scholarly journals Market and cadastral data comparison for the real estate market value forecasting

2020 ◽  
Vol 17 (4) ◽  
pp. 44-54
Author(s):  
M. B. Laskin ◽  
P. A. Cherkesova
Keyword(s):  
Real Estate ◽  
Normal Distribution ◽  
Market Value ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
Market Data ◽  
The Real ◽  
The Real Estate ◽  
Saint Petersburg ◽  
The Real Estate Market

The aim of the research is to develop theoretical and methodological approaches to market value forecasting in the real estate market. The relevance of the research is determined by the system-forming place that the real estate market occupies in the economy of the country and regions, affecting the interests of owners of various forms of ownership, construction and development companies, insurance companies, banks. Another aspect that determines the actuality of the study is the discrepancy between well-structured cadastral databases and market data dispersed between different owners of information resources, and the unstructured nature of market data, which in most cases is focused on advertising, rather than on analytical market research.Materials and methods. The study uses a model of a multidimensional logarithmically normal distribution law of the ensemble of prices for residential real estate at equidistant points of time and cadastral value, the ARIMA model for predicting market value, taking into account the features of the logarithmically normal distribution of prices, as a distribution with positive asymmetry. As a statistical material, we used market data on residential real estate published in the periodical press in the period from the end of 2012 to 2018. The volume of samples of weekly publications is 15000-20000 objects; data for 21 quarters (more than five years) was used. As a comparison base, we used data from cadastral registration of real estate objects in Saint Petersburg for 2018. The total volume of the cadastral database of residential real estate in Saint Petersburg (individual apartments) is 2 226734 objects with a fairly complete (and well-structured) set of price-forming factors. The authors propose a method for estimating the most likely movement of the market value for a pre-selected real estate object that has passed cadastral registration and has a cadastral value entered in the register and predicting the market value in the future period.Results. The theoretical significance of the work is the proposed algorithm for estimating the most probable trajectory of the market value of the investigated object, based on the conditional multivariate log-normal distribution for a given value of the cadastral value. A well-developed and studied ARIMA time series forecasting model is applied to the logarithms of the obtained time series, the return from logarithmic prices to real prices is carried out taking into account the peculiarities of the logarithmically normal distribution. Results are compared with median scores and estimates, obtained by average values.Conclusion. The paper shows that the introduction of cadastral value in the Russian Federation opens up new opportunities for analyzing and forecasting market prices, since cadastral databases contain the most complete lists of real estate objects, including the cadastral value, which now, in accordance with the law, must be updated at least once every three years and, as of 2015 and 2018, was determined as the market value, therefore, until the next cadastral assessment, can serve as a basis for constant comparison with market data, which are constantly changing, primarily in the composition of objects.

scholarly journals The cadastral value as a tool for monitoring the real estate market value

2021 ◽  
Vol 37 (1) ◽  
pp. 84-108
Author(s):  
Lyudmila Gadasina ◽  
◽  
Mikhail Laskin ◽  
Ekaterina Zaytseva ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Market Value ◽  
Real Estate Market ◽  
Theory And Practice ◽  
Two Dimensional ◽  
Market Prices ◽  
Market Data ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market

In the theory and practice of real estate valuation, in analytical studies of the dynamics of real estate markets there is a problem of tracking changes in market prices. The apparent simplicity of this task leads to the fact that in everyday practice both market participants and professional analysts are satisfied with observations of average prices. The advantage of this traditional approach is computational simplicity. However, in the conditions of presence of a large number of special software and extensive statistical material can be used more complex research methods. The purpose of this article is to research big current market data of real estate objects and compare these data with the cadastral value determined in accordance with Russian legislation as the market value at the specified date. In this regard, there are problems associated with the multidimensional distribution of market prices and cadastral values. The article presents the method of calculation of changes of the real estate market prices on the basis of comparison of two-dimensional prices distributions of offers and cadastral prices for two periods. The main problem in studying the dynamics of real estate market prices is the inability to track the change in market prices for each property, as objects are constantly put up for sale and removed from it. The work carried out in the Russian Federation in 2014 to establish the cadastral value of real estate opens opportunity to analyze two-dimensional distributions of current market and cadastral prices and to assess the dynamic characteristics of the market for any real estate objects. The main result of article is the method which allows to apprise the market value of real estate in real time when new market data come by their comparison with the previously established cadastral value. Cadastral value is assumed to be defined as market value at the valuation date.

