Real Estate Price Fluctuations Research Articles

РАЗВИТИЕ ИССЛЕДОВАНИЙ В СФЕРЕ РЫНКА НЕДВИЖИМОСТИ

The article analyzes in detail the dynamics and complexity of the real estate market with an emphasis on forecasting methodology and its practical application in an economic context. The main theme is the integration of various forecasting models that predict trends and fluctuations in real estate prices based on a multidisciplinary approach combining economic theory, statistical data and market analysis. First, the basic principles defining the real estate economy, its differences from other sectors in terms of market conditions and consumer behavior patterns are outlined. The importance of location and consumer characteristics in determining the value of the property is emphasized. It is explained how these factors distinguish the real estate market into a separate area of research. The challenges and imperfections of the real estate market, such as lack of competitiveness and inefficiency in comparison with finance, are shown. It is argued that these characteristics require complex predictive models to improve market efficiency and investor decisionmaking. In this context, various statistical and analytical tools that have been improved over the years to improve the accuracy of forecasts in the real estate market are discussed. Theoretical judgments are supplemented by examples and empirical data confirming the effectiveness of models in various economic conditions. The author advocates continuous innovative development and adaptation of forecasting techniques used to analyze the real estate market. The need for a multidisciplinary approach is emphasized, taking into account economic indicators, opinions of market participants and geopolitical factors in forecasts. This comprehensive strategy is presented as key to navigating the complexities of global real estate markets, taking advantage of investment opportunities in an everchanging economic environment.

Research on the Dynamic Impact of Real Estate Price Fluctuations on Systemic Financial Risks in China

Research on the Dynamic Impact of Real Estate Price Fluctuations on Systemic Financial Risks in China

Study On Influencing Factors of Real Estate Price Fluctuation from The Perspective of Behavioral Economics

Study On Influencing Factors of Real Estate Price Fluctuation from The Perspective of Behavioral Economics

Mortgage lending valuation bias under housing price changes and loan-to-value regulations

We examine valuation bias, regulatory loan-to-value limits, and real estate price fluctuations using unique data from two Norwegian banks. We investigate whether automated valuation methods significantly affect foreclosure discounts. Banks using multiple valuation methods tend to report loan-to-value bias by selecting the most optimistic value, underestimating and underreporting risk in declining property markets. This risk increases near regulatory loan-to-value limits, and the findings are robust across homogenous and heterogeneous properties. We recommend reporting automated valuation estimates for all applicable properties and disclosing the percentage of valuations done with different methods to improve transparency and risk comparability between banks.

Analysis of Factors Affecting the Dynamics of Residential Real Estate Prices in Russia

In this paper, we have constructed a VAR model to identify and assess the impact of real interest rate shocks, real estate demand, oil prices, uncertainty, and aggregate business activity on residential real estate prices in Russia. The relevance of the research is due to the following: the dynamics of real estate prices determines the consumer and investment behavior of households, and serious fluctuations in real estate prices lead to adverse consequences in many areas of life, so more and more researchers are asking questions about the presence of bubbles in the real estate market, which can be dangerous to the stability of the economy. In addition, a sharp increase in the cost of housing in Russia in 2020 is an open question for researchers. Our goal is to determine what factors caused the rise in real estate prices in Russia in the time interval from the Q1 of 2000 to the Q2 of 2022. A VAR model with a Cholesky decomposition was used for the evaluation. Several specifications were considered with the inclusion of the real oil price as an exogenous variable and a set of endogenous variables: real GDP, real interest rate, uncertainty index and housing price index. The main conclusion of the paper is that the housing market is sensitive to identified macroeconomic shocks, and a decrease in the interest rate leads to an increase in demand and real estate prices. The estimate of the long-term elasticity of housing prices for oil prices was 0.35, the dynamics of oil prices explained a significant proportion of the variation in real estate prices, but the predominant role in housing price fluctuations is given to housing demand shocks. The housing demand shocks in Russia itself had a negligible impact on GDP.

