scholarly journals Revisiting supply and demand indexes in real estate

2018 ◽  
Author(s):  
David Geltner ◽  
Alex van de Minne ◽  
Dorinth van Dijk
Keyword(s):  
Real Estate ◽  
Supply And Demand

Research on Supply and Demand of Xi'an Real Estate Market

2011 ◽  
Vol 368-373 ◽  
pp. 3078-3082
Author(s):  
Zhou Ji Meng ◽  
Tao Zhou ◽  
Shu Hua Gao
Keyword(s):  
Principal Component Analysis ◽  
Spectral Analysis ◽  
Real Estate ◽  
Spectral Density ◽  
Supply And Demand ◽  
Principal Component ◽  
Real Estate Market ◽  
Medium Term ◽  
Real Estate Price ◽  
Synthetic Indicators

In the passage, the indicators of supply and demand of real estate market in Xi'an are established, and such indicators are synthesized into a class of synthetic indicators using “principal component analysis”. After the spectral analysis of synthetic indicators, periodic change of supply and demand of real estate through spectral density could be determined. Through the analysis, great randomness existed in supply and demand of real estate in Xi’an. Furthermore, in the medium term, a 3.3 years’ secondary cycle still existed in synthetic indicators of demand, while randomness existed in synthetic indicators of supply. Such findings suggest a declined trend existed in real estate price in medium term of Xi’an.

International Real Estate Review

2001 ◽  
Vol 4 (1) ◽  
pp. 43-56
Author(s):  
Tsong-Yue Lai ◽  
◽  
Hin Man Mak ◽  
Ko Wang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Short Selling ◽  
Local Market ◽  
Short Sales ◽  
Rates Of Return ◽  
Short Sale ◽  
Asset Pricing Models ◽  
Short Sell ◽  
Property Markets

Asset pricing models have been used extensively in the recent real estate literature to evaluate real estate performance and estimate required rates of return of properties. In this paper, we show that the CAPM and its variants will derive a biased result when short sales are not allowed in the market. This problem is particularly serious for Asian property markets where investors are not able to short sell real estate indexes as a substitute for short selling real properties. We also demonstrate that the bias resulting from the short-sale constraint is related to the supply-and-demand conditions in the local market.

Designing an accommodation strategy: findings from an architecture school

Facilities ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chaiwat Riratanaphong
Keyword(s):  
Real Estate ◽  
Development Process ◽  
Supply And Demand ◽  
Development Theory ◽  
Architecture Education ◽  
Data Accessibility ◽  
Content Type ◽  
The Real Estate ◽  
Process Factors ◽  
Space Requirements

Purpose This study aims to explore the need for space (demand) and the provision thereof (supply) in the Faculty of Architecture building at Thammasat University Rangsit campus using variables from the designing an accommodation strategy (DAS) framework; these variables are incorporated to test and improve the framework. Another purpose is to examine the planning and development of the faculty building to understand its strategy, which serves as a means to contribute to the planning and development theory. Design/methodology/approach A case study of the Faculty of Architecture building was conducted at Thammasat University in Thailand. The DAS framework was used to reconstruct and examine the development process of the building to determine the gaps between supply and demand in terms of building space, to reflect on the building plan and process and to make suggestions as to how the DAS framework might be improved. Research methods included interviews and document analysis concerning space requirements and provision in the Faculty of Architecture building. Findings The gaps between supply and demand in terms of the faculty building space are affected by the condition of the building (i.e. building obsolescence), the number of building users and the changing environmental context. This study shows that both pre-design and post-occupancy evaluation are essential to collect data concerning the match or mismatch between supply and demand of space and to assess users’ needs and preferences concerning the faculty building. Regarding the building development process, factors impacting the step-by-step planning of the real estate interventions include the organisational context (public/private sector) and the management of the construction project (time, cost, quality). The DAS framework is found to be useful for structuring the information-generating processes necessary to determine gaps between demand and supply in terms of space and for making decisions regarding real estate interventions. Research limitations/implications Additional case studies in different environmental and organisational contexts are required to test the DAS framework and improve data validity. This study was conducted during the COVID-19 pandemic period, which affected data accessibility. Practical implications The results provide insight into the influence of various factors on the decision of corporate real estate. The DAS framework can be used to explore the range of demand for and supply of space and to find an optimal match. Originality/value This paper shows valuable steps in planning and development of educational real estate and a first application of the DAS framework in Thailand. The findings confirm the importance of the physical learning environment of architecture schools, particularly the studio spaces required in architecture education.

