Univ. Heidelberg
Statistics Group   Institute of Applied Mathematics   Faculty of Mathematics and Computer Science   University Heidelberg
Ruprecht-Karls-Universität Heidelberg Statistics of inverse problems Research Group Seminar Stochastic volatility models (WS 2020/21)
english



Time and location
Seminar program
Requirements
References
Last edited on
2020/09/11 by jj
.
Preliminary discussion:
Tuesday, November 3rd, 2020, 15:15

Registration:
Please register for the seminar by using MÜSLI.

Time and location of the seminar:
The seminar will be held as a Blockseminar on two days in January 2021.

Contact:
Sergio Brenner Miguel <brennermiguel[at]math.uni-heidelberg.de>
Jan JOHANNES <johannes[at]math.uni-heidelberg.de>
Questions, please directly by email or by using the contact form.

Language:
The seminar will be in English, if there is at least one non-German speaking participant.

Field:
Applied Mathematics, Stochastics

Description of the seminar:
The stochastic volatility model is a frequently used model in modern econometrics. In the last decades many authors introduced several different notion of volatility to model their believes in the underlying economically phenomenons. In this seminar we will focus on the statistical inferences on these models and the naturally occurying dependency structures on the data.

Possible presentation topics are:
Advanced probability theory
  • Stochastic differential equations (Achim Klenke:Probability theory, 2 talks )
Parametric statistics
  • Limit theorems for discretely observed stochastic volatility models (Genon-Catalot, Jeantheau, Laredo, 2 talks )
  • Parameter estimation for discretely observed stochastiv volatility models (Genon-Catalot, Jeantheau, Laredo, 2 talks )
  • Stochastic volatility models as hidden Markov models and statistical applications (Genon-Catalot, Jeantheau, Laredo, 2 talks )
Nonparametric statistics
  • Kernel deconvolution of stochastic volatility models (Comte, 2 talks )
  • Nonparametric volatility density estimation (Van Es, Spreij, Van Zanten, 1 talk )
  • Penalized projection estimator for volatility density (Comte, Genon-Catalot 2 talks )
  • Nonparametric estimation for a stochastic volatility model (Comte, Genon-Catalot, Rozenholc, 2 talks )

Each participant is expected to give a 60 minutes. A handout containing the most important definitions and results as well as short sketches of the proofs should be prepared for the other participants.

Requirements:
The seminar is for advanced Bachelor students and Master students who want to specialize in statistics and are already familiar with the topics typically covered in the lectures Probability Theory I and Statistics I.

Reference:
"Probability theory" Achim Klenke, Springer Spektrum Link to Heidi
"Limit theorems for discretely observed stochastic volatility models" Genon-Catalot, Jeantheau, Laredo, 1998 Link to PDF
"Parameter estimation for discretely observed stochastic volatility models" Genon-Catalot, Jeantheau, Laredo, 1999 Link to PDF
"Stochastic volatility models as hidden Markov models and statistical applications" Genon-Catalot, Jeantheau, Laredo, 2000 Link to PDF
"Kernel deconvolution of stochastic volatility models" Comte, 2001 Link to PDF
"Nonparametric volatility density estimation" Van Es, Spreij, Van Zanten, 2003 Link to PDF
"Penalized projection estimator for volatility density" Comte, Genon-Catalot, 2006 Link to PDF
"Nonparametric estimation for a stochastic volatility model" Comte, Genon-Catalot, Rozenholc 2007 Link to PDF

Contact
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