First A.I. ETF Claims It Can Replace An Army Of Research Analysts

“Look Dave, I can see you’re really upset about this. I honestly think you ought to sit down calmly, take a stress pill and think things over.”

 

From Stanley Kubrick’s 2001: A Space Odyssey.

As if MiFID II wasn’t bad enough, now this “EquBot AI Technology with Watson has the ability to mimic an army of equity research analysts working around the clock, 365 days a year, while removing human error and bias from the process.” That is the claim of Chida Khatua, the ETF’sCEO.Unlike the existing algos used by quant funds, A.I.   the ability to learn from its mistakes without further requiring programming.

This week, EquBot LLC, in partnership with ETF Managers Group (ETFMG) launched the world’s first ETF powered by artificial intelligence, the AI Powered Equity ETF (NYSE Arca: AIEQ). According to Business Wire, the new ETF uses “cognitive and big data processing abilities of IBM Watson™ to analyze U.S.-listed investment opportunities”.

For those in the dark as far as “Watson” is concerned, it’s Wiki entry notes “Watson is a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. Watson was named after IBM"s first CEO, industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! and, in 2011, the Watson computer system competed on Jeopardy! against former winners Brad Rutter and Ken Jennings winning the first place prize of $1 million. Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage…but was not connected to the Internet during the game. For each clue, Watson"s three most probable responses were displayed on the television screen. Watson consistently outperformed its human opponents on the game"s signaling device, but had trouble in a few categories, notably those having short clues containing only a few words.”

Business Wire explained how EquBot makes investment decisions “EquBot’s approach ranks investment opportunities based on their probability of benefiting from current economic conditions, trends, and world- and company-specific events, and identifies those equities with the greatest potential for appreciation. EquBot and ETFMG expect the fund’s portfolio to typically consist of 30 to 70 of U.S. equities only and volatility comparable to the broader U.S. equity market…the fund’s underlying technology is constantly analyzing information for approximately 6,000 U.S.-listed equities, including company management and market sentiment, and processes more than one million regulatory filings, quarterly results releases, news articles, and social media posts every day.”

According to Chida Khatua, CEO and co-founder of EquBot LLC “Machine learning is one of the most powerful applications of artificial intelligence. As powerful as many algorithms underlying expensive quantitative hedge funds and other vehicles might be, unless they’re also built with AI and machine learning baked right in, mistakes can be propagated and opportunities for outperformance can be missed.”

Neither of the founders is lacking in confidence when discussing the potential for the new ETF. From Business Wire “With the launch of AIEQ, we’re not only bringing our new fund to market,’ said Art Amador, co-founder and COO of EquBot. ‘We believe we’re pioneering a whole new investment category; one that will soon have investors and advisors diversifying their portfolios among passive, active and AI approaches”

He added “Everyday, there is more information, not less. That information explosion has made the jobs of portfolio managers, equity analysts, quantitative investors and even index builders more challenging.”

He"s not wrong there.

A.I. might be the future of investing, although there have been funds that were so good (LTCM), they didn’t need to post collateral. This is different, obviously as we’re not just talking about a bunch of really "brainy" humans.

But how sad will it be if we go from this...

To this...

To this...

An end up with this...

The regulators are already doing their best to make the investment world less fun.

“Open the pod bays doors, HAL”

Writing about this, we were reminded of another life or death confrontation between humans and technology in Stanley’s Kubrick’s “2001: A Space Odyssey”, which also had an oblique reference to an IBM computer. In the movie, there is an argument as to whether the failure of an antenna is due to human error, as the HAL 9000 insists, or HAL, as Mission Control advises. In the ensuing conflict, HAL initially gains the upper hand, kills Poole and almost kills Bowman. Bowman manages to re-enter the ship and get to HAL’s processor core, regressing HAL to his first programmed memory.

“I know everything hasn’t been quite right with me, but I can assure you now, very confidently, that it’s going to be alright again. I feel much better now.”

