We develop a new parametric estimation procedure for option panels observed with error which relies on asymptotic approximations assuming an ever increasing set of observed option prices in the moneyness-maturity (cross-sectional) dimension, but with a fixed time span. We develop consistent...

We analyze the high-frequency dynamics of S&P 500 equity-index option prices by constructing an assortment of implied volatility measures. This allows us to infer the underlying fine structure behind the innovations in the latent state variables driving the movements of the volatility surface....

This survey focuses on two families of nonlinear vector time series models, the family of Vector Threshold Regression models and that of Vector Smooth Transition Regression models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in...

We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with...

Counting processes provide a very flexible framework for modeling discrete events occurring over time. Estimation and interpretation is easy, and links to more familiar approaches are at hand. The key is to think of data as "event histories," a record of times of switching between states in a...

We introduce tractable models for commodity derivatives pricing with inventory and volatility effects, and illustrate with applications to the oil market. We contribute to the existing literature in several respects. First, whereas the previous literature uses futures data for investigating the...

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is...

In this paper we develop a testing and modelling procedure for describing the long-term volatility movements over very long return series. For the purpose, we assume that volatility is multiplicatively decomposed into a conditional and an unconditional component as in Amado and Teräsvirta...

The dynamic dependencies in financial market volatility are generally well described by a long-memory fractionally integrated process. At the same time, the volatility risk premium, defined as the difference between the ex-post realized volatility and the market’s ex-ante expectation thereof,...

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...