Pub Date : 2024-06-03DOI: 10.1080/10835547.2024.2353933
Ishaq Alam, Yousaf Ali
{"title":"A Linkage Analysis of Türkiye Real Estate Sector Based on Input-Output Model and Interpretive Structural Modelling","authors":"Ishaq Alam, Yousaf Ali","doi":"10.1080/10835547.2024.2353933","DOIUrl":"https://doi.org/10.1080/10835547.2024.2353933","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"55 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141269439","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 : 2024-02-29DOI: 10.1080/10835547.2024.2313401
Ying Zhang, Wikrom Prombutr, J. A. Hansz
{"title":"Real Estate Portfolio Diversification by Sectors Using a RAL Approach","authors":"Ying Zhang, Wikrom Prombutr, J. A. Hansz","doi":"10.1080/10835547.2024.2313401","DOIUrl":"https://doi.org/10.1080/10835547.2024.2313401","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140413803","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 : 2024-02-06DOI: 10.1080/10835547.2024.2303895
Kazushi Matsuo, Morito Tsutsumi, T. Imazeki
{"title":"Spillover Effect of Large Building Construction on Neighborhood Office Rents","authors":"Kazushi Matsuo, Morito Tsutsumi, T. Imazeki","doi":"10.1080/10835547.2024.2303895","DOIUrl":"https://doi.org/10.1080/10835547.2024.2303895","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"398 1-3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139860106","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 : 2024-02-06DOI: 10.1080/10835547.2024.2303895
Kazushi Matsuo, Morito Tsutsumi, T. Imazeki
{"title":"Spillover Effect of Large Building Construction on Neighborhood Office Rents","authors":"Kazushi Matsuo, Morito Tsutsumi, T. Imazeki","doi":"10.1080/10835547.2024.2303895","DOIUrl":"https://doi.org/10.1080/10835547.2024.2303895","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"12 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139800332","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 : 2023-10-03DOI: 10.1080/10835547.2023.2213601
Michael S. Young, Roger J. Brown
AbstractThe accuracy of real estate return distribution parameter estimation is affected by the tools used to do the work as well as the data sets employed. Consistent with previous studies, investment risk models with infinite variance describe distributions of individual property returns in the new NCREIF Indicators: Capital Performance and Property Operations individual property database over the period 1990–2021. Applying Maximum Likelihood Estimation (MLE) to historic data shows real estate investment risk to be heteroscedastic, but the Characteristic Exponent of the investment risk function varies more among property types than previously reported whether computed by MLE or other estimation techniques.Keywords: Asset-specific riskMaximum Likelihood EstimationNon-normalityDiversificationNCREIF AcknowledgementsThe authors wish to thank Jeffrey D. Fisher, John P. Nolan, Marlyn L. Hicks, and Kenneth M. Lusht for their considerable support in this project. All errors remain solely those of the authors.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The implementation of other analytical techniques up until the availability of Maximum Likelihood Estimators (MLE) for Levy-stable distributions is related in Young and Graff (Citation1995).2 Less frequently there are problems with market value estimates in a quarter such as recording a downpayment as the initial market value followed by the balance of the purchase price as the market value in the subsequent quarter. These cause extreme distortion of quarterly returns for individual properties, but are largely obscured in the aggregate NPI returns commonly cited as representative of the asset class. However, when working with individual property returns or smaller aggregations of property returns as in this study, these problems would necessarily distort the return distribution statistics as they unfortunately did in earlier NPI-based studies.3 Perhaps it should be noted that there have been other attempts to test the null hypothesis that real estate return distributions are Gaussian Normal using more conventional statistical techniques. The authors know of no cases that resulted in failing to