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 MACRO DYNAMICS OF THE REAL ESTATE MARKET VALUE: TEMPORAL EFFECTS

2020 ◽  
Vol 1 (13) ◽  
pp. 119
Author(s):  
Tomas Skripkiūnas ◽  
Valentinas Navickas
Keyword(s):  
Real Estate ◽  
Market Value ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Temporal Effects ◽  
The Real Estate Market

Real Estate Valuation Fraud

2015 ◽  
pp. 278-291
Keyword(s):  
Real Estate ◽  
Market Value ◽  
Real Estate Market ◽  
Personal Gain ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Valuation ◽  
The Real Estate Market ◽  
Real Market

Valuation profession is a link between the borrower and the lender. Fraud is an intentional deliberate deception committed for illegitimate personal gain. There are several forms of real estate fraud, especially when the real estate market is facing a boom. The most widespread types of real estate fraud include the preparation of two sets of settlement statements, property flipping, and fraudulent qualifications. There are mainly three types of valuation to look out for. Valuation may be received from an unauthorized agency. Furthermore, a real valuation may be altered from the original to generate profit. Thirdly, intentional inflation of the value of a property will hide the real market value. It is usually difficult to spot real estate fraudulent activities, so deep investigations and professionalism is needed. This chapter explores real estate fraud.

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.

scholarly journals MICROECONOMICS OF ARCHITECTURE: BETWEEN MARKET AND PUBLIC

2020 ◽  
Vol Vol. 36 (No. 2) ◽  
pp. 85-90
Author(s):  
Valentinas Navickas ◽  
Tomas Skripkiunas
Keyword(s):  
Literature Review ◽  
Real Estate ◽  
Public Goods ◽  
Market Value ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Nonmarket Goods ◽  
The Real Estate Market ◽  
Different Types

The position of architecture between market goods and public goods is addressed in this study. A transition of architectural objects of built environment from market goods towards public or nonmarket goods is presented in literature review. The real estate market value is highly influenced by concepts of externalities and public goods, therefore being highly spatially dependent and making the process of the real estate valuation more complex. The internalization of these externalities and public goods is impossible because of the nature of public space in the city. The concept of value and different types of value, like exchange, use, image, social, environmental, cultural value, are also presented in literature review. These different types of value are transferred to value in exchange when estimating market value. The aim of research is to calculate the amount of the real estate market value that is influenced by externalities, public or nonmarket goods. The process of value transfers between market and public is also discussed in this study. In the research part prices of similar apartments measure the coefficient of variance. Newly constructed apartment buildings with partial finishing interior within city boundaries are selected expecting their price to vary only because of different amount of externalities and public goods available inside district/region of selected building or provided by the actual building itself. The results show that up to 29% of the real estate market value is influenced by public or nonmarket goods. Implications of further research suggest controlling for market segmentation and architectural quality variables

scholarly journals Possible Focus Areas of Government Regulation of the Real Estate Market

2018 ◽  
Vol 28 (3) ◽  
pp. 508-516 ◽  
Author(s):  
Boris Bedin
Keyword(s):  
Real Estate ◽  
Government Regulation ◽  
Real Estate Market ◽  
The State ◽  
Residential Real Estate ◽  
The Real ◽  
The Real Estate ◽  
Meaningful Participation ◽  
The Real Estate Market ◽  
The Government

