The Effect of Alternative Return Measures on Restricted Mixed-Asset Portfolios

A restricted portfolio is constructed which includes NYSE common stocks, corporate bonds, government bonds, small capitalization common stocks, residential real estate and farmland and returns for each of four different tax brackets (0%, 15%, 30%, 45%). Next, three alternative measures of rates of return for residential real estate and farmland are used. Finally, since some researchers believe that standard risk measures (variance and standard deviation) do not capture the total risk in real estate, the risk for the real estate returns is increased five times while the returns are held constant. The twenty–four optimal portfolios (four tax brackets with two measures of risk and three measure of return for residential real estate and farmland) are then derived. These results are then compared and contrasted to each other to ascertain the change in sensitivity of the optimal portfolios due to different tax rates, different rates–of–return estimates and different risk estimates.     

REIT-Based Pure-Play Portfolios: The Case of Property Types

This article explores a technique for constructing REIT-based pure-play portfolios which replicate the performance of target real estate sectors without direct exposure to non-target sectors. The construction of pure-play portfolios uses a combination of long and short positions, and does not require time-series data for the target sectors. Pure-play portfolios may be useful for hedging, speculation, building custom-designed balanced portfolios, calculating betas for capital budgeting and developing historical performance indices. Performance indices for the four major commercial property-type sectors are presented in this paper. REIT-based sectoral returns are then compared with NCREIF-based returns by property type.     

Gains From Diversifying Into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model

This paper compares the investment policies and returns for portfolios of stocks and bonds with and without up to three categories of real estate. Both domestic and global settings are examined, with and without the possibility of leverage. The portfolios were generated via the dynamic investment model based on the empirical probability assessment approach applied to past (joint) realizations of returns, both with and without correction for "smoothing" in the real estate data series. Our principal findings are: (1) the gains from adding real estate, on a semi-passive (equal-weighted) basis, to portfolios of either U.S. or global financial assets were relatively modest; in contrast, (2) the gains from adding real estate to the universe of U.S. financial assets under an active strategy were rather large (in some cases highly statistically significant), especially for the very risk-averse strategies; (3) the gains from adding U.S. real estate to a universe of global financial assets under an active strategy were mixed, although generally favorable for the highly risk-averse strategies; (4) correcting for second-moment smoothing in the real estate returns series had a relatively small impact for the more risk-tolerant strategies; and (5) there was some evidence that desmoothing resulted in improved probability estimates.     

A Test of a Buying Rule for "Underpriced" Apartment Buildings

Apartment-building repeat-sales data are used to test a trading rule. Property values are estimated through regression; if the actual price is less than the estimated value, the property may be "undervalued." Returns are calculated for these "undervalued" properties and adjusted for risk using the Sharpe ratio. A test is done of whether these ratios are significantly different for different portfolios. The "undervalued" properties have higher appreciation returns, but once these are adjusted for risk, the differences in returns are not significant. The paper contributes to the real estate efficiency literature and suggests a workable method for comparing the performance of real estate portfolios on a risk-adjusted basis.     

Another Take on Real Estate's Role in Mixed‐Asset Portfolio Allocations

This article examines real estate's role in institutional mixed‐asset portfolios using both private‐ and public‐real estate indices, as a means of examining varying real estate‐related risk/return opportunities. In so doing, this article also examines the effects of: (1) increasing the investment horizon, (2) placing constraints on the maximum allocation to any one asset class, and (3) varying the risk preferences of investors. The empirical results suggest—using infinite‐horizon returns and all of the caveats that accompany such a perspective—that real estate allocations of approximately 10–15% of the mixed‐asset portfolio represent an upper bound for most investors. For those investors preferring low‐risk portfolios, (unlevered) private real estate is the vehicle serving this allocation preference; for those investors preferring high‐risk portfolios, public real estate (with its embedded leverage of 40–50%) is the vehicle serving this allocation preference—with such vehicles serving as substitutes for a variety of noncore real estate strategies. In some sense, the distinction between private and public real estate is more about the use of leverage. For those investors preferring moderate‐risk portfolios, an intermediate‐leverage approach seems optimal.     

Historic Returns and Institutional Real Estate Portfolios

This study employs a sample of equity REIT portfolios from 1972–78 to investigate various aspects of real estate returns. Return estimates are derived for the unlevered cash yields by property size, type and location. Based on these data, the effects of certain kinds of diversification on risk-adjusted returns are examined. Finally, historic REIT portfolios are compared to current commingled fund portfolios and suggestions made concerning the benefits of restructuring.     

