Abstract

http://ssrn.com/abstract=1743226
 
 

References (19)



 
 

Citations (1)



 


 



Predicting Extreme Returns and Portfolio Management Implications


Kevin Krieger


University of West Florida

Greg Stevenson


University of Tulsa

Andy Fodor


Ohio University

Nathan Mauck


University of Missouri - Kansas City

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.

Number of Pages in PDF File: 29

Keywords: predicting extreme returns

JEL Classification: G10, G14, G17

working papers series


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Date posted: January 20, 2011 ; Last revised: May 15, 2012

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: http://ssrn.com/abstract=1743226 or http://dx.doi.org/10.2139/ssrn.1743226

Contact Information

Kevin Krieger (Contact Author)
University of West Florida ( email )
Building 76, Room 226
Department of Accounting and Finance, UWF
Pensacola, FL 32514
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
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