ACIFF 2013

2nd International Workshop on Applying Computational Intelligence Techniques in Financial Time Series Forecasting and Trading

A Special Issue with extended versions of selected papers from the ACIFF workshop will be published in the Computational Economics Journal (Springer).

Summary

Computational Intelligence – a sub-branch of Artificial Intelligence – studies are primarily inspired by the laws of nature and adaptive mechanisms in order to enable or facilitate intelligent behavior in changing complex environments. These mechanisms include these Artificial Intelligence paradigms that exhibit an ability to learn and adapt to new situations, to generalize, abstract and discover new knowledge. The following paradigms are commonly associated with Computational Intelligence: artificial neural networks, evolutionary computation, swarm intelligence, artificial immune systems, and fuzzy systems. Individual techniques from these Computational Intelligence paradigms, as well as combinations (hybrid methods) of these paradigms, have been applied successfully to solve a variety of real world problems. In particular, these techniques have been widely applied to time series prediction, financial forecasting and trading.

The aim of this workshop is to serve as an interdisciplinary forum for bringing together specialists from the scientific areas of Computer Engineering, Finance and Operational Research. The focus of this workshop is on current technological advances and challenges about the applications of computational intelligence techniques in financial time-series forecasting and trading.

Therefore, the Workshop on “Applying Computational Intelligence Techniques in Financial Time Series Forecasting and Trading” will welcome paper submissions introducing and implementing Computational Intelligent techniques to address various modeling and predicting financial applications. This workshop will provide a medium for the exchange of ideas between theoreticians and practitioners.

Topics of interest

Topics of interest include, but are not limited to, the use of techniques like:

  • Traditional and Statistical Techniques
    • Autoregressive Moving Average (ARMA) techniques
    • Moving Average (MA) techniques
    • Fundamental trading techniques and strategies
    • Regressive Forecasting
    • Volatility based trading
    • Bayesian and likelihood based techniques
  • Artificial Neural Networks
    • Multi Layer Perceptrons
    • Higher Order Neural Networks
    • Recurrent Neural Networks
    • Radial Basis Function Neural Networks
    • Support Vector Machines
  • Evolutionary Techniques
    • Genetic Programming
    • Gene Expression Programming
    • Linear Genetic Programming
    • Evolutionary Strategies
    • Genetic Algorithm based hybrid techniques
    • Advanced and/or Hybrid Techniques
    • Random Trees – Random Forests
    • Fuzzy Logic based Techniques
    • Ensemble Techniques
    • Hybrid Techniques
    • Swarm Intelligence and Differential Evolution based Hybrid Techniques
  • Workshop Chairs

    Spiridon D. Likothanassis, University of Patras, Greece likothan@ceid.upatras.gr
    Efstratios F. Georgopoulos, Technological Educational Institute (T.E.I.) of Kalamata, Greece sfg@teikal.gr
    Georgios Sermpinis, University of Glasgow, Scotland georgios.sermpinis@glasgow.ac.uk
    Andreas S. Karathanasopoulos, London Metropolitan University, UK a.karathanasopoulos@londonmet.ac.uk
    Konstantinos Theofilatos, University of Patras, Greece theofilk@ceid.upatras.gr

    Academic Program Committee

    Spiridon D. Likothanassis, University of Patras, Greece
    Christian Dunis, Liverpool John Moores University, UK
    Hans-Jörg von Mettenheim, Institut für Wirtschaftsinformatik, Germany
    Efstratios F. Georgopoulos, Technological Educational Institute (T.E.I.) of Kalamata, Greece
    Georgios Sermpinis, University of Glasgow, Scotland
    Andreas S. Karathanasopoulos, London Metropolitan University, UK
    Rafael Rosillo, University of Oviedo, Spain
    Andreas Andreou, Cyprus University of Technology, Cyprus
    Grigorios Beligiannis, University of Western Greece, Greece
    Harris Papadopoulos, Frederick University, Cyprus
    Efi Papatheocharous, University of Cyprus, Cyprus

    Submission

    Authors are invited to submit original, English-language research contributions or experience reports. Papers should be no longer than 10 pages formatted according to the well-known LNCS Springer style. All aspects of the submission and notification process will be handled online via the EasyChair Conference System at:

    https://www.easychair.org/conferences/?conf=aiai2013

    Please make sure you select the workshop track in the first step of the submission process.

    Important Dates

    Paper submission:
    May 10, 2013 Extended: May 15, 2013

    Author notifications:
    May 30, 2013 Extended: June 7, 2013

    Camera-ready submission:
    June 7, 2013 Extended: June 21, 2013

    Early registration:
    June 7, 2013 Extended: June 14, 2013

    Publication

    Submitted papers will be refereed for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email. Accepted papers will be presented at the workshop and published in the Proceedings of the main event (by Springer). They will also be considered for potential publication in the Special Issues of the Conference.

    Registration fees and benefits for the workshops’ participants are exactly identical with the ones of the main AIAI 2013 event.