Using fundamental data to help predict market movement
Abstract
“Beating the market” has been of interest to researchers and investors for a long time. As early as 1900, Louis Bachelier (Bachelier L. 1900) notes that the dynamics of the stock exchange will never be an exact science, however it is possible to mathematically study the state of the market at a given moment and try to calculate probabilities of market movements. He concludes that past, present and future events often do not show relationship to price movements. Since then, different research has found different evidence about the predictability of market movements. This paper aims to explore financial statement items and which of them have the strongest predictive power in relation to stock price movements. The popular information gain metric is empirically calculated for items in the financial statements of a group of US companies and the results are presented on a sector basis.
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