A class of local linear kernel density estimators based on weighted least squares kernel estimation is considered within the framework of Aalen’s multiplicative intensity model. This model includes the filtered data model that, in turn, allows for truncation and/or censoring in addition to...

This paper proposes using realized range-based estimators to draw inference about the quadratic variation of jump-diffusion processes. We also construct a range-based test of the hypothesis that an asset price has a continuous sample path. Simulated data shows that our approach is efficient, the...

This paper proposes using realized range-based estimators to draw inference about the quadratic variation of jump-diffusion processes. We also construct a range-based test of the hypothesis that an asset price has a continuous sample path. Simulated data shows that our approach is efficient, the...

A continuous time econometric modelling framework for multivariate financial market event (or `transactions`) data is developed in which the model is specified via the vector stochastic intensity. This has the advantage that the conditioning sigma-field is updated continuously in time as new...

A continuous time econometric modelling framework for multivariate financial market event (or `transactions') data is developed in which the model is specified via the vector stochastic intensity. This has the advantage that the conditioning sigma-field is updated continuously in time as new...

A continuous time econometric modelling framework for multivariate market event (or 'transactions') data is developed in which the model is specified via the vector stochastic intensity. This has the advantage that the conditioning sigma-field is updated continuously in time as new information...

A continuous time econometric modelling framework for multivariate market event (or transactions) data is developed in which the model is specified via the vector stochastic intensity. This has the advantage that the conditioning sigma-field is updated continuously in time as new information...