The design and production of new retirement savings products: a note

With the population in the U.S. and other countries ageing rapidly, the burden of future pension liabilities is ever increasing. In recent years, governments and companies have become much more aware of the inherent risks that are involved. As a consequence, there is a worldwide tendency to shift from defined benefit pension plans to defined contribution plans. The implications for employees are far-reaching: under a defined contribution plan, the employee bears the investment risk: the level of his pension depends on the return on his investments. Under a defined benefit system, the level of pensions is fixed and the sponsor (in many cases the employer) bears the investment risk: the premiums required to fund the pension depend on the return on investments. In this joumal, Bodie and Crane (1999) (BC) recognize that the transfer of investment risk from employer to employee calls for easy-to-implement investment strategies that correctly reflect the trade-off between the risk of a poor pension and the joy of a sumptuous pension. They compare investments in traditional equity and bonds with investments in TIPS (inflation linked bonds) and equity with a protective floor. Their results suggest that a series of investments in a product with a protective floor have a much higher chance of reaching a specified retirement income level than investments in a mixture of equity and fixed income securities.

Hedging Large Portfolios of Options in Discrete Time

The problem studied is that of hedging a portfolio of options in discrete time where underlying security prices are driven by a combination of idiosyncratic and systematic risk factors. It is shown that despite the market incompleteness introduced by the discrete time assumption, large portfolios of options have a unique price and can be hedged without risk. The nature of the hedge portfolio in the limit of large portfolio size is substantially different from its continuous time counterpart. Instead of linearly hedging the total risk of each option separately, the correct portfolio hedge in discrete time eliminates linear as well as second and higher order exposures to the systematic risk factors only. The idiosyncratic risks need not be hedged, but disappear through diversification. Hedging portfolios of options in discrete time thus entails a trade-off between dynamic and cross-sectional hedging errors. Some computations are provided on the outcome of this trade-off in a discrete-time Black-Scholes world.Option hedging, discrete time, preference free valuation, hedging errors, cross-sectional hedging, static hedging, JEL Codes: G13, G12,

Clinical and economic aspects of newborn screening for severe combined immunodeficiency: DEPISTREC study results

PURPOSE: Severe combined immunodeficiency (SCID) refers to a group of genetic disorders characterized by greatly compromised cellular and humoral immunity. Children with SCID are asymptomatic at birth, but they die from infections within the first months of life if not treated. Quantification of T-cell receptor excision circles is an extremely sensitive screening method for detecting newborns who may have SCID.The goal of the DEPISTREC study was to evaluate the feasibility of nationwide newborn screening for severe T-cell lymphopenia in France as well as its economic and clinical utility. METHODS: The test universally used for neonatal screening for SCID was the quantification of TRECs on Guthrie cards. We compared a group of 190,517 babies from 48 maternities across the country who underwent newborn SCID screening with a control group of 1.4 million babies out of whom 28 were diagnosed with SCID without such screening during the course of the study. RESULTS: Within the screening group, 62 babies were found to be lymphopenic, including three with SCID. The cost of screening ranged from 4.7euro to euro8.15 per newborn. The average 18-month cost was euro257,574 vs euro204,697 in the control group. CONCLUSIONS: In this large-scale study, we demonstrate that routine SCID screening is feasible and effective. This screening offers the additional benefit of aiding in the diagnosis of non-SCID lymphopenia. Economic evaluation allowed us to calculate the cost per test. Newborn screening may also prevent death by SCID before any curative treatment can be administered. The difference in cost between screened and control children could not be ascertained because of the very low numbers and death of one of the children tested

Timber Harvesting as a Part of the Portfolio Management: A Multiperiod Stochastic Optimisation Approach

A multiperiod stochastic optimization model is formulated for a land owner who can speculate between investing harvesting income in financial assets and postponing harvesting. This paper demonstrates the benefits from using a multiperiod model, the effects of cointegration on optimal portfolio, and the differences between the timber harvesting model and the standard financial portfolio optimisation model. The demonstrations are made partly by using a real Finnish forest and price data, and partly by using artificial data. In the real data example, the system is demonstrated using a case where it is assumed that the land owner has several mature forest stands, which can be harvested at any time during the next 3 years. Investment alternatives are stocks, government bonds, and bank deposits. The forestry returns were defined as a sum of exponential physical growth and stumpage price return. The chosen definition of forestry returns makes the model very useful, for example, when speculating on what speed of physical growth is needed to make forestry a competitive investment alternative when both returns and risks are considered.Timber harvesting, Stochastic optimisation, Cointegration

Optimal selection of a portfolio of options under Value-at-Risk constraints: a scenario approach

This paper introduces a multiperiod model for the optimal selection of a financial portfolio of options linked to a single index. The objective of the model is to maximize the expected return of the portfolio under constraints limiting its Value-at-Risk. We rely on scenarios to represent future security prices. The model contains several interesting features, like the consideration of transaction costs, bid-ask spreads, arbitrage-free option pricing, and the possibility to rebalance the portfolio with options introduced at the start of each period. The resulting mixed integer programming model is applied to realistic test instances involving options on the S&P500 index. In spite of the large size and of the numerical difficulty of this model, near-optimal solutions can be computed by a standard branch-and-cut solver or by a specialized heuristic. The structure and the financial features of the selected portfolios are also investigated