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Finance and the Quantum Mechanical Formalism

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Beyond Traditional Probabilistic Methods in Economics (ECONVN 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 809))

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Abstract

This contribution tries to sketch how we may want to embed formalisms from the exact sciences (more precisely physics) into social science. We begin to answer why such an endeavour may be necessary. We then consider more specifically how some formalisms of quantum mechanics can aid in possibly extending some finance formalisms.

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Notes

  1. 1.

    A society is an example of a system; cell re-generation is another example of a system etc.

  2. 2.

    It is not totally ‘besides’ though...

  3. 3.

    Note that in the sequel h will be set to one. In physics this constant is essential to have the left and right hand sides of the Schrödinger partial differential equation to have units which agree.

  4. 4.

    This is one way to look at this equation. There are other ways.

  5. 5.

    Not to be confused with the so called Lagrangian!.

  6. 6.

    Contrary to the idea of energy conservation we mentioned above, potential energy need not be conserved.

  7. 7.

    Yes: physics is replete with differential equations (see our discussion above).

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Author information

Authors and Affiliations

  1. Memorial University, St. John’s, Canada

    Emmanuel Haven

  2. IQSCS, Leicester, UK

    Emmanuel Haven

Authors
  1. Emmanuel Haven
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Corresponding author

Correspondence to Emmanuel Haven .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

  3. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Duc Trung

  4. TTC Group, Ho Chi Minh City, Vietnam

    Dang Van Thanh

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Haven, E. (2019). Finance and the Quantum Mechanical Formalism. In: Kreinovich, V., Thach, N., Trung, N., Van Thanh, D. (eds) Beyond Traditional Probabilistic Methods in Economics. ECONVN 2019. Studies in Computational Intelligence, vol 809. Springer, Cham. https://doi.org/10.1007/978-3-030-04200-4_4

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