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Practice briefing – China's commercial real estate recovery, REITs and tax policies 实践简报-中国商业地产复苏,REITs和税收政策
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2022-02-01 DOI: 10.1108/jpif-03-2021-0024
Olivia Muszynski, Mine E. Cinar
PurposeCommercial property market allows for the potential development of a similar real estate investment trust (REIT) structure in China as the commercial REITs (C-REIT) such as those offshore in Hong Kong and Singapore.Design/methodology/approachThe authors examine tax codes of the present real estate investment methods in China in order to understand the interest for a new vehicle that specifically focuses on commercial real estate.FindingsGiven the progress of offshore C-REITS and Chinese government's emphasis on real estate, Chinese shareholders will benefit if onshore C-REITS are issued. Crucial to the success of C-REITS will be how the C-REIT shares will be priced with respect to Net Asset Value of underlying assets.Research limitations/implicationsCOVID-19 pandemic has changed government priorities, and development of C-REITS in real estate for growth may no longer be a priority policy for China.Practical implicationsLiquidity in real estate markets will be enhanced by C-REITS due to participation of private investors.Social implicationsOnshore C-REITS would allow small and individual investors to have a stake in their home country's commercial real estate as an investment security for their own future.Originality/valueThis policy article also includes an interview with real estate professional in China whose opinions are embedded and added to the article.
目的商业房地产市场允许在中国开发与商业房地产投资信托(C-REIT)类似的房地产投资基金(REIT)结构,如香港和新加坡的离岸房地产投资投资信托特别关注商业地产。发现鉴于离岸C-REITS的进展和中国政府对房地产的重视,如果在岸C-REITS发行,中国股东将受益。C-REITS成功的关键是C-REIT股票将如何相对于基础资产的资产净值进行定价。研究局限性/影响新冠肺炎疫情改变了政府的优先事项,发展房地产投资信托基金以促进增长可能不再是中国的优先政策。实际影响由于私人投资者的参与,房地产市场的流动性将因C-REITS而增强。社会影响陆上C-REITS将允许小型和个人投资者在本国的商业房地产中持有股份,作为他们自己未来的投资保障。原创/价值这篇政策文章还包括对中国房地产专业人士的采访,他们的观点被嵌入并添加到文章中。
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引用次数: 2
Safe as houses? Thinking on the rise of investment into UK residential markets 像房子一样安全?对英国住宅市场投资增长的思考
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2022-01-25 DOI: 10.1108/jpif-01-2022-0001
N. Livingstone
PurposeIn recent decades, institutional investment has become increasingly focussed on residential property in the United Kingdom, reflecting interest in what was previously considered an “alternative” asset class, but is now an evolving and ever more complex sector. This short thought piece considers how such processes may be understood through investment-related research.Design/methodology/approachThe UK residential market has experienced substantial capital inflows in the wake of the global financial crisis. This reflective piece suggests there is a need for more research into residential real estate as an institutional asset class to further unpack and understand shifting market dynamics within the United Kingdom. It offers insight into evolving market trends across a diverse range of investors and market sub-sectors.FindingsThis paper considers the diverse research opportunities within the residential investment markets, including, but not limited to, the private rented sector, build-to-rent and purpose-built student accommodation, presenting opportunities for burgeoning research.Practical implicationsThe viewpoint suggests how this research lacuna may be bridged through additional research in not just the UK residential market, but also how investors may further integrate and operationalise UK residential assets in diversified or specialised investments, from domestic to international propositions. The suggested research agenda promotes enhanced understandings of residential markets and processes driving investment decision-making.Originality/valueAs the integration of residential property into vehicles such as Real Estate Investment Trusts, private equity funds and managed multi-asset portfolios continues to increase, there is an amplified need to understand the market context in which such investment flows occur, including the potential impact of COVID-19, Brexit and the cyclical evolution of real estate markets more broadly.
