Slides of the talk at the 10th International Workshop on Multi-Agent Systems and Simulation, MAS&S 2016, Gdansk, Poland, 11-14 Sept. 2016

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: