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A Grouped Factor Model

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  • Chen, Pu

Abstract

In this paper we present a grouped factor model that is designed to explore grouped structures in factor models. We develop an econometric theory consisting of a consistent classification rule to assign variables to their respective groups and a class of consistent model selection criteria to determine the number of groups as well as the number of factors in each group. As a result, we propose a procedure to estimate grouped factor models, in which the unknown number of groups, the unknown relationship between variables to their groups as well as the unknown number of factors in each group are statistically determined based on observed data. The procedure can help to estimate common factor that are pervasive across all groups and group-specific factors that are pervasive only in the respective groups. Simulations show that our proposed estimation procedure has satisfactory finite sample properties.

Suggested Citation

  • Chen, Pu, 2010. "A Grouped Factor Model," MPRA Paper 28083, University Library of Munich, Germany, revised 11 Jan 2011.
    • Handle: RePEc:pra:mprapa:28083
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    File URL: https://mpra.ub.uni-muenchen.de/36082/2/MPRA_paper_36082.pdf
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    References listed on IDEAS

    as
    1. Connor, Gregory & Korajczyk, Robert A, 1993. "A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
    2. Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
    3. Sydney C. Ludvigson & Serena Ng, 2009. "A Factor Analysis of Bond Risk Premia," NBER Working Papers 15188, National Bureau of Economic Research, Inc.
    4. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    5. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2016. "Is Industrial Production Still the Dominant Factor for the US Economy?," Swiss Finance Institute Research Paper Series 16-11, Swiss Finance Institute.
    2. Chen, Pu, 2012. "Common Factors and Specific Factors," MPRA Paper 36085, University Library of Munich, Germany.

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    More about this item

    Keywords

    Factor Models; Generalized Principal Component Analysis; Model Selection;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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