## Abstract Financial market time series exhibit high degrees of non‐linear variability, and frequently have fractal properties. When the fractal dimension of a time series is non‐integer, this is associated with two features: (1) inhomogeneity—extreme fluctuations at irregular intervals, and (2) s
Order series method for forecasting non-Gaussian time series
✍ Scribed by Ming-De Chuang; Gwo-Hsing Yu
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 287 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1024
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
A new forecasting non‐Gaussian time series method based on order series transformation properties has been proposed. The proposed method improves Yu's method without using Hermite polynomial expansion to process nonlinear instantaneous transformations and provides acceptable forecasting accuracy. Copyright © 2007 John Wiley & Sons, Ltd.
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