Using Value-at-Risk to Estimate Downside Residential Market Risk

Jin, Changha; Ziobrowski, Alan J.

doi:10.1080/10835547.2011.12091309

Cited by 13 publications

(5 citation statements)

References 15 publications

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“…Recognising the advancement of GARCH-processes in the mainstream finance literature, Miles (2011b) used a C-GARCH model and found that it is a superior GARCH model compared with various GARCH models. Several studies have also used a GARCH-family model to examine the downside risk of US housing market (Jin and Ziobrowski, 2011) and the volatility linkages among 14 US metropolitan housing markets (Miao et al , 2011). Importantly, Miao et al (2011) asserted that both returns and volatility contain different sets of information.…”

Section: Literature Reviewmentioning

confidence: 99%

An examination of the risk-return relation in the Australian housing market

Lee

2017

IJHMA

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Purpose Extensive studies have investigated the relation between risk and return in the stock and major asset markets, whereas little studies have been done for housing, particularly the Australian housing market. This study aims to determine the relationship between housing risk and housing return in Australia. Design/methodology/approach The analysis of this study involves two stages. The first stage is to estimate the presence of volatility clustering effects. Thereafter, the relation between risk and return in the Australian housing market is assessed by using a component generalised autoregressive conditional heteroscedasticity-in-mean (C-CARCH-M) model. Findings The empirical results show that there is a strong positive risk-return relationship in all Australian housing markets. Specifically, comparable results are also evident in all housing markets in various Australian capital cities, reflecting that Australian home buyers, in general, are risk reverse and require a premium for higher risk level. This could be attributed the unique characteristics of the Australian housing market. In addition, there is evidence to suggest that a stronger volatility clustering effect than previously documented in the daily case. Practical implications The findings enable more informed and practical investment decision-making regarding the relation between housing return and housing risk. Originality/value This paper is the first study to offer empirical evidence of the risk-return relationship in the Australian housing market. Besides, this is the first housing price volatility study that utilizes daily data.

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Section: Literature Reviewmentioning

confidence: 99%

An examination of the risk-return relation in the Australian housing market

Lee

2017

IJHMA

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“…In some places also, bad omen are often associated to repossess properties which makes their resale extremely difficult unless they are highly discounted (DiPasquale, 1999;Boelhouwer and Van Weesep, 1988) Besides the credit or (re)payment risk associated with owner-occupation, the other risk is property price risk which others also referred to as equity price risk or simply asset risk. In the financial literature, asset risk is normally used in relation to the volatility or variation of the asset price over time (Crouhy et al, 2006;Crouhy, 2010;Jin and Ziobrowski, 2011). In the context of housing research, it is mostly restricted to the risk inherent in the decrease of the property price.…”

Section: Consequences Of Default In Repayment Of Mortgagementioning

confidence: 99%

“…However, it is well-known that this measure accounts only for the variations in the house price distribution from the average and does not necessarily capture the downside risk, which would be preferable. Jin and Ziobrowski (2011), proposed using the value-at-risk (VaR) instead of the standard deviation. This measure is a downside risk metric that indicates the worst-case loss on a portfolio held over a short period of time, given a certain confidence level (Crouhy et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Diffusion and Risks of House Prices in the Netherlands

