In mathematics, statistics and science certain formulas have been discovered/formulated such that they become laws and do prove certain things.
I agree with you, it's just that "proving" future events when there are so many variables involved causes me mental grief. Don
========= Don; May i add??? Lets use ''old math'' that new math would confuse anyone. Old math 93 + 7 = 100 is THE only correct answer. Don't know of any profitable traders who believe TA is so clearcut and precise like an old math class. =============================== However if you remember the old math ; several ways to find an average number that helps.
If you were to go about proving TA how would you do it? Since there are an infinite # of possible system/market/variable combinations I don't think that the question is reasonable. At best you would test a bunch of combinations and then would have to generalize the results (which is probably akin to saying after testing 9999 types of lightbulb filiments that don't work, and one that did, that the light bulb doesn't work, or at best doesn't work very well). All you will have proven is that it is hard to create a winning trading system. You could prove a particular system "works" or doesn't "work" over particular times and particular markets with particular variables used on history. But the assumption that historical behavior = future price movement is <probably> an invalid assumption. All this historical testing still doesn't prove that it will "work" or not "work" on live data. Even if you put live money behind a whole ton of systems (unreasonable even for the best funded projects) at best all you have proved is that those systems performed as such and such, but nothing that can be extrapolated to definitively prove or disprove TA.
One of the best and most fundamental relations in TA is the P, V relation. It certainly verifies how TA formations work.
It's not about "proving" future events, it's about proving that a MODEL can forecast future events : If it wasn't possible Science wouldn't exist see below "the aim of the science is to prediction" "Science and Hypothesis" by Jules Henri Poincaré was a mathematician, physicist, and philosopher of science. http://www.utm.edu/research/iep/p/poincare.htm#Science and Hypothesis "According to Poincaré, although scientific theories originate from experience, they are neither verifiable nor falsifiable by means of the experience alone. [...] For Poincaré, <B>the aim of the science is to prediction</B>. To accomplish this task, science makes use of generalizations that go beyond the experience. In fact, scientific theories are hypotheses. But every hypothesis has to be continually tested. And when it fails in an empirical test, it must be given up. According to Poincaré, a scientific hypothesis which was proved untenable can still be very useful. If a hypothesis does not pass an empirical test, then this fact means that we have neglected some important and meaningful element; thus the hypothesis gives us the opportunity to discover the existence of an unforeseen aspect of reality. As a consequence of this point of view about the nature of scientific theories, Poincaré suggests that a scientist must utilize few hypotheses, for it is very difficult to find the wrong hypothesis in a theory which makes use of many hypotheses."
Below is an article on a site who shows why generally statisticians and quants are skeptical about TA. I will write an article one day to oppose their approach because it is not epistemologically right and for that I will expose the point of view of Walter Shewart the great statistician who founded the Statiscal Framework for Quality Control - as I am affiliated to his school of thoughts as a former statistical process control engineer): http://www.burns-stat.com/ Introduction This was a scientific study aimed at testing the efficacy of technical analysis. The task was to select the real price series out of a set that included three random series when given the preceding two years of daily prices. Submissions were accepted from the 6th of September 2003 through the 4th of October 2003. Why the Challenge? The management of funds affects the future livelihood of virtually everyone. The finance industry should be using the best methodologies available, and should have a scientific reason, if possible, for believing in what is done. This test is a step in that direction -- to help prove or disprove the usefulness of technical analysis procedures. Results The report on the results of the study are in the Working Paper entitled The Technical Analysis Challenge (pdf). Abstract: We report on a study of the ability of analysts to distinguish an actual price series of an equity from random alternatives. Virtually all of the statistical tests on the results support the hypothesis that no skill was exhibited in selecting the correct response. Many of the analysts were extremely over-confident about their ability to select correct answers. The one area where it seems skill might have been exhibited is in the selection of correct answers that happened to be far from the random choices.
For example in S&C mag article http://store.traders.com/v1966474inca.html , there is an interview of Carol Osler researcher at the FED has making statistical enquiry who has made on the validity of supports resistances edited by six research companies - using Bootstrap method that is to say random generation of arbritrary levels and comparison with the ones tested - which is not accepted from the classical point of view of quants or academics since it implies path dependance, that is to say the price itself has a significance and not only its relative variation (must read the full article since what I said about path dependance is not in the summary of the article). She said that her and one of her collegue relates this to order flow and inventory problem by observing a trader in a bank : not astonishing see my signature below .