Results 151 to 160 of about 3,916 (205)

Enhancing Prediction by Incorporating Entropy Loss in Volatility Forecasting. [PDF]

Entropy (Basel)
Urniezius R, Petrauskas R, Vaitkus V, Karimov J, Brazauskas K, Repsyte J, Kacerauskiene E, Harms T, Dargiene J, Ezerskis D.   +9 more
europepmc   +1 more source

Modelling Asymmetric Sovereign Bond Yield Volatility with Univariate GARCH Models: Evidence from India

, 2023
M LB, Chakraborty S, Iyer V, N NM, Ledwani S.   +4 more
europepmc   +1 more source

To keep faith with homoskedasticity or to go back to heteroskedasticity? The case of FATANG stocks. [PDF]

Nonlinear Dyn, 2021
Curto JD.
europepmc   +1 more source

Weighted portmanteau statistics for testing for zero autocorrelation in dependent data. [PDF]

J Appl Stat
Muriel N.
europepmc   +1 more source

Comparative investment analysis between crypto and conventional financial assets amid heightened geopolitical risk. [PDF]

Heliyon
Ullah M, Sohag K, Haddad H.
europepmc   +1 more source

Early warning of regime switching in a financial time series: A heteroskedastic network model. [PDF]

PLoS One
Wang L, An S, Dong Z, Dong X, Li J.
europepmc   +1 more source

Robust control chart for nonlinear conditionally heteroscedastic time series based on Huber support vector regression. [PDF]

PLoS One
Kim CK, Yoon MH, Lee S.
europepmc   +1 more source

The dependency structure of international commodity and stock markets after the Russia-Ukraine war. [PDF]

PLoS One
Zhang C, Liu S, Qin M, Gao B.
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

Increasing correlations or just fat tails?. [PDF]

Campbell, Rachel A.J., Forbes, Catherine S., Koedijk, Kees G., Kofman, Paul   +3 more
core   +1 more source