IDEAS home Printed from https://ideas.repec.org/a/wly/finmar/v22y2013i3p171-207.html
   My bibliography  Save this article

The Fear Premium and Daily Comovements of the S&P 500 E/P ratio and Treasury Yields before and during the 2008 Financial Crisis

Author

Listed:
  • Christophe Faugère

Abstract

I develop a new risk measure called the Total Fear Premium that generalizes Faugere‐Van Erlach (2009) and accounts for both flight‐to‐safety and flight‐to‐liquidity behavior. This new measure helps to explain why the daily S&P 500 forward earnings yield (E/P ratio) is strongly negatively correlated with daily Treasury yields of all maturities during the 2008 financial crisis, which is a reversal from the relation that prevailed before the crisis. The Total Fear Premium “mimics” the VIX during the financial crisis. Once the basic GARCH formulation modeling the interaction between the earnings yield and Treasury yields is augmented with the Total Fear Premium, the relation between the earnings yield and short‐term Treasury yields becomes significantly positive, in line with Fama's (1975) view that short‐term yields are good proxies for expected inflation. Two by‐products of this analysis are: 1) a new risk premium measure associated with flight‐to‐liquidity and 2) a new way to measure the inflation risk premium on a daily basis.

Suggested Citation

  • Christophe Faugère, 2013. "The Fear Premium and Daily Comovements of the S&P 500 E/P ratio and Treasury Yields before and during the 2008 Financial Crisis," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 22(3), pages 171-207, August.
    • Handle: RePEc:wly:finmar:v:22:y:2013:i:3:p:171-207
    DOI: 10.1111/fmii.12009
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/fmii.12009
    Download Restriction: no
    File URL: https://libkey.io/10.1111/fmii.12009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Martha Douvogiannis & Joel Lander & Athanasios Orphanides, "undated". "Earnings Forecasts and the Predictability of Stock Returns: Evidence from Trading the S&P;," Finance and Economics Discussion Series 1997-06, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    2. Peter Hördahl & Oreste Tristani, 2012. "Inflation Risk Premia In The Term Structure Of Interest Rates," Journal of the European Economic Association, European Economic Association, vol. 10(3), pages 634-657, May.
    3. Shiller, Robert J. & Beltratti, Andrea E., 1992. "Stock prices and bond yields : Can their comovements be explained in terms of present value models?," Journal of Monetary Economics, Elsevier, vol. 30(1), pages 25-46, October.
    4. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    5. D’Amico, Stefania & Kim, Don H. & Wei, Min, 2018. "Tips from TIPS: The Informational Content of Treasury Inflation-Protected Security Prices," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(1), pages 395-436, February.
    6. Edwin J. Elton, 1999. "Presidential Address: Expected Return, Realized Return, and Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 54(4), pages 1199-1220, August.
    7. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Darby, Michael R, 1975. "The Financial and Tax Effects of Monetary Policy on Interest Rates," Economic Inquiry, Western Economic Association International, vol. 13(2), pages 266-276, June.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Charles Armah Danso & James Refalo, 2025. "An Examination of G10 Carry Trade and Covered Interest Arbitrage Before, During, and After Financial Crises," JRFM, MDPI, vol. 18(4), pages 1-15, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dimitrios Koutmos, 2015. "Is there a Positive Risk†Return Tradeoff? A Forward†Looking Approach to Measuring the Equity Premium," European Financial Management, European Financial Management Association, vol. 21(5), pages 974-1013, November.
    2. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    3. He, Changli & Teräsvirta, Timo, 1999. "Higher-order dependence in the general Power ARCH process and a special case," SSE/EFI Working Paper Series in Economics and Finance 315, Stockholm School of Economics.
    4. Tak Siu & John Lau & Hailiang Yang, 2007. "On Valuing Participating Life Insurance Contracts with Conditional Heteroscedasticity," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 255-275, September.
    5. Ender Su & John Bilson, 2011. "Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3891-3905.
    6. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    7. Alistair Mees & Berndt Pilgram, 2000. "Non-Linear Markov Modelling Using Canonical Variate Analysis: Forecasting Exchange Rate Volatility," Econometric Society World Congress 2000 Contributed Papers 1162, Econometric Society.
    8. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
    9. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    10. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    11. Diongue, Abdou Kâ & Guégan, Dominique, 2007. "The stationary seasonal hyperbolic asymmetric power ARCH model," Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1158-1164, June.
    12. Chris Motengwe & Angel Pardo, 2015. "A Study of Seasonality on the Safex Wheat Market," Agrekon, Taylor & Francis Journals, vol. 54(4), pages 45-72, November.
    13. Gavriilidis, Konstantinos & Kambouroudis, Dimos S. & Tsakou, Katerina & Tsouknidis, Dimitris A., 2018. "Volatility forecasting across tanker freight rates: The role of oil price shocks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 376-391.
    14. Shadi Tehrani & Jesús Juan & Eduardo Caro, 2022. "Electricity Spot Price Modeling and Forecasting in European Markets," Energies, MDPI, vol. 15(16), pages 1-23, August.
    15. Mohamed El Ghourabi & Christian Francq & Fedya Telmoudi, 2016. "Consistent Estimation of the Value at Risk When the Error Distribution of the Volatility Model is Misspecified," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 46-76, January.
    16. Haas, Markus, 2008. "The autocorrelation structure of the Markov-switching asymmetric power GARCH process," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1480-1489, September.
    17. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, June.
    18. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    19. Sheriffdeen A. Tella & Olumuyiwa G. Yinusa & Ayinde Taofeek Olusola & Saban Celik, 2011. "Global Economic Crisis And Stock Markets Efficiency: Evidence From Selected Africa Countries," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 25(1), pages 139-169.
    20. Ilu, Ahmad Ibraheem, 2020. "Exchange Rate Pass through to Stock Prices: A Multi GARCH Approach," MPRA Paper 98442, University Library of Munich, Germany.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:finmar:v:22:y:2013:i:3:p:171-207. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.