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

Delay for admission of unstable hospitalized patients to intensive care unit: a need for a medical emergency team?

INTRODUCTION. Patients admitted in Intensive Care Unit (ICU) from general wards are more severe and have a higher mortality than those admitted from emergency department as reported [1]. The majority of them develop signs of instability (e.g. tachypnea, tachycardia, hypotension, decreased oxygen saturation and change in conscious state) several hours before ICU admission. Considering this fact and that in-hospital cardiac arrests and unexpected deaths are usually preceded by warning signs, immediate on site intervention by specialists may be effective. This gave an impulse to medical emergency team (MET) implementation, which has been shown to decrease cardiac arrest, morbidity and mortality in several hospitals. OBJECTIVES AND METHODS. In order to verify if the same was true in our hospital and to determine if there was a need for MET, we prospectively collected all non elective ICU admissions of already hospitalized patients (general wards) and of patients remaining more than 3 h in emergency department (considered hospitalized). Instability criteria leading to MET call correspond to those described in the literature. The delay between the development of one criterion and ICU admission was registered. RESULTS. During an observation period of 12 months, 321 patients with our MET criteria were admitted to ICU. 88 patients came from the emergency department, 115 from the surgical and 113 from the medical ward. 65% were male. The median age was 65 years (range 17-89). The delay fromMETcriteria development to ICU admission was higher than 8 h in 155 patients, with a median delay of 32 h and a range of 8.4 h to 10 days. For the remaining 166 patients, an early MET criterion was present up to 8 h (median delay 3 h) before ICU admission. These results are quite concordant with the data reported in the literature (ref 1-8). 122 patients presented signs of sepsis or septic shock, 70 patients a respiratory failure, 58 patients a cardiac emergency. Cardiac arrest represent 5% of our collective of patients. CONCLUSIONS.Similar to others observations, the majority of hospitalized patients admitted on emergency basis in our ICU have warning signs lasting for several hours. More than half of them were unstable for more than 8 h. This shows there is plenty of time for early acute management by dedicated and specialized team such as MET. However, further studies are required to determine if MET implementation can reduce in-hospital cardiac arrests and influence the morbidity, the length of stay and the mortality.

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

Monthly Public Assistance Statistical Report Family Investment Program

2q34-qter duplication and 4q34.2-qter deletion in a patient with developmental delay.

The 2q3 duplication and 4q3 deletion syndromes are two conditions with variable phenotypes including Pierre-Robin sequence (PRS), limb anomalies, congenital heart defects (CHD), developmental delays and intellectual disabilities. We describe a patient born to a mother with a balanced t(2; 4) translocation who combines both a 2q34-qter duplication and a 4q34.2-qter deletion through inheritance of the derivative chromosome 4 (der(4)). He showed developmental delay, growth retardation, hearing problems, minor facial and non-facial anomalies, such as bilateral fifth finger shortness and clinodactyly, but no PRS or CHD. The comparison of his features with those of 46 and 65 published cases of 2q3 duplication and 4q3 deletion, respectively, allows us to further restrict the size of the proposed critical intervals for PRS and CHD on chromosome 4.

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

Monthly Public Assistance Statistical Report Family Investment Program

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

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

Monthly Public Assistance Statistical Report Family Investment Program

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

Monthly Public Assistance Statistical Report Family Investment Program

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

Monthly Public Assistance Statistical Report Family Investment Program