Abstract Cash holdings of equity mutual funds impose a drag on fund performance but also allow managers to make quick investments in attractive stocks and satisfy outflows without costly fire sales. This article shows that actively managed equity funds with high abnormal cash—that is, with cash holdings in excess of the level predicted by fund attributes—outperform their low abnormal cash peers by over 2% per year. Managers carrying high abnormal cash compensate for the low return on cash by making superior stock selection decisions, whereas less capable managers find abnormal cash costly and remain more fully invested in equities. Managers of high abnormal cash funds also proficiently satisfy fund outflows and control fund transaction costs, whereas low abnormal cash funds lack flexibility to cover outflows and can suffer from costly fire sales. The empirical evidence suggests that managers carrying abnormal cash benefit from the flexibility it provides despite the costs of holding cash.

Industries are economically linked through customer-supplier trade flows. We show that industry shocks propagating along this intersectoral trade network can feed back to the originating industry, causing an “echo”–intermediate-term autocorrelation in returns. Adopting techniques from graph theory, we find that the strength of the trade network feedback is a crucial determinant of the echo effect in industry returns. Returns of the echo strategy implemented within high-feedback strength industries reach 1% monthly. Consistent with limited-information models, the relation between feedback strength and echo profits is strongest in industries with information diffusion frictions, such as low analyst coverage, along the feedback loop. Overall, our results identify intersectoral trade networks as important conduits of industry shocks and provide the first explanation for the echo effect.

Prior theory suggests that time variation in the degree to which leverage constraints bind affects the pricing kernel. We propose a measure for this leverage constraint tightness by inverting the argument that constrained investors tilt their portfolios to riskier assets. We show that the average market beta of actively managed mutual funds—intermediaries facing leverage restrictions—captures their desire for leverage and thus the tightness of constraints. Consistent with theory, it strongly predicts returns of the betting-against-beta portfolio, and is a priced risk factor in the cross-section of mutual funds and stocks. Funds with low exposure to the factor outperform high-exposure funds by 5% annually, and for stocks this difference reaches 7%. Our results show that the tightness of leverage constraints has important implications for asset prices.

Prior studies have documented that pension plan sponsors often monitor a fund’s performance relative to a benchmark. We use a first-difference approach to show that in an effort to beat benchmarks, fund managers controlling large pension assets tend to increase their exposure to high-beta stocks, while aiming to maintain tracking errors around the benchmark. The findings support theoretical conjectures that benchmarking can lead managers to tilt their portfolio toward high-beta stocks and away from low-beta stocks, which can reinforce observed pricing anomalies.

Prior studies have documented that pension plan sponsors often monitor a fund's performance relative to a benchmark. We use a first-difference approach to show that in an effort to beat benchmarks, fund managers controlling large pension assets tend to increase their exposure to high-beta stocks, while aiming to maintain tracking errors around the benchmark. The findings support theoretical conjectures that benchmarking can lead managers to tilt their portfolio toward high-beta stocks and away from low-beta stocks, which can reinforce observed pricing anomalies.

Abstract Levered noise occurs when no-arbitrage replication hedges fundamentals but amplifies price errors. Motivated by our theory, we use widely-available end-of-day OptionMetrics data to improve accuracy of synthetic dividend strip prices and provide longer samples than prior studies. Term structure point estimates are approximately flat in simple returns (88 bp/month vs. 87 bp/month for short-term dividends vs. index), and upward-sloping in measurement-error-robust logarithmic returns (43 bp/month vs. 77 bp/month). These results from prominent index options show the importance of diagnosing noise in no-arbitrage prices. Prior conclusions of an average downward slope in the equity term structure are not robust.

Abstract In contrast with theoretical predictions, high-fee active equity funds generate worse net-of-expenses performance. We show that this fee-performance puzzle is driven by the preference of high-fee funds for stocks with low operating profitability and high investment rates, characteristics associated with low expected returns. After controlling for exposures to profitability and investment factors, we find high-fee funds significantly outperform low-fee funds before expenses and achieve similarly poor net-of-fees performance. In resolving the fee-performance puzzle, our findings provide support to the theoretical prediction that net alphas are unrelated to fees and challenge the common advice to prefer low-fee funds over high-fee counterparts. (JEL G23, G11, J24) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

A closet indexer is more likely to meet a value-weighted investment benchmark by value weighting the portfolio. Following this intuition, we introduce a simple measure of active management, the absolute difference between the value weights and actual weights held by a fund, summed across its holdings. This proxy captures managerial skill: active funds outperform passive ones by 2.5% annually. Compared with known measures of skill, our proxy robustly predicts fund flows, asset growth, factor-adjusted performance, and value added. Its predictive ability is orthogonal to that of other measures and is robust to controlling for volatility timing, past performance, and style. (JEL G10, G12, G14, G20, G23)

Unconditional alphas are biased when conditional beta covaries with the market risk premium (market timing) or volatility (volatility timing). We demonstrate an additional bias (overconditioning) that can occur any time an empiricist estimates risk using information, such as a realized beta, that is not available to investors ex ante. Calibrating to U.S. equity returns, volatility timing and overconditioning can plausibly impact alphas more than market timing, which has been the focus of prior literature. To correct market- and volatility-timing biases without overconditioning, we show that incorporating realized betas into instrumental variables estimators is effective. Empirically, instrumentation reduces momentum alphas by 20–40%. Overconditioned alphas overstate performance by up to 2.5 times. We explain the sources of both the volatility-timing and overconditioning biases in momentum portfolios.

We characterize linkages between average returns calculated at different horizons. Theoretically, when stocks incorporate information slowly, average short-horizon returns are downward biased. Buy-and-hold strategies can amplify the effect. In contrast, existing theories analyze price noises that are independent of fundamentals, and buy-and-hold portfolio returns are unaffected. We document horizon effects as large as 10% annualized in daily and monthly style portfolios and international indices. Slow reaction to market information, identified by gradually declining lagged betas, is an important cause. These findings have natural consequences for performance evaluation. Received July 2, 2012; accepted June 28, 2015 by Editor Andrew Karolyi.