2 research outputs found
FINANCE RESEARCH SEMINAR SUPPORTED BY UNIGESTION "WHICH NEWS MOVES STOCK PRICES? A TEXTUAL ANALYSIS" WHICH NEWS MOVES STOCK PRICES? A TEXTUAL ANALYSIS 1
No full textAbstract A basic tenet of financial economics is that asset prices change in response to unexpected fundamental information. Since A basic tenet of financial economics is that asset prices change in response to unexpected fundamental information. Since Roll's (1988) provocative presidential address that showed little relation between stock prices and news, however, the finance literature has had limited success reversing this finding. This paper revisits this topic in a novel way. Using advancements in the area of textual analysis, we are better able to identify relevant news, both by type and by tone. Once news is correctly identified in this manner, there is considerably more evidence of a strong relationship between stock price changes and information. For example, market model R 2 s are no longer the same on news versus no news days (i.e., Roll's (1988) infamous result), but now are 16% versus 33%; variance ratios of returns on identified news versus no news days are 120% higher versus only 20% for unidentified news versus no news; and, conditional on extreme moves, stock price reversals occur on no news days, while identified news days show an opposite effect, namely a strong degree of continuation. A number of these results are strengthened further when the tone of the news is taken into account by measuring the positive/negative sentiment of the news story. 1 Corresponding author: Shimon Kogan, GSB 5.159, McCombs School of Business, University of Texas at Austin, 1 University Station, B6600, Austin, TX 78712, Tel: +1 (512) 232-6839, email [email protected]. We would like to thank John Griffin and seminar participants at the University of Texas, Austin, and Stern NYU for their comments and suggestions
The Myth of Long-Horizon Predictability
No full textThe prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons. Common sampling error across equations leads to ordinary least squares coefficient estimates and R-super-2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. We perform joint tests across horizons for a variety of explanatory variables and provide an alternative view of the existing evidence. The Author 2006. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected], Oxford University Press.
