Using daily return, realized volatility, realized skewness and realized kurtosis as risk proxies,
we analyze the risk spillovers among crude oil, gold, economic policy uncertainty (EPU) and …

This study examines the connectedness and risk spillovers between Chinese FinTech and
traditional financial institutions by using quantile-based vector autoregression (QVAR) …

This paper investigates the multidimensional risk spillovers among crude oil, the US and
Chinese stock markets during the COVID-19 epidemic through a GARCHSK-Mixed Copula …

Great research efforts have been devoted to exploiting deep neural networks in stock
prediction. However, long-term dependencies and chaotic properties are still two major …

This study investigates the risk and returns on one of the newest digital asset classes
instruments, non-fungible tokens (NFTs), by accounting for tail dependence of higher-order …

This research uses a hybrid systemic risk indicator (rSYR) to measure the systemic financial
risk of China's banking industry from 2009 to 2019 and combines rSYR with sSYR (new …

We propose multilayer information spillover networks to measure the interconnectedness of
financial institutions by comprehensively considering mean spillover layer, volatility spillover …

The outbreak of the COVID-19 pandemic significantly negatively impacted the global
economy and stock markets. This paper investigates the stock-market tail risks caused by …

We investigate whether the global financial crisis (GFC) changed the tail and frequency
interdependence between BRICS stock markets and two strategic commodities (oil and …

This paper adopts the tail-event driven network (TENET) framework to explore the
connectedness and systemic risk of the banking industry along the Belt and Road (B&R) …