To make high-quality research more accessible and easier to explore.

Fields:
298 results ✕ Clear filters

The relation between equity incentives and misreporting: The role of risk-taking incentives

Journal of Financial Economics 2013 109(2), 327-350 open access
Prior research argues that a manager whose wealth is more sensitive to changes in the firm׳s stock price has a greater incentive to misreport. However, if the manager is risk-averse and misreporting increases both equity values and equity risk, the sensitivity of the manager׳s wealth to changes in stock price (portfolio delta) will have two countervailing incentive effects: a positive “reward effect” and a negative “risk effect.” In contrast, the sensitivity of the manager׳s wealth to changes in risk (portfolio vega) will have an unambiguously positive incentive effect. We show that jointly considering the incentive effects of both portfolio delta and portfolio vega substantially alters inferences reported in prior literature. Using both regression and matching designs, and measuring misreporting using discretionary accruals, restatements, and enforcement actions, we find strong evidence of a positive relation between vega and misreporting and that the incentives provided by vega subsume those of delta. Collectively, our results suggest that equity portfolios provide managers with incentives to misreport when they make managers less averse to equity risk.

Friction in the trading process and the estimation of systematic risk

Journal of Financial Economics 1983 12(2), 263-278
This paper considers how estimates of the market model beta parameter can be biased by friction in the trading process (information, decision, and transaction costs) that (a) leads to a distinction between observed and ‘true’ returns; (b) causes observed returns to be generated asynchronously for a set of interdependent securities; and (c) thereby introduces serial cross-correlation into security returns. Several propositions are derived from which consistent estimators of beta are obtained, and the effect of differencing interval length on beta estimates is specified. The formulation is contrasted with the related analyses of Scholes-Williams (1977) and Dimson (1979).

LTCM Redux? Hedge fund Treasury trading, funding fragility, and risk constraints

Journal of Financial Economics 2025 169, 104017
We exploit the 2020 Treasury market shock to analyze how external and internal constraints impact arbitrageurs. Using regulatory filings, we find that hedge funds reduced arbitrage activities and increased cash holdings, despite stable credit and low contemporaneous redemptions. Creditors’ regulatory and liquidity constraints were not propagated to hedge funds through repo—Treasury arbitrageurs’ predominant financing source. Fund-creditor borrowing data reveal more regulated dealers provided, and more important clients received, disproportionately higher funding. Value-at-risk reported by funds suggests internal risk constraints were binding. Our results support theoretical predictions that arbitrageur risk constraints and precautionary liquidity management can amplify market instability even when contemporaneous financing remains resilient.

Machine learning and fund characteristics help to select mutual funds with positive alpha

Journal of Financial Economics 2023 150(3), 103737 open access
Machine-learning methods exploit fund characteristics to select tradable long-only portfolios of mutual funds that earn significant out-of-sample annual alphas of 2.4% net of all costs. The methods unveil interactions in the relation between fund characteristics and future performance. For instance, past performance is a particularly strong predictor of future performance for more active funds. Machine learning identifies managers whose skill is not sufficiently offset by diseconomies of scale, consistent with informational frictions preventing investors from identifying the outperforming funds. Our findings demonstrate that investors can benefit from active management, but only if they have access to sophisticated prediction methods.

Optimal illiquidity

Journal of Financial Economics 2025 165, 103996
We study the socially optimal level of illiquidity in an economy populated by households with taste shocks and present bias with naive beliefs. The government chooses mandatory contributions to accounts, each with a different pre-retirement withdrawal penalty. Collected penalties are rebated lump sum. When households have homogeneous present bias, β, the social optimum is well approximated by a single account with an early-withdrawal penalty of 1−β. When households have heterogeneous present bias, the social optimum is well approximated by a two-account system: (i) an account that is completely liquid and (ii) an account that is completely illiquid until retirement.