Investing for the Long Run when Returns Are Predictable

We examine how the evidence of predictability in asset returns affects optimal portfolio choice for investors with long horizons. Particular attention is paid to estimation risk, or uncertainty about the true values of model parameters. We find that even after incorporating parameter uncertainty, there is enough predictability in returns to make investors allocate substantially more to stocks, the longer their horizon. Moreover, the weak statistical significance of the evidence for predictability makes it important to take estimation risk into account; a long-horizon investor who ignores it may overallocate to stocks by a sizeable amount.     

Optimal portfolio choice in real terms: Measuring the benefits of TIPS

In this paper we solve an optimal portfolio choice problem to measure the benefits of Treasury Inflation Indexed Securities (TIPS) to investors concerned with maximizing real wealth. We show how the introduction of a real riskless asset completes the investor asset space, by contrasting optimal portfolio allocations with and without such assets. We use historical data to quantify gains from availability of TIPS in the presence of other asset classes such as equities, commodities, and real estate. We draw a distinction between buy-and-hold long-term investors for whom TIPS fully displace nominal risk-free assets and short-term investors for whom TIPS improve the investment opportunity set of real returns. Finally, we show how gains from TIPS are tempered by the availability of alternative assets that covary with inflation, such as gold and real estate.     

Marketing Period Risk in a Portfolio Context: Theory and Empirical Estimates from the UK Commercial Real Estate Market

The role of selling (or marketing) period uncertainty in understanding risk associated with property investment is examined in this paper. Using an approach developed by Lin (2004), and Lin and Vandell (2001, 2005), combined with a statistical model of UK commercial property transactions, we show that the ex ante level of risk exposure for a commercial real estate investor is around one and a half times that obtained from historical statistics. The risk related to marketing time uncertainty can be reduced by constructing a portfolio. We find that at least ten properties are necessary to reduce this risk, assuming independence between marketing period risk and price risk. These findings have important implications for mixed-asset portfolio allocation decisions.      

A multivariate model of strategic asset allocation

We develop an approximate solution method for the optimal consumption and portfolio choice problem of an infinitely long-lived investor with Epstein–Zin utility who faces a set of asset returns described by a vector autoregression in returns and state variables. Empirical estimates in long-run annual and post-war quarterly U.S. data suggest that the predictability of stock returns greatly increases the optimal demand for stocks. The role of nominal bonds in long-term portfolios depends on the importance of real interest rate risk relative to other sources of risk. Long-term inflation-indexed bonds greatly increase the utility of conservative investors.     

Polynomial goal programming and the implicit higher moment preferences of US institutional investors in hedge funds

Polynomial goal programming (PGP) is a flexible method that allows investor preferences for different moments of the return distribution of financial assets to be included in the portfolio optimization. The method is intuitive and particularly suitable for incorporating investor preferences in higher moments of the return distribution. However, until now, PGP has not been able to meet its full potential because it requires quantification of “real” preference parameters towards those moments. To date, the chosen preference parameters have been selected somewhat “arbitrarily”. Our goal is to calculate implied sets of preference parameters using investors’ choices of and the importance they attribute to risk and performance measures. We use three groups of institutional investors—pension funds, insurance companies, and endowments—and derive implied sets of preference parameters in the context of a hedge fund portfolio optimization. To determine “real” preferences for the higher moments of the portfolio return distribution, we first fit implied preference parameters so that the PGP optimal portfolio is identical to the desired hedge fund portfolio. With the obtained economically justified sets of preference parameters, the well-established PGP framework can be employed more efficiently to derive allocations that satisfy institutional investor expectations for hedge fund investments. Furthermore, the implied preference parameters enable fund of hedge fund managers and other investment managers to derive optimal portfolio allocations based on specific investor expectations. Moreover, the importance of individual moments, as well as their marginal rates of substitution, can be assessed.     

Are Securitized Real Estate Returns more Predictable than Stock Returns?

This paper examines whether the predictability of securitized real estate returns differs from that of stock returns. It also provides a cross-country comparison of securitized real estate return predictability. In contrast to most of the literature on this issue, the analysis is not based on a multifactor asset pricing framework as such analyses may bias the results. We use a time series approach and thus create a level playing field to compare the predictability of the two asset classes. Forecasts are performed with ARMA and ARMA–EGARCH models and evaluated by comparing the entire empirical distributions of prediction errors, as well as with a trading strategy. The results, based on daily data for the 1990–2007 period, show that securitized real estate returns are generally more predictable than stock returns in countries with mature and well established REIT regimes. ARMA–EGARCH models are found to have portfolio outperformance potential even in the presence of transaction costs, with generally better results for securitized real estate than for stocks.     

