Hedge Fund Performance under Misspecified Models

48 Pages Posted: 18 Sep 2020 Last revised: 22 Sep 2020

See all articles by David Ardia

David Ardia

HEC Montreal - Department of Decision Sciences

Laurent Barras

McGill University - Desautels Faculty of Management

Patrick Gagliardini

University of Lugano; Swiss Finance Institute

O. Scaillet

University of Geneva GSEM and GFRI; Swiss Finance Institute; University of Geneva - Research Center for Statistics

Date Written: July 27, 2020

Abstract

We develop a new approach for evaluating performance across hedge funds. Our approach allows for performance comparisons between models that are misspecified – a common feature given the numerous factors that drive hedge fund returns. The empirical results show that the standard models used in previous work omit similar factors because they (i) perform exactly like the CAPM, and (ii) produce large and positive alphas. In contrast, we observe a large and statistically significant decrease in performance with a new model formed with alternative factors that capture variance, correlation, liquidity, betting-against-beta, carry, and time-series momentum strategies. Overall, the results suggest that the average returns of hedge funds are largely explained by mechanical trading strategies.

Keywords: Hedge funds, performance, model misspecification, large panel

JEL Classification: G11, G12, C14, C33, C58

Suggested Citation

Ardia, David and Barras, Laurent and Gagliardini, Patrick and Scaillet, Olivier, Hedge Fund Performance under Misspecified Models (July 27, 2020). Swiss Finance Institute Research Paper No. 20-82, Available at SSRN: https://ssrn.com/abstract=3661751 or http://dx.doi.org/10.2139/ssrn.3661751

David Ardia

HEC Montreal - Department of Decision Sciences ( email )

3000 Côte-Sainte-Catherine Road
Montreal, QC H2S1L4
Canada

Laurent Barras (Contact Author)

McGill University - Desautels Faculty of Management ( email )

1001 Sherbrooke St. West
Montreal, Quebec H3A1G5 H3A 2M1
Canada
+15143988862 (Phone)

Patrick Gagliardini

University of Lugano ( email )

Via Buffi 13
Lugano, TN 6900
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Olivier Scaillet

University of Geneva GSEM and GFRI ( email )

40 Boulevard du Pont d'Arve
Geneva 4, Geneva 1211
Switzerland
+ 41 22 379 88 16 (Phone)
+41 22 389 81 04 (Fax)

HOME PAGE: http://www.scaillet.ch

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

University of Geneva - Research Center for Statistics

Geneva
Switzerland

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