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EFFICIENT ESTIMATION OF MARKOV-SWITCHING MODEL WITH APPLICATION IN STOCK PRICE CLASSIFICATION | ||
Journal of Mathematics and Modeling in Finance | ||
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 07 دی 1400 | ||
نوع مقاله: Original Article | ||
شناسه دیجیتال (DOI): 10.22054/jmmf.2021.64976.1042 | ||
نویسندگان | ||
Farshid Mehrdoust ![]() | ||
1Department of Applied Mathematics, Faculty of Mathematical Science, University of Guilan | ||
2University of Guilan | ||
چکیده | ||
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. | ||
کلیدواژهها | ||
Regime-switching model؛ Estimation of Parameter؛ Expectation-maximization algorithm؛ Classification | ||
آمار تعداد مشاهده مقاله: 90 |