Real estate prices and stock market in Germany: analysis based on hedonic price index

2019 ◽  
Vol 12 (4) ◽  
pp. 687-707 ◽  
Author(s):  
Korhan Gokmenoglu ◽  
Siamand Hesami
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Stock Prices ◽  
Price Index ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Content Type ◽  
Long Run ◽  
Real Estate Prices ◽  
The Relationship

PurposeReal estate and stocks are two major asset types in an investor’s portfolio. Therefore, this paper aims to investigate the relationship between these two markets to provide a valuable insight into the process of portfolio optimization and security selection.Design/methodology/approachThis study examines the long-run relationship between residential real estate prices and stock market index in the case of Germany for the period of 2005-2017 by applying time series econometrics techniques. To this aim, this study uses Hedonic House Price Index as a proxy for real estate prices and DAX30 as a proxy for stock prices. Moreover, three additional variables, namely, consumer confidence, credit availability and supply of mortgage loans, are incorporated as control variables to assess the robustness of the results.FindingsObtained empirical results indicate a long-run relationship between stock prices and real estate prices which suggests that in long-run, there is no diversification benefit from allocating stock and real estate assets in a portfolio. This finding is especially important for long-term investors such as pension funds.Originality/valueTo the authors’ best knowledge, this is the first study that empirically investigates the relationship between the real estate market and stock prices using the Hedonic Price Index for the case of Germany.

Integration between real estate and stock markets: new evidence from Pakistan

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imran Yousaf ◽  
Shoaib Ali
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Stock Markets ◽  
Content Type ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Long Run ◽  
Short Run ◽  
The Relationship

Purpose This study aims to empirically examine the relationship between real estate and stock market of Pakistan. Design/methodology/approach The data of two real estate indices (house price index and plot price index) are taken for the Pakistan and its four big cities, i.e. Lahore, Karachi, Rawalpindi and Islamabad. It estimates the integration between series by applying the Johansen cointegration test. Moreover, the vector error correction model is applied to examine the short and long-run causal relationships between series. Findings The findings show that the real estate markets are cointegrated with the stock market. They imply that the real estate and stock markets are good substitutes in investment allocation, but investors cannot get the benefit of diversification by making a portfolio of real estate and stock markets in Pakistan. Moreover, the long-run causality is observed from majority house markets to the stock market, whereas short-run causality is evident from majority plot markets to the stock market. Hence, the real estate market leads the stock market in the short run and long run, suggesting the credit-price effect in the majority of real estate markets in Pakistan. These causality results are helpful for investors in the forecasting of real estate and stock markets in Pakistan. Research limitations/implications The limitation of the study is the lower number of observations (107), because house and land prices are only available in monthly frequency from January 2011 in Pakistan. Originality/value To the best of the authors’ knowledge, no researcher has investigated the real estate and stock market nexus in Pakistan. Therefore, this study focuses on examining the relationship between the real estate and stock market of Pakistan. The link between real estate and stock markets will provide useful insights to the portfolio managers, real estate companies, property agents, stockbrokers and investors.

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.

Linkages between cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles

2016 ◽  
Vol 9 (2) ◽  
pp. 123-146 ◽  
Author(s):  
Kim Hiang Liow
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Business Cycles ◽  
Spillover Effects ◽  
Real Estate Market ◽  
Stock Market Index ◽  
Content Type ◽  
Market Index ◽  
Cross Country ◽  
The Cross

Purpose This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014. Design/methodology/approach The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology. Findings There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered. Research limitations/implications The research is subject to the usual limitations concerning empirical research. Practical implications This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors. Originality/value In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Asymmetric impact of exchange rate changes on stock returns: evidence of two de facto regimes

2019 ◽  
Vol 19 (2) ◽  
pp. 147-173
Author(s):  
Walid M.A. Ahmed
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Spillover Effects ◽  
Content Type ◽  
Currency Depreciation ◽  
Long Run ◽  
Exchange Rate Changes

Purpose This study focuses on Egypt’s recent experience with exchange rate policies, examining the existence of spillover effects of exchange rate variations on stock prices across two different de facto regimes and whether these effects, if any, are asymmetric. Design/methodology/approach The empirical analysis is carried out using a nonlinear autoregressive distributed lag modeling framework, which permits testing for the presence of short- and long-run asymmetries. Relevant local and global factors are also included in the analysis as control variables. The authors divide the entire sample into a soft peg period and a free float one. Findings Over the soft peg regime period, both positive and negative changes in EGP/USD exchange rates seem to have a significant impact on stock returns, whether in the short or long run. Short-term asymmetric effects vanish in the free float period, while long-term asymmetries continue to exist. By and large, the authors find that currency depreciation tends to exercise a stronger influence on stock returns than does currency appreciation. Practical implications The results offer important insights for investors, regulators and policymakers. With the domestic currency depreciation having a negative impact on stock prices, investors should contemplate implementing appropriate currency hedging strategies to abate depreciation risks and, hence, preserve their expected rate of return on the Egyptian pound-denominated investments. In the current post-flotation era, the government could pursue a flexible inflation targeting monetary policy framework, with a view to both lowering the soaring inflation toward an announced target rate and stabilizing economic growth. The Central Bank of Egypt (CBE) could adopt indirect monetary policy instruments to secure tightened liquidity conditions. Besides, the CBE could raise policy rates to incentivize people to keep their money in local currency-denominated instruments, instead of dollarizing their savings, thereby relieving banks of foreign currency demand pressures. Nevertheless, while being beneficial to the country’s real economy on several aspects, such contractionary monetary measures may temporarily impinge on stock market performance. Accordingly, policymakers should consider precautionary measures that reduce the potential for price distortions and unnecessary volatility in the stock market. Originality/value To the best of the authors’ knowledge, the current study represents the first attempt to explore the potential impact of exchange rate changes under different regimes on Egypt’s stock market, thus contributing to the relevant research in this area.

