A WAVELET METHOD COUPLED WITH QUASI-SELF-SIMILAR STOCHASTIC PROCESSES FOR TIME SERIES APPROXIMATION

被引：17

作者：

Hamrita, Mohamed Essaied ^{[2
]}

Ben Abdallah, Nidhal ^{[3
]}

Ben Mabrouk, Anouar ^{[1
]}

机构：

[1] Fac Sci, Dept Math, Computat Math Lab, Monastir 5000, Tunisia

[2] Higher Inst Appl Sci & Technol, Hiboun 5111, Mahdia, Tunisia

[3] Fac Econ Sci & Management, Dept Quantitat Methods, Hiboun 5111, Mahdia, Tunisia

来源：

INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING | 2011年 / 9卷 / 05期

关键词：

Financial signals; approximation; wavelet decomposition; wavelet estimators; regression; self-similarity; exchange rate; SP500; MULTIFRACTAL FORMALISM; SYSTEMATIC-RISK; DECOMPOSITION; PREDICTION; VOLATILITY; TRANSFORM;

D O I：

10.1142/S0219691311004353

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Scaling laws and generally self-similar structures are now well known facts in financial time series. Furthermore, these signals are characterized by the presence of stochastic behavior allowing their analysis with pure functional methods being incomplete. In the present paper, some existing models are reviewed and modified, based on wavelet theory and self-similarity, to recover multi-scaling cases for approximating financial signals. The resulting models are then tested on some empirical examples and analyzed for error estimates.

引用

页码：685 / 711

页数：27

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