Improving probabilistic forecasts by using intra-day data: an application to financial and temperature data

Thesis

The thesis consists of three studies. The first two contribute to financial market risk modelling and the third contributes to the modelling of temperature extremes.

Value at risk (VaR) is a popular measure of market risk. The first study proposes new approximate long-memory VaR models that incorporate intra-day price ranges. These models use lagged intra-day range with the feature of considering different range components calculated over different time horizons. We also investigate...

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Authors: Meng, X

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English