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Big data and complexity go hand in hand and Econophysics is a way to use this kind of data, with the particularity of being used mainly in finance

From Big Data to Econophysics and Its Use to Explain Complex Phenomena

JOURNAL OF RISK AND FINANCIAL MANAGEMENT, no. 7 (2020)

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Abstract

Big data has become a very frequent research topic, due to the increase in data availability. In this introductory paper, we make the linkage between the use of big data and Econophysics, a research field which uses a large amount of data and deals with complex systems. Different approaches such as power laws and complex networks are disc...More

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Introduction
  • Big data has become a very popular expression in recent years, related to the advance of technology which allows, on the one hand, the recovery of a great amount of data, and on the other hand, the analysis of that data, benefiting from the increasing computational capacity of devices.
  • Different approaches such as power laws and complex networks are discussed, as possible frameworks to analyze complex phenomena that could be studied using Econophysics and resorting to big data.
Highlights
  • Big data has become a very popular expression in recent years, related to the advance of technology which allows, on the one hand, the recovery of a great amount of data, and on the other hand, the analysis of that data, benefiting from the increasing computational capacity of devices
  • Big data has been used in several research areas such as business intelligence (Chen et al 2012; Sun et al 2018), marketing (Verhoef et al 2015; Wright et al 2019), economics (Glaeser et al 2018; Sobolevsky et al 2017), health (Pramanik et al 2017; Rose et al 2019), and psychology (Matz and Netzer 2017; Adjerid and Kelley 2018), among many other areas and studies which could be mentioned
  • Econophysics is a neologism used in the branch of Complex Systems from Physics seeking to make a complete survey of the statistical properties of financial markets, using the immense volume of available data and the methodologies of statistical physics (Mantegna and Stanley 1999)
  • Big data and complexity go hand in hand and Econophysics is a way to use this kind of data, with the particularity of being used mainly in finance
  • Complexity has been providing methods and models that try to explain the instabilities occurring in different markets, leaving five important lessons for financial markets: 1
  • Extreme events can occur in stock markets
Results
  • The use of big data allows the analysis of complex problems and has attracted the attention of physicists in recent decades.
  • Big data and complexity are intimately related to the emergence of a new research area called Econophysics.
  • Finance is one of the areas showing increased work which could be considered as using big data, and has attracted researchers from other research fields, such as physicists, even creating multidisciplinary research fields such as econophysics.
  • Econophysics is a neologism used in the branch of Complex Systems from Physics seeking to make a complete survey of the statistical properties of financial markets, using the immense volume of available data and the methodologies of statistical physics (Mantegna and Stanley 1999).
  • Power-laws have played an important role in economics to the extent of warranting an extensive article in the Journal of Economic Perspective (JEP), in which Gabaix (2016) demonstrates their applications in relation to finance, city size, executive salaries and macroeconomics, very different subjects.
  • One research area which benefited from these new approaches is finance, for which network theory enabled measurement of the probability of systemic risk, due to the interconnections and interdependence between the agents of a given system or market, in which the insolvency or bankruptcy of a single entity can cause chain failures (Jackson 2010, 2014).
  • Complex networks have influenced analysis in finance, as in, for example Haldane and May (2011), who analyzed the banking system as an ecological network susceptible to financial risks due to its topology.
  • It is crucial to analyze the changing relevance of the nodes, according to Bartesaghi et al (2020), which in the context of crises and their potential financial implications, could be an interesting issue for analysis using big data.
Conclusion
  • The availability of large datasets, jointly with increased computational processing, made big data and finance very attractive research areas in general, of particular interest in the analysis of crisis events.
  • In the current context, where the authors are facing the Covid-19 crisis, which could be considered as a complex phenomenon (Wagner 2020), risk analysis is raised to another level, requiring the monitoring of several issues lying beyond economic or financial topics, and that risk analysis must incorporate issues related to the environment, public health, politics, credit, and energy, among others.
Funding
  • Paulo Ferreira acknowledges the financial support of Fundação para a Ciência e a Tecnologia (grants UIDB/05064/2020 and UIDB/04007/2020). Éder Pereira is pleased to acknowledge financial support from Fundação de Amparo e Pesquisa do Estado da Bahia—FAPESB (grant number BOL 0261/2017).
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Author
Paulo Ferreira
Paulo Ferreira
Éder J.A.L. Pereira
Éder J.A.L. Pereira
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