Dynamic Alpha: A Spectral Decomposition of Investment Performance Across Time Horizons

30 Pages Posted: 11 Jun 2018 Last revised: 1 Jul 2018

See all articles by Shomesh Chaudhuri

Shomesh Chaudhuri

Massachusetts Institute of Technology

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Date Written: May 22, 2018

Abstract

The value added by an active investor is traditionally measured using alpha, tracking error, and the information ratio. However, these measures do not characterize the dynamic component of investor activity, nor do they consider the time horizons over which weights are changed. In this paper, we propose a technique to measure the value of active investment that captures both the static and dynamic contributions of an investment process. This "dynamic alpha" is based on the decomposition of a portfolio's expected return into its frequency components using spectral analysis. The result is a static component that measures the portion of a portfolio's expected return due to passive investments and security selection, and a dynamic component that captures the manager's timing ability across a range of time horizons. Our framework can be universally applied to any portfolio, and is a useful method for comparing the forecast power of different investment processes. Several analytical and empirical examples are provided to illustrate the practical relevance of this decomposition.

Keywords: Investments; Performance Attribution; Portfolio Management; Alpha; Spectral Analysis

JEL Classification: G11; G12; E32; C22

Suggested Citation

Chaudhuri, Shomesh and Lo, Andrew W., Dynamic Alpha: A Spectral Decomposition of Investment Performance Across Time Horizons (May 22, 2018). Available at SSRN: https://ssrn.com/abstract=3184092 or http://dx.doi.org/10.2139/ssrn.3184092

Shomesh Chaudhuri

Massachusetts Institute of Technology ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
1,014
Abstract Views
5,976
rank
21,030
PlumX Metrics