Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data

R. Ito
We introduce the spline-DCS model with a dynamic cubic spline as a way of capturing periodic behavior in financial data that evolves over time. Our empirical application provides evidence for changing diurnal patterns in the high-frequency financial data we study. We illustrate that this generalization can lead to an improvement in the quality of the fit of the model to the empirical distribution of data, especially in the tail region, for an extended out-of-sample period....
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