Abstract: This paper examines whether information overload might partially explain why defined contribution plan participants tend to follow the "path of least resistance" (Choi et al. [2002]) In two experiments, we test how three common differences among defined contribution plans (the number of investment choices offered, the similarity of the choices, and the display of the choices) lead to varying degrees of information overload and the probability of opting for the default. Notably, we control for the financial aptitude of each individual. The findings suggest that the success of certain plan features depends strongly on the financial background of the participant. We find that low-knowledge individuals opt for the default allocation more often than high-knowledge individuals (experiment 1: 20% versus 2%). The results emphasize the importance of plan design, especially the selection of plan defaults, and the need to improve the financial literacy of participants.

Abstract: We examine whether mutual funds change their names to take advantage of current hot investment styles, and what effects these name changes have on inflows to the funds, and to the funds’ subsequent returns. We find that the year after a fund changes its name to reflect a current hot style, the fund experiences an average cumulative abnormal flow of 28%, with no improvement in performance. The increase in flows is similar across funds whose holdings match the style implied by their new name and those whose holdings do not, suggesting that investors are irrationally influenced by cosmetic effects. MUTUAL FUNDS OFFER A UNIQUE OPPORTUNITY to study the behavior of individual investors via the examination of mutual fund flow data. This is important, since investors’ asset allocation decisions across mutual funds may ultimately affect asset returns. For example, Goetzmann, Massa, and Rouwenhorst (2002) document that factors extracted from the covariance matrix of mutual fund flows provide incremental information beyond broad-based asset class returns in explaining returns in the cross-section. In this paper, we provide striking new evidence of seemingly irrational behavior by mutual fund investors when they allocate assets across mutual funds. We also provide evidence of timing behavior on the part of fund managers who appear to take advantage of the suboptimal behavior of investors. Specifically, we analyze fund flow patterns around conditional name changes in the mutual fund industry. We define conditional name changes as name changes by mutual funds either toward a name of a particular style when the corresponding style premium is up, or away from a name of a particular style when the corresponding style premium is down. We examine what effects these name changes have on the flows in and out of the funds, and the funds’ subsequent returns. To

Abstract: This paper proposes a new tractable approach to solving asset allocation problems in situations with a large number of risky assets which pose problems for standard approaches. Investor preferences are assumed to be defined over moments of the wealth distribution such as its mean, variance, skew and kurtosis. Time-variations in investment opportunities are represented by a flexible regime switching process. In the context of a four-moment international CAPM specification that relates stock returns in five regions to returns on a global market portfolio, we find evidence of distinct bull and bear states. Ignoring regimes, an unhedged US investor’s optimal portfolio is strongly diversified internationally. The presence of regimes in the return distribution leads to a large increase in the investor’s optimal holdings of US stocks as does the introduction of skew and kurtosis preferences. Our paper therefore offers an explanation of the strong home bias observed in US investors’ asset allocation based on regime switching and skew and kurtosis preferences.

Abstract: Managers appear to manipulate firm earnings through their characterizations of pension assets to capital markets and alter investment decisions to justify, and capitalize on, these manipulations. Managers are more aggressive with assumed long-term rates of return when their assumptions have a greater impact on reported earnings. Firms use higher assumed rates of return when they prepare to acquire other firms, when they issue equity, when they are near critical earnings thresholds and when their managers exercise stock options. Changes in assumed returns, in turn, influence pension plan asset allocations. Instrumental variables analysis indicates that 25 basis point increases in assumed rates are associated with 5 percent increases in equity allocations.

