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.

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

22. dagmar@monettdiaz.com
monettdiaz
Contact: