Real Estate Market Value Research Articles

Impact of Covid-19 on sectoral stock prices: An event study based on US stock market

The impact of COVID-19 on stock prices of different United States economic sectors is examined using event study methodology. Results revealed that the first confirmed case in US on January 21, 2020 was underestimated by investors and did not disturb stock prices significantly. However, the first local transmission case on February 26, 2020 hit the stock market in the post event window. Due to this event, the stock prices of industries in energy, financials, industrials, real estate and utilities sectors declined but observed price increases in health care, information technology and telecom services industries. First “stay at home” order issued by California State in USA on March 19, 2020, a form of lockdown which restricted public gathering, reduced the market value of consumer staples, health care, industrials, real estate and utilities sectors. This order brought positive changes in stock prices of energy, consumer discretionary, financials, information technology and telecom services sectors. Results of the study can help portfolio managers and investors in the process of asset selection and risk minimization during these types of pandemics. On the other hand, these findings can assist policy makers in designing strategies in advance for financial stability as well as minimizing the negative consequences resulting from COVID-19 related potential health crises in future.

The Application of Regression Analysis for Estimating the Market Value of Commercial Real Estate

The transaction price of a land property with commercial buildings depends on both its quantitative and qualitative attributes. Quantitative attributes include surface areas of plots of land and usable floor spaces of premises and buildings with various intended purposes, as well as values of rents. Qualitative attributes are represented by the global attributes of these properties.In the analysis of the land property market with commercial buildings, all pairs that relate a transaction price to individual attributes are considered. The market value prediction is based on multiple regression analysis for a two-dimensional random variable, represented by the price and the predetermined attribute. The final market value of the property being valued is calculated as the weighted average of the market values predicted for each attribute.This research paper presents the procedure for determining the market value of land with commercial buildings, which falls within the method of statistical analysis of the market. The derived formulas and substantively justified algorithms may be the basis for market analysis and estimation of the market value of such land. This procedure has been thoroughly verified using two practical numerical examples.

The Problem of Ensuring Representative Samples when Modeling the Market Value in the Regional Real Estate Market

The article describes the problem of the lack of a universal adequate method for achieving the representativeness of a sample of real estate objects when modeling their market value.The purpose of the work is to develop a methodology for creating a representative sample of real estate objects. This method can be used by specialists when working with inactive real estate markets in small cities and settlements. On the example of the market of land plots for individual housing in several cities of the Krasnodar krai, the analysis of the features of ensuring representativeness is carried out. There are opportunities and limitations of various tools for forming a representative sample.Materials and methods. When preparing the paper, the author studied the experience of forming representative samples accumulated by Russian and foreign scientists, considered in detail theoretical and practical approaches to analyzing the quality of the general set of market real estate objects. The methodology proposed in the article was tested on the example of the real estate market of the cities of Krasnodar, Goryachy Klyuch, Armavir. Тhe author used cartographic data, information from specialized portals of the real estate market and from the unified state register of rights. To achieve the objective, theoretical methods (comparative analysis, synthesis, generalization, analogy) and modelling were used.The main result of the paper is a reasonable method of radial circles, which allows you to select high-quality objects in a sample. Such land plots according to a certain significant price-forming factor in the city under consideration structurally correspond to the plots registered in the unified state real estate register. It is important to establish the conditions under which the sample becomes representative of the pricing factor associated with the location of the object. Тhe analytical material, stages and methods of selecting units in the sample presented in the article are of interest for the real estate researchers, analysts and experts, practitioners of state budgetary institutions engaged in state cadastral valuation.Conclusion. The method of radial circles can be further developed and used for other price-forming factors when modeling the market value of real estate.

Пріоритетні напрями діяльності органів місцевого самоврядування в контексті підвищення ефективності оцінки майна територіальних громад