ANALYSIS OF THE INTERACTION OF REAL ESTATE AND FINANCIAL MARKETS OF THE REPUBLIC OF ARMENIA OVER THE PAST FIVE YEARS

The real estate market is influenced by the development of the real and financial sectors, as supply and demand in this market depend on the state of the economy and the financial system of the country. The vulnerability of financial stability from fluctuations in real estate prices is mainly considered from the point of view of lending to the construction industry and loans secured by real estate, the materialization of risks of changes in the value of collateral. Sharp fluctuations in supply/demand for real estate, and consequently prices, may adversely affect the security and quality of bank loans, creating risks in terms of financial stability. The real estate market is an extremely important economic player. Real estate, in addition to meeting one of the most important needs of society, is one of the main "reserves" of wealth in the economy. Thus, in developing countries, the market value of shared real estate is usually many times higher than the capitalization of financial markets and the volume of investments coming into the country. This is a unique source of economic "energy". The evaluation and analysis of real estate in Armenia, the use of weak analysis methodology, are considered to be the causes of problems in the real estate market with incorrect versions and procedures, the lack of high-quality data on local markets, unreasonable market research and investment decisions based on them.

The Impacts of Land and Real Estate Price Fluctuations on Financial Stability: Evidence from China

AbstractWe construct a provincial financial stability index, and use panel vector autoregression to construct a model for empirical testing. We find that local governments' reliance on land grant premiums amplifies the impact on financial stability. In addition, the relationship between the real estate market and the financial system allows real estate price fluctuations to significantly affect market participants, further impacting financial system stability. Finally, in the eastern region, land price fluctuations have a less adverse impact on financial stability, while in other regions, rising commodity real estate prices are the biggest threat to financial stability.

양도소득세와 취득세 및 주택임대소득세제의 정책방향

Capital gain tax and acquisition tax are representative real estate related taxes of Korea as well as comprehensive real estate tax. In case of capital gain tax, tax-free conditions of one-household-one house cases were re- peatedly strengthened and relieved and acquisition tax rates were increased and decreased depending on real estate price fluctuation. That is, when real estate prices fell, the policy to reduce tax burden of real estate was executed by relieving tax-free conditions of one-household-one house cases or reducing acquisition tax rates and, when real estate prices rose, the policy to increase tax burden of real estate was executed by strengthening tax-free conditions of one-household-one house cases or increasing acquisition tax rates. However, it is questionable whether it was effective to change real estate taxation system depending on real estate price fluctuation and the effect might be negative in most of cases. In such respect, the measures to improve capital gain tax and acquisition tax may be arranged as shown below. First, in case of capital gain tax, it is desirable to increase the standard of a high-price house from KRW 1.2 billion to KRW 1.5 billion. Second, when it would be desirable to define a one-household-one house case based on dwelling period rather than possession period. Third, as special deduction for long-term possession basically intends removal of nominal gain, it is desirable to apply special deduction for long- term possession in case of multi-house holders, too. Fourth, it would be desirable to abrogate heavy tax rates exceeding 50% for short-term holders and multi-house holders. Fifth, it would not be desirable to reduce overall acquisition tax rates. Sixth, it is desirable to maintain current 4% of acquisition tax rate for acquisition of houses with payment and to abrogate high acquisition tax rates for multi-house holders. Seventh, it is required to set consistent taxation benefit in case of house rental income taxation system in order to give predictability and legal stability to registered rental businessmen.

РИЗИКИ ІПОТЕЧНОГО КРЕДИТУВАННЯ ТА ШЛЯХИ ЇХ МІНІМІЗАЦІЇ В УМОВАХ ФІНАНСОВОЇ НЕСАБІЛЬНОСТІ

The article provides the author's definition of the terms "mortgage loan" and "mortgage lending risk". The classification of mortgage lending risks according to risks related mainly to real estate (systemic, non-systematic, random) and risks related to the capital market (banking risks) is given. The definition of each risk highlighted in the author's risk classification of mortgage lending risks is given. The distribution of risks between participants in mortgage relations (creditor, borrower, issuer of mortgage securities, investor) is presented, depending on the one- and two-level model of mortgage lending. The correlation between the level of risks and the cost of credit services is indicated. A detailed analysis of the following risks was carried out: credit risk, market risk, interest rate risk, liquidity risk, currency risk, operational and technological risks, reputational risks and legal risk. Attention is paid to one of the types of credit risk – the risk of early loan repayment, and an example of its minimization is given. It is described how credit risk directly affects the market value and profitability of the mortgage portfolio. The causes of mortgage lending risks are listed and their consequences for all participants in credit relations are listed. The close relationship between the macroeconomic situation in the country and the effectiveness of mortgage lending is substantiated using the example of real estate price fluctuations. The importance of the correct assessment of collateral property when concluding a credit agreement is explained. The experience of the banks of the leading countries of the world and the leading banks of Ukraine in managing mortgage risks is presented. The methods of risk management given in the classification are considered and proposed, and the ways of improving the effectiveness of the mortgage loan are given. The most adequate monthly payment for a mortgage loan is given as a percentage of the borrower's income to ensure his solvency. Possible scenarios of fraud in the field of mortgage lending are given and recommendations for their prevention are given. Real cases of scams from developers of Ukraine in the context of mortgage lending to the population are given.

