Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns

Arbeitspapier

In this paper we analyze a multivariate non-stationary regression model empirically. With the knowledge about unconditional heteroscedasticty of financial returns, based on univariate studies and a congruent paradigm in Gürtler and Rauh (2009), we test for a time-varying covariance structure firstly. Based on these results, a central component of our non-stationary model is a kernel regression for pairwise covariances and the covariance matrix. Residual terms are fitted with an asymmetric Pearson type VII distribution. In an extensive study we estimate the linear dependence of a broad portfolio of equities and fixed income securities (including credit and currency risks) and fit the whole approach to provide distributional forecasts. Our evaluations verify a reasonable approximation and a satisfactory forecasting quality with an out performance against a traditional risk model.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper Series ; No. IF43V1

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General
• Subject: heteroscedasticity ; non-stationarity ; nonparametric regression ; volatility ; covariance matrix ; innovation modeling ; asymmetric heavy-tails ; multivariate distributional forecast ; empirical studies

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gürtler, Marc ; Rauh, Ronald
• Event: Veröffentlichung
• (who): Technische Universität Braunschweig, Institut für Finanzwirtschaft
• (where): Braunschweig
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/67961
• Last update: 10.03.2025, 11:45 AM CET