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On factorial HMMs for time series in finance
Saidane, Mohamed
;
Lavergne, Christian
- In:
The Kyoto economic review
75
(
2006
)
1
,
pp. 63-90
Persistent link: https://www.econbiz.de/10009934656
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2
A new online method for event detection and tracking : empirical evidence from the French stock market
Saidane, Mohamed
;
Lavergne, Christian
- In:
American journal of finance and accounting
1
(
2008/09
)
1
,
pp. 20-51
Persistent link: https://www.econbiz.de/10009887798
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3
Optimal prediction with conditionally heteroskedastic factor analysed hidden Markov models
Saidane, Mohamed
;
Lavergne, Christian
- In:
Computational economics
34
(
2009
)
4
,
pp. 323-364
Persistent link: https://www.econbiz.de/10003894935
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4
A new online method for event detection and tracking : empirical evidence from the French stock market
Saidane, Mohamed
;
Lavergne, Christian
- In:
American journal of finance and accounting
1
(
2008/09
)
1
,
pp. 20-51
Persistent link: https://www.econbiz.de/10003773988
Saved in:
5
A structured variational learning approach for switching latent factor models
Saidane, Mohamed
;
Lavergne, Christian
- In:
Advances in statistical analysis : AStA ; a journal of …
91
(
2007
)
3
,
pp. 245-268
Persistent link: https://www.econbiz.de/10003558111
Saved in:
6
On factorial HMMs for time series in finance
Saidane, Mohamed
;
Lavergne, Christian
- In:
The Kyoto economic review
75
(
2006
)
1
,
pp. 63-90
Persistent link: https://www.econbiz.de/10003475184
Saved in:
7
Modelling and forecasting volatility dynamics using quadratic GARCH-factor models : empirical evidence from international foreign exchange markets
Saidane, Mohamed
;
Lavergne, Christian
- In:
Stock returns : cyclicity, prediction and economic …
,
(pp. 231-267)
.
2009
Persistent link: https://www.econbiz.de/10003945037
Saved in:
8
A generalised latent Poisson factor modelling approach for default correlations in credit portfolios
Saidane, Mohamed
- In:
Journal of risk management in financial institutions
17
(
2023
)
1
,
pp. 89-105
Persistent link: https://www.econbiz.de/10014489156
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