IDEAS home Printed from https://ideas.repec.org/a/taf/jbemgt/v16y2015i4p786-807.html
   My bibliography  Save this article

Complex Model of Market Price Development and its Simulation

Author

Listed:
  • Bohumil Stádník
  • Algita Miečinskienė

Abstract

The purpose of this study is to suggest a complex model of market price development for liquid assets, which is able to simulate all of the main features particular to the real price development and has a realistic financial explanation. First, the paper defines assumptions for the model construction from empirically observed processes. Then, the model is implemented in the real simulation environment. Finally, the ability of the model is checked to simulate empirically observed features, e.g. leptokurtic characteristics or skewness of the price distribution. Also, this paper newly defines and implements the resonance effect. FFT analysis is used to support oscillation processes. Finally, selected markets are provided with parameter optimisation of the model based on empirical observations. It was found that the model built under the previously mentioned assumptions was able to explain empirically observed effects that reversely support the correctness of those assumptions. The practical value of the constructed model can be found in many areas, including risk management and asset valuation.

Suggested Citation

  • Bohumil Stádník & Algita Miečinskienė, 2015. "Complex Model of Market Price Development and its Simulation," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(4), pages 786-807, August.
    • Handle: RePEc:taf:jbemgt:v:16:y:2015:i:4:p:786-807
    DOI: 10.3846/16111699.2015.1076028
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.3846/16111699.2015.1076028
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.3846/16111699.2015.1076028?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. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    2. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    3. Alexander Franck & Andreas Walter & Johannes Witt, 2013. "Momentum strategies of German mutual funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(3), pages 307-332, September.
    4. Jiří Witzany, 2009. "Valuation of Convexity Related Interest Rate Derivatives," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(4), pages 309-326.
    5. James Primbs & Muruhan Rathinam, 2009. "Trader Behavior and its Effect on Asset Price Dynamics," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(2), pages 151-181.
    6. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    7. Alexandre Roch, 2011. "Liquidity risk, price impacts and the replication problem," Finance and Stochastics, Springer, vol. 15(3), pages 399-419, September.
    8. Jiří Witzany, 2013. "Estimating Correlated Jumps and Stochastic Volatilities," Prague Economic Papers, Prague University of Economics and Business, vol. 2013(2), pages 251-283.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Jennifer Huang & Jiang Wang, 2009. "Liquidity and Market Crashes," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2407-2443, July.
    11. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    12. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    13. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    14. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    15. Anatolyev, Stanislav & Gerko, Alexander, 2005. "A Trading Approach to Testing for Predictability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 455-461, October.
    16. David Rey & Markus Schmid, 2007. "Feasible momentum strategies: Evidence from the Swiss stock market," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 21(3), pages 325-352, September.
    17. Chan, Louis K C & Jegadeesh, Narasimhan & Lakonishok, Josef, 1996. "Momentum Strategies," Journal of Finance, American Finance Association, vol. 51(5), pages 1681-1713, December.
    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. Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.
    2. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    3. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Barnett, William A. & Serletis, Apostolos & Serletis, Demitre, 2015. "Nonlinear And Complex Dynamics In Economics," Macroeconomic Dynamics, Cambridge University Press, vol. 19(8), pages 1749-1779, December.
    5. Razvan Stefanescu & Ramona Dumitriu, 2016. "Contrarian and Momentum Profits during Periods of High Trading Volume preceded by Stock Prices Shocks," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 378-384.
    6. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    7. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    8. García Ruiz Reyna Susana & Cruz Aké Salvador & Venegas Martínez Francisco, 2014. "Una medida de eficiencia de mercado: Un enfoque de teoría de la información," Contaduría y Administración, Accounting and Management, vol. 59(4), pages 137-166, octubre-d.
    9. Alagidede, Paul, 2011. "Return behaviour in Africa's emerging equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 133-140, May.
    10. Bekiros, Stelios D., 2010. "Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets," European Journal of Operational Research, Elsevier, vol. 202(1), pages 285-293, April.
    11. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    12. Dutta, Shantanu & Essaddam, Naceur & Kumar, Vinod & Saadi, Samir, 2017. "How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 867-877.
    13. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.
    14. Ioannis D Vrontos & Loukia Meligkotsidou & Spyridon D Vrontos, 2011. "Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 292-307, September.
    15. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    16. Rashid, Abdul, 2007. "Stock prices and trading volume: An assessment for linear and nonlinear Granger causality," Journal of Asian Economics, Elsevier, vol. 18(4), pages 595-612, August.
    17. Ana Isabel Bezerra Cavalcanti, 2003. "Instabilidade e Não-Linearidades nos Mercados Financeiros," Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31st Brazilian Economics Meeting] c52, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    18. Remes, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports 62, VATT Institute for Economic Research.
    19. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    20. Subrata ROY, 2021. "Volatility Forecasting, Market Efficiency and Effect of Recession of SRI Indices," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(627), S), pages 259-284, Summer.

    More about this item

    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:taf:jbemgt:v:16:y:2015:i:4:p:786-807. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TBEM20 .

    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.