Pub Date : 2023-11-14DOI: 10.1108/jpif-10-2022-0069
Fong-Yao Chen, Michael Y. Mak
Purpose Valuers should independently assess market value. The purpose of this article is to analyze whether the valuation behavior remains independent when commissioned by publicly listed companies in Taiwan. Design/methodology/approach This study used both quantitative and qualitative methods. Quantitative data analysis was used to examine the estimated premium ratio and estimated divergent ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. To complement and validate the quantitative analysis, open-ended questionnaires were conducted, providing additional insights into the research findings. Findings The results showed that there is a significant difference in estimated valuations commissioned by representatives of buyers and sellers, and the estimated premium ratios commissioned by representatives of buyers were higher than those of sellers. Furthermore, the open-ended questionnaires results indicate that these findings may be influenced by clients for less experienced appraisers. However, for senior appraisers, this is seen as an action to gain a better understanding of the valuation purpose and always within a reasonable price range. In addition, client influence is not a static factor; it may transform into the valuer's behavior as the appraiser's experience grows and deepens. Practical implications It is difficult to obtain valuation reports commissioned by representatives of both buyers and sellers for the same property transactions. In this study, data were obtained from the Market Observation Post-System (MOPS) in Taiwan. As valuation reports could not be obtained, estimated valuations and transaction prices are used to calculate estimated premium ratio and estimated divergent ratios. Originality/value Previous investigations of the client effect have been conducted using qualitative methods including questionnaire surveys, in-depth interviews and experimental design. However, these studies are subject to moral hazard. This study may be the first study that has access to data on valuations for both buyers and sellers in such a formal setting.
{"title":"Client influence or the valuer's behavior? An empirical study of listed companies' valuation in Taiwan","authors":"Fong-Yao Chen, Michael Y. Mak","doi":"10.1108/jpif-10-2022-0069","DOIUrl":"https://doi.org/10.1108/jpif-10-2022-0069","url":null,"abstract":"Purpose Valuers should independently assess market value. The purpose of this article is to analyze whether the valuation behavior remains independent when commissioned by publicly listed companies in Taiwan. Design/methodology/approach This study used both quantitative and qualitative methods. Quantitative data analysis was used to examine the estimated premium ratio and estimated divergent ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. To complement and validate the quantitative analysis, open-ended questionnaires were conducted, providing additional insights into the research findings. Findings The results showed that there is a significant difference in estimated valuations commissioned by representatives of buyers and sellers, and the estimated premium ratios commissioned by representatives of buyers were higher than those of sellers. Furthermore, the open-ended questionnaires results indicate that these findings may be influenced by clients for less experienced appraisers. However, for senior appraisers, this is seen as an action to gain a better understanding of the valuation purpose and always within a reasonable price range. In addition, client influence is not a static factor; it may transform into the valuer's behavior as the appraiser's experience grows and deepens. Practical implications It is difficult to obtain valuation reports commissioned by representatives of both buyers and sellers for the same property transactions. In this study, data were obtained from the Market Observation Post-System (MOPS) in Taiwan. As valuation reports could not be obtained, estimated valuations and transaction prices are used to calculate estimated premium ratio and estimated divergent ratios. Originality/value Previous investigations of the client effect have been conducted using qualitative methods including questionnaire surveys, in-depth interviews and experimental design. However, these studies are subject to moral hazard. This study may be the first study that has access to data on valuations for both buyers and sellers in such a formal setting.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"6 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136229275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-10DOI: 10.1108/jpif-05-2023-0048
Guangping Liu, Kexin Zhou, Xiangzheng Sun
Purpose The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises. Design/methodology/approach Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk. Findings The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises. Practical implications It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems. Originality/value Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.
