DYNSTOCH Publications

From the Copenhagen Team.

From the Amsterdam Team.

From the Berlin Team.

From the Cartagena Team.

From the Freiburg Team.

From the Helsinki Team.

From the London Team.

From the Padua Team.

From the Paris Team.

Research Plan 2000 - 2004

In the period 2000 - 2004, the DYNSTOCH researcher worked on the following themes. Some of this work has been completed, while other projects are still ongoing. Several new projects that are not listed here have been initiated. In particular work on applications in molecular biology. The numbers in parentheses indicate the team that are most directly involved in the themes. The number are as on the main DYNSTOCH web-page.

Diffusion-type models. Statistical inference for discretely observed diffusion-type models (1,2,4,9); statistical methods for stochastic differential equations with memory (1,3,9); development of a software package for studying stochastic differential equations with memory (3).

Models driven by Lévy processes. Statistical methods for stochastic differential equations driven by Lévy processes (1,2,5,9); stochastic volatility models driven by Lévy processes (1,5); statistical methods for stochastic differential equations with memory driven by Lévy processes (3).

Hidden Markov models. Statistical methods for general hidden Markov models (1,2,4,8,9) and stochastic volatility models (1,2,5,9); realization theory (2,8).

Dynamical spatial/temporal models. Statistical methods for stochastic partial differential equations (1,3), interacting branching diffusions (5) and interacting particle systems (5,9), and marked point processes (1,2,5,7,9); simulation of continuous space-time stochastic models (7).

Asymptotic statistical theory. Asymptotic equivalence of experiments (3,6); geometry in asymptotics and information measures for stochastic processes (2,6,7,8); Hellinger processes for filtered experiments and asymptotic theory for semimartingales (2,7); asymptotics for diffusion-type models (1,3,4,5,9); asymptotics for hidden Markov models (1,9).

Applications in finance. Financial models based on stochastic differential equations driven by Lévy processes (1,2,5,9); term structure models (1,2,3,5,8); models based on stochastic differential equations with memory (3); cointegration for continuous-time models (1,4); relations between continuous-time models and discrete-time models in finance (1,2,3,6,9); application of stochastic system theory (2,8); portfolio optimization under incomplete information (8); probabilistic forecasting and optimality of forecasting methods (7); analysis of financial data (1,3,5,6,7).

Applications in hydrology and turbulence. Modelling of turbulence (1); modelling of rainfall and climate variability (7); analysis of turbulence data (1); analysis of data on rainfall and climate (7).

Applications in telecommunication. Modelling of telecommunication networks (6,9); analysis of data on telecommunication networks (2,6,9).

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