Quote from: MTL4 on November 26, 2019, 02:35:55 PM

Quote from: Gumbi on November 25, 2019, 05:47:36 PM

@MTL4
The Socrates premium analysis does go long or short hypothetically a number of positions based on the election of reversals from the daily to the monthly time level which I believe is the same as the chart you posted for example the Dow premium analysis monthly commentary says "we are currently hypothetically long 4 positions at this particular moment on the monthly level"

Armstrong mentioned that phase II of Socrates will add a backtesting feature to see what Socrates wrote on any given day.
https://www.armstrongeconomics.com/products_services/socrates/progress-report-on-socrates-deployment/

I think at this time we just don't have access to the chart which would be very helpful but there is still many other features that need to be added to the pro service

Gumbi, this is the issue I have with what you are saying. If you are really using this system to trade you need to know exactly when you are in/out of a position even if you are occasionally wrong (you can be wrong over 50% of the time and still have a winning strategy). All successful trading systems I'm aware of have very strict rules for exactly this reason and they must be followed at all times for it to work. As a trader I don't want to read some verbose consulting report every day which may say "we are currently hypothetically long 4 positions at this particular moment on the monthly level". Trading takes hard work and hours during each day are very limited so why not cut to the chase. You are given tons of technical BS with Socrates but the issue is you are still being left to decipher it (I have yet to see anyone do this on a consistent basis). If the system is that good then have it (computer is the expert, right?) interpret the info for us and display it in a table or chart. That way there's no room for error and everyone wins. I really don't see why this is even remotely hard to do even with my relatively low computer programming skills. You'd think that would be priority #1 when designing a system for financial folks to use.

MTL4,

I could not agree with you more. The user is not even getting an expert system that executes the rules that exist around Socrates to pick what to trade under what condition. Interestingly, Martin Armstrong claims that Socrates goes way beyond the quality of an expert system, talking about such systems as if they were a fraud:

Artificial Intelligence & Neural Nets – Sorting out Truth from Fraud

Give that some consideration.

The truth however is, that Socrates has been designed to be ambiguous and never give a definite answer for one purpose: To put the burden on the users, and be an engine to sell additional services such as seminars and training that would then provide the secret sauce for success.

To build a system that has a reasonable chance of trading success on the current core is impossible. I can say that because I am a programming expert who has coincidentally studied Socrates for years. To give you a rough idea: The system is one-dimensional in a sense that for every market it looks at, it looks only at this market, not any other market, no correlation with anything. More specifically, it looks only at past history in a single time frame, one at the time without any artificial intelligence whatsoever.

Proof: You have to combine the information of forecast arrays in all time frames yourself. The computer is unaware of its own surroundings. Such is "AI" in Socrates. That why I call it a contraption, not a computer system.

If, on the other hand, the system would hypothetically do what you request it to to, and be successful in doing this, then it would not be available as a service. Because it would generate more profit for a single operator than what can be generated by selling it as a service.

Martin Armstrong is a charlatan, and he spent 11 years in jail for a reason.

Read this blog starting at page 273 to find out more about computerized fraud.

See armstrongecmscam.blogspot.com for a more compact view of major findings posted in this blog.