• DocumentCode
    262143
  • Title

    Intelligent Stock Market Analysis System - A Fundamental and Macro-economical Analysis Approach

  • Author

    Tirea, Monica ; Negru, Viorel

  • Author_Institution
    Comput. Sci. Dept., West Univ. of Timisoara, Timisoara, Romania
  • fYear
    2014
  • fDate
    22-25 Sept. 2014
  • Firstpage
    519
  • Lastpage
    526
  • Abstract
    Stock Market Forecasting implies the use of a series of techniques that helps in determining the stock price evolution. The paper describes a multi-agent system that uses numerical, financial and economical data in order to evaluate the company´s position on the market, profitability, performance, future expectations in the company´s evolution. Determining the effect of political, governmental and social decisions along with detecting the way in which the price is constructed based on technical and fundamental analysis methods and the bid/ask situation helps in determining a more precise buy/sell signals, reducing the false signals and determining some risk/gain positions on different periods of time. In order to validate the results a prototype was developed.
  • Keywords
    financial data processing; forecasting theory; macroeconomics; multi-agent systems; profitability; stock markets; buy-sell signals; company evolution; economical data; financial data; governmental decisions; intelligent stock market analysis system; multiagent system; numerical data; political decisions; profitability; risk-gain positions; social decisions; stock market forecasting; stock price evolution; Companies; Data mining; Economic indicators; Investment; Libraries; Portfolios; Stock markets; Artificial Intelligence; Fundamental Analysis; Macro-economical Analysis; Multi-Agent System; Stock Market Forecasting; Technical Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2014 16th International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-1-4799-8447-3
  • Type

    conf

  • DOI
    10.1109/SYNASC.2014.75
  • Filename
    7034725