Using an unified framework, we integrate the two major Monte Carlo techniques currently available: Efficient Importance Sampling (EIS) and Markov Chain Monte Carlo (MCMC). We do so for two reasons. First, the two methods complement one another. Loosely, EIS is effective for integrating...

The performance of Monte Carlo integration methods like importance-sampling or Markov-Chain Monte-Carlo procedures depends greatly on the choice of the importance- or candidate-density. Such a density must typically be "close" to the target density to yield numerically accurate results with...

A dynamic Tobit model with Time-varying parameters is proposed for the daily reaction function of the Open Market Desk of the US Federal Reserve. Such a model offers a more realistic depiction of the Desk's behavior than those of past contributions in the literature as it allows for both...

The last couple of decades has witnessed a growing interest in hedge funds. Academics and practitioners are intrigued by the distinct characteristics of these investment vehicles: hedge funds are flexible with respect to the types of securities they hold and the type of positions they take; they...