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Re: [EquisMetaStock Group] Trading ain't gambling, is it?



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"What you mention here is an excellent example of what is meant with a
fat tailed distribution - the theoretical tails being the 7 good and 7
bad years in your example. The way in which the observed sample
behaved tells you that the market is fat-tailed (this is a well known
fact and has been so for a long time) and asymmetric (bad news counts
more than good news)..."

The market behavior is asymmetrical, but "news" has nothing to do 
with it, as studying the effects of news on the markets will show.  I 
say this as a clarification, because I don't want anyone reading this 
to think that your conclusions are mine.


S. 

--- In equismetastock@xxxxxxxxxxxxxxx, mgf_za_1999 <no_reply@xxxx> 
wrote:
> What you mention here is an excellent example of what is meant with 
a
> fat tailed distribution - the theoretical tails being the 7 good 
and 7
> bad years in your example.  The way in which the observed sample
> behaved tells you that the market is fat-tailed (this is a well 
known
> fact and has been so for a long time) and asymmetric (bad news 
counts
> more than good news).  Other well known phenomena include volatility
> clustering and low but persistant autocorrelation in the squares and
> an increase in efficiency as markets develop.  If you run an options
> book you can use some of these to your advantage.....
> 
> Regards
> MG Ferreira
> TsaTsa EOD Programmer and trading model builder
> http://www.ferra4models.com
> http://fun.ferra4models.com 
> 
> 
> 
> --- In equismetastock@xxxxxxxxxxxxxxx, sebastiandanconia
> <no_reply@xxxx> wrote:
> > Recently, I ran into a good example of how a mathematical formula 
> > isn't an accurate representation of what really happens in 
markets.
> > 
> > I took 44 years of annual returns in the SP500, then got the 
median 
> > of those returns (12.15%) and the standard deviation of those 
returns 
> > (15.69%).  
> > 
> > The standard deviation tells you the volatility of the returns in 
the 
> > security being traded, for anyone who isn't geeky that way.:)
> > 
> > Taking the 12.15% median annual return and subtracting the 
standard 
> > deviation of 15.69% gives you -3.54%.  Adding the median return 
to 
> > the standard deviation gives you +27.84%.  What this tells you is 
> > that 2/3 of the time, the annual return on the SP500 should fall 
> > within a range of -3.54% and +27.84%.  Only 1/3 of the time 
should 
> > returns fall outside of this range, 1/6 of the occurrences lower 
and 
> > 1/6 higher.
> > 
> > With 44 years of data, according to the math, there should be 7 
years
> > (44/6, rounded off) when the annual return would be less than -
3.54% 
> > and 7 years when it would be more than +27.84%.
> > 
> > What ACTUALLY occurred was that there were 11 years when the 
annual 
> > return was below the range and only 3 years when it was above.
> >    
> > Thinking about WHY that happened and what it means is how you 
come up 
> > with great trading concepts that nobody relying heavily on brute-
> > force number-crunching will ever "get."  Your understanding of 
what's 
> > happening and why not only gives you an "edge" but also saves you 
> > from having to do massive amounts of computer back-testing that 
may 
> > or may not tell you anything you can use.
> >  
> > JMO and FWIW.
> > 
> > 
> > Luck,
> > 
> > Sebastian       
> > 
> >    
> > 
> > 
> > --- In equismetastock@xxxxxxxxxxxxxxx, "rdb104" 
<richandellen@xxxx> 
> > wrote:
> > > I haven't done your Freeburg research but from experience I 
agree 
> > totally.
> > > There is always uncertainty..and most of these guys think you 
> > can 'find' the grail when dealing
> > > with randomness most of the time. I don't know why anyone 
thinks 
> > that fear and greed driven by emotion
> > > can fit neatly into some mathematical formula(s).
> > >   ----- Original Message ----- 
> > >   From: superfragalist 
> > >   To: equismetastock@xxxxxxxxxxxxxxx 
> > >   Sent: Monday, September 05, 2005 8:58 PM
> > >   Subject: [EquisMetaStock Group] Trading ain't gambling, is it?
