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=== Individual trading decisions in finance ===
=== Individual trading decisions in finance ===
Mantegna and collaborators have performed empirical investigations of stock market investment decisions of single investor (technically a single legal entity). They have shown how different categories of single investors react to endogenous and exogeneous news about the stock market [R] and they have detected and statistically validated the existence and evolution of different group of market participants that are competing in the financial market by adopting, using and eventually discarding continuously updated investment strategies<ref>Federico Musciotto, Luca Marotta, Jyrki Piilo, Rosario N. Mantegna. [https://doi.org/10.1057/s41599-018-0145-1 Long-term ecology of investors in a financial market]. ''Palgrave Communications'', volume 4, Article number: 92 (2018).</ref>. These empirical findings are supporting the adaptive market hypothesis<ref>[https://en.wikipedia.org/wiki/Adaptive_market_hypothesis Adaptive market hypothesis]</ref>.
Mantegna and collaborators have performed empirical investigations of stock market investment decisions of single investor (technically a single legal entity). They have shown how different categories of single investors react to endogenous and exogeneous news about the stock market<ref>Lillo, F., Miccichè, S., Tumminello, M., Piilo, J. and Mantegna, R.N., 2015. [https://doi.org/10.1080/14697688.2014.931593 How news affects the trading behaviour of different categories of investors in a financial market]. ''Quantitative Finance'', 15(2), pp.213-229.</ref> and they have detected and statistically validated the existence and evolution of different group of market participants that are competing in the financial market by adopting, using and eventually discarding continuously updated investment strategies<ref>Federico Musciotto, Luca Marotta, Jyrki Piilo, Rosario N. Mantegna. [https://doi.org/10.1057/s41599-018-0145-1 Long-term ecology of investors in a financial market]. ''Palgrave Communications'', volume 4, Article number: 92 (2018).</ref>. These empirical findings are supporting the adaptive market hypothesis<ref>[https://en.wikipedia.org/wiki/Adaptive_market_hypothesis Adaptive market hypothesis]</ref>.


== External links ==
== External links ==

Revision as of 16:39, 18 January 2023

Rosario N. Mantegna is Applied Physics professor[1] at Palermo University, Palermo, Italy, and member of the External Faculty of the Complexity Science Hub Vienna[2].

Rosario Nunzio Mantegna
Born
August 23th, 1960, Palermo, Italy
Nationality
Italian
Education
Master’s degree in physics at Palermo University obtained on June 29th 1984. Thesis: “Effetto della diffusione spettrale sulla cinetica di saturazione delle risonanze magnetiche (in Italian)”.
PhD in physics. Palermo University March 1990. Thesis: Processi stocastici e fenomeni caotici in sistemi non lineari a frequenza di microonde (in Italian)”.
Fields
Statistical Physics; Econophysics; Financial Markets; Complex systems; Complex networks.
Institutions
Full professor of Applied Physics at the Dipartimento di Fisica e Chimica - Emilio Segrè, Palermo University. Italy. Since 30/12/2004
Member of the External Faculty of the Complexity Science Hub Vienna, Wien, Austria. Since 4/2017.
Notes
Top Italian Scientist in Physics [3]

He graduated in Physics at Palermo University in 1984 and did his PhD in Physics at the same University defending his thesis on “Stochastic process at microwave frequency” in 1990. He was postdoc at the Max-Planck Institute for Quantum Optics in Munich where he did experiments on quantum chaos and at Boston University where he worked on complex systems under the mentorship of Gene Stanley. During 2012-2016 he was also professor at the “Center for Network Science” and “Department of Economics” of Central European University, Budapest, Hungary[4]. During 2016-2021 he was honorary professor at University College London, UK. He is an associate of the UCL Centre for Blockchain Technologies[5].

He has been principal investigator or member of several international and national research projects funded by the European Union, the National Science Foundation of USA, The Italian Ministry of Education, The Italian Institute for the Physics of Matter, and by the Institute for New Economic Thinking[6].

Education and career

Education

  • 1984: Master’s degree in physics at Palermo University obtained on June 29th 1984. Thesis: “Effetto della diffusione spettrale sulla cinetica di saturazione delle risonanze magnetiche (in Italian)”.
  • 1990: PhD in physics. Palermo University March 1990. Thesis: Processi stocastici e fenomeni caotici in sistemi non lineari a frequenza di microonde (in Italian)”.

Current positions

  • 30/12/2004 - today: Full professor of Applied Physics at the Dipartimento di Fisica e Chimica - Emilio Segrè, Palermo University. Italy.
  • 4/2017 - today: Member of the External Faculty of the Complexity Science Hub Vienna, Wien, Austria.

Previous positions

  • 1/10/1989 - 31/1/1990: with a CNR fellowship at “Istituto per le Applicazioni Interdisciplinari della Fisica” of Consiglio Nazionale delle Ricerche, Palermo.
  • 1/2/1990 - 31/1/1991: Post-Doc at the “Max-Planck Institut für Quantenoptik”, Munich (Germany) with an Advanced Fellowship NATO-CNR.
  • 14/10/1993 - 13/10/1994: Post-Doc at the “Center for Polymer Studies and Department of Physics of Boston University”, Boston MA, USA.
  • 17/10/1994 - 31/10/1999: Assistant professor of Physics at the “Dipartimento di Energetica ed Applicazioni di Fisica” of Palermo University, Palermo, Italy.
  • 1/11/1999 - 29/12/2004: Associate professor of Applied Physics at the “Dipartimento di Energetica ed Applicazioni di Fisica” and then at “Dipartimento di Fisica e Tecnologie Relative” of Palermo University, Palermo, Italy.
  • 1/9/2012 - 31/8/2016: Professor at the “Center for Network Science” and “Department of Economics”, Central European University, Budapest, Hungary.
  • 1/3/2016 - 28/2/2021: Honorary professor at the “Department of Computer Science” of University College London, London, UK.

Research

Early days of econophysics

His research concerns interdisciplinary applications of statistical physics. He contributed to the analysis and modeling of social and economic systems with tools and concepts of statistical physics as early as 1990 by writing what is considered the first paper of econophysics[7]. In 1995 he published the first Nature paper on econophysics together with Gene Stanley[8] and in 1999 he co-authored the first book on Econophysics[9].

In September 1998, Rosario Mantegna was the organizer and the Chairman of one of the first meetings on Econophysics. This was the “International Workshop on Econophysics and Statistical Finance” held at University of Palermo, Italy. This Workshop is the first Workshop on Econophysics that has published proceedings[10].

Lévy random variables algorithm

In 1994 Mantegna wrote an algorithm for the generation of random values of symmetric \alpha-stable Lévy random variables[11]. His algorithm is one the of the fastest and more accurate algorithms generating symmetric \alpha-stable Lévy variables in the interval a=(0.75,2) of the scaling parameter[12].

Truncated Lévy Flights

The work on the scaling behavior of returns of the S&P 500 index[13] highlighted the leptokurtic nature and the finiteness of the second moment of return distribution in finance. In Mantegna/Stanley study, this finding was obtained for the first time with intraday return and motivated the introduction of the concept of Truncated Lévy flights[14]. Truncated Lévy Flights are \alpha-stable-like Lévy random processes with finite second moment arising from a form of truncation of large values produced in various form. Truncated Lévy Flights are used in derivative modeling and risk assessment in finance[15].

Similarity based networks

In 1999[16] Mantegna introduced similarity-based networks by proposing the use of the Minimum Spanning Tree as a tool to filter information in multivariate time series[17]. The paradigmatic example was a set of financial.

returns of liquid stocks traded at the US stock markets. Since its introduction in Finance, Minimum Spanning Tree has been used as filtering tool in several financial systems both by academicians [M], financial economists [N] and financial practitioners. In 2004 Mantegna and collaborators introduced the Planar Maximally Filtered Graph as a generalization of the Minimum Spanning Tree[18].

Statistically validated networks

Rosario Mantegna has been also pioneering in the field of complex network filtering. The extraction of filtered elements of a complex network allows to focus the analysis on relevant connections that are highly representative of the system, discarding all those nodes and links that can be described by an appropriate statistical null hypothesis. In 2011 Mantegna and collaborators proposed one of the first analytical methods available to detect statistically validated over-expressed links in a bipartite network[19]. The method was soon generalized in several directions including directed networks and also the possibility to detect statistically validated under-expressed links[20], i.e., links that present events that occurs less than expected for the null model. In 2021, Mantegna and collaborators have introduced analytic, and computational approaches to filter hypergraphs and highlight the most relevant higher-order connections[21].

Individual trading decisions in finance

Mantegna and collaborators have performed empirical investigations of stock market investment decisions of single investor (technically a single legal entity). They have shown how different categories of single investors react to endogenous and exogeneous news about the stock market[22] and they have detected and statistically validated the existence and evolution of different group of market participants that are competing in the financial market by adopting, using and eventually discarding continuously updated investment strategies[23]. These empirical findings are supporting the adaptive market hypothesis[24].

External links

References

  1. ↑ Rosario Nunzio Mantegna - Università degli Studi di Palermo
  2. ↑ Rosario Mantegna - Palermo University & CSH External Faculty
  3. ↑ Rosario Nunzio Mantegna - Top Italian Scientist in Physics
  4. ↑ Exploring Criminal Patterns - Central European University
  5. ↑ Rosario Mantegna - UCL Blockchain
  6. ↑ Rosario Nunzio Mantegna - Institute for New Economic Thinking
  7. ↑ Rosario Nunzio Mantegna. Lévy walks and enhanced diffusion in Milan stock exchange. Physica A: Statistical Mechanics and its Applications. Volume 179, Issue 2, 1 December 1991, Pages 232-242.
  8. ↑ Rosario N. Mantegna & H. Eugene Stanley. Scaling behaviour in the dynamics of an economic index. Nature. 376, pages46–49 (1995).
  9. ↑ Mantegna, R., & Stanley, H. (1999). Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge: Cambridge University Press. The book has been translated in Japanese (EconomistSha, Inc.), in Polish (Polish Scientific Publishers PWN), in Indonesian (Pearson Education Asia), in Chinese (Lianjing Publishing House) and in Russian (Editorial URSS).
  10. ↑ Physica A: Statistical Mechanics and its Applications. ScienceDirect. Volume 269, Issue 1 Pages 1-188 (1 July 1999)
  11. ↑ Rosario Nunzio Mantegna. Fast, accurate algorithm for numerical simulation of Lévy stable stochastic processes. Physical Review E. P49, 4677 – Published 1 May 1994
  12. ↑ E Pantaleo, P Facchi, and S Pascazio, Simulations of Lévy flights. Physica Scripta, Volume 2009, Number T135 Published 31 July 2009. The Royal Swedish Academy of Sciences.
  13. ↑ Rosario N. Mantegna & H. Eugene Stanley. Scaling behaviour in the dynamics of an economic index. Nature, volume 376, pages46–49 (1995)
  14. ↑ Rosario N. Mantegna and H. Eugene Stanley. Stochastic Process with Ultraslow Convergence to a Gaussian: The Truncated Lévy Flight. Phys. Rev. Lett., 73, 2946 – Published 28 November 1994
  15. ↑ Ole E. Barndorff-Nielsen & Neil Shephard. Modelling by Lévy Processess for Financial Econometrics. Lévy Processes, pp 283–318
  16. ↑ Mantegna, R.N., 1999. Hierarchical structure in financial markets. The European Physical Journal B-Condensed Matter and Complex Systems, 11(1), pp.193-197.
  17. ↑ Stock correlation network
  18. ↑ M. Tumminello, T. Aste, T. Di Matteo, and R. N. Mantegna. A tool for filtering information in complex systems. APPLIED PHYSICAL SCIENCES. July 18, 2005. 102 (30) 10421-10426.
  19. ↑ Michele Tumminello, Salvatore Miccichè, Fabrizio Lillo, Jyrki Piilo, Rosario N. Mantegna. Statistically Validated Networks in Bipartite Complex Systems. PLOS One. Published: March 31, 2011.
  20. ↑ Vasilis Hatzopoulos, Giulia Iori, Rosario N. Mantegna, Salvatore Miccichè, Michele Tumminello. Quantifying preferential trading in the e-MID interbank market. Quantitative Finance. Volume 15, 2015 - Issue 4: Pages 693-710.
  21. ↑ Federico Musciotto, Federico Battiston, Rosario N. Mantegna. Detecting informative higher-order interactions in statistically validated hypergraphs. Communications Physics, volume 4, Article number: 218 (2021).
  22. ↑ Lillo, F., Miccichè, S., Tumminello, M., Piilo, J. and Mantegna, R.N., 2015. How news affects the trading behaviour of different categories of investors in a financial market. Quantitative Finance, 15(2), pp.213-229.
  23. ↑ Federico Musciotto, Luca Marotta, Jyrki Piilo, Rosario N. Mantegna. Long-term ecology of investors in a financial market. Palgrave Communications, volume 4, Article number: 92 (2018).
  24. ↑ Adaptive market hypothesis
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