The Risk Spillover Effects of the Real Estate Industry on the Financial Industry: A GARCH-Time-Varying-Copula-CoVaR Approach on China

This paper analyzes the multiple transmission mechanisms of the real estate industry’s risk spillovers to the financial industry. A GARCH-time-varying-copula-CoVaR model is used to measure the spillover effects and dynamic evolution trends of risk in the Chinese real estate industry. The results show that (1) in recent years, the risk spillovers from the real estate industry to the whole financial industry in China has been relatively high, and the possibility of systemic risks has increased. (2) The channel of the risk spillovers of the real estate industry into the financial industry has shifted from being concentrated within a traditional single banking industry to the accumulation and superposition of risk across the banking, securities, trust industries. (3) Current regulations have not fundamentally mitigated the risk spillovers. As such, this paper proposes three suggestions on financial policies and regulations: firstly, the government should reasonably regulate cooperation between the real estate industry and the financial industry, curb excessive speculation and abnormal fluctuations in real estate prices. Secondly, the government should maintain the continuity of regulatory policies, formulate differentiated policies according to the essential attributes of given industries, and eliminate risk contagion among the real estate industry and financial industries. Thirdly, the government should improve the macro prudential management framework.

Anomalies of the Housing Market in Albania

The real estate sector is one of the most important sectors of the economy for developing countries. The housing market is directly related to the performance of economy. The impact of this market is measured through the volume of various transactions, such as real estate sales, lease contracts, construction contracts, import transactions, foreign exchange, transactions of financial intermediaries and real estate agencies, employment contracts, etc. The real estate market is directly influenced by housing policies, the level of financial system development, visible additional costs (tax rates and credit costs) and its invisible costs (which is informality and information asymmetry). Hypotheses: The housing market operates according the rules of the supply-demand and the factors that affect the fluctuation of housing prices. The purpose of the article is to evaluate the demand factors in the performance of house prices in Albania. Methodology: The study employs an exploratory analysis based on the literature review, the secondary data and empirical analysis. The authors make a comparison between the factors identified by the literature review, the analysis of the secondary data for the Albanian real estate market, and statistical relationships of individual factors as well: GDP/capita, Exchange rate, Interest rates in ALL, Interest rates EURO, Remittances and the level of mortgage loans in EURO. In the conclusions of the paper, some of the factors that have directly influenced the fluctuations in real estate prices in Albania are: the demand and the supply of real estate; the change in the value of the functional currency; state intervention through fiscal policies and urban planning; credit financing to businesses and individuals, etc.

The Effects of Real Estate Price Fluctuations on Household Loans and Business Performance of Savings Banks

The Effects of Real Estate Price Fluctuations on Household Loans and Business Performance of Savings Banks

Financial stability and real estate price fluctuation in China

The relationship between financial stability and the real estate market has received increasing attention. Understanding the interaction between them may monitor financial risk and real estate price fluctuation. This paper aims at examining the cross-correlation between financial stability and real estate price fluctuation in China. A measure of financial stability is constructed and the cross-correlation between financial stability and the real estate market is demonstrated by using detrended cross-correlation analysis (DCCA). Furthermore, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) is used to evaluate the scaling properties of the cross-correlation among financial stability and real estate price fluctuation. Empirical results indicate that asymmetries exist in the cross-correlation and that the asymmetric cross-correlation is multifractal. The cross-correlation is related to the fluctuation magnitude if the financial stress index (or the growth rate in house prices) is in a different trend. Finally, DCCA analysis based on time-delay is employed to investigate transmission direction of the cross-correlation. Our findings indicate the transmission direction is bidirectional, but the impact of financial stability on real estate price fluctuation is larger than the impact in the reverse direction.

