Results 141 to 150 of about 291,653 (252)

Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances. [PDF]

J Environ Stud Sci, 2023
Villar-Rubio E, Huete-Morales MD, Galán-Valdivieso F.   +2 more
europepmc   +1 more source

Discrete-Valued Time Series. [PDF]

Entropy (Basel), 2023
Weiß CH.
europepmc   +1 more source

Generalized autoregressive conditional heteroskedasticity (GARCH) models for the estimation of the variance of the egyptian stock index [PDF]

, 2006
البيومي عوض عوض
openalex   +1 more source

Analysis of Drug-Resistant Bacteria Seasonality in Japan Using Financial Time Series Analysis Method: A Nationwide Longitudinal Study. [PDF]

Can J Infect Dis Med Microbiol
Ito H, Oshida J, Fujita M, Kobayashi D.
europepmc   +1 more source

Modeling Volatility for High-Frequency Data of Cryptocurrency Bitcoin Price using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model

, 2022
Nashirah Abu Bakar, Sofian Rosbi
openalex   +1 more source

Predicting the volatility of Chinese stock indices based on realized recurrent conditional heteroskedasticity. [PDF]

PLoS One
Zhang G, Zhao H, Fan R.
europepmc   +1 more source

Multiscale neural dynamics in sleep transition volatility across age scales: a multimodal EEG-EMG-EOG analysis of temazepam effects. [PDF]

Geroscience
Sirpal P, Sikora WA, Refai HH.
europepmc   +1 more source

Spatio-Temporal Generalized Autoregressive Conditional Heteroskedasticity Models

, 2016
This thesis presents a spatio-temporal extension of the GARCH process with a specific spatial dependence structure. Different simulation and estimation techniques are developed. Assuming a circular spatial structure at each time point, gives a closed and finite set of variables at each point in time, making the spatio-temporal process adapted in the ...
openaire   +1 more source

Predicting coal workers' pneumoconiosis trends: Leveraging historical data with the GARCH model in a Chinese Miner Cohort. [PDF]

Medicine (Baltimore)
Sun P, Wang B, Zhang H, Xu M, Han L, Zhu B.   +5 more
europepmc   +1 more source