Understanding the behaviour of the equity yield and its relation to the bond yield is important for portfolio managers and those engaged in modelling the interaction between asset classes. During the mid-1900s, the equity yield-which was previously greater than the bond yield-declined, while the...

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...

This paper considers whether adding two established anomalies, momentum and low volatility, will improve our understanding of asset pricing beyond the FF5 model. We do this by considering whether these factors provide economic, as opposed to statistical, significance within the asset pricing...

This paper examines mean and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine cross — asset spillovers and how they vary...

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...

This paper investigates the role of oil as a determinant of the US stock-bond correlation. The analysis uses monthly data over the period from February 1990 to July 2021. We examine the impact of oil shocks, using the Ready (2018) method, alongside a range of macroeconomic variables on the...

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...