 

Records Of 198 Million US Voters "Accidentally" Exposed By RNC Contractor

While the Republican National Committee was allegedly busy evading Russian hacking attempts during the campaign, one of the contractors tasked with running its big-data operation apparently stored some of its most-sensitive files on an unsecured Amazon server that could be accessed by anyone who stumbled across the URL. As the Hill reports, Deep Root Analytics left a database containing 24 terabytes of data, including information about 198 million potential voters, or virtually the entire eligible population. The data included sensitive, but publicly available, information like voters’ addresses and phone numbers.

But more interesting than any personal information involved in the leak was the insight into Deep Root’s "big data" modeling tactics. The data included probabilities for individual voters’ positions on dozens of political issues, as well as estimates of how they voted in past elections. It also provided some insight into how big-data firms collaborate, as identifiers in the data suggest some of it was provided to Deep Root from TargetPoint and the Data Trust, two other big-data firms used by the Republicans.

Here’s the Hill:

“For example, a 50-gigabyte file of "Post Elect 2016" information, last updated in mid-January, contained modeled data about a voter"s likely positions on 46 different issues ranging from "how likely it is the individual voted for Obama in 2012, whether they agree with the Trump foreign policy of "America First" and how likely they are to be concerned with auto manufacturing as an issue, among others."

That file appears in a folder titled "targetpoint," an apparent reference to another firm contracted by the RNC to crunch data. UpGuard speculates that the folder may imply that the firm TargetPoint compiled and shared the data with Deep Root. Another folder appears to reference Data Trust, another contracted firm.”

One UpGuard analyst who spoke with the Hill said he looked himself up in the data and that the estimated preferences were right on the money.

Gizmodo went into more detail about the exact nature of some of Deep Root’s models, including one that was used to predict voters’ opinions about the oil and gas industry in the US.

“One exposed folder is labeled “Exxon-Mobile” [sic] and contains spreadsheets apparently used to predict which voters support the oil and gas industry. Divided by state, the files include the voters’ names and addresses, along with a unique RNC identification number assigned to every US citizen registered to vote. Each row indicates where voters likely fall on issues of interest to ExxonMobil, the country’s biggest natural gas producer.”

“The data evaluates, for example, whether or not a specific voter believes drilling for fossil fuels is vital to US security. It also predicts if the voter thinks the US should be moving away from fossil-fuel use. The ExxonMobil ‘national score’ document alone contains data on 182,746,897 Americans spread across 19 fields.”

Some of the data were apparently scraped from various subreddits, including, bizarrely, the banned subreddit “r/fatpeoplehate.” As Gizmodo noted, this is likely an attempt by Republicans to match social-media profiles with individual voters, a technique at Obama’s 2012 reelection campaign pioneered.

“Some of the data included in Deep Root’s dataset veers into downright bizarre territory. A folder titled simply ‘reddit’ houses 170 GBs of data apparently scraped from several subreddits, including the controversial r/fatpeoplehate that was home to a community of people who posted pictures of people and mocked them for their weight before it was banned from Reddit’s platform in 2015. Other subreddits that appear to have been scraped by Deep Root or a partner organization focused on more benign topics, like mountain biking and the Spanish language.”

“The Reddit data could’ve been used as training data for an artificial intelligence algorithm focused on natural language processing, or it might have been harvested as part of an effort to match up Reddit users with their voter registration records. During the 2012 election cycle, Barack Obama’s campaign data team relied on information gleaned from Facebook profiles and matched profiles to voter records.”

Reddit was an important locus of activity for Trump supporters during the campaign: it was the medium where they would create memes and share news stories that countered the mainstream media narrative. The subreddit currently boasts more than 440,000 members. Deep Root was paid handsomely for its efforts. The Hill, citing FEC data, said the firm collected $983,000 from the RNC between January 2015 and November 2016, according to Ad Age.

Though Deep Root has characterized the leak as an oversight, it still amounts to the largest leak of voter information ever.

“It dwarfs the second-largest exposure of voter information — 93.4 million records of Mexican citizens — by more than 100 million voters and tops the largest data breach of voter information — 55 million records of Philippine voters — by more than 140 million."

For its part, Deep Root said it was merely using the data to help target TV ad-buys. “Deep Root Analytics builds voter models to help enhance advertiser understanding of TV viewership. The data accessed was not built for or used by any specific client. It is our proprietary analysis to help inform local television ad buying."