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.
Probabilty was the greatest and permanet subverter of people getting to be able to trade. The PC doesn't do probaility for most people, however. another el primo consideration is how raw data makes its way into the minds of PC users. Amost no one ever gets to "see" the markets. There are many many crutches that get in the way. A reference for what is what might be a good idea. Do a print of a zig zag chart; it tells you diectly the potenial of taking the market's offer. Do the crayola test on the print. This lets mostly everyone know rightfrom the start that they are not doing anything related to Boole, Carnap or Keynes to extract the offer of the market.
Who were some of the great guys who first used mathematics to produce "indications" of what the market was doing? How did the public mess up the works with misusing the indicators that were invented? In any profit segment, what is told to the trader about market sentiment? How are indicators so clear about this characterisitc of price segments. So why don't potential trader know how to "read" indicators in a way that is as super as the tape readers of the Ticker Tape era.
Why didn't the public follow the lead of guys like Dodd, Granville, Dunnigan and Darvas? The answer is fairly straight forward. Read the interviews and the reporting on these people. Darvas is knocking off millions by reapplying his capital and doing the same thing over and over again. He is "watching" the trap Dunnigan sees and then he trades the last move of the trend established by the trap. He sees the three moves in a trend clearly and precisely. All four use volume as a leading indicator of price. How did they get that viewpoint and why, today, is that lost on most potential traders. A large percentage of traders fail. Today and for the last few years "price action" has become the "buzz word of beginners and their respective vendors and brokers. All these people described volume and price using gerunds. NONE of these people had computers. could the computer be a fundamental cause of failure by most potential learning traders. Are most learning traders learning failure. Andrew Lo of MIT monitors big money traders. He discovrs their psychological condition while trading is one of anxiety, fear and anger. He is correct in how he pegged the emotions of traders. What is going on? I guess we need to look at the sources of these failures (emotionally and in trading the markets.)
And yes, Marsh`s Trade Zones are still working clock-work. Undercapitalization remains huge problem for those few who know how to use raw information.
Willingness be smarter faster and brighter then others. But prices usualy peak or bottom after the market, not before.
Some people will agree with you, others will not. For me it is not on the table. I only use RTH data to automate the market's orffer. Go to ant platform and request the egapping tool for that platform. Once you have that inplace non RTH's have dissappeared. Now you can begin to look at the pieces and at some pont you can put the pieces together.
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. This is a compound sentence. Two ideas are connected by a conjunction. The first idea: The rawest of information yields that the dimensions of the market are all discrete pieces. This idea has a subject and a predication about the subject. the subject is information that streams to anyone, stream by stream in a raw form. Read the words of computer science majors who are also, on the side, "analytic.". They cannot handle any of this raw steeaming data for some reasons. As the predication states they are befuddled by the pieces in the stream and they cannot process this data into anything that expands the degrees of freedom. Expanding the degrees of freedom is what gives a potential trader facts that can be used with the rules of operation of the market. So, in a word, the expansion of raw data is done to add degrees of freedom to the data and make it more informative. The handicap is that the stream comes with pieces and the pieces are given by their issuance in some manner or means. A person who is going to add degrees of freedom has to have replete full knowledge about the manner and the means of this issuance. The computer scienc major steps up to the line and recognizes that there are many many tools for dealing with streaming batches of information where the batches issuance is fully and wholly prescribed. The list of tools is usually found on the tool box cover or in the instruction manual for using the tools. Each piece of data comes from a market operating event introduced by the participants in the market. All is know about how the market is operating as the stream of events occurs. "the market is wholly defined by simple rules of operation by its participants." This idea's subject is how the market is defined. the market is defined by the participants who use the market. Those other than participants also do the "talk" aspects of markets. Anyone who wants can talk about the market BUT only the participants set up their rules of how the market operates. Individually and collectively, this rule of market operation scope and bounds act as what is today in computer science 101 called a "cloud". Participants make and define their individual rules of market operation. Most often they do not share these perceptions of how the market operates. I did, however. Two questions surround this. One is WHY? and the other is WHY NOT? You didn't get the sharing of my perceptions, apparently. You may want to remedy that. I felt that sharing how the market works and how to take the market's offer eddectively and efficienctly was a good general idea. The consequence could have been that then people could have more wealth and they could use some of their money and time to help solve local problems. This viewpoint is probably not very functional. For example, you may not want to share but you do , perhaps, want to have the information of just how the market works and just how to use that information to make money. Probably your comments are not really a requext at all. You are just expressing your attitude towards someone such as me. There is an informal filter in any type of forum. Over the spectrum of ET there are people who devour and make use of the expert solutions for extracting the market's offer. there are also people who are so handicapped that they will never even see the markets in their lfetime. Its fun to watch the entire spectrum. Wanting to be an outsider is especially sappy.