In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

This paper examined a set of over two thousand crypto-coins observed between 2015 and 2020 to estimate their credit risk by computing their probability of death. We employed different definitions of dead coins, ranging from academic literature to professional practice, alternative forecasting...

In this paper, we assess the Value at Risk (VaR) prediction accuracy and efficiency of six ARCH-type models, six realized volatility models and two GARCH models augmented with realized volatility regressors. The α-th quantile of the innovation's distribution is estimated with the fully...

This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model the DCC-HEAVY model as key ingredients are the Engle (2002) DCC model and Shephard and Sheppard (2012) HEAVY model. We discuss the models' dynamics and highlight their...

Realized covariance models specify the conditional expectation of a realized covariance matrix as a function of past realized covariance matrices through a GARCH-type structure. We compare the forecasting performance of several such models in terms of economic value, measured through economic...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

This paper is the first to compare the ability of the two structural credit risk models of Merton (1974) and Leland (1994a, b) to predict bankruptcy. We investigate different implementations of the Merton and Leland models on the whole CRSP/Compustat universe of firms from 1980 to 2015. Although...

The purpose of this article is the presentation of a novel and unconventional algorithm for bankruptcy risk management in banking technologies catered towards lending to legal entities (enterprises and companies). The challenges of assessing risk in this area primarily relate to the reduction of...