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follow BayAreaObserver 2017 Jun 14, 5:31pm
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If you haven't read my opening missive (link below this sentence), please do, as it's important.
Like Something Out of 'The Twilight Zone,' This Market Is About the Machines http://realmoney.thestreet.com/articles/06/14/2017/something-out-twilight-zone-market-about-machines?cm_ven_int=homepage-latest-headlines
This column extends the conversation about the problem with advanced market technologies and strategies a step further than most retail and institutional investors understand.
Most people think of artificial intelligence and algos as simply executing logical rules programmed into them by humans â€” the same rules that the programming humans would follow if they were presented with the same data and data analysis. The algos and AIs are doing it in the same way humans have always done and would do, but at a much slower speed or perhaps not at all because of the very weak and distant relationship of some data items to other data items.
The general belief is that algos and AIs are just "faster humans able to do a lot more calculations in a meaningful time frame". That may NOT be a correct characterization of some of the more powerful AIs that may be working in the markets. Of course, we don't know what AIs are working because there are no regulations requiring that machine decision-making accounts disclose and register as such â€¦ a very, very big gap in regulation.
True, AI and the related "machine learning" developments at the leading edge of such technology do NOT simply duplicate human rules and logic. Instead, while they may perform simple repetitive correlations initially on data as humans currently formulate that data, the more advanced machines go on to program themselves at successive layers, where the data being analyzed and correlated is no longer what we think of as data. Rather, it is often data artifacts created by the first layers in a form that no human would ever consider or has ever seen. To put in a more street-level way, the first level creates ghosts and apparitions and shadows that the second layer treats as real data on which it assesses correlation and predictability in the service of some decision asked of it. AND â€¦ a third and fourth and on and on are doing the same thing with output from each layer below it.
The result of this procedure is striking and terrifying when the the leading experts in AI and machine learning are interviewed. They admit that they have no way of determining what rules AI and machine- learning powered machines are following in making their decisions AND we cannot even know what inputs are being used in making those decisions.
Think about that. The creators have no knowledge of what their creations are thinking or what kind of inputs the machines are thinking about and how decisions about that are being made. The machines are inscrutable and, most terrifyingly important, UNPREDICTABLE.
We are not telling these AIs how to make decisions. The machines are figuring out how to decide to "make a profit" on their own and subject to no enforceable constraint.
The resulting risk of "flash crashes" â€” to lump all sudden and unexpected behaviors into a catchphrase â€” is unknowable but probably much greater than anyone even dreams. The machines have no fear of flash crashes or any other kind of crash. Such crashes might even serve their purpose of "making a profit."
Be forewarned as last Friday's Nasdaq schmeissing may be a walk in the park compared to what may happen in the future.
The risks are much greater than most imagine.
Much More: http://uschnews.com/doug-kass-not-even-the-algo-creators-know-what-is-going-on/
#Investing #Stocks #Trading #Finance
while they may perform simple repetitive correlations initially on data as humans currently formulate that data, the more advanced machines go on to program themselves at successive layers, where the data being analyzed and correlated is no longer what we think of as data. Rather, it is often data artifacts created by the first layers in a form that no human would ever consider or has ever seen
Exactly. It all boils down to this.
1. Humans try to estimate the value of a company. This sets the stock price.
2. Humans figure out they cannot do this, so they resort to educated guessing. Stock price is based on the aggregated guessing of the company's value.
3. Some humans then try to figure out future valuations based on what they guess the other humans are guessing. Stock price is based on the aggregated guessing of the company's value and the guessing of what other people will guess as to the company's value.
4. The amount of guessing of the company value is constant, but the guessing of other people's guesses grows. Stock price is based mostly on the aggregated guessing of how other people will guess, and little to do with the company's value.
5. Algorithms are used to guess how other people guess. These algorithms are executed faster than any human stock trader, so they dominate the market of guessing. Stock price is now determined by how computers guess humans will guess stock prices.
6. Everyone starts using algorithms, which are refined to handle the fact that everyone else is also using algorithms. Stock prices is now based on computers guessing what other computers will guess the stock price is.
7. Algorithms are replaced with deep learning. Stock prices are still based on computers guessing what other computers will guess, but now no human can possible understand how the system works.
8. The machines "panic", i.e. guess that all other machines will rapidly sell causing a self-fulfilling prophecy that takes 23 microseconds from start to finish. The market tanks and the economy follows, albeit at the incredibly slow pace of a few weeks.
9. Armed thugs in assless chaps go raping and pillaging along the former city landscapes. Sensible people have moved to isolated regions and are growing yams after having stockpiled ammo.
Did I miss anything?