Abstract. Introduction. The property management system in general, and the land use system in particular, in Ukraine, are currently undergoing a process of change. The development of a market system of relations promotes the establishment of cooperation between public authorities and territorial communities, and the sphere of community property management is one of the most promising areas for the development of this cooperation. However, the achievement of significant positive effects in the development of this area is possible only if some property management tools are improved - and also is the mechanism of property assessment of territorial communities. Purpose. It has been given the state of development of the mechanism of assessment of state property, the purpose of this article is to study the priority areas of local government in the context of improving the effectiveness of assessment. Results. In the process of analyzing the current situation in the field of municipal property management, based on the work of V. Alekseev, the author concludes that there are significant problems in the control of state property, which needs to take a number of steps, including increasing the frequency of use and evaluation property. A detailed analysis of a number of basic concepts of the real estate management process at the local level are the purpose, main goals, objectives of management. The various aspects and characteristics of real estate that affect its value are considered. Based on the preliminary data, the main activities of local governments in the context of improving the efficiency of property assessment of territorial communities have been identified. The mechanism of property valuation for calculating the rental rate and market value of real estate and their importance in the context of improving the property management system is analyzed. A number of recommendations are given to local communities to improve the property management system through the use of property valuation. Conclusions. The process of property valuation in today's community property management system is imperfect and requires a number of changes to improve its efficiency. Achieving results in this matter is possible only if the interaction between the state and society through compromise.

Predicting real estate market trends and value using pre-processing and sentiment text mining analysis

Ubiquitous growth in the text mining field is unprecedented, where social media mining is playing a significant role. Gigantic growth of text mining is becoming a potential source of crowd wisdom extraction and analysis especially in terms of text pre-processing and sentiment analysis. The analysis of a potential influence of sentiment on real estate markets controversially discussed by scholars of finance, valuation and market efficiency supporters. Therefore, it’s a significant task of current research purview which not only provide an appropriate platform for the contributors but also for active real estate market information seekers. Text mining has gained the widespread attention of real estate market information users which is almost on explosion level. Accessibility of data on such behemoth scale mandates regular and critical analysis of this information for various perspectives’ plausibility. Rich patterns of online social text can be exploited to extract the relevant real estate information effectively. As text mining plays a significant and crucial role in discovery of these insights therefore its challenges and contribution in social media analysis must be explored extensively. In this paper, we provide a brief about the current summary of the modern state of text mining in pre-processing and sentiment for the real estate market analysis. Empha-sis is placed on the resources and learning mechanism available to real estate researchers and practitioners, as well as the major text mining tasks of interest to the community. Thus, the main aim of this chapter is to expound and intellectualize the domains of social media which are accessible on an extraordinary range in the field of text mining real estate for predicting real estate market trends and value.

Features of determining the market value of retail real estate and individual trade related properties during pre-trial evaluation and forensic examination

The present article deals with the specifics of valuation of retail property and individual trade related properties on the basis of the international experience and as recommended by International Valuation Standards and RICS (The Royal Institution of Chartered Surveyors (Great Britain)) valuation standards (Red Book). The present article is justified as currently Russia lacks a standard, uniform for the valuers or legal experts, to be used for the purposes of valuation of similar subjects. At the same time, methodical literature is insufficient while there are numerous property disputes that call for pre-court valuations and expert evidence of valuation of such subjects, including numerous litigations arising out of bankruptcy or establishing cadaster value to the amount of market value. The author reviews the existing approaches to valuation of real estate in accordance with both the international and national standards and awards professional recommendations pertaining to the use of the income approach to value retail real properties and individual trade related properties. The definitions and metrics of the above real properties’ groups are described separately. Also, the author provides guidelines for inquiry of the documents and information necessary for the acquisition of the data to be used in the course of valuation and expert evidence. All pricing factors are described in detail in the present article against the examples of retail real properties and individual trade related properties (say, hotel) and explanation of their effect on the market value in case the income approach is applied is provided.

Effects of staining agents on an ornamental granite

Natural stone is quite popular and is commonly used in building interiors, for its aesthetic appeal and for its performance, durability and environmentally-friendly composition. Natural stone also adds considerably to the real estate market value of houses. Different types of natural stone, including granite, can be used in interior design. The stones are thus exposed to staining and are affected differently depending on the staining agent involved. The European standard UNE-EN 16301:2014 defines a procedure for determining the sensitivity of ornamental stones to accidental staining. However, a more detailed study of the physical and chemical effects of such staining agents on stones is required. Adapting this standard, nine different stains (red wine, olive oil, instant coffee, ketchup, cola, citric acid, artificial urine, lime juice and blueberry juice) were applied to a granite commonly used in the Iberian Peninsula. The granite had a polished finish, and three cycles of staining-cleaning (with an anionic detergent) were applied. In the standard evaluation, a qualitative score is awarded on a text-based scale, by external evaluators. In this study, a more complex physical, chemical and texture evaluation of the granite surfaces was carried out to determine the sensitivity of the granite to accidental staining. Colour, roughness, hydrophobicity, gloss and texture were considered key parameters for evaluating the sensitivity of the granite to accidental staining.The sensitivity of the granite to staining clearly depended on the characteristics of the staining agents. In terms of aesthetic properties, all stains except lime juice caused significant colour changes on the granite surface. None of the stains, except red wine, caused important changes in surface gloss. The staining agents, particularly ketchup, blueberry juice and citric acid increased the wettability of the granite surface, thus further enhancing the absorption of aqueous solutions. Olive oil residues were not completely removed from stone surfaces after the cleaning process and therefore caused an increase in the static contact angle, although the stained granite surfaces remained hydrophilic. Citric acid solution caused a chemical interaction with quartz grains, highlighted by the formation of etch pits.

