An Empirical Analysis of the Swaption Cube
We use a comprehensive database of inter-dealer quotes to conduct the first empirical analysis of the dynamics of the swaption cube. Using a model independent approach, we establish a set of stylized facts regarding the cross-sectional and time-series variation of conditional volatility and skewness of the swap rate distributions implied by the swaption cube. We then develop and estimate a dynamic term structure model that is consistent with these stylized facts, and use it to infer volatility and skewness of the risk-neutral and physical swap rate distributions. Finally, we investigate the fundamental drivers of these distributions. In particular, we find that volatility, volatility risk premia, skewness, and skewness risk premia are significantly related to the characteristics of agents' belief distributions for the macroeconomy, with GDP beliefs the most important factor in the USD market, and inflation beliefs the most important factor in the EUR market. This is consistent with differences in monetary policy objectives in the two markets.
|Date of creation:||Nov 2010|
|Date of revision:|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
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- Alessandro BEBER & Michael W. BRANDT, 2004.
"The Effects of Macroeconomic News on Beliefs and Preferences: Evidence from the Options Market,"
FAME Research Paper Series
rp105, International Center for Financial Asset Management and Engineering.
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- Alessandro Beber & Michael W. Brandt, 2003. "The Effect of Macroeconomic News on Beliefs and Preferences: Evidence from the Options Market," NBER Working Papers 9914, National Bureau of Economic Research, Inc.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004.
"Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies,"
NBER Working Papers
10914, National Bureau of Economic Research, Inc.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- Frank de Jong & Joost Driessen & Antoon Pelsser, 2004. "On the Information in the Interest Rate Term Structure and Option Prices," Review of Derivatives Research, Springer, vol. 7(2), pages 99-127, 08.
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