Trend Filtering Methods for Momentum Strategies

49 Pages Posted: 7 Jul 2013

See all articles by Benjamin Bruder

Benjamin Bruder

Lyxor Asset Management

Tung-Lam Dao

Millennium Capital Management, France branch

Jean-Charles Richard

Eisler Capital

Thierry Roncalli

Amundi Asset Management; University of Evry

Date Written: December 1, 2011


This paper studies trend filtering methods. These methods are widely used in momentum strategies, which correspond to an investment style based only on the history of past prices. For example, the CTA strategy used by hedge funds is one of the best-known momentum strategies. In this paper, we review the different econometric estimators to extract a trend of a time series. We distinguish between linear and nonlinear models as well as univariate and multivariate filtering. For each approach, we provide a comprehensive presentation, an overview of its advantages and disadvantages and an application to the S\&P 500 index. We also consider the calibration problem of these filters. We illustrate the two main solutions, the first based on prediction error, and the second using a benchmark estimator. We conclude the paper by listing some issues to consider when implementing a momentum strategy.

Keywords: momentum strategy, trend following, moving average, filtering, trend extraction

JEL Classification: G11, G17, C63

Suggested Citation

Bruder, Benjamin and Dao, Tung-Lam and Richard, Jean-Charles and Roncalli, Thierry, Trend Filtering Methods for Momentum Strategies (December 1, 2011). Available at SSRN: or

Benjamin Bruder

Lyxor Asset Management ( email )


Tung-Lam Dao

Millennium Capital Management, France branch ( email )

2 Rue Jean Rostand
Orsay, 91400
+33651093563 (Phone)

Jean-Charles Richard

Eisler Capital ( email )

16 St. James's Street
London, SW1A1ER

Thierry Roncalli (Contact Author)

Amundi Asset Management ( email )

90 Boulevard Pasteur
Paris, 75015

University of Evry ( email )

Boulevard Francois Mitterrand
F-91025 Evry Cedex

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