目的近几十年来,英国的机构投资越来越关注住宅物业,这反映出人们对以前被认为是“另类”资产类别的兴趣,但现在是一个不断发展且越来越复杂的行业。这篇简短的思考文章考虑了如何通过投资相关研究来理解这些过程。设计/方法/方法全球金融危机后,英国住宅市场出现了大量资本流入。这篇反思性文章表明,有必要对住宅房地产作为一种机构资产类别进行更多研究,以进一步揭示和了解英国不断变化的市场动态。它提供了对不同投资者和市场细分行业不断发展的市场趋势的见解。发现本文考虑了住宅投资市场中的各种研究机会,包括但不限于私人租赁部门、按租建造和专门建造的学生宿舍,为蓬勃发展的研究提供了机会。实际含义该观点表明,如何通过对英国住宅市场的额外研究,以及投资者如何在从国内到国际的多元化或专业投资中进一步整合和运营英国住宅资产,来弥补这一研究空白。建议的研究议程有助于加深对住宅市场和推动投资决策的过程的理解。创意/价值随着住宅房地产与房地产投资信托基金、私募股权基金和管理型多资产投资组合等工具的整合不断增加,更需要了解此类投资流发生的市场背景,包括新冠肺炎的潜在影响,英国脱欧和更广泛的房地产市场的周期性演变。
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引用次数: 2
Property development activities: value creation or distraction for REITs? 房地产开发活动:为REITs创造价值还是分散注意力?
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2022-01-07 DOI: 10.1108/jpif-10-2021-0079
W. Wong, J. Ooi
PurposeThis paper examines the evolution and impact of property development activities on REIT performance. The paper provides insights on whether REITs should venture into property development in addition to their core-business of holding income producing properties.Design/methodology/approachThis paper charts and highlights the evolution of development activities of US REITs from 1992 to 2020. The Tobin's Q of property developing REITs and non-property developing REITs are compared using univariate analysis.FindingsDevelopment activities of US REITs grew dramatically during the run up to global financial crisis (GFC) in 2008. The level of development activities has dropped since the GFC and it has not return to its pre-crisis peak. In comparison, development activities of listed property investment companies and homebuilders are less volatile over the same period. The data reveals that property developing REITs enjoy significantly higher Tobin's Q as compared to their non-developing counterparts.Practical implicationsOur graphical evidence from a market without development restriction suggests that development restriction in other REIT regimes has it value in limit REITs' excessive risk-taking tendency during a booming property market. The positive relationship between Tobin's Q and the existence of property development activity support the value creation of this business activity to REITs.Originality/valueThis paper raises overbuilding as a potential cause of the underperformance of the REIT sector during the GFC.
目的研究房地产开发活动的演变及其对房地产投资信托基金绩效的影响。本文就房地产投资信托基金除了持有创收物业的核心业务外,是否应涉足房地产开发提供了见解。设计/方法/方法本文描绘并强调了1992年至2020年美国房地产投资信托基金发展活动的演变。利用单变量分析比较了房地产开发REITs和非房地产开发REITs的托宾Q值。研究发现:2008年全球金融危机爆发前,美国房地产投资信托基金的开发活动急剧增长。自全球金融危机以来,发展活动水平有所下降,而且尚未恢复到危机前的峰值水平。相比之下,同期上市房地产投资公司和住宅建筑商的开发活动波动较小。数据显示,与非开发房地产投资信托基金相比,房地产开发REITs的托宾Q值明显更高。实际意义没有开发限制的市场的图形证据表明,其他房地产投资信托基金制度的开发限制在限制房地产投资信托基金在蓬勃发展的房地产市场中的过度冒险倾向方面具有其价值。托宾Q值与房地产开发活动的存在之间存在正相关关系,支持该业务活动对房地产投资信托基金的价值创造。原创性/价值本文提出,过度建设是全球金融危机期间REIT行业表现不佳的一个潜在原因。
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引用次数: 0
Grand ideas or delusions of grandeur? Placing big thinkers and essential theories in property economics research 伟大的想法还是自大的妄想?把大思想家和基本理论放在房地产经济学研究中
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-22 DOI: 10.1108/jpif-11-2021-0097
G. Squires
PurposeThis article is looking to reflect on the various important touchstones of “grand theory” and “big thinkers” that can be framed when engaging empirical evidence in property economics research.Design/methodology/approachThe paper is reflexive in nature, using experiential reflection to consider theory in property economics. The importance of “methodology” is emphasised rather than “method”.FindingsUsing reflexive mode, the paper does not have “findings” as such: if the views expressed are accepted, then a research agenda to better understand property economics research is implied.Research limitations/implicationsThe nature of reflection is that it follows from the writer's experiential processes and interpretations. The reader may come from a different stance. Broadly accepting the propositions, there is a call for property economics research to be formulated in reason and logic, particularly as humans do not reason from facts alone. Such reasoned thinking could for example be in the property economic concepts of space and place, contracts and justice, capital and financialisation.Practical implicationsTo engage with such theory would provide some depth of philosophical roots for property as a discipline. Elevating property as a “real-world” discipline rather than simply an applied mathematics discipline.Social implicationsThe paper enables an understanding of how property economics research can benefit from more ontology and more inductive reasoning.Originality/valueThe paper reflects the views and experience of the author based on over 15 years of research in property economics.
