4.7 Article

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

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Business, Finance

Extreme tail network analysis of cryptocurrencies and trading strategies

Syed Jawad Hussain Shahzad et al.

Summary: The study found that the interdependence of returns between cryptocurrencies is higher in the tails than at the medians, especially on the right tail. Smaller cryptocurrencies play a major role in risk transmission, rather than Bitcoin. The volatilities of market, size, and momentum drive return connectedness and clustering coefficients among cryptocurrencies.

FINANCE RESEARCH LETTERS (2022)

Article Computer Science, Information Systems

Where to go? Predicting next location in IoT environment

Hao Lin et al.

Summary: The paper proposes a method for next location prediction in the IoT environment via a session-based manner, by jointly modeling patterns hidden inside trajectory and signal sequences. The TSIS model is introduced and utilizes GRU and gated graph neural networks for modeling, and a session embedding is built to predict the next location. Extensive experiments show the effectiveness and robustness of TSIS compared to other competitive baselines in next location prediction on real-world Wi-Fi based mobility datasets.

FRONTIERS OF COMPUTER SCIENCE (2021)

Article Computer Science, Information Systems

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

Chen Xie et al.

Summary: This paper proposes an interpretable regression model for stock price prediction, which integrates a neuro-fuzzy system with the Hammerstein Wiener model. Experimental results show that the proposed Neural Fuzzy Hammerstein-Wiener (NFHW) outperforms other neuro-fuzzy systems and the conventional Hammerstein-Wiener model in stock price prediction.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

Attention based simplified deep residual network for citywide crowd flows prediction

Genan Dai et al.

Summary: This paper proposes a simplified deep residual network for crowd flows prediction, which achieves competitive prediction performance with less training time compared to existing methods. The addition of a spatio-temporal attention mechanism further improves network efficiency. Experimental results based on real datasets confirm the effectiveness of the proposed methods.

FRONTIERS OF COMPUTER SCIENCE (2021)

Article Computer Science, Information Systems

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

Yaoli Wang et al.

Summary: The study introduces an improved Elman neural network called Elman-DIOCs with direct input-to-output connections, demonstrating its effectiveness in stock forecasting. Experimental results show that DIOCs lead to significantly better prediction accuracy while requiring fewer hidden neurons. The study argues that DIOCs can improve accuracy and reduce complexity in neural networks for regression or classification tasks with linear components.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

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

Wei Chen et al.

Summary: The paper introduces a novel method for stock trend prediction using GC-CNN model, which considers both stock market information and individual stock information. Experimental analysis demonstrates that the proposed method outperforms several stock trend prediction methods and stock trading strategies.

INFORMATION SCIENCES (2021)

Article Business, Finance

Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers

Syed Jawad Hussain Shahzad et al.

Summary: This study investigates extreme return spillovers among US stock market sectors, particularly in the context of the COVID-19 outbreak. The results reveal significant differences in network structure and spillovers under different market conditions, with the pandemic period showing a unique restructuring of the network.

FINANCIAL INNOVATION (2021)

Article Computer Science, Information Systems

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

Qianchen Yu et al.

FRONTIERS OF COMPUTER SCIENCE (2020)

Article Computer Science, Information Systems

Adaptive stock trading strategies with deep reinforcement learning methods

Xing Wu et al.

INFORMATION SCIENCES (2020)

Article Computer Science, Artificial Intelligence

Predicting long-term returns of individual stocks with online reviews

Junran Wu et al.

NEUROCOMPUTING (2020)

Article Computer Science, Information Systems

Network Representation Learning: A Survey

Daokun Zhang et al.

IEEE TRANSACTIONS ON BIG DATA (2020)

Review Computer Science, Artificial Intelligence

Deep learning for time series classification: a review

Hassan Ismail Fawaz et al.

DATA MINING AND KNOWLEDGE DISCOVERY (2019)

Article Physics, Multidisciplinary

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

Qifa Xu et al.

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Deep learning-based feature engineering for stock price movement prediction

Wen Long et al.

KNOWLEDGE-BASED SYSTEMS (2019)

Review Physics, Multidisciplinary

Complex network approaches to nonlinear time series analysis

Yong Zou et al.

PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2019)

Article Engineering, Mechanical

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

Haicheng Zhang et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)

Article Economics

Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach

Qiang Ji et al.

QUARTERLY REVIEW OF ECONOMICS AND FINANCE (2018)

Article Biology

Predicting protein structural classes based on complex networks and recurrence analysis

Mohammad H. Olyaee et al.

JOURNAL OF THEORETICAL BIOLOGY (2016)

Article Multidisciplinary Sciences

Influence maximization in complex networks through optimal percolation

Flaviano Morone et al.

NATURE (2015)

Article Physics, Multidisciplinary

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

Na Wang et al.

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2012)

Article Physics, Multidisciplinary

Recurrence networks-a novel paradigm for nonlinear time series analysis

Reik V. Donner et al.

NEW JOURNAL OF PHYSICS (2010)

Article Physics, Multidisciplinary

Visibility graph approach to exchange rate series

Yue Yang et al.

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2009)

Article Multidisciplinary Sciences

From time series to complex networks:: The visibility graph

Lucas Lacasa et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2008)

Article Mathematics, Interdisciplinary Applications

Dynamical aspects of interaction networks

G Nicolis et al.

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS (2005)

Article Operations Research & Management Science

A tutorial on the cross-entropy method

PT De Boer et al.

ANNALS OF OPERATIONS RESEARCH (2005)