Computational Finance and Big Data


Within the last years, research in advanced computational methods has delivered new instruments, models, approaches and knowledge which can be applied to a large range of problems in finance and economics. The complexity of solving these issues includes enormous financial engineering challenges in diverse areas (e.g. portfolio selection, global trading and risk management among others). Additionally, the vast amount of data involved in these methods plays an important role in bringing value to inter-disciplinary research teams. Developing advanced and sophisticated financial models based on the Big Data perspective is not trivial due the magnitude of the impact on global markets, policy makers, banking sector, etc. These challenges demand the development of new methods and approaches that could evolve the Computational Finance domain supported by Big Data technologies. This special session aims at gathering not only leading researchers, but also young researchers as well as practitioners who do research on Computational Finance and Big Data and their applications.

Researchers are hereby invited to submit a full paper (5-6 pages) detailing their research, or a short paper (max 4 pages) describing their work-in-progress. All submitted papers will be subject to peer reviewing by at least two reviewers for technical merit, significance and relevance to the topics. Further information is available from the CEEC 2016 website http://www.ceec.uk. Submission implies the willingness of at least one author per paper to register, attend the conference and present the paper. Proceedings will be published on IEEE Xplore. Authors of selected articles will be invited to submit an extended version to a Special Issue of the Computers journal (http://www.mdpi.com/journal/computers/special_issues/ceec_2016).

This special session welcomes submissions of computational methods applied (but not limited) to the following topics:

  • Arbitrage Pricing Theory
  • Financial Markets Infrastructures
  • Financial Physics
  • Forecasting and Market Prediction
  • Genetic Models in Economics and Finance
  • High Frequency Trading
  • Macroeconomic Dynamics
  • Market Efficiency and Behavioural Finance
  • Monetary Policies
  • Portfolio Optimization and Analysis
  • Price Movements in Financial Markets
  • Pricing and Complexity in Derivatives
  • Quantitative Finance
  • Risk Management
  • Simulation Models for Economics and Finance
  • Stochastic Programming Models
  • Volatility Modelling
  • Big Data Analytics, Metrics and Visualisation
  • Big Data Applications on Banking
  • Big Data Architectures and Models
  • Big Data Platforms and Security
  • Cloud Computing Techniques for Big Data
  • Machine Learning based on Big Data
  • Next-generation Big Data Applications

Download the Computational Finance and Big Data Call For Papers here (PDF).