> > > 
> > > 
> > >   Well, I guess we have somewhat different opinions MG. 
> > > 
> > >   I've got a pile of research that I'm going through right now 
from
> > >   Nelson Freeburg. I think he would disagree with some of your 
> > points.
> > >   He's done many thousands of tests over the last 13 years. He 
has
> > >   trading systems that have traded only 9 or 10 times over 20 
years 
> > but
> > >   have beaten buy and hold by a few percentage points. Some of 
those
> > >   systems have winning trade percentages as high as 80%. 
There's 
> > nothing
> > >   academic about them. 
> > > 
> > >   A system making only 9 trades in 20 years says nothing about 
how 
> > long
> > >   a trade lasts. It says nothing about the cost of margin, or 
the 
> > amount
> > >   of money someone can make. Some of Freeburg's systems have 
> > benefited
> > >   from margin and some haven't. 
> > > 
> > >   He also has several systems that have been backtested for 
periods 
> > of
> > >   20 to 50 years. During that time, they showed consistent 
> > performance
> > >   but in the late 90's the systems started to drop off sharply 
in
> > >   performance, and some failed completely. 
> > > 
> > >   I'm not going to speculate on whether gambling is a sin, but 
many
> > >   types of gambling such as poker have the elements of luck, 
skill 
> > and
> > >   probabilities as their components. In the hands of a truly 
skilled
> > >   player, which there are very few, the odds are on the side of 
the
> > >   player. Based on my perspective, and not yours, trading is 
> > exactly the
> > >   same thing. You have to be lucky, skilled and have 
probabilities 
> > on
> > >   your side. 
> > > 
> > >   If you look at the top poker players over the last 20 years, 
none 
> > of
> > >   them made money consistently every year, but over the 20 
years 
> > they
> > >   did very well. They also had some losing years and some big 
> > winning
> > >   years. 
> > > 
> > >   Trading got popular when it was advertised and talked about 
all 
> > over
> > >   television. Poker is now popular for the same reasons. Every
> > >   once-in-a-while someone without truly good skills can get 
lucky 
> > and
> > >   win big. That's why a lot of people take up trading who don't 
> > have a
> > >   clue as to what it takes to be consistently good at it, and 
it's 
> > the
> > >   same reason people start playing internet poker and then 
throw 
> > down
> > >   $10,000 to play in a tournament. It's takes about $500,000 in 
> > front
> > >   money to play most of the world poker tour. How many players 
make 
> > more
> > >   than it cost them to play? How many traders make more than it 
> > costs
> > >   them to play? The drop out rate is about the same. 
> > > 
> > >   I use some of the same systems that Freeburg has been working 
> > with as
> > >   part of my market conditions barometer, which improves my 
winning
> > >   percentages as I've written about before. I'm hoping that 
some of 
> > the
> > >   improvements I've come up with to these systems will increase 
the
> > >   returns that Freeburg has shown over long periods of time. I 
don't
> > >   know yet. The couple that I have worked on so far have had 
very 
> > good
> > >   test results. 
> > > 
> > >   In my trading I stay keenly aware that on any day, I may not 
win. 
> > I've
> > >   educated myself to as high a level as possible regarding the 
game 
> > I
> > >   play. I've tested and retested everything I do so I know the
> > >   probabilities. I've practiced and practiced and practiced many
> > >   thousands of times before stepping up to table to play with 
real
> > >   money. Now I've played it live for several years, and I know 
> > pretty
> > >   well what I can expect to earn. However, I also know that 
when I'm
> > >   lucky, I make more money than when I'm not. I know the market 
is
> > >   unpredictable and may not deal me the cards I need, even when 
the
> > >   probabilities are 99 to 1. 
> > > 
> > >   Basically I make highly educated, well thought out, good 
> > probability
> > >   guesses. Well, now I'm guessing that if that's not gambling, 
it's
> > >   really really close. 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > > 
> > >   --- In equismetastock@xxxxxxxxxxxxxxx, mgf_za_1999 
> > <no_reply@xxxx> wrote:
> > >   > If your system trades 9 times in 20 years, either give the 
> > money to
> > >   > some index manager, or put it in the bank.  You are not 
> > trading, you
> > >   > are buying and holding or investing.  If you add any 
conceivable
> > >   > gearing then either you will run out of margin, or pay 
through 
> > your
> > >   > ears in carry over the 20 years with just 9 trades.