reject the null. For example, there have been studies in the U.S. and even more in the U.K. using Chi-Square, Kolmogorov-Smirnov, or Anderson-Darling tests of common distributions like Logistic, Normal, Student’s t, or Extreme Value. For a summary of these studies pre-2000, see Lizieri and Ward (Citation2001).4 It may be worth noting that the numerators of the Price and Cash Flow formulas are those originally proposed by Young et al. (Citation1995, Citation1996) as replacements for the so-called Capital and Income Returns. Since NCREIF did not adopt the changes and retained the original formulation of Capital and Income Returns, the new Price and Cash Flow formulas were introduced for researchers interested in the Young, Geltner, McIntosh, and Poutasse concept. Notice t
摘要房地产收益分布参数估计的准确性受到所使用的工具和所使用的数据集的影响。与以往的研究一致，无限方差的投资风险模型描述了新NCREIF指标:资本绩效和财产运营个人财产数据库1990-2021年期间的个人财产回报分布。将最大似然估计(MLE)应用于历史数据显示房地产投资风险是异方差的，但投资风险函数的特征指数在房地产类型之间的变化比以前报道的更大，无论是用MLE还是其他估计技术计算。关键词:资产特定风险最大似然估计非正态化多样化致谢作者要感谢Jeffrey D. Fisher, John P. Nolan, Marlyn L. Hicks和Kenneth M. Lusht对本项目的大力支持。所有错误仅由作者自行承担。披露声明作者未报告潜在的利益冲突。注1在levy稳定分布的极大似然估计(MLE)可用之前，其他分析技术的实施与Young和Graff (Citation1995)有关不太常见的是，在一个季度的市场价值估计中存在问题，例如将首付款记录为初始市场价值，然后将购买价格的余额记录为下一个季度的市场价值。这些因素导致个别房产的季度收益极度扭曲，但在通常被用作资产类别代表的总NPI回报中，这些因素在很大程度上被掩盖了。然而，在处理个别财产回报或本研究中较小的财产回报总和时，这些问题必然会扭曲回报分布统计数据，不幸的是，它们在早期基于国家利益指数的研究中就是这样做的也许应该指出的是，已经有其他尝试使用更传统的统计技术来检验房地产收益分布是高斯正态分布的零假设。据作者所知，没有任何案件导致未能驳回无效裁决。例如，在美国和英国都有研究使用卡方、Kolmogorov-Smirnov或Anderson-Darling检验常见分布，如Logistic、Normal、Student 's t或Extreme Value。关于2000年以前这些研究的总结，见Lizieri和Ward (Citation2001)值得注意的是，价格和现金流量公式的分子最初是由Young等人(Citation1995, Citation1996)提出的，用来替代所谓的资本回报和收入回报。由于NCREIF没有采用这些变化，并保留了资本和收入回报的原始公式，因此为对Young, Geltner, McIntosh和Poutasse概念感兴趣的研究人员引入了新的价格和现金流量公式。还请注意，作者还建议将NPI总回报、收入回报和资本回报的分母改为简单的第一季度的市场价值部分销售(PS)的例子包括一栋楼的净销售价格，比如一个多栋楼的工业园区，或者一个购物中心外围的一个外地的净销售价格资本支出通常报告为正数，但偶尔也会出现会计“反转”，导致在某一特定时期报告的资本支出为负数。由于日记账分录在不同期间对支出进行重新分类或转移，可能会出现一些反转每一种都有不同的风险特征(Citation1998)被动投资房地产是徒劳无益的。那些认为他们可以通过购买房地产投资信托基金股票来被动投资房地产的人很快就会发现他们只是买了股票机敏的观察者会立即发现一个悖论，即有效的边界图形构成了一个需要协方差矩阵的参数图。如果levy稳定分布没有方差，那么它们可以没有协方差。然而，我们必须记住，levy稳定分布在极限上缺乏方差。所有有限样本都有一个可以计算的方差。该演示演示了“边界”的形状，使用的样本被假定是从具有用户提供的参数的levy稳定总体中提取的。该演示位于:http://demonstrations.wolfram.com/FormingTheEfficientFrontierWhenReturnsAreNonNormal/
{"title":"Real Estate Return Distributions with New NCREIF Data Series","authors":"Michael S. Young, Roger J. Brown","doi":"10.1080/10835547.2023.2213601","DOIUrl":"https://doi.org/10.1080/10835547.2023.2213601","url":null,"abstract":"AbstractThe accuracy of real estate return distribution parameter estimation is affected by the tools used to do the work as well as the data sets employed. Consistent with previous studies, investment risk models with infinite variance describe distributions of individual property returns in the new NCREIF Indicators: Capital Performance and Property Operations individual property database over the period 1990–2021. Applying Maximum Likelihood Estimation (MLE) to historic data shows real estate investment risk to be heteroscedastic, but the Characteristic Exponent of the investment risk function varies more among property types than previously reported whether computed by MLE or other estimation techniques.Keywords: Asset-specific riskMaximum Likelihood EstimationNon-normalityDiversificationNCREIF AcknowledgementsThe authors wish to thank Jeffrey D. Fisher, John P. Nolan, Marlyn L. Hicks, and Kenneth M. Lusht for their considerable support in this project. All errors remain solely those of the authors.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The implementation of other analytical techniques up until the availability of Maximum Likelihood Estimators (MLE) for Levy-stable distributions is related in Young and Graff (Citation1995).2 Less frequently there are problems with market value estimates in a quarter such as recording a downpayment as the initial market value followed by the balance of the purchase price as the market value in the subsequent quarter. These cause extreme distortion of quarterly returns for individual properties, but are largely obscured in the aggregate NPI returns commonly cited as representative of the asset class. However, when working with