Risk and return in residential spatial markets: An empiric and theoretic model

The paper is concerned with price and rent fluctuations in predominantly owner-occupied residental real estate. It presents the owner-occupier household as a housing consumer as well as an investor. It conjectures that since risk and return are known to be positively related in financial markets, they might also be thus related in residential real estate markets. If that is so, neighborhoods that are known to yield high returns will be the ones less price and rent stable than low yielding ones.The Capital Asset Pricing Model is not helpful in explaining a possible risk/return relationship in housing markets. Its major assumption about portfolio diversification is contrary to the nature of owner-occupied residential real estate. An owner occupier household, by definition, holds one unit of the asset and acts simultaneously as an investor and consumer of housing. For the capital market investor, investment and consumption decisions are separable. Therefore, a new theoretical model of consumer choice is proposed. Tel-Aviv price and rent data during a volatile market period are used for testing the main risk/return conjecture as well as other related hypotheses stemming from the model. The findings lend support to the conjecture and shed light on possible spatial determinants of owners' risk.     

Optimal Time to Sell in Real Estate Portfolio Management

This paper examines the properties of optimal times to sell a diversified real estate portfolio. The portfolio value is supposed to be the sum of the discounted free cash flows and the discounted terminal value (the discounted selling price). According to Baroni et al. (Journal of Property Investment and Finance 25(6):603–625, 2007b), we assume that the terminal value corresponds to the real estate index. The optimization problem corresponds to the maximization of a quasi-linear utility function. We consider three cases. The first one assumes that the investor knows the probability distribution of the real estate index. However, at the initial time, he has to choose one deterministic optimal time to sell. The second one considers an investor who is perfectly informed about the market dynamics. Whatever the random event that generates the path, he knows the entire path from the beginning. Then, given the realization of the random variable, the path is deterministic for this investor. Therefore, at the initial time, he can determine the optimal time to sell for each path of the index. Finally, the last case is devoted to the analysis of the intertemporal optimization, based on the American option approach. We compute the optimal solution for each of these three cases and compare their properties. The comparison is also made with the buy-and-hold strategy.

An analysis of the impact of timberland, farmland and commercial real estate in the asset allocation decisions of institutional investors

We examine the effects of including timberland, farmland and commercial real estate in a mixed asset portfolio with stocks, government bonds and T-Bills. Using both smoothed and unsmoothed returns (as per Geltner [Geltner, D. (1993). Estimating market values from appraised values without assuming an efficient market. Journal of Real Estate Research, 8, 25-345.]) and both constrained and unconstrained allocation assumptions (as per Eichhorn, Gupta and Stubbs [Eichhorn, D., Gupta, F., & Stubbs, E. (1998). Using constraints to improve the robustness of asset allocation. Journal of Portfolio Management, Spring, 41-48.]), we employ Markowitz portfolio optimization and find widely varying allocation outcomes. However, timberland entered nearly all portfolios, accounting for large percentages in several scenarios, while farmland entered only low-risk portfolios. At lower risk levels, commercial real estate dominates the real estate allocation but as acceptable risk levels rise, timberland supplants commercial real estate as the primary component of the portfolio's real estate allocation.     

International diversification with securitized real estate and the veiling glare from currency risk

This paper analyzes diversification benefits from international securitized real estate in a mixed-asset context. We apply regression-based mean-variance efficiency tests, conditional on currency-unhedged and fully hedged portfolios to account for systematic foreign exchange movements. From the perspective of a US investor, it is shown that, first, international diversification is superior to a US mixed-asset portfolio, second, adding international real estate to an already internationally diversified stock and bond portfolio results in a further significant improvement of the risk-return trade-off and, third, considering unhedged international assets could lead to biased asset allocation decisions not realizing the true diversification benefits from international assets.     

Asymmetric Information and the Predictability of Real Estate Returns

This article examines the relation between systematic price changes and the heterogeneity of investors information sets in real estate asset markets. The empirical implications rely on a theoretical economy in which information asymmetry alters the dynamic relation between returns and trading volume. We employ a filter-rule methodology to determine predictability in returns and augment the return-based conditioning set with trading volume. The additional conditioning information is necessary since the model is underspecified when predictability is based on returns alone. Our results provide new insight into the coexistence of informational and noninformational exchange in the speculative markets for real estate assets. Specifically, we find that the predictability of real estate returns is generally more indicative of portfolio rebalancing effects than an adverse-selection problem. These results are unique in addressing the time-variation in information asymmetry.     

Multiple Regimes and Volatility Transmission in Securitized Real Estate Markets

We examine the dynamics and transmission of conditional volatilities with multiple structural changes in return volatility using Bai and Perron (2003)’s methodology, across five major securitized real estate markets as well as employing a multivariate regime-dependent asymmetric dynamic covariance methodology (MRDADC) that allows the conditional matrix to be both time- and state-varying. Our results imply that a multiple-regime time varying asymmetric variance and covariance approach is important in modeling real estate securities valuation and selection and portfolio optimization, and is consistent with popular beliefs that market volatility changes over time. Our MRDADC models detect the presence of significant mean-volatility linkages across the five major securitized real estate markets under different volatility regimes and would have implications for global investor in terms of estimating a dynamic risk-minimizing hedge ratio in international portfolio management.     

