Prediction of future security returns is possible by decomposing a securities price into weighted superpositions of underlying basis states, given stationary distributions of the basis states. The (ensemble) Hilbert-Huang transform (HHT) is an empirical two-step online methodology which carries...

The limit order book of an exchange represents an information store of market participants' future aims and for many traders the information held in this store is of interest. However, information loss occurs between orders being entered into the exchange and limit order book data being sent...

We describe novel Bayesian models for time-frequency inverse modelling of non-stationary signals. These models are based on the idea of a "Gabor regression", in which a time series is represented as a superposition of translated, modulated versions of a window function exhibiting good...

Following the Loss Distribution Approach (LDA), this article develops two procedures for the simulation of an annual loss distribution for the modeling of operational risk. First, we provide an overview of the typical compound-process LDA used widely in operational risk modeling, before...

Discrete-time stochastic volatility (SV) models have generated a considerable literature in financial econometrics. However, carrying out inference for these models is a difficult task and often relies on carefully customized Markov chain Monte Carlo techniques. Our contribution here is twofold....