Providing a hybrid strategy based on the theory of turbulence and price acceleration in the Iranian stock market
الموضوعات :Rohollah Hamidi 1 , Ali Saeedi 2 , Mohammad Khodaei Valazaghard 3 , Mehdi Naghavi 4
1 - Department of Financial Management, North Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Associate Professor, Department of Management, North Tehran Branch, Islamic Azad University, Tehran, Iran.
3 - Department of Financial Management, Tehran North Branch, Islamic Azad University, Tehran, Iran
4 - Department of Financial Management, North Tehran Branch, Islamic Azad University, Tehran, Iran
الکلمات المفتاحية: price acceleration, Chaos theory, stock price, Forecast,
ملخص المقالة :
Stock prices are influenced by economic, technological, psychological and geopolitical factors. A review of the literature in this field shows that stochastic approaches, trend analysis and econometrics have been used to demonstrate stock market dynamics and price forecasting. However, these techniques cannot provide a comprehensive overview of market dynamics. Because they ignore the temporal relationship between these factors and are unable to understand their cumulative effects on prices. By integrating chaos theory and continuous data mining based on price acceleration, this study has eliminated these gaps by inventing a new price forecasting method called dynamic stock market recognition simulator and combining two methods: one is delay structures. Or gives time intervals to the data set, and the other is the method of selecting new variables for the market environment. The results showed that the method used can be used to predict the long-term stock price using a small data set with small dimensions.
References
[1] Ahmadkhanbeigi, S., Abdolvand, N., Stock Price Prediction Modeling Using Artificial Neural Network Approach and Imperialist Competitive Algorithm Based on Chaos Theory, Financial Management Strategy, 5(3): 27-73. doi: 10.22051/JFM.2017.14635.1319
[2] Azadi, M., Izadikhah, M., Ramezani, F., Hussain, F.K., A mixed ideal and anti-ideal DEA model: an application to evaluate cloud service providers, IMA Journal of Management Mathematics, 2020; 31(2): 233-256. doi: 10.1093/imaman/dpz012
[3] Boeing. G., Chaos Theory and the Logistic Map, Journal of the Optical Society of America B Optical Physics, 2015; 3(5):741.
[4] Boeing, G., Visual Analysis of Nonlinear Dynamical Systems, Chaos, Fractals, Self-Similarity and the Limits of Prediction. Systems. 2021; 4(4): 37.
[5] Fama, E. F., Fisher, L., Jensen, M. C., Roll, R., The adjustment of stock prices to new information, International economic review, 1969:10(1): 1-21. Doi: 10.2307/2525569
[6] Jianga, Z-Q., Xie, W-J., Zhou, W-X., Sornette, D, Multifractal analysis of financial markets, Research Center for Econophysics, East China University of Science and Technology, 2018, 82(12), P. 1-145.
[7] Jokar, H., Shamsaddini, K., Daneshi, V., Investigating the Effect of Investors' Behavior and Management on the Stock Returns: Evidence from Iran. Advances in Mathematical Finance and Applications, 2018; 3(3): 41-52.
doi: 10.22034/amfa.2018.544948
[8] Galacgac, J., Singh, A., Implications of Chaos Theory in Managment Science, Department of Civil and Environmental Engineering, University of Hawaii at Manoa, Chaotic Modeling and Simulation (CMSIM), 2016; 4: 515-527.
[9] Hsieh, D., Chaos and Nonlinear Dynamics: Application to Financial Markets, The Journal of Finance, 2018; 46(5): 1-15.
[10] Kaur, I., Effect of mutual funds characteristics on their performance and trading strategy: A dynamic panel approach, Vassilios Papavassiliou, University College Dublin, Ireland Cogent Economics & Finance, 2018; 6(1):1-17. Doi: 10.1080/23322039.2018.1493019
[11] Klioutchnikov, I., Sigova, M., Beizerov, N., Chaos Theory in Finance, 6th International Young Scientists Conference in HPC and Simulation, Kotka, Finland, 2017; 1-8.
[12] Meissner, G., Correlation Trading Strategies–Opportunities and Limitations, The Journal of Trading, 2021; 1-15. Doi: 10.3905/jot.2016.2016.1.050
[13] Moffitt, S.D., Why Markets Are Inefficient: A Gambling Theory of Financial Markets for Practitioners and Theorists, SSRN Electronic Journal, 2017; 1-31. doi: 10.2139/ssrn.2925532
[14] Litimi, H., BenSaïda, A., Belkacem, L., Abdallah, O., Chaotic behavior in financial market volatility, Journal of Risk, 2019; 21(3): 27-53. doi: 10.21314/JOR.2018.400
[15] Oprean, C., Theoretical and methodological proposals regarding the informational efficiency of Financial Markets, Lucian Blaga University, Sibiu, Romania Revista Economica, 2021; 67(6): 1-15.
[16] Poincaré, J. H., The three-body problem and the equations of dynamics: Poincaré's foundational work on dynamical systems theory, Popp, Bruce D. (Translator). Cham, Switzerland: Springer International Publishing, 2017.
[17] Parsa, B., Sarraf, F., Financial Statement Comparability and the Expected Crash Risk of Stock Prices, Advances in Mathematical Finance and Applications, 2018; 3(3):77-93. doi: 10.22034/amfa.2018.544951
[18] Poordavoodi, A., Moazami Goudarzi, M.R., Haj Seyyed Javadi, H., Rahmani, A.M., Izadikhah, M., Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs, Computer Modeling in Engineering & Sciences, 2020; 123(2): 525-570, doi: 10.32604/cmes.2020.08854
[19] Roostaee, R., Izadikhah, M., Hosseinzadeh Lotfi, F., An interactive procedure to solve multi-objective decision-making problem: an improvment to STEM method, Journal of Applied Mathematics, 2012; 324712: 1-18. doi: 10.1155/2012/324712
[20] Radovanov, B., Marcikic, A., Bootstrap testing of trading strategies in emerging balkan stock markets, University of Novi, Ekonomie a Management, 2017, 20(4), P. 103-119. doi: 10.15240/tul/001/2017-4-008
[21] Salehi, A., Mohammadi, S., Afshari, M., Impact of Institutional Ownership and Board Independence on the Relationship Between Excess Free Cash Flow and Earnings Management. Advances in Mathematical Finance and Applications, 2017, 2(3), P. 91-105. doi: 10.22034/amfa.2017.533104
[22] Tavana, M., Izadikhah, M., Farzipoor Saen, R., Zare, R., An integrated data envelopment analysis and life cycle assessment method for performance measurement in green construction management, Environ Sci Pollut Res, 2021, 28, P. 664–682. doi: 10.1007/s11356-020-10353-7
[23] Xu, M., Cryptanalysis of an Image Encryption Algorithm Based on DNA Sequence Operation and Hyper-Chaotic System, 3D Research, 2017, 8(15), doi: 10.1007/s13319-017-0126-y
[24] Zare, R., Izadikhah, M., Multi-criteria decision making methods for comparing three models of aluminum ingot production through life cycle assessment, Applied Ecology and Environmental Research, 2017, 15(3), P. 1697-1715, doi: 10.15666/aeer/1503_16971715