Portfolio Considerations in the Valuation of Real Estate

When a real asset rises in price faster than inflation (as real estate did in the late 1970s) and rises significantly in price over an extended period (as real estate has done for the last decade and one-half), it concerns valuation and investment professionals who fear about it being over-valued. One of the reasons for such price performance may be an increase in demand due to the portfolio characteristics of the asset during the period of time in question. For real estate this means the proportion included in optimal portfolios should be significant and increasing as individual tax rates increase in an environment of increasing average tax rates.
This study uses six tax brackets (0%, 10%, 20%, 30%, 40%, 50%) and portfolios consisting of three traditional assets (NYSE common stocks, corporate bonds and small stocks) plus three types of real estate (residential, business and farmland) to demonstrate that this is what has transpired in the real estate markets. Optimal portfolio weights are derived for each asset for after-tax portfolios. Real estate in general and residential real estate especially increased as a proportion of the optimal after-tax portfolio as individual tax rates increased. Other studies are used to demonstrate an environment of increasing average tax rates.     

Diversification Benefits of REIT Preferred and Common Stock: New Evidence from a Utility‐based Framework

We study the diversification benefits of REIT preferred and common stock using a utility‐based framework in which investors segment based on risk aversion. We examine optimal mean‐variance portfolios of investors with different levels of risk aversion given access to different classes of assets and establish three main results. First, REIT common stock helps low risk aversion investors attain portfolios with higher returns, while REIT preferred stock helps high risk aversion investors by providing a venue for risk reduction. Second, REIT preferred stock has a risk‐return profile not easily replicated by other asset classes. Finally, conclusions drawn from the empirical analysis are markedly different under these constraints compared to the classical unconstrained setting.     

The Performance of Commercial Mortgages

This study examines the return characteristics of a large, well-diversified commercial mortgage portfolio. Mortgage-specific cash-flow histories are constructed for 2,480 loans originated over the period 1974 through 1990, and a contingent-claims approach to pricing risky debt is used to estimate inter-temporal market values. Quarterly holding-period returns are compared across selected mortgage groups and to alternate asset classes. Our findings suggest that both mortgage returns and volatility of return are comparable to those of other forms of fixed-income assets over the study period. Implied property price volatility is found to average 17%, a result significantly higher than reported in earlier studies. While mortgage returns are found to vary by property type and region of origin, cross correlation of returns is found to be high, illustrating the systematic effect of interest rates on the performance of commercial mortgages over the period 1974 through 1990. However, an increase in credit risk in the latter years of the study suggests that diversification may be a worthwhile objective for holders of these assets. We do not find evidence to suggest that abnormal returns were earned on commercial mortgage portfolios over the study period.     

The Fractal Structure of Real Estate Investment Trust Returns: The Search for Evidence of Market Segmentation and Nonlinear Dependency

This article presents a further test for market segmentation between the real estate market and the capital markets. We use rescaled range analysis developed in the fractal geometry literature to test for nonlinear trends in the returns series for different asset classes. We make three major conclusions: (1) the stock market displays tendencies consistent with a random walk, (2) portfolios of mortgage and equity REIT returns display tendencies consistent with a random walk and, (3) conditional upon the methods used, segmentation does not exist between different real estate markets and between the real estate and stock markets.     

The Impact of Market Imperfections on Real Estate Returns and Optimal Investor Portfolios

This study investigates the consequences of several imperfections associated with real estate markets on pricing and optimal investor portfolios from a CAPM context. CAPM assumptions are relaxed to recognize illiquidity, the consumption and investment attributes of owner-occupied housing, and a mildly segmented market structure. The study finds that relaxing the CAPM assumptions lead to a separate pricing paradigm for financial assets, income-producing real estate and owner-occupied housing respectively, that a "dividend effect" arises for real estate as the result of illiquidity, and that illiquidity reduces the extent to which investors hold real estate in their portfolios.     

Do Common Risk Factors in the Returns on Stocks and Bonds Explain Returns on REITs?

The monthly returns on equity and mortgage real estate investment trusts (REITs) are analyzed over the period July 1976 to December 1992. The results indicate that risk premiums on equity REITs are significantly related to risk premiums on a market portfolio of stocks as well as to the returns on mimicking portfolios for size and book-to-market equity factors in common stock returns. Mortgage REIT risk premiums are significantly related to the three stock market factors and two bond market factors in returns. Also, mortgage REIT shares underperform by an average of 6.8% per year.     

Time and Risk Diversification in Real Estate Investments: Assessing the Ex Post Economic Value

Welfare gains to long-horizon investors may derive from time diversification that exploits nonzero intertemporal return correlations associated with predictable returns. Real estate may thus become more desirable if its returns are negatively serially correlated. While it could be important for long-horizon investors, time diversification has been mostly investigated in asset menus without real estate and focusing on in-sample experiments. This article evaluates, ex post, the out-of-sample gains from diversification when equity real estate investment trusts (REITs) belong to the investment opportunity set. We find that diversification into REITs increases both the Sharpe ratio and the certainty equivalent of wealth for all investment horizons and for both classical and Bayesian (who account for parameter uncertainty) investors. The increases in Sharpe ratios are often statistically significant. However, the out-of-sample average Sharpe ratio and realized expected utility of long-horizon portfolios are frequently lower than that of a one-period portfolio, which casts doubt on the value of time diversification.     