HARA utility maximization in a Markov-switching bond–stock market

We present a flexible multidimensional bond–stock model incorporating regime switching, a stochastic short rate and further stochastic factors, such as stochastic asset covariance. In this framework we consider an investor whose risk preferences are characterized by the hyperbolic absolute risk-aversion utility function and solve the problem of optimizing the expected utility from her terminal wealth. For the optimal portfolio we obtain a constant-proportion portfolio insurance-type strategy with a Markov-switching stochastic multiplier and prove that it assures a lower bound on the terminal wealth. Explicit and easy-to-use verification theorems are proven. Furthermore, we apply the results to a specific model. We estimate the model parameters and test the performance of the derived optimal strategy using real data. The influence of the investor’s risk preferences and the model parameters on the portfolio is studied in detail. A comparison to the results with the power utility function is also provided.     

Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation

This paper examines the effects of uncertainty about the stock return predictability on optimal dynamic portfolio choice in a continuous time setting for a long-horizon investor. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a state-dependent relation between the optimal portfolio choice and the investment horizon. There is substantial market timing in the optimal hedge demands, which is caused by stochastic covariance between stock return and dynamic learning. The opportunity cost of ignoring predictability or learning is found to be quite substantial.     

Sequential Learning,Predictability, and Optimal Portfolio Returns

This paper finds statistically and economically significant out‐of‐sample portfolio benefits for an investor who uses models of return predictability when forming optimal portfolios. Investors must account for estimation risk, and incorporate an ensemble of important features, including time‐varying volatility, and time‐varying expected returns driven by payout yield measures that include share repurchase and issuance. Prior research documents a lack of benefits to return predictability, and our results suggest that this is largely due to omitting time‐varying volatility and estimation risk. We also document the sequential process of investors learning about parameters, state variables, and models as new data arrive.     

The Role of Real Estate in an Institutional Investor's Portfolio Revisited

Many papers have recently pointed out that institutional investors allocate only a very small fraction of their portfolio to real estate, much smaller than theory would dictate. This raises the question, are institutional investors underinvested in real estate equities? Or do we simply have the wrong priors? This paper is an attempt to provide some new insights into this asset allocation paradox. The key conclusions of the paper are several: First, unlike other assets, it would appear that real estate, and real estate diversification, pays off at the very time when the benefits are most needed, that is, when consumption growth opportunities are low. Second, real estate returns are predictable. In fact, the amount of predictability in real estate returns appears to be about the same as in stock returns. Third, real estate performs well in an asset-liability framework. Fourth, the chance of experiencing a large loss on real estate over a long horizon is quite small. We also report here that private sector commercial real estate investments represent between 6 and 12 percent of investable wealth in the United States. Thus, it follows (if one believes the capital asset pricing model) that if institutional investors were to invest more in real estate (up to 12 percent of their assets), they should be able to eliminate nonmarket or unique risk. All of this leaves us a bit dumbfounded as to why institutional investors hold only between 2 and 3 percent of their assets in real estate.     

On the Predictability of Stock Returns: An Asset-Allocation Perspective

Sample evidence about the predictability of monthly stock returns is considered from the perspective of a risk-averse Bayesian investor who must allocate funds between stocks and cash. The investor uses the sample evidence to update prior beliefs about the parameters in a regression of stock returns on a set of predictive variables. The regression relation can seem weak when described by usual statistical measures, but the current values of the predictive variables can exert a substantial influence on the investor's portfolio decision, even when the investor's prior beliefs are weighted against predictability.     

A Benchmark Approach to Portfolio Optimization under Partial Information

This paper proposes a filtering methodology for portfolio optimization when some factors of the underlying model are only partially observed. The level of information is given by the observed quantities that are here supposed to be the primary securities and empirical log-price covariations. For a given level of information we determine the growth optimal portfolio, identify locally optimal portfolios that are located on a corresponding Markowitz efficient frontier and present an approach for expected utility maximization. We also present an expected utility indifference pricing approach under partial information for the pricing of nonreplicable contracts. This results in a real world pricing formula under partial information that turns out to be independent of the subjective utility of the investor and for which an equivalent risk neutral probability measure need not exist.      

Assessing the Economic Significance of Return Predictability: A Research Note

The predictability of stock returns is often assessed using classical statistical significance from predictive regressions. Statistical inference, however, can belie the economic importance with which investors regard various predictors. This paper examines the influence that predictors have on an investor's optimal portfolio allocations. The results show that return predictability is sufficient to induce horizon effects in optimal allocations. After incorporating estimation risk, however, little evidence of predictability remains. We also assess the relative importance of three predictor variables. While dividend yield is the most important predictor, optimal allocations are also sensitive to the term spread and the relative bill rate.     

Portfolio selection and skewness: Evidence from international stock markets

This paper finds that the returns of the world's 14 major stock markets are not normally distributed, and that the correlation matrix of these stock markets was stable during the January 1988–December 1993 time period. Polynomial goal programming, in which investor preferences for skewness can be incorporated, is utilized to determine the optimal portfolio consisting of the choices of 14 international stock indexes. The empirical findings suggest that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of the optimal portfolio. The evidence also indicate that investors trade expected return of the portfolio for skewness.