Uncovering Long Memory in High Frequency UK Futures

TL;DR

This paper investigates long memory in high frequency UK futures volatility, revealing its strength varies across asset types and is most pronounced in absolute returns, with implications for volatility modeling.

Contribution

It introduces an analysis of long memory in high frequency UK futures, highlighting its variation across asset types and the effectiveness of the APARCH model.

Findings

Long memory is strongest in bond futures.

Absolute returns exhibit the strongest long memory.

APARCH model effectively captures volatility features.

Abstract

Accurate volatility modelling is paramount for optimal risk management practices. One stylized feature of financial volatility that impacts the modelling process is long memory explored in this paper for alternative risk measures, observed absolute and squared returns for high frequency intraday UK futures. Volatility series for three different asset types, using stock index, interest rate and bond futures are analysed. Long memory is strongest for the bond contract. Long memory is always strongest for the absolute returns series and at a power transformation of k < 1. The long memory findings generally incorporate intraday periodicity. The APARCH model incorporating seven related GARCH processes generally models the futures series adequately documenting ARCH, GARCH and leverage effects.