Tiziana Di Matteo

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Tiziana Di Matteo
Alma mater University of Salerno
Queen Mary University
Scientific career
Institutions King's College London

Tiziana Di Matteo is a Professor of Econophysics at King's College London. She studies complex systems, such as financial markets, and complex materials (such as superconductors). She serves on the council of the Complex Systems Society.

Contents

Education and early career

Di Matteo graduated cum laude from the University of Salerno in 1994. [1] She was an Erasmus student at Queen Mary University of London. She remained at the University of Salerno for her graduate studies, completing her PhD on Josephson junctions networks in 1999. [2] After her PhD, she became interested in the data sets of real financial markets. [3]

Selected publications

Awards and honours

Di Matteo was a QEII Fellow at the Australian National University. [4] [5] She joined the Department of Mathematics at King's College London in 2009. [1] [6] She has used the generalised Hurst approach to study the foreign exchange market and stock markets. [7] In 2014 she was made a Professor of Econophysics at King's College London. [8] Econophysics uses the statistical methods of physics to analyse financial markets. [9]

She was appointed to the Council of the Complex Systems Society in 2018. [9] Di Matteo is the editor-in-chief of the Journal of Network theory in Finance. [10] She also serves as editor for the European Physical Journal B. [11]

Related Research Articles

Econophysics is a heterodox interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics, usually those including uncertainty or stochastic processes and nonlinear dynamics. Some of its application to the study of financial markets has also been termed statistical finance referring to its roots in statistical physics. Econophysics is closely related to social physics.

The Associateship or Associate of King's College (AKC) award was the degree-equivalent qualification of King's College London from 1833. It is the original qualification that King's awarded to its students. In current practice, it is an optional award, unique to King's College London, that students can study in addition to their degree proper. After successfully completing the AKC course, participants may apply to be elected by the Academic Board of King's College London as an 'Associate of King's College' (AKC). Once their election has been ratified, they are permitted to use the post-nominal letters "AKC" along with their main qualification.

Statistical finance, is the application of econophysics to financial markets. Instead of the normative roots of finance, it uses a positivist framework. It includes exemplars from statistical physics with an emphasis on emergent or collective properties of financial markets. Empirically observed stylized facts are the starting point for this approach to understanding financial markets.

The Hurst exponent is used as a measure of long-term memory of time series. It relates to the autocorrelations of the time series, and the rate at which these decrease as the lag between pairs of values increases. Studies involving the Hurst exponent were originally developed in hydrology for the practical matter of determining optimum dam sizing for the Nile river's volatile rain and drought conditions that had been observed over a long period of time. The name "Hurst exponent", or "Hurst coefficient", derives from Harold Edwin Hurst (1880–1978), who was the lead researcher in these studies; the use of the standard notation H for the coefficient also relates to his name.

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Quantum finance is an interdisciplinary research field, applying theories and methods developed by quantum physicists and economists in order to solve problems in finance. It is a branch of econophysics.

A stock correlation network is a type of financial network based on stock price correlation used for observing, analyzing and predicting the stock market dynamics.

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References

  1. 1 2 "Homepage". nms.kcl.ac.uk. Retrieved 2019-02-06.
  2. Di Matteo, T.; Paasi, J.; Tuohimaa, A.; De Luca, R. (June 1999). "Three-dimensional network of inductively coupled Josephson junctions as a vectorial magnetic field sensor". IEEE Transactions on Applied Superconductivity . 9 (2): 3515–3518. Bibcode:1999ITAS....9.3515D. doi:10.1109/77.783788. ISSN   1051-8223. S2CID   38415485. Wikidata   Q105576234.
  3. "King's College London - Professor Tiziana Di Matteo". www.kcl.ac.uk. Retrieved 2019-02-06.
  4. "DR. TIZIANA DI MATTEO". spie.org. Retrieved 2019-02-07.
  5. Abergel, Frédéric; Aoyama, Hideaki; Chakrabarti, Bikas K.; Chakraborti, Anirban; Ghosh, Asim (2013-09-07). Econophysics of Agent-Based Models. Springer Science & Business Media. ISBN   9783319000237.
  6. Thurner, Stefan (2016-11-11). 43 Visions For Complexity. World Scientific. ISBN   9789813206861.
  7. Matteo, T. Di; Aste, T.; Dacorogna, Michel M. (April 2005). "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development". Journal of Banking and Finance . 29 (4): 827–851. arXiv: cond-mat/0403681 . doi:10.1016/J.JBANKFIN.2004.08.004. ISSN   0378-4266. S2CID   18005919. Wikidata   Q105576212.
  8. "King's College London - Prof Tiziana Di Matteo". www.kcl.ac.uk. Retrieved 2019-02-06.
  9. 1 2 "King's College London - Professor Tiziana Di Matteo elected to Council of Complex Systems Society". www.kcl.ac.uk. Retrieved 2019-02-06.
  10. "Journal of Network Theory in Finance Editorial Board". Risk.net. Retrieved 2019-02-06.
  11. "Cambridge Scholars Publishing". www.cambridgescholars.com. Retrieved 2019-02-06.