A Double-Threshold GARCH Model for the French Franc/Deutschmark Exchange Rate

By Chris Brooks. 2001

123 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/e3936b015417cf27df82f6165713fa11b6cb4a3c

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Citations in the corpus

THE PERFORMANCE OF SETAR MODELS: A REGIME CONDITIONAL EVALUATION OF POINT, INTERVAL AND DENSITY FORECASTS (2004, background): “Although there have been many applications of threshold models to describe the nonlinearities and asymmetries of exchange rate dynamics (Kräger and Kugler, 1993, Brooks, 1997, 2001), there are still few studies on the forecasting performance of the models, using historical time series data.”
A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors (2001, methodology): “Extension to a double-threshold GARCH model was considered by Brooks (2001). Ling (1999b) showed that, if Pp i1⁄4 1 maxj j (j) i j < 1 and P r i1⁄4 1 maxk (k) i < 1, then there exists a strictly stationary solution {yt; "t} satisfying models (6.1)–(6.3), and E 1 (j yt j) and E 2 (" (2)t ) are finite”
The Two-sided Weibull Distribution and Forecasting Financial Tail Risk (2013, methodology): “The two top ranked models based on average ESRate ratios, with values of 1.02 and 1.05, are the GARCH and T-GARCH with STW errors.”
Bayesian Time-Varying Quantile Forecasting for Value-at-Risk in Financial Markets (2011, methodology): “We focus on the conditional autoregressive VaR (CAViaR) models proposed by Engle and Manganelli (2004), to estimate quantiles (VaR) directly, and expand the existing CAViaR models into a fully nonlinear family of dynamic models, in the spirit of threshold GARCH modeling (see Zakoian 1994 and Brooks ”
On a threshold heteroscedastic model (2006, methodology): “Brooks (2001) further generalizes this to a double threshold GARCH model.”