Published papers
« Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified », 2024, Journal of Financial Economics
(with David Ardia, Patrick Gagliardini and Olivier Scaillet)
Winner of the 2022 Best Asset Pricing Paper Award at the Annual French Finance Association Meeting
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We develop a novel approach to separate alpha and beta under model misspecification. It
comes with formal tests to identify less misspecified models and sharpen the return decomposition of individual funds. Our hedge fund analysis reveals that: (i) prominent models are as misspecified as the CAPM, (ii) several factors (time-series momentum, variance, carry) capture alternative strategies and lower performance in all investment categories, (iii) fund heterogeneity in alpha and beta is large—an important result for fund selection and models of active management, (iv) performance is increasingly similar to mutual funds, (v) fund valuation is sensitive to investor sophistication.
« Skill, Scale, and Value Creation in the Mutual Fund Industry », 2022, Journal of Finance 77, 601-638
(with Patrick Gagliardini and Olivier Scaillet)
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We develop a flexible and bias-adjusted approach to jointly examine skill, scalability, and value added across individual funds. We find that skill and scalability (i) vary substantially across funds, and (ii) are strongly related as great investment ideas are difficult to scale up. The combination of skill and scalability produces a value added that (i) is positive for the majority of funds, and (ii) approaches its optimal level after an adjustment period possibly due to investors’ learning. These results are consistent with theoretical models in which funds are skilled and able to extract economic rents from capital markets.
« Reassessing False Discoveries in Mutual Fund Performance: Skill, Luck, or Lack of Power? A Reply», 2020, Journal of Finance (Replications and Corrigenda), 1-34
(with O. Scaillet and R. Wermers)
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Andrikogiannopoulou and Papakonstantinou (AP; 2019) conduct an inquiry into the bias of the False Discovery Rate (FDR) estimators of Barras, Scaillet, and Wermers (BSW; 2010). In this Reply, we replicate their results, then further explore the bias issue by (i) using different parameter values, and (ii) updating the sample period. Over the original period (1975-2006), we show how reasonable adjustments to the parameter choices made by BSW and AP results in a sizeable reduction in the bias relative to AP. Over the updated period (1975-2018), we further show that the performance of the FDR improves dramatically across a large range of parameter values. Specifically, we find that the probability of misclassifying a fund with a true alpha of 2% per year is 32% (versus 65% in AP). Our results, in combination with those of AP, indicate that the use of the FDR in finance should be accompanied by a careful evaluation of the underlying data generating process, especially when the sample size is small.
« A Large-Scale Approach for Evaluating Asset Pricing Models», 2019, Journal of Financial Economics 134, 549-569
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Recent studies show that the standard test portfolios do not contain sufficient information to discriminate between asset pricing models. To address this issue, we develop a large-scale approach that expands the cross-section to several thousand portfolios. Our novel approach is simple, widely applicable, and allows for formal evaluation/comparison tests. Its benefits are confirmed in empirical tests of CAPM- and characteristic-based models. While these models are all misspecified, we uncover striking performance differences between them. In particular, the human capital and conditional CAPMs largely outperform the CAPM which suggests that labor income and time-varying recession risks are primary concerns for investors.
« Does Variance Risk Have Two Prices? Evidence from the Equity and Option Markets », 2016, Journal of Financial Economics 121, 79-92
(with A. Malkhozov)
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We formally compare two versions of the market Variance Risk Premium (VRP) measured in the equity and option markets. Both VRPs follow common patterns and respond similarly to changes in volatility and economic conditions. However, we reject the null hypothesis that they are identical and find that their difference is strongly related to measures of the financial standing of intermediaries. These results shed new light on the information content of the VRP, suggest the presence of market frictions between the two markets, and are consistent with the key role played by intermediaries in setting option prices.
« Hedge Fund Return Predictability Under the Magnifying Glass », 2013, Journal of Financial and Quantitative Analysis 48, 1057-1083
(with D. Avramov and R. Kosowski)
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This paper develops a unified approach to comprehensively analyze individual hedge fund return predictability, both in- and out-of-sample. In-sample, we find that variation in hedge fund performance across changing market conditions is both widespread and economically significant. The predictability pattern across funds is consistent with economic rationale, and largely reflects differences in key hedge fund characteristics, such as leverage or capacity constraints. Out-of-sample, we show that a very simple strategy that combines the funds’ return forecasts obtained from individual predictors delivers superior performance, even during the 2008 financial crisis. Importantly, we show that in- and out-of-sample predictability are closely related, contrary to the results documented in the previous literature.
« False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas », 2010, Journal of Finance 65, 179-216
(with O. Scaillet and R. Wermers)
Winner of the 2008 Swiss Finance Institute/Banque Privée Espirito Santo Outstanding Paper Award
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This paper develops a simple technique that controls for « false discoveries, » or mutual funds that exhibit significant alphas by luck alone. Our approach precisely separates funds into (1) unskilled, (2) zero-alpha, and (3) skilled funds, even with dependencies in cross-fund estimated alphas. We find that 75% of funds exhibit a zero alpha (net of expenses), consistent with the Berk and Green (2004) equilibrium. Further, we find a significant proportion of skilled (positive alpha) funds prior to 1996, but almost none by 2006. We also show that controlling for false discoveries substantially improves the ability to find funds with persistent performance.
« International Conditional Asset Allocation Under Specification Uncertainty », 2007, Journal of Empirical Finance 14, 443-464
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This paper examines the impact of specification uncertainty on the performance of international mean-variance conditional asset allocation. This notion is defined as the uncertainty faced by the investor regarding the specification choices necessary to implement a conditional strategy. To assess the impact of this phenomenon, we measure the performance of a group of strategies that the investor could reasonably consider. The strong performance variability across the strategies indicates that the gains previously documented are overstated. Our findings provide an explanation to the apparent paradox between the economic and statistical significance of predictability, and are consistent with the semi-strong form of market efficiency.
« How to Diversify Internationally? A Comparison of Conditional and Unconditional Asset Allocation Methods », 2003, Financial Markets and Portfolio Management 17, 194-212
(with D. Isakov)
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To obtain the maximum benefits from diversification, financial theory suggests that investors should invest internationally because of the larger potential for risk reduction. The question that we raise in this paper is how to select the optimal portfolio of developed and emerging countries? This article synthesizes the major international asset allocation methods based on mean-variance analysis that have been proposed so far in the literature. In particular it compares two types of conditional asset allocation with unconditional methods. The asset allocation methods are implemented from a Swiss perspective over the period 1988-2001. We find that conditional methods based on direct predictability of expected returns outperform all other asset allocation methods.