We propose an integrated model of the joint dynamics of FX rates and asset prices for the pricing of FX derivatives, including Quanto products; the model is based on a multivariate construction for Levy processes which proves to be analytically tractable. The approach allows for simultaneous...

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

We solve a dynamic general equilibrium model with generalized disappointment aversion preferences and continuous state endowment dynamics. We apply the framework to the term structure of interest rates and show that the model generates an upward sloping term structure of nominal interest rates,...

In this paper we apply the multivariate construction for Lévy processes introduced by Ballotta and Bonfiglioli (2014) to propose an integrated model for the joint dynamics of FX exchange rates and asset prices. We show that the proposed construction is consistent in terms of symmetries with...

This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....

Semantic frames are a rich linguistic resource. There has been much work on semantic frame parsers, but less that applies them to general NLP problems. We address a task to predict change in stock price from financial news. Semantic frames help to generalize from specific sentences to scenarios,...