Application of Generalized Geometric Bravoni Motion Model by Markov Switching Regime Process in Stock Price Simulation: System Dynamics Approach
Subject Areas : Financial engineering
Nahid
Malekiniya
1
(Department of accounting and management, Bilesavar branch, Islamic Azad University, Bilesavar, Iran)
Hosein
Asgari Alouj
2
(Department of accounting and management, Bilesavar branch, Islamic Azad University, Bilesavar, Iran)
zaher
sepehrian
3
(Department of applied mathematics, Bilesavar branch, Islamic Azad University, Bilesavar, Iran)
Keywords: Calibration, System dynamic, Drift, Geometrical Braunion Motion, Markov Switching regim,
Abstract :
Objective: In this study, the changes of the stock price of Iran Khodro Company listed in Tehran Stock Exchange (TSE) has been studied on the issue of prediction modeling during of 9/13/1387 to 13/12/1396 based on Geometric Brownian Motion (GBM) model generalized by the Markov switching regime (MSR).Methods: The research model was designed by system dynamics (SD) approach and Vensim DSS software in the causal- loop diagrams (CLD) firstly and then after specifying the flow-state variables, mono-loop and two-loop stock–flow diagrams (SFDs) was designed and daily final stock price was simulated. Two-parameter of noise seed and time step were identified and applied as sensitivity analysis parameters.Results: The simulation error was estimated for the random variations of the noise seed and the time step configured by default user parameters up to 22/74 and 30/35 percent, respectively. Both parameters were calibirated due to higher simulation error than acceptable error of 15 percent. Trial - error and field observation methods was performed in order to appropriate estimation of the calibration parameters range.The post-calibration accuracy of simulation per noise seed parameter increased from 77/26 to 91/5 percent and per time step from 69/65 to 96/37 percent.Conclusion: Findings indicate that the error roots have reached to the ideal mode by optimizing of the calibration parameters as covariance inequality error approached to one unit and base inequality error and variance inequality error approached to zero and indicate functionality accuracy of the GBM generalized by the MSR in stock price simulation.
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