Journal of Property Investment & Finance最新文献

{"title":"The big data regime shift in real estate","authors":"J. Delisle, Brent Never, T. Grissom","doi":"10.1108/jpif-10-2019-0134","DOIUrl":"https://doi.org/10.1108/jpif-10-2019-0134","url":null,"abstract":"The paper explores the emergence of the “big data regime” and the disruption that it is causing for the real estate industry. The paper defines big data and illustrates how an inductive, big data approach can help improve decision-making.,The paper demonstrates how big data can support inductive reasoning that can lead to enhanced real estate decisions. To help readers understand the dynamics and drivers of the big data regime shift, an extensive list of hyperlinks is included.,The paper concludes that it is possible to blend traditional and non-traditional data into a unified data environment to support enhanced decision-making. Through the application of design thinking, the paper illustrates how socially responsible development can be targeted to under-served urban areas and helps serve residents and the communities in which they live.,The paper demonstrates how big data can be harnessed to support decision-making using a hypothetical project. The paper does not present advanced analytics but focuses aggregating disparate longitudinal data that could support such analysis in future research.,The paper focuses on the US market, but the methodology can be extended to other markets where big data is increasingly available.,The paper illustrates how big data analytics can be used to help serve the needs of marginalized residents and tenants, as well as blighted areas.,This paper documents the big data movement and demonstrates how non-traditional data can support decision-making.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-10-2019-0134","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45235207","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}

{"title":"Fundamentals for automating due diligence processes in property transactions","authors":"Philipp Maximilian Müller, Philipp Päuser, Björn-Martin Kurzrock","doi":"10.1108/jpif-09-2019-0130","DOIUrl":"https://doi.org/10.1108/jpif-09-2019-0130","url":null,"abstract":"PurposeThis research provides fundamentals for generating (partially) automated standardized due diligence reports. Based on original digital building documents from (institutional) investors, the potential for automated information extraction through machine learning algorithms is demonstrated. Preferred sources for key information of technical due diligence reports are presented. The paper concludes with challenges towards an automated information extraction in due diligence processes.Design/methodology/approachThe comprehensive building documentation including n = 8,339 digital documents of 14 properties and 21 technical due diligence reports serve as a basis for identifying key information. To structure documents for due diligence, 410 document classes are derived and documents principally checked for machine readability. General rules are developed for prioritized document classes according to relevance and machine readability of documents.FindingsThe analysis reveals that a substantial part of all relevant digital building documents is poorly suited for automated information extraction. The availability and content of documents vary greatly from owner to owner and between document classes. The prioritization of document classes according to machine readability reveals potentials for using artificial intelligence in due diligence processes.Practical implicationsThe paper includes recommendations for improving the machine readability of documents and indicates the potential for (partially) automating due diligence processes. Therefore, document classes are derived, reviewed and prioritized. Transaction risks can be countered by an automated check for completeness of relevant documents.Originality/valueThis paper is the first published (empirical) research to specifically assess the automated digital processing of due diligence reports. The findings are helpful for improving due diligence processes and, more generally, promoting the use of machine learning in the property sector.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-09-2019-0130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44413116","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}

{"title":"The initial impacts of Minimum Energy Efficiency Standards (MEES) in England","authors":"S. Sayce, Syeda Marjia Hossain","doi":"10.1108/jpif-01-2020-0013","DOIUrl":"https://doi.org/10.1108/jpif-01-2020-0013","url":null,"abstract":"PurposeThe paper investigates the initial impacts on asset management and valuation practice of the Minimum Energy Efficiency Standard (MEES) introduced in England and Wales from April 2018 for new lettings.Design/methodology/approachThe paper reports findings from a small-scale pilot study of valuers, asset managers, lawyers and building consultants. Interviews were conducted over the summer of 2019 and explored the impact on practice and market values and perceived links to the carbon reduction agenda. Data were analysed thematically manually and using NVivo software.FindingsParticipants welcomed MEES but many had doubts about the use of energy performance certificates (EPCs) as the appropriate baseline measure. Compliance was perceived as too easy; further, enforcement is not occurring. Vanguard investors have aligned portfolios for carbon reduction; others have not. Lease practices are changing with landlords seeking greater control over tenant behaviours. Valuers reported that whilst MEES consideration is embedded in due diligence processes, there is limited value impact.Research limitations/implicationsThe study is limited by its small-scale and that the MEES regulations are not yet fully implemented. However, the research provides early findings and lays out recommendations for future research by identifying areas in which the regulations are/are not proving effective to date.Practical implicationsThe findings will inform investors, consultants and policy makers.Social implicationsAchieving energy efficiency in buildings is critical to driving down carbon emission; it also has economic and social benefits through cost savings and reducing fuel poverty.Originality/valueBelieved to be the first post-implementation qualitative study of MEES.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-01-2020-0013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41599963","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}

