Multicriteria analysis and genetic algorithms for mass appraisals in the Italian property market

2018 ◽  
Vol 11 (2) ◽  
pp. 229-262 ◽  
Author(s):  
Pierluigi Morano ◽  
Francesco Tajani ◽  
Marco Locurcio
Keyword(s):  
Genetic Algorithms ◽  
Real Estate ◽  
Polynomial Regression ◽  
Real Estate Market ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Multi Objective ◽  
Evolutionary Polynomial Regression ◽  
Residential Properties

Purpose This paper aims to test and compare two innovative methodologies (utility additive and evolutionary polynomial regression) for mass appraisal of residential properties. The aim is to deepen their characteristics, by exploring the potentialities and the operating limits. Design/methodology/approach With reference to the same case studies, concerning samples of residential properties recently sold in three Italian cities, the two procedures are tested and the results are compared. The first method is the utility additive, which interprets the process of the property price formation as a multi-criteria selection of multi-objective typology, where the selection criteria are the property characteristics that are decisive in the real estate market; the second method is a hybrid data-driven technique, called evolutionary polynomial regression, that uses multi-objective genetic algorithms to search those models expressions that simultaneously maximize accuracy of data and parsimony of mathematical functions. Findings The outputs obtained from the experimentation highlight the potentialities and the limits of the two methodologies, as well as the possibility of jointly applying them to interpret and predict the real estate phenomena in a more realistic representation. Originality value In all countries, mass appraisal techniques have become strategic for the definition of management and enhancement policies of public and private property assets, in the case of investments of technical and economic refunctionalization (energy, environment, etc.), and for the alienation of buildings no longer suitable for public needs (military barracks, hospitals, areas in disuse, etc.). In this context, the use of mass appraisal techniques for residential properties assumes a leading role for sector operators (buyers, sellers, institutions, insurance companies, banks, real estate funds, etc.). Therefore, the results of the applications outline the potentialities of the two methodologies implemented and the opportunity of further insights of the topics that have been dealt with in this research.

Godrej properties: valuation using the capital cash flow technique

2020 ◽  
Vol 10 (3) ◽  
pp. 1-23
Author(s):  
Rajni Kant Rajhans
Keyword(s):  
Real Estate ◽  
Cash Flow ◽  
Structural Changes ◽  
Real Estate Market ◽  
Firm Valuation ◽  
Free Cash Flow ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market

Learning outcomes The case is focused to meet the following learning objectives: the readers will be able to recall basic cash flow estimation concepts; and the readers will be able to explain various features of capital cash flow (CCF). The participants will be able to implement the CCF model in real estate firm valuation. The participants will be able to compare CCF and free cash flow to the firm (FCFF) models. The participants will be able to evaluate the benefits of CCF over FCFF. The readers will be able to construct the CCF valuation model for firm valuation. Case overview/synopsis On 19th April 2019, Mr Kai, an analyst tracking real estate firms was excited to present to his team a new robust technique of firm valuation suitable for real estate companies, namely, the CCF technique and was also keen to deliberate on its application. Though the investment scope using this technique could be located in Godrej properties (GP), a reputed brand and the largest listed real estate developer by sales in 2018, yet, he was concerned about the assumptions of growth of real estate industry in India, in general, and the GP in particular. Importantly, this was because the real estate market in India was undergoing many structural changes. For instance, the buyers’ preferences were changing and unsold inventory in the industry was at its peak. Under these market conditions, an announcement was made by GP about a target return on equity of 20% in 2018–2023 expecting a dominant place in the real estate market in India, which also carried the threat of jeopardizing the reputation of GP, if under any circumstance the target was not accomplished. Complexity academic level Masters program. Supplementary materials Teaching notes are available for educators only. Subject code CSS: 11 Strategy.

scholarly journals Impacts of digitization on real estate sector jobs

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Piazolo ◽  
Utku Cem Dogan
Keyword(s):  
Real Estate ◽  
Weighted Average ◽  
Real Estate Market ◽  
Real Estate Industry ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Employment Agency ◽  
Real Estate Sector ◽  
Substitution Probability

PurposePrevious research on automation and job disruption is only marginally related to the real estate industry and its characteristics. This study investigates the effects of digitization on jobs in German real estate sector, in order to assess the proportion of jobs threatened to be replaced by automation. Since Germany is the largest EU economy insights for the German real estate market allow a first approximation for Europe.Design/methodology/approachAn extensive database of the German Federal Employment Agency containing job definitions and occupation titles is matched with real estate criteria to create a subset with the relevant real estate occupations. This data is combined with a database of the German Institute of Employment Research reflecting to what extent tasks within jobs can be automated by current technical capabilities.FindingsFor the 286 identified occupations within the real estate sector a weighted average of 47 percent substitution probability through current technological capabilities is derived for tasks within the examined occupations.Practical implicationsThis contribution indicates the extent of the structural change the real estate sector has to face due to digitization: One out of two real estate jobs will have to be re-created.Originality/valueThis research quantifies the magnitude of the job killer aspect of digitization in the real estate sector.