本文旨在反思“大理论”和“大思想家”的各种重要试金石,这些试金石在从事房地产经济学研究的经验证据时可以被框定。设计/方法/方法本文本质上是反思性的,使用经验反思来考虑财产经济学的理论。强调“方法论”的重要性,而不是“方法”。使用反思性模式,本文没有这样的“发现”:如果所表达的观点被接受,那么就隐含了更好地理解房地产经济学研究的研究议程。研究局限/启示反思的本质是它遵循作者的经验过程和解释。读者可能有不同的观点。在广泛接受这些命题的情况下,人们呼吁用理性和逻辑来制定财产经济学研究,特别是因为人类并不仅仅从事实来进行推理。例如,这种理性思考可以出现在空间和地点、合同和正义、资本和金融化等财产经济概念中。实践意义参与这样的理论将为财产作为一门学科提供一定深度的哲学根源。将财产提升为一门“现实世界”学科,而不仅仅是一门应用数学学科。社会意义本文使我们能够理解财产经济学研究如何从更多的本体论和更多的归纳推理中受益。原创性/价值本文反映了作者在房地产经济学领域超过15年研究的观点和经验。
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引用次数: 0
Data intelligence and real estate – machines are the real game changer 数据智能和房地产——机器才是真正的游戏规则改变者
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-22 DOI: 10.1108/jpif-11-2021-0101
Marcelo Cajias, Anett Wins
PurposeThe paper shows with two concrete examples about how algorithms are used in active real estate management. The paper also highlights that the discussion about the adoption of new technologies is crucial for market players.Design/methodology/approach The authors review the current status quo about new technologies in real estate and provide two examples of how algorithms can be used to understand locations and the value drivers of rents.FindingsLocation, location, location is nowadays data, data, data coupled with the knowledge of how to create life out of data. Algorithm can help to understand the value drivers of rents and can also help to evaluate the attractiveness of a location.Practical implicationsReal estate management will adapt to new technologies fast. This change has the potential to disrupt exiting strategies due to the increase in efficiency, insights, transparency and location knowledge. Investment managers walking this talk will definitely benefit in future.Originality/valueThe paper makes usage of the latest machine learning technologies applied to real estate investment cases. This is a unique opportunity on bringing light on the discussion about transparency in real estate.
