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Settar, Abdeljalil, Chegdal, Sara, Kabil, Mustapha, Benrhmach, Ghassane. (1404). Modeling log-volatility with zero returns: empirical evidence for asymmetric SV and log-GARCH models. فیزیولوژی و بیوتکنولوژی آبزیان, (), -. doi: 10.22124/jmm.2026.31979.2889
Abdeljalil Settar; Sara Chegdal; Mustapha Kabil; Ghassane Benrhmach. "Modeling log-volatility with zero returns: empirical evidence for asymmetric SV and log-GARCH models". فیزیولوژی و بیوتکنولوژی آبزیان, , , 1404, -. doi: 10.22124/jmm.2026.31979.2889
Settar, Abdeljalil, Chegdal, Sara, Kabil, Mustapha, Benrhmach, Ghassane. (1404). 'Modeling log-volatility with zero returns: empirical evidence for asymmetric SV and log-GARCH models', فیزیولوژی و بیوتکنولوژی آبزیان, (), pp. -. doi: 10.22124/jmm.2026.31979.2889
Settar, Abdeljalil, Chegdal, Sara, Kabil, Mustapha, Benrhmach, Ghassane. Modeling log-volatility with zero returns: empirical evidence for asymmetric SV and log-GARCH models. فیزیولوژی و بیوتکنولوژی آبزیان, 1404; (): -. doi: 10.22124/jmm.2026.31979.2889

Modeling log-volatility with zero returns: empirical evidence for asymmetric SV and log-GARCH models

Journal of Mathematical Modeling
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 11 بهمن 1404    اصل مقاله (1.07 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22124/jmm.2026.31979.2889
نویسندگان
Abdeljalil Settar* 1؛ Sara Chegdal1؛ Mustapha Kabil1؛ Ghassane Benrhmach2
1Laboratory of mathematics, computer science and applications (LMCSA), FST Mohammedia, Hassan II university, 20650 Casablanca, Morocco
2Department of Mathematics and Statistics, College of Engineering, Abu Dhabi University, 59911 Abu Dhabi, UAE
چکیده
In this work, we address the challenges posed by zero returns in both stochastic volatility (SV) and log-GARCH models in their asymmetric form. Building upon EM imputation for handling zero returns, we propose a unified approach that enhances parameter estimation robustness for both model classes. Specifically, we employ the Quasi-Maximum Likelihood (QML) estimation, incorporating the Kalman filter for both asymmetric SV and asymmetric log-GARCH models, to ensure robust parameter estimation even in the presence of zero returns. By comparing the performance of these models under our proposed framework, we provide new insights into their relative strengths in capturing the asymmetric volatility dynamics in the presence of zero returns. This contribution extends the existing literature by proposing a computational framework applicable to such models, based on a logarithmic specification of volatility.
کلیدواژه‌ها
Stochastic volatility؛ log-GARCH؛ zero returns؛ quasi-maximum likelihood؛ Kalman filter
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تعداد مشاهده مقاله: 76
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