Spectral Factor Models

57 Pages Posted: 13 Nov 2018 Last revised: 9 Jul 2019

See all articles by Federico M. Bandi

Federico M. Bandi

Johns Hopkins University - Carey Business School

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)

Andrea Tamoni

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick; London School of Economics & Political Science (LSE)

Date Written: July 7, 2019

Abstract

We represent risk factors as sums of orthogonal components capturing fluctuations over different frequencies. The representation leads to novel spectral factor models in which systematic risk is allowed (without being forced) to vary across different frequencies. Frequency-specific systematic risk is captured by a notion of spectral beta. We show that traditional factor models restrict the spectral betas to be constant. Spectral factor models dispense with this restriction and explicitly link its violation to the delayed reaction of prices to changes in the systematic factors. We illustrate how the methods may lead to dimension reduction in the factor space.

Keywords: systematic risk, factor models, investment horizon, portfolio optimization, cross-sectional pricing

JEL Classification: C22, C32, E32; G11; G12

Suggested Citation

Bandi, Federico Maria and Chaudhuri, Shomesh and Lo, Andrew W. and Tamoni, Andrea, Spectral Factor Models (July 7, 2019). Johns Hopkins Carey Business School Research Paper No. 18-17. Available at SSRN: https://ssrn.com/abstract=3275567 or http://dx.doi.org/10.2139/ssrn.3275567

Federico Maria Bandi

Johns Hopkins University - Carey Business School ( email )

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Shomesh Chaudhuri

Massachusetts Institute of Technology ( email )

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Cambridge, MA 02139-4307
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Andrew W. Lo

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

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National Bureau of Economic Research (NBER) ( email )

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

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Andrea Tamoni (Contact Author)

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

1 Washington Park
Newark, NJ 07102
United States

London School of Economics & Political Science (LSE) ( email )

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