Computational Optimization Methods in Statistics, Econometrics and Finance

Partners involved
Univ. Paris-Dauphine (Local organizer of part I), Univ. of Copenhagen (Local organizer of part II), Univ. of Giessen, Imperial College, Univ. of Zurich, Univ. de Genève, Deutsche Bank

Date and location:
Part I: 18/10/2007 - 20/10/2007 in London

Motivation and objectives

Techniques of financial econometrics and mathematical finance are of increasing importance in financial practice. The goal of these tutorials is to provide the necessary background in fundamental concepts and to illustrate how to apply them to major issues in finance and financial economics. The tutorials cover fundamental topics in empirical asset pricing, risk management, in particular credit risk valuation and credit risk management modelling (accounting for dependencies across obligors), portfolio optimization, term structure modelling as well as market microstructure analysis.

Organization

Both tutorials will comprise two days with six lectures of 90 minutes and an afternoon "hands on" session in the computer laboratory.

Part I:

1. Empirical concepts in risk management: Estimating Value-at-Risk; application of extreme value theory in risk management.
2. (Multivariate) stochastic volatility models.
3. Derivative pricing I: The pricing of standard options.
4. Derivative pricing II: The pricing of exotic options. The pricing of credit derivatives.
5. Evaluation of credit risk.
6. Credit risk management: Accounting for dependencies across obligors.
7. "Hands-on" session with real financial datasets.

Part II:

1. Estimation and testing of asset pricing models: Stochastic discount factor.
2. Consumption-based asset pricing using GMM techniques: Estimating empirical stochastic discount factors; multi-factor asset pricing models.
3. Portfolio optimization and asset allocation: Empirical concepts for the portfolio construction; portfolio evaluation.
4. Dynamic portfolio optimization: Optimal asset allocation and performance attribution.
5. Term structure modelling: Estimating the term structure of interest rates; affine yield models.
6. Empirical analysis of financial transaction data: Modelling the intraday trading process; volatility and liquidity measurement; assessment of market microstructure relations.
7. "Hands-on" session with financial datasets.