Content Strategy in Management of Communications

2021 ◽  
Vol 12 (3) ◽  
pp. s232-s242
Author(s):  
Olha Balabash ◽  
Valerii Ilin ◽  
Nataliia Poprozman ◽  
Inna Kuznetsova ◽  
Dmytro Shushpanov ◽  
...  
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Construction Company ◽  
The Real Estate Market ◽  
Content Strategy ◽  
Alternative Sources ◽  
The Web

The aim of the article is to substantiate the theoretical and methodological support for the formation and implementation of the content strategy of a construction company.  The article considers the formation of content strategy, its place in the management of communications of the enterprise. The following methods were used in the course of the research: the method of statistical analysis (for the analysis of the tendency of the real estate market development of Ukraine); analysis, synthesis, logical and theoretical generalization – to specify the factors of supply and demand in the real estate market; graphical method, table method (to visualize the results of the study); method of calculating specific indicators of communicative activity (CPC (Cost Per Click), CPA (Cost Per Action), CTR (Click Through Rate)) for analysing trends in traffic to the company's website and identifying alternative sources of traffic. The specifics of developing a content strategy taking into account the peculiarities of the company's construction industry are shown. An analysis of trends in the real estate market of Ukraine is carried out based on official statistics. The dynamics of the volume of construction works is analysed, the housing price indices in Ukraine are determined and the factors of supply and demand in the real estate market are specified. The analysis of communicative efficiency of the web-system of the construction company is carried out, as a result of which, measures for improvement of management of its external communications by substantiation of variants of advancement on the Internet are developed. This is done by analysing trends in traffic to the company's website and identifying alternative sources of traffic. The developed measures will increase the efficiency of management of the construction company. The article proposed a procedure for analysing the web-system of a construction company based on attendance indicators and search activity, which allows identifying alternative sources of traffic and developing appropriate measures to manage communications of the enterprise in order to achieve their efficiency. The practical significance lies in the fact that the developed recommendations for the formation of the communication strategy of the construction company can be further used to intensify the promotion of the company's services in the real estate market and attract investment.

Forces Affecting Supply and Demand for Industrial Real Estate

2019 ◽  
pp. 173-184
Author(s):  
Dror Poleg
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Industrial Real Estate

scholarly journals Level of Foreign Direct Investments and Transparency of Polish and Global Real Estate Market

2013 ◽  
Vol 21 (2) ◽  
pp. 22-28 ◽  
Author(s):  
Karolina Czechowska
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Real Estate Market ◽  
Easy Access ◽  
Foreign Direct Investments ◽  
The Real ◽  
The Real Estate ◽  
Market Transparency ◽  
Property Prices ◽  
The Real Estate Market

Abstract The article aimed to present the dependencies between the transparency of the real estate market and the level of foreign investments realized on it. For developers on the real estate market, a key element, other than potential profits, may be the market’s transparency. The main feature of a transparent real estate market is easy access to credible data concerning supply and demand, rent, property prices, transactions, vacant houses and capitalization rates that could be the basis for analysis. Market transparency does not guarantee the success of an investment, but considerably influences investment decisions and the level of risk connected with them.

scholarly journals Assessing the Possibility of Implementing Tools of Technical Analysys for Real Estate Market Analysis

2016 ◽  
Vol 24 (2) ◽  
pp. 85-96
Author(s):  
Justyna Brzezicka
Keyword(s):  
Real Estate ◽  
Capital Market ◽  
Traditional Approach ◽  
Supply And Demand ◽  
Technical Analysis ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Capital Market

Abstract Technical analysis (TA) and its different aspects are widely used to study the capital market. In the traditional approach, this analysis is used to determine the probability of changes in current rates on the basis of their past changes, accounting for factors which had, have or may have an influence on shaping the supply and demand of a given asset. In the practical sense, TA is a set of techniques used for assessing the value of an asset based on the analysis of the asset's trajectories as well as statistical tools. The work assumes three research objectives: 1) a review of tools applied in technical analysis, 2) an attempt at implementing selected tools of technical analysis for analyzing the real estate market (REM), 3) an assessment of the possibilities of implementing selected tools for assessing the real estate market on the example of the Olsztyn residential real estate market. The research hypothesis is a presumption regarding the possibility of implementing tools used in traditional technical analysis for the analysis of the real estate market accounting for the natural limitations and specifics of the market. The work extends scientific achievements in the part regarding the methods and tools of analyzing the real estate market as well as the connections between the real estate market and the capital market.

scholarly journals Estimating Warehouse Rental Price using Machine Learning Techniques

