Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

We investigate the distributions of e-drawdowns and e-drawups of the most liquid futures financial contracts of the world at time scales of 30 seconds. The e-drawdowns (resp. e-drawups) generalise the notion of runs of negative (resp. positive) returns so as to capture the risks to which...

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...

The catastrophic failures of risk management systems in 2008 bring to the forefront the need for accurate and flexible estimators of market risk. Despite advances in the theory and practice of evaluating risk, existing measures are notoriously poor predictors of loss in high-quantile events. To...

This paper investigates the impact of individual bank fundamental variables on stock market returns using data from a panel of 235 European banks from 1991 to 2005. The sample period marks a significant transition in the European banking sector, characterized by higher competition, lower profit...

We advocate the use of absolute moment ratio statistics in conjunctionwith standard variance ratio statistics in order to disentangle lineardependence, non-linear dependence, and leptokurtosis in financial timeseries. Both statistics are computed for multiple return horizonssimultaneously, and...

The so-called 'Monday effect ' has been found for various stock markets of the world. The empirical finding that Monday returns are significantly smaller than returns measured for the remaining days of the week calls the efficiency hypothesis for pricing processes operating on stock markets into...

This paper investigates the impact of individual bank fundamental variables on stock market returns using data from a panel of 235 European banks from 1991 to 2005. The sample period marks a significant transition in the European banking sector, characterized by higher competition, lower profit...

This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price...

We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...