Measuring Banks’ Antifragility via Fuzzy Logic
Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.
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 N. N. Taleb, Antifragile: Things that gain from disorder. Random House Incorporated, 2012.
 J. Johnson and A. V. Gheorghe, “Antifragility analysis and measurement framework for systems of systems,” Int. J. Disaster Risk Sci., vol. 4, no. 4, pp. 159–168, 2013.
 Y. Bar-Yam, “Multiscale variety in complex systems,” Complexity, vol. 9, no. 4, pp. 37–45, 2004.
 J. H. Holland, “Studying complex adaptive systems,” J. Syst. Sci. Complex., vol. 19, no. 1, pp. 1–8, 2006.
 O. T. Holland, “Partitioning method for emergent behavior systems modeled by agent-based simulations,” 2012.
 K. J. Hole, Anti-fragile ICT Systems. 2016.
 R. Chiva, P. Ghauri, and J. Alegre, “Organizational Learning, Innovation and Internationalization: A Complex System Model,” Br. J. Manag., vol. 25, no. 4, pp. 687–705, 2014.
 M. Gell-Mann and S. Lloyd, “Information measures, effective complexity, and total information,” Complexity, vol. 2, no. 1, pp. 44–52, 1996.
 B. Ellis and S. I. Herbert, “Complex adaptive systems (CAS): An overview of key elements, characteristics and application to management theory,” J. Innov. Heal. Informatics, vol. 19, no. 1, pp. 33–37, 2011.
 Y. M. Carlisle and E. McMillan, “Complex Adaptative Systems and Strategy as Learning,” in Global Innovation and Entrepreneurship: Challenges and Experiences from East and West, 2017, pp. 43–60.
 D. Parker and R. Stacey, Caos, administração e economia as implicações do pensamento não-linear. Instituto Liberal, 1995.
 R.-A. Thietart and B. Forgues, “Complexity science and organization,” SAGE Handb. Complex. Manag., pp. 53–64, 2011.
 A. Danchin, P. M. Binder, and S. Noria, “Antifragility and tinkering in biology (and in business) flexibility provides an efficient epigenetic way to manage risk,” Genes (Basel)., vol. 2, no. 4, pp. 998–1016, 2011.
 J. L. Casti, X-Events: The collapse of everything. Harper Collins, 2012.
 N. N. Taleb, The Black Swan: The impact of the highly improbable. 2010.
 M. Gladwell, The tipping point: How little things can make a big difference. Little, Brown, 2006.
 N. N. Taleb and R. Douady, “Mathematical definition, mapping, and detection of (anti)fragility,” Quant. Financ., vol. 13, no. 11, pp. 1677–1689, 2013.
 A. Ghasemi and M. Alizadeh, “Evaluating Organizational Antifragility Via Fuzzy Logic . The case of an Iranian Company,” Oper. Res. Decis., vol. 27, no. 2, pp. 21–43, 2017.
 P. Triana, Lecturing Birds on Flying: Can Mathematical Theories Destroy the Financial Markets? 2009.
 T. Aven, “The Illusion of Risk Control,” in A conceptual foundation for assessing and managing risk, surprises and black swans, Springer, Cham, 2017, pp. 23–39.
 D. Geer, “Resolved: The Internet is no place for critical infrastructure,” Commun. ACM, vol. 58, no. 6, pp. 48–53, 2013.
 F. Allen and D. Gale, “Financial contagion,” J. Polit. Econ., vol. 108, no. 1, pp. 1–33, 2000.
 D. Acemoglu Asuman Ozdaglar Alireza Tahbaz-Salehi, D. Brown, O. Candogan, G. Gorton, A. Jadbabaie, J.-C. Rochet, A. Simsek, and A. Shourideh, “Systemic Risk and Stability in Financial Networks Systemic Risk and Stability in Financial Networks,” Am. Econ. Rev., vol. 105, no. 2, pp. 564--608, 2015.
 S. Markose, S. Giansante, and A. R. Shaghaghi, “‘Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic risk,” J. Econ. Behav. Organ., vol. 83, no. 3, pp. 627–646, 2012.
 S. Vitali, J. B. Glattfelder, and S. Battiston, “The network of global corporate control,” PLoS One, vol. 6, no. 10, p. e25995, 2011.
 H. Elsinger, A. Lehar, and M. Summer, “Network models and systemic risk assessment,” Handb. Syst. Risk, no. 403, pp. 1–24, 2013.
 K. Anand, S. Brennan, P. Gai, S. Kapadia, and M. Willison, “A Network Model of Financial System Resilience,” J. Econ. Behav. Organ., vol. 85, no. 1, pp. 219–235, 2013.