{"title":"The influence mechanism of real estate enterprises' status on debt default risk","authors":"Guangping Liu, Kexin Zhou, Xiangzheng Sun","doi":"10.1108/jpif-05-2023-0048","DOIUrl":"https://doi.org/10.1108/jpif-05-2023-0048","url":null,"abstract":"Purpose The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises. Design/methodology/approach Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk. Findings The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises. Practical implications It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems. Originality/value Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136254893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-10DOI: 10.1108/jpif-06-2023-0051
Visar Hoxha
Purpose The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices. Design/methodology/approach The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al . (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model. Findings The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy. Practical implications The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation. Originality/value Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.
{"title":"Exploring the predictive power of ANN and traditional regression models in real estate pricing: evidence from Prishtina","authors":"Visar Hoxha","doi":"10.1108/jpif-06-2023-0051","DOIUrl":"https://doi.org/10.1108/jpif-06-2023-0051","url":null,"abstract":"Purpose The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices. Design/methodology/approach The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al . (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model. Findings The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy. Practical implications The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation. Originality/value Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136255016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.1108/jpif-08-2023-0076
Larry Wofford
Purpose Starting with the notion that each building has an overall life cycle, the paper uses building-based and investment-based life cycles to identify likely decision points for renovations, including sustainability enhancements, and identifies patterns in sustainability decisions. Design/methodology/approach This real estate insights paper considers how commercial real estate and the built environment it creates, owns and manages impacts the sustainability of urban areas and the globe. By combining building-based and investment-based life cycles, it is possible to develop a unique “sustainability enhancement quotient” for individual buildings and the built environment for an urban area over a given time interval. Findings Using two life cycles allows the identification and likelihood of sustainability decision points. The same life cycles and decision points are used to consider the likely extent of such renovations. This is in addition to continuous consideration of renovations producing economic benefits in the form of lower operating costs and quick return of capital. Research limitations/implications Useful for investment decision-making and policy design and implementation. Practical implications This is a useful tool for public and private decision making. It is suggested that the sustainability enhancement quotient may be used to design and implement policies and decisions maximising the likelihood of sustainability enhancement in an urban area's built environment. Social implications Provides a framework for more effective sustainability decisions and public policy. The public-private interplay inherent in every building is emphasised throughout. Originality/value Original combination of existing tools.
{"title":"Real Estate Insights Back to the basics of sustainability","authors":"Larry Wofford","doi":"10.1108/jpif-08-2023-0076","DOIUrl":"https://doi.org/10.1108/jpif-08-2023-0076","url":null,"abstract":"Purpose Starting with the notion that each building has an overall life cycle, the paper uses building-based and investment-based life cycles to identify likely decision points for renovations, including sustainability enhancements, and identifies patterns in sustainability decisions. Design/methodology/approach This real estate insights paper considers how commercial real estate and the built environment it creates, owns and manages impacts the sustainability of urban areas and the globe. By combining building-based and investment-based life cycles, it is possible to develop a unique “sustainability enhancement quotient” for individual buildings and the built environment for an urban area over a given time interval. Findings Using two life cycles allows the identification and likelihood of sustainability decision points. The same life cycles and decision points are used to consider the likely extent of such renovations. This is in addition to continuous consideration of renovations producing economic benefits in the form of lower operating costs and quick return of capital. Research limitations/implications Useful for investment decision-making and policy design and implementation. Practical implications This is a useful tool for public and private decision making. It is suggested that the sustainability enhancement quotient may be used to design and implement policies and decisions maximising the likelihood of sustainability enhancement in an urban area's built environment. Social implications Provides a framework for more effective sustainability decisions and public policy. The public-private interplay inherent in every building is emphasised throughout. Originality/value Original combination of existing tools.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135477698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.1108/jpif-04-2023-0035
Martin Hoesli, Louis Johner, Jon Lekander
Purpose Using data spanning 145 years for Sweden, the authors investigate the benefits of holding multi-family properties for investors who aim to hedge wage growth. Design/methodology/approach The authors assess the risk-adjusted excess return that results from adding multi-family properties to a mixed-asset portfolio that aims to track wage growth. The authors also analyse the macroeconomic determinants of asset returns. Finally, the authors test whether a causal relationship exists between the growth rate of real wages and that of real net operating income. Findings The benefits from holding multi-family properties are the greatest for low-risk allocation approaches. For more risky strategies, the role of real estate is more muted, and it varies greatly over time. Holding real estate was most beneficial during the first two decades of the 21st century. Multi-family properties are found to be the only asset class to be positively related to wage growth. The authors show that the net operating income acts as the transmission channel between wages and property returns. Practical implications The paper assesses whether the growing interest of pension funds for multi-family properties is warranted in the context of a portfolio that aims to track wage growth. Originality/value Using long term data makes it possible to use a rolling windows approach and hence to consider multiple outcomes for an allocation strategy over a typical investment horizon. This permits to assess the dispersion of performance across several periods rather than just one as is commonly done in the literature. The results show that the conclusions that would be drawn from looking at the past two or three decades of data differ substantially from those for earlier time periods.