{"title":"House prices and credit cycles: the case of Cyprus","authors":"Dario Pontiggia, P. Sivitanides","doi":"10.1108/jpif-02-2020-0022","DOIUrl":"https://doi.org/10.1108/jpif-02-2020-0022","url":null,"abstract":"Purpose - The purpose of this paper is to assess whether the rapid accumulation of bank deposits before the global financial crisis and their subsequent drastic reduction was the main driving force of the Cyprus house price cycle over the period 2006–2015. Design/methodology/approach - To this aim we estimate a three-equation model in which house prices are determined by housing loans, among other factors, and housing loans are determined by bank deposits. All equations are estimated using partial adjustment model specifications. Findings - Our findings indicate that housing loans, which capture the effect of credit availability on housing demand, had the smallest effect on house prices, thus providing little support to our proposition of a deposits-driven cycle in house prices. Research limitations/implications - The main limitation of the study is the use of the housing loan stock instead of the actual volume of housing loans in each period due to lack of such data. As a result our econometric estimates may not accurately capture the magnitude of the effect of housing loans on house prices. Practical implications - The study has important practical implications for policy makers as it highlights the importance of availability of credit in supporting effective demand for housing during periods of economic growth. Furthermore, it highlights the key role of house price increases in combination with the collateral effect in driving the house price cycle. Originality/value - This is among the few studies internationally and the first study in Cyprus that attempts to link econometrically the credit and house price cycles that were caused by the global financial crisis.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-02-2020-0022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48544639","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}

{"title":"Performing technical analysis to predict Japan REITs' movement through ensemble learning","authors":"Wei Kang Loo","doi":"10.1108/jpif-01-2020-0007","DOIUrl":"https://doi.org/10.1108/jpif-01-2020-0007","url":null,"abstract":"PurposeThe purpose of this study is to evaluate the performance of the ensemble learning models, such as the Random Forest and Extreme Gradient Boosting models, in predicting the direction of the Japan real estate investment trusts (J-REITs) at different return horizons, based on input obtained from various technical indicators.Design/methodology/approachThis study measures the predictability of J-REITs with technical indicators by using different horizons of REITs' return and machine learning models. The ensemble learning models includes Random Forest and Extreme Gradient Boosting models while the return horizons of REITs ranging from 1 to 300 days. The results were further split into individual years to check for the consistency of the performance across time.FindingsThe Extreme Gradient Boosting appears to be the best method in improving forecast accuracy but not the trading return. A wider return horizons platform seemed to deliver a relatively better performance in both forecast accuracy and trading return, when compared to the return horizon of one.Practical implicationsIt is recommended that the Extreme Gradient Boosting and Random Forest model be considered by practitioners for back-testing trading model. In addition, selecting different return horizons so as to achieve a better performance in trading/investment should also be considered.Originality/valueThe predictability of J-REITs using technical indicators was compared among different returns horizons and the models (Extreme Gradient Boosting and Random Forest).","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-01-2020-0007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45168729","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}

