Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo [Slides]
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The document presents a talk on simulating the fractional reserve banking system using agent-based modeling with NetLogo, focusing on enhancing understanding through simulations and graphics. It explores the dynamics of the banking system, identifying conditions leading to bank insolvency and emphasizing the importance of depositor confidence. The findings reveal that decreased confidence and low reserves significantly increase the likelihood of bank failures.
Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo [Slides]
- 1. Simulating the Fractional Reserve Banking using Agent- based Modelling with NetLogo Talk at the 10th International Workshop on Multi-Agent Systems and Simulation, MAS&S 2016 Prof. Dr. Dagmar Monett Dr. Jesús Emeterio Navarro-Barrientos
- 2. D. Monett 2Gdańsk, Poland, September 11 – 14, 2016 Finance is a black box “If the physical world is so uncertain, so difficult to know precisely, then how much more uncertain and unknowable must be the world of money? Finance is a black box covered by a veil.” Mandelbrot, Benoit, and Hudson, Richard L. (2004) The (mis)Behavior of Markets: A Fractal View of Risk, Ruin, and Reward. New York, NY: Basic Books. Mandelbrot‘s work via C. Lewis
- 3. D. Monett 3Gdańsk, Poland, September 11 – 14, 2016 Background
- 4. D. Monett 4Gdańsk, Poland, September 11 – 14, 2016 FRB … “in which banks hold only a fraction of their deposits in reserves, so that the reserve- deposit ratio is less than 1” (Abel & Bernanke, 2005) The fractional reserve banking is a banking system... The bank invests or loans the rest of the deposits.
- 5. D. Monett 5Gdańsk, Poland, September 11 – 14, 2016 FRB cycle
- 6. D. Monett 6Gdańsk, Poland, September 11 – 14, 2016 Our approach
- 7. D. Monett 7Gdańsk, Poland, September 11 – 14, 2016 Start simple “In building a model, start simple.” (Mandelbrot & Hudson, 2004)
- 8. D. Monett 8Gdańsk, Poland, September 11 – 14, 2016 Paraphrasing... In understanding a model, simulate it.
- 9. D. Monett 9Gdańsk, Poland, September 11 – 14, 2016 Our work ■ No “big” economics insights there... ■ ...but a simple agent-based computational model ■ ...that uses NetLogo ■ ...to focus on the dynamics of the fractional reserve banking system ■ ...to ease its understanding through simulations and graphical tools!
- 10. D. Monett 10Gdańsk, Poland, September 11 – 14, 2016 Why? ■ To anticipate economic scenarios that could eventually be avoided ■ To provide artificial ways to represent and to simulate the impact of the FRB system ■ To provide a basic playground setting for doing it ■ To drive the policies and behaviours of banks before testing their validity in the real world ■ To find out the sufficient conditions for a banking system to become fragile and unstable
- 11. D. Monett 11Gdańsk, Poland, September 11 – 14, 2016 An agent-based computational model for the FRB
- 12. D. Monett FRB model overview 12Gdańsk, Poland, September 11 – 14, 2016
- 13. D. Monett Deliberation: depositor 13Gdańsk, Poland, September 11 – 14, 2016
- 14. D. Monett Deliberation: depositor 14Gdańsk, Poland, September 11 – 14, 2016 t : trust in the bank C : current capital D : amount to deposit S : current deposit : deposit interest rate W : amount to withdraw p : time preference
- 15. D. Monett 15Gdańsk, Poland, September 11 – 14, 2016 Experimental settings and results (more: on the paper!)
- 16. D. Monett Experiments 16Gdańsk, Poland, September 11 – 14, 2016 We are interested in finding which parameter values lead to either bank insolvency or to a stationary scenario with no insolvency of the bank, over iterations ■ 1 bank and fixed no. of depositors/debtors ■ E.g. of parameters: ■ loan (credit) interest, start capital, confidence win/loss rates, minimum reserve rate, deposit interest, among others
- 17. D. Monett FRB in NetLogo 17Gdańsk, Poland, September 11 – 14, 2016
- 18. D. Monett Some results 18Gdańsk, Poland, September 11 – 14, 2016 ■ avg loss of confidence > avg win of confidence ■ depositors & debtors lose their trust in the bank ■ Insolvency of the bank more probable: ■ when loss of confidence increases ■ when reserves are low ■ when depositors & debtors lose their trust ■ when depositors start to withdraw deposits (just one single depositor could be enough for starting a cascade)
- 19. D. Monett 19Gdańsk, Poland, September 11 – 14, 2016 Further work
- 20. D. Monett Further work 20Gdańsk, Poland, September 11 – 14, 2016 To consider/study… ■ different trust reputation mechanisms ■ whether the dynamics of the model scale in size or not ■ impact of excluding external sources that would help a bank to pay to the depositors and keep it solvent ■ money needed on average to help a bank avoid insolvency? average lifetime of banks?
- 21. D. Monett Sources 21Gdańsk, Poland, September 11 – 14, 2016 Related work: - See references list on our paper! ■ https://www.researchgate.net/publication/304244558_Simu lating_the_Fractional_Reserve_Banking_using_Agent- based_Modelling_with_NetLogo