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The purpose of this study, the nonlinear relationship between the real estate market and the stock market was investigated in Iran. For this intent, the monthly data from 2012:4 to 2022:5 is used.

In this study, the quantile-on-quantile estimation method is used, which is a combination of the nonparametric estimation methods and the quantile regression.

The research results show that, in the low quantiles, the effect of stock market return on the housing market return is negative or zero. In fact, in this situation, the increasing returns in the stock market will shift part of the financial resources of the economy to the market and create stagnation or even negative returns in the housing market. This situation is seen more strongly in some other quantiles, including the 0.25 and 0.75 quantiles; in contrast, the effect of high quantiles of stock market returns is positive on the housing market.

It seems that the demand in the housing market increase in a situation where the returns of the stock market are growing, and the market is in a bullish condition, and this causes an increase in the price and returns in this market. In addition, the results show that the effect of stock market returns on capital market returns is asymmetric and nonlinear.

This paper aims to examine the housing market responses to two outbreaks of respiratory diseases in Hong Kong during the Information Era – the 2003 SARS and COVID-19 outbreaks.

The authors first investigate the aggregate housing price changes during SARS and COVID-19. Next, the authors conduct a battery of univariate analyses pertaining to the relationship between district-level housing price movements and geographic and demographic patterns during the pandemic periods. Finally, to shed light on the housing price dynamics at the micro level, the authors conduct an estate-level analysis with the data of 234 residential estates from 2003 to 2020, focusing on the impacts of SARS and COVID-19 on the idiosyncratic volatility of residential estates.

Overall, SARS and COVID-19 outbreaks are negatively associated with housing prices. However, unlike SARS, the impact of COVID-19 on housing prices was moderate and transient. The geographic imbalances of the epidemic-induced underperformance are observed at the district and estate levels. Finally, the estate-level analysis presented in this paper indicates that the average idiosyncratic volatility of residential estates is 1.5% higher during the SARS period but 3.7% lower during the COVID-19 period. Lower volatility during COVID-19 is likely explained by household learning from the SARS period.

Regulators and investors could resort to efficient information disclosure to attenuate idiosyncratic volatility's adverse impact on housing market returns.

To the best of the authors’ knowledge, the authors are among the first to examine housing market responses to the 2003 SARS and COVID-19 outbreaks using the Hong Kong housing market as a laboratory.

Market sentiment has shown to influence housing prices in the global north, but in emerging economies, the nexus is rare to chance on in the current state of science for policy direction. More importantly in the recent decade where policymakers are yet to conclude on the myriad of factors confronting the housing market in sub-Saharan Africa inhibiting affordability. This paper therefore examines the impact of market sentiment on house prices in South Africa.

The study used the Autoregressive Distributed Lag (ARDL) approach with quarterly data spanning from 2005Q1 to 2020Q4.

In all, it was established that market sentiment plays a minimal role in the property market in South Africa. But there was enough evidence of cointegration from the bound test between sentiment and house prices. Nevertheless, the lag values of sentiment pointed to a rise in house prices. Exchange rate volatilities and inflation had a statistically significant effect on prices in both the long and short term, respectively.

Policymakers could still monitor market sentiment in the housing market due to the strong chemistry between house prices and sentiment, as evidenced from the bound test, but focus on economic fundamentals as the main policy tool for house price reduction.

The findings and the creation of the sentiment index make an invaluable contribution to the paper and add to the paucity of literature on the study of market sentiment in the housing market.

India is one of those countries that are severely affected by the COVID-19 pandemic. With the upsurge in the cases, the country recorded high unemployment rates, economic uncertainties and slugging growth rates. This adversely affected the real estate sector in India. As the relation of the housing market with the gross domestic product is quite lasting thus, the decline in housing prices has severely impacted the economic growth of the nation. Hence, the purpose of this paper is to gauge the asymmetric impact of COVID-19 shocks on housing prices in India.