The housing problem is relevant for many countries, including Russia. The solution of this problem is impossible without active and meaningful participation by the state. The residential real estate market has specific characteristics that significantly distinguish it from other markets. The article highlights the features of the residential real estate market as an object of government regulation. The author describes specific features of the government as a subject of management of the residential real estate market, substantiates rationale for the active participation of the state in the management of the real estate market, and outlines possible directions of government regulation of the residential real estate market. The author also describes the Russian experience of implementing certain measures in the framework of direct and indirect forms of government regulation of the residential real estate market as well as the results of such events.

scholarly journals Listing of Developer Companies as a Predictor of the Situation on the Residential Real Estate Market

2018 ◽  
Vol 26 (4) ◽  
pp. 12-21
Author(s):  
Rafal Wolski
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Housing Market ◽  
Stock Exchange ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Secondary Housing Market

Abstract The stock exchange is considered one of the most important financial institutions in the market economy. The stock market reacts to the state of the economy almost immediately, and, in the end, the quotations of companies affect the state of other markets. The author decided to look at companies from the WIG Real Estate index as important entities shaping the real estate market. When comparing the situation on the capital market with the situation on the residential real estate market, one could, building an appropriate model, conclude how much these markets interact. Purpose - The purpose of the article is to present the links between two important markets, the capital market, with real estate companies as its representatives, and the secondary housing market. In order to achieve the goal, a research hypothesis was formulated: the economic situation on the real estate companies market will be reflected in the situation on the secondary housing market. Design/methodology/approach - Cross-sectional regression analysis was used in the study. Using the data from the Warsaw Stock Exchange and the National Bank of Poland, regression models where price changes in the secondary housing market are explained by the quotations of real estate companies and selected stock exchange indices were built. The study was carried out from the first quarter of 2011 to the third quarter of 2017. Findings - Two models were built in which the rates of return on investments in real estate companies explain the price changes in the secondary housing market in a statistically significant way. Thus, the research hypothesis was positively verified, showing that the real estate market and the stock market of real estate companies are interrelated. Originality/Value - The alternative method of analyzing the real estate market can be considered as the original value of the presented results. A demonstration of the connections between both markets allows us to validate the methods used on the stock market to analyze the real estate market. An example application is the use of methods for estimating the cost of capital from the stock market in the real estate market.

scholarly journals The Application of Japanese Candlestick Charting on the Residential Real Estate Market

2015 ◽  
Vol 22 (4) ◽  
pp. 27-34 ◽  
Author(s):  
Anna Gdakowicz
Keyword(s):  
Real Estate ◽  
Capital Market ◽  
Stock Exchange ◽  
Technical Analysis ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Capital Market

Abstract The real estate market is regarded as a part of the capital market. Just as they invest in securities, investors allocate their funds in real estate, hoping to make a sound profit. There are many tools that support the process of investing on the stock exchange, such as a technical analysis. There are also proven methods that help predict future prices of assets on the basis of their historic quotations. The article is an attempt to transfer the Japanese method of candlestick charting used in the technical analysis of securities onto the real estate market. The method has been implemented on the residential real estate market due to the relatively large number of transactions being concluded there.

scholarly journals Assessment of the Real Estate Market Value in the European Market by Artificial Neural Networks Application

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jasmina Ćetković ◽  
Slobodan Lakić ◽  
Marijana Lazarevska ◽  
Miloš Žarković ◽  
Saša Vujošević ◽  
...  
Keyword(s):  
Real Estate ◽  
Input Data ◽  
Market Value ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Price Forecast ◽  
The Real Estate Market ◽  
Artificial Neural ◽  
The Impact

Using an artificial neural network, it is possible with the precision of the input data to show the dependence of the property price from variable inputs. It is meant to make a forecast that can be used for different purposes (accounting, sales, etc.), but also for the feasibility of building objects, as the sales price forecast is calculated. The aim of the research was to construct a prognostic model of the real estate market value in the EU countries depending on the impact of macroeconomic indicators. The available input data demonstrates that macroeconomic variables influence determination of real estate prices. The authors sought to obtain correct output data which show prices forecast in the real estate markets of the observed countries.

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