Journal of Asset Management

, Volume 20, Issue 6, pp 442–468 | Cite as

Trends everywhere? The case of hedge fund styles

  • Charles ChevalierEmail author
  • Serge Darolles
Original Article


This paper investigates empirically whether time-series momentum returns can explain the performance of hedge funds in the cross section. Relying on the trend-following literature, a volatility-adjusted time-series momentum signal is applied on a daily basis across a large set of futures, covering the major asset classes. We build a hierarchical set of trend factors: the full version TREND can be split in summable factors across two dimensions: the horizon of the signals and the traded asset class. We show that Managed Futures, Global Macro and Fund of Hedge Funds strategies can be partly explained by a TREND exposure. Moreover, a TREND exposure is a significant determinant of hedge funds returns at the fund level, for Managed Futures and Global Macro but also, and more surprisingly, for the other styles.


Managed Futures Time-series momentum Trend following Commodity Trading Advisor (CTA) Hedge funds Trading strategies 

JEL Classification

G11 G12 G15 F37 



We thank Pedro Barroso, Paul Karehnke, Guillaume Monarcha and the people at KeyQuant, for various useful comments and suggestions. In addition, we are grateful to the participants of: the DRM Finance PhD Seminar, the Quantitative Finance and Financial Econometrics 2018 Conference, the Econometric Research in Finance 2018 Workshop, the 10th French Econometrics Conference, the 12th International Conference on Computational and Financial Econometrics, the 11th Annual Hedge Funds and Private Equity Research Conference, the 12th Financial Risks International Forum, the ANR MultiRisk 2019 Workshop and the 36th International Conference of the French Finance Association. We gratefully acknowledge the financial support of the chair QuantValley/Risk Foundation “Quantitative Management Initiative.” We are also grateful to the Agence Nationale de la Recherche (ANR), which supported this work via the Project MultiRisk (ANR-16-CE26-0015-02).


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Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.KeyQuantParisFrance
  2. 2.CNRS, UMR [7088], DRMUniversité Paris-Dauphine, PSL Research UniversityParisFrance

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