Studies revealed the symmetric impact of macroeconomic variables, and contingencies on housing prices dominate the literature. However, the assumption of linearity fails to apprehend the asymmetric dynamics of the housing sector. Thus, the author uses a nonlinear autoregressive distributed lag model to address this limitation and test the existence of short- and long-run asymmetry.

The findings revealed the long- and short-run asymmetric impact of the COVID-19 outbreak and the peak of the COVID-19 on housing prices. The results indicate that the peak of COVID-19 had a greater impact on housing prices in comparison to the outbreak of COVID-19. This can be explained as prices will revert to normal at a speed of 0.978% with the decline in the number of COVID-19 cases. Whereas the housing prices rise at a rate of 0.714 as a result of government intervention to deal with the ill effects of the COVID-19 outbreak. Moreover, it can be inferred that both the outbreak and peak of COVID-19 will lead to a minimal decline in housing prices, while with the decline in the number of cases and reduction in the impact of the outbreak of COVID, the housing prices will rise at an increasing rate.

To the best of the authors’ knowledge, this is the first study to understand the impact of the outbreak and peak of COVID-19 on the housing prices separately.

This study aims to address the critical need for innovative financing solutions in the global housing sector, focusing specifically on Malaysia’s distinct housing finance system encompassing both conventional and Islamic loans. The primary objective is to develop a transformative housing finance model that addresses affordability challenges and reshapes the Malaysian housing landscape.

The study presents an alternate housing finance model for Malaysia, integrating lower monthly payments and reduced household debt. Key variables include house price appreciation rates, interest rates, initial guarantee fees and loan-to-value ratios. Inspired by the Help to Buy (HTB) scheme, the model aligns with proven global initiatives for enhanced affordability, balancing payment amounts, loan interest rates and acceptable price thresholds.

The study’s findings promise to address affordability disparities and reshape Malaysia’s housing finance landscape. The emphasis is on introducing a structured repayment plan that offers a sustainable path to homeownership, particularly for low-income families. Incorporating the future value adaptation concept, inspired by reverse mortgages and Islamic finance, enhances adaptability, ensuring long-term sustainability despite economic shifts.

The proposed model promotes widespread access to homeownership, offering practical solutions for policymakers to improve affordability, prompting adaptable risk management strategies for financial institutions and empowering potential homebuyers with increased flexibility.

The study introduces a transformative housing finance model for Malaysia, merging elements from reverse mortgages, Islamic finance and the HTB scheme, offering potential applicability to similar systems globally.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

The learning outcomes of this study are as follows: identify key elements of luxury branding in the context of a new residential real estate brand; select target segment/s and outline the sales pitch for a luxury residential real estate brand; plot the pre-sales stage of the customer journey path (CJP) for a luxury residential real estate brand; and plan a pre-sales customer engagement strategy for a luxury residential real estate brand.

This case enumerates Aldeola de Siolim, Goa’s (ASG) pre-sales promotional challenges. ASG was an upcoming luxury residential property in Goa, India. Venky Infar – the developer of ASG – a family-owned civil construction firm – wanted to diversify into Goa’s vibrant luxury housing market. In India’s housing market, the success of a project often depends on the “pre-sales,” i.e. attracting target customers and maximizing the sales before the construction. V. Rama Rao, the project manager’s task, was challenging because ASG and Venky were new entrants in a mature and competitive market. However, Rao was determined to capture a slice of this lucrative market. The case discusses the following four points to help the students understand the marketing challenges and decision context. First, ASG’s key attractions, second, overview of the Indian real estate market, third, characteristics of Goa’s luxury home market and finally, Customer Journey Path for residential real estate purchase. The case elaborates on the nuances of strategic dilemmas and and presents competitors' practices and emerging consumer trends.

The case will help students analyze and formulate a pre-sales promotional plan for a luxury real estate product. It is suitable for marketing elective courses, e.g. branding, sales management and luxury management.

Teaching notes are available for educators only.

CSS 8: Marketing

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.

In this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.

This paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.

The inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.

Protection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.

Inflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.

The originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.