Portfolio valuation in banks

Frequent references are made to the use of portfolio spread rates in managing financial risks in banks, but indications as to the procedures for determining such rates are very scant.The purpose of this article is to present some initial ideas on the subject: a Standard Funding system indicates what each portfolio should have earned, while an Actual Funding system points out what each portfolio did, in fact, earn; additionally, by comparing the outcomes of the two funding systems for each portfolio, it is possible to determine what each portfolio earned (or lost) in the way of arbitrage.

The portuguese insurance industry: basis for strategic process decision

Nowadays, the Portuguese insurance industry operates in a market with a much more aggressive structure than a few decades ago. Markets and the economy have become globalised since the last decade of the 20th century. Market forces have gradually shifted – power is now mainly on the demand side. In order to meet the new requirements, the insurance industry must develop a strong strategic ability to respond to constant changes of the new international economic order.One of the basic aspects of this strategic development will focus on the ability to predict the future. We introduce the subject by briefly describing the sector, its organisational structure in the Portuguese market, and challenges arising from the development of the European Union. We then analyse the economic and financial structure of the sector. From this point of view, we aim at the possibility of designing models that could explain the demand for insurance, claims and technical reserves evolution. Such models, (even if based on the past), would resolve, at least partly, one of the greatest difficulties experienced by insurance companies when estimating the budget. Thus, we examine the existence of variables that explain the previous points, which are capable of forming a basis for designing models that are simple but efficient, and can be used for strategic planning.

Optimal insurance with counterparty default risk

We study the design of optimal insurance contracts when the insurer can default on its obligations. In our model default arises endogenously from the interaction of the insurance premium, the indemnity schedule and the insurer’s assets. This allows us to understand the joint effect of insolvency risk and background risk on efficient contracts. The results may shed light on the aggregate risk retention sched- ules observed in catastrophe reinsurance markets, and can assist in the design of (re)insurance programs and guarantee funds.

Tools for testing the Solvency Capital Requirement for life insurance

Longevity risk is one of the major risks that an insurance company or a pension fund has to deal with and it is expected that its importance will grow in the near future. In agreement with these considerations, in Solvency II regulation the Standard formula furnished for calculating the Solvency Capital Requirement explicitly considers this kind of risk. According to the new European rules in our paper we suggest a multiperiod approach to evaluate the SCR for longevity risk. We propose a backtesting framework for measuring the consistency of SCR calculations for life insurance policies.

The European challenge of KMN and innovation: a skills and competence portfolio for knowledge worker in SME's

Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf

Commercial agents portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.