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Research Papers

Detecting intraday financial market states using temporal clustering

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Pages 1657-1678 | Received 19 Aug 2015, Accepted 17 Mar 2016, Published online: 27 Apr 2016

References

  • Abergel, F. and Jedidi, A., Long time behaviour of a hawkes process-based limit order book. Working Paper, 2015. Available online at SSRN: http://ssrn.com/abstract=2575498.
  • Adi, A., Botzer, D., Nechushtai, G. and Sharon, G., Complex event processing for financial services. In Proceedings from the IEEE Services Computing Workshops, Chicago, IL, pp. 7–12, 2006.
  • Arthur, W., Complexity in economic and financial markets. Complexity, 1995, 1(1), 20–25.
  • Arthur, W., Holland, J., LeBaron, B., Palmer, R. and Taylor, P., Asset pricing under endogenous expectations in an artificial stock market. In The Economy as an Evolving Complex System, edited by W.B. Arthur, S.N. Durlauf and D.A. Lane, Vol. 2, pp. 15–44, 1997 (Westview Press: Boulder, CO).
  • Bacry, E., Mastromatteo, I. and Muzy, J., Hawkes processes in finance. Market Micro. Liquid., 2015, 1(1), 1550005.
  • Baldovin, F., Camana, F., Caporin, M., Caraglio, M. and Stella, A., Ensemble properties of high-frequency data and intraday trading rules. Quant. Finance, 2015, 15(2), 231–245.
  • Bastian, M., Heymann, S. and Jacomy, M., Gephi: An open source software for exploring and manipulating networks. In Proceedings from the International AAAI Conference on Weblogs and Social Media, San Jose, CA, 2009.
  • Bauke, H., Parameter estimation for power-law distributions by maximum likelihood methods. Eur. Phys. J. B, 2007, 58(2), 167–173.
  • Biais, L., Glosten, C. and Spatt, C., Market microstructure: A survey of microfoundations, empirical results, and policy implications. J. Financ. Markets, 2005, 8(2), 217–264.
  • Blatt, M., Wiseman, S. and Domany, E., Superparamagnetic clustering of data. Phys. Rev. Lett., 1996, 76(18), 3251–3254.
  • Blatt, M., Wiseman, S. and Domany, E., Data clustering using a model granular magnet. Neural Comput., 1997, 9, 1805–1842.
  • Brock, W., Pathways to randomness in the economy: Emergent nonlinearity and chaos in economics and finance. Estud. Econ., 1993, 8, 3–55.
  • Cieslakiewicz, D., Unsupervised asset cluster analysis implemented with parallel genetic algorithms on the Nvidia CUDA platform. Master’s Thesis, University of the Witwatersrand, 2014.
  • Clauset, A., Shalizi, C. and Newman, M., Power-law distributions in empirical data. SIAM Rev., 2009, 51(4), 661–703.
  • Cont, R. and Tankov, P., Financial Modelling with Jump Processes, CRC Financial Mathematics Series, 2004 (Chapman & Hall: London).
  • Dacorogna, M., Gauvreau, C., Muller, U., Olsen, R. and Pictet, O., Changing time scale for short-term forecasting in financial markets. J. Forecasting, 1996, 15, 203–227.
  • Derman, E., The perception of time, risk and return during periods of speculation. Quant. Finance, 2002, 2, 282–296.
  • Easley, D., López de Prado, M. and O’Hara, M., The volume clock: Insights into the high-frequency paradigm (digest summary). J. Portfolio Manage., 2012, 39(1), 19–29.
  • Emmert-Streib, F. and Dehmer, M., Influence of the time scale on the construction of financial networks. PLoS ONE, 2010, 5(9), e12884.
  • Engle, R. and Russell, J., Autoregressive conditional duration: A new model for irregularly spaced transaction data. Econometrica, 1998, 66, 1127–1162.
  • Fruchterman, T. and Reingold, E., Graph drawing by force-directed placement. Software Pract. Exper., 1991, 21(11), 1129–1164.
  • Gabaix, X., Gopikrishnan, P., Plerou, V. and Stanley, H., A theory of power-law distributions in financial market fluctuations. Nature, 2003, 423(6937), 267–270.