{"title":"Is the MD&A of US REITs informative? A textual sentiment study","authors":"M. Koelbl","doi":"10.1108/jpif-12-2019-0149","DOIUrl":"https://doi.org/10.1108/jpif-12-2019-0149","url":null,"abstract":"This study examines whether language disclosed in the Management Discussion and Analysis (MD&A) of US Real Estate Investment Trusts (REITs) provides signals regarding future firm performance and thus generates a market response.,This research conducts textual analysis on a sample of approximately 6,500 MD&As of US REITs filed by the SEC between 2003 and 2018. Specifically, the Loughran and Mcdonald (2011) financial dictionary, and a custom dictionary for the real estate industry created by Ruscheinsky et al. (2018), are employed to determine the inherent sentiment, that is, the level of pessimistic or optimistic language for each filing. Thereafter, a panel fixed-effects regression enables investigating the relationship between sentiment and future firm performance, as well as the markets’ reaction.,The empirical results suggest that higher levels of pessimistic (optimistic) language in the MD&A predict lower (higher) future firm performance. Hereby, the use of a domain-specific real estate dictionary, namely that developed by Ruscheinsky et al. (2018) leads to superior results. Corresponding to the notion that the human psyche is affected more strongly by negative than positive news (Rozin and Royzman, 2001), the market responds solely to pessimistic language in the MD&A.,The results suggest that the market can benefit from textual analysis, as investigating the language in the MD&A reduces information asymmetries between US REIT managers and investors.,This is the first study to analyze exclusively US REITs, whether language in the MD&A is predictive of future firm performance and whether the market responds to textual sentiment.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-12-2019-0149","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49169058","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}

{"title":"Spillovers between US real estate and financial assets in time and frequency domains","authors":"A. Tiwari, C. André, Rangan Gupta","doi":"10.1108/JPIF-08-2019-0110","DOIUrl":"https://doi.org/10.1108/JPIF-08-2019-0110","url":null,"abstract":"Real estate, either in physical or securitised form, provides valuable diversification opportunities to investors. However, spillovers reduce the benefits of portfolio diversification, especially in times of crisis, when asset returns tend to be more correlated. This paper assesses the strength and time variation of spillovers between returns on residential real estate, real estate investment trusts (REITs), stocks and bonds in the United States, using the Diebold-Yilmaz (DY) (2012) approach in the time domain and the Barunik-Křehlik (BK) (2018) methodology in the frequency domain. On average, spillovers between housing, stock and bond returns are relatively modest and shocks to stock and bond markets affect housing returns more than the other way round, even though net spillovers from housing to other assets spiked in the aftermath of the subprime crisis. Spillovers in both directions are much stronger between REITs and stocks than between REITs and housing. The analysis in the frequency domain highlights the persistence of effects from shocks originating in the housing market, particularly in the aftermath of the subprime crisis.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/JPIF-08-2019-0110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48155806","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}

{"title":"Risks in feasibility and viability appraisal process for property development and the investment market in Nigeria","authors":"Z. T. Jagun","doi":"10.1108/jpif-12-2019-0151","DOIUrl":"https://doi.org/10.1108/jpif-12-2019-0151","url":null,"abstract":"The feasibility and viability appraisal technique is becoming increasingly crucial in the planning systems, theory, applications and outputs for property development and project investments. This paper aims to account for the findings of the practices associated with risk in the feasibility and viability appraisal process. Also, it examines the need for a practical framework for conducting a feasibility and viability appraisal, which can be employed by estate surveyors and valuers in Nigeria,This study adopted purposive sampling techniques to administer 240 sets of questionnaires, out of which 210 sets were well-thought-out to be useable for the analysis after data screening. Statistical package for social sciences (SPSS), structural equation modelling (SEM) and analysis of movement structures (AMOS) were the main analytical tools used to carry out the reliability test, normality test, exploratory factor analysis, confirmatory factor analysis, measurement and structural model.,The analysis results indicated that the P-values of the various forms of concepts of risks in feasibility and viability appraisal process (preparation) for property development and the investment market was statistically significant: technological factor - 0.000; political factor- 0.000 and economic factor- 0.000. However, a non-significant effect was found with socio-environmental factors on the preparation of housing development appraisal with P-value 0.155, and that risk management is neither holistically implemented in the feasibility and viability appraisal process nor extensively taken into cognisance.,This paper reports the results of the practices among estate surveyors and valuers in regarding the risk associated in the preparation stages of the feasibility and viability appraisal process,There are limited studies that suggest risk management factors in the appraisal reports for property development. Although previous studies have identified the risk factors, there is a lack of emphasis on management, which entails identification, assessment, monitoring and control. This study, therefore, recommends the incorporation of risk management into the feasibility and viability appraisal process implemented by estate surveyors and valuers. It is envisaged that the process will protect investors from the potential risk factors associated with investments in property development.,The study highlighted the need for practical or empirical research to be used to assess the significant risk factors that are needed to be reflected in the preparation stages of the feasibility and viability appraisal conduct of estate surveyors and valuers in Abuja, Nigeria.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-12-2019-0151","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44981361","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}

