English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Using the concept of self-decomposable subordinators introduced in Gardini etal. [11], we build a new bivariate Normal Inverse Gaussian process that cancapture stochastic delays. In addition, we also develop a novel path simulationscheme that relies on the mathematical connection between self-decomposableInverse Gaussian laws and L\'evy-driven Ornstein-Uhlenbeck processes withInverse Gaussian stationary distribution. We show that our approach provides animprovement to the existing simulation scheme detailed in Zhang and Zhang [23]because it does not rely on an acceptance-rejection method. Eventually, theseresults are applied to the modelling of energy markets and to the pricing ofspread options using the proposed Monte Carlo scheme and Fourier techniques

A bivariate Normal Inverse Gaussian process with stochastic delay: efficient simulations and applications to energy markets