Read All About It: News as a Predictor of Stock Price Volatility

Not long after the Dow Jones slid to a six-year low, Assistant Professor Anna Scherbina presented her research about stock price volatility at Tulane University’s Freeman School of Business in March.

Scherbina’s study, “Unusual News Events and the Cross-Section of Stock Returns,” co-authored by Turan G. Bali of Baruch College’s Zicklin School of Business and Yi Tang of Fordham University’s School of Business, identified a pattern in which stocks that experience a sudden increase in volatility earn higher returns for a month, only to drop and underperform during subsequent months.

The study’s findings indicate that volatility jumps can be traced to unusual press release activity by the company that lead to an increase in investor disagreement regarding the value of the stock. This high volatility in conjunction with investor disagreement regarding the value of the stock creates a situation where short selling is too risky and costly. These results lead to a split between pessimistic buyers who won’t purchase the stock and at the same time cannot sell short due to short-selling constraints, and the more optimistic investors who continue bidding the stock upward.

Scherbina and her co-authors conclude that the jumps in stocks’ volatility that accompany these events make short-selling costly and prices rise to reflect the more optimistic views. In the subsequent months, as investors start to come to an agreement on the implications of the news, prices converge down, erasing roughly half of the initial price run-up. Scherbina’s work reveals market patterns that are useful for arbitrageurs and investors who are navigating and making data-based decisions in markets.

Most recently, Scherbina presented another paper, “Mispricing and Costly Arbitrage,” at the spring 2009 Journal of Investment Management’s Conference on Leverage and Liquidity in San Francisco.