Dynamical Analysis of the Dow Jones Index Using Dimensionality Reduction and Visualization

• Type: Article in International Scientific Journal
• Date: 2021

Authors

António Mendes Lopes (Author) FEUP; José A. Tenreiro Machado (Author) Other

Journal

Title: Entropy

Vol. 23

Pages: 1-600

ISSN: 1099-4300

Publisher: MDPI

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00T-Z9J

DOI: 10.3390/e23050600

Abstract (EN): Time-series generated by complex systems (CS) are often characterized by phenomena such as chaoticity, fractality and memory effects, which pose difficulties in their analysis. The paper explores the dynamics of multidimensional data generated by a CS. The Dow Jones Industrial Average (DJIA) index is selected as a test-bed. The DJIA time-series is normalized and segmented into several time window vectors. These vectors are treated as objects that characterize the DJIA dynamical behavior. The objects are then compared by means of different distances to generate proper inputs to dimensionality reduction and information visualization algorithms. These computational techniques produce meaningful representations of the original dataset according to the (dis)similarities between the objects. The time is displayed as a parametric variable and the non-locality can be visualized by the corresponding evolution of points and the formation of clusters. The generated portraits reveal a complex nature, which is further analyzed in terms of the emerging patterns. The results show that the adoption of dimensionality reduction and visualization tools for processing complex data is a key modeling option with the current computational resources.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20