Managing Innovation: The Role of Collateral

Using exogenous variations in the market value of corporate real estate, this paper investigates whether appreciation of corporate collateral value facilitates innovation. My baseline finding shows that real estate appreciation leads to an increase in innovation quantity as measured by patent productions and in innovation quality as measured by citations per patent, especially when firms are credit constrained. To uncover the underlying channel, I show that real estate appreciation allows additional secured borrowing, which enables firms to increase their innovative investments including internal research and development (R&D), the acquisition of innovative target firms, and corporate venture capital (CVC). Moreover, following real estate appreciation, firms change the trajectory of innovation, as reflected in the patent-filing industries and in the characteristics of acquisitions and CVC investment deals. Finally, I provide evidence that firms that innovate more in response to real estate appreciation tend to have better future financial health and accounting profitability.

Managing innovation: The role of collateral

Using exogenous variations in the market value of corporate real estate, this paper investigates whether appreciation of corporate collateral value facilitates innovation. My baseline finding shows that real estate appreciation leads to an increase in innovation quantity as measured by patent productions and in innovation quality as measured by citations per patent, especially when firms are credit constrained. To uncover the underlying channel, I show that real estate appreciation allows additional secured borrowing, which enables firms to increase their innovative investments including internal research and development (R&D), the acquisition of innovative target firms, and corporate venture capital (CVC). Moreover, following real estate appreciation, firms change the trajectory of innovation, as reflected in the patent-filing industries and in the characteristics of acquisitions and CVC investment deals. Finally, I provide evidence that firms that innovate more in response to real estate appreciation tend to have better future financial health and accounting profitability.

The Complex Neural Network Model for Mass Appraisal and Scenario Forecasting of the Urban Real Estate Market Value That Adapts Itself to Space and Time

In the modern scientific literature, there are many reports about the successful application of neural network technologies for solving complex applied problems, in particular, for modeling the urban real estate market. There are neural network models that can perform mass assessment of real estate objects taking into account their construction and operational characteristics. However, these models are static because they do not take into account the changing economic situation over time. Therefore, they quickly become outdated and need frequent updates. In addition, if they are designed for a specific city, they are not suitable for other cities. On the other hand, there are several dynamic models taking into account the overall state of the economy and designed to predict and study the overall price situation in real estate markets. Such dynamic models are not intended for mass real estate appraisals. The aim of this article is to develop a methodology and create a complex model that has the properties of both static and dynamic models. Moreover, our comprehensive model should be suitable for evaluating real estate in many cities at once. This aim is achieved since our model is based on a neural network trained on examples considering both construction and operational characteristics, as well as geographical and environmental characteristics, along with time-changing macroeconomic parameters that describe the economic state of a specific region, country, and the world. A set of examples for training and testing the neural network were formed on the basis of statistical data of real estate markets in a number of Russian cities for the period from 2006 to 2020. Thus, many examples included the data relating to the periods of the economic calm for Russia, along with the periods of crisis, recovery, and growth of the Russian and global economy. Due to this, the model remains relevant with the changes of the international economic situation and it takes into account the specifics of regions. The model proved to be suitable for solving the following tasks: industrial economic analysis, company strategic and operational management, analytical and consulting support of investment, and construction activities of professional market participants. The model can also be used by government agencies authorized to conduct public cadastral assessment for calculating property taxes.