Investor attention for retail and institutional investors: a test on the real estate market

2013 ◽  
Vol 31 (4) ◽  
pp. 314-328
Author(s):  
Gianluca Mattarocci ◽  
Georgios Siligardos
Keyword(s):  
Real Estate ◽  
Institutional Investors ◽  
Real Estate Market ◽  
Investor Attention ◽  
Causality Test ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market

PurposeThe paper aims to investigate the relationship between different investor attention proxies for different types of funds (retail vs institutional ones) looking at a sample of real estate funds.Design/methodology/approachThe authors collect data about searching frequency on Google and all the news published in Italian specialized newspapers for a set of real estate funds. Following the approach proposed by Da, Engelberg and Gao, the authors construct a set of attention proxies and they compare the ranking with some summary statistics and evaluate the causality relationship among them using a Granger causality test.FindingsResults demonstrate that online search frequency is relevant for both institutional and retail funds and normally internet data are able to anticipate the news that will be published in the newspapers.Research limitations/implicationsThe analysis proposed is focused only on a small real estate market (Italy) where funds are specialized for the type of investor. A wider database can allow excluding that results achieved are biased by the specific features of the market analysed.Practical implicationsThe role of internet proxies attention measures also for institutional investors demonstrate that the managing companies offering financial instruments reserved to institutional investors should consider both channels of information – newspapers and the internet – to measure any positive or negative sign of investor attention to their products.Originality/valueThe article represents the first analysis of investor attention proxies on the real estate market and the first comparison of investor attention proxies for retail and institutional investors.

Financialisation and development: a case study of Ethiopia

2019 ◽  
Vol 11 (2) ◽  
pp. 138-196
Author(s):  
Anne Löscher
Keyword(s):  
Real Estate ◽  
Financial Development ◽  
Industrial Development ◽  
Real Estate Market ◽  
Economic Research ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Debt Levels

Purpose This paper aims to shed light on financial development in Ethiopia and its implications for overall economic development. It does so with particular focus on development understood as industrial development and with special attention drawn on inequality and debt levels as well as the real estate market in Ethiopia. Two research questions are focussed on in particular, where the first serves as prerequisite for the assessment of the second: What kind of financial development took place in Ethiopia in the past quarter of a century? Furthermore, are processes of financialisation visible in Ethiopia, and if so, to what effect? Design/methodology/approach The paper is based on publicly available macro-data and qualitative and quantitative data collected by the author herself during a three months’ research stay in Ethiopia. Findings It is found that despite higher levels of financial inclusion and deepening, industrialisation is on a relative decline. What is more, inequality and debt levels increase, and the recent growth spurts seem to be rooted in the construction sector with prices in the real estate market surging. In can be concluded that despite a flourishing financial sector, the Ethiopian economy is faced with the peril of crises associated with an inflated real estate market, inequality, debt burdens and impeded industrialisation. Originality/value African economies and, in particular, the development and effects of financial markets are still a blind spot in economic research. By combining quantitative and qualitative data on and gathered in Ethiopia, this paper therefore conducts greenfield research.

Calibration of impact of attributes in the real estate mass appraisal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Krzysztof Dmytrów ◽  
Wojciech Kuźmiński
Keyword(s):  
Real Estate ◽  
Design Methodology ◽  
Hybrid Approach ◽  
Calibration System ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Hybrid Approaches ◽  
Residential Properties ◽  
Statistical Approaches

PurposeOur research aims in designation of a hybrid approach in the calibration of an attribute impact vector in order to guarantee its completeness in case when other approaches cannot ensure this.Design/methodology/approachReal estate mass appraisal aims at valuating a large number of properties by means of a specialised algorithm. We can apply various methods for this purpose. We present the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA) and the four methods of calibration of an attribute impact vector. Eventually, we present its application on the example of 318 residential properties in Szczecin, Poland.FindingsWe compare the results of appraisals obtained with the application of the hybrid approach with the appraisals obtained for the three remaining ones. If the database is complete and reliable, the econometric and statistical approaches could be recommended because they are based on quantitative measures of relationships between the values of attributes and properties' unit values. However, when the database is incomplete, the expert and, subsequently, hybrid approaches are used as supplementary ones.Originality/valueThe application of the hybrid approach ensures that the calibration system of an attribute impact vector is always complete. This is because it incorporates the expert approach that can be used even if the database excludes application of approaches that are based on quantitative measures of relationship between the unit real estate value and the value of attributes.

