We examine how the tail risk of currency returns over the past 20 years were impacted by central bank (monetary and liquidity) measures across the globe with an original and unique dataset that we make publicly available. Using a standard factor model, we derive theoretical measures of tail...

We propose a novel specification strategy using a SVAR identified with zero and sign-restrictions to uncover real-time financial shocks in an emerging market. By adding a foreign exogenous block and differentiating between local and US risk premia, we build on the literature that employs...

We implement multivariate, self-exciting Peaks-over-Threshold (POT) methods to measure extremal losses in high-frequency return series of cryptocurrencies. For that purpose, we implement trivariate Hawkes-POT and the autoregressive conditional intensity ACI-POT models for Bitcoin, Ethereum, and...

This paper constructs Tail Risk-Managed (TRM) portfolios in real time, where the scaling of exposures to factors is determined by forecasts of probabilities of VaR violations. Using a set of US Fama-French factors and a set of International equity portfolios, we show that TRM portfolios achieve...

We use extreme value theory to study idiosyncratic tail risk for a large panel of US stocks. Surprisingly, calls and puts contain important information about the lower and upper tails, respectively. Furthermore, the direction of this information is often wrong: Over prolonged periods of time,...