Applications of Hilbert–Huang transform to non‐stationary financial time series analysis

By Norden E. Huang, Man-li C. Wu, Wendong Qu, Steven R. Long, S. P. Shen. 2003

526 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Computer Vision and Pattern Recognition, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/005d8448c5c0455b68b375013228e0815b42d570

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Ben M. Hambly
2. Huining Yang
3. Renyuan Xu

In Economics and Econometrics

1. Ben M. Hambly
2. Huining Yang
3. Renyuan Xu

Citations in the corpus

• Recent advances in reinforcement learning in finance (2021, background): “Financial time series are known to be nonstationary (Huang et al., 2003), and hence historical data that are further away in timemay not be helpful in training efficient learning algorithms for the current market environment.”
• Texture analysis based on local analysis of the Bidimensional Empirical Mode Decomposition (2005, methodology): “Such as the Hilbert-Huang Transform in the case of onedimensional signal analysis [44], we present an image analysis method by studying local properties of 2D-IMF obtained by BEMD.”