Abstract
For over a hundred years, diffusion differential equations have been used to model the changes in asset prices. Despite obvious fundamental problems with these equations, such as the requirement of continuity, they often provide adequate local fits to the observed asset price process. There are, however, several aspects of the empirical process that are not fit by simple diffusion equations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andersen, T. G., Bollerslev, T., & Diebold, F. X. (2007). Roughing it up: Including jump components in the measurement, modeling and forecasting of return volatility. Review of Economics and Statistics, 89(4), 701–720.
Bandi, F. M., & Russell, J. R. (2006). Separating microstructure noise from volatility. Journal of Financial Economics, 79, 655–692.
Barndorff-Nielsen, O. E., Graversen, S. E., Jacod, J., Podolskij, M., & Shephard, N. (2006). From stochastic analysis to mathematical finance, festschrift for Albert Shiryaev. New York: Springer.
Barndorff-Nielsen, O. E., & Shephard, N. (2004). Power and bipower variation with stochastic volatility and jumps. Journal of Financial Econometrics, 2, 1–48.
Barndorff-Nielsen, O. E., & Shephard, N. (2006). Econometrics of testing for jumps in financial economics using bipower variation. Journal of Financial Econometrics, 4(1), 1–30.
Cont, R., & Tankov, P. (2004). Financial modelling with jump processes. Chapman & Hall/CRC.
Fan, J., & Wang, Y. (2007). Multi-scale jump and volatility analysis for high-frequency financial data. Journal of the American Statistical Association, 102(480), 1349–1362.
Huang, X., & Tauchen, G. (2005). The relative contribution of jumps to total price variation. Journal of Financial Econometrics, 3, 456–499.
Jacod, J., & Shiryaev, A. N. (1987). Limit theorems for stochastic processes. New York: Springer.
Jiang, G. J., Lo, I., & Verdelhan, A. (2008). Information shocks and bond price jumps: Evidence from the U.S. treasury market. Working Paper.
Jiang, G. J., & Oomen, R. C. (2008). Testing for jumps when asset prices are observed with noise - A “Swap Variance” approach. Journal of Econometrics, 144(2), 352–370.
Lee, S. S., & Mykland, P. A. (2008). Jumps in financial markets: A new nonparametric test and jump dynamics. Review of Financial Studies, 21(6), 2535–2563.
Neuberger, A. (1994). The log contract - A new instrument to hedge volatility. Journal of Portfolio Management, 20(2), 74–80.
Sen, R. (2008). Jumps and microstructure noise in stock price volatility. In G. N. Gregoriou (Ed.), Stock market volatility. Chapman Hall-CRC/Taylor and Francis.
Zhang, L., Mykland, P. A., & Aït-Sahalia, Y. (2005). A tale of two time scales: Determining integrated volatility with noisy high-frequency data. Journal of the American Statistical Association, 100, 1394–1411.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bjursell, J., Gentle, J.E. (2012). Identifying Jumps in Asset Prices. In: Duan, JC., Härdle, W., Gentle, J. (eds) Handbook of Computational Finance. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17254-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-17254-0_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17253-3
Online ISBN: 978-3-642-17254-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)