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The Role of Financial Spinning, Learning, and Predation in Market Failure

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Abstract

This paper examines the possibility that market failures may be explained by predatory information flows between sellers and buyers when they act in dysfunctional relationships characterized by predator–prey dynamics and a behavioral pattern we define as “financial spinning.” The Global Financial Crisis serves as an example, among many others. It involved predatory mortgages and heavy securitization, and illustrates the fact that some sellers of toxic products (individuals and corporations) may have strong incentives to get buyers-prey to become disconnected from their financial needs, goals, and preferences, while accumulating debt. This may happen even in the context of a knowledge economy, and may lead the market towards failure. Computer-driven trajectory exploration based on learning-factored Lotka-Volterra equations shows that the predatory, noxious information is beneficial to sellers-predators but only up to a point. Consumers, for their part, are not always willing or able to receive sufficient information, which would otherwise allow them to protect themselves. Our approach may also guide corporations’ efforts towards improving their customer relationships, social image, and community participation. We contribute to the use of Lotka-Volterra equations and trajectory exploration in the context of predatory asymmetry of information at the interpersonal, sellers-buyers level, of spinning and of market failure.

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Notes

  1. Appendix 1 provides the main economic models attempting to explain/understand market failure by various scholars with their shortfalls.

  2. Indeed, the expression “burden” is mostly used in a legal context, such as “burden of proof,” or in an accounting framework. We use the term burden to assign the weight of responsibility that some consumers bear when acting as consumers. This is exemplified, for example, in the context of bio-responsible purchasing or when dealing with the burden of taxes (Cunningham, 2002).

  3. CAPM: Capital Asset Pricing Model, used extensively to approximate the expected rate of return of an asset (Levy, 2010).

  4. The absence of substitutes and of geographical expansion renders the debt trap consumers-prey fall in that much more lethal.

  5. This applies to all predators (active and inactive) and all prey (real and potential).

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Authors and Affiliations

  1. ICN Business School, 86 rue du Sergent Blandan, 70148, 54003, Nancy Cedex, CS, France

    Olivier Mesly, Hareesh Mavoori & Nicolas Huck

  2. University of Lorraine- CEREFIGE, Nancy, France

    Olivier Mesly, Hareesh Mavoori & Nicolas Huck

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  1. Olivier Mesly
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Appendices

Appendix 1. Main economic models attempting to explain/understand market failures

Model

Scholarly authors

Year

Shortfall

SRISK

Engle & Ruan

2019

The behavioral aspects of market agents largely ignored

Global financial cycle

Habib & Venditti, European Central Bank

2019

Discuss risk aversion, but not speculation

Predatory dynamics

Huck et al

2019

No discussion on spinning

Animal Spirits

Akerlof & Shiller

2016

Do not anchor opportunistic behaviors in a larger frame that includes business cycles

Macroeconomic model

Brunnermeier & Sannikov

2014

Discuss volatility, but not moral hazards generated by market agents

Financial accelerator and the role of the Federal Reserve

Bernanke

2013

Does not explain the mathematical link between consumers and suppliers’ behaviors

Liquidity spiral

Brunnermeier & Oehmke

2012

Do not address in-depth how toxic products infect markets

Bubbles and crashes

Abreu & Brunnermeier

2003

Address rationality but not moral hazard

Opportunism and contract theory

Williamson

1981

Opposes trust to opportunistic behaviors in contractual agreements without reference to business cycles

Credit cycles

Kiyotaki & Moore

1997

Do not link impatience to speculation

Appendix 2. List of parameters used in the spinning model

Trajectory

1

2

3

4

5

 

Stable oscillations

Spiral/Convergence

Learning, Prey + , oscillations

Learning, Pred + , oscillations

Spiral + Predator learning

Learning

No

No

Yes

Yes

Yes

S

0

0

-1

1

1

Α

0.02

0.20

0.02

0.03

0.50

Β

0.003

0.010

0.003

0.003

0.020

ϒ

0.03

0.08

0.05

0.05

0.20

δ (or δ0 if learning)

0.0010

0.0010

0.0015

0.0015

0.0010

L

0.000000

0.000000

0.000001

0.000400

0.005000

Nb Prey (initial)

50

100

19

50

100

Nb Pred (initial)

10

10

5

10

10

Nb periods

1000

1000

950

810

1000

Time step

0.100

2.000

0.001

0.010

1.000

Number of points

10000

500

950000

81000

1000

  1. Nb number, pred predators

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Mesly, O., Mavoori, H. & Huck, N. The Role of Financial Spinning, Learning, and Predation in Market Failure. J Knowl Econ 14, 517–543 (2023). https://doi.org/10.1007/s13132-021-00862-2

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