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Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo [Slides]

Presentation · September 2016

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1 author: 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 Dagmar Monett Hochschule für Wirtschaft und Recht Berlin

All content following this page was uploaded by Dagmar Monett on 12 September 2016.

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

• D. Monett

2 Gdańsk, 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

• D. Monett

3 Gdańsk, Poland, September 11 – 14, 2016

Background

• D. Monett

4 Gdańsk, 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.

• D. Monett

5 Gdańsk, Poland, September 11 – 14, 2016

FRB cycle

• D. Monett

6 Gdańsk, Poland, September 11 – 14, 2016

Our approach

• D. Monett

7 Gdańsk, Poland, September 11 – 14, 2016

Start simple

“In building a model, start simple.”

(Mandelbrot & Hudson, 2004)

• D. Monett

8 Gdańsk, Poland, September 11 – 14, 2016

Paraphrasing...

In understanding a model, simulate it.

• D. Monett

9 Gdańsk, 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!

• D. Monett

10 Gdańsk, 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

• D. Monett

11 Gdańsk, Poland, September 11 – 14, 2016

An agent-based computational model for the FRB

• D. Monett

FRB model overview

12 Gdańsk, Poland, September 11 – 14, 2016

• D. Monett

Deliberation: depositor

13 Gdańsk, Poland, September 11 – 14, 2016

• D. Monett

Deliberation: depositor

14 Gdańsk, 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

• D. Monett

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Experimental settings and results

(more: on the paper!)

• D. Monett

Experiments

16 Gdańsk, 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

• D. Monett

FRB in NetLogo

17 Gdańsk, Poland, September 11 – 14, 2016

• D. Monett

Some results

18 Gdańsk, 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

• ne single depositor could be enough for starting

a cascade)

• D. Monett

19 Gdańsk, Poland, September 11 – 14, 2016

Further work

• D. Monett

Further work

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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?

• D. Monett

Sources

21 Gdańsk, 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

dagmar@monettdiaz.com monettdiaz

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