{"title":"The role of multi-family properties in hedging pension liability risk: long-run evidence","authors":"Martin Hoesli, Louis Johner, Jon Lekander","doi":"10.1108/jpif-04-2023-0035","DOIUrl":"https://doi.org/10.1108/jpif-04-2023-0035","url":null,"abstract":"Purpose Using data spanning 145 years for Sweden, the authors investigate the benefits of holding multi-family properties for investors who aim to hedge wage growth. Design/methodology/approach The authors assess the risk-adjusted excess return that results from adding multi-family properties to a mixed-asset portfolio that aims to track wage growth. The authors also analyse the macroeconomic determinants of asset returns. Finally, the authors test whether a causal relationship exists between the growth rate of real wages and that of real net operating income. Findings The benefits from holding multi-family properties are the greatest for low-risk allocation approaches. For more risky strategies, the role of real estate is more muted, and it varies greatly over time. Holding real estate was most beneficial during the first two decades of the 21st century. Multi-family properties are found to be the only asset class to be positively related to wage growth. The authors show that the net operating income acts as the transmission channel between wages and property returns. Practical implications The paper assesses whether the growing interest of pension funds for multi-family properties is warranted in the context of a portfolio that aims to track wage growth. Originality/value Using long term data makes it possible to use a rolling windows approach and hence to consider multiple outcomes for an allocation strategy over a typical investment horizon. This permits to assess the dispersion of performance across several periods rather than just one as is commonly done in the literature. The results show that the conclusions that would be drawn from looking at the past two or three decades of data differ substantially from those for earlier time periods.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135491423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/jpif-09-2021-0075
Graeme Newell, Muhammad Jufri Marzuki, Martin Hoesli, Rose Neng Lai
Purpose Opportunity real estate funds are an important style of real estate investing for institutional investors seeking nonlisted real estate exposure. Importantly, institutional investors have sought exposure to the China real estate market, often via opportunity real estate funds. This has been by a pure China opportunity real estate fund (100% China opportunity real estate) or by a pan-Asia opportunity real estate fund where China opportunity real estate was part of this pan-Asia opportunity real estate portfolio. Using two bespoke China opportunity real estate indices developed by the authors, this paper aims to assess the risk-adjusted performance and portfolio diversification benefits of China opportunity real estate in a mixed-asset portfolio over 2008–2020. It also highlights critical issues for institutional investors going forward to factor into their real estate investment decision-making for effective China real estate exposure. Design/methodology/approach This paper develops two bespoke China opportunity real estate fund performance indices to assess the risk-adjusted performance and portfolio diversification benefits of China opportunity real estate funds in a mixed-asset portfolio over 2008–2020. An asset allocation diagram is used to assess the role of China opportunity real estate in a mixed-asset portfolio via both the non-listed and listed real estate investment channels. Findings Over 2008–2020, China opportunity real estate exposure via pan-Asia opportunity real estate funds were seen to outperform pure China opportunity real estate funds. In both formats, China opportunity real estate funds were seen to have a significant role in a China mixed-asset portfolio across most of the portfolio risk spectrum; particularly compared to listed real estate exposure in China. On-going issues regarding real estate risk management in China will take on increased importance for institutional investors seeking China real estate exposure. Practical implications Opportunity real estate funds are an important style of real estate investing, often used by institutional investors to gain non-listed real estate exposure in a developing real estate market. This style of real estate investing has been popular with institutional investors seeking exposure to China real estate as part of the China economic growth dynamic. The results of this research highlight the importance of opportunity real estate investing in China, both via a pure China opportunity real estate fund and via a pan-Asia opportunity real estate fund. Based on this empirical analysis, China opportunity real estate exposure is seen to be more effective via a pan-Asia opportunity real estate fund than a 100% China opportunity real estate fund. A range of practical China real estate investment issues are also highlighted for the effective delivery of China real estate exposure for institutional investors going forward; this particularly relates to the on-going risk management for rea
{"title":"The performance of non-listed opportunity real estate funds in China","authors":"Graeme Newell, Muhammad Jufri Marzuki, Martin Hoesli, Rose Neng Lai","doi":"10.1108/jpif-09-2021-0075","DOIUrl":"https://doi.org/10.1108/jpif-09-2021-0075","url":null,"abstract":"Purpose Opportunity real estate funds are an important style of real estate investing for institutional investors seeking nonlisted real estate exposure. Importantly, institutional investors have sought exposure to the China real estate market, often via opportunity real estate funds. This has been by a pure China opportunity real estate fund (100% China opportunity real estate) or by a pan-Asia opportunity real estate fund where China opportunity real estate was part of this pan-Asia opportunity real estate portfolio. Using two bespoke China opportunity real estate indices developed by the authors, this paper aims to assess the risk-adjusted performance and portfolio diversification benefits of China opportunity real estate in a mixed-asset portfolio over 2008–2020. It also highlights critical issues for institutional investors going forward to factor into their real estate investment decision-making for effective China real estate exposure. Design/methodology/approach This paper develops two bespoke China opportunity real estate fund performance indices to assess the risk-adjusted performance and portfolio diversification benefits of China opportunity real estate funds in a mixed-asset portfolio over 2008–2020. An asset allocation diagram is used to assess the role of China opportunity real estate in a mixed-asset portfolio via both the non-listed and listed real estate investment channels. Findings Over 2008–2020, China opportunity real estate exposure via pan-Asia opportunity real estate funds were seen to outperform pure China opportunity real estate funds. In both formats, China opportunity real estate funds were seen to have a significant role in a China mixed-asset portfolio across most of the portfolio risk spectrum; particularly compared to listed real estate exposure in China. On-going issues regarding real estate risk management in China will take on increased importance for institutional investors seeking China real estate exposure. Practical implications Opportunity real estate funds are an important style of real estate investing, often used by institutional investors to gain non-listed real estate exposure in a developing real estate market. This style of real estate investing has been popular with institutional investors seeking exposure to China real estate as part of the China economic growth dynamic. The results of this research highlight the importance of opportunity real estate investing in China, both via a pure China opportunity real estate fund and via a pan-Asia opportunity real estate fund. Based on this empirical analysis, China opportunity real estate exposure is seen to be more effective via a pan-Asia opportunity real estate fund than a 100% China opportunity real estate fund. A range of practical China real estate investment issues are also highlighted for the effective delivery of China real estate exposure for institutional investors going forward; this particularly relates to the on-going risk management for rea","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135633413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-14DOI: 10.1108/jpif-12-2021-0104
Cay Oertel, E. Kovaleva, Werner Gleißner, S. Bienert
PurposeThe risk management of transitory risk for real assets has gained large interest especially in the past 10 years among researchers as well as market participants. In addition, the recent regulatory tightening in the EU urges financial market participants to disclose sustainability-related financial risk, without providing any methodological guidance. The purpose of the study is the identification and explanation of the methodological limitations in the field of transitory risk modeling and the logic step to advance toward a stochastic approach.Design/methodology/approachThe study reviews the literature on deterministic risk modeling of transitory risk exposure for real estate highlighting the heavy methodological limitations. Based on this, the necessity to model transitory risk stochastically is described. In order to illustrate the stochastic risk modeling of transitory risk, the empirical study uses a Markov Switching Generalized Autoregressive Conditional Heteroskedasticity model to quantify the carbon price risk exposure of real assets.FindingsThe authors find academic as well as regulatory urgency to model sustainability risk stochastically from a conceptual point of view. The own empirical results show the superior goodness of fit of the multiregime Markov Switching Generalized Autoregressive Conditional Heteroskedasticity in comparison to their single regime peer. Lastly, carbon price risk simulations show the increasing exposure across time.Practical implicationsThe practical implication is the motivation of the stochastic modeling of sustainability-related risk factors for real assets to improve the quality of applied risk management for institutional investment managers.Originality/valueThe present study extends the existing literature on sustainability risk for real estate essentially by connecting the transitory risk management of real estate and stochastic risk modeling.
{"title":"Stochastic framework for carbon price risk estimation of real estate: a Markov switching GARCH simulation approach","authors":"Cay Oertel, E. Kovaleva, Werner Gleißner, S. Bienert","doi":"10.1108/jpif-12-2021-0104","DOIUrl":"https://doi.org/10.1108/jpif-12-2021-0104","url":null,"abstract":"PurposeThe risk management of transitory risk for real assets has gained large interest especially in the past 10 years among researchers as well as market participants. In addition, the recent regulatory tightening in the EU urges financial market participants to disclose sustainability-related financial risk, without providing any methodological guidance. The purpose of the study is the identification and explanation of the methodological limitations in the field of transitory risk modeling and the logic step to advance toward a stochastic approach.Design/methodology/approachThe study reviews the literature on deterministic risk modeling of transitory risk exposure for real estate highlighting the heavy methodological limitations. Based on this, the necessity to model transitory risk stochastically is described. In order to illustrate the stochastic risk modeling of transitory risk, the empirical study uses a Markov Switching Generalized Autoregressive Conditional Heteroskedasticity model to quantify the carbon price risk exposure of real assets.FindingsThe authors find academic as well as regulatory urgency to model sustainability risk stochastically from a conceptual point of view. The own empirical results show the superior goodness of fit of the multiregime Markov Switching Generalized Autoregressive Conditional Heteroskedasticity in comparison to their single regime peer. Lastly, carbon price risk simulations show the increasing exposure across time.Practical implicationsThe practical implication is the motivation of the stochastic modeling of sustainability-related risk factors for real assets to improve the quality of applied risk management for institutional investment managers.Originality/valueThe present study extends the existing literature on sustainability risk for real estate essentially by connecting the transitory risk management of real estate and stochastic risk modeling.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44195293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-09DOI: 10.1108/jpif-11-2021-0090
L. Cradduck, G. Warren-Myers
Purpose This research seeks to understand the potential impact to investors from government responses to climate change risk, as reflected in changes to planning processes made after significant weather events.Design/methodology/approach The research examines the land planning responses within a select local government authority (“LGA”) area following four significant weather events, in order to identify any changes made, and the impact on future development proposals. The LGA selected is the Central Coast Council, which is a coastal LGA in the Australian State of New South Wales. The research engaged with the publicly accessible records available on the Central Coast Council, Australian Bureau of Meteorology and other websites; and extant literature.Findings The research reveals that some adjustments were made by the Central Coast Council, and or the State government, to relevant laws, policies and processes following these events. These changes, however, tended to focus on imposing additional requirements on future development applications, rather than on requiring changes to current structures, or prohibiting further development works.Research limitations/implications The research has three limitations: (1) land law in Australia varies, as each State and Territory, and LGA, has specific laws, policies and processes; (2) as laws and policies are subject to change, it was necessary to select points in time at which to engage with those laws and processes; and (3) COVID-19's impact on domestic Australian travel [the authors could not travel interstate] meant only documents available on the Internet were considered, however, not all documents relating to development; or changes to laws and processes were easily accessible online. As the research focussed on one case study area, this may limit the applicability of the results to other areas. However, as extreme events are international, the related issues are a concern in all areas.Practical implications This research confirms the results of other extant research, which observed that some risks cannot be properly mitigated, such that any development in an at-risk area remains at risk. It also identifies that more current, accurate and publicly accessible data are required to enable investors to more easily and accurately identify all risks affecting a property.Originality/value The research provides a snapshot of one LGA's response to the physical risks arising from climate change events. As investors and other organisations integrate and build up their analysis of climate risks to their portfolios and organisations, governments become more aware of the long-term effects of climate change and consistently with extant research; this research indicates that a greater awareness is required of current risks and action to manage the short-term effects and cost challenges, in addition to the long-term adaptation requirements.
