• Title/Summary/Keyword: 부동산 투자

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Spatial analysis for a real transaction price of land (공간회귀모형을 이용한 토지시세가격 추정)

  • Choi, Jihye;Jin, Hyang Gon;Kim, Yongku
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.217-228
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    • 2018
  • Since the real estate reporting system was first introduced, about 2 million real estate transaction per year have been reported over the last 10 years with an increasing demand for real estate price estimates. This study looks at the applicability and superiority of the regression-kriging method to derive effective real transaction prices estimation on the location where information about real transaction is unavailable. Several issues on predicting the real estate price are discussed and illustrated using the real transaction reports of Jinju, Gyeongsangnam-do. Results have been compared with a simple regression model in terms of the mean absolute error and root square error. It turns out that the regression-kriging model provides a more effective estimation of land price compared to the simple regression model. The regression-kriging method adequately reflects the spatial structure of the term that is not explained by other characteristic variables.

호텔 체인업체 발리 리조트 시장으로 러시

  • Kim, So-Jin
    • 주택과사람들
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    • s.207
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    • pp.36-41
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    • 2007
  • 신들이 선택한 '성지의 땅'이라 불리는 발리.외국의 유명 호텔 체인업체들이 발리에 깃발을 꽂고 리조트사업을 펼치고, 해외 투자 자본들이 발리 부동산 시장으로 이동하고 있다. 리조트 단지 곳곳에 신을 섬기고, 자연에 순응하며 살아가는 발리인들의 생활문화가 고스란히 녹아 있는 발리를 다녀왔다.

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두 얼굴의 도시, 자카르타

  • Kim, So-Jin
    • 주택과사람들
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    • s.204
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    • pp.46-49
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    • 2007
  • 1997년 아시아 외환위기를 겪은 인도네시아는 아직 환란을 완전히 극복하지 못했다. 환율은 여전히 안정적이지 않고, 부실 대출 비율이 증가하는 등 불안 요인도 많다. 정부 차원에서 외국인 투자 유치를 위한 정책을 내놓는 등 시장 활성화에 힘쓰고 있는 인도네시아 자카르타 부동산 시장을 짚어보았다.

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SPECIAL REPORT-용산, 뚝섬 재개발 지분 강세

  • Lee, Eun-Suk
    • 주택과사람들
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    • s.195
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    • pp.28-31
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    • 2006
  • 정부의 세금 정책과 잇단 공급 규제로 인해 하반기 부동산 시장은 침체 일로를 걷고 있다. 이 같은 상황에서 유일한 대안으로 떠오르는 것이 바로 재개발 지분 투자. 한남동 성수동 등 한강변 인접 지역 중심으로 지분값이 초강세를 보이고 있는 재개발 지역을 취재했다.

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A Study of Rent Determinants of Small and Medium-Sized Office Buildings in Seoul Using a Dynamic Panel Model: Focusing on CBD and GBD Comparison (동적패널모형을 활용한 서울시 중소형 오피스 빌딩 임대료 결정 요인 연구: CBD(도심권)와 GBD(강남권) 비교를 중심으로)

  • NaRa Kim;JinSeok Yu;Jongjin Kim
    • Land and Housing Review
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    • v.14 no.4
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    • pp.47-62
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    • 2023
  • Using the dynamic panel model, this study investigates rent determinants for small and medium-sized office buildings in Korea's CBD and Gangnam areas, key business districts. The results reveal that rents for small and medium-sized office buildings in CBD and Gangnam areas are influenced by macroeconomic fluctuations and characteristics of buildings and locations, suggesting a market with both spatial consumer and investment goods attributes. There are several investment implications as follows. First, even if the location in the CBD area is advantageous, the practical limitations in renovating aging small and medium-sized office buildings must be taken into account when investing. Second, parking conditions are a key factor influencing rent prices in CBD areas, so evaluating the parking facilities and improvement potential of small and medium-sized office buildings is essential for investors. Finally, due to the high sensitivity of Gangnam's small and medium-sized office market to macroeconomic trends, it's vital to prioritize monetary policy shifts as a key factor in investment decisions.

