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An intertemporal capital asset pricing model with bank credit growth as a state variable

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  • Hammami, Yacine
  • Lindahl, Anna

Abstract

An ICAPM which includes bank credit growth as a state variable explains 94% of the cross-sectional variation in the average returns on the 25 Fama–French portfolios. We find compelling evidence that bank credit growth is priced in the cross-section of expected stock returns, even after controlling for well-documented asset pricing factors. These results are robust to the inclusion of industry portfolios in the set of test assets. They are also robust to the addition of firm characteristics and lagged instruments in the factor model. Bank credit growth is important because of its ability to predict business cycle variables as well as future labor income growth. These findings underscore the relevance of bank credit growth in stock pricing.

Suggested Citation

  • Hammami, Yacine & Lindahl, Anna, 2014. "An intertemporal capital asset pricing model with bank credit growth as a state variable," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 14-28.
  • Handle: RePEc:eee:jbfina:v:39:y:2014:i:c:p:14-28
    DOI: 10.1016/j.jbankfin.2013.10.008
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    Cited by:

    1. Vithessonthi, Chaiporn, 2016. "Deflation, bank credit growth, and non-performing loans: Evidence from Japan," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 295-305.
    2. Wei, Xin & Liu, Xi & Zhang, Xueyong, 2022. "Shadow banking and the cross-section of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    3. Efdal Ulas Misirli, 2018. "Productivity Risk and Industry Momentum," Financial Management, Financial Management Association International, vol. 47(3), pages 739-774, September.
    4. Kwon, Ji Ho, 2022. "More predictors of the investment opportunity set in the ICAPM," Finance Research Letters, Elsevier, vol. 47(PA).
    5. Rafique, Amir & Iqbal, Khurram & Zakaria, Muhammad & Mujtaba, Ghulam, 2019. "Investigating ICAPM with mean-reverting dynamic conditional correlation: Evidence from an emerging stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 514-523.
    6. Kenneth Högholm & Johan Knif & Gregory Koutmos & Seppo Pynnönen, 2021. "Financial crises and the asymmetric relation between returns on banks, risk factors, and other industry portfolio returns," The Financial Review, Eastern Finance Association, vol. 56(1), pages 179-198, February.

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    More about this item

    Keywords

    Asset pricing models; Horse races; Predictability; Bank credit; Business cycle; Labor income;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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