Saturday, 22 November 2014

Call for Papers IJCNN 2015 Special Session "Modeling and Forecasting Financial and Commodity Markets by Neural Networks"

Special Session for IEEE IJCNN 2015.Updated submission deadline: 5th February, 2015.

Aim and scope

Behaviors of stock price changes in financial and commodity markets have long been a focus of economic research for a more clear understanding of mechanism and characteristics of markets. In the empirical research, some statistical properties for the market fluctuations are uncovered by the high frequency financial time series, such as fat tails distribution of price changes, power-law of logarithmic returns and volumes, volatility clustering, multifractality of volatility, etc. The applications of neural networks in time series forecasting for financial applications have gained enormous popularity in the recent years. In fact, the analysis of financial time series is of primary importance in the economic world; by using a data driven empirical analysis, the goal is to obtain insights into the dynamics of series and out-of-sample forecasting. If one were able to forecast tomorrow’s returns on an asset with some degree of precision, one could use this information in an investment today.

The aim of this special session, which stems by the excellent success obtained during the 2014 IEEE WCCI Conference held in Beijing, is to promote research and reflect the most recent advances of neural networks, including their hybridization with evolutionary computation, fuzzy systems, metaheuristic techniques and other intelligent methods, in a series of practical problems relevant to the interactions between machine learning and financial modeling and forecasting, the main interest being finalized for searching optimal relationships in the area of financial engineering, energy commodity trading, risk management, portfolio optimization, industrial organization, auctions, searching equilibriums, financial forecasting, market simulation, agent-based computational economics, and many other areas.

Topics

The topics of interest to be covered by this Special Session include, but are not limited to:

  • Financial data mining
  • Time series analysis and forecasting
  • Soft computing applications
  • Dynamics of commodity markets
  • Decision support systems
  • Risk analysis and credit scoring
  • Portfolio management
  • Automated trading systems
  • Agent-based computational economics
  • Economic modeling and finance
  • Stock volatility prediction
  • Investment strategy
  • Artificial economics
  • Simulation of social processes

Important Dates

Paper submission UPDATED: February 5, 2015
Paper decision notification: March 15, 2015
Camera-ready submission: April 15, 2015
Conference days: July 12-17, 2015

Submission

Manuscripts submitted to special sessions should be done through the paper submission website of IJCNN 2015. All papers submitted to special sessions will be subject to the same peer-review procedure as the regular papers. If a sufficient number of papers are accepted to fill a special session, then it will be included in the final program. If not enough papers are accepted for this special session, then the accepted papers will be automatically moved to regular sessions.

The authors intended to contribute to this special session are kindly recommended to follow the manuscript style information and templates of regular IJCNN 2015 papers, as described here.

When submitting their manuscripts, authors are recommended to follow these steps:
  1. select the Special Session ID and Name in the “Main research topic” dropdown list, that is SS29 - Modeling and Forecasting Financial and Commodity Markets by Neural Networks 
  2. fill out the input fields, upload the PDF file and finalize the submission by January 15, 2015.

Special Session Organizer

MASSIMO PANELLA, Ph.D.
Dept. of Information Engineering, Electronics and Telecommunications
University of Rome “La Sapienza”
Via Eudossiana 18, 00184 Rome, Italy
Tel.: +39-0644585496; Skype: m.panella
E-mail: massimo.panella@uniroma1.it
Web: http://massimopanella.site.uniroma1.it
LinkedIn: http://it.linkedin.com/in/massimopanella

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