We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest....

Risk estimation or volatility estimation at financial markets, particularly stock exchange markets, is complex issue of great importance to theorists and practitioners. Models used to estimate volatility forecasts are translated into better pricing of stocks and better risk management. The aim...

In this paper, we propose a multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution. This distribution, defined by a mixture of the multivariate normal distribution and the tempered stable subordinator, is consistent with two stylized facts...

To improve the dynamic assessment of risks of speculative assets, we apply a Markov switching MGARCH approach to portfolio forecasting. More specifically, we take advantage of the flexible Markov switching copula multivariate GARCH (MS-C-MGARCH) model of Fülle and Herwartz (2021). As an...

We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk...

Is univariate or multivariate modelling more effective when forecasting the market risk of stock portfolios? We examine this question in the context of forecasting the one-week-ahead Expected Shortfall of a portfolio invested in the Fama-French and momentum factors. Apply ingextensive tests and...

Given the increasing interest in cryptocurrencies shown by investors and researchers, and the importance of the potential loss scenarios resulting from investment/trading activities, this research provides market operators with a dynamic overview on the short-term portfolio tail risk...

The majority of industry credit portfolio risk models, as well as recent scientific results, are based on isolated modules for default probabilities and recoveries in the event of default. This paper shows that these common methods lead to various econometric drawbacks when the parameters are...

Credit risk is an important issue in many finance areas, such as the determination of cost of capital, the valuation of corporate bonds and pricing of credit derivatives. Credit risk has also been a cause and consequence of the current financial crisis. Thus, methods for measuring credit risk,...