目的通过两个具体的实例说明算法在主动房地产管理中的应用。本文还强调,关于采用新技术的讨论对市场参与者至关重要。作者回顾了房地产新技术的现状,并提供了两个例子,说明如何使用算法来理解位置和租金的价值驱动因素。如今,位置、位置、位置就是数据、数据、数据,再加上如何从数据中创造生活的知识。算法可以帮助理解租金的价值驱动因素,也可以帮助评估一个地点的吸引力。房地产管理将快速适应新技术。由于效率、洞察力、透明度和位置知识的提高,这种变化有可能破坏现有的战略。这样做的投资经理将来肯定会受益。本文将最新的机器学习技术应用于房地产投资案例。这是一个独特的机会,让关于房地产透明度的讨论变得明朗。
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引用次数: 1
The human factor: the “unknown unknowns” in the real estate development process 人的因素:房地产开发过程中的“未知的未知”
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-20 DOI: 10.1108/jpif-11-2021-0099
Elaine Worzala, D. Wyman
PurposeVolatility, Uncertainty, Complexity and Ambiguity (VUCA) are terms the military have coined to describe the environment they often operate in. This paper examines how this decision-making framework can be used to better inform real estate investment and development. In celebration of this journal's 40th anniversary, we also explore how VUCA can be related to and expand on the teachings of Dr. James A. Graaskamp who published his seminal piece on the Fundamentals of Real Estate Development (1981) the same year. In that piece, he highlights the importance of paying attention to the human factor, the consumers of real estate.Design/methodology/approachThis is a thought piece on an alternative decision-making framework that can help capture the dynamic environment that commercial real estate investors and developers are currently working in. VUCA captures the difficulty of predicting the future in a world of accelerating, unpredictable change. This is particularly important in today's rapidly changing world caused not only by the current COVID-19 pandemic but also the exponential growth of the proptech industry as well as the increasing risks and opportunities associated with climate change that continues to impact the built environment.FindingsThis is not a traditional research project with empirical findings. We are presenting an alternative framework for thinking about making investment decisions in these current volatile, uncertain, complex and ambiguous times today and in the future. In addition, the importance of multidisciplinary training and the human factor are stressed.Research limitations/implicationsThere are no limitations to this research as it is the ideas of the authors. Implications are to help real estate investors, developers and educators better understand the environment that they are working in.Practical implicationsVUCA captures better the dynamic nature of real estate investments compared to traditional analysis. It helps one better analyze the risks and returns but also to acknowledge that there is a lot you cannot predict and there are many exogenous variables that can, at times, completely change the rules of the game. Flexibility and adaptability are essential tools for working in a VUCA environment. In addition, the human factor plays an increasingly important role and real estate investors and developers that clearly understand this and focus on the consumer will likely be more successful.Originality/valueWe believe that this is the first time that VUCA has been used in the real estate academic literature.
目的波动性、不确定性、复杂性和模糊性(VUCA)是军方用来描述他们经常行动的环境的术语。本文探讨了如何利用这一决策框架更好地为房地产投资和开发提供信息。为了庆祝本刊创刊40周年,我们还探讨了VUCA如何与James A. Graaskamp博士的教诲相关联并扩展,James A. Graaskamp博士在同一年发表了他的开创性作品《房地产开发基础》(1981)。在那篇文章中,他强调了关注人为因素的重要性,即房地产的消费者。设计/方法论/方法这是一篇关于替代决策框架的思想文章,可以帮助捕捉商业房地产投资者和开发商目前所处的动态环境。VUCA抓住了在一个不断加速的、不可预测的变化世界中预测未来的困难。在当今瞬息万变的世界中,这一点尤为重要,这不仅是因为当前的COVID-19大流行,还因为proptech行业的指数级增长,以及与气候变化相关的风险和机遇不断增加,气候变化继续影响建筑环境。这不是一个传统的实证研究项目。我们提出了另一种框架,用于思考在当前和未来动荡、不确定、复杂和模棱两可的时期做出投资决策。此外,还强调了多学科培训和人的因素的重要性。研究的局限性/意义本研究没有局限性,因为这是作者的想法。其影响是帮助房地产投资者、开发商和教育工作者更好地了解他们所处的环境。与传统分析相比,uca更好地捕捉了房地产投资的动态性质。它有助于人们更好地分析风险和回报,但也要承认,有很多事情是你无法预测的,有很多外生变量,有时会完全改变游戏规则。灵活性和适应性是在VUCA环境中工作的基本工具。此外,人的因素扮演着越来越重要的角色,房地产投资者和开发商清楚地认识到这一点,专注于消费者可能会更成功。原创性/价值我们认为这是VUCA第一次在房地产学术文献中被使用。
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引用次数: 1
Commercial real estate finance and the lending cap rate 商业地产金融贷款上限利率
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-20 DOI: 10.1108/jpif-10-2021-0081
J. Stokes, Arthur T. Cox
PurposeThe aim of this study is to report on a simple derivation that results in what the authors refer to as the lending cap rate. The lending cap rate is a unique cap rate resulting in a property valuation that perfectly aligns the maximum loan amount for the financing of commercial real estate.Design/methodology/approachThe derivation is the result of simple algebra relating the two most common underwriting ratios: debt service coverage and loan-to-value with the formula for the present value of an annuity. Numerical examples are presented to demonstrate the calculation of the lending cap rate, property valuation and maximum loan amount. The authors also present comparative statics results.FindingsThe main finding of this research is that once a lender knows the debt service coverage ratio, loan-to-value ratio and lending terms for a specific property financing request, a simple calculation reveals the lending cap rate and the property valuation that aligns the maximum loan amount implied by the two underwriting ratios.Practical implicationsOne practical implication of the research is that a simple calculation reveals the lending cap rate which facilitates timely property evaluations for lending purposes. The methods demonstrated also offer real estate finance educators a practical means of connecting the loan underwriting process with property appraisal thereby facilitating conceptual understanding.Originality/valueThe key finding is original, and the importance of the finding is that the determination of the lending cap rate is simple and has the ability to make commercial real estate lending faster and cheaper, especially in lending situations where an evaluation rather than an appraisal is appropriate.
