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A Frequency Decomposition of Approximation Errors in Stochastic Discount Factor Models

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  • Cogley, Timothy

Abstract

This article extends the work of Hansen and Jagannathan by showing how to decompose approximation errors in stochastic discount factor models by frequency. This decomposition is applied to a number of consumption-based discount factor models in order to investigate how well they fit at low frequencies. There is some evidence of improved fit at low frequencies, but only in models with high degrees of risk aversion. In models with low degrees of risk aversion, approximation errors at low frequencies are just as severe as those at high frequencies.

Suggested Citation

  • Cogley, Timothy, 2001. "A Frequency Decomposition of Approximation Errors in Stochastic Discount Factor Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(2), pages 473-503, May.
    • Handle: RePEc:ier:iecrev:v:42:y:2001:i:2:p:473-503
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    Cited by:

    1. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
    2. Bandi, Federico M. & Chaudhuri, Shomesh E. & Lo, Andrew W. & Tamoni, Andrea, 2021. "Spectral factor models," Journal of Financial Economics, Elsevier, vol. 142(1), pages 214-238.
    3. Jozef Baruník and Ev~en Kocenda, 2019. "Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    4. Chang-Chih Chen & Chia-Chien Chang, 2019. "How Big are the Ambiguity-Based Premiums on Mortgage Insurances?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(1), pages 133-157, January.
    5. Christiano, Lawrence J. & Vigfusson, Robert J., 2003. "Maximum likelihood in the frequency domain: the importance of time-to-plan," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 789-815, May.
    6. Luca Sala, 2015. "Dsge Models in the Frequency Domains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 219-240, March.
    7. Brož, Václav & Kočenda, Evžen, 2022. "Mortgage-related bank penalties and systemic risk among U.S. banks," Journal of International Money and Finance, Elsevier, vol. 122(C).
    8. Chen, Chang-Chih & Ho, Kung-Cheng & Yan, Cheng & Yeh, Chung-Ying & Yu, Min-Teh, 2023. "Does ambiguity matter for corporate debt financing? Theory and evidence," Journal of Corporate Finance, Elsevier, vol. 80(C).
    9. Otrok, Christopher & Ravikumar, B. & Whiteman, Charles H., 2007. "A generalized volatility bound for dynamic economies," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2269-2290, November.
    10. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    11. Neuhierl, Andreas & Varneskov, Rasmus T., 2021. "Frequency dependent risk," Journal of Financial Economics, Elsevier, vol. 140(2), pages 644-675.
    12. Kang, Byoung Uk & In, Francis & Kim, Tong Suk, 2017. "Timescale betas and the cross section of equity returns: Framework, application, and implications for interpreting the Fama–French factors," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 15-39.
    13. Muhammad Abubakr Naeem & Mudassar Hasan & Abraham Agyemang & Md Iftekhar Hasan Chowdhury & Faruk Balli, 2023. "Time‐frequency dynamics between fear connectedness of stocks and alternative assets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2188-2201, April.

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