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The Impact of Jumps in Volatil...
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MCMC analysis of diffusion models with appliction to finance
Eraker, Bjørn
- In:
Journal of business & economic statistics : JBES ; a …
19
(
2001
)
2
,
pp. 177-191
Persistent link: https://www.econbiz.de/10001568816
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2
Convergence of Markov chain Monte Carlo algorithms
Polson, Nicholas G.
-
1993
Persistent link: https://www.econbiz.de/10000899197
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3
MCMC methods for continuous-time financial econometrics
Johannes, Michael
;
Polson, Nicholas G.
-
2010
Persistent link: https://www.econbiz.de/10003900732
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4
Augmented Markov chain Monte Carlo simulation for two-stage stochastic programs with recourse
Ekin, Tahir
;
Polson, Nicholas G.
;
Soyer, Refik
- In:
Decision analysis : a journal of the Institute for …
11
(
2014
)
4
,
pp. 250-264
Persistent link: https://www.econbiz.de/10010467454
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5
Sequential bayesian learning for stochastic volatility with variance-gamma jumps in returns
Warty, Samir P.
;
Lopes, Hehibert F.
;
Polson, Nicholas G.
-
2014
Persistent link: https://www.econbiz.de/10010440180
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6
Markov Chain Monte Carlo
Johannes, Michael
;
Polson, Nicholas G.
- In:
Handbook of financial time series
,
(pp. 1001-1013)
.
2009
Persistent link: https://www.econbiz.de/10003834286
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7
Particle filtering
Johannes, Michael
;
Polson, Nicholas G.
- In:
Handbook of financial time series
,
(pp. 1015-1029)
.
2009
Persistent link: https://www.econbiz.de/10003834288
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8
MCMC maximum likelihood for latent state models
Jacquier, Eric
;
Johannes, Michael
;
Polson, Nicholas G.
- In:
Journal of econometrics
137
(
2007
)
2
,
pp. 615-640
Persistent link: https://www.econbiz.de/10003442024
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9
Particle learning for fat-tailed distributions
Lopes, Hedibert Freitas
;
Polson, Nicholas G.
- In:
Econometric reviews
35
(
2016
)
8/10
,
pp. 1666-1691
Persistent link: https://www.econbiz.de/10011592384
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