Absolute return volatility

Volatility modelling is a key issue for the finance industry from an academic and practitioner perspective. This is understandable given the importance that volatility plays in risk management and the development of accurate risk measures in a univariate or multivariate framework. To illustrate, successful market risk management requires the use of accurate risk measures such as minimum capital requirements. These risk measures are underpinned by the input of volatility estimates. An important question thus arises: how to people obtain accurate volatility measures that can be used in market risk management? This article addresses this by exploring the asymptotic and finite sample properties of absolute return volatility. These measures are model-free and avoid model risk with other frameworks such as autoregressive conditional heteroscedasticity processes. Absolute return volatility is obtained by aggregating high-frequency absolute returns into relatively low-frequency, for example, daily volatility estimates. The use of these measures is illustrated by obtaining the commonly used market risk measure, minimum capital requirements.