Literature Review of the Research on Real Estate Financial Risk

After a brief conceptual explanation and background introduction of real estate finance and its risks, this paper mainly focuses on the relationship between real estate price fluctuation and financial risk, real estate bubble, the formation and transmission of real estate financial risk, and the control of real estate financial risk. Several research categories were classified and related research was reviewed. In the end, it summarizes and puts forward that China’s research on real estate financial risk also has the following problems and development direction: the research on the connotation of real estate financial risk needs to be improved; the research on real estate bubble needs to be quantified; the research on risk formation needs to be deepened from the mechanism; the research on risk transmission needs to be combined with the reality of China; and the empirical research on real estate financial risk needs to be improved.

A Study of the Subjective Expectation Model of Real Estate Price Fluctuation Employing Two-person Game Theory

In the real estate market, the demanding of customers vary as their price expectations change. Conversely, changes in the needs of customers affect the price of real estate. This research proposes a model for expected alterations in real estate prices by analyzing variations using two-person game theory. The research also provides evidence for a psychological quantitative study of customer expectation.

Impact of Urban Economic Openness on Real Estate Prices: Evidence from Thirty-Five Cities in China

Over the past decade, China’s major cities have experienced significant real estate price increase which has been fueled by the sustained growth of the economic fundamentals. It is well believed that deeper integration with the world market is one of the major reasons for such high speed macroeconomic growth. In this paper, we examined the linkage between urban economic openness, the ratio of trade volume as a percentage of GDP, and urban real estate prices basing on quality of life theory as well as Balassa-Samuelson (B-S) effects. Using panel data of 35 large Chinese cities from the year 1998 to 2006, we empirically find that for every 1% increase in urban economic openness, urban real estate prices will increase significantly by 0.282%, after controlling for other traditional demand-supply factors. Urban economic openness alone accounted for about 15.90% appreciations of Chinese real estate prices during the sample period, which is not neglectable. This result implies that urban real estate price fluctuations are potentially affected by international economic factors. The economic distance to the international market could be deemed as productive and consumption amenity for a city as well. This study enriches the perception of quality of life factors, and furthermore provides a new perspective for understanding the real estate price dynamics in the globalized economic development today.

Collateral, Capital Structure, and Debt Structure

This paper tests how collateral value affects a firm's choice between bank debt and public debt by considering the exogenous variation in the market value of a firm's real estate assets caused by fluctuations in local real estate prices. Using local land supply elasticities as an instrument for local real estate prices, I estimate that a one standard deviation increase in collateral value causes bank debt as a fraction of total debt to increase by 6 percentage points.

Real Estate, the External Finance Premium and Business Investment: A Quantitative Dynamic General Equilibrium Analysis

This article studies the connection between the capital market and the real estate market. Empirically, we find that positive real house price shocks lower the external finance premium and stimulate nonresidential investment and real gross domestic product (GDP). Our theoretical framework is able to mimic the volatility of the external finance premium, the relative price of real estate and capital and the investment in real estate and capital. It also captures the cyclicality of the external finance premium and of real estate prices. The contribution of real estate price fluctuations to the variability of the external finance premium and the GDP is confirmed to be significant.

Influence of real estate prices on domestic bank loans in Southeast Asia

This study examines whether and how fluctuations in real estate prices affected bank lending in Malaysia, Singapore, and Thailand before and after the 1997–98 Asian financial crisis. Since the crisis, it has been claimed that the rise and fall in the price of real estate, which is used as collateral, affected bank lending and the macroeconomy in these Southeast Asian countries. The study implements a dynamic model of bank lending and employs a test using the panel data of domestic bank balance sheets in order to estimate the influence of real estate prices on new bank lending in the three countries. The study also examines the conditions surrounding the role of real estate as collateral for bank loans in the countries. The regression results suggest that fluctuations in real estate prices can influence domestic bank lending and did so, especially after the crisis in Singapore and Thailand, and that domestic bank lending behaviour in these countries changed after the crisis.

Excess Liquidity, Housing Price Booms and Policy Challenges in China

AbstractIncorporating asymmetric cost and benefit of supplying excess liquidity into an otherwise standard time inconsistency model, this paper offers an explanation of the excess liquidity and housing price booms recently experienced in China. We find that the central bank's incentive to stimulate economic growth with excess liquidity fuels real estate prices and accelerates inflation bias. Therefore, the central bank should free itself from the pressure to achieve an economic growth rate higher than the potential level, and assign an appropriate weight to the real estate price fluctuations in the central bank's objective function, so that the central bank's policy of stimulating economic growth with excess liquidity can be constrained.