It is well known in the literature that the joint parameter estimation of the Smooth Autoregressive – Generalized Autoregressive Conditional Heteroskedasticity (STAR-GARCH) models poses many numerical challenges with unknown causes. This paper aims to uncover the root of the numerical difficulties in obtaining stable parameter estimates for a class of three-regime STAR-GARCH models using Quasi-...

Yingfu Xie. Maximum Likelihood Estimation and Forecasting for GARCH, Markov Switching, and Locally Stationary Wavelet Processes. Doctoral Thesis. ISSN 1652-6880, ISBN 978-91-85913-06-0. Financial time series are frequently met both in daily life and the scientific world. It is clearly of importance to study the financial time series, to understand the mechanism giving rise to the data, and/or p...

Recently, there has been a growing interest in the methods addressing volatility in computational finance and econometrics. Peiris et al. [8] have introduced doubly stochastic volatility models with GARCH innovations. Random coefficient autoregressive sequences are special case of doubly stochastic time series. In this paper, we consider some doubly stochastic stationary time series with GARCH ...

We collect some continuous time GARCH models and report on how they approximate discrete time GARCH processes. Similarly, certain continuous time volatility models are viewed as approximations to discrete time volatility models. 1 Stochastic volatility models and discrete GARCH Both stochastic volatility models and GARCH processes are popular models for the description of financial time series....

این پژوهش با الهام گرفتن از نتایج یک طرح مطالعاتی کاربردی، رویکرد سلسله­‌مراتبی جهت پیگیری فرایند توسعه تأمین‌کنندگان و حمایت تصمیمات موجود در هر مراحل آن ارائه‌ می‌کند. ابتدا، زمینه‌های تأمین نیازمند سپس واجد شرایط هریک زمینه‌ها به کمک تصمیم‌گیری چندشاخصه بهترین-بدترین مشخص می‌گردند. معیارهای شناسایی نیز مرور مطالعات پیشین بهره‌گیری نظرات خبرگان حوزه‌ی خرید استخراج‌شده‌اند. درنهایت، مدل ریاضی ...