Abstract: portfolio allocation. We find that the perceived state probability has a large effect on the optimal asset allocation, particularly at short investment horizons. If ignored, the presence of such regimes gives rise to substantial welfare costs. Parameter estimation uncertainty, while clearly important, does not overturn the conclusion that predictability in the return distribution linked to the presence of bull and bear states has a significant effect on investors' strategic

Abstract: We investigate the implications of time-varying expected return and volatility on asset allocation in a high-dimensional setting We propose a DFMSV model that allows the first two moments of returns to vary over time for a large number of assets We then evaluate the economic significance of the DFMSV model by examining the performance of various dynamic portfolio strategies chosen by mean-variance investors in a universe of 36 stocks We find that the DFMSV dynamic strategies significantly outperform various benchmark strategies out of sample This outperformance is robust to different performance measures, investor's objective functions, time periods, and assets

Abstract: We examine the relation between analyst forecast characteristics and the cost of debt financing Consistent with the view that the information contained in analysts’ forecasts is economically significant across asset classes, we find that analyst activity reduces bond yield spreads We also find that the economic impact of analysts is most pronounced when uncertainty about firm value is highest (ie, those with high idiosyncratic risk) Our results are robust to controls for the amount of private information in equity prices and the level of corporate disclosures Overall, our the results indicate that the information contained in analyst forecasts is valued outside the equity market and provide an additional channel in which better information is associated with a lower cost of capital

Abstract: In this paper, we show how an investor can incorporate uncertainty about expected returns when choosing a mean-variance optimal portfolio. In contrast to the Bayesian approach to estimation error, where there is only a single prior and the investor is neutral to uncertainty, we consider the case where the investor has multiple priors and is averse to uncertainty. We characterize the multiple priors with a confidence interval around the estimated value of expected returns and we model aversion to uncertainty via a minimization over the set of priors. The multi-prior model has several attractive features: One, just like the Bayesian model, it is firmly grounded in decision theory. Two, it is flexible enough to allow for different degrees of uncertainty about expected returns for different subsets of assets, and also about the underlying asset-pricing model generating returns. Three, for several formulations of the multi-prior model we obtain closed-form expressions for the optimal portfolio, and in one special case we prove that the portfolio from the multi-prior model is equivalent to a 'shrinkage' portfolio based on the mean-variance and minimum-variance portfolios, which allows for a transparent comparison with Bayesian portfolios. Finally, we illustrate how to implement the multi-prior model for a fund manager allocating wealth across eight international equity indices; our empirical analysis suggests that allowing for parameter and model uncertainty reduces the fluctuation of portfolio weights over time and improves the out-of-sample performance relative to the mean-variance and Bayesian models.

Abstract: This paper takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty. The shrinkage approach explicitly shows how predictive distributions incorporate data and prior beliefs. It enables us to solve the optimal portfolios for uncertainty-averse investors. Aversion to uncertainty about the CAPM leads investors to hold a portfolio that is not mean-variance efficient for any predictive distribution. However, mean-variance efficient portfolios corresponding to extremely strong beliefs in the Fama-French model are approximately optimal for uncertainty-averse investors. The empirical Bayes approach does not deliver optimal portfolios when investors are averse to uncertainty. Uncertainty aversion does not justify U.S. investors’ home bias, and diversification benefit is robust to uncertainty about the world CAPM.

Abstract: Are excess returns predictable and if so, what does this mean for investors? Previous literature has tended toward two polar viewpoints: that predictability is useful only if the statistical evidence for it is incontrovertible, or that predictability should affect portfolio choice, even if the evidence is weak according to conventional measures. This paper models an intermediate view: that both data and theory are useful for decision-making. We investigate optimal portfolio choice for an investor who is skeptical about the amount of predictability in the data. Skepticism is modeled as an informative prior over the improvement in the Sharpe ratio generated by using the predictor variable. We find that the evidence is sufficient to convince even an investor with a highly skeptical prior to vary his portfolio on the basis of the dividend-price ratio and the yield spread. The resulting weights are less volatile, and, as we show, deliver superior out-of-sample performance compared with weights implied by diffuse priors, dogmatic priors, and ordinary least squares regression.