> > >   > 
> > >   > Anyhow, 9 trades in 20 years sounds academic to me - 30 
trades 
> > plus
> > >   > degrees of freedom sounds practical to me.
> > >   > 
> > >   > I do use such long term, 9-trades-in-20-years systems to 
> > extract the
> > >   > long term trend from a ticker.  But I do not use that as a 
> > trading
> > >   > decision - just as part of the input.
> > >   > 
> > >   > Yes I agree with you, trading is not investing.  But I 
> > certainly don't
> > >   > think trading is gambling.  It is gambling if you don't 
know 
> > what you
> > >   > are doing, probably with much worse odds than you'd get in 
a 
> > gambling
> > >   > house.  Trading is buying and selling of financial 
instruments 
> > with a
> > >   > view to making a speculative profit while gambling is 
> > statistical and,
> > >   > given the odds, a sin!
> > >   > 
> > >   > Regards
> > >   > MG Ferreira
> > >   > TsaTsa EOD Programmer and trading model builder
> > >   > http://www.ferra4models.com
> > >   > http://fun.ferra4models.com
> > >   > 
> > >   > --- In equismetastock@xxxxxxxxxxxxxxx, superfragalist 
> > <no_reply@xxxx>
> > >   > wrote:
> > >   > > Your premise is from a purely mathematical view, 
specifically
> > >   > > statistical. However, the market doesn't always supply 
data 
> > in a
> > >   > > complete packages ready for statistical testing and 
> > inference. 
> > >   > > 
> > >   > > Suppose we have a market timing system that has made only 
9 
> > trades in
> > >   > > the last 20 years and all of the trades have been highly 
> > profitable.
> > >   > > Do we use the system or not? There are not enough trades 
to 
> > validate
> > >   > > the results. 
> > >   > > 
> > >   > > We can wait another 40 years or so and we'll probably 
have 
> > enough data
> > >   > > and enough trades to make statistically meaningful 
> > inferences. 
> > >   > > 
> > >   > > None of this is neat, precise or absolute. And there are 
no 
> > hard and
> > >   > > fast rules for how many trades a system needs to give 
good 
> > test
> > >   > > results. There are approaches which are better than 
others 
> > like this
> > >   > > one by MG, but there is no one correct answer to the 
question.
> > >   > > 
> > >   > > After many millions of systems tests and a lot of trading 
> > years in the
> > >   > > markets, no one has come with a trading system, a timing 
> > system or any
> > >   > > other system that works consistently over long periods of 
> > market
> > >   > history. 
> > >   > > 
> > >   > > Trading is not investing, it's gambling with an edge to 
the 
> > player if
> > >   > > the player is an expert at that game. However, the house 
is 
> > always
> > >   > > changing a little something here or there that changes the
> > >   > > probabilities of events just enough to change the game. 
It's 
> > the
> > >   > > players job to stay up with these changes and adapt well 
> > enough to
> > >   > > keep the edge on the house. 
> > >   > > 
> > >   > > Newbie's just don't get how long it takes and how hard it 
is 
> > to get
> > >   > > the edge consistently and over long periods of time. A 
newbie 
> > thinks
> > >   > > if they make money one year, they're going to be a 
successful 
> > trader
> > >   > > every year. Call me in twenty years with your track 
record 
> > and if it
> > >   > > measures up, I'll send you your certificate of 
validation. 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > 
> > >   > > --- In equismetastock@xxxxxxxxxxxxxxx, mgf_za_1999 
> > <no_reply@xxxx>
> > >   > wrote:
> > >   > > > The 30 trades is based on the central limit theorem - 
after 
> > about 30
> > >   > > > observations things settle down if the mean of random 
> > samples
> > >   follows
> > >   > > > a normal distribution.  There are several assumptions 
in 
> > this
> > >   > > > approach, but it should give a good idea.  I'd push it 
up a 
> > bit, say
> > >   > > > to 35 or 40.  Also, you need to adjust for degrees of 
> > freedom if you
> > >   > > > do any optimisation.  Suppose your system is driven by 
1 
> > parameter,
> > >   > > > then you must add this to the 30.  Suppose you have a 
big 
> > system
> > >   that
> > >   > > > uses say 10 parametrs - then you need at least 40 
trades. 
> > >   Especially
> > >   > > > if the system gets bigger, it needs more trades to give 
any
> > >   > > > confidence, and I will feel better if such a system 
> > produced good
> > >   > > > results in 50 or more trades.
> > >   > > > 
> > >   > > > Another, excellent way to test is to use a hold out 
sample. 
> > >   Build the
> > >   > > > system on a portion of the data, say an 80% sample.  
Then 
> > test it on
> > >   > > > the rest and you can see if you have a winner or fools 
> > gold.  The
> > >   > > > *proper* way to do this is to segment the sample in say 
10
> > >   blocks (of
> > >   > > > 10% of the data each).  Now you choose randomly any 8 
> > blocks,
> > >   optimise
> > >   > > > the parameters of the system on it, and test it on the 
> > remaining 2. 
> > >   > > > Then you choose another 8 blocks randomly, optimise the 
> > system, test
> > >   > > > it on the remaining 2 and so on.  After you've done 
this 
> > say 100
> > >   > > > times, you test the results.
> > >   > > > 
> > >   > > > For this you need special software - one good example 
can be
> > >   found at
> > >   > > > 
> > >   > > >     http://weka.sf.net
> > >   > > > 
> > >   > > > In practise, just chop off the most recent 20% and 
you'd 
> > get a good
> > >   > > > idea if the system will work or not.
> > >   > > > 
> > >   > > > Regards
> > >   > > > MG Ferreira
> > >   > > > TsaTsa EOD Programmer and trading model builder
> > >   > > > http://www.ferra4models.com
> > >   > > > http://fun.ferra4models.com
> > >   > > > 
> > >   > > > 
> > >   > > > --- In equismetastock@xxxxxxxxxxxxxxx, "rvalue1" 
> > <rvalue1@xxxx>
> > >   wrote:
> > >   > > > > I would contend that if you generated >30 trades in 
the up
> > >   > direction 
> > >   > > > > for a sufficiently long period 2 years or so, you 
would 
> > have 
> > >   > > > > confidence that the system does well in the up 
direction. 
> > Same
> > >   for 
> > >   > > > > down and catch the sideways as it transitions.  Very 
> > unusual to
> > >   > find 
> > >   > > > > a great system up, down and sideways!!  If you have 
one, 
> > let me
> > >   > know.
> > >   > > > > 
> > >   > > > > If you are waiting for 1000 trades, you must trade 
very 
> > often.
> > >   > > > > 
> > >   > > > > --- In equismetastock@xxxxxxxxxxxxxxx, "Ed Hoopes" 
> > >   > > > > <reefbreak_sd@xxxx> wrote:
> > >   > > > > > I recently attended a lecture by Keith Fitchen, the 
> > author of 
> > >   > > > > several
> > >   > > > > > successful trading systems most notably 
Aberration.  He 
> > says
> > >   that
> > >   > > > > > statistics on more than 1000 trades must be 
compiled 
> > before the
> > >   > > > > > results can be considered valid.
> > >   > > > > > 
> > >   > > > > > Ed Hoopes 
> > >   > > > > > 
> > >   > > > > > --- In equismetastock@xxxxxxxxxxxxxxx, chichungchoi
> > >   > <no_reply@xxxx> 
> > >   > > > > wrote:
> > >   > > > > > > Does anyone know how many trades the evaluation 
needs 
> > to be
> > >   > sound 
> > >   > > > > > > statistically?
> > >   > > > > > > Thank you in advance
> > >   > > > > > > Eric
> > > 
> > > 
> > > 
> > > 
> > >   SPONSORED LINKS Business finance course  Business finance 
online 
> > course  Business finance class  
> > >         Small business finance  Business finance schools  
Business 
> > finance small software  
> > > 
> > > 
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