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.

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.

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.

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.

Measuring behavioural biases affecting real estate investment decisions in India: using IRT

2018 ◽  
Vol 11 (4) ◽  
pp. 648-668 ◽  
Author(s):  
Richa Pandey ◽  
V. Mary Jessica
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Investment Decisions ◽  
Real Estate Market ◽  
Psychometric Test ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Level Of Agreement

Purpose This study aims to investigate the behavioural biases influencing the real estate market investing decisions of normal non-professional investors in India. Design/methodology/approach As the study involves the behavioural data with polytomous response format, psychometric test- graded response model (IRT approach) was used for the study with the help of STATA 14. Multi-stage stratified sampling was used to collect a sample of 560 respondents. The study used a 14-item scale representing behavioural biases derived from two broad behavioural theories, i.e. heuristics and prospect theories. Sample characteristics were checked using SPSS 20. Pre-required assumptions for IRT (i.e. local independence and unidimensionality) were tested by CFA using AMOS 20. Findings Five items, four of which belong to heuristics (anchoring – 2, representativeness – 1 and availability bias – 1) and one belong to prospect theory (regret aversion) are sufficient to measure the behavioural attitude of real estate investors in the Indian scenario. Item discrimination ai ranged from 0.95 to 1.52 (average value 1.29), showing moderate discrimination power of the items. The items have done a pretty good job of assessing the lower level of agreement. For the higher level of agreement, the scale came out to be less precise, with less information and higher standard error of measurement. Research limitations/implications As the behavioural biases are often false, the study suggests the investors not to repeat these nasty biases to improve investment strategies. As they are shared and not easily changeable, understanding these biases may also help them in beating the market by acting as “noise traders”. Practical implications The traditional price index is incomplete in some essential respects. The inclusion of these behavioural biases into the construction of price index will greatly improve the traditional price index, policymakers should seriously think about it. Social implications Shelter is one of the basic needs; a dwelling unit is needed for one to stay in, develop and contribute to economy and society. If investors try to minimise these biases and policymakers keep a track of these while making strategies, mispricing in this sector can be controlled to some extent, which will ultimately help in the well-being of society. Originality/value This study contributes to the limited research by investigating the behavioural biases influencing the real estate market investment decisions of normal non-professional investors. It contributes to the lacking academe on real estate market in India. The study has used a psychometric test, i.e. the item response theory, for evaluating the quality of the items.

The impact of external factors on housing prices in Lithuania

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alina Stundziene ◽  
Vaida Pilinkienė ◽  
Andrius Grybauskas
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
External Factors ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Impact

Purpose This paper aims to identify the external factors that have the greatest impact on housing prices in Lithuania. Design/methodology/approach The econometric analysis includes stationarity test, Granger causality test, correlation analysis, linear and non-linear regression modes, threshold regression and autoregressive distributed lag models. The analysis is performed based on 137 external factors that can be grouped into macroeconomic, business, financial, real estate market, labour market indicators and expectations. Findings The research reveals that housing price largely depends on macroeconomic indicators such as gross domestic product growth and consumer spending. Cash and deposits of households are the most important indicators from the group of financial indicators. The impact of financial, business and labour market indicators on housing price varies depending on the stage of the economic cycle. Practical implications Real estate market experts and policymakers can monitor the changes in external factors that have been identified as key indicators of housing prices. Based on that, they can prepare for the changes in the real estate market better and take the necessary decisions in a timely manner, if necessary. Originality/value This study considerably adds to the existing literature by providing a better understanding of external factors that affect the housing price in Lithuania and let predict the changes in the real estate market. It is beneficial for policymakers as it lets them choose reasonable decisions aiming to stabilize the real estate market.

Centipede Game network model of investment in real estate market based on grey integration and forwards induction

2014 ◽  
Vol 4 (2) ◽  
pp. 321-327 ◽  
Author(s):  
Lulu Shui
Keyword(s):  
Real Estate ◽  
Network Model ◽  
Real Estate Market ◽  
Market Game ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Multi Agent ◽  
Investment Process

Purpose – The purpose of this paper is to attempt the construct of a Centipede Game network model of investment in real estate market based on grey integration and forwards induction. Design/methodology/approach – The investment process of decision making in the real estate market is a multi-agent-stage dynamic process. The behavior of the game are interdependent and the ultimated equilibrium is an outcome of every the game adjust themselves comprehensively in certain conditions. The paper constructs a Centipede Game network model of investment in real estate market based on grey integration and forwards induction, regulars the method framework based on grey integration and forwards induction. Findings – The results verifies that the validity of Centipede Game network model by taking N's real estate market as an example. Practical implications – Most of the existing real estate market game researches study it from the view of pairwise game or one-to-many game, in fact, the game tend to be developed in the form of a network. And the paper puts forward Centipede Game network model based on the mode of players game in real estate market. Originality/value – The paper succeeds in providing a new and systematic framework of studying the real estate market game by using game theory.

Sub-optimal behavioural biases and decision theory in real estate

2019 ◽  
Vol 12 (2) ◽  
pp. 330-348 ◽  
Author(s):  
Richa Pandey ◽  
V. Mary Jessica
Keyword(s):  
Real Estate ◽  
Evolutionary Psychology ◽  
Real Estate Market ◽  
Mediating Effect ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Long Time ◽  
The Relationship

Purpose The purpose of this study is to explain the relationship between behavioural biases, investment satisfaction and reinvestment intention considering the effect of evolutionary psychology. The study believes that biases are not at all times bad; sometimes, biases can assist the individual investor to select the top course of action and allow them to go for the less costly mistakes, thereby helping in achieving satisficing behaviour. Design/methodology/approach Data were collected using structured and a close-ended questionnaire from a sample of 560 respondents by using multi-stage stratified sampling method. PLS-SEM was used for preliminary validation of the questionnaire. Mediation model using the structural equation model (SEM) with the help of AMOS 20 was used for the analyses. Pre-requisite assumptions for SEM were checked by using sample characteristics. The study has three constructs with multiple items; hence, the instrument validation was done by measuring the construct validity and reliability using Cronbach’s alpha, exploratory factor analysis and confirmatory factor analysis with the help of SPSS 20 and AMOS 20. Findings The study confirms that behavioural biases influence investment decisions in the real estate market. Further, investment satisfaction is found to have a significant and complementary partial mediating effect. The positive mediating effect of investment satisfaction between behavioural biases and reinvestment intention shows that biases are natural tendencies in response to limit to learning which can be explained by evolutionary psychology. Research limitations/implications There are chances that the result obtained here is because of myopic decision-making behaviour in which the long-time horizon is not considered and behavioural biases, as well as evolutionary psychology, are adaptive, so the result may change in the long-time horizon, which seeks further investigations. The study talked about the relationship between behavioural biases, investment satisfaction and reinvestment intention; it will be interesting to bring some more constructs in this model, for example, investment intention and reinvestment behaviour; this can deliver a more precise picture in this regard. Practical implications Understanding such relationships will help in better clarity about the way investment is made. The study confirms that market behaviour in the real estate market is sub-optimal, which shows that there is an opportunity for attentive investors by trading and gathering on information. Real estate practitioners can get clues from market anomalies and investor phenomena; understanding these may suggest ways to use them in the market. Social implications Reforms in the housing sector do not only satisfy one of the basic needs but also leads to holistic economic development. Besides direct contribution, it contributes to social capital. Originality/value The study extends the current knowledge base about the relationship between behavioural biases, investment satisfaction and reinvestment intention. This study investigates the behavioural biases influencing the real estate market investment decisions of non-professional investors considering the effect of evolutionary psychology.

scholarly journals Trust in a viable real estate economy with disruption and blockchain

Facilities ◽  
2018 ◽  
Vol 36 (1/2) ◽  
pp. 103-120 ◽  
Author(s):  
Jan Veuger
Keyword(s):  
Real Estate ◽  
Value Chain ◽  
Social Impact ◽  
Real Estate Market ◽  
Content Type ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Impact

Purpose The real estate world finds itself at a tipping point of a transition: a dramatic and irreversible shift in (real estate) systems in society. This paper is a State of the art of Disruption, Blockchain and Real Estate in the Netherlands and international. Design/methodology/approach The following questions were asked to all those involved: What do you think is the essence of Blockchain for real estate? What is the most current situation with respect to Blockchain and real estate from your perspective? Which publications are important from your perspective? What do you expect with respect to the impact of Blockchain on real estate for (social) real estate? What are questions for the future for real estate and Blockchain? In addition, interviews, exploratory conversations and correspondence took place, and the content was peer reviewed. Findings Changes in value concepts affect the valuation of real estate and the thinking about it. The orientation of changing users and owners of real estate affects innovativeness, values and flexibility in managing that property. Orientation on disruption must be seen as proof that the real estate world is able to actually innovate the accumulated assets and consolidate this. The financial and real estate markets are markets that exaggerate through irrational behaviour. Fear of “eat or be eaten” determines people’s behaviour. Financial and thus real estate markets are always unstable and must always be regulated by people and organizations. Research limitations/implications The question that remains is whether it is important to look at disruptive innovations in existing markets or newcomers in the real estate market and Blockchain. The question is whether Blockchain is only a technological disruption, or a real game changer, and whether the entire value chain of the real estate market will embrace it. No two disruptions are the same. Trust in Blockchain is a prerequisite for guiding the predictable form of that disruption where start-up companies use new technology to offer cheaper and inferior alternatives to real estate in the market. You could also talk about anti-fragile value: “Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile. Let us call it antifragile” (Taleb, 2012), in other words: attention to disruption and Blockchain creates a viable real estate economy. Practical implications The true meaning of the Blockchain technology for real estate still needs to be investigated. The author is still curious to understand and clarify the value of Blockchain for real estate processes. Doubt continues to exist and is therefore a feeding ground for further research, because we do not know what we have not seen. Social implications Looking at the impact of Blockchain on real estate, a number of conclusions can be drawn. First of all, the relationship between Blockchain and real estate has not yet been proven in practice. It is expected to develop further in the form of registering transaction processes and the DNA passport of a real estate object. Secondly, completeness and transparency are the basic ingredients for trust in the system. Third, real estate wants to remain viable. For this reason, taking the offense is necessary for real estate and management to connect with social demand. Behaviour also leads to new earnings models of the social and economic spin-off of disruptive real estate. If the Dutch real estate sector embraces Blockchain and is able to realize innovations, there are opportunities for real estate entrepreneurs to exploit the disruptive character to provide those new services. Originality/value The way in which disruption, Blockchain and real estate will develop in the coming years are not the only obvious characteristics of a particular era but also its social impact and user behaviour. This also applies to how this real estate transition can best be tracked, guided and utilized in society at the international, national and regional level. Disruptive organizations clearly respond to the viability of the (built) environment and therefore determine competitive strength. This affects the current and future valuation of real estate.

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