Individual property tax to fund public transport

Efficient and reliable public transport is of prime concern to city dwellers. To function efficiently, public transport generally needs subsidies from the state or local government. Our goal was to design and develop an alternative model of property tax that would provide financing for public transport. It was hypothesised that if the market value of real estate depends on the proximity of public transport, property tax can be a reliable source of financing for public transport. Based on the hedonic pricing theory, we used multiple regression to measure the impact of public transport proximity on the value of residential property. The data on the market value of property and property tax was taken from statistical tax reporting forms of the Federal Tax Service. The data on various public transport infrastructure facilities was used from the specialized open registers. We tested our alternative model of property tax, using the case of the Ekaterinburg Metro and the Tram and Trolleybus Company, through regression analysis of 7,685 objects of residential property in the City of Ekaterinburg. It was found that the efficiency of the underground service is higher than that of the city’s tram network. On the average, the proximity of underground stations increases the value of housing by over 6%. As predictive estimation of the amount of tax determined by the proximity of public transport showed, the alternative model of property tax is sufficient to cover capital expenditures of the city’s public transport operators and could, therefore, contribute to further expansion and modernization of the transport network.

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

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.

The influence of architecture on real estate market value: A methodological framework

The influence of architecture on real estate market value: A methodological framework

MICROECONOMICS OF ARCHITECTURE: BETWEEN MARKET AND PUBLIC

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

RESEARCH OF THE MARKET OF MINI APARTMENT

The purpose of the article is to investigate the development of a new segment of the real estate market in urban development projects. The definition of a mini apartment - the gostinka. The analysis of the world market of mini-apartments is carried out. There are questions of living of different social groups in society in mini-apartments. A classification of mini-apartments has been developed. Factors significantly affect the cost of a mini-apartment. Conclusions are made about the future market of mini-apartments in the city economy The development of the market of mini-apartments can be considered as a new social phenomenon. Many social groups have access to the purchase of a mini-apartment. The residential real estate market is in a difficult stage now. The economic crisis has had a strong impact on stakeholders. The market of mini-apartments in Ukraine is a new and currently unexplored social phenomenon. The market of mini-apartments is of great importance for urban development and has high uncertainty in further development. Therefore, the development of the market of mini-apartments poses many problems for urban development in the future Today in Ukraine in the real estate market of Kharkiv increased activity in such a segment of real estate as mini-apartments. The results of the research show that the cost range of 1 sq.m. for such objects is very large and ranges from 300 to 1000 US dollars. Which is 2 times lower than the average market prices for typical apartments. Let's analyze the primary and secondary markets of mini-apartments. The houses in which the mini-apartments are located can be characterized. Mini-apartments in reconstructed houses are of great interest to stakeholders. Here they are much lower than their cost. Mini-apartments are now actively bought by the following social groups and categories of people. Mini-apartments in reconstructed houses are of great interest to stakeholders. Here they are much lower than their cost. The classification of mini-apartments was carried out according to the parameters that significantly affect the prices in the studied segment. They can increase or decrease the market value of such real estate. The price is significantly affected by such a parameter as the ratio of total and living space. The author proposes factors that affect the cost of mini-apartments. Thus, in Ukraine, the market of mini-apartments (hotels) arose and developed due to the unstable economic situation, the devaluation of the hryvnia and declining incomes. Today, renting apartments is expensive, so mini-apartments are the best option for affordable housing. Many people buy mini-apartments as temporary housing. This segment of real estate has a fairly high profitability for investors. The cost of 1 sq m of mini apartments depends on the investment attractiveness of the regional center. Market research and excellent characteristics of mini-apartments. In large cities of Ukraine, especially in Kyiv and Kharkiv, the number of mini-apartments under construction is growing. The analysis of the market showed that such apartments are in demand among stakeholders today. Factors increasing demand for mini-apartments. Conclusions. 1. The researched market of small-sized housing can be considered as a new social phenomenon in large cities of Ukraine. The question of a new segment of the real estate market in urban development projects is highly relevant 2. In Ukraine, the market of mini-apartments (hotels) has emerged and is developing due to the unstable economic situation, the devaluation of the hryvnia and declining incomes. The cost of 1 square meter of mini-apartments depends on the investment attractiveness of the regional center. 3. The whole market of mini-apartments (hotels) in large cities of Ukraine is actively developing. In Kharkov, in most cases, buy small apartments for further rent. Keywords: real estate market, mini apartment, gostinka, studio, classification of mini apartments, social groups in society, factors influencing the value, municipal economy.

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

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.

Economic landslide susceptibility under a\xa0socio-economic perspective: an application to Umbria Region (Central Italy)

An accurate understanding of physical and socio-economic effects of landslides is fundamental to develop more refined risk management, mitigation strategies and land use policies. In this paper we develop a measure to consider the interconnection between physical and economic exposure, i.e. what we call the economic landslide susceptibility, namely the probability of landslide occurrence in an area weighted for its socio-economic exposure considering the real-estate market values. The economic landslide susceptibility is estimated through a method designed for large areas that we applied to the Umbria Region (Central Italy). The method makes use of landslide susceptibility maps and a real estate market value map for any given area under analysis. The innovative concept of economic landslide susceptibility (that is de facto an ex ante landslide cost assessment) may be interpreted as the potential loss that an area might suffer in terms of its propensity for landslides. Useful applications of the proposed method lie in a better territorial management and in the land use planning.