Teye

2018

Architecture and the Built Environment

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The rate of home-ownership has increased significantly in many countries over the past decades. One motivating factor for this increase has been the creation of wealth through the accumulation of housing equity, which also forms the basic tenet of the asset-based welfare system. In generating the home equity, house price developments play an important role. Generally, house prices show an increasing trend over long time period, however, there are short-term negative appreciations that may have inherent risks for the housing equity. Following the 2007-08 Global Financial Crisis (GFC), for example, the collapse of house prices has caused many recent home buyers to run into negative equity. Some housing researchers and experts have suggested that a better understanding of the spatial diffusion mechanisms of house prices will aid resuscitating the housing market after the GFC. Others also advocated adopting insurance schemes to protect the home equity that yields the welfare benefits. Unfortunately, however, little research insight exists on the Dutch house price diffusion process, although there are empirical results for countries such as the UK, US and China, where the contexts differ from the Netherlands. Furthermore, the current existing home-value insurance scheme in the literature is found to be less efficient and eliminates only up to 50% of the house price risks. This dissertation covers important aspects of house price diffusion and risks in the Netherlands. The aim is to better understand the diffusion mechanism and the risks of house prices, while it also contributes to the measurement of these housing risks. More specifically, there are three objectives: first, to discover the diffusion mechanism of house prices in the Netherlands and the pattern particularly from the capital Amsterdam; second, to examine the spatial distribution of the house price risk; and third, to investigate the efficiency of the index-based home-value insurance for reducing the house price risk in the Dutch context. The diffusion mechanism relates to the so-called ripple or spillover effect, for which movements of house prices in one location temporarily or permanently spread over their influence to other regions. The risks analyses capture the probability of selling the residential property below the purchase price. The index-based home-value insurance scheme is concerned with the reduction of the house price risk, while its efficiency and loss coverage are analysed. The contributions of the dissertation are specifically elaborated in five chapters. The chapters are self-contained, four of them having been published separately in international journals and the other being currently under review. Chapter 2 is a literature study that presents the general trend and an overview of the risks in home-ownership. It particularly discusses the government mortgage guarantee and tax deduction, among other factors, which contribute to home-ownership in the Netherlands. Mortgage default risk and house price risk, which are the two important risks from the perspective of the home-owners are also discussed in the context of the Dutch market. Chapter 3 investigates the house price diffusion mechanism between the twelve provinces in the Netherlands. The methodology adopts a new Bayesian graphical approach which enables a data-driven identification of the important regions where the diffusion may predominantly emerge. Using quarterly house price indexes, the findings suggest that house price diffusion exists in the Netherlands with a pattern varying over the period of time. Focusing specifically on the period prior to the 2007-2008 Global Financial Crisis (GFC), the house price diffusion predominantly originated from Noord-Holland. House prices in Amsterdam – the capital and an important economic hub of the Netherlands, are more likely to diffuse to other parts of the country. Thus in Chapter 4, attention is paid to the house price diffusion pattern from the capital Amsterdam to the other Dutch regional housing markets. The Granger causality and cointegration techniques are used, while controlling for the important house price fundamentals. The results suggest a possible house price diffusion existing from Amsterdam to all regions in the Netherlands except for Zeeland. The strongest long-run impact of Amsterdam house price diffusion potentially occur in Utrecht. As one of the largest and most dynamic in the Netherlands, the Amsterdam housing market is itself an interesting case study. One part of Chapter 5, therefore, deals with the diffusion pattern by studying the spatial interrelationships between house prices in Amsterdam. The other part of the chapter studies the house price risks. Using the Granger causality test, a general causal flow of house prices is observed from the central business districts to the peripherals. Simple statistics similarly reveal that house prices grow faster and are more risky in the central business districts than those on the peripherals of the city. Chapter 6 is concerned with the efficiency and loss coverage of the index-based home-value insurance scheme. It proposes a modification of the index-based home-value insurances policy, which seeks to reduce the large idiosyncratic residual house price risks. The modification uses aggregate measures of the reference index. Using the hedonic and repeated sales indexes, the empirical analysis suggests the proposed modified scheme is highly efficient and may eliminate up to 70% of the residual risks. In general, the dissertation adopts innovative empirical methodological approach that combines standard statistical analyses and more recent and complex econometric modelling techniques in the study of the diffusion and risks of house prices in the Netherlands. The application of the graphical approach to the study of diffusions particularly in Chapter 3, is the first of its kind in the context of the housing market. Furthermore, this dissertation is among the first to entirely provide a comprehensive analysis and the much needed body of knowledge regarding the house price diffusion and risks for the highly regulated Dutch housing market. The results have important policy implications and applications for households, commercial investors and financial institutions in the Netherlands. The results may also generally apply and replicable in other countries and economies with similar housing market conditions.

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“…Besides the credit or (re)payment risk associated with owner-occupation, the other risk is property price risk which others also referred to as equity price risk or simply asset risk. In the financial literature, asset risk is normally used in relation to the volatility or variation of the asset price over time (Crouhy et al , 2006; Crouhy, 2010; Jin and Ziobrowski, 2011). In the context of housing research, it is mostly restricted to the risk inherent in the decrease of the property price.…”

Section: General Overview Of Risk In Homeownershipmentioning

confidence: 99%

Risks in homeownership: a perspective on The Netherlands

Teye

Haan

Elsinga

et al. 2017

IJHMA

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Purpose The purpose of this paper is to explore the risk factors in homeowners from the individual household’s perspectives within the owner-occupied housing sector of The Netherlands. Risk in home ownership from mortgage providers’ perspectives has received tremendous attention than individual home owner’s perspectives in existing literature following the financial crisis in 2007/2008 within the euro zone. Design/methodology/approach The paper adopted a broader review of extent literature on the different concepts and views on risk in homeownership. These concepts are unified into a framework that enhances our understanding of the perceived sophisticated risk in owner-occupier with focus on The Netherlands. Findings From the perspective of the homeowner, two main types of risks were identified: default payment and property price risk. The paper has unearthed a quantum number of factors which underline the above risks. These factors relate to the initial amount of mortgage loan taken out, the future housing expenses and the income development of the owner-occupier. Family disintegration is identified, as one of the main causes of mortgage default and that of property price risk are mainly influenced by income levels, interest rates and conditions in the social and private rental sectors. Research limitations/implications Findings of the paper are based on review of the extant literature in the context of the Dutch housing market. Possible rigorous situational analysis using other tools are recommended for further research. Originality/value This paper contributes to the much needed body of knowledge in the owner-occupied sector and provides a better understanding of risk in home ownership from the individual perspectives.

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Using Value-at-Risk to Estimate Downside Residential Market Risk

Cited by 13 publications

References 15 publications

An examination of the risk-return relation in the Australian housing market

An examination of the risk-return relation in the Australian housing market

Diffusion and Risks of House Prices in the Netherlands

Risks in homeownership: a perspective on The Netherlands

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