 S. Battiston, G. Caldarelli, R. M. May, T. Roukny, and J. E. Stiglitz, “The price of complexity in financial networks,” Proc. Natl. Acad. Sci., vol. 113, no. 36, pp. 10031–10036, 2016.
 T. Adrian and M. K. Brunnermeier, “Tobias Adrian and Markus K. Brunnermeier 1,” J. Econ. Perspect., vol. 106, no. 7, pp. 1705–1741, 2016.
 M. Billio and A. W. Lo, “Econometric measures of systemic risk in the finance and insurance sectors,” 2010.
 S. Benoit, J. Dudek, and M. Sharifova, “Identifying SIFIs: Toward the simpler Approach,” pp. 1–33, 2013.
 BCBS, Basel III: A global regulatory framework for more resilient banks and banking systems. Bank for International Settlements, 2011.
 BCBS, Basel III: Finalizing post-crisis reforms. Bank for International Settlements, 2017.
 R. Dahlberg, “From Risk to Resilience - Challenging Predictability in Contemporary Disaster and Emergency Management Thinking,” University of Copenhagen, 2017.
 S. Dekker, P. Cilliers, and J. H. Hofmeyr, “The complexity of failure: Implications of complexity theory for safety investigations,” Saf. Sci., vol. 49, no. 6, pp. 939–945, 2011.
 J. Park, T. P. Seager, P. S. C. Rao, M. Convertino, and I. Linkov, “Integrating risk and resilience approaches to catastrophe management in engineering systems,” Risk Anal., vol. 33, no. 3, pp. 356–367, 2013.
 E. Hollnagel, “Resilience engineering and the built environment,” Build. Res. Inf., vol. 42, no. 2, pp. 221–228, 2014.
 A. W. Righi, T. A. Saurin, and P. Wachs, A systematic literature review of resilience engineering: Research areas and a research agenda proposal, vol. 141. Elsevier, 2015.
 J. Bergström, R. Van Winsen, and E. Henriqson, “On the rationale of resilience in the domain of safety: A literature review,” Reliab. Eng. Syst. Saf., vol. 141, pp. 131–141, 2015.
 T. Aven, “Risk assessment and risk management: Review of recent advances on their foundation,” Eur. J. Oper. Res., vol. 253, no. 1, pp. 1–13, 2015.
 V. De Florio, “On Resilient Behaviors in Computational Systems and Environments,” J. Reliab. Intell. Environ., pp. 33–46, 2015.
 G. C. Gallopín, “Linkages between vulnerability, resilience, and adaptive capacity,” Glob. Environ. Chang., vol. 16, no. 3, pp. 293–303, 2006.
 U. Rafi, A. Mirakhor, and H. Askari, “Radical uncertainty , non-predictability , antifragility and risk-sharing Islamic finance,” PSL Quartely Rev., vol. 69, no. 279, pp. 337–372, 2016.
 P. Gai, A. Haldane, and S. Kapadia, “Complexity, concentration and contagion,” J. Monet. Econ., vol. 58, no. 5, pp. 453–470, 2011.
 D. Kennon, C. S. L. Schutte, and E. Lutters, “An alternative view to assessing antifragility in an organisation: A case study in a manufacturing SME,” CIRP Ann. - Manuf. Technol., vol. 64, no. 1, pp. 177–180, 2015.
 N. N. Taleb, “A Map and Simple Heuristic to Detect Fragility, Antifragility, and Model Error,” SSRN Electron. J., pp. 1–15, 2011.
 G. Gigerenzer and H. Brighton, “Homo Heuristicus: Why Biased Minds Make Better Inferences,” Top. Cogn. Sci., vol. 1, no. 1, pp. 107–143, 2009.
 F. Artinger, M. Petersen, G. Gigerenzer, and J. Weibler, “Heuristics as adaptive decision strategies in management,” J. Organ. Bahevior, vol. 36, no. S1, 2014.
 D. S. Passos, H. Coelho, and F. M. Sarti, “From Resilience to the Design of Antifragility,” in PESARO 2018: The Eight International Conference on Performance, Safety and Robustness in Complex Systems and Applications, 2018, pp. 7–11.
 V. De Florio, “Antifragility = Elasticity + Resilience + Machine learning: Models and algorithms for open system fidelity,” Procedia Comput. Sci., vol. 32, no. Antifragile, pp. 834–841, 2014.
 J. Kephart and D. Chess, “The Vision of Autonomic Computing,” IEEE Comput., vol. 36, no. 1, pp. 41–50, 2003.
 E. Verhulsta, “Applying systems and safety engineering principles for antifragility,” Procedia Comput. Sci., vol. 32, no. Antifragile, pp. 842–849, 2014.
 S. Jackson and T. L. J. Ferris, “Resilience Principles for Engineered Systems,” Syst. Eng., vol. 16, no. 2, pp. 152–164, 2013.