目的本研究的目的是报告一个简单的推导,得出作者所说的贷款上限利率。贷款上限利率是一种独特的上限利率,可使房地产估值与商业房地产融资的最高贷款金额完美匹配。设计/方法/方法该推导是将两种最常见的承保比率(偿债覆盖率和贷款价值比)与年金现值公式联系起来的简单代数的结果。通过算例说明了贷款上限利率、房地产估价和最高贷款额的计算。作者还介绍了静力学的比较结果。发现这项研究的主要发现是,一旦贷款人知道特定房地产融资请求的偿债覆盖率、贷款价值比和贷款条款,一个简单的计算就会揭示贷款上限利率和房地产估值,这两个承销比率所隐含的最大贷款额是一致的。实际含义研究的一个实际含义是,一个简单的计算就可以揭示贷款上限利率,这有助于为贷款目的及时进行房地产评估。所展示的方法还为房地产金融教育工作者提供了一种将贷款承销过程与房地产评估联系起来的实用方法,从而促进概念理解。独创性/价值关键发现是独创性的,该发现的重要性在于,贷款上限利率的确定很简单,能够使商业房地产贷款更快、更便宜,尤其是在适合评估而非评估的贷款情况下。
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引用次数: 0
Risk management processes used in determining project feasibility in the property development process early stages by Australia/New Zealand property developers 澳大利亚/新西兰房地产开发商在房地产开发过程的早期阶段用于确定项目可行性的风险管理流程
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-14 DOI: 10.1108/jpif-08-2021-0071
Matthew Moorhead, L. Armitage, M. Skitmore
PurposeThe purpose is to examine the risk management processes and methods used in determining project feasibility in the early stages of the property development process by Australia/New Zealand property developers, including Monte Carlo simulation, Bayesian models and real option theory embedded in long-term property development and investment decision-making as instruments for providing flexibility and managing risk, uncertainty and change.Design/methodology/approachA questionnaire survey of 225 Australian and New Zealand trader developers, development managers, investors, valuers, fund managers and government/charities/other relating to Australia/New Zealand property development companies' decision-making processes in the early stages of the development process prior to site acquisition or project commencement – the methods used and confidence in their organisations' ability to both identify and manage the risks involved.FindingsFew of the organisations sampled use sophisticated methods; those organisations that are more likely to use such methods for conducting risk analysis include development organisations that undertake large projects, use more risk analysis methods and have more layers in their project approval process. Decision-makers have a high level of confidence in their organisation's ability to both identify and manage the risks involved, although this is not mirrored in their actual risk management processes. Although the majority of property developers have a risk management plan, less than half have implemented it, and a third need improvement.Practical implicationsProperty development organisations should incorporate more modern and sophisticated models of risk analysis to determine the uncertainty of, and risk in, a change of input variables in their financial viability appraisals. Practical application includes using such multiple techniques as what-if scenarios and probability analysis into feasibility processes and utilise these specific techniques in the pre-acquisition stages of the property development process and, specifically, in the site acquisition process to support decision-making, including a live risk register and catalogue of risks, including identification of and plans for mitigation of project risks, as a form of risk management.Originality/valueFirst study to examine the extent of the decision-making methods used by property developers in the pre-acquisition stage of the development process.