Continental Factors in International Real Estate Returns

This paper examines the extent to which real estate returns are driven by continental factors. This subject is relevant for determining the country allocation of international real estate portfolios. If returns are driven by a continental factor, investors should look for diversification opportunities outside their own continent. This paper finds strong continental factors in North America and especially in the United States. For the Asia–Pacific region, real estate returns are not driven by a continental factor. The results suggest that, for European, North American and Asia—Pacific real estate portfolio managers, the Asia—Pacific region provides attractive international diversification opportunities.     

Crypto-assets portfolio optimization under the omega measure

Abstract

Crypto-currencies, or crypto-assets, represent a new class of investment assets. The traditional portfolio analysis approach of Markowitz is not appropriate for use with portfolios containing crypto-assets, as the model requires that the investor have a quadratic utility function or that the returns be normally distributed, which isn’t the case for crypto-assets. We develop a portfolio optimization model based on the Omega measure which is more comprehensive than the Markowitz model, and apply this to four crypto-asset investment portfolios by means of a numerical application. The results indicate that these portfolios should favor traditional market assets over crypto-assets. In the case of portfolios formed only by crypto-assets, there is no clear preference in favor of any crypto-asset in particular.     

Asset Location,Timing Ability and the Cross‐Section of Commercial Real Estate Returns

This study examines the sensitivity of equity REIT returns to time‐varying MSA allocations of REIT property portfolios. Using a large sample of individual commercial property holdings, we find significant cross‐sectional and time variation in REIT geographic exposures and the ability of these exposures to explain the cross‐section of REIT returns. We further find evidence consistent with REIT managers being able, on average, to time allocation decisions ahead of MSA outperformance. This effect is most prevalent in non‐gateway markets, varies significantly across MSAs and over time, and is concentrated in financially flexible firms with a more diversified geographic portfolio.     

Returns and Information Transmission Dynamics in Public and Private Real Estate Markets

This paper examines U.S. public and private commercial real estate returns at the aggregate level and by the four major property types over the 1994–2012 time period. Returns are carefully adjusted for differences between public and private markets in financial leverage, property type focus and management fees. Unconditionally, we find that passive portfolios of unlevered core real estate investment trusts (REITs) outperformed their private market benchmark by 49 basis points (annualized) over the 1994–2012 sample period. Our baseline vector autoregression results suggest that REIT returns do not embed additional commercial real‐estate‐specific information useful in predicting private market returns. These results strongly suggest that equity REIT returns react to fundamental (latent) asset pricing information more quickly than private market returns given their greater liquidity and price revelation. REITs therefore serve as a fundamental information transmission channel to private market returns when asset pricing variables are omitted.     

Price Signaling and Return Chasing: International Evidence from Maturing REIT Markets

This article examines the liquidity of international real estate securities across 10 markets over the period 1990–2015. We apply and compare results for four different measures of liquidity, and find that while liquidity has increased consistently, wide variations still exist across markets, with the United States and Japan in the lead. Our results also suggest that the introduction of local REIT regimes did not have any pervasive effects on stock liquidity. When we study the relationship between liquidity and returns, we document new and consistent evidence for international return chasing behavior, whose pattern is a function of local market efficiency, listed real estate market maturity and stock ownership dispersion. The introduction of REIT regimes seems to weaken the importance of extra performance over and above general equity returns as investors tend to allocate funds to real estate securities within real estate rather than equity portfolios.     

不可再生资源消耗与内生经济增长：模型与实证

随着中国经济的高速增长，资源对增长的约束日益突出，资源稀缺与巨大需求之间 的矛盾使得增长与资源的关系值得关注。本文在Groth和Schou模型基础上扩展基于不可再生 资源①的内生增长模型，并利用中国1981～2009年数据实证检验持续增长所需要的条件， 最后给出有关资源利用的政策建议.     

Robust future‐oriented technology portfolios: Black–Litterman approach

We propose a new way of constructing more robust technology portfolios to overcome the weaknesses of previous technology portfolios based either on the judgments of experts or on quantitative data such as patents. Instead of using historical data, the method of nonlinear forecasting enables us to forecast the future number of patent citations and accordingly, to use the forecast as a quantitative proxy for future returns and risks of technologies. Using the Black–Litterman portfolio model, we improve the accuracy of inputs by combining the future views of experts with the future returns and risks of technologies. As a consequence of this, the portfolio becomes strongly future‐oriented. With our approach, corporate managers use both experts and data more effectively to build robust technology portfolios. In particular, our method is of great help for companies launching new businesses because the method avoids heavy dependency on internal experts with little knowledge about emerging technologies. A company entering the molecular amplification instrument market is exemplified herein.