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

1 Introduction

Estimates of the future volatility of asset returns are of great interest to many
financial market participants. Generally, there are two approaches which can
be employed to obtain such estimates. First, predictions of future volatility can
be generated from econometric models of volatility given historical information
(model based forecasts, MBF). For surveys of common modeling techniques
see Campbell, Lo and MacKinlay (1997) and Gourieroux and Jasiak (2001).
Second, estimates of future volatility can be derived from option prices using
implied volatility (IV). IV should represent a market’s best prediction of an
assets’ future volatility (see, amongst others, Jorion, 1995, Poon and Granger,
2003, 2005).

Given the importance of volatility forecasting, a large number of studies have
examined the forecast performance of various approaches. Poon and Granger
(2003, 2005) survey the results of 93 articles that consider tests of volatility
forecast performance. The general result of this survey was that IV estimates
often provide more accurate volatility forecasts than competing MBF. This
result is rationalised on the basis that IV should be based on a larger and
timelier information set. In a related yet different context Becker, Clements and
White (2006) examine whether a particular implied volatility index derived from
SVP 500 option prices, the VIX, contains any information relevant to future
volatility beyond that reflected in model based forecasts. As they conclude
that the VIX does not contain any such information this result, at first sight,
appears to contradict the previous findings summarised in Poon and Granger

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