目的:目的是研究澳大利亚/新西兰房地产开发商在房地产开发过程的早期阶段确定项目可行性所使用的风险管理过程和方法,包括蒙特卡罗模拟、贝叶斯模型和长期房地产开发和投资决策中嵌入的实物期权理论,作为提供灵活性和管理风险、不确定性和变化的工具。设计/方法/方法对225名澳大利亚和新西兰的贸易商开发商、开发经理、投资者、估价师、基金经理和政府/慈善机构/其他与澳大利亚/新西兰房地产开发公司在土地收购或项目开始之前的开发过程的早期阶段的决策过程有关的人进行问卷调查-所使用的方法和对其组织识别和管理所涉及风险的能力的信心。调查结果抽样调查的组织中很少使用复杂的方法;那些更有可能使用这种方法进行风险分析的组织包括承担大型项目的开发组织,使用更多的风险分析方法,在项目审批过程中有更多的层次。决策者对其组织识别和管理所涉及的风险的能力有很高的信心,尽管这并没有反映在他们实际的风险管理过程中。尽管大多数房地产开发商都有风险管理计划,但只有不到一半的开发商实施了风险管理计划,三分之一的开发商需要改进。实际意义房地产开发机构应采用更现代和复杂的风险分析模型,以确定其财务可行性评估中输入变量变化的不确定性和风险。实际应用包括在可行性过程中使用多种技术,如假设情景和概率分析,并在房地产开发过程的收购前阶段,特别是在场地收购过程中利用这些具体技术来支持决策,包括实时风险登记册和风险目录,包括识别和减轻项目风险的计划,作为风险管理的一种形式。原创性/价值优先研究考察房地产开发商在开发过程的收购前阶段使用的决策方法的程度。
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引用次数: 1
Long lease real estate – a revised role for real estate in pension fund portfolios 长期租赁房地产——房地产在养老基金投资组合中的修订角色
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-13 DOI: 10.1108/jpif-05-2021-0050
Nick Mansley, Zilong Wang
PurposeLong lease real estate funds (over £15bn in Q3 2020) have emerged as an increasingly important part of UK pension fund real estate portfolios. This paper explores the reasons for their dramatic growth, their characteristics and performance.Design/methodology/approachThis study uses data for the period 2004–2020 collected directly from fund managers and from AREF/MSCI and empirical analysis to explore their characteristics and performance.FindingsPension fund de-risking and regulatory guidance have supported the dramatic growth of long lease real estate funds. Long lease real estate funds have delivered strong risk-adjusted returns relative to both balanced property funds (with shorter lease terms) and the wider property market. This relative performance has been particularly strong when wider property market performance has been weak. Long lease funds have objectives aligned with liability matching and their performance suggests they are lower risk (more bond-like) investments. In addition, our analysis highlights they are far less responsive to the wider property market than balanced funds. However, they are not significantly different from balanced property funds in terms of their short-term relationship with gilt yield movements.Practical implicationsFor pension funds and other investors the paper highlights that long lease real estate funds offer a different exposure than balanced property funds. Long lease funds have objectives more closely aligned to the overall objectives for pension fund investment but are not significantly more reliable than balanced property funds in the short-term as a liability hedge. For real estate fund managers, occupiers, developers and others active in the real estate market, the paper highlights why these funds have been (and are likely to remain) attractive to investors leading to substantial demand for long lease real estate investments.Originality/valueThis is the first study to review this increasingly important part of the UK real estate fund universe.
