This thesis presents an inquiry into the historical performance of core institutional real estate investment property during the 1984-2003 period. The focus of the analysis is on identifying systematic determinants of long run investment performance. The analysis seeks to increase our understanding of equilibrium asset pricing within this asset class, as well to provide some useful perspective for core portfolio strategic or tactical planning. This thesis extends earlier research by Geltner (1999) and Li and Price (2005) that indicated that a classical single-factor CAPM accurately modeled the cross-section of long-run total returns across the major asset classes, including real estate. The present thesis narrows that earlier focus to concentrate on the cross-section of long-run total return performance within the core institutional real estate asset class. This thesis uses the property level data of the NCREIF Index to construct portfolios and historical return indexes based on property size (value), and based on CBSA "tier" (that is, "upper", "middle", and "tertiary" cities from an institutional investment perspective). By using unique portfolios created from the NCREIF property set that represent possible factors that systematically affect asset pricing, such as property location, property size and property type, and calculating their beta estimates from historical data, this thesis tests various CAPM models including the single factor Sharpe-Linter model, as well as a multi factor Fama-French-like model. The beta for the portfolios was defined with respect to the performance of the aggregate of all NCREIF properties. This thesis finds that an equilibrium asset pricing model consisting of the two Fama-French-like factors, property size and MSA tier, plus property type dummy variables, explains some 90% of the long-run historical cross-section of core property portfolio returns. Interestingly, the "market factor", the beta with respect to aggregate NCREIF, is found to be insignificant, and possibly a negative influence on expected return. Furthermore, the size factor works opposite to the way it does in the stock market, with larger properties commanding an expected return premium. Surprisingly, the city "tier" factor gives an expected return premium to upper tier cities. Tests for an "income factor" (similar to the Fama-French book-to-market factor) found this factor to be insignificant. The most significant factor was found to be the property type. Thus, the equilibrium asset price model that seems to work well within the institutional core real estate asset class seems to be very different from, almost opposite to, the analogous model within the stock market.

This book is dedicated to real estate scholastic work, in advancing the greater understanding of real estate investment analysis. This is because there has been limited research in bringing out clearly the uncertainty or risk, which is quantifiable uncertainty in real estate market analysis. Even real estate market research, which is carried out as an industry practice among private real estate researches, is no exception. Another reason is that it has been widely accepted that while the financial revolution has substantially changed many sectors of the financial industry, it has made little impact on real estate development and investment practice as Ill as scholastic work. Furthermore, while it is readily acknowledged that despite its huge share in the world Ialth, real estate investment discipline and research is on the whole still a poorly researched subject area. As a result, the industry tends to be dominated by traditional real estate analysts with little understanding of real estate market uncertainty and capital markets. These commentators are widely regarded to spend too much time worrying about local space supply and demand conditions, while totally losing sight of the everchanging real estate market and capital market conditions. The theme of this book is real estate investment analysis of direct and indirect real, which in turn can be appropriately managed under economic theory and the theoretical conceptions of real estate finance, provided the uncertainty is quantifiable. The book deploys case studies involving Singapore and Asia. This Black over White background viii framework enables real estate market analysis to attempt what defines the Asian direct and indirect real estate sectors; what is being measured; how it behaves (in terms of price and non-price factors); how it is structured and how it effectively achieves the objectives of sustainable total returns and manageable real estate market uncertainty. Managing real estate market uncertainty optimally is achieved at the portfolio level through real estate asset allocation. This is important because the real estate portfolio is able to virtually eliminate the unique (i.e. specific) uncertainties among the various Asian real estate sectors; thus retaining within the portfolio only the systemic (i.e. market-wide) uncertainty. Apart from real estate asset allocation, the alternative and modern approach to risk management at the portfolio level, is the value-at-risk (VaR) approach. Another modern and important alternative to coping with uncertainty is real option analysis and pricing that help to better define real estate market uncertainty in extent and time. Real option analysis and pricing also represent uncertainty via a decision tree and the risk-neutral probability conception, in order to comprehend how uncertainty impacts on the value of real estate investment decisions. The pricing of uncertainty is based on the risk-free hedge security conception. These are best examined at the micro level of the investment in a real estate development opportunity on vacant land. Nevertheless, the real estate sectors in Singapore and Asia offer promising prospects since the Asian currency crisis of 1997. It is now timely to take stock and make an assessment of how the sectors would pan out for the future, Ill into at least rest the next century. I are very pleased to present our thinking and research in international real estate with particular emphasis on Asia. The region’s vast potential for real estate is itself a large incentive for international real estate research and education that has inspired me to document the significant work I have done over the years. Black over White background ix I wish all readers a pleasurable reading of this book, and I thank you sincerely for your support without which the publication of this book would be made all the more difficult. Dr HO, Kim Hin / David Honorary Professor (University of Hertfordshire, UK) (International Real Estate & Public Policy) March 2021.

