Predicting Covariance Matrices with Financial Conditions Indexes

Arbeitspapier

We model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we consider daily stock returns of US deposit banks during the period 1994-2011, and proxy financial conditions by the Bloomberg Financial Conditions Index (FCI) which comprises the money, bond, and equity markets. We find that worse financial conditions are associated with both higher volatility and higher average correlations between stock returns. Especially during crises the additional impact of the FCI indicator is considerable, with an increase in correlations by 0.15. Moreover, including the FCI in volatility and correlation modeling improves Value-at-Risk forecasts, particularly at short horizons.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. 13-113/III

Classification and Topics

• Classification: Wirtschaft ; Financial Forecasting and Simulation ; Pension Funds; Non-bank Financial Institutions; Financial Instruments; Institutional Investors ; Financial Markets and the Macroeconomy
• Subject: Dynamic correlations ; Volatility modeling ; Financial Conditions Indexes ; Bank holding companies

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Opschoor, Anne ; van Dijk, Dick ; van der Wel, Michel
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/87165
• Last update: 17.03.2025, 2:28 PM CET