult to separate the decision-making process but questioned to be solved by the theory of the general legal action. Ministry of Transportation is scheduled to introduce real estate sales and lease contract using a variety of electronic devices such as computer, tablet PC, smart phones and so on without a paper contract. This system is conducted to global expansion of Seoul in demonstration zone on May 8, 2016 and will be implemented nationwide in the second half of 2017. Electronics contract Real estate has some benefits because made by linking electronic contract system and the electronic registration system - the economic effects discounts on various kinds of fees, the prevention from real estate fraud beforehand and the solution to the complexity of the process the seller and the buyer visits The Real estate agency. However, it has some problem- the disorder in the real estate contract market, the occurrence of the real estate agency accident and the author of the electronic real estate contracts have limited only to realtor. In this paper, I suggest the activation plan to search for establishment and effect of electronic contracts and declaration of intention in electronic depending on the Electronic Contract Real Estate system.