Results 211 to 220 of about 3,114 (262)

Nickel price forecasting based onempirical mode decomposition and deep learning model with expansion mechanism. [PDF]

PLoS One
Li J, Yu Z, Zhang J, Meng W.
europepmc   +1 more source

Temperature evolution of the high‐harmonic magnetic modulations in DyFeO3

Journal of Applied Crystallography, Volume 59, Issue 4, Page 1332-1337, August 2026.
The temperature evolution of the high‐harmonic incommensurate magnetic ordering of Dy3+ in DyFeO3 orthoferrite is compared with the literature results on the soliton lattice of TbFeO3 observed in an external magnetic field.We report on the temperature evolution of magnetic satellites associated with the incommensurate magnetic ordering of Dy3+ ions in ...
Piotr Fabrykiewicz, Dnyaneshwar R. Bhosale, Martin Meven, Astrid Schneidewind, Karin Schmalzl, Michał Stękiel   +5 more
wiley   +1 more source

Temporal trends and forecasting of respiratory mortality in Bangladesh: A SARIMA model for seasonal mortality risk and public health action. [PDF]

J Public Health Res
Hasan P, Khan TD, Abedin M, Haque ME.
europepmc   +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

Volatility, correlation and risk spillover effect between freight rates in BCI and BPI markets: Evidence from static and dynamic GARCH-Copula and dynamic CoVaR models. [PDF]

PLoS One
Zou Y, Xu J, Chen Y.
europepmc   +1 more source

AI companies' strategies with traditional vs. digital assets amid geopolitical and banking crises. [PDF]

Heliyon
Dammak W, Fakhfekh M, Alnafisah H, Jeribi A.   +3 more
europepmc   +1 more source

Mitigating the choice of the duration in DDMS models through a parametric link. [PDF]

J Appl Stat
Mendes FHPES, Turatti DE, Pumi G.
europepmc   +1 more source

Evaluating GARCH models [PDF]

Journal of Econometrics, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stefan Lundbergh, Timo Teräsvirta
openaire   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

ON MIXTURE MEMORY GARCH MODELS

Journal of Time Series Analysis, 2013
We propose a new volatility model, which is called the mixture memory generalized autoregressive conditional heteroskedasticity (MM‐GARCH) model. The MM‐GARCH model has two mixture components, of which one is a short‐memory GARCH and the other is the long‐memory fractionally integrated GARCH.
Li, M, Li, WK, Li, G
openaire   +4 more sources