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A Performance Comparison of Large-n Factor Estimators

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  • Gregory Connor

    () (Department of Economics, Finance and Accounting, National University of Ireland, Maynooth)

  • Zhuo Chen

    (PBC School of Finance, Tsinghua University,)

  • Robert A. Korajczyk

    (Kellogg School of Management, Northwestern University, IL 60208-2001, USA)

Abstract

This paper uses simulations to evaluate the performance of various methods for estimating factor returns in an approximate factor model when the cross-sectional sample (n) is large relative to the time-series sample (T). We study the performance of the estimators under a variety of alternative speci?cations of the underlying factor structure. We ?nd that 1) all of the estimators perform well, even when they do not accommodate the form of heteroskedasticity present in the data; 2) for the sample sizes considered here, accommodating heteroskedasticity does not deteriorate performance much when simple forms of heteroskedaticity are present; 3) estimators that handle missing data by substituting ?tted returns from the factor model converge to the true factors more slowly than the other estimators.

Suggested Citation

  • Gregory Connor & Zhuo Chen & Robert A. Korajczyk, 2014. "A Performance Comparison of Large-n Factor Estimators," Economics, Finance and Accounting Department Working Paper Series n255-14.pdf, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
  • Handle: RePEc:may:mayecw:n255-14.pdf
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    References listed on IDEAS

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    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    2. Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, vol. 13(3), pages 341-360, December.
    3. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    5. 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.
    6. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    7. Donald Rubin & Dorothy Thayer, 1982. "EM algorithms for ML factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 47(1), pages 69-76, March.
    8. Roll, Richard & Ross, Stephen A, 1980. " An Empirical Investigation of the Arbitrage Pricing Theory," Journal of Finance, American Finance Association, vol. 35(5), pages 1073-1103, December.
    9. Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
    10. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
    11. Lehmann, Bruce N. & Modest, David M., 1988. "The empirical foundations of the arbitrage pricing theory," Journal of Financial Economics, Elsevier, vol. 21(2), pages 213-254, September.
    12. Gregory Connor and Robert A. Korajczyk., 1987. "Estimating Pervasive Economic Factors with Missing Observations," Research Program in Finance Working Papers 173, University of California at Berkeley.
    13. 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.
    14. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
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