This book introduces three innovative concepts and associated financial instruments with the potential to revolutionise real estate finance. The factorisation of commercial real estate with factor-based real estate derivatives is the first concept analysed in this book. Methodological issues pertaining to factors in real estate risk analysis are covered in detail with in-depth academic reference. The book then analyses the digitalisation of commercial real estate. The environment in which buildings operate is changing fast. Cities which used to be made up of inanimate architectural structures are growing digital skins and becoming smarter. Smart technologies applied to the built environment are fundamentally changing buildings’ role in cities and their interactions with their occupants. The book introduces the concept of smart space and analyses the emergence of ‘digital rights’ or property rights for smart buildings in smart environments. It proposes concepts and methods for identifying, pricing, and trading these new property rights which will dominate commercial real estate in the future. Finally, the tokenisation of commercial real estate is explored. Sometimes described as an alternative to securitisation, tokenisation is a new tool in financial engineering applied to real assets. The book suggests two innovative applications of tokenisation: private commercial real estate index tokenisation and data tokens for smart buildings. With factorisation, digitalisation, and tokenisation, commercial real estate is at the forefront of innovations. Real estate’s unique characteristics, stemming from its physicality, trigger new ways of thinking which might have a profound impact on other asset classes by paving the way for micro markets. Factor-based property derivatives, digital rights, and tokens embody how commercial real estate can push the boundaries of modern capitalism and, in doing so, move at the centre of tomorrow’s smart economies. This book is essential reading for all real estate, finance, and smart technology researchers and interested professionals.

This book is concerned with the unique findings, contributions and recommendations made on several crucial issues, relating to the concomitant subjects of direct real estate (DRE) risk premiums and DRE risk management. Chapter 1 examines the institutional nature of legal origin and the total returns (TRs), from investing in a country’s DRE and via the adoption of a multi-factor arbitrage pricing theory (APT) model. Chapter 2 affirms the true historical volatility to be a reasonable estimation of international DRE risk premiums, when the autoregressive lag orders of the de-smoothed returns and the multi-factor model are taken into account. Chapter 3’s real world of international DRE investing counts on sustainable international DRE investing, imperative for the investing organization’s willingness and preparedness to effectively manage risk or uncertainty, early enough as part of the risk management cycle, in pursuing high risk-adjusted TRs for DRE assets. Chapter 4 recommends a model of the intuitive build-up approach of forming the DRE investment hurdle rates for new DRE investing. The resultant DRE risk premiums serve a rough guide to ensure that the DRE hurdle rate is stringent and high enough, to achieve the risk-adjusted and Sharpe-optimal portfolio TR. Chapter 5 examines the integrated DRE investment strategy for a 13-city Pan Asia DRE portfolio, of office, industrial real estate and public listed DRE companies, adopting the analytic hierarchy process (AHP) and the Markowitz quadratic programming models. Such models enable the versatile strategic asset (SAA) and the tactical asset (TAA) allocations. Chapter 6 enables the DRE institutional investor to achieve a comprehensive and in-depth return and risk assessment at the DRE level for the 4 prime Asia residential sectors of Shanghai (SH), Beijing (BJ), Bangkok (BK), and Kuala Lumpur (KL), under the DRE VaR, incremental DRE VaR and the risk-adjusted return on capital (RAROC), Chapter 7 reiterates that public policies on macroeconomic management have to be consistent and non-conflicting in a widely accepted ‘policy compact’. It is because the policies reinforce the fundamental investment value of large and complex developments, affecting the sustainable viability like the integrated resort (IR)-at-Marina-Bay, Singapore. Chapter 8 draws attention to the aftermath of the Asian economic crisis, terrorism and viral epidemics, that compel more DRE investors to risk-diversify their operations beyond their primary market into other parts of Asia. However, limited studies examine risk-reduction diversification strategies via split returns i.e. decomposing TRs into rental-yield returns and capital value (CV) returns. Chapter 9 proposes and recommends the intelligent building (IB) framework, via the fuzzy logic (FL) engine, leading to a robust measure of building intelligence, and a standard guideline for a consistent performance-based structure for the promotion of the correct IB classification.

Represents the culmination of 30 years research in financial astrology. Williams share the techniques he used to score an 80 percent accuracy rating in predicting the ups & downs of the U.S. economy. Astrological concepts have been incorporated into a method, which does not require any previous astrological or stock market knowledge.