Investigating the causes of increasing consumer demand for real estate housing in Bangladesh

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mazed Parvez ◽  
Sohel Rana
Keyword(s):  
Real Estate ◽  
Consumer Satisfaction ◽  
Secondary Data ◽  
Real Estate Market ◽  
Sample Size Determination ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Increasing Demand

Purpose The purpose of this paper is to find out the causes of increasing population in the real estate area. The demographic in information of the respondents and the level of satisfaction was also carried out for this study. Design/methodology/approach The authors use both primary and secondary data. Total 329 respondents were surveyed at the real estate area after completing sample size determination. Secondary data was collected from journals, real estate offices and papers. After that, using regression and correlation analysis, the data was analyzed and finalized. Findings This study identified migration as the most critical variable. The study determined ten hypotheses and only accepted two. By that, this study finds out the causes of the increasing demand of plots and flats in real estate. Originality/value This study will work as a baseline study for the real estate sector in Bangladesh. Most of the research on Bangladesh’s real estate is done mainly on real estate market assessment and consumer satisfaction. Nevertheless, this study will find out the causes of the increasing population in real estate.

Cyclical capitalization and lag vacancy

2017 ◽  
Vol 10 (2) ◽  
pp. 211-238 ◽  
Author(s):  
Maurizio d’Amato
Keyword(s):  
Real Estate ◽  
Market Value ◽  
Real Estate Market ◽  
Mortgage Lending ◽  
Property Market ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Valuation Process

Purpose This paper aims to propose a new valuation method for income producing properties. The model originally called cyclical dividend discount models (d’Amato, 2003) has been recently proposed as a family of income approach methodologies called cyclical capitalization (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017). Design/methodology/approach The proposed methodology tries to integrate real estate market cycle analysis and forecast inside the valuation process allowing the appraiser to deal with real estate market phases analysis and their consequence in the local real estate market. Findings The findings consist in the creation of a methodology proposed for market value and in particular for mortgage lending determination, as the model may have the capability to reach prudent opinion of value in all the real estate market phase. Research limitations/implications Research limitation consists mainly in a limited number of sample of time series of rent and in the forecast of more than a cap rate or yield rate even if it is quite commonly accepted the cyclical nature of the real estate market. Practical implications The implication of the proposed methodology is a modified approach to direct capitalization finding more flexible approaches to appraise income producing properties sensitive to the upturn and downturn of the real estate market. Social implications The model proposed can be considered useful for the valuation process of those property affected by the property market cycle, both in the mortgage lending and market value determination. Originality/value These methodologies try to integrate in the appraisal process the role of property market cycles. Cyclical capitalization modelling includes in the traditional dividend discount model more than one g-factor to plot property market cycle dealing with the future in a different way. It must be stressed the countercyclical nature of the cyclical capitalization that may be helpful in the determination of mortgage lending value. This is a very important characteristic of such models.

Real estate market cyclical dynamics

2014 ◽  
Vol 10 (2) ◽  
pp. 241-262 ◽  
Author(s):  
Kim Hin/David Ho ◽  
Kwame Addae-Dapaah
Keyword(s):  
Hong Kong ◽  
Real Estate ◽  
Real Estate Market ◽  
Var Model ◽  
Kuala Lumpur ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Price Response ◽  
Real Estate Cycle

