Download this Paper Open PDF in Browser

Predicting Extreme Returns and Portfolio Management Implications

29 Pages Posted: 20 Jan 2011 Last revised: 15 May 2012

Kevin Krieger

University of West Florida

Greg Stevenson

University of Tulsa

Andy Fodor

Ohio University

Nathan Mauck

University of Missouri - Kansas City

Date Written: May 14, 2012

Abstract

We consider which readily observable characteristics of individual stocks (e.g., option implied volatility, accounting data, analyst data) may be used to forecast subsequent extreme price movements. We are the first to explicitly consider the predictive influence of option implied volatility in such a framework, which we unsurprisingly find to be an important indicator of future extreme price movements. However, after controlling for implied volatility levels, other factors, particularly firm age and size, still have additional predictive power of extreme future returns. Furthermore, excluding predicted extreme return stocks leads to a portfolio that has lower risk (standard deviation of returns) without sacrificing performance.

Keywords: predicting extreme returns

JEL Classification: G10, G14, G17

Suggested Citation

Krieger, Kevin and Stevenson, Greg and Fodor, Andy and Mauck, Nathan, Predicting Extreme Returns and Portfolio Management Implications (May 14, 2012). Available at SSRN: https://ssrn.com/abstract=1743226 or http://dx.doi.org/10.2139/ssrn.1743226

Kevin Krieger (Contact Author)

University of West Florida ( email )

11000 University Parkway
Pensacola, FL 32514-5750
United States

Greg Stevenson

University of Tulsa ( email )

600 South College
Tulsa, OK 74104
United States

Andy Fodor

Ohio University ( email )

234 Copeland
Athens, OH 45701
United States
740.593.0514 (Phone)

Nathan Mauck

University of Missouri - Kansas City ( email )

5100 Rockhill Road
Kansas City, MO 64110-2499
United States

Paper statistics

Downloads
458
Rank
51,297
Abstract Views
2,279