Introduction -- ARMA models -- Forecasting stationary processes -- Estimation of Mean and Autocovariance Function -- Estimation of ARMA Models -- Spectral Analysis and Linear Filters -- Integrated Processes -- Models of Volatility -- Multivariate Time series -- Estimation of Covariance Function...

We utilise functional time series (FTS) techniques to characterise and forecast implied volatility in foreign exchange markets. In particular, we examine the daily implied volatility curves of FX options, namely; EUR-USD, EUR-GBP, and EUR-JPY. Based on existing techniques in the literature, the...

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for ‘nowcasting’. The...

This study investigates the practical importance of several VaR modeling and forecasting issues in the context of intraday stock returns. Value-at-Risk (VaR) predictions obtained from daily GARCH models extended with additional information such as the realized volatility and squared overnight...