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An empirical investigation of asset pricing models under divergent lending and borrowing rates

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  • Yacine Hammami

Abstract

Asset pricing theory implies that the estimate of the zero-beta rate should fall between divergent lending and borrowing rates. This paper proposes a formal test of this restriction using the difference between the prime loan rate and the 1-month Treasury bill rate as a proxy for the difference between borrowing and lending rates. Based on simulations, this paper shows that in the ordinary least squares case, the Fama and MacBeth (J Pol Econ 81:607–636, 1973 ) t-statistic has high power against a general alternative, which is not true of the Shanken (Rev Financ Stud 5:1–33, 1992 ) and Kan et al. (J Financ doi: 10.1111/jofi.12035 , 2013 ) t-statistics. In the generalized least squares case, all three t-statistics have high power. The empirical investigation highlights that only the intertemporal capital asset pricing model reasonably prices the zero-beta portfolio. Other models, such as the Fama and French (J Financ Econ 33:3–56, 1993 ) model, do not assign the correct value to the zero-beta rate. Copyright Swiss Society for Financial Market Research 2014

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  • Yacine Hammami, 2014. "An empirical investigation of asset pricing models under divergent lending and borrowing rates," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(3), pages 263-279, August.
  • Handle: RePEc:kap:fmktpm:v:28:y:2014:i:3:p:263-279
    DOI: 10.1007/s11408-014-0233-1
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    1. Jagannathan, Ravi & Wang, Zhenyu, 1996. "The Conditional CAPM and the Cross-Section of Expected Returns," Journal of Finance, American Finance Association, vol. 51(1), pages 3-53, March.
    2. Forbes, Shwan M. & Paul, Chris II, 1992. "Modeling the prime rate: An ordered-response approach," International Review of Economics & Finance, Elsevier, vol. 1(2), pages 147-157.
    3. Brennan, M. J., 1971. "Capital Market Equilibrium with Divergent Borrowing and Lending Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(5), pages 1197-1205, December.
    4. Shanken, Jay & Zhou, Guofu, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," Journal of Financial Economics, Elsevier, vol. 84(1), pages 40-86, April.
    5. Raymond Kan & Chu Zhang, 1999. "Two‐Pass Tests of Asset Pricing Models with Useless Factors," Journal of Finance, American Finance Association, vol. 54(1), pages 203-235, February.
    6. Kling, John L., 1985. "The dynamic behavior of business loans and the prime rate : Reply," Journal of Banking & Finance, Elsevier, vol. 9(4), pages 581-584, December.
    7. Raymond Kan & Cesare Robotti & Jay Shanken, 2013. "Pricing Model Performance and the Two‐Pass Cross‐Sectional Regression Methodology," Journal of Finance, American Finance Association, vol. 68(6), pages 2617-2649, December.
    8. Goldberg, Michael A., 1982. "The pricing of the prime rate," Journal of Banking & Finance, Elsevier, vol. 6(2), pages 277-296, June.
    9. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    10. Shanken, Jay, 1992. "On the Estimation of Beta-Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 1-33.
    11. Paul Söderlind, 2006. "C-CAPM Refinements and the Cross-Section of Returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(1), pages 49-73, April.
    12. Ravi Jagannathan & Yong Wang, 2007. "Lazy Investors, Discretionary Consumption, and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1623-1661, August.
    13. Ralitsa Petkova, 2006. "Do the Fama–French Factors Proxy for Innovations in Predictive Variables?," Journal of Finance, American Finance Association, vol. 61(2), pages 581-612, April.
    14. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    15. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    16. Kling, John L., 1985. "The dynamic behavior of business loans and the prime rate," Journal of Banking & Finance, Elsevier, vol. 9(3), pages 421-442, September.
    17. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    18. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    19. Ravi Bansal & Robert F. Dittmar & Christian T. Lundblad, 2005. "Consumption, Dividends, and the Cross Section of Equity Returns," Journal of Finance, American Finance Association, vol. 60(4), pages 1639-1672, August.
    20. Martin Lettau & Sydney Ludvigson, 2001. "Resurrecting the (C)CAPM: A Cross-Sectional Test When Risk Premia Are Time-Varying," Journal of Political Economy, University of Chicago Press, vol. 109(6), pages 1238-1287, December.
    21. 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.
    22. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    23. Qing Li & Maria Vassalou & Yuhang Xing, 2006. "Sector Investment Growth Rates and the Cross Section of Equity Returns," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1637-1665, May.
    24. Shanken, Jay, 1986. "Testing Portfolio Efficiency When the Zero-Beta Rate Is Unknown: A Note," Journal of Finance, American Finance Association, vol. 41(1), pages 269-276, March.
    25. Motohiro Yogo, 2006. "A Consumption‐Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.
    26. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    27. Grauer, Robert R. & Janmaat, Johannus A., 2009. "On the power of cross-sectional and multivariate tests of the CAPM," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 775-787, May.
    28. Black, Fischer, 1972. "Capital Market Equilibrium with Restricted Borrowing," The Journal of Business, University of Chicago Press, vol. 45(3), pages 444-455, July.
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    1. Kruschwitz, Lutz & Löffler, Andreas & Lorenz, Daniela, 2019. "Divergent interest rates in the theory of financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 48-55.

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    More about this item

    Keywords

    Asset pricing models; Two-pass cross-sectional regressions; Zero-beta portfolio; Misspecification-robust t-ratio; C10; G10; G12;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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