A random coefficient autoregressive Markov regime switching model for dynamic futures hedging

✍ Scribed by Hsiang-Tai Lee; Jonathan K. Yoder; Ron C. Mittelhammer; Jill J. McCluskey

• Publisher: John Wiley and Sons
• Year: 2005
• Tongue: English
• Weight: 392 KB
• Volume: 26
• Category: Article
• ISSN: 0270-7314
• DOI: 10.1002/fut.20193

✦ Synopsis

Abstract

The random coefficient autoregressive Markov regime switching model (RCARRS) for estimating optimal hedge ratios, which generalizes the random coefficient autoregressive (RCAR) and Markov regime switching (MRS) models, is introduced. RCARRS, RCAR, MRS, BEKK‐GARCH, CC‐GARCH, and OLS are compared with the use of aluminum and lead futures data. RCARRS outperforms all models out‐of‐sample for lead and is second only to BEKK‐GARCH for aluminum in terms of variancereduction point estimates. White's data‐snooping reality check null hypothesis of no superiority is rejected for BEKK‐GARCH and RCARRS for aluminum, but not for lead. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:103–129, 2006