2000
DOI: 10.1002/1099-131x(200007)19:4<277::aid-for774>3.0.co;2-5
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Modelling the absolute returns of different stock indices: exploring the forecastability of an alternative measure of risk

Abstract: Conventional measures of the risk of a financial asset make use of the unobserved (conditional) variance or standard deviation of its return. In this paper, we treat the observed absolute return as a measure of risk and explore its forecastability. Two simple models are considered. One is a new AR‐like model which is applied to the absolute return. The other is an ARCH‐like model called Asymmetric Power ARCH. The forecastability is evaluated with the average log‐likelihood of absolute return, instead of that o… Show more

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Cited by 56 publications
(36 citation statements)
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“…As such they offer an alternative to methods such as those in Engle and Manganelli (2004) and Granger and Sin (2000), that are based on conditional autoregressive models.…”
Section: Discussionmentioning
confidence: 99%
“…As such they offer an alternative to methods such as those in Engle and Manganelli (2004) and Granger and Sin (2000), that are based on conditional autoregressive models.…”
Section: Discussionmentioning
confidence: 99%
“…Modeling and estimation is not very difficult and in practice the problem of estimated quantiles crossing appears not to be difficult (see Granger and Sin, 2000). The observed long-memory properties of volatility should be observed in the quantiles due to breaks.…”
Section: Distributionsmentioning
confidence: 99%
“…As a matter of fact, next to the traditional volatility modelling from daily returns measured as the log-difference of closing prices, we can consider absolute returns on which considerable modeling effort is present in the literature (Taylor, 1986;Ding et al, 1993;Granger and Sin, 2000) and, with the already mentioned provisos, realized volatility as the standard deviation of intra-daily returns observed at regular intervals. Furthermore, it has long been recognized that the spread between the highest recorded daily price and the lowest recorded daily price is a function of the volatility during the day and, as such, can lead to an improvement of the volatility estimates.…”
Section: Introductionmentioning
confidence: 99%