individual property returns or smaller aggregations of property returns as in this study, these problems would necessarily distort the return distribution statistics as they unfortunately did in earlier NPI-based studies.3 Perhaps it should be noted that there have been other attempts to test the null hypothesis that real estate return distributions are Gaussian Normal using more conventional statistical techniques. The authors know of no cases that resulted in failing to reject the null. For example, there have been studies in the U.S. and even more in the U.K. using Chi-Square, Kolmogorov-Smirnov, or Anderson-Darling tests of common distributions like Logistic, Normal, Student’s t, or Extreme Value. For a summary of these studies pre-2000, see Lizieri and Ward (Citation2001).4 It may be worth noting that the numerators of the Price and Cash Flow formulas are those originally proposed by Young et al. (Citation1995, Citation1996) as replacements for the so-called Capital and Income Returns. Since NCREIF did not adopt the changes and retained the original formulation of Capital and Income Returns, the new Price and Cash Flow formulas were introduced for researchers interested in the Young, Geltner, McIntosh, and Poutasse concept. Notice t","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135738604","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 : 2023-09-29DOI: 10.1080/10835547.2023.2247172
Glenn R. Mueller, Andrew G. Mueller
AbstractThe NCREIF Property Index (NPI) data starts in 1978 and has been used as a benchmark index for over 45 years. In 2006 NCREIF created the NCREIF Open-End Diversified Core Equity Index (ODCE) and used historic fund level data to create performance data back to 1978. ODCE was the first “investable index” in direct real estate for institutional investors, family offices, and high net worth investors who can meet these direct funds’ minimum investment levels (typically $5 million). Individual investors with less money can also access ODCE returns through Interval Funds or “Fund-of-Funds” that invest in and are designed to track or beat the ODCE Index. Since 2009 general partners of funds are required to update their net asset value (NAV) to “fair market value” on a quarterly basis as a result of Topic 820 of the Financial Accounting Standards Board. Both ODCE funds and interval funds have improved their liquidity with either monthly or quarterly redemption options, making them more competitive (from a liquidity aspect) with publicly traded securities. We analyze portfolio allocations over 45 years – the longest time frame ever studied and over 6 NEBR economic cycles and 4 ODCE real estate return cycles using Markowitz efficient frontier analysis. We inspect up-cycle and down-cycle periods separately and add to the literature by analyzing the ¼, ½, and ¾ points (low, medium, and high risk/return points) along the Markowitz efficient frontier. Our findings support many of the 45 studies published, but conflict with some depending upon their study methodology and time frame (9 to 25 years) studied. We conclude that real estate would have improved historic risk adjusted returns in many cycle periods.KEY FINDINGSDirect real estate investment and public REIT inclusion in a mixed asset portfolio with stocks and bonds are analyzed over a 45-year period (the longest period ever studied) through 6-economic cycles and 4-real estate cycles. Optimal asset class allocations are analyzed at low – medium – and high risk/return points on the Markowitz efficient frontier curve. The results show that both direct real estate and REITs improved historic mixed asset portfolio returns. Direct real estate’s high-income return (76% of total return historically in the NPI-ODCE Index) – potentially makes real estate a bond like substitute. Real estate was historically a very competitive asset class, with strong efficient frontier allocations overall (especially in higher return portfolios) and in most economic and real estate cycle periods. Investors should consider increasing future direct and public real estate (REIT) allocations in their portfolios.Keywords: Portfolio allocationefficient frontierMarkowitzdirect real