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 <[EMAIL PROTECTED]> 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, .
