Schroeder, Anna Louise and Fryzlewicz, Piotr 
ORCID: 0000-0002-9676-902X
(2013)
Adaptive trend estimation in financial time series via multiscale change-point-induced basis recovery.
Statistics and Its Interface, 6 (4).
pp. 449-461.
ISSN 1938-7997
|
PDF
- Published Version
Download (1MB) | Preview |
Abstract
Low-frequency financial returns can be modelled as centered around piecewise-constant trend functions which change at certain points in time. We propose a new stochastic time series framework which captures this feature. The main ingredient of our model is a hierarchically-ordered oscillatory basis of simple piecewise-constant functions. It differs from the Fourier-like bases traditionally used in time series analysis in that it is determined by change-points, and hence needs to be estimated from the data before it can be used. The resulting model enables easy simulation and provides interpretable decomposition of nonstationarity into short- and long-term components. The model permits consistent estimation of the multiscale change-point-induced basis via binary segmentation, which results in a variablespan moving-average estimator of the current trend, and allows for short-term forecasting of the average return.
| Item Type: | Article |
|---|---|
| Official URL: | http://dx.doi.org/10.4310/SII.2013.v6.n4.a4 |
| Additional Information: | © 2013 International Press of Boston, Inc. |
| Divisions: | Statistics |
| Subjects: | H Social Sciences > HG Finance Q Science > QA Mathematics |
| JEL classification: | G - Financial Economics > G0 - General |
| Date Deposited: | 16 Dec 2013 14:00 |
| Last Modified: | 01 Apr 2024 08:21 |
| Funders: | Economic and Social Research Council |
| URI: | http://eprints.lse.ac.uk/id/eprint/54934 |
Actions (login required)
 |
View Item |
Download Statistics
Download Statistics