IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v89y2024ipbp159-171.html
   My bibliography  Save this article

Uncertainty measure: As a proxy for the degree of market imperfection

Author

Listed:
  • Zhang, Hailiang
  • Sattar, Muhammad Atif
  • Wang, Haijun

Abstract

This study makes a significant contribution to the existing literature on the concept of the “degree of imperfection between markets” and its evaluation model, which was originally developed by Wang and Hsu in 2004. By further expanding upon this foundational framework, Hsu (2010) established that the degree of imperfection between markets also applies within a market and can be operationalized in option markets. With these insights as a basis, this study formulates hypotheses to examine the relationship between the degree of imperfection and three key variables: the absolute error (AE) of call prices, the absolute error (AE) of implied volatility, and uncertainty. The empirical results of the hypothesis reveal a positive association between the degree of imperfection and the AE of call price, AE of implied volatility, and uncertainty. Moreover, the Study introduces Shannon entropy as a measure of uncertainty, and establishes uncertainty as a viable proxy for quantifying the degree of imperfection.

Suggested Citation

  • Zhang, Hailiang & Sattar, Muhammad Atif & Wang, Haijun, 2024. "Uncertainty measure: As a proxy for the degree of market imperfection," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 159-171.
  • Handle: RePEc:eee:reveco:v:89:y:2024:i:pb:p:159-171
    DOI: 10.1016/j.iref.2023.09.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056023003684
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2023.09.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Saurabh Mishra & Bilal M. Ayyub, 2019. "Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2160-2181, October.
    2. repec:bla:jfinan:v:44:y:1989:i:5:p:1289-1311 is not listed on IDEAS
    3. Oksana MYKHAILOVSKA, 2014. "The Nature Of Entropy In Socio-Economic Systems," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 3(1), pages 1-9, January.
    4. Christoffersen, Peter & Jacobs, Kris, 2004. "The importance of the loss function in option valuation," Journal of Financial Economics, Elsevier, vol. 72(2), pages 291-318, May.
    5. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    6. Baltussen, Guido & van Bekkum, Sjoerd & van der Grient, Bart, 2018. "Unknown Unknowns: Uncertainty About Risk and Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(4), pages 1615-1651, August.
    7. Les Gulko, 1997. "Dart Boards And Asset Prices," Advances in Econometrics, in: Applying Maximum Entropy to Econometric Problems, pages 237-276, Emerald Group Publishing Limited.
    8. Janchung Wang & Hsinan Hsu, 2006. "Degree of market imperfection and the pricing of stock index futures," Applied Financial Economics, Taylor & Francis Journals, vol. 16(3), pages 245-258.
    9. Shternshis, Andrey & Mazzarisi, Piero & Marmi, Stefano, 2022. "Measuring market efficiency: The Shannon entropy of high-frequency financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    10. Yun Yin & Peter G. Moffatt, 2019. "Correcting the Bias in the Practitioner Black-Scholes Method," JRFM, MDPI, vol. 12(4), pages 1-12, September.
    11. Hsinan Hsu & Janchung Wang, 2004. "Price Expectation and the Pricing of Stock Index Futures," Review of Quantitative Finance and Accounting, Springer, vol. 23(2), pages 167-184, September.
    12. Philippatos, George C & Wilson, Charles J, 1974. "Information theory and risk in capital markets," Omega, Elsevier, vol. 2(4), pages 523-532, August.
    13. Janchung Wang, 2008. "Degree of market imperfections: evidence from four Asian index futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 18(15), pages 1233-1246.
    14. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    15. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    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. Lin, Xiaoqiang & Chen, Qiang & Tang, Zhenpeng, 2014. "Dynamic hedging strategy in incomplete market: Evidence from Shanghai fuel oil futures market," Economic Modelling, Elsevier, vol. 40(C), pages 81-90.
    2. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    3. Yongxin Yang & Yu Zheng & Timothy M. Hospedales, 2016. "Gated Neural Networks for Option Pricing: Rationality by Design," Papers 1609.07472, arXiv.org, revised Mar 2020.
    4. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    5. Tai‐Yong Roh & Alireza Tourani‐Rad & Yahua Xu & Yang Zhao, 2021. "Volatility‐of‐volatility risk in the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 245-265, February.
    6. Dennis Bams & Thorsten Lehnert & Christian C. P. Wolff, 2009. "Loss Functions in Option Valuation: A Framework for Selection," Management Science, INFORMS, vol. 55(5), pages 853-862, May.
    7. Antonio Cosma & Stefano Galluccio & Paola Pederzoli & O. Scaillet, 2012. "Valuing American Options Using Fast Recursive Projections," Swiss Finance Institute Research Paper Series 12-26, Swiss Finance Institute.
    8. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    9. Ying Chang & Yiming Wang & Sumei Zhang, 2021. "Option Pricing under Double Heston Jump-Diffusion Model with Approximative Fractional Stochastic Volatility," Mathematics, MDPI, vol. 9(2), pages 1-10, January.
    10. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Asset prices and “the devil(s) you know”," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 20-35.
    11. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2009. "Common Factors and Causality in the Dynamics of Implied Volatility Surfaces: Evidence from the FX OTC Market," The Journal of Economic Asymmetries, Elsevier, vol. 6(1), pages 49-74.
    12. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.
    13. Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk, 2017. "Which Option Pricing Model Is the Best? HF Data for Nikkei 225 Index Options," Central European Economic Journal, Sciendo, vol. 4(51), pages 18-39.
    14. Guidolin, Massimo & Wang, Kai, 2023. "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    15. Vipul Kumar Singh, 2013. "Effectiveness of volatility models in option pricing: evidence from recent financial upheavals," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 10(3), pages 352-375, October.
    16. Daniele Angelini & Matthieu Garcin, 2024. "Market information of the fractional stochastic regularity model," Papers 2409.07159, arXiv.org.
    17. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
    18. Janis Bauer & Holger Fink & Eva Stoller, 2020. "Are Issuer Margins Fairly Stated? Evidence from the Issuer Estimated Value for Retail Structured Products," Forecasting, MDPI, vol. 2(4), pages 1-23, September.
    19. Jarrow, Robert & Kwok, Simon Sai Man, 2015. "Specification tests of calibrated option pricing models," Journal of Econometrics, Elsevier, vol. 189(2), pages 397-414.
    20. DeLisle, R. Jared & Diavatopoulos, Dean & Fodor, Andy & Kassa, Haimanot, 2022. "Variation in option implied volatility spread and future stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 152-160.

    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:eee:reveco:v:89:y:2024:i:pb:p:159-171. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    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.