Simulating the Fractional Reserve Banking using Agent-based - PDF document

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/308019713 Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo [Slides] Presentation · September 2016 DOI: 10.13140/RG.2.2.14110.74567 CITATIONS READS 0 34 1 author: Dagmar Monett Hochschule für Wirtschaft und Recht Berlin 71 PUBLICATIONS 134 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Research on Excellent Teaching (RET) View project Predicting Star Ratings based on Annotated Reviews of Mobile Apps View project All content following this page was uploaded by Dagmar Monett on 12 September 2016. The user has requested enhancement of the downloaded file.

Simulating the Fractional Reserve Banking using Agent- based Modelling with NetLogo Prof. Dr. Dagmar Monett Dr. Jesús Emeterio Navarro-Barrientos Talk at the 10th International Workshop on Multi-Agent Systems and Simulation, MAS&S 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 Gdańsk, Poland, September 11 – 14, 2016 D. Monett 2

Background Gdańsk, Poland, September 11 – 14, 2016 D. Monett 3

FRB The fractional reserve banking is a banking system... … “ 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 bank invests or loans the rest of the deposits. Gdańsk, Poland, September 11 – 14, 2016 D. Monett 4

FRB cycle Gdańsk, Poland, September 11 – 14, 2016 D. Monett 5

Our approach Gdańsk, Poland, September 11 – 14, 2016 D. Monett 6

Start simple “ In building a model, start simple. ” (Mandelbrot & Hudson, 2004) Gdańsk, Poland, September 11 – 14, 2016 D. Monett 7

Paraphrasing... In understanding a model, simulate it. Gdańsk, Poland, September 11 – 14, 2016 D. Monett 8

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! Gdańsk, Poland, September 11 – 14, 2016 D. Monett 9

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 Gdańsk, Poland, September 11 – 14, 2016 D. Monett 10

An agent-based computational model for the FRB Gdańsk, Poland, September 11 – 14, 2016 D. Monett 11

FRB model overview Gdańsk, Poland, September 11 – 14, 2016 D. Monett 12

Deliberation: depositor Gdańsk, Poland, September 11 – 14, 2016 D. Monett 13

Deliberation: depositor 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 Gdańsk, Poland, September 11 – 14, 2016 D. Monett 14

Experimental settings and results (more: on the paper!) Gdańsk, Poland, September 11 – 14, 2016 D. Monett 15

Experiments 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 Gdańsk, Poland, September 11 – 14, 2016 D. Monett 16

FRB in NetLogo Gdańsk, Poland, September 11 – 14, 2016 D. Monett 17

Some results ■ 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) Gdańsk, Poland, September 11 – 14, 2016 D. Monett 18

Further work Gdańsk, Poland, September 11 – 14, 2016 D. Monett 19

Further work 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? Gdańsk, Poland, September 11 – 14, 2016 D. Monett 20

Sources 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 Gdańsk, Poland, September 11 – 14, 2016 D. Monett 21

Contact: dagmar@monettdiaz.com monettdiaz View publication stats View publication stats