Modelling and forecasting multivariate realized volatility

Arbeitspapier

This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter restrictions. We provide an empirical application of the model, in which we show by means of stochastic dominance tests that the returns from an optimal portfolio based on the model's forecasts second-order dominate returns of portfolios optimized on the basis of traditional MGARCH models. This result implies that any risk-averse investor, regardless of the type of utility function, would be better-off using our model.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CoFE Discussion Paper ; No. 08/06

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 ; Forecasting Models; Simulation Methods ; Portfolio Choice; Investment Decisions
• Subject: Forecasting ; Fractional integration ; Stochastic dominance ; Portfolio optimization ; Realized covariance

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Chiriac, Roxana ; Voev, Valeri
• Event: Veröffentlichung
• (who): University of Konstanz, Center of Finance and Econometrics (CoFE)
• (where): Konstanz
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/32169
• URN: urn:nbn:de:bsz:352-opus-116658
• Last update: 10.03.2025, 11:42 AM CET