University of Oxford
Carlos Vázquez Cendón
University of A Coruña
This volume of The Journal of Computational Finance is a special issue of peer-reviewed articles related to works presented at the Third International Conference on Computational Finance (ICCF2019). Following successful events in Greenwich (2015) and Lisbon (2017), this third incarnation, organized by the University of A Coruña, brought around 120 participants from 25 countries to A Coruña (Spain) from July 8 to 11, 2019.
ICCF2019 included plenary talks from academic researchers and industry professionals, minisymposia and contributed talks. The presentations covered diverse topics of current interest on the modeling and computational aspects of financial problems. The program included an industrial roundtable on hot topics in the financial industry.
Among the attendees were an encouraging number of young researchers. Although the competition was tight due to the high standard of entries, the Journal of Computational Finance Young Researcher Award for the best work submitted by a researcher within five years of completing their PhD was ultimately presented to Anastasia Borovykh and Beatriz Salvador.
The Organizing Committee of ICCF2019 is grateful to all participants for their stimulating scientific discussions, to the Scientific Committee for its valuable input on the scientific program, to the local Organizing Committee coordinated by Iñigo Arregui for its enthusiasm and the smooth running of the conference, to the Fundación Barrié and Afundación for hosting ICCF2019 in their buildings, and, last but not least, to all of the event’s sponsors: the Xunta de Galicia government through the “Axudas de Consolidacion a Grupos de referencia competitiva” program; the Spanish Research Agency through the Strategic Mathematics Network (REM); the Galician Singular Research Center CITIC; the Technological Institute of Industrial Mathematics (ITMATI); the European Consortium of Mathematics and Industry (ECMI); the European Commission’s Horizon 2020 Programme; the Spanish bank Abanca; the University of A Coruña; and our publisher, Risk.net.
This special issue comprises eight papers across two volumes. In the first paper, “Nowcasting networks”, Marc Chataigner, Stéphane Crépey and Jiang Pu introduce a new type of neural network architecture that is able to reconstruct surfaces such as implied volatility from given time series of meshed data in real time. The authors use numerical examples of repurchase agreement curves, equity options and swaptions to show the efficacy of their approach.
“Introducing two mixing fractions to a lognormal local-stochastic volatility model”, our second paper, finds Geoffrey Lee, Bowie Owens and Zili Zhu discussing the calibration of local stochastic volatility models to exotic contracts by introducing a mixing fraction for the correlation on top of the more traditional mixing of the volatility-of-volatilities. The authors demonstrate numerically that the extra time-dependent parameter allows a good fit for some one-touch contracts.
Fabien Le Floc’h and Cornelis W. Oosterlee, previous editor of The Journal of Computational Finance, consider an extension of the Heston stochastic volatility model for derivative valuation, which was recently proposed in the literature, in “Numerical techniques for the Heston collocated volatility model”, this issue’s third paper. The authors discuss their Heston collocated volatility model in detail, along with its calibration and numerical solution.
In our final paper, “A Libor market model including credit risk under the real world measure”, Sara Dutra Lopes and Carlos Vázquez model simply compounded forward interest rates corresponding to different credit ratings under the real-world probability measure, allowing for negative interest rates. The authors also present a simulation methodology for generating future interest rate scenarios.
The authors devise a neural network-based compression/completion methodology for financial nowcasting.
The authors present a methodology to generate future scenarios of interest rates for different credit ratings under a real-world probability measure.
In this paper, the authors introduce two mixing fractions that can be controlled separately to apply impact to the volatility-of-volatility and the correlation in a lognormal LSV model.
In this paper, the authors discuss all aspects of derivative pricing under the Heston–CLV model: calibration with an efficient Fourier method; a Monte Carlo simulation with second-order convergence; and accurate partial differential equation pricing…