scholarly journals The Dynamic Relationship Between Stock and Real Estate Prices in Kuwait

2019 ◽  
Vol 11 (5) ◽  
pp. 30
Author(s):  
Sadeq J. Abul
Keyword(s):  
Real Estate ◽  
Stock Prices ◽  
Stock Markets ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
The Real Estate ◽  
Dynamic Relationship ◽  
Emerging Stock Markets ◽  
The State Of Kuwait ◽  
Real Estate Prices

This paper examines empirically the dynamic relationship existing between the stock and real estate markets in the State of Kuwait for the period from January 2007 to December 2017. The main features of the real estate market in Kuwait are reviewed, and two indices are constructed to measure the activity of the residential real estate (land and houses) and multi-apartment buildings in the Kuwaiti real-estate market. The empirical analysis employs the main proper tests, such as the Johansen (1998) cointegration test and Vector Error Correction Model (VECM). These two tests confirm the long- and short-term association between Kuwaiti stock prices and multi-apartment building prices only, while no evidence of such a relationship is found for the residential real estate (land and houses) prices. This paper extends the literature available on the emerging stock markets, as the Kuwaiti Stock Market is one of the oldest stock markets in the member countries of the Gulf Cooperation Council (GCC). In addition, the results obtained in this paper have useful implications for academics and policy-makers in Kuwait.

scholarly journals Evaluation of the Applicability of Statistical Methods in Studies on Price Dynamics on the Real Estate Market

2013 ◽  
Vol 21 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Sebastian Kokot ◽  
Marcin Bas
Keyword(s):  
Real Estate ◽  
Traditional Approach ◽  
Real Estate Market ◽  
Price Dynamics ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
Time Period ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The specific character of the real estate market is the reason why observations of transaction prices seen as statistical variables are taken in a non-standard way. In the traditional approach each time period or specific moments of time are attributed with one observation of a studied variable per one object. In the case of the real estate market, this is not possible since transactions relate to different objects, i.e., properties, and occur at irregular, or even random, moments. This is why traditional methods used to examine the dynamics of economic phenomena must be adapted to specific conditions on the real estate market. Keeping that in mind, the aim of this paper is to adapt classical statistical examination methods of dynamics to specific conditions of the real estate market followed by the actual examination of the dynamics of real estate prices in three sub-segments of the housing market in Szczecin. On its basis, the authors evaluate various methods of examining real estate price dynamics in terms of their applicability in real estate appraisal procedures and, in a broader perspective, present characteristic phenomena that can be observed on the real estate market.

An Empirical Research on the Relationship between Real Estate Prices and Inflation

2011 ◽  
Vol 55-57 ◽  
pp. 1992-1996
Author(s):  
Tie Qun Li
Keyword(s):  
Real Estate ◽  
Stock Prices ◽  
Test Analysis ◽  
Social Demand ◽  
The Real Estate ◽  
Key Factor ◽  
Negative Effect ◽  
Labor Service ◽  
Real Estate Prices ◽  
The Relationship

The former researches referring to inflation and real estate prices concentrated mainly on the stock prices rather than the real estate prices. Owing to the enlarging ratio of real estate industry in national economy with each passing day, as well as the overheating real estate prices in recent years, the relationship between real estate prices and inflation is particularly vital to the monetary policy making for the monetary authorities. According to the test analysis of data from 2001 to 2009, it is found that real estate prices is Granger Cause of inflation while inflation is not the Granger Cause of real estate prices in this paper. Through the Effects of Wealth, Credit and Tobin, real estate prices drive the growth of social consumption and investments and expand the total social demand which possess an positive effect on inflation; nevertheless the rising of real estate prices causes the rising of currency for real estate purchasing, which, under the circumstance of that currency supply remains, will inevitably bring about the reduction of currency for other consumption and investments and restrain the total social demand which would mean a suppression of continuous rising of prices of other commodity and labor service. All these show that real estate also has a negative effect on inflation. The cancellations between the two effects make the long-term influence real estate bearing on inflation is not obvious. The experimental results indicate that when the price of real estate rises 1%, inflation only rises 0.058%. Consequently, a strict controlling of the amount of money issued is the key factor for keeping the over rapid rising of real estate prices from leading to inflation.

scholarly journals Use of Statistical Models for Simulating Transactions on the Real Estate Market

2015 ◽  
Vol 23 (2) ◽  
pp. 102-111 ◽  
Author(s):  
Radosław Cellmer ◽  
Katarzyna Szczepankowska
Keyword(s):  
Probability Distribution ◽  
Real Estate ◽  
Statistical Models ◽  
Real Estate Market ◽  
Model Parameters ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The regularities and relations between real estate prices and the factors that shape them may be presented in the form of statistical models, thanks to which the diagnosis and prediction of prices is possible. A formal description of empirical observation presented in the form of regressive models also offers a possibility for creating certain phenomena in a virtual dimension. Market phenomena cannot be fully described with the use of determinist models, which clarify only a part of price variation. The predicted price is, in this situation, a special case of implementing a random function. Assuming that other implementations are also possible, regressive models may constitute a basis for simulation, which results in the procurement of a future image of the market. Simulation may refer both to real estate prices and transaction prices. The basis for price simulation may be familiarity with the structure of the analyzed market data. Assuming that this structure has a static character, simulation of real estate prices is performed on the basis of familiarity with the probability distribution and a generator of random numbers. The basis for price simulation is familiarity with model parameters and probability distribution of the random factor. The study presents the core and theoretical description of a transaction simulation on the real estate market, as well as the results of an experiment regarding transaction prices of office real estate located within the area of the city of Olsztyn. The result of the study is a collection of virtual real properties with known features and simulated prices, constituting a reflection of market processes which may take place in the near future. Comparison between the simulated characteristic and actual transactions in turn allows the correctness of the description of reality by the model to be verified.

