Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model Engle et al. (2019) is able overcome this via nonlinear shrinkage estimation unconditional correlation matrix. In paper, we show how performance can be increased further by using open/high/low/close (OHLC) price data instead simply daily returns. A key innovati...

The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models credit risk assessment. Forecasting coefficients yields better model accuracy than trivial of using computed past statistics the next time period. In this paper, new method scoring proposed, which aimed at computing default probability borrower. It was empi...

Using the COVID-19 and Sino-US trade war as background, data of stock markets in China US from March 1, 2017 to September 11, 2020 are divided into 3 phases, high-frequency return series extracted by empirical mode decomposition algorithm, excluding interference medium-frequency low-frequency data. The DCC-GARCH model is used analyze China-US market linkage results show that: both have a signif...