We present a new approach to generalised autoregressive conditional heteroscedasitic (GARCH) modelling for asset returns. Instead of attempting to choose a speciic distribution for the errors, as in the usual GARCH model formulation, we use a nonparametric distribution to estimate these errors. This takes into account the common problems encountered in nan-cial time series, for example, asymmet...

Heart Rate Variability (HRV) series exhibit long memory and time-varying conditional variance. This work considers the Fractionally Integrated AutoRegressive Moving Average (ARFIMA) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors. ARFIMA-GARCH models may be used to capture and remove long memory and estimate the conditional volatility in 24 h HRV recordings. Th...

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...

سابقه و هدف: آب هوای یک منطقه در دوره بلندمدت را اقلیم گویند. شناسایی طبقه‌بندی اقلیمی از دیرباز مورد توجه متخصصان هواشناسی بوده است. محققان با به کارگیری روش ­های مختلف استفاده متغیرهای همچون بارش دما، زمین مناطق همگن طبقه ­بندی کرده‌اند نتایج پهنه‌بندی ارزیابی کمبود منابع مقیاس­ های کوچک بزرگ منظور پیش‌بینی اقدامات عملی برای کنترل خشکی آسیب‌پذیر به‌کار برده‌اند. هدف این تحقیق به‌‌روزرسانی تحل...