This paper introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non-Gaussian Ornstein-Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented. Further we study the...

This paper introduces the class of volatility modulated Lévy-driven Volterra (VMLV) processes and their important subclass of Lévy semistationary (LSS) processes as a new framework for modelling energy spot prices. The main modelling idea consists of four principles: First, deseasonalised spot...

This paper introduces a new continuous-time framework for modelling serially correlated count and integer-valued data. The key component in our new model is the class of integer-valued trawl (IVT) processes, which are serially correlated, stationary, infinitely divisible processes. We analyse...

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility of...

We extend the study of an established parametric latent model for extreme values which captures serial dependence in the exceedances above a threshold using so-called trawl processes - a family of stationary and infinitely divisible random processes. We prove that the observed process is...

This paper studies the effect of time - inhomogeneous jumps and leverage type effects on realised variance calculations when the logarithmic asset price is given by a Levy-driven stochastic volatility model. In such a model, the realised variance is an inconsistent estimator of the integrated...

We extend the study of a parametric latent model for extreme values from Noven et al. (2018) which captures serial dependence in the exceedances above a threshold using so-called trawl processes (Barndorff-Nielsen (2011)) - a family of stationary and infinitely divisible random processes. In...

The importance of solar energy has been growing in recent years. This raises the need for efficient modelling and forecasting methods. The existing methods are predominantly based on weather predictions or forecast solar radiation, which is not easy to convert into production forecast. Instead...

Understanding variance risk is of key importance in mathematical finance since it affects risk management, asset allocation and derivative pricing. Variance risk is priced in financial markets by the so-called variance risk premium (VRP), which refers to the premium demanded for holding assets...