Following Upward On Facebook's Regulatory Risk Is Existent Too It Is Magnificent (Fb)

Some tips on frontrunning the algorithms as well as the hazards of shorting inwards a bull market.

Here's the introduction to March 19's "Facebook's Regulatory Risk Is Real as well as It Is Magnificent (FB)":

So far this yr nosotros convey had over 30 posts on TheFacebook, every bit it was 1 time known, amongst almost all of them beingness critical of the fellowship inwards 1 agency or another.
The risks highlighted tin move broken downward into iv wide areas:

1) The media backlash to having their concern models undermined yesteryear Facebook as well as Google.
2) The surveillance capabilities of the platform companies as well as the privacy/security risks they pose.
3) The deliberate addiction of users brains via neurotransmitter manipulation as well as psychological engineering.
4) The role of the to a higher house characteristics yesteryear political operators to gain their ain ends as well as the diverse outrages, imitation as well as otherwise, elicited.

Our motivation is pretty straightforward: How tin nosotros brand a buck or 2 off what appears to move going on?

Recognizing opportunity earlier the computers produce is 1 approach. The muddied petty clandestine of machine learning is that the computers tin real rapidly categorize what they are witnessing solely if they convey seen the province of affairs previously. We used 1 of the funnier examples inwards the outro from Dec 2017's:

Artificial Intelligence inwards Risk Management: Looking for Risk inwards All the Wrong Places
Opportunity is where y'all detect it, plough your opportunity director into a net income center. ...
From naked capitalism, Nov 15:...

...AI cannot deal good amongst dubiety because it is non possible to develop an AI engine against unknown data. The machine is actually proficient at processing information nigh things it has seen. It tin handgrip counterfactuals when these arise inwards systems amongst clearly stated rules, similar amongst Google’s AlphaGo Zero (Silver et al. 2017). It cannot argue nigh the time to come when it involves outcomes it has non seen....MORE 

e.g.

"When Google was grooming its self-driving auto on the streets of Mountain View, California, the auto rounded a corner and  encountered a woman inwards a wheelchair, waving a broom, chasing a duck. The auto hadn’t encountered this earlier as well as thence it stopped as well as waited."

—Markets as well as Waterfowl: Machine Learning Is Only As Good As the Training It Receives

This introduction is getting a combat wordy as well as thence we'll chop things into a twosome to a greater extent than posts tomorrow precisely that's the premise, await for risks that AI hasn't even as well as thence been trained on inwards an endeavor to gain some asymmetric advantage.
If, inwards the meantime y'all tin convince yourself y'all are performing some form of societal good, all the better. Speaking of the meantime here's some proficient insight until nosotros acquire or as well as thence to parts II as well as mayhap III.

And the result:

FinViz

Too much stress, non plenty compensation for beingness correct on the thesis as well as incorrect on the timing.
Our full general rule: "Only curt frauds inwards a bull market"