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Giovanni Montana

Personal Details

First Name:Giovanni
Middle Name:
Last Name:Montana
Suffix:
RePEc Short-ID:pmo385
http://www2.imperial.ac.uk/~gmontana/

Affiliation

Imperial College Mathematics Department

http://www2.imperial.ac.uk/mathematics/
London

Research output

as
Jump to: Working papers Articles

Working papers

  1. Kostas Triantafyllopoulos & Giovanni Montana, 2008. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Papers 0808.1710, arXiv.org, revised May 2009.
  2. Kostas Triantafyllopoulos & Giovanni Montana, 2007. "Fast estimation of multivariate stochastic volatility," Papers 0708.4376, arXiv.org, revised Nov 2007.
  3. Giovanni Montana & Kostas Triantafyllopoulos & Theodoros Tsagaris, 2007. "Flexible least squares for temporal data mining and statistical arbitrage," Papers 0709.3884, arXiv.org.

Articles

  1. Sim Aaron & Tsagkrasoulis Dimosthenis & Montana Giovanni, 2013. "Random forests on distance matrices for imaging genetics studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(6), pages 757-786, December.
  2. Silver Matt & Montana Giovanni & Alzheimer's Disease Neuroimaging Initiative, 2012. "Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-43, January.
  3. K. Triantafyllopoulos & G. Montana, 2011. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Computational Management Science, Springer, vol. 8(1), pages 23-49, April.
  4. Maurice Berk & Giovanni Montana, 2009. "Functional modelling of microarray time series with covariate curves," Statistica, Department of Statistics, University of Bologna, vol. 69(2), pages 159-186.
  5. Kendall, Wilfrid S. & Montana, Giovanni, 2002. "Small sets and Markov transition densities," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 177-194, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kostas Triantafyllopoulos & Giovanni Montana, 2008. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Papers 0808.1710, arXiv.org, revised May 2009.

    Cited by:

    1. Tim Leung & Brian Ward, 2015. "The golden target: analyzing the tracking performance of leveraged gold ETFs," Studies in Economics and Finance, Emerald Group Publishing, vol. 32(3), pages 278-297, August.
    2. Yerkin Kitapbayev & Tim Leung, 2017. "Mean Reversion Trading with Sequential Deadlines and Transaction Costs," Papers 1707.03498, arXiv.org, revised Jan 2018.
    3. David S. Sun & Shih-Chuan Tsai & Wei Wang, 2013. "Behavioral Investment Strategy Matters: A Statistical Arbitrage Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S3), pages 47-61, July.
    4. Clegg, Matthew & Krauss, Christopher, 2016. "Pairs trading with partial cointegration," FAU Discussion Papers in Economics 05/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. Tim Leung & Xin Li, 2014. "Optimal Mean Reversion Trading with Transaction Costs and Stop-Loss Exit," Papers 1411.5062, arXiv.org, revised May 2015.
    6. Kevin Guo & Tim Leung, 2016. "Understanding the Tracking Errors of Commodity Leveraged ETFs," Papers 1610.09404, arXiv.org.
    7. Cathy W. S. Chen & Sangyeol Lee & Shu-Yu Chen, 2016. "Local non-stationarity test in mean for Markov switching GARCH models: an approximate Bayesian approach," Computational Statistics, Springer, vol. 31(1), pages 1-24, March.
    8. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.
    9. Bolgun, Evren & Kurun, Engin & Guven, Serhat, 2009. "Dynamic Pairs Trading Strategy For The Companies Listed In The Istanbul Stock Exchange," MPRA Paper 19887, University Library of Munich, Germany.
    10. Krauss, Christopher, 2015. "Statistical arbitrage pairs trading strategies: Review and outlook," FAU Discussion Papers in Economics 09/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    11. João Frois Caldeira & Gulherme Valle Moura, 2013. "Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy," Brazilian Review of Finance, Brazilian Society of Finance, vol. 11(1), pages 49-80.

  2. Giovanni Montana & Kostas Triantafyllopoulos & Theodoros Tsagaris, 2007. "Flexible least squares for temporal data mining and statistical arbitrage," Papers 0709.3884, arXiv.org.

    Cited by:

    1. Zsuzsanna Zsibók & Balázs Varga, 2012. "Inflation Persistence in Hungary: a Spatial Analysis," Working Papers 1203, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    2. Evžen Kocenda & Balázs Varga, 2017. "The Impact of Monetary Strategies on Inflation Persistence," CESifo Working Paper Series 6306, CESifo Group Munich.
    3. K. Triantafyllopoulos & G. Montana, 2011. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Computational Management Science, Springer, vol. 8(1), pages 23-49, April.
    4. Josipa VIŠIC & Blanka ŠKRABIC, "undated". "Determinants of Incoming Cross-Border M&A: Evidence from European Transition Economies," EcoMod2010 259600168, EcoMod.
    5. Theodoros Tsagaris & Ajay Jasra & Niall Adams, 2010. "Robust and Adaptive Algorithms for Online Portfolio Selection," Papers 1005.2979, arXiv.org.
    6. Uliha, Gábor, 2016. "Az olajár gyengülő makrogazdasági hatásai. Két versengő elmélet szintézise
      [Weakening macroeconomic effects of the oil price. A synthesis of two competing theories]
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 787-818.
    7. Zsolt Darvas & Balázs Varga, 2012. "Uncovering Time-Varying Parameters with the Kalman-Filter and the Flexible Least Squares: a Monte Carlo Study," Working Papers 1204, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    8. Krauss, Christopher, 2015. "Statistical arbitrage pairs trading strategies: Review and outlook," FAU Discussion Papers in Economics 09/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    9. Kuethe, Todd H. & Foster, Kenneth A. & Florax, Raymond J.G.M., 2008. "A Spatial Hedonic Model with Time-Varying Parameters: A New Method Using Flexible Least Squares," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6306, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

Articles

  1. Silver Matt & Montana Giovanni & Alzheimer's Disease Neuroimaging Initiative, 2012. "Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-43, January.

    Cited by:

    1. Binder Harald & Müller Tina & Schwender Holger & Golka Klaus & Steffens Michael & Hengstler Jan G. & Ickstadt Katja & Schumacher Martin, 2012. "Cluster-Localized Sparse Logistic Regression for SNP Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-31, August.

  2. K. Triantafyllopoulos & G. Montana, 2011. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Computational Management Science, Springer, vol. 8(1), pages 23-49, April.
    See citations under working paper version above.
  3. Kendall, Wilfrid S. & Montana, Giovanni, 2002. "Small sets and Markov transition densities," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 177-194, June.

    Cited by:

    1. van Lieshout, M.N.M. & Stoica, R.S., 2006. "Perfect simulation for marked point processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 679-698, November.

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