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Statistical Methods in Financial Risk Management

Statistical Methods in Financial Risk Management
Typ: Vorlesung
Lehrstuhl: Statistik, Ökonometrie und Mathematische Finanzwirtschaft
Semester: WS 2012/2013
Ort:

Geb. 20.13, 006 (V)
Geb. 20.13, 006 (Ü)

Zeit: Montag 9:45 – 11:15 (V)
Montag 11:30 – 13:00 (Ü)
Beginn: 15.10.2012
Dozent:

Kim

SWS: 4
LVNr.: 2521353
Prüfung:

Mündlich, nach Vereinbarung

Hinweis:

To be held in English

Inhalt

The course will cover the following topics:

Part 1: Financial Risk Management: risk indicators at instrumental level; (Single Fixed Flow, Fixed Rate Bond, FRA, Interest Rate Futures, Interest Rate Swaps, FX Spot, FX Forward, Plain Vanilla Options), Credit Risk, Risk Indicators at the Portfolio Level (Pricing Environment, Interest Rate Factors, FX Factors), Value-at-Risk (VAR) and Asset-Liability Management, Risk Metrics - Market Risk in a Single Position. Measures of Market Risk: (Linear and Non-linear Positions), Market Risk Limits, Calibrating Valuation and Risk Models Performance Evaluation, Probability Distributions and Statistical Assumptions Forecasting Volatilities and Correlations (Basic Design, Ex-post Estimation, Ex-ante Estimation - Forecasting, Defining the Optimal Decay Factor), Assessing Performance (Univariate and Multivariate Tail Probabilities), Mathematics of Structures Monte Carlo (Generating Statistics, Properties of the Correlation Matrix), Mapping Algorithms (Fixed Income, Foreign Exchange, Commodities, Options). Models for Credit Risk: Introduction to Operational Risk

Part 2: Optimal portfolio management: portfolio construction, long/short investing, transaction costs and turnover, performance analysis, asset allocation, benchmark timing. Integrating the equity portfolio management process, active versus passive portfolio management, tracking error (backward-looking versus forward looking tracking error, the impact of portfolio size, benchmark volatility and portfolio betas on tracking error), equity style management (types of equity styles, style classification system), passive strategies(constructing an index portfolio, index tracking and cointegration), active investing (top-down and bottom-up approaches to active investing, fundamental law of active management, strategies based on technical analysis, technical analysis and statistical pattern recognition, market-neutral strategies and statistical arbitrage), application of multifactor risk models(risk Decomposition, Portfolio construction and Risk Control, Assessing the exposure of a portfolio, Risk control against a stock-market index, Tilting a portfolio).


Literatur

Fat-Tailed and Skewed Asset Return Distributions: Implications for  Risk Management, Portfolio Selection, and Option Pricing,  Rachev, S.,  Menn, C. and Fabozzi, F., John Wiley, Finance, 2005
Financial Optimization, Zenios, S. A., Cambridge University Press, 1993
The Mathematics of Financial Modeling and Investment Management, Focardi, S., and Fabozzi, F., Wiley, 2004

 

 

Excercises