Knowledge that Transforms

Government bonds comove more strongly with bond-like stocks: stocks of large, mature, low-volatility, profitable, dividend-paying firms that are neither high growth nor distressed. Variables that are derived from the yield curve that are already known to predict returns on bonds also predict returns on bond-like stocks; investor sentiment, a predictor of the cross-section of stock returns, also predicts excess bond returns. These relationships remain in place even when bonds and stocks become “decoupled” at the index level. They are driven by a combination of effects including correlations between real cash flows on bonds and bond-like stocks, correlations between their risk-based return premia, and periodic flights to quality.

We analyze mutual fund industry selectivity—the performance of a fund’s industry allocation relative to the market. We find that industry selection accounts for a full third of fund performance based on two-digit standard industrial classification (SIC) codes, with the remaining attributable to the performance of individual stocks relative to their own industries. More importantly, we find that industry-selection skill drives persistence in relative performance. Unlike stock-selection ability, industry selectivity is not eroded by increasing fund assets. Our results suggest that accounting for a manager’s ability to pick outperforming industries provides information beyond standard performance measures that can enhance a fund investor’s future performance.

Many institutions are attracted to diversified portfolios of hedge funds, referred to as Funds of Hedge Funds (FoHFs). In this article, we examine a new database that separates out for the first time the effects of diversification (the number of underlying hedge funds) from scale (the magnitude of assets under management). We find with others that the variance-reducing effects of diversification diminish once FoHFs hold more than 20 underlying hedge funds. This excess diversification actually increases their left-tail risk exposure once we account for return smoothing. Furthermore, the average FoHF in our sample is more exposed to left-tail risk than are naïve 1/N randomly chosen portfolios. This increase in tail risk is accompanied by lower returns, which we attribute to the cost of necessary due diligence that increases with the number of hedge funds.

Cover Get access The Review of Asset Pricing Studies, Volume 1, Issue 1, December 2011, Page NP, https://doi.org/10.1093/rapstu/rar006 Published: 01 December 2011

We provide a model in which a single psychological constraint, limited attention, explains both under- and overreaction to different earnings components. Investor neglect of earn-ings induces post-earnings announcement drift and the profit anomaly. Neglect of earnings components causes accrual and cash flow anomalies. The model offers empirical implica-tions relating the strength of earnings-related anomalies to the forecasting power of current earnings-related information for future earnings, investor attentiveness, and the volatilities of and correlation between accruals and cash flows. We also show that, owing to atten-tion costs, in equilibrium not all investors choose to attend to earnings or its components. (JEL G12, G14, M41, M43) Market reactions to earnings and earnings components present a striking puzzle. Stock prices on average underreact to earnings surprises (post-earnings an-nouncement drift), but overreact to the operating accruals component of earn-ings.1 Earnings- and accruals-related patterns of return predictability are often referred to as “anomalies, ” “under- ” and “overreaction, ” or reflecting investor “optimism, ” “pessimism, ” or “naı̈veté. ” Such labels offer little guidance as to

Classical approaches to estimation and decisions requiring estimation often are at odds. When values critical to the decision are convex or concave functions of unknown parameters, the statistician's estimation error adjustments are the opposite of what is appropriate for the decision. We illustrate the conflict by studying multi-period investment problems. The proper application of Jensen's inequality to the decision turns finance intuition on its head: Multi-period investments with negative risk premia can be profitable, risk-averse investors can have infinite demand for risky securities, settings exist in which risk-averse investors should not diversify, and demand for mutual funds with negative alphas may be rational.

We present a novel methodology for estimating/testing the Bansal and Yaron (2004) and related long-run risks (LRR) models based on the observation that the latent state variables are known functions of observables. The large standard error of the estimated elasticity of intertemporal substitution explains the controversy on its magnitude. The model requires higher persistence of consumption and dividend growth to explain the cross-section of returns than that observed in the data. The model matches the unconditional moments of consumption and dividend growth, but implies a higher risk-free rate and lower volatility of the price/dividend ratio, risk-free rate, and market return than those observed in the data. Contrary to the model implications, the conditional variance of the LRR variable fails to capture the large time variation in the equity premium.

We show whether central clearing of a particular class of derivatives lowers counterparty risk. For plausible cases, adding a central clearing counterparty (CCP) for a class of derivatives such as credit default swaps reduces netting efficiency, leading to an increase in average exposure to counterparty default. Further, clearing different classes of derivatives in separate CCPs always increases counterparty exposures relative to clearing the combined set of derivatives in a single CCP. We provide theory as well as illustrative numerical examples of these results that are calibrated to notional derivatives position data for major banks.