There is always huge scope
In gaining useful perspectives
esp from those who are rigorous and innovative in quantitative testing..
The themes in Wyckoff don't necessarily mean they can not be quantified or tested.. it is a matter of working out how and realizing that it will always be limited and more suggestive than definitive...
eg here are some bits and pieces I had come across from this Author..
Using a profit target will:
1. Double the probability of being at or above that target at the end of a fixed period of time.
2. Have no impact on your expected gain or loss.
3. Reduce your variance and standard deviation
4. Result in larger losses than gains
This result derives from the fact that the normal distribution is symmetric and self-similar. Thus it obeys a property called the Reflection Principle. Each price path has an equal and opposite mirror image. Each price point reached has a distribution of points past it and an equal and opposite distribution of points which were 'reflected back'. Elementery proofs for the analogous case of stops, using nothing more than high school algebra, are given in my book Optimal Portfolio Modeling.
It should be emphasized that this is the theoretical model. To the extent that one can find empirical evidence that the market does not conform to this, there may be something tradeable. But just because you can manipulate your distribution to double the probability of a winning trade does not mean that the average winnings will be any better My Motto: You need an edge ”” never let your money leave home without it.
You need an edge ”” never let your money leave home without it.
The ultimate question. Is our fate (and trading success) predetermined or do we have some control over it?
Perhaps a better way to express the problem is through the paradigm of statistical thinking. In statistics the central concept is randomness. Randomness is actually a very deep philosophical issue. It is not the same for all people. Rather randomness depends greatly upon what you know, and different people know different things.
Suppose a company has a great quarter. During the quarter many employees will have a pretty good idea that the quarter is going well. Those at the top such as the CEO and CFO will have a very clear picture. After the end of the quarter the outside auditors may get a good idea as well. Then some time later the earnings report is released to the public and the stock moves unexpectedly. To the outside investor the event seemed random and unpredictable. But clearly someone knew.
The central point is that from the perspective of those who knew of the coming announcement in advance the event was not completely random. From the perspective of those who knew nothing the event was unexpected and seemingly random. Randomness and non-randomness can coexist in different people with different information. So then the best definition of randomness must ultimately be egocentric. What is random to me is that which I do not know and cannot predict.
This concept can be quantified very nicely by various statistical ideas.
A little counting can greatly reduce the randomness in our trading.
Randomness is actually a very deep philosophical issue. It is not the same for all people. Rather randomness depends greatly upon what you know, and different people know different things.
A little counting can greatly reduce the randomness in our trading.
Encoding prices as Binary Codes, from Philip J. McDonnell
Claude Shannon's work on information theory demonstrated conclusively that all information could be efficiently represented in binary code. This breakthrough enabled tremendous advances in digital communications. In addition nearly every computer since that time has used some form of binary storage for both numbers and character oriented information.
With recent discussion of information theory it is appropriate to note that price patterns can be conveniently encoded as binary patterns as well. For example if a day was up that would be a 1 (one) bit and if it was down it would be a 0 (zero). Binary representation only has two digits 1 and 0.
To use this to construct character codes for price patterns we could take the last 3 days of up down net change and assign 1 if up and 0 if down. The pattern + - + would take on the code 101. Here is a table of the first 8 binary numbers:
decimal binary
0 000
1 001
2 010
3 011
4 100
5 101
6 110
7 111
So if we are studying what happens the day after a number 5 pattern we put all those results into bin number five. Thus from the bin 5 results we can calculate the average, standard deviation and probability of being up after that pattern is seen. The same principal applies to the other bins.
Another different use for such bins is to calculate the entropy of all the bins for a recent period. In an earlier study I found that increased entropic diversity tended to be followed by better markets than other periods. One simple measure of this would be to take the last 8 non-overlapping periods of 3 days and set up the bins as described above. We now look at how many fell into each of the 8 bins. The maximum diversity is achieved when each bin contains exactly 1 observation. The minimum is when all observations fall into only one bin. So our resulting statistic is a number from 1 through 8 which can be checked for its relationship to subsequent market performance.
A slight refinement of this would be to do a more sophisticated entropy calculation using a summation of the logs of estimated probabilities per Shannon's original formula.
With recent discussion of information theory it is appropriate to note that price patterns can be conveniently encoded as binary patterns as well.
All of these points are principles of the Wyckoff Mehod
The last is Wyckoff P&F methodology for goodness sake
So I am interested .....
( The above are not quotes from the book . But I think it is his only book to date)
He makes a distinction between counting and TA
Perhaps most importantly, counting looks to repeatable observations and analyses. What one observer sees and analyzes looks the same to another counter. Observations are objectively repeatable. By contrast, TA allows chart interpretations. A pattern which one trained analyst sees on a chart may not be interpreted the same way by another. TA allows subjective non-repeatable interpretation whereas counting does not.
Counting requires some sort of significance testing. To my knowledge there is no TA testing software which includes any sort of significance testing. In fact the only time a standard deviation is normally used in TA is in the calculation of John's own Bollinger Bands.
Your knowledge through tradeguider should allow you to see Wyckoff is about counting not TA in this sense
A SOS a Test etc even a "binary pattern" on a P&F chart
are all
repeatable observations and analyses
price volume and time can be given quantifiable definitions
But relative to the prior data
This is exactly what tradeguider tries to do for You
and Wyckoff teaches You to do
P&F patterns are Quantities
No ambiguity at all..
motorway
motorway