Hello Les,lesm said:A question here is, do we see what we want to see or can we discern repeatable patterns in a deterministic manner that is consistently repeatable?
The computer between our ears is very powerful and by learning and understanding market behaviour and the ability to identify patterns that are immediately discernable is within its capabilities. We have natural inbuilt neural network, we just need to learn to use it effectively. The more we look at something the more likely we are to run the risk of seeing what we want to see. What we see in the first couple of seconds (or less) of looking at a chart is most likely the correct interpretation.
The more we study patterns enables us to determine their reliability as a method for determining, which way the market or an individual stock might move. We can gather information, which we can use to develop a probalilistic mathematical model to reduce the guess work. Afterall, probability is a mathematical approach to dealing with uncertainty. We can refine and monitor the model through time, as there are no gurantees that a particular pattern will not fail through time or at particular times due to changes in market behaviour/dynamics.
This is my first cut at responding to your “epiphany” in post 155 on this thread (155!!! Wow, we must have been busy posters. Barney will be pleased he kicked off a monster!).
Psychology:
To what extent do we “colour” what we see in a chart?
Douglas goes into the psychology underlying the way people impose a view on a chart. He gives the example of two different hypothetical situations where a child for the first time meets with a dog, child “A” meets a friendly dog, while child “B” meets with a vicious dog.
A’s first experience is pleasant, and the child associates the nice feeling of the dogs coat, and the joy of patting it, instilling a positive emotional memory.
B on the other hand is bitten and attacked by the dog, and associates dogs with an unpleasant experience and danger.
In both cases any future dogs each child meets is perceived in the emotional framework established from the first experience. Of course Douglas goes into much greater detail, but this line of thinking I think has a lot of merit, and that the experiences that we as traders/investors have will unconsciously affect the way we view the whole process let alone our view of a chart.
Gann made some interesting observations here too. He writes about each individual having an innate bias when looking at charts, either bullish or bearish. The idea is that we all have a bias, and tend to read our bias (bullish or bearish) into a chart.
McLaren talks about different trading dispositions too. Some people are greedy, counting how much profit they have made while the trade is still active, hoping for that extra few point to bring in enough profits to buy that new car… so they tend to overstay positions. The fearful trader tends to get “nicked” out of positions, often setting stops too close, or not being confident enough either to pull the trigger, or to stay long enough in a winning position.
So, I suppose you can have a greedy bull, a fearful bear, a greedy bear, or a fearful bull, if you mix the various psychologies together…
So I agree, the aim is to precisely set up a “probabilistic mindset” ala Douglas, which equates with your comment on a mathematical model. The key process though is to try to compensate as much as possible for innate psychological influences from colouring our view in the chart.
The Psychology of Chart Analysis:
Now, I do agree that in the first few seconds when looking at a chart, a portion of the mind intuitively takes stock of the situation and makes an immediate judgement. Sometimes this can be spot on, but sometimes it can be heavily influenced by the propensity to impose a view on the market.
In my experience, you also need to study both markets in general, and the actual underlying you are looking at to determine its nature.
Based on this bedrock of experience, by going through a series of technical analysis steps and really examining the chart in detail, all sorts of clues can present themselves, but you have to know what to look for.
When it comes to time cycles, the more you do it, the quicker you get at seeing the “3D” like picture behind the obvious bars. But I find this takes a little longer to get your eye in, and I’m still really an intermediate player doing this. The best practitioners I know have been doing it for well over a decade ranging up to decades.
Assessing Probabilities:
To really come up with a consistent approach to assessing probabilities in the market, I’d tend to argue that it is through the process that Douglas ventures in “Trading in the Zone” that this can be achieved, either through a mathematical algorithm, or through a combination of well developed charting with the Douglas axioms and checklist in place (and maybe add some custom criteria – especially a set of requirements if using options).
While I agree that mathematics can aid in estimating risk, and ascribing probability, I would argue that while there are some aspects of the market that can be quantified, that there are some elements where all any of us have is a guess, some more educated than others.
It’s kind of like an actuary in an insurance firm trying to assess the probability of a hurricane hitting a part of Florida, and trying to work out what premium to charge to cover the potential losses in the context of the chances of a hurricane hitting.
You can’t really predict this with an iron clad algorithm. There is a degree of pure speculation and “guesstimation” involved. Executives fudge all the time, and try to hide it behind techno-jargon and gobbledegook. Same is true for risk management in quoting on an IT implementation when a whole range of unknowns will only be unearthed once the project is underway. Half the game in any kind of implementation I’d suggest, whether it’s in the building game, IT, or other commercial activities, is being able to guesstimate well.
How about you Les, what is your perspective on this?
Regards
Magdoran