This paper analyzes the special features of electricity spot prices derived from the physics of this commodity and from the economics of supply and demand in a market pool. Besides mean-reversion, a property they share with other commodities, power prices exhibit the unique feature of spikes in...

With hedgefunds, managers develop risk management models that mainly aim to play on the effect of de correlation.In order to achieve this goal,companies use the correlation coefficient as an indicator for measuring dependencies existing between(i)the various hedge funds strategies and share...

Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identification and correction is therefore an important objective of financial modeling. This paper introduces a simple method to detect outliers in a financial series. It uses an AR(1)–GARCH(1,1) model...

This article adopts the asymmetric DCC with one exogenous variable (ADCCX) model developed by Vargas (2008), by updating the concept of ‘volatility surprise’ to capture cross-market relationships. Current methods for measuring spillovers do not focus on volatility interactions, and neglect...

The thesis draws lessons from behavioural finance and nonlinear econometrics to build models that provide better explanatory and predictive powers of exchange rate dynamics than traditional models. The first article justifies the failure of traditional models by the failure of their underlying...

In 1996, Propp and Wilson introduced coupling from the past (CFTP), an algorithm for generating a sample from the exact stationary distribution of a Markov chain. In 1998, Fill proposed another so–called perfect sampling algorithm. These algorithms have enormous potential in Markov Chain Monte...

We consider the probabilistic numerical scheme for fully nonlinear PDEs suggested in [12], and show that it can be introduced naturally as a combination of Monte Carlo and finite differences scheme without appealing to the theory of backward stochastic differential equations. Our first main...

Reversible jump methods are the most commonly used Markov chain Monte Carlo tool for exploring variable dimension statistical models. Recently, however, an alternative approach based on birth-and-death processes has been proposed by Stephens for mixtures of distributions. We show that the...

We consider the generic problem of performing sequential Bayesian inference in a state-space model with observation process y, state process x and fixed parameter theta. An idealized approach would be to apply the iterated batch importance sampling (IBIS) algorithm of Chopin (2002). This is a...