2018 ◽  
Vol 13 (2) ◽  
pp. 235-250 ◽  
Author(s):  
Yixuan Ma ◽  
Zhenji Zhang ◽  
Alexander Ihler ◽  
Baoxiang Pan
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Real Estate ◽  
Rapid Development ◽  
Supply And Demand ◽  
Machine Learning Techniques ◽  
Gradient Boosting ◽  
Logistics Industry ◽  
Real Estate Price ◽  
Learning Techniques

Boosted by the growing logistics industry and digital transformation, the sharing warehouse market is undergoing a rapid development. Both supply and demand sides in the warehouse rental business are faced with market perturbations brought by unprecedented peer competitions and information transparency. A key question faced by the participants is how to price warehouses in the open market. To understand the pricing mechanism, we built a real world warehouse dataset using data collected from the classified advertisements websites. Based on the dataset, we applied machine learning techniques to relate warehouse price with its relevant features, such as warehouse size, location and nearby real estate price. Four candidate models are used here: Linear Regression, Regression Tree, Random Forest Regression and Gradient Boosting Regression Trees. The case study in the Beijing area shows that warehouse rent is closely related to its location and land price. Models considering multiple factors have better skill in estimating warehouse rent, compared to singlefactor estimation. Additionally, tree models have better performance than the linear model, with the best model (Random Forest) achieving correlation coefficient of 0.57 in the test set. Deeper investigation of feature importance illustrates that distance from the city center plays the most important role in determining warehouse price in Beijing, followed by nearby real estate price and warehouse size.

scholarly journals Insight into Market Supply and Demand of Private Forests in Croatia

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Karlo Beljan ◽  
Ana Bašić ◽  
Matija Bakarić ◽  
Jiří Dvořák
Keyword(s):  
Real Estate ◽  
Free Market ◽  
Supply And Demand ◽  
Temporal Distribution ◽  
Real Estate Market ◽  
Private Forests ◽  
Economic Point ◽  
Wood Processing ◽  
Average Area ◽  
The Relationship

Due to their modest 23% share, private forests in Croatia are a resource that is perceived as less important than state-owned forests. One of the basic characteristics of private forests is fragmentation, which is also the biggest obstacle to a successful and, economically speaking, sustainable management of private forests. The cases in which a private forest with its area and integrity can generate a sustainable economic income to its owner are not common. However, from an economic point of view, private forests still have one advantage. Unlike state-owned forests, private forests can be the subject of investment and change hands. Based on this, this paper investigates the supply of private forests on the free market. For private forests that were publicly put for sale in the period from 2010 to 2020, their spatial-temporal distribution and supply dynamics and trends (price and quantity) were analyzed. The data were collected from the leading real estate advertising platform in Croatia (Njuškalo.hr), and a total of 866 advertisements were analyzed, relating exclusively to the sale of raw wood material along with the accompanying forest land. On the other hand, in order to assess the demand, data were collected on the number of potential buyers who viewed the advertisements (period 2020-2021). In the observed ten-year period, a total of 1,890.63 ha of private forests with a total asking value of €32.14 million were offered on the market. The share of advertisements advertised through real estate agencies is 42.1%. The average total annual supply is 170 ha and has a growing trend (in the advertisements in the coastal part of Croatia, the average area is 1.3 ha, while the average area in the continental part is 3 ha). The prices are not constant but rising. According to compound interest, the price increase in the coastal area is 1.57% and 7.49% in the continental area. From the relationship between supply and demand or, more precisely, the relationship between price and the quantity, it was concluded that the market is not well developed and that the price is not affected by the supply/demand quantity of private forests. Furthermore, it was concluded that this market is developing in the direction of a typical real estate market in Croatia due to the fact that forest management and wood processing characteristics of forests do not define the price, but that the price is largely determined by a market with greater financial importance (the market in real estate near the Adriatic coast).

scholarly journals ANALYSIS OF PRICING FACTORS IN REAL ESTATE MARKET

2019 ◽  
Vol 6 (2) ◽  
pp. 79-85
Author(s):  
Maria Chernyshova ◽  
Arina Malenkaya ◽  
Tatyana Mezhuyeva
Keyword(s):  
Real Estate ◽  
Supply And Demand ◽  
Market Price ◽  
Real Estate Market ◽  
Physical Factors ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Pricing Factors ◽  
Real Estate Prices

In the real estate market price depends on supply and demand is formed under the influence of social, economic and physical factors. The article presents the results of the analysis of pricing factors in the real estate market, the forecast of real estate prices in 2019.

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