Investor sentiment affects stock market liquidity by affecting noise trading and irrational market makers. Previous studies have focused on this effect with the time-series variation in sentiment and liquidity. This paper utilizes firm-specific news sentiment (FSNS) to examine its effect on...

In this study, we test a set of country macro sentiment indexes that measure the trailing sentiment on both scheduled and unscheduled economic and geopolitical news events. We develop a cross-over strategy in the FX market based on short to long-term news sentiment inflection points covering the...

I examine whether the market's reaction to firms' earnings news varies with analysis (i.e., editorial content) produced by financial journalists. A series of restructuring events at The Wall Street Journal (WSJ) suggests that WSJ articles improve price discovery and increase trading volume at...

This paper examines the effect of macroeconomic news announcements (MNA) on the stock market. Stocks exhibit a strong positive response to major MNA: 1 standard deviation of MNA surprise causes 11-25 bps higher returns. This response is highly time-varying and is weaker during periods of high...

The stock market is affected by sentiment. The question is, however, how to quantify this effect on asset prices. By utilizing the unique RavenPack Sentiment Index, a news-based proxy for market sentiment, this paper intends to address this issue empirically by exploring the pricing implications...

We find that the FOMC-announcement-day return premium earned by a firm is positively related to the increase in its ex ante, option-implied skewness prior to the announcement. This finding is consistent with: (1) the existence of an announcement-day Fed put that is partially anticipated by the...

Recent evidence suggests that there is strong relation between investor sentiment and cross-sectional anomalies. However, I present evidence of a weak relation between cross-sectional anomalies and investor sentiment. Using a larger collection of cross-sectional anomalies, I find that only a...

I develop a theoretical framework to identify investors' subjective beliefs that are jointly consistent with survey expectations and asset prices in markets where investors face trading frictions. To quantify the deviation of investors' beliefs from Rational Expectations (RE), I provide a metric...

Using a large dataset of news releases, we study instances of investors' mistaken reaction, or misreaction, to news. We define misreaction as stock prices moving in the direction opposite to the news when it is released. We find that news tone predicts returns in the cross-section only upon the...

We introduce a novel method for training computer algorithms to measure news sentiment. Our approach leverages human-coded sentiment scores from over 200,000 newspaper articles to teach the computer to select words, word combinations, and their linear weights. In an out-of-sample test, examining...