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Regularities and Discrepancies of Credit Default Swaps: a Data Science approach through Benford's Law

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  • Marcel Ausloos
  • Rosella Castellano
  • Roy Cerqueti

Abstract

In this paper, we search whether the Benford's law is applicable to monitor daily changes in sovereign Credit Default Swaps (CDS) quotes, which are acknowledged to be complex systems of economic content. This test is of paramount importance since the CDS of a country proxy its health and probability to default, being associated to an insurance against the event of its default. We fit the Benford's law to the daily changes in sovereign CDS spreads for 13 European countries, - both inside and outside the European Union and European Monetary Union. Two different tenors for the sovereign CDS contracts are considered: 5 yrs and 10 yrs, - the former being the reference and most liquid one. The time period under investigation is 2008-2015 which includes the period of distress caused by the European sovereign debt crisis. Moreover, (i) an analysis over relevant sub-periods is carried out, (ii) several insights are provided also by implementing the tracking of the Benford's law over moving windows. The main test for checking the conformance to Benford's law is - as usual - the $\chi^{2}$ test, whose values are presented and discussed for all cases. The analysis is further completed by elaborations based on Chebyshev's distance and Kullback and Leibler's divergence. The results highlight differences by countries and tenors. In particular, these results suggest that liquidity seems to be associated to higher levels of distortion. Greece - representing a peculiar case - shows a very different path with respect to the other European countries.

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  • Marcel Ausloos & Rosella Castellano & Roy Cerqueti, 2016. "Regularities and Discrepancies of Credit Default Swaps: a Data Science approach through Benford's Law," Papers 1603.01103, arXiv.org.
  • Handle: RePEc:arx:papers:1603.01103
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    References listed on IDEAS

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    16. Ausloos, M. & Herteliu, C. & Ileanu, B., 2015. "Breakdown of Benford’s law for birth data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 736-745.
    17. Mir, T.A., 2014. "The Benford law behavior of the religious activity data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 1-9.
    18. Tariq Ahmad Mir & Marcel Ausloos & Roy Cerqueti, 2014. "Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions," Papers 1410.2890, arXiv.org.
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    Cited by:

    1. Carbone, Anna & Jensen, Meiko & Sato, Aki-Hiro, 2016. "Challenges in data science: a complex systems perspective," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 1-7.
    2. Ausloos, Marcel & Cerqueti, Roy & Mir, Tariq A., 2017. "Data science for assessing possible tax income manipulation: The case of Italy," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 238-256.
    3. Bogdan Vasile Ileanu & Marcel Ausloos & Claudiu Herteliu & Marian Pompiliu Cristescu, 2019. "Intriguing behavior when testing the impact of quotation marks usage in Google search results," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2507-2519, September.
    4. Azevedo, Caio da Silva & Gonçalves, Rodrigo Franco & Gava, Vagner Luiz & Spinola, Mauro de Mesquita, 2021. "A Benford’s Law based methodology for fraud detection in social welfare programs: Bolsa Familia analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    5. Herteliu, Claudiu & Jianu, Ionel & Dragan, Irina Maria & Apostu, Simona & Luchian, Iuliana, 2021. "Testing Benford’s Laws (non)conformity within disclosed companies’ financial statements among hospitality industry in Romania," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    6. Ausloos, Marcel & Cerqueti, Roy & Bartolacci, Francesca & Castellano, Nicola G., 2018. "SME investment best strategies. Outliers for assessing how to optimize performance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 754-765.
    7. Riccioni, Jessica & Cerqueti, Roy, 2018. "Regular paths in financial markets: Investigating the Benford's law," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 186-194.
    8. Ausloos, Marcel & Cerqueti, Roy & Lupi, Claudio, 2017. "Long-range properties and data validity for hydrogeological time series: The case of the Paglia river," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 39-50.
    9. Tudorel Andrei & Bogdan Oancea & Peter Richmond & Gurjeet Dhesi & Claudiu Herteliu, 2017. "Decomposition of the Inequality of Income Distribution by Income Types - Application for Romania," Papers 1709.07960, arXiv.org.
    10. Roy Cerqueti & Claudio Lupi, 2021. "Some New Tests of Conformity with Benford’s Law," Stats, MDPI, vol. 4(3), pages 1-17, September.
    11. Cerqueti, Roy & Maggi, Mario, 2021. "Data validity and statistical conformity with Benford’s Law," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

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