Price graphs: Utilizing the structural information of financial time series for stock prediction

Attention based simplified deep residual network for citywide crowd flows prediction

(2021) Genan Dai et al.   Frontiers of Computer Science

An interpretable Neural Fuzzy Hammerstein-Wiener network for stock price prediction

(2021) Chen Xie et al.   INFORMATION SCIENCES

Extreme tail network analysis of cryptocurrencies and trading strategies

(2021) Syed Jawad Hussain Shahzad et al.   Finance Research Letters

Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection

(2020) Qianchen Yu et al.   Frontiers of Computer Science

Adaptive stock trading strategies with deep reinforcement learning methods

(2020) Xing Wu et al.   INFORMATION SCIENCES

Where to go? Predicting next location in IoT environment

(2020) Hao Lin et al.   Frontiers of Computer Science

Predicting long-term returns of individual stocks with online reviews

(2020) Junran Wu et al.   NEUROCOMPUTING

Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting

(2020) Yaoli Wang et al.   INFORMATION SCIENCES

A novel graph convolutional feature based convolutional neural network for stock trend prediction

(2020) Wei Chen et al.   INFORMATION SCIENCES

Deep learning for time series classification: a review

(2019) Hassan Ismail Fawaz et al.   DATA MINING AND KNOWLEDGE DISCOVERY

Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach

(2019) Qifa Xu et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

An uncertain possibility-probability information fusion method under interval type-2 fuzzy environment and its application in stock selection

(2019) Xiuzhi Sang et al.   INFORMATION SCIENCES

Predicting catastrophes of non-autonomous networks with visibility graphs and horizontal visibility

(2018) Haicheng Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep learning-based feature engineering for stock price movement prediction

(2018) Wen Long et al.   KNOWLEDGE-BASED SYSTEMS

Complex network approaches to nonlinear time series analysis

(2018) Yong Zou et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Predicting protein structural classes based on complex networks and recurrence analysis

(2016) Mohammad H. Olyaee et al.   JOURNAL OF THEORETICAL BIOLOGY

Influence maximization in complex networks through optimal percolation

(2015) Flaviano Morone et al.   NATURE

Unraveling chaotic attractors by complex networks and measurements of stock market complexity

(2014) Hongduo Cao et al.   CHAOS

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

(2012) Na Wang et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Recurrence networks—a novel paradigm for nonlinear time series analysis

(2010) Reik V Donner et al.   NEW JOURNAL OF PHYSICS

Visibility graph approach to exchange rate series

(2009) Yue Yang et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

From time series to complex networks: The visibility graph

(2008) Lucas Lacasa et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA