Michael Johannes
Michael Johannes
Professor of Finance, Columbia University
Verifierad e-postadress på gsb.columbia.edu
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The impact of jumps in volatility and returns
B Eraker, M Johannes, N Polson
The Journal of Finance 58 (3), 1269-1300, 2003
1780*2003
Model specification and risk premia: Evidence from futures options
M Broadie, M Chernov, M Johannes
The Journal of Finance 62 (3), 1453-1490, 2007
6322007
The statistical and economic role of jumps in continuous‐time interest rate models
M Johannes
The Journal of Finance 59 (1), 227-260, 2004
5712004
MCMC methods for continuous-time financial econometrics
M Johannes, N Polson
Handbook of Financial Econometrics: Applications, 1-72, 2010
4102010
Particle learning and smoothing
CM Carvalho, MS Johannes, HF Lopes, NG Polson
Statistical Science 25 (1), 88-106, 2010
4042010
Understanding index option returns
M Broadie, M Chernov, M Johannes
The Review of Financial Studies 22 (11), 4493-4529, 2009
2982009
Optimal filtering of jump diffusions: Extracting latent states from asset prices
MS Johannes, NG Polson, JR Stroud
The Review of Financial Studies 22 (7), 2759-2799, 2009
265*2009
Sequential learning, predictability, and optimal portfolio returns
M Johannes, A Korteweg, N Polson
The Journal of Finance 69 (2), 611-644, 2014
194*2014
Parameter learning in general equilibrium: The asset pricing implications
P Collin-Dufresne, M Johannes, LA Lochstoer
American Economic Review 106 (3), 664-98, 2016
1722016
Option pricing of earnings announcement risks
A Dubinsky, M Johannes, A Kaeck, NJ Seeger
The Review of Financial Studies 32 (2), 646-687, 2019
137*2019
The impact of collateralization on swap rates
M Johannes, S Sundaresan
The Journal of Finance 62 (1), 383-410, 2007
136*2007
MCMC maximum likelihood for latent state models
E Jacquier, M Johannes, N Polson
Journal of Econometrics 137 (2), 615-640, 2007
1142007
Learning about consumption dynamics
M Johannes, LA Lochstoer, Y Mou
The Journal of finance 71 (2), 551-600, 2016
982016
Sequential optimal portfolio performance: Market and volatility timing
MS Johannes, N Polson, JR Stroud
Available at SSRN 304976, 2002
842002
Particle learning for sequential Bayesian computation
J Bernardo, M Bayarri, J Berger, A Dawid, D Heckerman, A Smith, M West
Bayesian Statistics 9 9, 317, 2011
802011
Particle filtering
M Johannes, N Polson
Handbook of Financial Time Series, 1015-1029, 2009
482009
State dependent jump models: How do US equity indices jump
M Johannes, R Kumar, NG Polson
Woking Paper, University of Chicago, 1999
461999
Asset pricing when ‘this time is different’
P Collin-Dufresne, M Johannes, LA Lochstoer
The Review of Financial Studies 30 (2), 505-535, 2017
442017
Sequential parameter estimation in stochastic volatility models with jumps
M Johannes, N Polson, J Stroud
Wharton School, University of Pennsylvania, Philadelphia, PA, 2006
332006
Bayesian modeling and forecasting of 24-hour high-frequency volatility
JR Stroud, MS Johannes
Journal of the American Statistical Association 109 (508), 1368-1384, 2014
29*2014
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Artiklar 1–20