Academics Research on After the Bell

• Good news: Using news feeds with genetic programming to predict stock prices, Larkin, F., & Ryan, C. (2008, March). Good news: Using news feeds with genetic programming to predict stock prices. In European Conference on Genetic Programming (pp. 49-60). Springer, Berlin, Heidelberg. This paper introduces a new data set for use in the financial prediction domain, that of quantified News Sentiment. This data is automatically generated in real time from the Dow Jones network with news stories being classified as either Positive, Negative or Neutral in relation to a particular market or sector of interest. We show that with careful consideration to fitness function and data representation, GP can be used effectively to find non-linear solutions for predicting large intraday price jumps on the S&P 500 up to an hour before they occur. The results show that GP was successfully able to predict stock price movement using these news alone, that is, without access to even current market price. 
• Impact of the federal open market committee's meetings and scheduled macroeconomic news on stock market uncertainty, Nikkinen, J., & Sahlstrm, P. (2004). Impact of the federal open market committee's meetings and scheduled macroeconomic news on stock market uncertainty. International Review of Financial Analysis, 13(1), 1-12. This study investigates the impact of the scheduled Federal Open Market Committee (FOMC) meetings and the scheduled macroeconomic news releases on stock market uncertainty. For that purpose, the behavior of the implied volatility of the S&P100 index (VIX) is investigated around the FOMC meeting days and around the employment, producer price index (PPI), and consumer price index (CPI) reports. The results support the hypothesis that implied volatility increases prior to the scheduled news and drops after the announcement. The results reveal that investors regard the FOMC meetings as highly significant for valuing stocks as hypothesized. Of the macroeconomic news releases, the employment report has the largest impact on uncertainty, whereas investors regard the information content of the PPI and CPI together as significant. 
• Relative importance of scheduled macroeconomic news for stock market investors, Graham, M., Nikkinen, J., & Sahlstrm, P. (2003). Relative importance of scheduled macroeconomic news for stock market investors. Journal of Economics and Finance, 27(2), 153-165. This paper investigates the relative importance of scheduled U.S. macroeconomic news releases for stock valuation. The study focuses on 11 macroeconomic announce-ments selected on the basis of the previous literature and the Bureau of Labor Statistics classifications of major economic indicators. The paper shows that five out of the 11 announce-ments have significant influence on stock valuation. These are the Employment Report, NAPM (manufacturing), Producer Price Index, Import and Export Price Indices, and Employment Cost Index. Of these six announcements, the Employ- ment Report and NAPM (manufacturing) exert the greatest influence. The time of the announcement, measured by days from the beginning of the month to the release day, has a moderating impact on the relationship between macro-economic announcements and its importance. (JEL E52, GI4) 
• Do price discreteness and transactions costs affect stock returns? Comparing exdividend pricing before and after decimalization, Graham, J. R., Michaely, R., & Roberts, M. R. (2003). Do price discreteness and transactions costs affect stock returns? Comparing exdividend pricing before and after decimalization. The Journal of Finance, 58(6), 2611-2636. By the end of January 2001, all NYSE stocks had converted their price quotations from 1/8s and 1/16s to decimals. This study examines the effect of this change in price quotations on exdividend day activity. We find that abnormal exdividend day returns increase in the 1/16 and decimal pricing eras, relative to the 1/8 era, which is inconsistent with microstructure explanations of exday price movements. We also find that abnormal returns increase in conjunction with a May 1997 reduction in the capital gains tax rate, as they should if relative taxation of dividends and capital gains affects exday pricing. 
• Daily stock market forecast from textual web data, Wuthrich, B., Cho, V., Leung, S., Permunetilleke, D., Sankaran, K., & Zhang, J. (1998, October). Daily stock market forecast from textual web data. In SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 98CH36218) (Vol. 3, pp. 2720-2725). IEEE. Our aim is to predict stock markets using information contained in articles published on the Web, mostly textual articles appearing in the leading and influential financial newspapers. From those articles the daily closing values of major stock market indices in Asia, Europe and America are predicted. Textual statements contain not only the effect but also why it happened. A prediction system has been built that uses data mining techniques and sophisticated keyword tuple counting and transformation to produce periodically forecasts in stock markets. Exploiting textual information in addition to numeric time series data increases the quality of the input, hence improved predictions are expected. The forecasts are available in real-time via the Internet Web site. The system's accuracy for this difficult but also extremely challenging application is highly promising.