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A new government bond volatility index predictor for the U.S. equity premium

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  • Pan, Zheyao
  • Chan, Kam Fong

Abstract

This study proposes a new predictor constructed under the state-preference asset pricing framework to forecast the U.S. monthly equity premium. The index, termed as the government bond volatility index or GBVX, reflects the Treasury implied volatility. The innovation in the GBVX delivers statistically and economically significant in-sample and out-of-sample predictive results over the recent 2000–2015 sample period. It yields a sizable increase in terminal wealth growth, Sharpe ratio, and utility gains. In addition, the predictive ability of the innovation in the GBVX is comparable to, and in a majority of cases, surpasses those of conventional predictors commonly used in the literature, as well as a range of historical and other implied volatility indices. The strong predictive ability of the innovation in the GBVX stems from its anticipation of cash flow news.

Suggested Citation

  • Pan, Zheyao & Chan, Kam Fong, 2018. "A new government bond volatility index predictor for the U.S. equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 200-215.
    • Handle: RePEc:eee:pacfin:v:50:y:2018:i:c:p:200-215
    DOI: 10.1016/j.pacfin.2016.12.007
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Campbell, John Y & Ammer, John, 1993. "What Moves the Stock and Bond Markets? A Variance Decomposition for Long-Term Asset Returns," Journal of Finance, American Finance Association, vol. 48(1), pages 3-37, March.
    3. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    4. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    5. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    6. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    7. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
    8. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    9. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    10. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    11. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    12. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
    13. Sébastien Fries & Jean‐Stéphane Mésonnier & Sarah Mouabbi & Jean‐Paul Renne, 2018. "National natural rates of interest and the single monetary policy in the euro area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 763-779, September.
    14. Steve Ross, 2015. "The Recovery Theorem," Journal of Finance, American Finance Association, vol. 70(2), pages 615-648, April.
    15. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    16. Ericsson, Jan & Jacobs, Kris & Oviedo, Rodolfo, 2009. "The Determinants of Credit Default Swap Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 109-132, February.
    17. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    18. Lutz Kilian & Clara Vega, 2011. "Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 660-671, May.
    19. Engsted, Tom & Pedersen, Thomas Q. & Tanggaard, Carsten, 2012. "Pitfalls in VAR based return decompositions: A clarification," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1255-1265.
    20. K. J. Arrow, 1964. "The Role of Securities in the Optimal Allocation of Risk-bearing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 31(2), pages 91-96.
    21. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    22. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    23. Banerjee, Prithviraj S. & Doran, James S. & Peterson, David R., 2007. "Implied volatility and future portfolio returns," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3183-3199, October.
    24. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    25. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    26. Garrett, Ian & Priestley, Richard, 2012. "Dividend Growth, Cash Flow, and Discount Rate News," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(5), pages 1003-1028, October.
    27. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    28. Long Chen & Xinlei Zhao, 2009. "Return Decomposition," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5213-5249, December.
    29. Yan, Shu, 2011. "Jump risk, stock returns, and slope of implied volatility smile," Journal of Financial Economics, Elsevier, vol. 99(1), pages 216-233, January.
    30. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    31. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    32. Long Chen & Zhi Da & Xinlei Zhao, 2013. "What Drives Stock Price Movements?," The Review of Financial Studies, Society for Financial Studies, vol. 26(4), pages 841-876.
    33. Deuskar, Prachi & Gupta, Anurag & Subrahmanyam, Marti G., 2011. "Liquidity effect in OTC options markets: Premium or discount?," Journal of Financial Markets, Elsevier, vol. 14(1), pages 127-160, February.
    34. Taylor, Stephen J. & Yadav, Pradeep K. & Zhang, Yuanyuan, 2010. "The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 871-881, April.
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    3. Balachandran, Balasingham & Williams, Barry, 2018. "Effective governance, financial markets, financial institutions & crises," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 1-15.

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    More about this item

    Keywords

    Bond volatility index; Stock return predictability; Asset allocation; Out-of-sample test; Return decomposition;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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