Om, hey, New.Morning;  do you ever interact with the FF TM university 
about
this?  On their radio broadcasts they (Drs. Hagelin and
Morris) and other PhD's are saying the ME is an absolute scientific
certainty.  A fact. Their method it seems is that if they say this 
enough
times and their ME studies get published in newsprint and broadcast 
enough times then 
hence,
it might be true then.  It is pretty dramatic the way they say it.  Of
course, it is being said to a packed jury.  

What do any of them say to you about your analysis of their work 
though?  
That thing also that you mention about 'peer review', which allows 
for others to demonstrate a 
repeatability and then they have 'substance'?   Is their public 
relations certainty anywhere near the 
point where they have substance?

They seem pretty certain the way they present, and it sounds really 
neat and convincing the way they say it.

-Doug in Iowa 


Flaw in the ME studies:


http://groups.yahoo.com/group/FairfieldLife/message/124066



More at:

http://2006-course-effects.blogspot.com/


--- In FairfieldLife@yahoogroups.com, new.morning <[EMAIL PROTECTED]> 
wrote:
>
> I have corrected and updated some recent posts on the flawed MUM
> analysis of the IA experiment.
> 
> A 13% Gain over 17 weeks in NOT a Rare Event
> 
> A recent IA experiment press release states the "advanced 
econometric
> models" show a 3/10,000 chance for normal occurance of recent market
> increases since the start of IA. Thus the so-called rarity of the
> event opens the door for claims of some special new effect.
> 
> Lets actually look at the data.
> 
> The current IA experiment has run 17 full weeks, and the S&P 500 has
> risen 12.9% in that period. Good show.
> 
> But what is the naturally occurring frequency of a 12.9% or better
> gain in any 17 weeks period. Going back to 1960, it has occurred on
> average 4.98 times / year. That is, for any given start week, there 
is
> a about a 10% (4.98/52) chance, historically over almost 50 years,
> that there will be a 12.9% or better gain in the S&P500.
> 
> And if you allow 20 weeks to realize the same 12.9% gains, that is,
> same returns, albeit gained slightly more slowly, it has occured on
> average 7.1 times per year. About a 15% probability that any week 
will
> be the start of a 12.9+ gain over the next 20 weeks.
> 
> And there is a 20% probability that you will get a 10% or better
> return on the S&P 500 within 20 weeks.
> 
> For the IA experiement claim the current rise in the financial 
markets
> since July 21, 2006, the start of the IA experiment, is a very rare
> event, of the magnitude of 3/10,000 probability is preposterous, and
> indicative of very naive or slanted research.
> 
> 12 times there has been double or greater that approximate 13% gain,
> that is greater or equal to 26% gain in 17 weeks periods -- going 
back
> to 1960. It has occurred on average once every four years.
> 
> So if the IA produced that rate of growth, they might begin to be 
able
> to claim something fairly unique is occuring. Or best, if the S&P 
500
> yielded a 35% gain in 17 weeks -- which has never occurred in the
> period since 1960.
> 
> .....
> 
> 
>  IA Analysis Goofs: Assuming Normality, or Overspecification of the 
Event?
> 
> The enourmous goof, cited in the last post, by IA researchers is
> astonishing. How could such mistakes occur -- in the face of real
> data. (claiming a 3/10,000 chance for normal occurance of recent
> market increases since the start of IA -- when such an event -- a 
13%
> run-up in 17 weeks -- has occurred over 220 times since 1960.
> 
> One possibility for the goof is a well-known issue that can be made 
in
> studies of financial markets is to using analysis and models that
> assume a normal distribution. Distributions of the returns for most
> financial markets, certainly the S&P 500 -- the proxy for all US
> markets -- has "fat tails" and a lower peak than a normal
> distribution. More like the top half of a somewhat flattened 
circle --
> aka an elipse, than the classic "bell" shape of a normal (aka
> guassian) distribution.
> 
> For some analysis, in the main body of the distriubtion, the
> difference is not to substantial. However, when analyzing the tails,
> the extreme events, the normal distribution extremely underestimates
> the occurence of extreme gains or losses, that is the top or bottom 
1%
> or more accutely, the top .1% of the distribution.
> 
> ...
> 
> A second possibility of where the IA analysis flaw lies is
> overspecification of the event. For example, instead of testing for
> 13% rises in the S&P 500 over 17 weeks, one could have tested 13%
> rises in the S&P 500 over 17 weeks where there is a pattern that 
there
> are weekly declines in the 3rd, 5th and 7th weeks of the series. 
That
> is the pattern of the recent rise, but is absolutely unimportant to
> the premise being tested: if the 13% rises in the S&P 500 over 17
> weeks is "rare" or if it naturally occurs periodically. The 
occurence
> of 13% rises in the S&P 500 over 17 weeks with weekly declines in 
the
> 3rd, 5th and 7th weeks of the series is indeed much rarer than the
> over 220 times the simpler 13% rises in the S&P 500 over 17 weeks 
has
> occurred since 1960.
> 
> Perhaps the overspecified event happened only this time, First time
> ever. So it would about 1/2500 (52 weeks * 47 years) or so
> probability, which is in the range of the IA's 3/10,000, 1/3333 or
> .033% stated probability. But of course such a hypothetical
> overspecified analysis is quite flawed since the pattern of weekly
> declines in the 3rd, 5th and 7th weeks is totally inconsequential to
> the event of interest: a 13% rise in 17 weeks. The event, not
> overqualified or orverspecified in inessential ways, has occurred 
over
> 220 times in under 2500 weeks -- about 10%. Far from .033%.
> 
> Thus, the caveat to always eye-ball the underlying data and results.
> Does looking at the recent rise in the context of looking at the 
last
> 10 or best yet, 40 years of S&P 500 data seem quite unique? No,
> similar run-ups occured quite periodically.
> 
> 
> 
> More at:
> 
> http://2006-course-effects.blogspot.com/
> 
> 
> 
> 
> --- In FairfieldLife@yahoogroups.com, new.morning <no_reply@> wrote:
> >
> > --- In FairfieldLife@yahoogroups.com, off_world_beings <no_reply@>
> > wrote:
> > >
> > > Even though I do not consider stock markets a measure of 
anything 
> > > significant, do you really thingk that 30 year Statistician 
Maestro 
> > > Maxwell Rainforth 
> > 
> > He was not listed as having done the study.
> > 
> > > did not account for this layman's mistake?
> > > Don't kid yourself...he accounted for it.
> > > 
> > > OffWorld
> > 
> > But OK then. If you are sure. 
> > 
> > Even though this "layman's mistake" is made by many. Its common to
> > assume normality of distrubutions without testing specifically for
> > such. Often, results are not too distorted. Except as, stated, 
when
> > dealing with extremes at the tail of the distribution.
> >  
> > 
> > So if my hypothesis is incorrect as to why their analysis was so 
far
> > off, by a factor of 5000, then perhaps you can explain why they 
could
> > be so far off.  They "found" a 1/50,00 chance of a market rise 
such as
> > the currently one, when such naturally occurs about 5 out of any 
52
> > starting weeks, on average in any given year. That is, a 12.9% 
gain or
> > better for a 17 weeks period it has occurred on average 4.98 times
> > year, going back to 1960, .
>


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