{"title":"Development in a state of climate change: an Australian case study of government response","authors":"L. Cradduck, G. Warren-Myers","doi":"10.1108/jpif-11-2021-0090","DOIUrl":"https://doi.org/10.1108/jpif-11-2021-0090","url":null,"abstract":"Purpose This research seeks to understand the potential impact to investors from government responses to climate change risk, as reflected in changes to planning processes made after significant weather events.Design/methodology/approach The research examines the land planning responses within a select local government authority (“LGA”) area following four significant weather events, in order to identify any changes made, and the impact on future development proposals. The LGA selected is the Central Coast Council, which is a coastal LGA in the Australian State of New South Wales. The research engaged with the publicly accessible records available on the Central Coast Council, Australian Bureau of Meteorology and other websites; and extant literature.Findings The research reveals that some adjustments were made by the Central Coast Council, and or the State government, to relevant laws, policies and processes following these events. These changes, however, tended to focus on imposing additional requirements on future development applications, rather than on requiring changes to current structures, or prohibiting further development works.Research limitations/implications The research has three limitations: (1) land law in Australia varies, as each State and Territory, and LGA, has specific laws, policies and processes; (2) as laws and policies are subject to change, it was necessary to select points in time at which to engage with those laws and processes; and (3) COVID-19's impact on domestic Australian travel [the authors could not travel interstate] meant only documents available on the Internet were considered, however, not all documents relating to development; or changes to laws and processes were easily accessible online. As the research focussed on one case study area, this may limit the applicability of the results to other areas. However, as extreme events are international, the related issues are a concern in all areas.Practical implications This research confirms the results of other extant research, which observed that some risks cannot be properly mitigated, such that any development in an at-risk area remains at risk. It also identifies that more current, accurate and publicly accessible data are required to enable investors to more easily and accurately identify all risks affecting a property.Originality/value The research provides a snapshot of one LGA's response to the physical risks arising from climate change events. As investors and other organisations integrate and build up their analysis of climate risks to their portfolios and organisations, governments become more aware of the long-term effects of climate change and consistently with extant research; this research indicates that a greater awareness is required of current risks and action to manage the short-term effects and cost challenges, in addition to the long-term adaptation requirements.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49382152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-09DOI: 10.1108/jpif-03-2022-193
N. French
{"title":"Editorial – Property investment – What is it worth?","authors":"N. French","doi":"10.1108/jpif-03-2022-193","DOIUrl":"https://doi.org/10.1108/jpif-03-2022-193","url":null,"abstract":"","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46941305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-02DOI: 10.1108/jpif-08-2021-0068
D. Lo, M. McCord, P. Davis, J. McCord, Martin Haran
PurposeHouse price-to-rent (P-t-R) ratios are among the most widely used measures of housing market conditions. Given the theoretical and apparent bidirectional, causal relationships and imbalances between the housing market, broader economy and financial market determinants, it is important to understand the relationship between macro- and micro-economic characteristics in relation to the P-t-R ratio to enhance the understanding of housing market dynamics. This paper studies the joint dynamics and persistence of house prices and rents and examines the temporal interactions of the P-t-R ratio and economic and financial determinants.Design/methodology/approachThe authors examine the lead–lag relationships between the P-t-R ratios and a spectrum of macroeconomic variables using cointegration and causality methods, initially at the aggregate position and also across housing types within