Portfolio optimization when risk factors are conditionally varying and heavy tailed

Arbeitspapier

Assumptions about the dynamic and distributional behavior of risk factors are crucial for the construction of optimal portfolios and for risk assessment. Although asset returns are generally characterized by conditionally varying volatilities and fat tails, the normal distribution with constant variance continues to be the standard framework in portfolio management. Here we propose a practical approach to portfolio selection. It takes both the conditionally varying volatility and the fat-tailedness of risk factors explicitly into account, while retaining analytical tractability and ease of implementation. An application to a portfolio of nine German DAX stocks illustrates that the model is strongly favored by the data and that it is practically implementable.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CFS Working Paper ; No. 2006/24

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Portfolio Choice; Investment Decisions ; Information and Market Efficiency; Event Studies; Insider Trading ; General Financial Markets: Government Policy and Regulation
• Subject: Multivariate Stable Distribution ; Index Model ; Portfolio Optimization ; Value-at- Risk ; Model Adequacy ; Portfolio-Management ; Value at Risk

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Doganoglu, Toker ; Hartz, Christoph ; Mittnik, Stefan
• Event: Veröffentlichung
• (who): Goethe University Frankfurt, Center for Financial Studies (CFS)
• (where): Frankfurt a. M.
• (when): 2006

Further information

• Handle: http://hdl.handle.net/10419/25490
• URN: urn:nbn:de:hebis:30-33306
• Last update: 10.03.2025, 11:44 AM CET