Mikhail Vladimirovich Batsyn

Personal Details

First Name:	Mikhail
Middle Name:	Vladimirovich
Last Name:	Batsyn
Suffix:
RePEc Short-ID:	pba1059
	http://www.hse.ru/en/org/persons/452159

Affiliation

Национальный исследовательский университет Высшая школа экономики, Лаборатория алгоритмов и технологий анализа сетевых структур (National Research University Higher School of Economics, Laboratory of algorithms and technologies for networks analysis)

http://nnov.hse.ru/en/latna
Russia, Nizhny Novgorod

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.

Articles

1. Evgeny Maslov & Mikhail Batsyn & Panos Pardalos, 2014. "Speeding up branch and bound algorithms for solving the maximum clique problem," Journal of Global Optimization, Springer, vol. 59(1), pages 1-21, May.

   Cited by:

   1. Wu, Qinghua & Hao, Jin-Kao, 2015. "A review on algorithms for maximum clique problems," European Journal of Operational Research, Elsevier, vol. 242(3), pages 693-709.
   2. Coniglio, Stefano & Furini, Fabio & San Segundo, Pablo, 2021. "A new combinatorial branch-and-bound algorithm for the Knapsack Problem with Conflicts," European Journal of Operational Research, Elsevier, vol. 289(2), pages 435-455.
   3. San Segundo, Pablo & Furini, Fabio & Álvarez, David & Pardalos, Panos M., 2023. "CliSAT: A new exact algorithm for hard maximum clique problems," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1008-1025.
   4. Stefano Coniglio & Stefano Gualandi, 2022. "Optimizing over the Closure of Rank Inequalities with a Small Right-Hand Side for the Maximum Stable Set Problem via Bilevel Programming," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1006-1023, March.
   5. Yuichi Asahiro & Tomohiro Kubo & Eiji Miyano, 2019. "Experimental Evaluation of Approximation and Heuristic Algorithms for Maximum Distance-Bounded Subgraph Problems," The Review of Socionetwork Strategies, Springer, vol. 13(2), pages 143-161, October.
   6. Assif Assad & Kusum Deep, 2018. "A heuristic based harmony search algorithm for maximum clique problem," OPSEARCH, Springer;Operational Research Society of India, vol. 55(2), pages 411-433, June.

2. Kocheturov, Anton & Batsyn, Mikhail & Pardalos, Panos M., 2014. "Dynamics of cluster structures in a financial market network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 523-533.

   Cited by:

   1. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
   2. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
   3. Dimitris Andriosopoulos & Michael Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Post-Print hal-02880149, HAL.
      • Dimitris Andriosopoulos & Michael Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Post-Print hal-02879937, HAL.
      • Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
   4. Haiming Long & Ji Zhang & Nengyu Tang, 2017. "Does network topology influence systemic risk contribution? A perspective from the industry indices in Chinese stock market," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-19, July.
   5. Huang, Wei-Qiang & Yao, Shuang & Zhuang, Xin-Tian & Yuan, Ying, 2017. "Dynamic asset trees in the US stock market: Structure variation and market phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 94(C), pages 44-53.
   6. Bentian Li & Dechang Pi, 2018. "Analysis of global stock index data during crisis period via complex network approach," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-16, July.
   7. khoojine, Arash Sioofy & Han, Dong, 2019. "Network analysis of the Chinese stock market during the turbulence of 2015–2016 using log-returns, volumes and mutual information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1091-1109.
   8. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
   9. Zhu, Xiaoyu & Ma, Yinghong & Liu, Zhiyuan, 2018. "A novel evolutionary algorithm on communities detection in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 938-946.
   10. Kong, Xiaolin & Ma, Chaoqun & Ren, Yi-Shuai & Narayan, Seema & Nguyen, Thong Trung & Baltas, Konstantinos, 2023. "Changes in the market structure and risk management of Bitcoin and its forked coins," Research in International Business and Finance, Elsevier, vol. 65(C).
   11. Tristan Millington & Mahesan Niranjan, 2020. "Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation," Papers 2005.03963, arXiv.org, revised Nov 2020.
   12. Millington, Tristan & Niranjan, Mahesan, 2021. "Stability and similarity in financial networks—How do they change in times of turbulence?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
   13. Lu, Ya-Nan & Li, Sai-Ping & Zhong, Li-Xin & Jiang, Xiong-Fei & Ren, Fei, 2018. "A clustering-based portfolio strategy incorporating momentum effect and market trend prediction," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 1-15.
   14. Fazlollah Soleymani & Mahdi Vasighi, 2022. "Efficient portfolio construction by means of CVaR and k‐means++ clustering analysis: Evidence from the NYSE," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3679-3693, July.
   15. Millington, Tristan & Niranjan, Mahesan, 2021. "Construction of minimum spanning trees from financial returns using rank correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
   16. Andrea Di Iura, 2022. "Comparison of empirical and shrinkage correlation algorithm for clustering methods in the futures market," SN Business & Economics, Springer, vol. 2(8), pages 1-17, August.

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