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

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 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

https://robotenomics.com/


Background


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.


FRB cycle


Our approach


Start simple

“In building a model, start simple.”

(Mandelbrot & Hudson, 2004)


Paraphrasing...

In understanding a model, simulate it.


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!


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


An agent-based

computational model

for the FRB

D. Monett

FRB model overview

12Gdańsk, Poland, September 11 – 14, 2016

D. Monett

Deliberation: depositor


D. Monett

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


Experimental settings

and results(more: on the paper!)

D. Monett

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

D. Monett

FRB in NetLogo


D. Monett

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)


Further work

D. Monett

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?

D. Monett

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

http://www.psdgraphics.com/buttons/round-rating-buttons-psd/

[email protected]

monettdiaz

Contact:

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

Economy & Finance

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