We develop a new autoregressive conditional seasonal variance (ARCSV) process that captures both the changes in and the persistency of the intraday seasonal (U-shape) pattern of volatility. Unlike other procedures for seasonality, this approach allows for the intraday volatility pattern to...

The intraday seasonal variance pattern contains stochastic as well as deterministic components. Therefore, the estimation of information arrivals in the associated volatility process requires the proper filtering of both of these seasonal components. However, popular current models remove only...

We examine the long memory of real estate investment trust (REIT) volatility in the mature REIT markets of Australia, Japan, the UK and the US, and propose a modified fractionally integrated (FIGARCH) model for forecasting at daily and weekly frequencies. Long memory of volatility occurs when...

We use a new futures database to identify and determine the importance of spread volume for currency futures and hence the liquidity available for spreading. Spreads are a significant proportion of total volume for currency futures, with both calendar and cross-spreads being significant....