Farmas USA

once
diario

semanal

si respeta el triangulo roto rango 52,50 51,60
si no lo respeta 45,50
si se hunde del todo 34

fibo en semanal.

gap en 41.23

Mil gracias.

Once .

ACHN
Animando el patio para el lunes.
http://www.bidnessetc.com/72988-jj-working-a-breakthrough-hcv-cure-gilead-feel-threatened/

Ya le tiro líneas hasta a los tuyos.
Me voy a meter en la piscina, demasiado sol :)

NVAX

http://seekingalpha.com/instablog/498952-bret-jensen/4915655-sunday-review-2-biotech-picks-and-week-1-fantasy-football-sleepers?source=email_rt_author_readmore&uprof=45&isDirectRoadblock=false

Por si hay algún curioso sobre este tema, que me parece capital para la inversión en biotech, pongo un artículo sobre por qué fallan tantas fases 3 y de nuevo lo mal que se interpretan los p-values.

http://drugbaron.com/why-too-many-clinical-trials-fail-and-a-simple-solution-that-could-increase-returns-on-pharma-rd/

Un extracto:

After a study reads out ‘positive’ (that is, with a p value below 0.05), the chance of a further study now failing is not less than 5% as suggested above, you will be wrong at least 30% of the time. It might even be as high as 70% depending on the overall experimental design.

If you run lots of phase 2 trials with different drug candidates where only a minority (lets say 10%) actually work, then with standard trial statistics (80% power and 5% false positive rate) you will get 4.5% false positive and 8% true positives – so less than 2 out of every 3 positive trial results were real. A much lower success rate than the 5% error rate commonly assumed.

Prof Colquhoun illustrates the problem using the example of a screening test for cancer. Imagine performing a 100,000 tests for a rare cancer (only 1 in 1000 of those tested actually have it). Even if the test has excellent (95%) sensitivity and specificity – better than almost all real-world tests – then most of the “diagnoses” still turn out to be wrong. Here’s the math: with a specificity of 95%, 5 out of every hundred people without cancer yield a false positive – so with 99,900 tests on people without cancer we will collect 2,495 false positives. This contrasts with the 95 real positives (5 of the 100 with cancer get missed due to the 95% sensitivity). Only about 4% of the positive diagnoses of cancer turn out to be correct. This phenomenoni is often termed as the False Discovery Rate (FDR).

Y aquí se explica en aún más detalle:

http://rsos.royalsocietypublishing.org/content/1/3/140216

¿Tenéis un plan para el día D si la fase 3 ha sido exitosa?

¿Vender en apertura?
¿Vender cuando suba un X%?
¿Vender al cierre?
¿Vender cuando venda Framus?
¿Vender cuando lo diga el sistema de Magura?
¿Aguantar a la espera de un posible BO?

Yo venderé, pero aún no tengo claro en qué momento de la sesión, y creo que es algo que vale la pena tener pensado antes del día de autos (aunque luego se cambie el plan sobre la marcha).

NVAX