INITIAL TRAINING NETWORKS (January 2013-December 2016)
Call: FP7-PEOPLE-2012-ITN

Multiproject: Multi-ITN STRIKE – Novel methods in computational finance.

General Project Background
In recent years the computational complexity of mathematical models employed in financial mathematics has witnessed a tremendous growth. Advanced numerical techniques are imperative for the most present-day applications in financial industry.

The motivation for this training network is the need for a network of highly educated European scientists in the field of financial mathematics and computational science, so as to exchange and discuss current insights and ideas, and to lay groundwork for future collaborations. Besides a series of internationally recognized researchers from academics, leading quantitative analysts from the financial industry also participate in this network. The challenge lies in the necessity of combining transferable techniques and skills such as mathematical analysis, sophisticated numerical methods and stochastic simulation methods with deep qualitative and quantitative understanding of mathematical models arising from financial markets.

The main training objective is to prepare, at the highest possible level, young researchers with a broad scope of scientific knowledge and to teach transferable skills, like social awareness which is very important in view of the recent financial crises. The current topic in this network is that the financial crisis in the European countries is a contagion and herding effect and is clearly outside of the domain of validity of Black-Scholes and Merton’s theory, since the market is not Gaussian and it is not frictionless and complete. In this research training network our aim is to deeper understand complex (mostly nonlinear) financial models and to develop effective and robust numerical schemes for solving linear and nonlinear problems arising from the mathematical theory of pricing financial derivatives and related financial products. This aim will be accomplished by means of financial modelling, mathematical analysis and numerical simulations, optimal control techniques and validation of models.

The Valencia strike team
Key Scientific Staff:

PostDoctoral Researchers:

STRIKE Fellows:

Ph. D. Students:


  • Phone: 0034-963879144
  • Fax: 0034 963877669
Local Objectives: Numerical Methods for Nonlinear Models
This project will be focused on numerical analysis and computing of numerical solutions for several option pricing models that generalize the Black-Scholes model. Special attention will be paid to stochastic volatility models. Another point of interest will be the partial integro-differential equations (PIDEs) which arise in option pricing theory when the underlying asset is driven by a Lévy process in both cases whewhen the models present finite and infinity activity. The general scenarion when the stochastic volatility models with jumps are assumed will be treated as well as the study of multifactor problems. The study of suitable numerical properties as the consistency, positivity and the stability of the proposed FDMs will be included.
Consortium participants
  • Institute for Modelling, Analysis and Computational Mathematics, Bergische Universität Wuppertal, Germany.
  • Department of Applied Mathematics and Statistics, Comenius University Bratislava, Hungary.
  • Instituto de Matematica Multidisciplinar, Universidad Politecnica Valencia, Spain.
  • Faculty of Nature Sciences and Education, University Rousse, France 5. Centre for Applied Mathematics and Economics, Universidade Tecnica de Lisboa, Portugal.
  • Faculty of Mathematics/Natural Sciences, University of Applied Sciences Zittau, Germany.
  • Institute for Analysis and Scientific Computing, Vienna University of Technology, Austria.
  • Delft Institute of Applied Mathematics, Delft University of Technology, Netherlands.
  • School of Computing and Mathematical Sciences, University Greenwich, United Kingdom.
  • Institute for Mathematics, University of Würzburg, Germany.
  • Department of Mathematics and Computer Science, University of Antwerp, Netherlands Local Research Team.

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