This paper explores a common machine learning tool, the kernel ridge regression, as applied to financial volatility forecasting. It is shown that kernel ridge provides reliable forecast improvements to both a linear specification, and a fitted nonlinear specification which represents well known...

This paper examines if overreaction of oil price forecasters is related to uncertainty. Furthermore, it takes into account impacts from oil price return and oil price volatility on forecast changes. The panel smooth transition regression model from González et al. (2005) is applied with...

In this paper, we challenge the traditional assumption of a linear relationship between exchange rate volatility and economic growth in South Africa. By using data collected from 1970 to 2016 applied to a smooth transition regression (STR) model, we are able to prove that the exchange...

A major theme of this book is the development of a consistent unified model framework for the evaluation of bond options. In general options on zero bonds (e.g. caps) and options on coupon bearing bonds (e.g. swaptions) are linked by no-arbitrage relations through the correlation structure of...