Advanced Asset Pricing (WiSe 2024/25)


Veranstaltungsnummer
048328

Vorlesungsverzeichnis

Learnweb-Plattform

Typ
Doktorandenseminar

Vorlesungssprache
englisch


Veranstaltungszeitplan

Tag Zeit Häufigkeit Datum Raum
Montag 08:00- 10:00 Uhr wöchentlich 07.10.2024- 18.11.2024 Juridicum, JUR 253
Dienstag 08:00- 10:00 Uhr wöchentlich 08.10.2024- 19.11.2024 Juridicum, JUR 253

Hinweis

The first part of the course deals with asset allocation. It goes back to the seminal portfolio theory of Markowitz. We look at the optimal asset allocation decisions – and also at the optimal consumption-investment decisions – in one-period and multi-period models. Important concepts include the impact of relative risk aversion and intertemporal elasticity of substitution. For asset allocation, we study the myopic and hedging demand. For the consumption-investment decision, we consider the income effect and the substitution effect.

The second part of the class deals with asset pricing. General equilibrium models relate (stock) prices and interest rates to fundamentals. They give a relation between future dividend payments, preferences of investors, and prices. We start with the classic Lucas tree model in which consumption is given exogenously. The basic model with i.i.d. consumption growth gives rise to several puzzles, including the equity premium puzzle, the risk-free rate puzzle, and the excess volatility puzzle. These puzzles are solved in modern asset pricing models. The three model classes mostly used today are disaster risk models, models with habit formation, and long-run risks models. We discuss these models and show how to solve them. We also discuss the implications of these models for the pricing of further assets like e.g. options or variance contracts, and we deal with the cross section of asset returns.

The third part of the class covers option pricing models. It goes back to the model of Black and Scholes. In the class, we allow for stochastic volatility and jumps. We give economic explanations for the implied volatility smile such as leverage and crash-o-phobia. Since these models often do not allow for closed-form solutions, the class also discusses numerical procedures like Monte-Carlo simulation. We also discuss option-implied information and its use, which gives us a link back to asset pricing.

Please be aware that the course is intended for PhD candidates, but we welcome applications from other interested students.

Dozenten

  • Prof. Dr. Nicole Branger (verantwortlich)
  • Dr. Timo Wiedemann (begleitend)
  • Leander Gayda (begleitend)