Purpose – The purpose of this paper is to help us understand the real estate cycle and offers an analysis using a vector auto regression (VAR) model. The authors study the key international cities of Hong Kong, Kuala Lumpur and Singapore. The authors find four key outcomes. One, the real estate cycle is generally different from the underlying business cycle in local markets for the cities studies. Two, the real estate cycle is more exaggerated in the construction and development areas than in rents and vacancies. Three, the vacancy cycle tends to lead the rental cycle. And four, new construction completions tend to peak when vacancy is also peaking. The authors believe that future research should try to help understand the linkages that drive these outcomes. For example, are rigidities in the local permit and construction markets responsible for the link between construction peaks and vacancy peaks? Design/methodology/approach – Real estate market cyclical dynamics and its estimation via VAR model offers an insightful set of practical and empirical models. It affirms a comprehensive theoretical underpinning for analysing the prime office and residential sectors of the capitol cities of Kuala Lumpur, Singapore and Hong Kong in the fast developing Asia region. Its unrestricted form also provides an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, furnished by real estate market data providers. Findings – The office rental VAR model for Singapore (SOR), KL (KOR) and HK (HOR) show good fits. In the HOR model, rents and vacancies are negatively signed and significant for certain lagged relationships with other variables and with rents themselves. The office CV VAR model for Singapore (SOCV), KL (KOCV) and HK (HOCV) show good fits. In the HOCV model, capital values (CVs) and initial yields are negatively signed and significant for certain lagged relationships with other variables and with CVs themselves. Impulse response functions specified for seven years to mirror a medium-term real estate market cycle “die out” to zero for the stationary VAR models that are estimated for the endogenous variables. The accumulated responses asymptote to some non-zero constant. Practical implications – The VAR model offers a complete and meaningful dynamic system of solely real estate variables for international real estate investors and policy makers in decision making. Its unrestricted form offers an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, which can be reliably provided by a dedicated real estate information and consultancy provider of international standing. Originality/value – The theoretical model offers a complete dynamic model system of the real estate space market, comprising a unique system of six linked equations that denote the relationship among supply, demand, construction, vacancy and rent over time, inclusive of price response slopes and lags. The VAR model enables the investigation of the effect of the lagged values of all the variables concerned. It also enables the explicit and rigorous quantitative forecasts of say rents and CVs when the rest of the variable can be forecasted beforehand.

Determinants of residential property time on the real estate market in Nigeria

2016 ◽  
Vol 27 (2) ◽  
pp. 148-155
Author(s):  
Victoria Amietsenwu Bello ◽  
Taiwo Olusola Adeola
Keyword(s):  
Real Estate ◽  
Multiple Regression Model ◽  
Real Estate Market ◽  
Residential Property ◽  
The Real ◽  
The Real Estate ◽  
Time On The Market ◽  
The Real Estate Market ◽  
Bare Land ◽  
Residential Properties

The real estate market consist of properties of various types (commercial, industrial, agricultural, recreational and residential) that are believed to have inflation hedging characteristics that make them ideal investment in the building industry. In the market, investment in residential property is not a liquid asset; its illiquidity is most often measured by the time the property spends on the market. The time on the market may be determined by variables such as physical attributes of the property and macroeconomic variables. The paper therefore examined the variables that explain the time bare land (for residential development) and residential property spends on the market before being sold in Akure, Nigeria. Using the Multiple Regression Model, the study finds Season Property was Listed for Sale, Distance to the Tarred Road and Asking Price to have influence on the time bare land was sold. For the residential properties, variables such as State of Repairs, State of Water Supply, Zone and Number of Convenience in a house were significant. The study therefore recommended that property developers should pay attention on these housing attributes that influence time on the market in order to enhance the marketability of their properties and thereby reduce the time property spends on the market.

A spatiotemporal exploratory analysis of real estate sales in Turkey using GIS

2019 ◽  
Vol 12 (2) ◽  
pp. 207-226
Author(s):  
Saffet Erdoğan ◽  
Abdulkadir Memduhoğlu
Keyword(s):  
Real Estate ◽  
Spatiotemporal Analysis ◽  
Real Estate Market ◽  
Investment Planning ◽  
Annual Average ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Real Estate Sales

PurposeThe purpose of this paper is to examine the real estate sales in Turkey on a district basis to reveal the current state of real estate sales and any meaningful changes in the last period. The real estate market is important and is an indicator of the country’s general economic health, as real estate is seen as an investment.Design/methodology/approachAs a powerful method of spatial analysis and evaluation, geographic information systems have been used to examine real estate data in both spatial and temporal ways. In this study, 14 years of sales data covering the years 2004 to 2017 obtained from government agencies on a district basis were evaluated using spatiotemporal methods. Several maps were produced using Getis-Ord Gi* and local Moran’s I indices, which showed the spatiotemporal change of sales and sales rates.FindingsWhen looking at the maps, provinces such as Istanbul, Ankara, Izmir, Antalya and their surrounding districts have buoyant real estate markets compared to the other side of the country. Real estate sales are more stagnant in the eastern and northern parts of the country. In addition, the authors found that the growth rate of annual average real estate sales was approximately seven times higher than the annual average population growth.Originality/valueThis spatiotemporal study, which presents 14 years of performance data of the real estate market and, by extension, the economic situation, also highlights the regions that stand out for investment planning throughout the country. The results of spatiotemporal analysis also present a new way of real estate market visualization using maps with well-designed categorizations.

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