• 제목/요약/키워드: Real Estate Market

검색결과 349건 처리시간 0.023초

실물옵션 기법을 응용한 부동산 가치평가 연구: 인구구조 변화를 고려하여 (A Study on the Valuation of Real Estate Using the Applies Real Option Model Considering Population Structure Changes)

  • 구승환;왕핑;장성용
    • 경영과학
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    • 제31권1호
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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.

금융권 가계부채 위험증가에 따른 금융감독원 관리방안에 관한 연구 (Study on Management Plan of the Financial Supervisory Service According to Increase of Risk of Household Debts)

  • 이윤홍
    • 한국건설관리학회논문집
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    • 제19권2호
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    • pp.96-106
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    • 2018
  • 정부는 낮은 경제성장률을 극복하기 위해 부동산 활성화정책을 도입하였다. 정부가 추진한 부동산 활성화정책은 규제를 낮춰 대출한도를 높였고, 기준금리도 인하하여 부동산 투자비용을 절감시켰다. 부동산투자를 활성화하기 위해 다주택자에게 양도세 부과를 유예하고, 전매제한도 해지시켰다. 부동산규제 완화는 주택매매 증가와 가격상승으로 이어졌고, 분양아파트는 단기간에 분양이 완료되어 프리미엄이 형성되는 등 부동산시장이 과열양상으로 전환되었다. 이러한 시장분위기는 본인의 소득이 아닌 금융권 '부채의존형'으로 주택을 소유하게 되어 가계대출이 크게 증가되었다. 2017년부터는 가계대출 축소를 위해 부동산대책이 강화되었고, 기준금리도 상승하여 대출 금리도 높아진 만큼, 가계부채 부담은 더욱 증가될 것으로 판단된다. 본 연구논문은 가계부채의 발생 원인과 문제점을 분석하여 금융감독원이 금융권을 효율적으로 관리할 수 있는 방안을 제안하고자 한다.

주택수와 인구증가 변화를 반영한 지역별 부동산 시장 예측 (Prediction of the Real Estate Market by Region Reflecting the Changes in the Number of Houses and Population)

  • 배영민
    • 한국융합학회논문지
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    • 제12권4호
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    • pp.229-236
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    • 2021
  • 인구 증감과 주택공급의 변화를 반영하여 지역별 주택 수급 예측에 대한 중·장기적인 연구는 부족하였다. 본 연구에서는 최근 35년간 인구 1,000 명당 주택 수, 지역별 인구 변화율 그리고 향후 예측되는 지역별 인구증가 예측율을 반영하여 부동산 시장의 수요와 공급 측면에서 지역별 주택수 공급과 수요에 대하여 마코프 체인 모형의 전이확률을 적용하여 중·장기적인 지역별 주택수를 확인한다. 모형 수행결과, 지역별 부동산 시장은 경기, 인천, 서울 등 수도권에 대한 주택공급은 지역별 인구변화를 고려할 때 상당기간 부족할 것으로 예상되며 시간이 지나면서 다른 지역은 전국평균 주택수에 수렴하는 경향을 통해 안정화 될 것으로 예측되었고 부동산 시장 안정을 위해서는 지역별 주택공급 차별화를 적극 적용할 필요가 있는 것으로 확인되었다. 이번 연구에서 제시된 방법에 대해 실용적으로 사용될 수 있는 점과 지역별 인구증감 예측을 반영한 지역별 부동산 시장의 중·장기적인 방향성을 확인한다는 점에서 의미를 기대할 수 있다.

리츠와 건설경기, 부동산경기, 주식시장과의 관계 분석 (Relation Analysis Between REITs and Construction Business, Real Estate Business, and Stock Market)

