اخبار و اعلانات
آمار
| تعداد نشریات | 61 |
| تعداد شمارهها | 2,201 |
| تعداد مقالات | 17,941 |
| تعداد مشاهده مقاله | 55,027,321 |
| تعداد دریافت فایل اصل مقاله | 28,800,232 |
Efficient estimation of Markov-switching model with application in stock price classification | ||
| Journal of Mathematics and Modeling in Finance | ||
| دوره 1، شماره 2، اسفند 2021، صفحه 97-112 اصل مقاله (282.04 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22054/jmmf.2021.13843 | ||
| نویسندگان | ||
| Farshid Mehrdoust* 1؛ Idin Noorani2؛ Mahdi Khavari2 | ||
| 1Department of Applied Mathematics, Faculty of Mathematical Sciences, University Guilan, Rasht, Iran | ||
| 2Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran | ||
| 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 | ||
| مراجع | ||
|
[1] C. Alexander, L. M. Nogueira, Hedging with stochastic local volatility, 2004. [2] M. Avellaneda, A. Levy, and A. Paras, Pricing and hedging derivative securities in markets with uncertain volatilities, Applied Mathematical Finance, 2 (1995), pp. 73-88. [3] M. Avellaneda, R. Buff, Combinatorial implications of nonlinear uncertain volatility models: the case of barrier options, Applied Mathematical Finance, 6 (1999), pp. 1-18. [4] T. Davig, Regime-switching debt and taxation, Journal of Monetary Economics, 51 (2004), pp. 837-859. [5] A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society: Series B (Methodological), 39 (1977), pp. 1-22. [6] E. Derman, I. Kani, The volatility smile and its implied tree, Goldman Sachs Quantitative Strategies Research Notes, 2 (1994), pp. 45-60. [7] B. Dumas, J. Fleming, and R. E. Whaley, Implied volatility functions: Empirical tests, The Journal of Finance, 53 (1998), pp. 2059-2106. [8] B. Dupire, Pricing with a smile, Risk, 7 (1994), pp. 18-20. [9] R. J. Elliott, L. Aggoun, and J. B. Moore, Hidden Markov models: estimation and control, Springer Science & Business Media, 2008. [10] B. Engelmann, M. R. Fengler, M. Nalholm, and P. Schwendner, Static versus dynamic hedges: an empirical comparison for barrier options, Review of Derivatives Research, 9 (2006), pp. 239-264. [11] S. Fallah, F. Mehrdoust, American option pricing under double Heston stochastic volatility model: simulation and strong convergence analysis, Journal of Statistical Computation and Simulation, 89 (2019), pp. 1322-1339. [12] S. Fallah, F. Mehrdoust, On the existence and uniqueness of the solution to the double Heston model equation and valuing Lookback option, Journal of Computational and Applied Mathematics, 350 (2019), pp. 412-422. [13] S. Fallah, F. Mehrdoust, CEV model equipped with the long-memory, Journal of Computational and Applied Mathematics, 389 (2021), pp. 113359. [14] G. A. Fink, Markov models for pattern recognition: from theory to applications, Springer Science & Business Media, 2014. [15] S. Goutte, A. Ismail, and H. Pham, Regime-switching stochastic volatility model: estimation and calibration to VIX options, Applied Mathematical Finance, 24 (2017), pp. 38-75. [16] P. S. Hagan, D. Kumar, A. S. Lesniewski, and D. E. Woodward, Managing smile risk, The Best of Wilmott, 1 (2002), pp. 249-296. [17] M. Hahn, S. Fruhwirth-Schnatter, and J. Sass, Estimating models based on Markov jump processes given fragmented observation series, AStA Advances in Statistical Analysis, 93 (2009), pp. 403-425. [18] J. D. Hamilton, Analysis of time series subject to changes in regime, Journal of Econometrics, 45 (1990), PP. 39-70. [19] J. D. Hamilton, Regime switching models. In Macroeconometrics and time series analysis, Palgrave Macmillan, London, 2010. [20] C. J. Kim, Dynamic linear models with Markov-switching, Journal of Econometrics, 60 (1994), pp. 1-22. [21] Q. Luo, X. Mao, Stochastic population dynamics under regime switching Journal of Mathematical Analysis and applications, 334 (2007), pp. 69-84. [22] F. Mehrdoust, I. Noorani, Forward price and tting of electricity Nord Pool market under regime-switching two-factor model, Mathematics and Financial Economics, (2021), pp. 1-43. | ||
|
آمار تعداد مشاهده مقاله: 731 تعداد دریافت فایل اصل مقاله: 812 |
||
Scholarly Journals Management System © 1991.05.01 by Allameh Tabatabaei University is
licensed under Attribution-NonCommercial 4.0 International.