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This paper aims to examine the effects of investor sentiment on the development of the real estate corporate bond market in Vietnam.

The research uses an autoregressive distributed lag (ARDL) model with quarterly data. Additionally, the study employs Google Trends search data (GVSI) related to topics such as “Real Estate” and “Corporate Bond” to construct a sentiment index.

The empirical outcomes reveal that real estate market sentiment improves the growth of the real estate corporate bond market, while stock market sentiment reduces it. Also, there is evidence of a long-run negative effect of corporate bond market sentiment on the total value of real estate bond issuance. Further empirical research evidences the short-term effect of sentiment and economic factors on corporate bond development in the real estate industry.

Due to difficulties in collecting data, this paper has the limited sample of 54 valid quarterly observations. Moreover, the sentiment index based on Google search volume data only reflects the interest level of investors, not their attitudes.

These results yield important implications for policymakers in respect of strengthening the corporate bond market platform and maintaining stability in macroeconomic and monetary policies in order to promote efficient and sustainable market development.

The study offers some suggestions for regulators and governments to improve the real estate corporate bond market.

This is the first quantitative study to examine the effect of sentiment factors on real estate corporate bond development in Vietnam.

Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently.

The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020.

The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility.

This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets.

This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.

Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.

The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.

The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.

This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.

This study attempts to find the response of the real estate market to economic changes by identifying cause-effect relationships between mortgage, residential investment, and Saudi employment.

A quantitative approach to analytically examine the relationship among the variables. To find out the impact of investment, mortgage and Saudi employment on the Saudi real estate growth from 1970 to 2019. All data sets were obtained from the General Authority for Statistics (GAST), Saudi Central Bank (SAMA) and World Bank Group.

This study reveals a positive relationship between the mortgage and GDP in the Saudi Arabian real estate market. The same results for employment and investment; both have a positive effect on the GDP of the real estate market.

Analyzing the impact of real estate financing on various industries and the extent to which it is related to employment and unemployment rates is essential for future research. Moreover, this research can be applied to different countries and compared based on similarities and differences in implementing mortgage-related policies.

The government must encourage investment in various ways and establish a stable structure that ensures market stability and finds a balance between supply and demand.

This study reflects the importance of real estate financing not only to individuals and governments but also to investors and business workers, and it is essential to analyze the impact of real estate financing on various industries, as well as the extent to which it is related to employment and unemployment rates. This research can be applied to different countries and compared based on similarities and differences in the implementation of mortgage-related policies.

This study contributes to testing this study’s hypothesis: that mortgage positively impacts the real estate market of Saudi Arabia.

The real estate markets may be significantly influenced by the uncertainty in global economic policy. This paper aims to evaluate the time-varying connectedness between global economic policy uncertainty and regional real estate markets to understand how regional real estate markets and uncertainty in global economic policy are related throughout time.

The current study includes the monthly data from April 2007 to August 2022 of major regions (i.e. Asia Pacific, Europe, Africa, North America and Latin America). Moreover, the authors use the time-varying parameter vector auto-regression (TVP-VAR) approach for the analysis.

The finding revealed a significant level of connectedness among global economic policy uncertainty and selected regional real estate markets. The result highlights more than 80% connectivity between the two variables, which makes the current study valuable. Furthermore, results determine Africa and North America are the shock transmitters; thus, they are considered safe-haven for investors to invest in these markets.

The main novelty is that this research highlights the time-varying connectedness between global economic policy uncertainty and five regional real estate markets (Africa, Asian Pacific, Europe, Latin America and North America) using TVP-VAR. Furthermore, the authors used the standard and poor daily real estate investment trust (REIT) indices for the selected REIT markets. Finally, this research suggests practical implications for real estate investors, property developers, stakeholders, policymakers and managers to revise their current policies to maintain the real estate market stability during economic and political uncertainty or in other uncertain situations.

Geopolitical risks (GPR) and increase in equity market volatility due to health pandemics have great implications on assets prices around the world. Many empirical studies have focused on the effects of these risks on different financial assets. The purpose of this paper is to contribute to this related literature by examining the dynamic effects of GPRs and infectious diseases–induced equity market volatility on regional and global house price indexes.

This paper explores the asymmetric effects of infectious diseases and GPRs on house prices across different market conditions using the quantile regression approach. This technique enables us to examine the nonlinear asymmetric effects of GPRs and infectious diseases on both global and regional house price indexes using daily data from January 1, 2011, to June 3, 2022. It focuses on both the effects of a composite measure of GPR as well as the disaggregated effects of threats and acts (war) on the real estate markets under different market conditions.

