Detecting Predictable Segments of Chaotic Financial Time Series via Neural Network

Detecting Predictable Segments of Chaotic Financial Time Series via Neural Network

In this study, a new idea is proposed to analyze the financial market and detect price fluctuations, by integrating the technology of PSR (phase space reconstruction) and SOM (self organizing maps) neural network algorithms. The prediction of price and index in the financial market has always been a...

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Bibliographic Details
Main Authors: Tianle Zhou, Chaoyi Chu, Chaobin Xu, Weihao Liu, Hao Yu
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Electronics
Subjects:
financial time series
chaotic dynamics
SOM neural network
clustering
LSTM
Online Access:https://www.mdpi.com/2079-9292/9/5/823

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