Extending Bayesian back-calculation to estimate age and time specific HIV incidence

Lifetime Data Analysis - CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their...     

A comparison of risk transfer strategies for a portfolio of life annuities based on RORAC

This paper aims to compare different reinsurance arrangements in order to reduce the longevity and financial risk originated by a life insurer while managing a portfolio of annuities policies. Linear and nonlinear reinsurance strategies as well as swap like agreements are evaluated via a discrete-time actuarial risk model. Specifically, longevity dynamics are represented by Lee–Carter type models, while interest rate is modeled by Cox–Ingersoll–Ross model. The reinsurance strategies effectiveness is evaluated according to the Return on Risk Adjusted Capital under a ruin probability constrain.     

Acquired immune deficiency syndrome projections in England and Wales: interplay of methodology and data

Since the late 1980s, regular monitoring of the human immunodeficiency virus epidemic in England and Wales has been carried out through the work of successive national working groups. One of their tasks has been to provide short-term projections of the incidence of acquired immune deficiency syndrome. In this paper the data and methods used in this projection work are reviewed and results critically assessed with the aim of highlighting the strong interaction between methodological developments and data acquisition.     

Estimates of human immunodeficiency virus prevalence and proportion diagnosed based on Bayesian multiparameter synthesis of surveillance data

Summary.  Estimates of the number of prevalent human immunodeficiency virus infections are used in England and Wales to monitor development of the human immunodeficiency virus–acquired immune deficiency syndrome epidemic and for planning purposes. The population is split into risk groups, and estimates of risk group size and of risk group prevalence and diagnosis rates are combined to derive estimates of the number of undiagnosed infections and of the overall number of infected individuals. In traditional approaches, each risk group size, prevalence or diagnosis rate parameter must be informed by just one summary statistic. Yet a rich array of surveillance and other data is available, providing information on parameters and on functions of parameters, and raising the possibility of inconsistency between sources of evidence in some parts of the parameter space. We develop a Bayesian framework for synthesis of surveillance and other information, implemented through Markov chain Monte Carlo methods. The sources of data are found to be inconsistent under their accepted interpretation, but the inconsistencies can be resolved by introducing additional 'bias adjustment' parameters. The best-fitting model incorporates a hierarchical structure to spread information more evenly over the parameter space. We suggest that multiparameter evidence synthesis opens new avenues in epidemiology based on the coherent summary of available data, assessment of consistency and bias modelling.     

China and the Different Regional Approaches in Africa

African countries have a tiny share in the international economy and are not able to play more than a small role in the International Relations arena. Nevertheless, major players are looking at Africa with a renewed interest and, among them, China seems to have the most dynamic approach in order to catch-up with other nations and upgrade relations with African countries. However, the EU is also carrying on its new strategy toward parts of Africa. In these world powers strategies, multiple approaches related to subregions exist, instead of a single regional approach. The objective of this paper is to have a closer look and to analyze how the different regions and major nations of Africa Western Africa, Egypt, Eastern Africa and South Africa) are dealing with their economic and political development path and their interconnection with other areas of the World, with an important focus on China-Africa relations.

Latent class models for financial data analysis: some statistical developments

I exploit the potential of latent class models for proposing an innovative framework for financial data analysis. By stressing the latent nature of the most important financial variables, expected return and risk, I am able to introduce a new methodological dimension in the analysis of financial phenomena. In my proposal, (i) I provide innovative measures of expected return and risk, (ii) I suggest a financial data classification consistent with the latent risk-return profile, and (iii) I propose a set of statistical methods for detecting and testing the number of groups of the new data classification. The results lead to an improvement in both risk measurement theory and practice and, if compared to traditional methods, allow for new insights into the analysis of financial data. Finally, I illustrate the potentiality of my proposal by investigating the European stock market and detailing the steps for the appropriate choice of a financial portfolio.     

A dynamic analysis of stock markets using a hidden Markov model

This paper proposes a framework to detect financial crises, pinpoint the end of a crisis in stock markets and support investment decision-making processes. This proposal is based on a hidden Markov model (HMM) and allows for a specific focus on conditional mean returns. By analysing weekly changes in the US stock market indexes over a period of 20 years, this study obtains an accurate detection of stable and turmoil periods and a probabilistic measure of switching between different stock market conditions. The results contribute to the discussion of the capabilities of Markov-switching models of analysing stock market behaviour. In particular, we find evidence that HMM outperforms threshold GARCH model with Student-t innovations both in-sample and out-of-sample, giving financial operators some appealing investment strategies.     

The Russian Military Spending: Modernization Not Rearmament

The Russian Federation has come back on the international scene, in the past years, thanks to its economic expansion and its political stability. The defence sector, a pillar of the Soviet regime, takes advantage of this situation and is receiving increasing funds, although the fraction of the GDP remains constant. Some experts fear a renewed arms race and a new threat for the world security. The analysis of the overall figures leads to a more moderate view. The situation of the Armed Forces suffers from many problems and it is far from being dangerous for the world stability. The core of the Army, the personnel, is in a terrible situation with a huge gap compared with other developed nations. In addition, Russia endures a demographic collapse and it will be always more difficult to find capable arms that use the new generation armaments of the proclaimed modernization plans.