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Are combination forecasts of S&P 500 volatility statistically superior?

By Ralf Becker and Adam Clements

Abstract

Forecasting volatility has received a great deal of research attention, with the relative performances of econometric model based and option implied volatility forecasts often being considered. While many studies find that implied volatility is the pre-ferred approach, a number of issues remain unresolved, including the relative merit of combining forecasts and whether the relative performances of various forecasts are statistically different. By utilising recent econometric advances, this paper considers whether combination forecasts of S&P 500 volatility are statistically superior to a wide range of model based forecasts and implied volatility. It is found that a combination of model based forecasts is the dominant approach, indicating that the implied volatility cannot simply be viewed as a combination of various model based forecasts. Therefore, while often viewed as a superior volatility forecast, the implied volatility is in fact an inferior forecast of S&P 500 volatility relative to model-based forecasts

Topics: 150202 Financial Econometrics, Implied volatility, volatility, forecasts, volatility models, combination forecasts, model confidence sets
Publisher: Elsevier BV, North-Holland
Year: 2008
DOI identifier: 10.1016/j.ijforecast.2007.09.001
OAI identifier: oai:eprints.qut.edu.au:30809
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