Abstract: The US housing market has experienced significant cyclical volatility over the last twenty-five years due to major structural changes and economic fluctuations In addition, the housing market is generally considered to be weak form inefficient Houses are relatively illiquid, exceptionally heterogeneous, and are associated with large transactions costs As such, past research has shown that it is possible to predict, at least partially, the time path of housing prices The ability to predict housing prices is important such that investors can make better asset allocation decisions, including the pricing and underwriting of mortgages Most of the prior studies examining the US housing market have employed constant coefficient approaches to forecast house price movements However, this approach is not optimal as an examination of data reveals substantial sub-sample parameter instability To account for the parameter instability, we employ alternative estimation methodologies where the estimated parameters are allowed to vary over time The results provide strong empirical evidence in favor of utilizing the rolling Generalized Autoregressive Conditional Heteroskedastic (GARCH) Model and the Kalman Filter with an Autoregressive Presentation (KAR) for the parameters’ time variation Lastly, we provide out-of-sample forecasts and demonstrate the precision of our approach

Abstract: In sharp contrast to the recommendations of Modern Portfolio Theory, a vast majority of investors are not well diversified. The author attempts to provide a solution to this diversification paradox, by expanding the Markowitz framework of diversifying market risk to also include the concepts of personal risk and aspirational goals. The wealth allocation framework enables individual investors to construct appropriate portfolios using all their assets, such as their home, mortgage, market investments, and human capital. The investor may choose to accept a slightly lower average rate of return in exchange for downside protection and upside potential. The resulting portfolios are designed to meet individual investors9 needs and preferences, as well as to protect individuals from personal, market, and aspirational risk factors. A major conclusion of this work is that, for the individual investor, risk allocation should precede asset allocation.

Abstract: Financial markets are highly interdependent and for many decades portfolio managers have scrutinised the comovements between markets. It is regrettable, however, that traditional quantitative portfolio construction still heavily relies on the analysis of correlations for modelling the complex interdependences between financial assets. Admittedly, the application of the concept of correlation has been improved and, over the last ten years, following the generalised use of the JP Morgan (1994) RiskMetrics approach, quantitative portfolio managers have made increasing use of conditional correlations.

Abstract: Classic asset pricing is problematic as a method to assess privately held asset investment performance. We propose an alternative approach that involves adjusting the characteristics of assets constituting an index or portfolio to match the asset characteristics of a reference index or portfolio. This approach is applied to commercial real estate, where we create an index of REIT returns to compare to the NCREIF index. To enhance comparability, return indices are adjusted for partial-year financial data, leverage, asset mix and fees. Adjusted results over a 1980–1998 sample period show general convergence between the indices, although an annual return difference of over three percentage points remains in favor of public market asset ownership. Possible causes of the investment performance gap include liquidity and geography as missing risk factor adjustments, an unrepresentative sample period, and the form in which commercial real estate assets are held.

Abstract: This study analyzes the economic importance of portfolio advice for an investor with an international and multiple-asset investment strategy. We construct portfolios based upon the asset allocation and security market advice of major international investment bankers and analyze the performance using weight-based techniques. Our results indicate that portfolio advisers are not able to outperform passive benchmarks. They do not realize superior performance either through appropriate timing or selection skills. Apparent market timing skills as measured by the Portfolio Change Measure are to a large extent an artifact caused by serial correlation in the return indices used. Likewise, the apparent short-run performance persistence is more due to the serial correlation in returns than to active portfolio selection strategies.

Abstract: The paper presents a framework for analyzing the degree of financial transmission between money, bond and equity markets and exchange rates within and between the United States and the euro area. We find that asset prices react strongest to other domestic asset price shocks, and that there are also substantial international spillovers, both within and across asset classes. The results underline the dominance of US markets as the main driver of global financial markets: US financial markets explain, on average, more than 25% of movements in euro area financial markets, whereas euro area markets account only for about 8% of US asset price changes. The international propagation of shocks is strengthened in times of recession, and has most likely changed in recent years: prior to EMU, the paper finds smaller international spillovers. JEL Classification: E44, F3, C5