Design of Real Estate Price Index System Based on Hedonic Price Method

2014 ◽  
Vol 488-489 ◽  
pp. 1463-1466
Author(s):  
Yun Du ◽  
Hui Qin Sun ◽  
Su Ying Zhang ◽  
Qiang Tian
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Hedonic Price Method ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Price Series ◽  
Research Level

Urban real estate price index (hereinafter referred to as UREPI) is a basic data of the real estate market, its accuracy is very important for enterprises, consumers and housing management department. In view of current research level here in China and popular models, the UREPI system is compiled based on the Hedonic price method because of its advantages such as calculation simple and sample easily etc. Compiled by Eviews the system has three main stages: the data standardization, the benchmark model establishment and the application of two periods chained update method to update price series. UREPI system is combined with the real deal, so it can be used to analysis the market accurately. The results completely meet the design requirements.

Distance in geographic and characteristics space for real estate pricing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Evgeniy M. Ozhegov ◽  
Alina Ozhegova
Keyword(s):  
Real Estate ◽  
Explanatory Power ◽  
Price Transmission ◽  
Hedonic Price ◽  
Content Type ◽  
Geographic Space ◽  
Residential Properties ◽  
Clustering Approach ◽  
Real Estate Prices ◽  
Automated Valuation

PurposeA common approach to predicting the price of residential properties uses the hedonic price model and its spatial extensions. Within the hedonic approach, real estate prices are decomposed into internal characteristics of an apartment, apartment characteristics and external characteristics. To account for the unobserved quality of the surrounding environment, price models include spatial price correlation factors, where the distance is usually measured as the distance in geographic space. In determining the price, a seller focuses not only on the observed and unobserved factors of the apartment and its environment but also on the prices of similar marketed objects that can be selected both by geographic proximity and by characteristics similarity. The purpose of this study is to show the latter point empirically. Design/methodology/approachThis study uses an ensemble clustering approach to measure objects' proximity and test whether the proximity of objects in the property characteristics space along with spatial correlation explain the significant variation in prices. FindingsIn this paper, the pricing behaviour of sellers in a reselling market in Perm, Russia is studied. This study shows that the price transmission mechanism includes both geographic and characteristics spaces. Practical implicationsAfter testing on market data, the proposed framework for the distance construct could be used to obtain higher predictive power for price predictive models and construction of automated valuation services. Originality/valueThis study tests the higher explanatory power of the model that includes both the distance measured in geographic and property characteristics spaces.

Property prices index numbers and derived indices

2014 ◽  
Vol 32 (2) ◽  
pp. 139-153 ◽  
Author(s):  
Francesca Salvo ◽  
Marina Ciuna ◽  
Manuela De Ruggiero
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Real Estate Market ◽  
Index Numbers ◽  
Market Prices ◽  
Sales Price ◽  
Content Type ◽  
Property Prices ◽  
Innovative Methodology ◽  
Definition Of

Purpose – A useful instrument to understand and examine the inner workings of the property trade is devising index numbers of property prices based on historical sequences of market prices. The present work aims at the definition of index numbers of property prices, proposing an innovative methodology compared with what usually recurs in literature. The purpose of this paper is to discuss these issues. Design/methodology/approach – The analysis proposed, based on the mechanisms of formation of stock indices, investigates the analogies between stock and property information, according to the peculiarities of the property trade, leading to a methodology approach, derived from Simple Price Index Method, able to consider possible anomalies in the collected sample of purchase prices, using weighting coefficients based on reliability coefficients of sale prices of properties. Findings – The novel approach proposed has led to the definition of a original methodology useful to appraise property price index numbers and other derived indicators, effective for interpreting and identifying real estate market dynamics in a given area of study, regarded as a standard estimating methodology applicable to any geographical context and kind of property. Practical implications – Methodology proposed in this work is useful to revalue real estate sales price and to consider presence of anomalous sales price in property samples. Originality/value – The calculation of index numbers of prices is usually based on Simple Price Index Methods. Literature shows large use of different methods, such as Repeat Sales Method, Hedonic Price Method, Repeat Value Model. The present work propose an innovative methodology able to detect the presence of possible anomalous market prices in the representative sample, using an appropriate vector of weights in order to take into account the level of reliability of market data.

Sign in / Sign up

Export Citation Format

Share Document