IDEAS home Printed from https://ideas.repec.org/p/zbw/ifwedp/201920.html
   My bibliography  Save this paper

A quantum framework for economic science: New directions

Author

Listed:
  • Patra, Sudip

Abstract

The current paper explores the cutting-edge applications of quantum field theory and quantum information theory modelling in different areas of economic science, namely, in the behavioural modelling of agents under market uncertainty, and mathematical modelling of asset or option prices and firm theory. The paper then provides a brief discussion into a possible extension of the extant literature of quantum-like modelling based on scattering theory and statistical field theory. A statistical theory of firm based on Feynman path integral technique is also proposed very recently. The collage of new initiatives as described in the current paper will hopefully ignite still newer ideas.

Suggested Citation

  • Patra, Sudip, 2019. "A quantum framework for economic science: New directions," Economics Discussion Papers 2019-20, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwedp:201920
    as

    Download full text from publisher

    File URL: http://www.economics-ejournal.org/economics/discussionpapers/2019-20
    Download Restriction: no
    File URL: https://www.econstor.eu/bitstream/10419/194872/1/1662969260.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2007. "Probabilities in Economic Modeling," PIER Working Paper Archive 07-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Khrennikova, Polina & Patra, Sudip, 2019. "Asset trading under non-classical ambiguity and heterogeneous beliefs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 562-577.
    4. Edward W. Piotrowski & Jan Sladkowski, "undated". "An Invitation to Quantum Game Theory," Departmental Working Papers 15, University of Bialtystok, Department of Theoretical Physics.
    5. Sudipto Bhattacharya, 1979. "Imperfect Information, Dividend Policy, and "The Bird in the Hand" Fallacy," Bell Journal of Economics, The RAND Corporation, vol. 10(1), pages 259-270, Spring.
    6. V. Yukalov & D. Sornette, 2011. "Decision theory with prospect interference and entanglement," Theory and Decision, Springer, vol. 70(3), pages 283-328, March.
    7. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    8. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    9. Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2007. "Probabilities in Economic Modeling," PIER Working Paper Archive 07-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Itzhak Gilboa, 2010. "Questions in Decision Theory," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 1-19, September.
    2. Stijn Claessens & M. Ayhan Kose, 2013. "Financial Crises: Explanations, Types and Implications," CAMA Working Papers 2013-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. John S. Strong & John R. Meyer, 1990. "Sustaining Investment, Discretionary Investment, and Valuation: A Residual Funds Study of the Paper Industry," NBER Chapters, in: Asymmetric Information, Corporate Finance, and Investment, pages 127-148, National Bureau of Economic Research, Inc.
    4. Steven D. Moffitt, 2018. "Why Markets are Inefficient: A Gambling "Theory" of Financial Markets For Practitioners and Theorists," Papers 1801.01948, arXiv.org.
    5. Aerts, Diederik & Geriente, Suzette & Moreira, Catarina & Sozzo, Sandro, 2018. "Testing ambiguity and Machina preferences within a quantum-theoretic framework for decision-making," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 176-185.
    6. Chen, Shenglan & Chou, Robin K. & Liu, Xiaoling & Wu, Yuhui, 2020. "Deregulation of short-selling constraints and cost of bank loans: Evidence from a quasi-natural experiment," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    7. Steffen Andersen & John Fountain & Glenn Harrison & E. Rutström, 2014. "Estimating subjective probabilities," Journal of Risk and Uncertainty, Springer, vol. 48(3), pages 207-229, June.
    8. repec:spo:wpecon:info:hdl:2441/eu4vqp9ompqllr09iepso50rh is not listed on IDEAS
    9. Thomas Boyer-Kassem & Sébastien Duchêne & Eric Guerci, 2016. "Quantum-like models cannot account for the conjunction fallacy," Theory and Decision, Springer, vol. 81(4), pages 479-510, November.
    10. Fakhrul Hasan & Umar Nawaz Kayani & Tonmoy Choudhury, 2023. "Behavioral Risk Preferences and Dividend Changes: Exploring the Linkages with Prospect Theory Through Empirical Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 517-535, December.
    11. Godfrey Cadogan, 2012. "Representation theory for risk on markowitz-tversky-kahneman topology," Economics Bulletin, AccessEcon, vol. 32(4), pages 1-34.
    12. Hsin, Chin-Wen & Peng, Shu-Cing, 2023. "Investor propensity to speculate and price delay in emerging markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    13. Bernstein, J.I. & Nadiri, M.I., 1993. "Production, Financial Structure and Productivity Growth in U.S. Manufacturing," Working Papers 93-10, C.V. Starr Center for Applied Economics, New York University.
    14. Steven M. Fazzari & R. Glenn Hubbard & Bruce C. Petersen, 1988. "Financing Constraints and Corporate Investment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 141-206.
    15. Ulrike Malmendier, 2018. "Behavioral Corporate Finance," NBER Working Papers 25162, National Bureau of Economic Research, Inc.
    16. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    17. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09iepso50rh is not listed on IDEAS
    18. Korinek, Anton & Stiglitz, Joseph E., 2009. "Dividend taxation and intertemporal tax arbitrage," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 142-159, February.
    19. Mohrschladt, Hannes & Schneider, Judith C., 2021. "Option-implied skewness: Insights from ITM-options," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    20. Oxoby, Robert J., 2014. "Social inference and occupational choice: Type-based beliefs in a Bayesian model of class formation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 51(C), pages 30-37.
    21. Jeffrey K. MacKie-Mason, 1990. "Do Firms Care Who Provides Their Financing?," NBER Chapters, in: Asymmetric Information, Corporate Finance, and Investment, pages 63-104, National Bureau of Economic Research, Inc.
    22. Thakor, Anjan V. & Callaway, Richard, 1983. "Costly Information Production Equilibria in the Bank Credit Market with Applications to Credit Rationing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 18(2), pages 229-256, June.

    More about this item

    Keywords

    quantum like modelling; contextuality; QFT (quantum field theory); self-adjoint operators; uncertainty; epistemic; ontic;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:ifwedp:201920. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.