Skip to main content
SpringerLink
Log in

Informing a Financial Market

  • Conference paper
  • First Online:
Decision Economics: Minds, Machines, and their Society (DECON 2020)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 990))

Included in the following conference series:

  • 304 Accesses

Abstract

This article reports on a scheme to exploit human computation and data science for fostering financial markets’ efficiency. The scheme consists in incentivizing market’s agents to assess their own risk of defaulting to financial contracts (that is, human computation) and in an eigenvector model of credit risk (that is, data science) aggregating agents’ assessments of their defaulting risk estimates into a global, or systemic, credit risk rating. The systemic credit risk rating in turn informs the market’s agents what nudges them to decisions beneficial not only to themselves, but also to the market as a whole.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    “Collective intelligence” is understood in the sense of Condorcet’s jury theorem [10] and of Galton’s observation on the “trustworthiness of popular judgments” [11].

  2. 2.

    Derivative contracts like swaps do not specify which contract party will be the debtor and which will be the creditor, hence the phrase “(actual of potential) debtor”.

  3. 3.

    The European Sovereign-Debt Crisis since 2009 can be seen as an evidence of this backflow through a currency of credit risk [13].

  4. 4.

    It is because of these paths that central banks can control the monetary base.

  5. 5.

    The asymmetric relations referred to in this article are those specified by networks’ directed edges.

  6. 6.

    Superscript t denotes time, not matrix transposition which is denoted, as usual, by superscript T.

References

  1. Altman, E.I., Saunders, A.: Credit risk measurement: developments over the last 20 years. J. Bank. Financ. 21, 1721–1742 (1998)

    Article  Google Scholar 

  2. Bhattacharya, S., Boot, A.W.A., Thakor, A.V.: The economics of bank regulation. J. Money Credit Bank. 30(4), 745–770 (1998)

    Article  Google Scholar 

  3. Bisias, D., Flood, M.D., Lo, A.W., Valavanis, S.: A Survey of Systemic Risk Analytics. Report 0001, U.S. Department of Treasury, Office of Financial Research (2012)

    Google Scholar 

  4. Bluhm, C., Oberbeck, L., Wagner, C.: An Introduction to Credit Risk Modeling. Chapman & Hall, CRC Financial Mathematics Series (2003)

    Google Scholar 

  5. Board of Governors: Report to the Congress on Credit Scoring and Its Effects on the Availability and Affordability of Credit. Report, Federal Reserve System (2007)

    Google Scholar 

  6. Bonacich, P.: Eigenvector-like measures of centrality for asymmetric relations. Soc. Networks 23, 191–201 (2001)

    Article  Google Scholar 

  7. Bordo, M.D.: A Brief History of Central Banks. Economic Commentary of the Federal Reserve Bank of Cleveland (2007)

    Google Scholar 

  8. Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Comput. Networks ISDN Syst. 30(1–7), 107–117 (1988)

    Google Scholar 

  9. Bry, F.: Handbook of human computation. In: Human Computation-Enabled Network Analysis for a Systemic Credit Risk Rating, pp. 215–245. Springer-Verlag (2013)

    Google Scholar 

  10. de Condorcet, N.: Éssai sur l’application de l’analyse à la probabilité des décisions rendues à la pluralité des voix. Imprimerie Royale, essay on the application of analysis to the probability of decisions rendered by the plurality of votes (1785)

    Google Scholar 

  11. Galton, F.: Vox populi. Nature 75, 450–451 (1907)

    Article  Google Scholar 

  12. Graeber, D.: Debt: The First 5000 Years. Allen Lane (2011)

    Google Scholar 

  13. Haidar, J.I.: Sovereign credit risk in the eurozone. World Econ. 13(1), 123–136 (2012)

    Google Scholar 

  14. Haldane, A.G., May, R.M.: Systemic risk in banking ecosystems. Nature 469, 351–355 (2011)

    Article  Google Scholar 

  15. Hansen, L.P.: Challenges in Identifying and Measuring Systemic Risk. Working Paper 18505, National Bureau of Economic Research (2013)

    Google Scholar 

  16. Kothari, V.: Credit Derivatives and Structured Credit Trading. In: Approaches to Quantification of Credit Risk, Wiley (2012)

    Google Scholar 

  17. Kyriakopoulos, F., Thurner, S., Puhr, C., Schmitz, S.W.: Network and eigenvalue analysis of financial transaction networks. Eur. Phys. J. B 71(4), 523–531 (2009)

    Article  Google Scholar 

  18. Langville, A.N., Meyer, C.D.: Google’s PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press, Hoboken (2006)

    Google Scholar 

  19. Mandelbrot, B., Hudson, R.L.: The Misbehavior of Markets: A Fractal View of Financial Turbulence. Basic Books, New York (2004)

    Google Scholar 

  20. Michelucci, P. (ed.): Handbook of Human Computation. Springer-Verlag (2013)

    Google Scholar 

  21. von Mises, R., Pollaczek-Geiringer, H.: Praktische Verfahren der Gleichungsauflösung. Zeitschrift für Angewandte Mathematik und Mechanik, practical methods for solving equations 9, 152–164 (1929) (in German)

    Google Scholar 

  22. Mitchell-Innes, A.: The credit theory of money. Bank. Law J. 31, 151–168 (1914)

    Google Scholar 

  23. Simkovic, M.: Paving the way for the next financial crisis. Bank. Financ. Serv. Policy Rep. 29(3), 1–20 (2010)

    Google Scholar 

  24. Simmel, G.: Philosophy of Money. Routledge and Kegan Paul Ltd. (1978)

    Google Scholar 

  25. Steele, K., Stefánsson, H.O.: Decision theory. In: The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University (2016)

    Google Scholar 

  26. Taleb, N.N.: The Black Swan – The Impact of the Highly Improbable. Random House, 2nd edn. (2007)

    Google Scholar 

  27. Tobin, J.: A proposal for international monetary reform. Eastern Econ. J. 153–159 (1978)

    Google Scholar 

  28. Treacy, W.F., Carey, M.S.: Credit Risk Rating at Large U.S. Banks. Federal Reserve Bulletin, pp. 897–921 (1998)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute for Informatics, Ludwig-Maximilian University of Munich, Munich, Germany

    François Bry

Authors
  1. François Bry
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to François Bry .

Editor information

Editors and Affiliations

  1. Department of PPEQS, Section of Economics and Quantitative Methods, University of Chieti-Pescara, Pescara, Pescara, Italy

    Edgardo Bucciarelli

  2. Department of Economics, National Chengchi University, Taipei, Taiwan

    Shu-Heng Chen

  3. AIR Institute - Deep Tech Lab, University of Valladolid, Valladolid, Spain

    Juan M. Corchado

  4. Department of Business and Economics Adminstration, University of Salamanca, Salamanca, Spain

    Javier Parra D.

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bry, F. (2021). Informing a Financial Market. In: Bucciarelli, E., Chen, SH., Corchado, J.M., Parra D., J. (eds) Decision Economics: Minds, Machines, and their Society. DECON 2020. Studies in Computational Intelligence, vol 990. Springer, Cham. https://doi.org/10.1007/978-3-030-75583-6_23

Download citation

Publish with us

Policies and ethics

Search

Navigation