Results 221 to 230 of about 37,790 (282)

Immunotherapy drug target identification using machine learning and patient-derived tumour explant validation. [PDF]

Nat Mach Intell
Augustine M, Nene NR, Fu H, Pinder CL, Ligammari L, Simpson AP, Sanz-Fernández I, Thakkar K, Qian D, Fitzsimons E, Simpson BS, Vendramin R, Castro A, Niederer H, Turajlic S, Quezada SA, McGranahan N, Watkins C, Swanton C, Litchfield K.   +19 more
europepmc   +1 more source

Cyberchondria in Migraine: The Role of Disease Burden and Medication Overuse. [PDF]

Eur J Pain
Kizilkilic EK, Karahoca M.
europepmc   +1 more source

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Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models

Energy Economics, 2020
Using a textual analysis based geopolitical risk (GPR) index, this paper exploits the effects of geopolitical risk uncertainty on oil futures price volatility within a mixed data sampling (MIDAS) modeling framework. With a variety of MIDAS specifications,
Yin Liao, Feng Ma, Lu Wang
exaly   +2 more sources

Forecasting stock price volatility: New evidence from the GARCH-MIDAS model

International Journal of Forecasting, 2020
This paper introduces a combination of asymmetry and extreme volatility effects in order to build superior extensions of the GARCH-MIDAS model for modeling and forecasting the stock volatility.
Feng Ma
exaly   +2 more sources

Can economic policy uncertainty predict exchange rate volatility? New evidence from the GARCH-MIDAS model

Finance Research Letters, 2020
This paper investigates the impact of relative economic policy uncertainty between China and the United States (the Sino-US EPU ratio) on the Chinese exchange rate volatility by employing a GARCH-MIDAS model.
Zhongbao Zhou
exaly   +2 more sources

Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks

International Journal of Forecasting, 2023
We investigate the role of geopolitical risks (GPR) in forecasting stock market volatility in a robust autoregressive Markov-switching GARCH mixed data sampling (ARMSGARCH-MIDAS) framework that accounts for structural breaks through regime switching and ...
Mawuli Segnon, Rangan Gupta, Bernd Wilfling   +2 more
semanticscholar   +1 more source

Volatility forecasting with an extended GARCH‐MIDAS approach

Journal of Forecasting, 2023
This paper uses the generalized autoregressive conditional heteroscedasticity mixing data sampling (GARCH‐MIDAS) model to construct three types of extended models.
Xiongying Li, Cheng Ye, M. Bhuiyan, Shuiren Huang   +3 more
semanticscholar   +1 more source

Midas

2023
The condition of England,* on which many pamphlets are now in the course of publication, and many thoughts unpublished are going on in every reflective head, is justly regarded as one of the most ominous, and withal one of the strangest, ever...
openaire   +2 more sources