Behavioral aspects of investment fund's markets: are good managers lucky or skilled?

It is generally accepted that financial markets are efficient in the long run a lthough there may be some deviations in the short run. It is also accepted that a good portfolio manager is the one who beats the market persistently along time, this type of manager could not exist if markets were perfectly efficient According to this in a pure efficient market we should find that managers know that they can not beat the market so they would undertake only pure passive management strategies. Assuming a certain degree of inefficiency in the short run, a market may show some managers who tr y to beat the market by undertaking active strategies. From Fama’s efficient markets theory we can state that these active managers may beat the market occasionally although they will not be able to enhance significantly their performance in the long run. On the other hand, in an inefficient market it would be expected to find a higher level of activity related with the higher probability of beating the market. In this paper we follow two objectives: first, we set a basis to analyse the level of efficiency in an asset invest- ment funds market by measuring performance, strategies activity and it’s persistence for a certain group of funds during the period of study. Second, we analyse individual performance persistence in order to determine the existence of skilled managers. The CAPM model is taken as theoretical background and the use of the Sharpe’s ratio as a suitable performance measure in a limited information environment leads to a group performance measurement proposal. The empiri- cal study takes quarterly data from 1999-2007 period, for the whole population of the Spanish asset investment funds market, provided by the CNMV (Comisión Nacional del Mercado de Valores). This period of study has been chosen to ensure a wide enough range of efficient market observation so it would allow us to set a proper basis to compare with the following period. As a result we develop a model that allows us to measure efficiency in a given asset mutual funds market, based on the level of strategy’s activity undertaken by managers. We also observe persistence in individual performance for a certain group of funds

Adaptive search and information updating in sequential mate choice

Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, December 2003

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2004

Monthly Public Assistance Statistical Report Family Investment Program

Choice of an adequate promoter for efficient complementation in Saccharomyces cerevisiae: a case study.

Conservation of the function of open reading frames recently identified in fungal genome projects can be assessed by complementation of deletion mutants of putative Saccharomyces cerevisiae orthologs. A parallel complementation assay expressing the homologous wild type S. cerevisiae gene is generally performed as a positive control. However, we and others have found that failure of complementation can occur in this case. We investigated the specific cases of S. cerevisiae TBF1 and TIM54 essential genes. Heterologous complementation with Candida glabrata TBF1 or TIM54 gene was successful using the constitutive promoters TDH3 and TEF. In contrast, homologous complementation with S. cerevisiae TBF1 or TIM54 genes failed using these promoters, and was successful only using the natural promoters of these genes. The reduced growth rate of S. cerevisiae complemented with C. glabrata TBF1 or TIM54 suggested a diminished functionality of the heterologous proteins compared to the homologous proteins. The requirement of the homologous gene for the natural promoter was alleviated for TBF1 when complementation was assayed in the absence of sporulation and germination, and for TIM54 when two regions of the protein presumably responsible for a unique translocation pathway of the TIM54 protein into the mitochondrial membrane were deleted. Our results demonstrate that the use of different promoters may prove necessary to obtain successful complementation, with use of the natural promoter being the best approach for homologous complementation.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, March 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, April 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, May 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, June 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2002

Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, December 2001

Monthly Public Assistance Statistical Report Family Investment Program