Date of Award:
Doctor of Philosophy (PhD)
Mathematics and Statistics
Piotr S. Kokoszka
Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for the prediction of intraday returns for various financial assets, including stock and commodity futures.
Zhang, Xi, "Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data" (2013). All Graduate Theses and Dissertations. 1973.
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