Clustering of financial time series
Author
Abstract
Suggested Citation
DOI: 10.1016/j.physa.2013.01.027
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Jie-Jun Tseng & Sai-Ping Li, 2010. "Asset returns and volatility clustering in financial time series," Papers 1002.0284, arXiv.org, revised Apr 2011.
- Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
- Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 323-340, December.
- Basalto, Nicolas & Bellotti, Roberto & De Carlo, Francesco & Facchi, Paolo & Pantaleo, Ester & Pascazio, Saverio, 2007. "Hausdorff clustering of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 635-644.
- Caiado, Jorge & Crato, Nuno, 2007. "A GARCH-based method for clustering of financial time series: International stock markets evidence," MPRA Paper 2074, University Library of Munich, Germany.
- Tseng, Jie-Jun & Li, Sai-Ping, 2011. "Asset returns and volatility clustering in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1300-1314.
- I. Vodenska-Chitkushev & F. Z. Wang & P. Weber & K. Yamasaki & S. Havlin & H. E. Stanley, 2008. "Comparison between volatility return intervals of the S&P 500 index and two common models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(2), pages 217-223, January.
- Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
- Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
- Mantegna, Rosario N. & Stanley, H.Eugene, 1998.
"Modeling of financial data: Comparison of the truncated Lévy flight and the ARCH(1) and GARCH(1,1) processes,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 254(1), pages 77-84.
- Rosario N. Mantegna & H. Eugene Stanley, 1998. "Modeling of Financial Data: Comparison of the Truncated L\'evy Flight and the ARCH(1) and GARCH(1,1) processes," Papers cond-mat/9804126, arXiv.org.
- Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.
- Dose, Christian & Cincotti, Silvano, 2005. "Clustering of financial time series with application to index and enhanced index tracking portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 145-151.
- Domenico Piccolo, 1990. "A Distance Measure For Classifying Arima Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(2), pages 153-164, March.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Podobnik, Boris & Ivanov, Plamen Ch. & Grosse, Ivo & Matia, Kaushik & Eugene Stanley, H., 2004. "ARCH–GARCH approaches to modeling high-frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 216-220.
- R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
- Benoit Mandelbrot, 2015.
"The Variation of Certain Speculative Prices,"
World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78,
World Scientific Publishing Co. Pte. Ltd..
- Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394-394.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Li, Hailin, 2015. "Piecewise aggregate representations and lower-bound distance functions for multivariate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 10-25.
- G.M. Gallo & D. Lacava & E. Otranto, 2020.
"On Classifying the Effects of Policy Announcements on Volatility,"
Working Paper CRENoS
202008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Papers 2011.14094, arXiv.org, revised Feb 2021.
- John R. J. Thompson & Longlong Feng & R. Mark Reesor & Chuck Grace, 2021.
"Know Your Clients’ Behaviours: A Cluster Analysis of Financial Transactions,"
JRFM, MDPI, vol. 14(2), pages 1-29, January.
- John R. J. Thompson & Longlong Feng & R. Mark Reesor & Chuck Grace, 2020. "Know Your Clients' behaviours: a cluster analysis of financial transactions," Papers 2005.03625, arXiv.org, revised May 2020.
- Zhang, Yali & Wang, Jun, 2017. "Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 741-756.
- Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
- Moliner, Jesús & Epifanio, Irene, 2019. "Robust multivariate and functional archetypal analysis with application to financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 195-208.
- Dongjun Kim & Jinsung Yun & Kijung Kim & Seungil Lee, 2021. "A Comparative Study of the Robustness and Resilience of Retail Areas in Seoul, Korea before and after the COVID-19 Outbreak, Using Big Data," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
- Luis Lorenzo & Javier Arroyo, 2022. "Analysis of the cryptocurrency market using different prototype-based clustering techniques," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-46, December.
- Luo, Yi & Li, Xiaoming & Yu, Wei & Huang, Kun & Yang, Yihe & Huang, Yao, 2024. "Research on human dynamics characteristics under large-scale stock data perturbation," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
- Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2021. "Trimmed fuzzy clustering of financial time series based on dynamic time warping," Annals of Operations Research, Springer, vol. 299(1), pages 1379-1395, April.
- Giovanni De Luca & Paola Zuccolotto, 2021. "Regime dependent interconnectedness among fuzzy clusters of financial time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(2), pages 315-336, June.
- Román Ferrer & Rafael Benítez & Vicente J. Bolós, 2021. "Interdependence between Green Financial Instruments and Major Conventional Assets: A Wavelet-Based Network Analysis," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
- Tseng, Jie-Jun & Li, Sai-Ping, 2012. "Quantifying volatility clustering in financial time series," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 11-19.
- Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
- Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.
- Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2019. "A novel approach to detect volatility clusters in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
- Gilles Zumbach & Luis Fern�ndez & Caroline Weber, 2014. "Processes for stocks capturing their statistical properties from one day to one year," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 849-861, May.
- Andrea Gaunersdorfer & Cars Hommes, 2007.
"A Nonlinear Structural Model for Volatility Clustering,"
Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288,
Springer.
- Gaunersdorfer, A. & Hommes, C.H., 2000. "A Nonlinear Structural Model for Volatility Clustering," CeNDEF Working Papers 00-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Gaunersdorfer, A. & Hommes, C.H., 2005. "A nonlinear structural model for volatility clustering," CeNDEF Working Papers 05-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Giulia Di Nunno & Kk{e}stutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From constant to rough: A survey of continuous volatility modeling," Papers 2309.01033, arXiv.org, revised Sep 2023.
- Michele Vodret & Iacopo Mastromatteo & Bence Tóth & Michael Benzaquen, 2023. "Microfounding GARCH models and beyond: a Kyle-inspired model with adaptive agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 599-625, July.
- Di Xiao & Jun Wang & Hongli Niu, 2016. "Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 607-625, December.
- Kim, Kyungwon, 2013. "Modeling financial crisis period: A volatility perspective of Credit Default Swap market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4977-4988.
- Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
- Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
- Gürtler, Marc & Rauh, Ronald, 2012. "Challenging traditional risk models by a non-stationary approach with nonparametric heteroscedasticity," Working Papers IF41V1, Technische Universität Braunschweig, Institute of Finance.
- Eom, Cheoljun & Kaizoji, Taisei & Scalas, Enrico, 2019.
"Fat tails in financial return distributions revisited: Evidence from the Korean stock market,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
- Cheoljun Eom & Taisei Kaizoji & Enrico Scalas, 2019. "Fat Tails in Financial Return Distributions Revisited: Evidence from the Korean Stock Market," Papers 1904.02567, arXiv.org.
- Tzouras, Spilios & Anagnostopoulos, Christoforos & McCoy, Emma, 2015. "Financial time series modeling using the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 50-68.
- Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
- Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "VaR performance during the subprime and sovereign debt crises: An application to emerging markets," Emerging Markets Review, Elsevier, vol. 20(C), pages 23-41.
- Gil-Alana, Luis A. & Cunado, Juncal & de Gracia, Fernando Perez, 2013. "Salient features of dependence in daily US stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3198-3212.
- Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
More about this item
Keywords
Financial time series; GARCH models; Partitioning around medoids; Dailies returns of Euro exchange rates; Econophysics;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:392:y:2013:i:9:p:2114-2129. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.