estateREITsinvestingdiversification Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Investable Real Estate Allocations in a Mixed Asset Portfolio; Both Long Term and During Different Cycles","authors":"Glenn R. Mueller, Andrew G. Mueller","doi":"10.1080/10835547.2023.2247172","DOIUrl":"https://doi.org/10.1080/10835547.2023.2247172","url":null,"abstract":"AbstractThe NCREIF Property Index (NPI) data starts in 1978 and has been used as a benchmark index for over 45 years. In 2006 NCREIF created the NCREIF Open-End Diversified Core Equity Index (ODCE) and used historic fund level data to create performance data back to 1978. ODCE was the first “investable index” in direct real estate for institutional investors, family offices, and high net worth investors who can meet these direct funds’ minimum investment levels (typically $5 million). Individual investors with less money can also access ODCE returns through Interval Funds or “Fund-of-Funds” that invest in and are designed to track or beat the ODCE Index. Since 2009 general partners of funds are required to update their net asset value (NAV) to “fair market value” on a quarterly basis as a result of Topic 820 of the Financial Accounting Standards Board. Both ODCE funds and interval funds have improved their liquidity with either monthly or quarterly redemption options, making them more competitive (from a liquidity aspect) with publicly traded securities. We analyze portfolio allocations over 45 years – the longest time frame ever studied and over 6 NEBR economic cycles and 4 ODCE real estate return cycles using Markowitz efficient frontier analysis. We inspect up-cycle and down-cycle periods separately and add to the literature by analyzing the ¼, ½, and ¾ points (low, medium, and high risk/return points) along the Markowitz efficient frontier. Our findings support many of the 45 studies published, but conflict with some depending upon their study methodology and time frame (9 to 25 years) studied. We conclude that real estate would have improved historic risk adjusted returns in many cycle periods.KEY FINDINGSDirect real estate investment and public REIT inclusion in a mixed asset portfolio with stocks and bonds are analyzed over a 45-year period (the longest period ever studied) through 6-economic cycles and 4-real estate cycles. Optimal asset class allocations are analyzed at low – medium – and high risk/return points on the Markowitz efficient frontier curve. The results show that both direct real estate and REITs improved historic mixed asset portfolio returns. Direct real estate’s high-income return (76% of total return historically in the NPI-ODCE Index) – potentially makes real estate a bond like substitute. Real estate was historically a very competitive asset class, with strong efficient frontier allocations overall (especially in higher return portfolios) and in most economic and real estate cycle periods. Investors should consider increasing future direct and public real estate (REIT) allocations in their portfolios.Keywords: Portfolio allocationefficient frontierMarkowitzdirect real estateREITsinvestingdiversification Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135194827","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 : 2023-09-05DOI: 10.1080/10835547.2023.2246004
K. Goodwin, Shinhua Liu
{"title":"Creating the XLRE: Market Implications for REITs and the Real Estate Sector","authors":"K. Goodwin, Shinhua Liu","doi":"10.1080/10835547.2023.2246004","DOIUrl":"https://doi.org/10.1080/10835547.2023.2246004","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46886874","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 : 2023-07-31DOI: 10.1080/10835547.2023.2233348
Islam Ibrahim, Heidi Falkenbach
{"title":"Diversification and Cost of Public Debt for REITs: Evidence from the US","authors":"Islam Ibrahim, Heidi Falkenbach","doi":"10.1080/10835547.2023.2233348","DOIUrl":"https://doi.org/10.1080/10835547.2023.2233348","url":null,"abstract":"","PeriodicalId":35895,"journal":{"name":"Journal of Real Estate Portfolio Management","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42848770","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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