Statistical Methods in Financial Risk Management

  • Typ: Vorlesung
  • Lehrstuhl: Lehrstuhl für Ökonometrie und Statistik
  • Ort:

    Geb. 20.13, Raum 006

  • Zeit:

    Mo 09:45 - 11:15 Uhr
    Mo 11:30 - 13:00 Uhr

  • Beginn: 28.10.2013
  • Dozent:

    Dr. Nazemi

  • SWS: 4
  • LVNr.: 2521353
  • Hinweis:

    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, Credit Scoring, Credit Rating, Risk Indicators at the Portfolio Level (Pricing Environment, Interest Rate Factors, FX Factors), Value-at-Risk (VAR) and Asset-Liability Management, Stress testing, 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, 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, Liquidity Risk and Basel regulation.

     

    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, 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

    § Consumer Credit Models: Pricing, Profit and Portfolio, Thomas, L., Oxford University Press, 2009

    § Financial Optimization, Zenios, S. A., Cambridge University Press, 1993

    The Mathematics of Financial Modeling and Investment Mangement, Focardi, S., and Fabozzi, F., Wiley, 2004