The cryptocurrency market is a complex and rapidly evolving fnancial landscape in which understanding the inter- and intra-asset dependencies among key fnancial variables, such as return and liquidity, is crucial. In this study, we analyze daily return and liquidity data for six major...

It has been shown that, despite being consistent and in some cases efficient, maximum pseudo-likelihood (MPL) estimation for copula models overestimates the level of dependence, especially for small samples with a low level of dependence. This is especially relevant in finance and insurance...

We analyze how earnings dynamics changed in the US after the financial crisis of 2007- 2009. Differently from most models for earnings mobility, we allow persistence patters to depend semi-nonparametrically on both the past individual position in the distribution and on a set of individual-level...

High levels of carbon emissions and rising income inequality are interconnected challenges for the global society. Commonly-applied linear regression models fail to unravel the complexity of potential bi-directional transmission channels. Specifically, consumption, energy sources and the...

High levels of carbon emissions and rising income inequality are interconnected challenges for the global society. Commonly-applied linear regression models fail to unravel the complexity of potential bi-directional transmission channels. Specifically, consumption, energy sources and the...

We explore extreme return-volumes dependence among different cryptocurrencies such as Bitcoin, Ethereum, Ripple, and Litecoin by using the Copula approach. We use Student-t, Frank, Clayton, Survival Clayton, Gumbel, and SJC copulas. We filter out margins by using the EGARCH model for return...