An agent-based model for community flood adaptation under uncertain sea-level rise

Adaptation has become the major approach to reduce the adverse effects of storm surge and sea-level rise. However, maladaptation can happen when adaptation actions unintentionally increase community vulnerability. To evaluate the adequacy and efficacy of adaptation policies under uncertain sea-level rise, this study presents an agent-based model by integrating the random nature of storm surges, private adaptation decisions, and real estate market valuation. We evaluated the evolving flood damage of different adaptation strategies under two bounding cases of real estate market change. Our model results quantitatively illustrate the accelerating damages of storm surges under climate-induced sea-level rise. A reform in flood insurance to risk-based rates with a means-tested voucher program and a government-subsidized “twice and out” buyout program could both substantially improve coastal resilience. However, community adaptation with a public seawall may deliver false risk perception to high-risk property owners and result in maladaptation when sea-level rise rate is high. The modeling approach developed in this study can be used as a policy analysis tool to measure the impacts of sea-level rise and the effectiveness of adaptation strategies in coastal communities.

An Attempt to Determine the Impact of Energy Intensity on the Market Value of Residential Units on the Example of Selected Buildings in Szczecin

Abstract Environmental requirements, constantly increasing energy prices as well as energy consumption by residential units and buildings have become an important factor in the decision-making processes in the real estate market. The preferences of residential unit buyers who recognize the problem of energy intensity and translate it into the transaction price have also been changing. However, amendments to the Act on real estate management and new European standards have imposed an obligation to include the certificates of energy performance of buildings and premises on real estate valuers in the valuation process. In this paper, energy intensity understood as the heating requirements of multi-family residential buildings is the basis for assessing the impact of the proposed variants on the market value of residential units. The paper analyzes the energy intensity of various types of buildings (e.g. in low and high buildings) and its impact on the market value of residential units in a selected housing estate in Szczecin, when the property valuer has access to energy performance certificates of neither the unit under valuation nor the units selected for comparison. The purpose of this study is to identify the relationship between the energy intensity and the market value of residential units. The proposed three models of real estate market value: non-classical, multiple regression and average price adjustment taking into account energy intensity, obtain results consistent with the actual transaction price at a satisfactory level. The assessment was made using standard deviation, a coefficient of variation and the average error of forecasts.

Evaluation of real estate market value in Ukraine using web-scraping

Ринкова цінність є одним з важливіших видів інформації для кожного виду бізнесу – як для стартапів на етапі планування, так і для вже вирощеного бізнесу. Це дозволяє робити точніші прогнози доходів на етапі фінансового планування, а отже, інвестиційні рішення. У деяких випадках ідентифікація ринкової вартості може бути тривіальним завданням, коли ми маємо справу з відкритою організованою інформацією, але здебільшого, оцінювання цього параметра є надскладним завданням, яке займає багато часу і вимагає залучення експертів різних сфер. Певні обмеження виникають, якщо оцінюється вартість неліквідних активів, таких, як активи на ринках нерухомості. Розглянуто підхід до оцінювання ринкової вартості ринку нерухомості або його капіталізації за допомогою підходу агрегування та структурування даних із веб-джерел на основі веб-скрейпінгу із використанням мови програмування Python. Webcrawler – це вдосконалене програмне забезпечення, штучний інтелект, що переміщується по веб-сайтах, переходить по посиланнях для пошуку та вилучення даних за допомогою конкретних правил. Загальна ринкова вартість згідно з інформацією, представленою на ria.ua, приблизно дорівнює на певну дату 10,9 мільярда доларів. Оцінювання показує концентрацію ринку в основному у Києві, за винятком комерційної нерухомості, заміських будинків, готелів, земель та складських приміщень. Водночас Київ є безперечним лідером у сфері офісних комплексів, паркування, рекреаційного відпочинку. Лідерами із продажу квартир є Київ та Одеська область, інші регіони значно відстають від цих міст. На основі аналізу зроблено висновок, що ціна сильно корелює з типом нерухомості та меншою мірою корелює з регіоном продажу.