Financial Analysis and Prediction Research Group

Group head: Prof. Feras Mashgba


Description of activities

Macroeconomic prediction and analysis, especially for the purpose of prediction and diagnosis.

  • From among these topics, this activity centres on:
  • Macroeconomic modelling, forecasting and diagnosis.
  • Prediction of daily data and economic activity schedules: transport and communications, sales, stock, monetary aggregates, movement of cash at cash points, contamination, Forex trading, etc.
  • Modelling of financial data volatility.
  • The development of new econometric methods.


Lines of research

  • Comprehensive Modeling.
  • Data mining (DM).
  • Density functions of macroeconomic predictions.
  • Information Retrieval (IR).
  • Disintegration of macroeconomic variables.
  • Artificial intelligence (AI).
  • Methodology for the construction of vectorial macroeconomic models for the components of the GDP in its breakdown of production and spending and combination of results from both breakdowns: application to Spain.
  • Methodology for the construction of econometric models.
  • Methodology for the prediction of inflation.
  • Non-linear modeling.
  • Use of bootstrap techniques.
  • Modeling of Uncertainty.

Major Research Outcomes: 

1- New Era Forex Prediction Algorithm (NEFP):

The NEFP Algorithm is an algorithm created based on novel Data Mining technique that merges concepts and ideas from information retrieval and artificial intelligence fields. The NEFP Algorithm was tested on 17000 forex financial transactions (using Dow Jones) and it proves its ability to predict the market direction, Take Profit (TP), and Stop Loss (SL).


Registration to use the NEFP is available only for limited period until 15\9\2018.