The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Tails, Fears, and Risk Premia
Abstract
We show that the compensation for rare events accounts for a large fraction of the average equity and variance risk premia. Exploiting the special structure of the jump tails and the pricing thereof, we identify and estimate a new Investor Fears index. The index reveals large time‐varying compensation for fears of disasters. Our empirical investigations involve new extreme value theory approximations and high‐frequency intraday data for estimating the expected jump tails under the statistical probability measure, and short maturity out‐of‐the‐money options and new model‐free implied variation measures for estimating the corresponding risk‐neutral expectations.
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Cites
Artzner, P., Delbaen, F., Eber, J., & Heath, D. (1999) · Mathematical Finance · doi:10.1111/1467-9965.00068 · Cited by 8,806
By Force of Habit: A Consumption‐Based Explanation of Aggregate Stock Market Behavior
Campbell, J. Y., & Cochrane, J. H. (1999) · Journal of Political Economy · doi:10.1086/250059 · Cited by 5,210
Stochastic Integration and Differential Equations
Protter, P. E. (2005) · Stochastic Modelling and Applied Probability · doi:10.1007/978-3-662-10061-5 · Cited by 4,583
Embrechts, P., Klüppelberg, C., & Mikosch, T. (1997) · doi:10.1007/978-3-642-33483-2 · Cited by 4,402
Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles
Bansal, R., & Yaron, A. (2004) · The Journal of Finance · doi:10.1111/j.1540-6261.2004.00670.x · Cited by 4,242
Limit Theorems for Stochastic Processes.
Monrad, D., Jacod, J., & Shiryaev, A. N. (1988) · Journal of the American Statistical Association · doi:10.2307/2290171 · Cited by 3,990
Modeling and Forecasting Realized Volatility
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2003) · Econometrica · doi:10.1111/1468-0262.00418 · Cited by 3,863
Self-citationAnswering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts
Andersen, T. G., & Bollerslev, T. (1998) · International Economic Review · doi:10.2307/2527343 · Cited by 3,375
Self-citationIngersoll, J. E., & Duffie, D. (1993) · The Journal of Finance · doi:10.2307/2329081 · Cited by 2,891
Transform Analysis and Asset Pricing for Affine Jump-diffusions
Duffie, D., Pan, J., & Singleton, K. J. (2000) · Econometrica · doi:10.1111/1468-0262.00164 · Cited by 2,712
Cited by
Ilhan, E., Sautner, Z., & Vilkov, G. (2021) · The Review of Financial Studies · doi:10.1093/rfs/hhaa071 · Cited by 1,136
Ilhan, E., Sautner, Z., & Vilkov, G. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3204420 · Cited by 1,136
The Price of Political Uncertainty: Theory and Evidence from the Option Market
KELLY, B., PÁSTOR, Ľ., & VERONESI, P. (2016) · The Journal of Finance · doi:10.1111/jofi.12406 · Cited by 760
Financial Reporting Opacity and Expected Crash Risk: Evidence from Implied Volatility Smirks
Kim, J., & Zhang, L. (2014) · Contemporary Accounting Research · doi:10.1111/1911-3846.12048 · Cited by 486
Bollerslev, T., Li, S. Z., & Todorov, V. (2016) · Journal of Financial Economics · doi:10.1016/j.jfineco.2016.02.001 · Cited by 180
Self-citation
Metadata
- Authors
- BOLLERSLEV, T., & TODOROV, V.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2011-11-14
- Volume
- 66
- Issue
- 6
- Pages
- 2165-2211
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3023591372
- Cited by
- 804
- References
- 66
- FWCI
- 84.85
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