scholarly journals The use of mean values for reporting real estate prices

2021 ◽  
Vol 64 (04) ◽  
pp. 513-532
Author(s):  
Melita Ulbl ◽  
Andraž Muhič
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Mean Values ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Special Challenge ◽  
The Republic ◽  
Real Estate Prices ◽  
The One

The proper and unambiguous reporting of the real estate market is one of the main requirements for ensuring its transparency. Reporting on the prices of real estate realised on the market is a special challenge here. For this purpose, averages are generally used, requiring both the reporter and the reader to be well acquainted with the rules of individual types of averages on the one hand and the specificities and heterogeneity of the real estate market on the other. In this paper, we present the specifics of individual mean values that can be used for this purpose. These characteristics are analysed in more detail and presented in the case of the Slovenian housing market. The purpose of this paper is to present the dilemmas faced in Slovenia when reporting on real estate prices on the market and present the solutions that the Surveying and Mapping Authority of the Republic of Slovenia will begin to introduce in its reports on the real estate market.

scholarly journals COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)

2020 ◽  
Vol 9 (7) ◽  
pp. 114 ◽  
Author(s):  
Vincenzo Del Giudice ◽  
Pierfrancesco De Paola ◽  
Francesco Paolo Del Giudice
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Campania Region ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Short Run ◽  
Predator Model ◽  
Real Estate Prices

The COVID-19 (also called “SARS-CoV-2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

scholarly journals FOR SALE… BUT FOR HOW LONG? A METHODOLOGICAL PROPOSAL FOR ESTIMATING TIME-ON-THE-MARKET

2015 ◽  
Vol 19 (4) ◽  
pp. 309-324 ◽  
Author(s):  
Vanda C. S. MARTINS ◽  
Marlene N. M. FILIPE ◽  
Fernando A. F. FERREIRA ◽  
Marjan S. JALALI ◽  
Nelson J. S. ANTÓNIO
Keyword(s):  
Real Estate ◽  
Evaluation System ◽  
Socioeconomic Development ◽  
Cognitive Mapping ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
Analytic Hierarchy ◽  
The Real Estate ◽  
Time On The Market ◽  
Measurement Framework

Residential real estate assumes crucial importance in a country's socioeconomic development. It is an important field of study, and much work has gone into better understanding the sector and the factors determining sales within it, such as time-on-the-market (TOM). TOM can be influenced by a variety of elements; a fact that in effect raises a lot of issues, because these determinants are often interpreted in an ambiguous or unstructured way. This study aims to bring greater accuracy and structure to our understanding of these factors, by showing that the integrated use of cognitive mapping with the Analytic Hierarchy Process (AHP) can give rise to a conceptually coherent and empirically valid framework to calculate TOM indices in the residential real estate market. Because it takes into account both tangible and intangible characteristics of a house, this measurement framework also boosts strategic planning support and allows for more informed business planning, which we believe can be a real contribution to the development of the real estate market. The practical implications and limitations of this evaluation system are also discussed.

scholarly journals The Mathematical Model of Forecasting the Price Level in the Regional Market of Residential Real Estate

2019 ◽  
pp. 40-55
Author(s):  
Ekaterina Voronina ◽  
Olga Yarosh ◽  
Natalya Bereza ◽  
Marina Rossinskaya
Keyword(s):  
Mathematical Model ◽  
Real Estate ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
The Real ◽  
The Real Estate ◽  
Goods And Services ◽  
Regional Market ◽  
The Real Estate Market ◽  
Intelligent Data Processing

The purpose of this article is to develop a mathematical model for estimating the value of a real estate object, taking into account the trends in the residential real estate market using indicators of the object’s state and indicators of the real estate market. The real estate market is a complex mechanism that includes subjects, objects, processes and infrastructure. The real estate market has its own characteristics that distinguish it from the market of goods and services related to the duality of real estate, its special characteristics. Despite the high conservatism, there are certain innovative trends in the development of the residential real estate market (innovations in construction, architecture, services and marketing, logistics, customer focus). The article considers the residential real estate market as a complex socio-technical system, to predict the development of which it is advisable to use a combination of classical forecasting methods and soft computing or intelligent data processing methods. A forecast of the development of the residential real estate services market was made using foresight technologies (industry roadmap). The analysis was carried out and the main factors acting on the market were identified, and their influence on the development of market trends was determined. A mathematical model for predicting the value of residential real estate based on the theory of fuzzy sets has been developed.

scholarly journals Construction of social indicators using information measuring principles. Case study of real estate prices simulation model

2011 ◽  
Vol 52 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Natalja Kosareva ◽  
Laura Gudelytė
Keyword(s):  
Real Estate ◽  
Simulation Model ◽  
Empirical Data ◽  
Social Indicators ◽  
Real Estate Market ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Testing Tool ◽  
Real Estate Prices

The article analyses the data concerning the real estate market of last years in Vilnius. The approach of dichotomous diagnostic operators as general testing tool creation from the empirical data is used and deterministic clusterization of catchments is provided. Based on this analysis, questionnaire concerning the information about catchment is constructed for the evaluation of aggregated appartment price.

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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