
Realized jumps on financial markets and predicting credit spreads
This paper extends the jump detection method based on bipower variation to identify realized jumps on financial markets and to estimate parametrically the jump intensity, mean, and variance. Finite sample evidence suggests that the jump parameters can be accurately estimated and that the statistical inferences are reliable under the assumption that jumps are rare and large. Applications to equity market, treasury bond, and exchange rate data reveal important differences in jump frequencies and volatilities across asset classes over time. For investment grade bond spread indices, the estimated jump volatility has more forecasting power than interest rate factors and volatility factors including option-implied volatility, with control for systematic risk factors. The jump volatility risk factor seems to capture the low frequency movements in credit spreads and comoves countercyclically with the pricedividend ratio and corporate default rate. © 2010 Elsevier B.V. All rights reserved.
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- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics
Citation

Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics