Titlebook: Mathematical and Statistical Methods for Actuarial Sciences and Finance; MAF 2016 Marco Corazza,Florence Legros,Marilena Sibillo Book 2017

脫落

Book 2017arial Sciences and Finance”, held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016..The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in in

Magnitude

Markov Switching GARCH Models: Filtering, Approximations and Duality,ace representation, we are able to give a unique framework to reconcile the estimation obtained by filtering procedure with that coming from some auxiliary models proposed in the literature. Estimation on short-term interest rates shows the feasibility of the proposed approach.

富饒

Uncertainty in Historical Value-at-Risk: An Alternative Quantile-Based Risk Measure,risk measure (the Spectrum Stress .) to capture the uncertainty in the historical . approach. This one provides flexibility to the risk manager to implement prudential regulatory framework. It can be a . based stressed risk measure. In the end we propose a stress testing application for it.

審問

indices

The Effect of Credit Rating Events on the Emerging CDS Market,First, we find on average a competition (imitation) effect of downgrades (upgrades) among emerging portfolios. Results confirms that non-event portfolios responds positively to credit deteriorations in terms of an improvement in sovereign credit risk. Second, the sovereign credit risk of non-event c

NAV

鐵塔等

Projecting Dynamic Life Tables Using Data Cloning,s. We assume that the latent mortality factor of LC is common for all of them, given the linkage among them. On the other hand, hierarchical modeling is usually conducted by Bayesian approach, which has the disadvantage that assumptions on the prior distributions are needed, which are not usually kn

cognizant

Markov Switching GARCH Models: Filtering, Approximations and Duality, dependence which makes the estimation step unfeasible with usual Maximum Likelihood procedure. However, by rewriting the model in a suitable state space representation, we are able to give a unique framework to reconcile the estimation obtained by filtering procedure with that coming from some auxi

AVOW

BIAS

An Evolutionary Approach to Improve a Simple Trading System,e time-window widths used to calculate them. To attempt to improve the performances of the TS, we optimize these parameters (that is the time-window widths) by the Particle Swarm Optimization (PSO), which is a metaheuristic used to solve global optimization problems. The use of PSO is necessary sinc