The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for whi...

Herein, we propose a novel hybrid method for forecasting steel prices by modeling nonlinearity and time variations together to enhance adaptability. The multivariate empirical mode decomposition (MEMD)–ensemble-EMD (EEMD) approach was employed preprocessing separate the nonlinear variation components of hot-rolled coil (HRC) price return series, particle swarm optimization (PSO)-based least squ...

This paper uses simulation-based portfolio optimization to mitigate the left tail risk of portfolio. The contribution is twofold. (i) We propose Markov regime-switching GARCH model with multivariate normal tempered stable innovation (MRS-MNTS-GARCH) accommodate fat tails, volatility clustering and regime switch. each asset independently follows regime-switch model, while correlation joint model...