Real estate as a common risk factor in bank stock returns

Carmichæl, Benoı̂t; Coën, Alain

doi:10.1016/j.jbankfin.2018.07.007

Cited by 24 publications

(10 citation statements)

References 26 publications

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“…The same could be said regarding credit availability (loans) and infrastructure. For the first one, the finding was consistent with the outcomes of Ling et al (2016) and inconsistent with Cerutti et al (2017), Bian et al (2018); Carmichael and Coën (2018); Hashmat and Rouillard (2017), Sakr-Tierney (2017); Christopoulos and Barratt (2016), Shen and Yin (2016); Owusu-Manu et al (2015), Wu et al (2015); Onofrei and Anghel (2012). Finally, the results indicated that the value of the coefficient of INFR was, as expected, positive but statistically insignificant and this was inconsistent with the finding reached by Cordera et al (2018).…”

Section: Results Analysis and Discussionmentioning

confidence: 49%

“…Another study conducted by Cerutti et al (2017) examined housing finance and real-estate booms and they found that they were strongly linked. However, this finding varied from one country to another based on the prevailing loan to value ratios (Bian et al, 2018;Carmichael and Coën, 2018;Hashmat and Rouillard, 2017;Sakr-Tierney, 2017;Christopoulos and Barratt, 2016;Shen and Yin, 2016;Owusu-Manu et al, 2015;Wu et al, 2015;Onofrei and Anghel, 2012).…”

Section: Loans Availabilitymentioning

confidence: 99%

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Real estate investors’ behaviour

Abdallah

Al‐Tamimi

Duqi

2021

QRFM

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Purpose This paper aims to investigate perceptions of United Arab Emirates (UAE) real estate investors’ behaviour and the factors that most influence their investment decisions. Design/methodology/approach This study used a modified questionnaire that was divided into two parts. The first part covered demographic and socioeconomic variables. The second part identified 36 factors that affect the perceptions of real estate investors in the UAE regarding their investment decisions. These factors were placed in eight different categories that correspond to non-personal factors such as, profit, market conditions, risk, transparency, credit facilities (loans), infrastructure and services. Findings The findings confirm that there is a significant and positive relationship between three factors; namely, profitability, risk and service quality regarding investments in the real estate sector. The findings also confirm a positive but statistically insignificant relationship between transparency, market conditions, credit facilities, infrastructure and investment in the UAE’s real estate sector. Research limitations/implications The sample size represents one of the limitations of this study. In addition, the gender of the sample is another limitation as, in general, men are more involved in investment than women are. Furthermore, there are no previous studies regarding the behaviour of UAE real estate investors; thus, the findings of this study cannot be directly compared with other empirical studies. Practical implications It might be helpful to create separate units under the name “Real Estate Information Unit” in every municipality of each of the seven emirates. In addition, it is recommended that decision makers should consider ensuring that modern high-quality real estate infrastructure is available to attract more investors. Finally, minimizing any restrictions on access financing facilities may encourage investors to invest more in the UAE real estate sector. Originality/value This study is the first of its kind to be conducted in the context of the behaviour of UAE real estate investors.

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Section: Results Analysis and Discussionmentioning

confidence: 49%

Section: Loans Availabilitymentioning

confidence: 99%

Real estate investors’ behaviour

Abdallah

Al‐Tamimi

Duqi

2021

QRFM

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“…Our empirical context is the Irish residential real estate auction market in what turns out to be approaching the peak of the bubble. Residential real estate markets are an interesting research context to explore, as such markets are particularly prone to anomalous behavior (Scherbina and Schlushe, 2015), and have significant spillover effects into the banking system (Carmichael and Coën, 2018), and the wider economy (Bengtsson, Grothe and Lepers, 2018). We conjecture that in the height-in-bubble phase of such markets bidder decision making is likely to be dominated by feelings of excitement and mania such that conventional measures of financial risk will not impact on pricing outcomes.…”

Section: Resultsmentioning

confidence: 99%

“…In comparison to other asset pricing bubbles, the banking and macroeconomic impact of residential real estate bubbles are particularly damaging to both the banking system and the wider macroeconomy (e.g. Bengtsson, Grothe andLepers, 2018, Carmichael andCoën, 2018). Scherbina and Schlusche (2012) argue that bubbles are pervasive in residential real estate markets as such markets are dominated by financially unsophisticated households who often develop optimistic views by overextrapolating from a time-series of past price movements.…”

Section: Introductionmentioning

confidence: 99%

Emotions, Uncertainty, Gender and Residential Real Estate Prices: Evidence from a Bubble Market

Ryan¹,

Branigan²

2019

26th Annual European Real Estate Society Conference

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This paper investigates the impact of valuation uncertainty on residential property prices near the peak of a bubble. Our hand-collected sample comprises the sequence of bids and gender of the participating bidders at Irish residential real estate auctions, prior to the collapse of a bubble, which when it burst had disastrous implications for the banking system and the economy itself. Portfolios of practitioner-and hedonic pricing model-selected self-similar properties provide benchmark property price estimates and uncertainty is calculated by reference to various measures of dispersion related to prices achieved for comparable properties. We find, in aggregate, auction winners do not shade bids with increased valuation uncertainty. In addition, winning female bidders, in contrast to findings in the extant literature across a wide range of academic disciplines, including experimental bubble markets, are not less risk averse, or more likely to shy away from competitive situations than their male counterparts.

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“…The Basel II International Banking Agreement (Bank for International Settlements, 2006) and the close relationship between the value of real estate and banking stability (Koetter and Poghosyan, 2010) highlighted the need to review the value of mortgaged properties on a frequent basis to accurately measure credit risk (Carmichael and Co€ en, 2018). The regulations of the European Union (European Council, 2006) established the need for an assessment of the portfolio of real estate for commercial use once a year and for residential once every three years, although there are also specific regulations established for each of the member countries.…”

Section: Introductionmentioning

confidence: 99%

A computer-assisted expert algorithm for real estate valuation in Spanish cities

Larraz

Navarro

Cano

et al. 2020

Environment and Planning B: Urban Analytics and City Science

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Some of the most overlooked valuation systems in current literature are those based on expert algorithms. Yet these algorithms can form the basis of a good estimation of the value of real estate since they allow simple computational methods that use big data to be integrated with the appraiser’ own knowledge of the situation. The main usefulness of the methodology is an ongoing mortgage risk appraisal for banking institutions. The current expert algorithms based on the sales comparison approach use the arithmetic mean of the comparable prices. But this mean gives equal importance to all neighbouring dwellings instead of giving more importance to those dwellings which are more similar and are nearer to the target dwelling. Improving the classical arithmetic mean or the more robust median, this article proposes a computer-assisted expert algorithm which includes a weighted estimator able to consider the differences in characteristics compared to similar properties and their relative locations. It allows to estimate, in a simple and rapid way using objective criteria, the value of any residential property in Spain. The results show good fit for large cities in terms of the usual error margins while improving the results with regards to smaller cities. In all cases, in terms of mean absolute percentage error, the weighted estimator improves the arithmetic mean or median results.

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Real estate as a common risk factor in bank stock returns

Cited by 24 publications

References 26 publications

Real estate investors’ behaviour

Real estate investors’ behaviour

Emotions, Uncertainty, Gender and Residential Real Estate Prices: Evidence from a Bubble Market

A computer-assisted expert algorithm for real estate valuation in Spanish cities

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