Details

Autor(en) / Beteiligte

• Berger, T.
• Missong, M.

Titel

Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling

Ist Teil von

• International review of financial analysis, 2014-05, Vol.33, p.33-38

Ort / Verlag

Greenwich: Elsevier Inc

Erscheinungsjahr

2014

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Forecasting Value-at-Risk (VaR) for financial portfolios is a crucial task in applied financial risk management. In this paper, we compare VaR forecasts based on different models for return interdependencies: volatility spillover (Engle & Kroner, 1995), dynamic conditional correlations (Engle, 2002, 2009) and (elliptical) copulas (Embrechts et al., 2002). Moreover, competing models for marginal return distributions are applied. In particular, we apply extreme value theory (EVT) models to GARCH-filtered residuals to capture excess returns. Drawing on a sample of daily data covering both calm and turbulent market phases, we analyze portfolios consisting of German Stocks, national indices and FX-rates. VaR forecasts are evaluated using statistical backtesting and Basel II criteria. The extensive empirical application favors the elliptical copula approach combined with extreme value theory (EVT) models for individual returns. 99% VaR forecasts from the EVT-GARCH-copula model clearly outperform estimates from alternative models accounting for dynamic conditional correlations and volatility spillover for all asset classes in times of financial crisis. •We forecast Value-at-Risk for different financial portfolios.•Sample periods cover both calm and turmoil market phases.•We evaluate time-variant and time-invariant return dependency schemes.•Copula approaches with extreme value distributed returns perform best.•The choice of marginal return distributions turns out to be crucial.