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Practitioners’ Corner

Practitioners’ Corner Journal of Financial Econometrics, 2006, Vol. 4, No. 3, 531–536 During the 1980s, the early stages of modeling financial time series focused on the striking stylized fact that while returns were themselves not serially correlated, squared returns were. This history has been nicely documented in the influential book by Taylor (1986) and, indeed, the opening chapters of contemporary finan- cial econometrics open with Engle (1982) and Bollerslev (1986) who provided a specific ARMA structure of squared returns via the celebrated [G]ARCH models. This general orientation in effect acknowledged that there was some room for predicting risk, as measured by squared values or absolute values of returns, while at the same time maintaining the hypothesis that returns themselves were hardly predictable in keeping with some version of market efficiency. However, this paradigmatic view has been challenged over the subsequent 20 years in at least three regards. First, with Nelson (1991), it has been widely acknowledged that although GARCH modeling is about forecasting squared returns, there is no reason to consider that the relevant conditioning information used to predict future squared returns is encapsulated in past squared returns. The observed past values of the signs of returns may be relevant as http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Financial Econometrics Oxford University Press

Practitioners’ Corner

Canopius, Adam
Journal of Financial Econometrics , Volume 4 (3) – Jun 26, 2006
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Publisher
Oxford University Press
Copyright
© Published by Oxford University Press.
ISSN
1479-8409
eISSN
1479-8417
DOI
10.1093/jjfinec/nbj016
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Abstract

Journal of Financial Econometrics, 2006, Vol. 4, No. 3, 531–536 During the 1980s, the early stages of modeling financial time series focused on the striking stylized fact that while returns were themselves not serially correlated, squared returns were. This history has been nicely documented in the influential book by Taylor (1986) and, indeed, the opening chapters of contemporary finan- cial econometrics open with Engle (1982) and Bollerslev (1986) who provided a specific ARMA structure of squared returns via the celebrated [G]ARCH models. This general orientation in effect acknowledged that there was some room for predicting risk, as measured by squared values or absolute values of returns, while at the same time maintaining the hypothesis that returns themselves were hardly predictable in keeping with some version of market efficiency. However, this paradigmatic view has been challenged over the subsequent 20 years in at least three regards. First, with Nelson (1991), it has been widely acknowledged that although GARCH modeling is about forecasting squared returns, there is no reason to consider that the relevant conditioning information used to predict future squared returns is encapsulated in past squared returns. The observed past values of the signs of returns may be relevant as

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Journal of Financial Econometrics – Oxford University Press

Published: Jun 26, 2006

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