  • Garman, M., Market microstructure. J. Financ. Econ., 1976, 3, 257–275.
  • Gençay, R., Gradojevic, N., Selçuk, F. and Whitcher, B., Asymmetry of information flow between volatilities across time scales. Quant. Finance, 2010, 10(8), 895–915.
  • Giada, L. and Marsili, M., Data clustering and noise undressing of correlation matrices. Phys. Rev. E, 2001, 63(1), 061101.
  • Hasbrouck, J., Trades, quotes, inventories and information. J. Financ. Econ., 1988, 22, 229–252.
  • Hasbrouck, J., Measuring the information content of stock trades. J. Finance, 1991, 46, 179–207.
  • Hendricks, D., Gebbie, T. and Wilcox, D., High-speed detection of emergent market clustering via an unsupervised parallel genetic algorithm. S. Afr. J. Sci., 2016, 112(1/2).
  • Hinton, G., Learning multiple layers of representation. Trends Cogn. Sci., 2007, 11(10), 428–434.
  • Hommes, C., Financial markets as nonlinear adaptive evolutionary systems. Quant. Finance, 2001, 1(1), 149–167.
  • JSE, Dual-listed companies, 2014. Available online at: http://www.jse.co.za/how-tolist/mainboard/dual-listed-companies.aspx ( accessed 8 March 2014).
  • JSE, Market data -- Equities, derivatives and interest rate products price list, 2015. Available online at: https://www.jse.co.za/content/JSEPricingItems/JSE%20Equities,%20Derivatives%20and%20Interest%20Rate%20Products%20Price%20List%202016.pdf ( accessed 13 July 2015).
  • Kullmann, L., Kertész, J. and Mantegnae, R., Identification of clusters of companies in stock indices via potts super-paramagnetic transitions. Working Paper, 2000. Available online at arXiv: http://arxiv.org/abs/cond-mat/0002238.
  • Large, J., Measuring the resiliency of an electronic limit order book. J. Financ. Markets, 2000, 10, 1–25.
  • Madhavan, A., Market microstructure: A survey. J. Financ. Markets, 2000, 3(3), 205–258.
  • Marsili, M., Dissecting financial markets: Sectors and states. Quant. Finance, 2002, 2(4), 297–302.
  • Mastromatteo, I. and Marsili, M., On the criticality of inferred models. J. Stat. Mech.: Theory Exper., 2011, 2011(10), P10012.
  • McLachlan, G., Peel, D. and Whiten, W., Maximum likelihood clustering via normal mixture models. Signal Process.: Image Commun., 1996, 8(2), 105–111.
  • McNeil, A., Frey, R. and Embrechts, P., Quantitative Risk Management: Concepts, Techniques and Tools, Princeton Series in Finance, 2015 (Princeton University Press: Princeton, NJ).
  • Müller, U., Dacorogna, M., Davé, R., Pictet, O.V., Olsen, R. and Ward, J., Fractals and Intrinsic Time -- A Challenge to Econometricians, 1995 (Zurich: Olsen and Associates).
  • Mungan, M. and Ramasco, J., Stability of maximum-likelihood-based clustering methods: Exploring the backbone of classifications. J. Stat. Mech.: Theory Exper., 2010, 4, P04028.
  • Noh, J., A model for correlations in stock markets. Phys. Rev. E., 2000, 61, 5981.
  • O’Hara, M., Market Microstructure Theory, 1998 (Blackwell: Hoboken, NJ).
  • Patterson, D. and Hennessy, J., Computer Organization and Design: The Hardware/Software Interface, 5th ed., 2013 (Morgan Kaufmann: Burlington, MA).
  • Toke, I. and Pomponio, F., Modelling trades-through in a limit order book using Hawkes processes. Economics, 2012, 6(22), 1–23.
  • Wang, S. and Swendsen, R., Cluster monte carlo algorithms. Physica A, 1990, 167(565), 565–579.
  • Wilcox, D. and Gebbie, T., Hierarchical causality in financial economics. Working Paper, 2014. Available online at SSRN: http://ssrn.com/abstract=2544327.
  • Wiseman, S., Blatt, M. and Domany, E., Superparamagnetic clustering of data. Phys. Rev. E, 1998, 57, 37–67.
  • Zhang, L., Mykland, P. and Aït-Sahalia, Y., A tale of two time scales: Determining integrated volatility with noisy high-frequency data. J. Am. Stat. Assoc., 2005, 100(472), 1394–1411.

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