Real-Estate Price Prediction in South Korea via Machine Learning Modeling (머신러닝 기법을 통한 대한민국 부동산 가격 변동 예측)

  • Nam, Sanghyun;Han, Taeho;Kim, Leeju;Lee, Eunji
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.15-20
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    • 2020
  • Recently, the real estate is of high interest. This is because real estate, which was considered only a residential environment in the past, is recognized as a stable investment target due to the ever-growing demand on it. In particular, in the case of the domestic market, despite the decrease in the number of people, the number of single-person households and the influx of people to large cities are accelerating, and real estate prices are rising sharply around the metropolitan area. Therefore, accurately predicting the prospects of the future real estate market becomes a very important issue not only for individual asset management but also for government policy establishment. In this paper, we developed a program to predict future real estate market prices by learning past real estate sales data using machine learning techniques. The data on the market price of real estate provided by the Korea Appraisal Board and the Ministry of Land, Infrastructure and Transport were used, and the average sales price forecast for 2022 by region is presented. The developed program is publicly available so that it could be used in various forms.

A Study on Transaction Service of Virtual Real Estate based on Metaverse (메타버스 기반 가상부동산 거래 서비스 연구)

  • Yoo, Jongyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.83-88
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    • 2022
  • The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

Effects of Investment Behavior Factors and Sub-attributes for Lots Shopping Building on Investment Intention: Comparative Studies between Factor Level and Attribute Level and among Investors Segmented by Investment Intention (분양상가 투자행동요인과 속성들이 투자의도에 미치는 영향: 요인과 속성수준에서의 비교 및 투자의도 세분화집단 간 비교)

  • Jang, Hosup;Kim, Joongin
    • The Journal of the Korea Contents Association
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    • v.21 no.12
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    • pp.348-362
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    • 2021
  • Real estate investment behavior factors are divided into profitability, risks (stability), liquidity, and regulation (deregulation) factors. The sub-attributes of the investment behavior factors are generally formative indicators. Unlike reflection indicators, formative indicators can identify not only the influence of investment behavior factors on dependent variables, but also the influence of sub-attributes on dependent variables. Therefore, theoretical and practical needs of comparing the influences of factors and sub-attributes on dependent variables has been suggested. In this study, in order to provide information that help marketing for lots shopping building, both the causality between investment behavior factors and investment intention and the causality between sub-attributes and investment intention were comparatively studied for each of the three investor groups: the whole group, the group with high investment intention and the group with low investment intention. For this purpose, a survey and multiple regression analyses were conducted on 237 existing investors in the customer DB of a company that have been developing and selling lots shopping building in the metropolitan area and Sejong City. At the factor level, the effects of profitability and regulation were significant in the whole group and the group with low investment intention, but the effects of risk and liquidity were significant in the group with high investment intention. At the sub-attribute level, all three groups showed different results.

A Study about creating jobs suitable for the ubiquitous age - The center of the real estate industry - (유비쿼터스 시대에 맞는 일자리창출에 관한 연구 - 부동산산업 중심으로 -)

  • Kim, Hyeong-Geun;Kim, Boo-Sung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.3
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    • pp.499-503
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    • 2013
  • In the real estate industry, job creation is dominated by SOC financial investment expansion. Financial investment like SOC can induce employment only if is executed as cost of equipment by setting the budget as a long-term project. In this study, a hypothesis was set regarding how the real estate industry affects job creation, and makes suggestions based on analysis of relational structure among variables through the research model.

An Empirical Study on the Estimation of Housing Sales Price using Spatiotemporal Autoregressive Model (시공간자기회귀(STAR)모형을 이용한 부동산 가격 추정에 관한 연구)

  • Chun, Hae Jung;Park, Heon Soo
    • Korea Real Estate Review
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    • v.24 no.1
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    • pp.7-14
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    • 2014
  • This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.