Fundamental Analysis and the Prediction of Earnings with Emphasis on Role of Contextual Factors

This paper takes fundamental analysis research beyond the spatial and temporal bounds of previous studies. It was investigated that how detailed financial statement data enter the decisions of market makers by examining how current changes in the fundamental signals chosen can provide information on subsequent earnings changes. Using Tehran Stock Exchange’s firms data from 2003 to 2012, the role of fundamental signals for prediction of future earnings changes was tested. In addition, the influence of contextual factors including prior earnings news and macroeconomic variables (GDP growth and inflation) on the relationship between fundamental signals and future earnings changes was investigated. Results indicate that the fundamental signals are significant predictors of short-term but not long-term future earnings changes. Moreover, prior earnings news doesn’t affect earnings predictability, but this predictability is significantly higher in lower GDP and higher inflation periods. In addition to corroborating prior research with fundamental analysis, this research adds to what has previously been conducted and extends investigations with examination of the predictive link between the fundamental signals and future earnings change by introducing prior earnings news and macroeconomic conditions as contextual factors in order to look for a possible effect which has not been investigated in prior research.