Quote from outsource:
There are two kind of them.
1.greed - read - super computer systems
2.fear - read - lower computer systems
We both are sure that a lot of pepole nd organizations operate on fear or greed or a combination of the two.
Neither deal in exact sciences.
History does provide a narrative of those who oreint to the markets vey pragmatically and bypass the science of the markets.
By stepping over those bounds, it is possible to look at markets from a science orientation.
Modelling and developing models for extracting the market's offer is tangential to history and particularly to the "greed" and "fear" part of such a Venn Universe.
The precision of science makes it possible to extract the market's offer.
To step into the probability part of what is possible is more like deciding to apply a technique before you look at what is the basis for reasing through how to understand a system either by synthesis or by analysis of by proceeding to do interative refinement by using their combination.
One major facet of using the exactitude of science is that it is an orderly and refined human process.
The rawest of information yields that the dimensions of the market are all discrete pieces and the market is wholly defined by simple rules of operation by its participants.
Could there be a simpler problem to attack and conquer? It is doubtful that there is a simpler system to examine and gain control over.
This means that the tools of science can be deployed in a very clean and certain manner. The OP characterizes how clean and thoroughly markets can be handled and participated in.
Humans use the descrete market rules to particpate according to single or multiple portions of the two variables.
A simple market (ES for example) has but one instrument and it is defined in terms of ticks and contracts. Participation requirements are as clear as a bell ringing.
Settling into a specific margin requirement is just like using chips at a poker table. Market information is given to anyone who pays for it. It is like all the cards are face up during markets hours.
There is no gamble involved in trading, however.
How does a market behave when the market is open to participation? Price and volume are involved. and participating is fully defined. A record of participation flows as the market operates.
For making money in markets only one characteristic is considered: price change. To the degree of participation, a person or organization does only one thing: make money via price change.
1. Price change is divided into segments that go from price A to price B. The difference is the profit of the segment.
2. Volume leads price and volume defines the division of the profit segments.
I would say most people can only get so far in processing how to make money and how markets work and how to use their minds to participate in markets.
The theory of any model is based upon using all the principles in the correct relationship.
I just use the two numbered principles stated above. They are much older than am I.
I was lucky because I used science from day one onward.
Modelling the market is only done with certainty. Put it another way: there is no guessing in modelling.
A complete system emerges and in today's lingo it is a system that operates in real time and there is no noise nor anomalies. It is a computer system that does not use probability.
You can ask any computer scientist if a computer system operates based on probability. When you turn on your computer, it operates in a way that all the activity is done in a probability free environement. This is often referred to data processing.
Today, PC's do the job that heretofore was done by human minds during the period before computers.
I used the ststements 1 and 2 for many years, beginning in 1957, to extract profits segment by segment. Then, computers were studied under electrical engineering. I worked at IBM in the Data Systems Division and we had 80% of the world market.
Computers in those days liked binary inputs.
What I did then was use statements 1. and 2. in a binary form in a scientific way.
Here in ET and on the web, we see, globally, that very few people know how to use market raw information and get it into a state that allows analysis.
In 1957, the ticker tape was the way raw market information flowed.
"Tape readers" processed the tapes.
People divided the trading day(s) into profit segments.
That is all that is necessary today as it was then.
I would say from about 1790 onward, the reading of the markets was known publically.
By 1959 when Darvas's book was published following a Time magazine article, it was widely known just how to make money in markets.
Market data was processed by individuals into segments for profit taking.
Then as now, it is a deductive process that involves the exact science where volume and price are interrelated.
If you read this, then you get to be able to DO it.
The computer science part is to DO it the way computers do any data processing.
Computer science has a 101 level, that is all that is needed. It is applied to the raw market data.
Use a gerund approach for both V and P. Use an if, then form for connecting V and P.
The statements used to process data are arranged so that mathematics is honored for the algebra, the relationships and everything is in the same language, meaning everything is in "like kind".
Who do we owe the mathematics principles to that are applied?
George Boole gave us the Agebra around 1842.
Carnap and Keynes followed.
Most people cannot understand my commentary. It is too precise and exact.
For me, I am going to forward the consideration of how the exact science got subverted by the public over time.