The main findings of this study demonstrates that the effects of geopolitical and infectious diseases–related risks vary differently across regional real estate markets and the nature of the GPR. In particular, the effects of geopolitical threats are stronger than those of geopolitical acts, especially for the European, Asia-Pacific and North American regions during bullish market periods. Except for the effects of geopolitical threats during real estate market downturns, the African real estate market appears to be insulated from the effects of GPRs across all market conditions. Also, the authors show that infectious diseases increase losses in real estate investments when the market condition is bearish for all markets and could extend toward the normal market period for the North American, Asia-Pacific and European markets. However, across all the market conditions, the effects of the composite index of GPRs are not significant for the Asia-Pacific and European regional markets. Results are mixed for the remaining markets, especially for the global market. Whereas during bearish market periods, the effect is positive, it becomes negative when the market condition become normal and insignificant when it becomes bullish. For the North American and African regional markets, the effect is positive under the bearish market state.

Increase in equity market volatility due to infectious diseases as well as conflicts and tensions among major powers, including potential risks of financial instability, all lead to significant increase in shocks to financial markets. To the best of the authors’ knowledge, this is the first study to analyze the asymmetric and comparative effects of GPRs and infectious diseases–related equity market volatility on real estate investments across different regions and market conditions. Because of the complexity of these risks and policy shifts, and the characteristics and heterogeneity of different regional financial markets, the impacts of shock from these risks are intuitively diverse, with practical implications for portfolio management.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

The aim of this Real Estate Insight is to comment upon commercial real estate research. Much of the current research on commercial real estate sits in academic silos, constrained by disciplinary boundaries and rejecting insights from other areas. This can lead to an impoverished understanding of the processes and practices that drive market behaviour.

This Real Estate Insight, through the lens of history, draws on insights from a century earlier and, in particular, from the work of Frank Ramsey; the paper argues that market behaviour is shaped by the role of key actors and persistent beliefs which need to be accounted for in our models of market practice.

The paper argues that current research paradigms need to accommodate agency explicitly into existing models and that real estate research will benefit immensely if researcher were more open in seeking ideas from outside the real estate field and to be more open to external ideas and concepts.

The paper suggests that property research needs to be more embracing of other academic disciplines to develop a full understanding of the numerous and various drivers within commercial real estate markets.

This is a review of how beliefs impact upon commercial real estate markets. As with many things, history can help researchers today get a broader and more appropriate perspective on market drivers and how they affect decision-making.

The article aims to analyze the behavior of commercial real estate prices in Europe, with a focus on the post-coronavirus disease 2019 (COVID-19) pandemic period. The authors use national and city-level data for the various commercial real estate sectors in ten countries, as well as listed real estate data, to assess any differences across property type and space.

The authors analyze the behavior of commercial real estate prices after the COVID-19 pandemic, emphasizing differences across property types. For that purpose, the authors use national and city-level direct real estate data for the ten largest countries in terms of market capitalization, as well as listed real estate data. The article then turns to discussing the likely trajectory of commercial real estate prices in the future.

The recent rise in interest rates and geopolitical instability have affected prices differently across sectors. Industrial properties benefited from the pandemic, although prices declined significantly in 2022. Residential properties continued their upward price trend and have been the best-performing property type during the last two decades. Retail real estate continued its downward price trajectory. Thus far, office markets do not appear to be significantly affected by structural changes in the sector. The data for listed real estate markets in Europe suggest that markets bottomed out in early 2023.

This paper provides for a better understanding of the behavior of commercial real estate prices in Europe since the COVID-19 pandemic. The authors assess whether the effects found during the COVID-19 crisis were temporary or long-lasting. Also, many economic and political uncertainties have emerged since the beginning of the Ukraine war in February 2022, and it is important to analyze the effects of such uncertainties on commercial real estate prices.

To investigate whether additional information of the permanent news flow, especially reporting intensity, can help to increase transparency in housing markets, this study aims to examine the relationship between news coverage or news sentiment and residential real estate prices in Germany at a regional level.

Using methods in the field of natural language processing, in particular word embeddings and dictionary-based sentiment analyses, the authors derive five different sentiment measures from almost 320,000 news articles of two professional German real estate news providers. These sentiment indicators are used as covariates in a first difference fixed effects regression to investigate the relationship between news coverage or news sentiment and residential real estate prices.

The empirical results suggest that the ascertained news-based indicators have a significant positive relationship with residential real estate prices. It appears that the combination of news coverage and news sentiment proves to be a reliable indicator. Furthermore, the extracted sentiment measures lead residential real estate prices up to two quarters. Finally, the explanatory power increases when regressing on prices for condominiums compared with houses, implying that the indicators may rather reflect investor sentiment.

To the best of the authors’ knowledge, this is the first paper to extract both the news coverage and news sentiment from real estate-related news for regional German housing markets. The approach presented in this study to quantify additional qualitative data from texts is replicable and can be applied to many further research areas on real estate topics.