the Northern Ireland housing market to establish whether there are subtle differences in how various housing segments react to changes in economic activity and market fundamentals.FindingsThe findings reveal price switching dynamics and some very distinct long- and short-run relationships between macroeconomic and financial indicators and the P-t-R ratios across the various housing segments. The results exhibit monetary supply, foreign exchange markets and the stock market to be important drivers of the P-t-R ratio, with P-t-R movements seemingly tied, or are in tandem, with the overall economy, particularly with the construction sector.Practical implicationsThe study shows that the P-t-R ratio can be used as an early measure for establishing the effects of macroprudential policy changes and how these may manifest across housing tiers and quality, which can further act as a signal for preventing or at least mitigating future irrational price cyclicity. These insights serve to inform housing and economic policy and macroprudential policy design, principally within lending policy and the effect of regulatory interventions and further enhance the understanding of the P-t-R ratio on housing market structure and dynamics.Originality/valueThis study is the first in the housing literature that examines the causal relationships between the P-t-R ratio and macroeconomic activity at the sub-market level. It investigates whether and how money supply, inflation, foreign exchange markets, general economic productivity and other important macroeconomic factors interact with the pricing of different property types over time.
{"title":"Causal relationships between the price-to-rent ratio and macroeconomic factors: a UK perspective","authors":"D. Lo, M. McCord, P. Davis, J. McCord, Martin Haran","doi":"10.1108/jpif-08-2021-0068","DOIUrl":"https://doi.org/10.1108/jpif-08-2021-0068","url":null,"abstract":"PurposeHouse price-to-rent (P-t-R) ratios are among the most widely used measures of housing market conditions. Given the theoretical and apparent bidirectional, causal relationships and imbalances between the housing market, broader economy and financial market determinants, it is important to understand the relationship between macro- and micro-economic characteristics in relation to the P-t-R ratio to enhance the understanding of housing market dynamics. This paper studies the joint dynamics and persistence of house prices and rents and examines the temporal interactions of the P-t-R ratio and economic and financial determinants.Design/methodology/approachThe authors examine the lead–lag relationships between the P-t-R ratios and a spectrum of macroeconomic variables using cointegration and causality methods, initially at the aggregate position and also across housing types within the Northern Ireland housing market to establish whether there are subtle differences in how various housing segments react to changes in economic activity and market fundamentals.FindingsThe findings reveal price switching dynamics and some very distinct long- and short-run relationships between macroeconomic and financial indicators and the P-t-R ratios across the various housing segments. The results exhibit monetary supply, foreign exchange markets and the stock market to be important drivers of the P-t-R ratio, with P-t-R movements seemingly tied, or are in tandem, with the overall economy, particularly with the construction sector.Practical implicationsThe study shows that the P-t-R ratio can be used as an early measure for establishing the effects of macroprudential policy changes and how these may manifest across housing tiers and quality, which can further act as a signal for preventing or at least mitigating future irrational price cyclicity. These insights serve to inform housing and economic policy and macroprudential policy design, principally within lending policy and the effect of regulatory interventions and further enhance the understanding of the P-t-R ratio on housing market structure and dynamics.Originality/valueThis study is the first in the housing literature that examines the causal relationships between the P-t-R ratio and macroeconomic activity at the sub-market level. It investigates whether and how money supply, inflation, foreign exchange markets, general economic productivity and other important macroeconomic factors interact with the pricing of different property types over time.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43489328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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