目的长期租赁房地产基金(2020年第三季度超过150亿英镑)已成为英国养老基金房地产投资组合中越来越重要的一部分。本文探讨了他们戏剧性成长的原因、特点和表现。设计/方法论/方法本研究使用了直接从基金经理和AREF/MSCI收集的2004-2020年期间的数据,并进行了实证分析,以探索其特征和表现。Findings养老基金的去风险和监管指导支持了长期租赁房地产基金的大幅增长。相对于平衡的房地产基金(租赁期较短)和更广泛的房地产市场,长期租赁房地产基金带来了强劲的风险调整回报。当整体房地产市场表现疲软时,这种相对表现尤其强劲。长期租赁基金的目标与负债匹配一致,其表现表明它们是风险较低(更像债券)的投资。此外,我们的分析强调,它们对更广泛的房地产市场的反应远不如平衡基金。然而,就其与金边债券收益率变动的短期关系而言,它们与平衡型房地产基金没有显著差异。实际含义对于养老基金和其他投资者来说,本文强调,长期租赁房地产基金提供的风险敞口与平衡房地产基金不同。长期租赁基金的目标与养老基金投资的总体目标更为一致,但在短期内作为负债对冲,其可靠性并不明显高于平衡房地产基金。对于房地产基金经理、占用人、开发商和其他活跃在房地产市场的人来说,本文强调了为什么这些基金一直(并且可能继续)对投资者有吸引力,从而导致对长期租赁房地产投资的巨大需求。独创性/价值这是第一项回顾英国房地产基金领域这一日益重要的部分的研究。
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引用次数: 0
Artificial intelligence algorithms to predict Italian real estate market prices 预测意大利房地产市场价格的人工智能算法
IF 1.3 Q2 Economics, Econometrics and Finance Pub Date : 2021-12-07 DOI: 10.1108/jpif-08-2021-0073
Luca Rampini, F. Re Cecconi
PurposeThe assessment of the Real Estate (RE) prices depends on multiple factors that traditional evaluation methods often struggle to fully understand. Housing prices, in particular, are the foundations for a better knowledge of the Built Environment and its characteristics. Recently, Machine Learning (ML) techniques, which are a subset of Artificial Intelligence, are gaining momentum in solving complex, non-linear problems like house price forecasting. Hence, this study deployed three popular ML techniques to predict dwelling prices in two cities in Italy.Design/methodology/approachAn extensive dataset about house prices is collected through API protocol in two cities in North Italy, namely Brescia and Varese. This data is used to train and test three most popular ML models, i.e. ElasticNet, XGBoost and Artificial Neural Network, in order to predict house prices with six different features.FindingsThe models' performance was evaluated using the Mean Absolute Error (MAE) score. The results showed that the artificial neural network performed better than the others in predicting house prices, with a MAE 5% lower than the second-best model (which was the XGBoost).Research limitations/implicationsAll the models had an accuracy drop in forecasting the most expensive cases, probably due to a lack of data.Practical implicationsThe accessibility and easiness of the proposed model will allow future users to predict house prices with different datasets. Alternatively, further research may implement a different model using neural networks, knowing that they work better for this kind of task.Originality/valueTo date, this is the first comparison of the three most popular ML models that are usually employed when predicting house prices.
目的房地产价格的评估取决于多种因素,而传统的评估方法往往难以完全理解这些因素。房价尤其是更好地了解建筑环境及其特征的基础。最近,机器学习(ML)技术作为人工智能的一个子集,在解决房价预测等复杂非线性问题方面势头越来越大。因此,本研究采用了三种流行的ML技术来预测意大利两个城市的房价。设计/方法/方法通过API协议收集了意大利北部两个城市(布雷西亚和瓦雷泽)的大量房价数据集。这些数据用于训练和测试三个最流行的ML模型,即ElasticNet、XGBoost和人工神经网络,以预测具有六个不同特征的房价。发现使用平均绝对误差(MAE)评分来评估模型的性能。结果表明,人工神经网络在预测房价方面比其他模型表现更好,其MAE比第二好的模型(XGBoost)低5%。研究局限性/含义所有模型在预测最昂贵的情况时的准确性都有所下降,可能是由于缺乏数据。实际含义所提出的模型的可访问性和易用性将允许未来用户使用不同的数据集预测房价。或者,进一步的研究可以使用神经网络实现不同的模型,因为他们知道它们更适合这类任务。原创性/价值迄今为止,这是对预测房价时通常使用的三种最流行的ML模型的首次比较。
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引用次数: 6
期刊
Journal of Property Investment & Finance
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