{"title":"The investment opportunities in the innovation-led listed satellite and telecommunication infrastructure sectors","authors":"M. Marzuki, G. Newell","doi":"10.1108/jpif-10-2019-0132","DOIUrl":"https://doi.org/10.1108/jpif-10-2019-0132","url":null,"abstract":"PurposeCommunication infrastructure assets present a compelling investment opportunity for investors interested to tap into the technology-driven and innovation-led infrastructure segments, given the need for intensified capital deployment to prepare for the future substantial flow in volume and velocity of information. These communication infrastructure assets exist either in the segments of satellite or telecommunication infrastructure. This paper intends to empirically assess the performance attributes of listed satellite and telecommunication infrastructure over January 2000–June 2019. Sub-period performance dynamics of listed satellite and telecommunication infrastructure in the pre-GFC (January 2000–June 2007) and the post-GFC (July 2009–June 2019) investment horizons are provided.Design/methodology/approachNineteen-year monthly total returns over 2000–2019 were used to analyse the risk-adjusted performance and portfolio diversification potential of both listed satellite and telecommunication infrastructure. The mean-variance portfolio optimisation framework using the full period and post-GFC ex-post returns, risk and correlation coefficient of listed satellite and telecommunication infrastructure and other financial assets was developed to determine the added-value benefits of listed satellite and telecommunication infrastructure in an optimised investment framework.FindingsListed satellite and telecommunication infrastructure delivered mixed investment performance. They were highly volatile and there was a significant discount in total return performance against the other asset classes in the full and pre-GFC periods. However, listed telecommunication infrastructure delivered stronger performance in the post-GFC period across all performance measures. Listed satellite and telecommunication infrastructure offered strong diversification benefits for investors across all investment horizons. Further, the inclusion of listed telecommunication infrastructure in both the full period and post-GFC mixed-asset investment framework was also empirically justified.Practical implicationsCommunication infrastructure assets such as satellite and telecommunication infrastructure are the key infrastructure assets to ensure the seamless operation of and interaction with modern technology going forward. Whilst being a small proportion of the overall infrastructure asset class universe, the $2.1 trillion progressively expanding listed communication infrastructure sector is having an important role to stimulate investor capital deployments in high quality and future-proof communication infrastructure assets. Listed satellite and telecommunication infrastructure assets are an opportunistic investment given their future growth potential and are seen as a suitable fit for investors with a secular investment profile.Originality/valueDespite the infrastructure asset class being the focus of growing attention and empirical analysis, no previous studies have empiric","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jpif-10-2019-0132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48347837","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}

{"title":"Crowdfunding REITs: a new asset class for the real estate industry?","authors":"Lucia Gibilaro, G. Mattarocci","doi":"10.1108/JPIF-08-2019-0112","DOIUrl":"https://doi.org/10.1108/JPIF-08-2019-0112","url":null,"abstract":"PurposeThe paper aims to study the performance of crowdfunding REITs with respect to traditional REITs in order to evaluate the differences in the risk–return profile and their usefulness for a diversification strategy within the indirect real estate investments.Design/methodology/approachThe paper considers the crowdfunding REITs introduced after the JOBS act in the United States and evaluates their performance and risk during the time period 2016–2018. Performance achieved by crowdfunding REITs is compared with other types of REITs in order to evaluate their usefulness for constructing an optimal portfolio strategy based on a standard mean variance approach.FindingsResults show that the performance of crowdfunding REITs is more stable over time with respect to other REITs and the lack of correlation with traditional REITs may be exploited for constructing a more efficient diversified portfolio of indirect real estate investments.Practical implicationsCrowdfunding REITs have different performance with respect to standard REITs and, especially individual investors, may benefit from including this new investment opportunity in their portfolio.Originality/valueThe paper is the first study on the performance of the crowdfunding REITs that is evaluating their usefulness for a diversification strategy within the real estate sector.","PeriodicalId":46429,"journal":{"name":"Journal of Property Investment & Finance","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2020-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/JPIF-08-2019-0112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226661","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}