Assumptions about the dynamic and distributional behavior of risk factors are crucial for the construction of optimal portfolios and for risk assessment. Although asset returns are generally characterized by conditionally varying volatilities and fat tails, the normal distribution with constant...

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,...

The literature on the licensing of an innovation has mainly focused on some speci c contract types. We show within the framework of a fairly general model that removing these contractual limitations will lead to extreme market outcomes. Speci cally, we nd that when the patentee can employ...

We introduce a fairly general licensing model with an endogenous industry structure - in terms of number of active firms - and general licensing contracts. We show that when the patentee can employ contracts that can condition on market entry or price, it can implement an outcome that yields...

This paper examines situations where two vertically integrated firms consider supplying an input to an independent downstream competitor via privately observed contracts. We identify equilibria where competition in the upstream market emerges—the downstream competitor gets supplied—as well...

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 simulatedmoments estimator for option volatilities described in Mizrach (2002); the second is a new approach...

While much of classical statistical analysis is based on Gaussian distributional assumptions, statistical modeling with the Laplace distribution has gained importance in many applied fields. This phenomenon is rooted in the fact that, like the Gaussian, the Laplace distribution has many...

Using unobservable conditional variance as measure, latent-variable approaches, such as GARCH and stochastic-volatility models, have traditionally been dominating the empirical finance literature. In recent years, with the availability of high-frequency financial market data modeling realized...

We present a multivariate generalization of the mixed normal GARCH model proposed in Haas, Mittnik, and Paolella (2004a). Issues of parametrization and estimation are discussed. We derive conditions for covariance stationarity and the existence of the fourth moment, and provide expressions for...