Time series forecasting with applications in macroeconomics and energy

Thesis

The aim of this study is to develop novel forecasting methodologies. The applications of our proposed models lie in two different areas: macroeconomics and energy. Though we consider two very different applications, the common underlying theme of this thesis is to develop novel methodologies that are not only accurate, but are also parsimonious.

For macroeconomic time series, we focus on generating forecasts for the US Gross National Product (GNP). The contribution of our study on m...

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Authors: Arora, S

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Probabilistic modelling; Nonlinear and nonparametric methodologies; Short-term load forecasting; Conditional kernel density estimation; Rule-based forecasting
• Subjects: Energy modelling; Forecasting; Nonlinear and nonparametric methodologies; Time series analysis