Model Averaging in Risk Management with an Application to Futures Markets

Arbeitspapier

This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio management. Evaluation of volatility models is then considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for individual as well as average' models. The asymptotic as well as the exact finite-sample distribution of the test statistic, dealing with the possibility of parameter uncertainty, are established. The model averaging idea and the VaR diagnostic tests are illustrated by an application to portfolios of daily returns on six currencies, four equity indices, four ten year government bonds and four commodities over the period 1991-2007. The empirical evidence supports the use of thick' model averaging strategies over single models or Bayesian type model averaging procedures.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 2231

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods ; Portfolio Choice; Investment Decisions
• Subject: model averaging ; Value-at-Risk ; decision based evaluations ; Value at Risk ; Portfolio-Management ; Volatilität ; Prognoseverfahren ; Zeitreihenanalyse ; Financial Futures ; Welt

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Pesaran, Mohammad Hashem ; Schleicher, Christoph ; Zaffaroni, Paolo
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/26276
• Last update: 10.03.2025, 11:45 AM CET