1 Albano G. et al., A comparison among alternative parameters estimators in the Vasicek process: a small sample analysis -- 2 Amendola A. et al., On the use of mixed sampling in modelling realized volatility: The MEM–MIDAS -- 3 Amerise I. L. and Tarsitano A., Simultaneous prediction intervals...

We study the empirical performance of alternative risk and reward specifications in portfolio selection. In particular, we look at models that take into account asymmetry of returns, and treat losses and gains differently. In tests on a dataset of German equities, we find that portfolios...

Climate change affects hydropower production by modifying total annual inflow volumes and their seasonal distribution. Moreover, increasing air temperatures impact electricity consumption and, as a consequence, electricity prices. All together, these phenomena may lead to a loss in revenue. We...

We study the empirical performance of alternative risk and reward specifications in portfolio selection. In particular, we look at models that take into account asymmetry of returns, and treat losses and gains differently. In tests on a dataset of German equities we find that portfolios...

Portfolio selection is about combining assets such that investors' financial goals and needs are best satisfied. When operators and academics translate this actual problem into optimisation models, they face two restrictions: the models need to be empirically meaningful, and the models need to...

Modern finance, both theoretical and practical, makes extensive use of mathematical reasoning and modelling. But this reliance on exact methods comes with unfortunate side effects: numerical precision is emphasised, but without an equal insistence on empirical accuracy; methods that do not offer...

Computational-optimization methods can broadly be classified into two groups: classical methods, which require and exploit specific functional forms of objective function and constraints, and heuristics. Those latter methods impose few, if any, restrictions on models, at the price of being more...

Calibrating option pricing models to market prices often leads to optimisation problems to which standard methods (like such based on gradients) cannot be applied. We investigate two models: Heston's stochastic volatility model, and Bates's model which also includes jumps. We discuss how to...

There is a large number of optimisation problems in theoretical and applied finance that are difficult to solve as they exhibit multiple local optima or are not lsquo;well-behaved' in other ways (eg, discontinuities in the objective function). One way to deal with such problems is to adjust and...