
Michael Johannes
· Mario J. Gabelli Professor of Finance; Chair of Finance DivisionColumbia University · French and Italian
Active 2000–2026
Research topics
- Economics
- Business
- Financial economics
- Physics
- Econometrics
- History
- Actuarial science
- Monetary economics
Selected publications
Time-varying macroeconomic announcement risk
Journal of Econometrics · 2026-02-03
articleOpen access1st authorThis paper examines an issue overlooked in the finance and economics literature: time variation in announcement volatility or event risk. To identify this, we combine long spans of high-frequency data with a flexible model of returns. The model allows us to separately identify conditional event risk from other factors like time-varying volatility, jumps and intraday periodicity, and long time spans of data are needed given the infrequency of most announcements. We focus on crude oil due to its economic importance, high volatility and complex announcement structure. Results indicate strong evidence for time-varying announcement volatility as announcement event risk varies by as much as a factor of 10 over time.
SSRN Electronic Journal · 2024 · 3 citations
1st authorCorresponding- Economics
- Financial economics
- Business
SSRN Electronic Journal · 2023 · 5 citations
1st authorCorresponding- Business
- Monetary economics
- Economics
Time-Varying Macroeconomic Announcement Risk
SSRN Electronic Journal · 2022 · 1 citations
1st authorCorrespondingB2 stress indices for thin walled straight pipes with D/t > 50 and imperfections
International Journal of Pressure Vessels and Piping · 2018-05-28 · 1 citations
articleSenior authorAnticipated Uncertainty, Earnings Announcements and Equity Options
Review of Financial Studies · 2018-01-01
articleSenior authorOption Pricing of Earnings Announcement Risks
Review of Financial Studies · 2018-05-11 · 97 citations
articleOpen accessCorrespondingThis paper uses option prices to learn about the equity price uncertainty surrounding information released on earnings announcement dates. To do this, we introduce reduced-form models and estimators to separate price uncertainty about earnings announcements from normal day-to-day volatility. Empirically, we find strong support for the importance of earnings announcements. We find that the anticipated price uncertainty is quantitatively large, varies across time, and is informative about the future return volatility. Finally, we quantify the impact of earnings announcements on formal option pricing models. Received April 13, 2017; editorial decision February 5, 2018 by Editor Stijn Van Nieuwerburgh. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
Asset Pricing When ‘This Time Is Different’
Review of Financial Studies · 2016-09-30 · 76 citations
articleOpen accessRecent evidence suggests that younger people update beliefs in response to aggregate shocks more than older people. We embed this generational learning bias in an equilibrium model in which agents have recursive preferences and are uncertain about exogenous aggregate dynamics. The departure from rational expectations is statistically modest, but generates high average risk premiums varying at generational frequencies, a positive relation between past returns and agents' future return forecasts, and substantial and persistent over-and undervaluation. Consistent with the model, the price-dividend ratio is empirically more sensitive to macroeconomic shocks when the fraction of young in the population is higher.
Replication data for: Parameter Learning in General Equilibrium: The Asset Pricing Implications
ICPSR Data Holdings · 2016-01-01
datasetOpen accessParameter learning strongly amplifies the impact of macroeconomic shocks on marginal utility when the representative agent has a preference for early resolution of uncertainty. This occurs as rational belief updating generates subjective long-run consumption risks. We consider general equilibrium models with unknown parameters governing either long-run economic growth, rare events, or model selection. Overall, parameter learning generates long-lasting, quantitatively significant additional macroeconomic risks that help explain standard asset pricing puzzles. (JEL C52, D83, E13, E32, G12)
Failure of Thin-Walled Pipes With D/T up to 140 and Conclusions for the Design Codes
2016-07-17 · 1 citations
articleSenior authorThe influence of imperfections on the instability bending moment of thin-walled straight pipes with D/t-ratios (D - outside diameter, t - wall thickness) up to 140 is determined using nonlinear Finite Element (FE) analyses. The analyses show that the type and size of the imperfection, the D/t ratio and the material properties have significant influences on the instability moment. The nominal bending stress of pipes (yield stress 500 MPa) with D/t > 70 and an ovality of 0.5% is smaller than the yield stress at the instability point. That means, the failure occurs by buckling in the elastic range of the nominal bending stress. In static analyses the moment decreases abruptly after reaching the instability moment. In the dynamic analyses the pipe jumps abruptly to the state with smaller moment. The obtained results are applied to calculate the B2 index for pipes with D/t ≤ 140. The B2 indices for thin-walled straight pipes with D/t > 40 are considerably higher than 1.0. In general, there is a good agreement between the calculated B2 values and the values of the ASME Code. A correction factor for higher temperatures is not necessary. The allowable moments calculated with the B2 index and the stress intensification factor i are compared. The bending moments from disabled thermal expansion and anchor movements have the same effect on the failure due to (plastic) buckling as the primary moments and must be taken into account.
Frequent coauthors
- 14 shared
Pierre Collin‐Dufresne
- 13 shared
Nicholas Polson
- 13 shared
Lars A. Lochstoer
Anderson University - South Carolina
- 10 shared
Jonathan Stroud
Georgetown University
- 9 shared
Nick Polson
- 8 shared
Nicholas G. Polson
- 6 shared
Hedibert F. Lopes
Insper
- 6 shared
Carlos M. Carvalho
Universidade do Estado da Bahia
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