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Markov Switching Models and their Applications in Finance

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Markov Switching Models and their Applications in Finance

Mainly Wednesdays 15:30 - 17:00 in 48-438, see below.

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Lecture

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The next lecture is Wednesday, Nov. 22, at 16:15 in 48-438.

Lecture notes up to Section 3.1 available now.

Please register for the lecture until October 27, noon, in URM .

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Lecture

Content: This lecture gives an introduction to Markov switching models in continuous time and hidden Markov models in a discrete time setting. Topics cover filtering and parameter estimation, inference and the modelling and prediction of financial time series with focus on asset price prediction and portfolio optimization, see Modulbeschreibung (in German).

Literature:

  • Bain, Crisan: Fundamentals of Stochastic Filtering
  • Cappé, Moulines, Rydén : Inferences in Hidden Markov Models
  • Elliott, Aggoun, Moore: Hidden Markov Models - Estimation and Control
  • Frühwirth-Schnatter: Finite Mixture and Markov Switching Models
  • Tsay: Analysis of Financial Time Series

Lecture notes: During the term.

Prerequisites: "Probability Theory" or "Mathematical Statistics" are essential. "Financial Mathematics" and "Regresion and Time Series Analysis" are recommendend.

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