  • 이치주;이강
    • 한국건설관리학회논문집
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    • 제11권5호
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    • pp.41-52
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    • 2010
  • 리츠는 주식시장에 상장되어 있으면서 부동산 개발을 위한 자금조달의 성격과 부동산에 투자하는 특징도 있으므로, 주식 시장과 건설 및 부동산시장과 관계가 있을 것으로 예상할 수 있다. 본 연구에서는 리츠와 주식시장, 건설 및 부동산 경기와 관계된 지표들을 시계열 분석하여, 리츠와의 영향관계를 분석하였다. 시계열 분석은 백터자기회귀모형과 백터오차수정모형을 사용하였으며, 다음의 세 부분으로 분류하여 분석하였다. 첫째, 리츠와 건설 코스피 지수와의 관계를 분석한 결과, 건설 코스피 지수가 리츠에 영향을 주는 것으로 분석되었다. 둘째, 리츠와 건설경기 동행지수인 건축착공면적, 부동산 경기 지수인 오피스 임대지수와 주택매매가격지수와의 관계를 분석하였다. 각 지표들은 서로 인과관계는 없는 것으로 분석되었지만, 리츠와 주택매매가격지수는 서로에게 영향을 주는 것으로 분석되었다. 셋째, 리츠와 건설경기 선행지수인 건축허가면적의 관계를 분석하였다. 두 지표는 서로 인과관계가 없는 것으로 분석되었지만, 건축허가면적이 리츠에 영향을 미치는 것으로 분석되었다. 본 연구를 통해 리츠는 주식시장과 주택경기, 건설경기 선행지표인 건축허가 면적에 영향을 받지만, 건설경기 동행지표인 건축착공면적과 오피스 임대지수에는 상대적으로 영향을 작게 받는 것으로 분석되었다.

자산가격의 결정요인에 대한 실증분석 : 미국사례를 중심으로 (A Study on Determinants of Asset Price : Focused on USA)

  • 박형규;정동빈
    • 산경연구논집
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    • 제9권5호
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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.

Prediction Model of Real Estate ROI with the LSTM Model based on AI and Bigdata

  • Lee, Jeong-hyun;Kim, Hoo-bin;Shim, Gyo-eon
    • International journal of advanced smart convergence
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    • 제11권1호
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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.

부동산 구매자의 협상력 결정요인에 관한 연구 (A study of the determinant factors of Negotiation Power of Real estate buyer)

  • 권호근;김동현
    • 한국전자통신학회논문지
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    • 제8권10호
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    • pp.1553-1560
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    • 2013
  • 본 연구는 주거용 부동산시장을 중심으로 부동산의 매매과정에서 구매자 입장에서 본 협상력의 결정요인들을 추출하고자 하였다. 구매자는 주택의 매수 이외에 임대 등 여러 대안을 가질수록, 매매과정에서 관련 정보가 많을수록 주택의 매매 가격협상에 있어서 유리하다. 그리고 협상과정에서 외부나 계약 당사자 간의 상황이 변경되었을 경우, 얼마나 유연하게 대처하는가의 정도와 상황변경에 따르는 비용이 적게 들수록 주택의 매매협상에서 유리하게 작용됨을 볼 수 있다.

부동산거래 안정을 위한 에스크로우 활성화 방안에 대한 연구 (A Study on the Scheme to Revitalize the Escrow through the Stabilization of Real Estate Transactions)

  • 권영식;박창수
    • 한국전자통신학회논문지
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    • 제7권2호
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    • pp.349-356
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    • 2012
  • 국제화시대에 다국적 부동산기업들이 국내에 진출하면서 거래의 투명성과 안정성에 대한 요구는 더욱 늘어가고 있다. 부동산 거래사고를 사전에 방지할 수 있는 대안이 바로 에스크로우제도이다. 우리나라 부동산 시장에서 에스크로우의 현황과 실태를 분석하고 그 활성화 방안을 제시하면 다음과 같다. 첫째, 부동산 거래 일괄서비스 시스템의 구축에 정부지원이 있어야 한다. 둘째, 에스크로우 제도 참여확대를 위한 세제혜택을 부여하여야 한다. 셋째, 에스크로우 관련 전문 인력을 많이 배출하여야 한다.

부동산시장 변화에 따른 대형건설사 리스크관리 방안에 관한 연구 (A Study on the Risk Management Strategy of the Large Scale Construction Company According to the Change of Real Estate Market)

  • 이윤홍;지규현
    • 토지주택연구
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    • 제9권1호
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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.

An Activation Plan of Electronic Contract Real Estate

  • Youn, Sung-Ho
    • 한국컴퓨터정보학회논문지
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    • 제21권10호
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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.