Abstract: We investigate multiperiod portfolio selection problems in a Black & Scholes type market where a basket of 1 riskfree and m risky securities are traded continuously. We look for the optimal allocation of wealth within the class of ’constant mix’ portfolios. First, we consider the portfolio selection problem of a decision maker who invests money at predetermined points in time in order to obtain a target capital at the end of the time period under consideration. A second problem concerns a decision maker who invests some amount of money (the initial wealth or provision) in order to be able to fullfil a series of future consumptions or payment obligations. Several optimality criteria and their interpretation within Yaari’s dual theory of choice under risk are presented. For both selection problems, we propose accurate approximations based on the concept of comonotonicity, as studied in Dhaene, Denuit, Goovaerts, Kaas & Vyncke (2002 a,b). Our analytical approach avoids simulation, and hence reduces the computing effort drastically.

Abstract: We empirically examines the financial portfolio choice of households as a function of their exposure to real estate risk as a possible background risk. Using Panel Study of Income Dynamics data from 1984 to 2001, our estimation results control for sample selection and unobservable time-invariant heterogeneity in an environment of non-strictly exogenous explanatory variables. Our analysis finds that larger real estate exposure is correlated with a lower likelihood of stock market participation and with reduced holdings of stocks and other risky financial assets in households' financial asset portfolios. We also measure the variability of homeowners' house values and provide evidence that it is also associated with lower stock market participation and, conditional on participation, lower equity investments.Previous version titled "Real Estate and its Role in Asset Allocation"

Abstract: This paper analyzes the performance of portfolio strategies that invest in no-load, open-end U.S. domestic equity mutual funds, incorporating predictability in (i) manager skills, (ii) fund risk-loadings, and (iii) benchmark returns. Predictability in manager skills is found to be the dominant source of investment profitability -- long-only strategies that incorporate such predictability considerably outperform prior-documented "hot-hands" and "smart-money" strategies, and generate positive and significant performance with respect to the Fama-French and momentum benchmarks. Specifically, these strategies outperform their benchmarks by 2-4% per year through their ability to time industries over the business cycle. Moreover, they choose individual funds that outperform their industry benchmarks to achieve an additional 3-6% per year. Overall, our findings indicate that industries are important in locating outperforming mutual funds, and that active management adds much more value than documented by prior studies.

Abstract: A system and computer-implemented method for graphical display of risk and return information of an investment mix or an investment portfolio based upon investment asset classes from which the investor selects a mix and assigns desired weights for each asset class in the mix. The investor's risk tolerance is dynamically assessed by graphically presenting different risk and return scenarios for a plurality of investment mixes calculated from the selected asset classes and assigned weights. Once a user selects an investment mix commensurate with the investor's risk tolerance, the investor may then enter financial data corresponding to actual investments, transactions of which are tracked in the system and performance evaluated based upon the investor's targeted risk and return values and benchmark funds consistent with the investors investment mix.

Abstract: The year 2000 started the evolution of the German market for Structured Products with incorporated Hedge Fund exposures. This paper provides an extensive commentary on this fast growing segment. Our analysis suggests that the market for existing products is affected by significant heterogeneity. This heterogeneity relates to amongst others the underlying product and cost structure, the performance and the investment style. The diversity and flexibility that enables the investor to acquire a tailor-made and portfolio-optimized asset allocation, has proven to remain attractive, despite the events of recent years. A new investment act ('Investmentmodernisierungsgesetz') was implemented in Germany in 2004. This means that direct investments in (Fund of) Hedge Funds now compete against Structured Products. However our analysis concludes that these product groups coexist. One reason is the innovation power of financial engineers who continuously create new structured products with specific features.

Abstract: Investors often consider Sharpe ratios when making asset allocation decisions and comparing portfolios. Given sampling error in estimated means and variances of returns, promoting Sharpe ratios as useful to help choose between asset allocations or portfolios may be misleading. Estimators of the Sharpe ratio have less helpful distributions than estimators of mean and variance. The error in the estimate of the Sharpe ratio can be simply too large to make useful conclusions. Investors are often overly swayed by historical performance in making investment decisions: why make matters worse by obscuring what information we have by combining past performance characteristics in an unhelpful ratio?

