Predicting volatility and correlations with Financial Conditions Indexes
We model the impact of financial conditions on asset market volatilities and correlations. We extend the Spline-GARCH model for volatility and DCC model for correlation to allow for inclusion of 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 correlations between stock returns, especially during crises. Moreover, inclusion of the FCI in volatility and correlation modeling improves Value-at-Risk estimates, particularly at short horizons.
|Keywords||Bank holding companies, Dynamic correlations, Financial Conditions Indexes, Volatility modeling|
|Persistent URL||dx.doi.org/10.1016/j.jempfin.2014.10.003, hdl.handle.net/1765/101550|
|Journal||Journal of Empirical Finance|
Opschoor, A, van Dijk, D.J.C, & van der Wel, M. (2014). Predicting volatility and correlations with Financial Conditions Indexes. Journal of Empirical Finance, 29, 435–447. doi:10.1016/j.jempfin.2014.10.003