We use portfolio holdings to show that mutual funds preferentially trade stocks according to the stocks' sentiment betas. Stocks with high sentiment betas are more responsive to investor sentiment and increase (decrease) in value as sentiment increases (decreases). Sentiment-based trades may be...

Using an extended version of the credit risk model CreditRisk, we develop a flexible framework with numerous applications amongst which we find stochastic mortality modelling, forecasting of death causes as well as profit and loss modelling of life insurance and annuity portfolios which can be...

Credit migration matrices are cardinal inputs to many risk management applications; their accurate estimation is therefore critical. We explore two approaches: cohort and two variants of duration - one imposing, the other relaxing time homogeneity - and the resulting differences, both...

Current research on financial risk management applications of econometrics centres on the accurate assessment of individual market and credit risks with relatively little theoretical or applied econometric research on other types of risk, aggregation risk, data incompleteness and optimal risk...

An immediate consequence of the Efficient Market Hypothesis (EMH) is the absence of auto-correlation of the return series of the financial prices and the exclusion of excess profitability made by any (active) trading strategy. However, the precondition for the validity of EMH, which assumes that...

We introduce an additive stochastic mortality model which allows joint modelling and forecasting of underlying death causes. Parameter families for mortality trends can be chosen freely. As model settings become high dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation....

Despite mounting evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. Based on empirical evidence we propose a parsimonious model that is a mixture of (two) Markov chains, where...

We introduce an additive stochastic mortality model which allows joint modelling and forecasting of underlying death causes. Parameter families for mortality trends can be chosen freely. As model settings become high dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation....

We propose a novel method of estimating default probabilities using equity option data. The resulting default probabilities are highly correlated with estimates of default probabilities extracted from CDS spreads, which assume constant recovery rates. Additionally, the option implied default...

Modified Value-at-Risk (mVaR) and Modified Expected Shortfall (mES) are risk estimators that can be calculated without modelling the distribution of asset returns. These modified estimators use skewness and kurtosis corrections to normal distribution parametric VaR and ES formulas to reduce bias...