A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...

A new and quite general model class for modeling asset returns and forecasting Value at Risk is proposed. It combines a dynamic multi-component GARCH structure with the stable Paretian distributional assumption. The new model nests several successful models for modeling asset returns, including...

The recently proposed class of MixN-GARCH models, which couple a mixed normal distributional structure with linked GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as well as admirable out-of-sample forecasting performance, for financial...

Financial markets embed expectations of central bank policy into asset prices. This paper compares two approaches that extract a probability density of market beliefs. The first is a simulated moments estimator for option volatilities described in Mizrach (2002); the second is a new approach...

Macroeconomic asset pricing literature is concerned with many puzzling aspects in the financial market. Most prominent are the equity premium puzzle, the risk–free rate puzzle, and the volatility puzzle. Moreover, the literature has come to different conclusions regarding the movement of the...

Sustainable debt has become a key issue in rating of private as well as sovereign debtors. The problem of how to estimate sustainable debt has also been at the center of debate over theAsian 1997-1998 financial crisis. If the external value of the currency depends on the external debt of a...