Abstract
Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their “thematic” features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be “abnormally large,” can be partially explained by the flow of news. In this sense, our results prove that there is no “excess trading,” when restricting to times when news is genuinely novel and provides relevant financial information.
Highlights
Neoclassical financial economics based on the ‘‘efficient market hypothesis’’ (EMH) considers price movements as almost perfect instantaneous reactions to information flows
We mine raw texts of more than 24 million news records provided by Thompson Reuters and examine their impact on trading activity in stocks of the 206 firms listed in the S&P 500 US stock index for each of which there were more than 5,000 news records over the period from January 2003 to June 2011
We performed an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity of the stock of 206 major firms included in the S&P 500 index
Summary
Neoclassical financial economics based on the ‘‘efficient market hypothesis’’ (EMH) considers price movements as almost perfect instantaneous reactions to information flows. According to the EMH, price changes reflect exogenous news Such news - of all possible types (geopolitical, environmental, social, financial, economic, etc.) - lead investors to continuously reassess their expectations of the cash flows that firms’ investment projects could generate in the future. These reassessments are translated into readjusted demand/supply functions, which push prices up or down, depending on the net imbalance between demand and supply, towards a fundamental value. As a consequence, observed prices are considered the best embodiments of the present value of future cash flows In this view, market movements are purely exogenous without any internal feedback loops. The most extreme losses occurring during crashes are considered to be solely triggered exogenously
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