We propose new systematic tail risk measures constructed using two different approaches. The first extends the canonical downside beta and co-moment measures, while the second is based on the sensitivity of stock returns to innovations in market crash risk. Both tail risk measures are associated...

We show that liquidity tail risk in credit default swap (CDS) spreads is time-varying and explains variation in CDS spreads. We capture the liquidity tail risk of a CDS contract written on a firm by estimating the tail dependence, i.e., the asymptotic probability of a joint surge in the bid-ask...

The paper considers the problem as to whether financial returns have a common volatility process in the framework of stochastic volatility models that were suggested by Harvey et al. (1994). We propose a stochastic volatility version of the ARCH test proposed by Engle and Susmel (1993), who...

This paper revisits the performance of frequently used risk forecasting methods, such as the Value-at-Risk models. The aim is to analyze its performance, and mitigate its pitfalls by incorporating conditional variance estimates, as generated by a GARCH model. Notably, this paper tests several...

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

This paper aims to assess dynamic tail risk exposure in the hedge fund sector using daily data. We use a copula function to model both lower and upper tail dependence between hedge-fund and broad-market returns as a function of market uncertainty. We proxy the latter by means of a single index...

This paper extends the extreme downside correlation (EDC) and extreme downside hedge (EDH) methodology to model the interdependence in the sensitivity of assets to the downside risk of other financial assets under severe firm-level and market conditions. The model is applied to analyze both...

We propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic...

We comprehensively investigate the usefulness of tail risk measures proposed in the literature. We evaluate both the statistical and the economic validity of the measures. The option-implied measure of Bollerslev and Todorov (2011b) (BT11Q) performs the best overall. While some other tail risk...