Abstract: This research investigates the persistence of investment risk across time horizon, a crucial issue in asset allocation decisions. Previous empirical results have focused mainly on US data and suffer from limited sample size in the analysis of long-horizon returns. Investigation of a long-term sample of thirty countries provides additional empirical evidence. The results are not reassuring. There is no evidence of long-term mean reversion in the expanded data sample. Downside risk is not reduced as the horizon lengthens. On the positive side, a globally diversified portfolio would have displayed much less downside risk than any single market.

Abstract: This paper compares two recent Monte Carlo methods advocated for the computation of optimal portfolio rules. The candidate methods are the approach based on Monte Carlo with Malliavin Derivatives (MCMD) proposed by Detemple, Garcia and Rindisbacher [Detemple et al., 2003. A Monte-Carlo method for optimal portfolios. Journal of Finance 58, 401–406] and the approach based on Monte Carlo with regression (MCR) of Brandt, Goyal, Santa-Clara and Stroud [Brandt et al., 2003. A simulation approach to dynamic portfolio choice with an application to learning about return predictability. Working paper, Wharton School]. Our comparisons are carried out in the context of various intertemporal portfolio choice problems with two assets, a risky asset and a riskless asset, and different configurations of the state variables. The specifications studied include a linear model with a single state variable admitting an exact solution and a non-linear model with two state variables that requires a purely numerical resolution. The accuracies of the candidate methods are compared. We provide, in particular, efficiency plots displaying the speed–accuracy trade-off for various selections of the relevant simulation and discretization parameters. MCMD is shown to dominate in all the settings considered.

Abstract: Executive Summary. Quantitative models of asset allocation are increasingly used by institutional commercial real estate investors as a guide for investment strategy. Real estate as an asset class,...

Abstract: It is well known that an unbiased forecast of the terminal value of a portfolio requires compounding at the arithmetic mean return over the investment horizon. However, the maximum-likelihood practice, common with academics, of compounding at the estimator of mean return results in upward biased and highly inefficient estimates of long-term expected returns. We derive analytically both an unbiased and a small-sample efficient estimator of long-term expected returns for a given sample size and horizon. Both estimators entail penalties that reduce the annual compounding rate as the investment horizon increases. The unbiased estimator, which is far lower than the compounded arithmetic average, is stillveryinefficient, oftenmore sothanasimplegeometric estimator known to practitioners. Our small-sample efficient estimator is even lower. These results compound the sobering evidence in recent work that the equity riskpremiumislower thansuggestedby post-1926data. Our methodology and results are robust to extensions such as predictable returns. We also confirm analytically that parameter uncertainty, properly incorporated, produces optimal asset allocations, in stark contrast to conventional wisdom. Longer investment horizons require lower, not higher, allocations to risky assets.

Abstract: The growth optimal portfolio (GOP) is a portfolio which has a maximal expected growth rate over any time horizon. As a consequence, this portfolio is sure to outperform any other significantly different strategy as the time horizon increases. This property in particular has fascinated many researchers in finance and mathematics created a huge and exciting literature on growth optimal investment. This paper attempts to provide a comprehensive survey of the literature and applications of the GOP. In particular, the heated debate of whether the GOP has a special place among portfolios in the asset allocation decision is reviewed as this still seem to be an area where some misconceptions exists. The survey also provides an extensive review of the recent use of the GOP as a pricing tool, in for instance the so-called “benchmark approach”. This approach builds on the numeraire property of the GOP, that is, the fact that any other asset denominated in units of the GOP become a supermartingale JEL classification: B0, G10 Mathematics Subject Classification (2000): Primary: 91B28, Secondary: 60H30, 60G44, 91B06 ∗University of Southern Denmark, Email: morten.m.christensen@sam.sdu.dk. The author would like to thank Christian Riis Flor and Eckhard Platen for valuable comments and suggestions.