Forecasting Financial Market Structure from Network Features using Machine Learning

1Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), São Carlos, Brazil 2Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK 3School of Management, University College London, Gower Street, London, WC1E 6BT, UK 4Institute for Systems and Computer Engineering, Technology and Science, University of Porto (UP), Porto, Portugal 5Laboratory of Technology and Innovation (LATIN), Federal Institute of South of Minas Gerais (IFSULDEMINAS), Poços de Caldas, Brazil *douglas.braz@ifsuldeminas.edu.br +these authors contributed equally to this work

[1]  João Gama,et al.  An overview of social network analysis , 2012, WIREs Data Mining Knowl. Discov..

[2]  Jan-Frederik Mai,et al.  Portfolio selection based on graphs: Does it align with Markowitz-optimal portfolios? , 2018 .

[3]  T. Aste,et al.  Correlation based networks of equity returns sampled at different time horizons , 2007 .

[4]  Efraim Turban,et al.  Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance , 1992 .

[5]  Alessandro Spelta,et al.  Financial market predictability with tensor decomposition and links forecast , 2017, Applied Network Science.

[6]  Linyuan Lü,et al.  Predicting missing links via local information , 2009, 0901.0553.

[7]  M Tumminello,et al.  A tool for filtering information in complex systems. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Yang Liu,et al.  Novel volatility forecasting using deep learning-Long Short Term Memory Recurrent Neural Networks , 2019, Expert Syst. Appl..

[9]  R. Mantegna.  Hierarchical structure in financial markets , 1998, cond-mat/9802256.

[10]  Zan Huang,et al.  The Time-Series Link Prediction Problem with Applications in Communication Surveillance , 2009, INFORMS J. Comput..

[11]  Tomaso Aste,et al.  Predicting future stock market structure by combining social and financial network information , 2018, Physica A: Statistical Mechanics and its Applications.

[12]  D. Ruppert.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .

[13]  Toktam A. Oghaz,et al.  Review on Graph Feature Learning and Feature Extraction Techniques for Link Prediction , 2019, ArXiv.

[14]  K. Kaski,et al.  Dynamics of market correlations: taxonomy and portfolio analysis. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Rosario N. Mantegna,et al.  Empirical Analyses of Networks in Finance , 2018 .

[16]  Fabrizio Lillo,et al.  Correlation, Hierarchies, and Networks in Financial Markets , 2008, 0809.4615.

[17]  Vito Latora,et al.  The multiplex dependency structure of financial markets , 2016, Complex..

[18]  Frank Nielsen,et al.  A Proposal of a Methodological Framework with Experimental Guidelines to Investigate Clustering Stability on Financial Time Series , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

[19]  Lada A. Adamic,et al.  Friends and neighbors on the Web , 2003, Soc. Networks.

[20]  Jun-ichi Inoue,et al.  On the non-stationarity of financial time series: impact on optimal portfolio selection , 2012, 1205.0877.

[21]  Boris Podobnik,et al.  Systemic risk and spatiotemporal dynamics of the US housing market , 2013, Scientific Reports.

[22]  Facundo Mémoli,et al.  Characterization, Stability and Convergence of Hierarchical Clustering Methods , 2010, J. Mach. Learn. Res..

[23]  R. Cont.  Long range dependence in financial markets , 2005 .

[24]  Fernando Berzal Galiano,et al.  A Survey of Link Prediction in Complex Networks , 2016, ACM Comput. Surv..

[25]  T. Aste,et al.  Spread of risk across financial markets: better to invest in the peripheries , 2013, Scientific Reports.

[26]  Jon M. Kleinberg,et al.  The link-prediction problem for social networks , 2007, J. Assoc. Inf. Sci. Technol..

[27]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[28]  Jean-Yves Potvin,et al.  Generating trading rules on the stock markets with genetic programming , 2004, Comput. Oper. Res..

[29]  T. D. Matteo,et al.  Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series , 2011, 1109.0465.

[30]  Ganapati Panda,et al.  Sentiment analysis of Twitter data for predicting stock market movements , 2016, 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES).

[31]  Mohammad Al Hasan,et al.  Link prediction using supervised learning , 2006 .

[32]  André Carlos Ponce de Leon Ferreira de Carvalho,et al.  Improving Portfolio Optimization Using Weighted Link Prediction in Dynamic Stock Networks , 2019, ICCS.

[33]  K. Kaski,et al.  Asset Trees and Asset Graphs in Financial Markets , 2003 .

[34]  Tiziana di Matteo,et al.  Clustering and hierarchy of financial markets data: advantages of the DBHT , 2014, ArXiv.

[35]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[36]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[37]  Tomaso Aste,et al.  Interplay between past market correlation structure changes and future volatility outbursts , 2016, Scientific Reports.

[38]  Wen Long,et al.  Deep learning-based feature engineering for stock price movement prediction , 2019, Knowl. Based Syst..

[39]  Frank Nielsen,et al.  A Review of Two Decades of Correlations, Hierarchies, Networks and Clustering in Financial Markets , 2017, Signals and Communication Technology.

[40]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[41]  Yue Yang,et al.  Complex network-based time series analysis , 2008 .

[42]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[43]  K. Kaski,et al.  Clustering and information in correlation based financial networks , 2003, cond-mat/0312682.

[44]  Tomaso Aste,et al.  Non-stationary multifractality in stock returns , 2013 .

[45]  Wolfram Barfuss,et al.  Parsimonious modeling with Information Filtering Networks , 2016, Physical review. E.

[46]  Jae Wook Song,et al.  Link prediction in the Granger causality network of the global currency market , 2020 .

[47]  G. Hunanyan,et al.  Portfolio Selection , 2019, Finanzwirtschaft, Banken und Bankmanagement I Finance, Banks and Bank Management.

[48]  Tiziana di Matteo,et al.  Hierarchical Information Clustering by Means of Topologically Embedded Graphs , 2011, PloS one.

[49]  K. Kaski,et al.  Dynamic asset trees and Black Monday , 2002, cond-mat/0212037.