Random Forest Based Feature Selection of Macroeconomic Variables for Stock Market Prediction

Macroeconomic Variables and Stock Market: US Review

This focus of this paper are the effect, implication, impact and realtionship between selected macroeconomic variables and wider US indices S&P 500 and industrial Dow Jones Industrial Average (DJIA). I Consider inflation, interest rates, money supply, producer price index, industrial production index, oil price and unemployment and their impact on selected stock indices in the USA between 1999 ...

Designing a Bankruptcy Prediction Model Based on Account, Market and Macroeconomic Variables (Case Study: Cyprus Stock Exchange)

The development of the Cyprus Stock Exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. In such circumstances, the first step towards a sustainable development of the Exchange is to support the investors. Risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. In th...

Feature Selection for Stock Market Analysis

The analysis of the financial market always draws a lot of attention from investors and researchers. The trend of stock market is very complex and is influenced by various factors. Therefore to find out the most significant factors to the stock market is very important. Feature Selection is such an algorithm that can remove the redundant and irrelevant factors, and figure out the most significa...

The Relationship Between Stock Market And Macroeconomic Variables: A Case Study For Iran

The Relationship between Stock Market and Macroeconomic Variables: a Case Study for Iran

This paper examines the causal relationship between stock prices and macroeconomic aggregates in Iran, by applying the techniques of the long–run Granger non–causality test proposed by Toda and Yamamoto (1995). We test the causal relationships between the TEPIX Index and the three macroeconomic variables: money supply, value of trade balance, and industrial production using quarterly data for t...