Statistical Analysis of Delay in Time Series
Access Status
Open access
Date
2023Supervisor
Honglei Xu
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Science and Engineering
School
School of Electrical Engineering, Computing and Mathematical Sciences
Collection
Abstract
This thesis focuses on delay in time series data. The first delay involves the m-delay autoregressive model. This approach considers only the first and the last previous observation of the traditional autoregressive model. Next, the delay is added to the stochastic differential equation for matching the volatility between real-world financial data and Monte Carlo simulations. Finally, a two-delay combination method is proposed to increase the prediction accuracy of the individual deep learning model.
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