Document Type : Research Article
Authors
- Farshid Mehrdoust ^{} ^{1}
- Idin Noorani ^{2}
- Mahdi Khavari ^{2}
^{1} Department of Applied Mathematics, Faculty of Mathematical Sciences, University Guilan, Rasht, Iran
^{2} Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
Abstract
In this paper, we discuss the calibration of the geometric Brownian motion model equipped with Markov-switching factor. Since the motivation for this research comes from a recent stream of literature in stock economics, we propose an efficient estimation method to sample a series of stock prices based on the expectation-maximization algorithm. We also implement an empirical application to evaluate the performance of the suggested model. Numerical results through the classification of the data set show that the proposed Markov-switching model fits the actual stock prices and reflects the main stylized facts of market dynamics. Since the motivation for this research comes from a recent stream of literature in stock economics, we propose an efficient estimation method to sample a series of stock prices based on the expectation-maximization algorithm. Numerical results through the classification of the data set show that the proposed Markov-switching model fits the actual stock prices and reflects the main stylized facts of market dynamics. Since the motivation for this research comes from a recent stream of literature in stock economics, we propose an efficient estimation method to sample a series of stock prices based on the expectation-maximization algorithm.
Keywords
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