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Hassan Ismail Fawaz et al.
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KiHwan Nam et al.
DECISION SUPPORT SYSTEMS (2019)
Multivariate LSTM-FCNs for time series classification
Fazle Karim et al.
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Wen Long et al.
KNOWLEDGE-BASED SYSTEMS (2019)
A Series-based group stock portfolio optimization approach using the grouping genetic algorithm with symbolic aggregate Approximations
Chun-Hao Chen et al.
KNOWLEDGE-BASED SYSTEMS (2017)
A multiple support vector machine approach to stock index forecasting with mixed frequency sampling
Yuchen Pan et al.
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Forecasting price movements using technical indicators: Investigating the impact of varying input window length
Yauheniya Shynkevich et al.
NEUROCOMPUTING (2017)
Cleaning large correlation matrices: Tools from Random Matrix Theory
Joel Bun et al.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2017)
Rotational Invariant Estimator for General Noisy Matrices
Joel Bun et al.
IEEE TRANSACTIONS ON INFORMATION THEORY (2016)
Global financial indices and twitter sentiment: A random matrix theory approach
A. Garcia
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2016)
Clustering stocks using partial correlation coefficients
Sean S. Jung et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2016)
A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems: D-MOFARC algorithm
Michela Fazzolari et al.
APPLIED SOFT COMPUTING (2014)
A causal feature selection algorithm for stock prediction modeling
Xiangzhou Zhang et al.
NEUROCOMPUTING (2014)
JIDT: an information-theoretic toolkit for studying the dynamics of complex systems
Joseph T. Lizier
FRONTIERS IN ROBOTICS AND AI (2014)
Efficient or adaptive markets? Evidence from major stock markets using very long run historic data
Andrew Urquhart et al.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS (2013)
Collective behavior in financial markets
T. K. Dal'Maso Peron et al.
EPL (2011)
Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange
Yakup Kara et al.
EXPERT SYSTEMS WITH APPLICATIONS (2011)
Eigenvectors of some large sample covariance matrix ensembles
Olivier Ledoit et al.
PROBABILITY THEORY AND RELATED FIELDS (2011)
A method for automatic stock trading combining technical analysis and nearest neighbor classification
Lamartine Almeida Teixeira et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting
Esmaeil Hadavandi et al.
KNOWLEDGE-BASED SYSTEMS (2010)
Surveying stock market forecasting techniques - Part II: Soft computing methods
George S. Atsalakis et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Forecasting histogram time series with k-nearest neighbours methods
Javier Arroyo et al.
INTERNATIONAL JOURNAL OF FORECASTING (2009)
Local information transfer as a spatiotemporal filter for complex systems
Joseph T. Lizier et al.
PHYSICAL REVIEW E (2008)
Common volatility and correlation clustering in asset returns
George A. Christodoulakis
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2007)
Causality detection based on information-theoretic approaches in time series analysis
Katerina Hlavackova-Schindler et al.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2007)
Quantifying cognitive biases in analyst earnings forecasts
Geoffrey Friesen et al.
JOURNAL OF FINANCIAL MARKETS (2006)
Systematic analysis of group identification in stock markets
DH Kim et al.
PHYSICAL REVIEW E (2005)
Support vector machine with adaptive parameters in financial time series forecasting
LJ Cao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2003)
Time series forecasting using a hybrid ARIMA and neural network model
GP Zhang
NEUROCOMPUTING (2003)
Analysing the information flow between financial time series - An improved estimator for transfer entropy
R Marschinski et al.
EUROPEAN PHYSICAL JOURNAL B (2002)
Quantifying and interpreting collective behavior in financial markets
P Gopikrishnan et al.
PHYSICAL REVIEW E (2001)
Measuring information transfer
T Schreiber
PHYSICAL REVIEW LETTERS (2000)