|
PureBytes Links
Trading Reference Links
|
obviously there is no single contained field
of mathematics that you can apply to time series
forecasting.
on top of that you have to separate the math
into math you use for modeling
1. profit/loss expectation, 2. supply/demand, 3. price/volume
process from math you use
for price forecasting.
again since we do really know what p&l expectations
of all participants are, therefore do we can not
know the supply/demand as a result of actions based
on those expectations. so we only know the result
product of the process namely price and volume.
so we can only model process in theory for which
the math is separate and requires NLD and regression
analysis and other kinks.
once you passed this theoretical phase you
will learn how to bypass 1 and 2 and work only with 3
but still utilizing the theoretical laws from 1 and 2.
these are the limitation of the holy grail, which is we
don't know 1 and 2 and we can only know the process
and the law that result in 3. so given those limitations
you learn how to work with 3 only.
*** price forecasting or prediction is basically comes
down to finding short term vs long term dominant
profit and loss expectations which in tern will result
in action ( buying and selling or supply / demand ) which will produce price
and
volume curve as the realized dominant price expectation.
loop closed.
if you can mathematically find what the majority of participants
will do next ( how they will react ), then you got it....
mostly it's non traditional regression analysis since all traditional
regression techniques will not work in this case.
noise is very important part of the equation but i hate calling it
noise since there is no noise in price really.
so you might want to take a look at the NDT.
decision making process in system is pretty straight forward
so there is no need to get into that.
i only use and believe in univariate approach ( only the tape tells you the
truth )
so i don't go out there looking for external things that move price.
if price goes for who cares what reason, it goes and the system will pick
that up.
adaptive statistics is a major chuck of math but it's not too complex.
you can't use straightforward stat analysis since data is non stationary.
all typical stat bs will not work.
you gotta think adaptive which is not the hardest part of the system math.
and after all of the muffled stuff above and to clear things up
you need to basically know three things:
- probable signal ( noise vs signal , tradable vs untradable )
- probable potential for the trade. ( min predictive delta )
- those two have to be nailed 6-7 out of 10 times.
if you get probable signal and the trade has potential then
you go for it.
as a result the tricks are: how do you pick probable
signals adaptively and the most important and the hardest
is how to do calculate the min potential of the trade
and how do you do that with over 60% accuracy :-)
it's hard not only mathematically but mainly conceptually.
other thing is how do you properly correct the errors.
on top of that there are a ton of other things.
i always recommend to start from head to tail.
picture how the system should trade
where the signals should be ( dont be greedy and
don't play "i want to sell the top and buy the bottom game )
run the logic in your mind.
picture the winners and the losers.
lay out system signal logic next for winners and losers.
find vars that are missing and those that you need for
the logic to work.
formulate the problem in math of how to find those vars.
solve for those vars one step at a time.
plug those into the logic and check how the system
works.
signals then logic then vars ( deduction )
if you can get to the part where you can formulate the
math problem then you are half way there :-)
finding the solution is just a matter of time to apply proper math.
curiously most people do the opposite ( induction ):
they play with vars and the logic and then examine how
the signals look :-) and if they look bad then
they try some other vars or and other logic and
there goes the never ending trial and errors approach.
cart in the front of the horse.
that is the key... if you have no idea how the system
should trade and where the signal should be located
on the chart you will never find anything that works
because you don't know what to look for.
the first approach makes you concentrate on
proper solution and forces you on that narrow path...
whereas the second approach forces you to run
around flailing like a mad man looking for that road
that you don't even know if it's the road that you
should take.
regards.
bilo.
----- Original Message -----
From: "David Rosenthal" <davidrnews@xxxxxxxxxxxxx>
To: "Bilo Selhi" <citadel@xxxxxxxxxxxx>; "Omega List"
<omega-list@xxxxxxxxxx>
Sent: Sunday, April 29, 2001 6:46 PM
Subject: RE: Trading Systems
Bilo,
Thank you for your thoughtful post, and congratulations on reaping the
benefits of
your years of hard work.
Would you be willing to share what areas of mathematics have been most
critical to
your study?
David
|