Svitlana Galeshchuk

Lauréate du Programme Atlas

séjour du 19 avril 2017 au 18 juillet 2017

Biographie

Dr. Svitlana Galeshchuk has earned her doctorate degree in Economics from Ternopil National Economic University, Ukraine. She has served a Fulbright Scholar visiting the College of Engineering and Computing at Nova Southeastern University, the USA. She has a faculty position at Ternopil National Economic University. She has been accepted as a Visiting Researcher at the National Bank of Poland in January 2017. She delivered a number of seminars and talks at leading universities in France, Spain, Sweden, and Poland. Her research interests are in the areas of market inefficiencies and economic forecasting. She is currently investigating the relative merits of econometric and artificial intelligence for technical and fundamental analysis in foreign exchange markets. Her focus is in the area of neural computing.

Projets de recherche 

Deep learning for exchange rate prediction in Eastern partnership area. 

Publications

  • Galeshchuk S., Mukherjee S. (2017) Deep Networks for Predicting Direction of Change in Foreign Exchange Rates. Early View in Intelligent Systems in Accounting, Finance and Management (John Wiley & Sons).
  • Galeshchuk S., Mukherjee S. (2017). Deep Learning for Predictions in Emerging Currency Markets. (ICAART, 2017), Springer.
  • Galeshchuk S. (2016) Neural networks performance in exchange rate prediction. Neurocomputing (Elsevier Science), Vol. 172(C), 446-452.
  • Galeshchuk S. (2016) Prediction of Trading Profits of Transnational Company Using Artificial Neural Networks: A Case Study of Nestle in Europe. Journal of Global Economics, Management and Business Research (International Knowledge Press), Vol. 7(2), 96-102.
  • Galeshchuk S. (2016) The Role of Technological Changes in Foreign-Exchange Market Inefficiency. In: Decision Economics, Eds. Bucciarelli, E., Silverti, M., Rodriguez Gonzalez, S., (Springer Verlag), AISC, Vol. 475, 27-34.
  • Galeshchuk S., Demazeau Y. (2016) Exchange-rates Market, Deep Learning, and Agent Modelling. Proceedings of the 2nd International Symposium on Ethics in Engineering, Science and Technology, ETHICS’2016, Vancouver. Abstract #43,
  • Galeshchuk S. (2014). Neural-Based Method of Measuring Exchange-Rate Impact on International Companies Revenue. Proceedings of the 11th International Conference on Distributed Computing and Artificial Intelligence, Eds. Omatu, E. et al (Springer Verlag), AISC, Vol. 290, 529-536.
  • Galeshchuk S. (2014) Behavioral economics as the new mainstream in economic thinking: reinterpretation of financial and currency risks. Investment Management and Financial Innovations (Consulting Publishing Company Business Perspectives), Vol. 11(1), 29-33