In this work, we propose to define Gaussian Processes indexed by multidimensional distributions. In the framework where the distributions can be modeled as i.i.d realizations of a measure on the set of distributions, we prove that the kernel defined as the quadratic distance between the...

IV regression in the context of a re-sampling is considered in the work. Comparatively, the contribution in the development is a structural identication in the IV model. The work also contains a multiplier-bootstrap justication.

The paper examines the potential of deep learning to produce decision support models from structured, tabular data. Considering the context of financial risk management, we develop a deep learning model for predicting whether individual spread traders are likely to secure profits from future...

We model the term structure of implied volatility (TSIV) with an adaptive approach to improve predictability, which treats dynamic time series models of globally time- varying but locally constant parameters and uses a data-driven procedure to ?nd the local optimal interval. We choose two...