Efficient estimation of Markov-switching model with application in stock price classification
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JMMF-1-2_008
تاریخ نمایه سازی: 18 بهمن 1400
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.
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Authors
Farshid Mehrdoust
Department of Applied Mathematics, Faculty of Mathematical Sciences, University Guilan, Rasht, Iran
Idin Noorani
Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
Mahdi Khavari
Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran