The long-memory and nonlinearity coexist in realised volatility. This paper incorporates the linear AR and HAR models with regime-switching models, including the smooth transition and Markov-switching approaches, to assess the forecasting performance of realized volatility. In-sample results...

This study seeks to examine the behaviour of subsequent trading activity in international stock markets. We investigate whether stock returns can explain subsequent trading using wavelet time-scaled returns and volume. A wavelet decomposition of trading volume over time-scales of up to 32 days...

We use wavelet analysis to examine the impact of macro-news announcements on the stock-bond correlation. Significant announcement effects appear after controlling for the recent financial crisis, with a link between the speed of reaction and the timing of announcements, with early released news...

This paper examines the ability of different GARCH models to forecast stock return volatility under a range of forecast metrics, including both statistical and economic evaluation. In particular, we are interested in whether wavelet de-noising of the data prior to estimation affects the ability...

We investigate the joint ability of fundamental-based and market-based news to explain the anomalous underperformance of the stocks with high idiosyncratic volatility (high IVOL). An out-of-sample prediction of future profitability is adopted as a proxy for the fundamental–based news while...

This paper analyses the dynamic transmission mechanism of volatility spillovers between key global financial indicators and G20 stock markets. To examine the volatility spillover relations a bivariate GARCH-BEKK model, which captures volatility spillovers, is combined with complex network...

Forecasts of stock market volatility is an important input for market participants in measuring and managing investment risks. Thus, understanding the most appropriate methods to generate accurate is key. This paper examines the ability of Machine Learning methods, and specifically Artificial...

Research across international markets identifies lottery-like stocks that contradict the standard positive risk-return trade-off paradigm. This paper, consistent with those results, reports under-performance for lottery-like stocks in the UK market. Moreover, while the under-performance appears...

We investigate whether range-based estimators contain information in forecasting realized volatility within a HAR-RV-X framework and applied to G7 stock markets. Using a rolling window approach and QLIKE, HMSE and MCS forecast criteria, overall findings suggest that while no single model...

The HAR model dominates current volatility forecasting. This model implies a restricted lag approach, with three parameters accounting for an AR(22) structure. This paper uses the Lasso method, which selects a parsimonious lag structure, while allowing both a flexible lag structure and lags...