Using Artificial Intelligence To Analyze Markets: An Interview With Ainstein AI CEO Suzanne Cook

Investing

To learn more about the use of artificial intelligence at it may be applied to analyzing stocks and markets, I asked the CEO and originator of Ainstein AI about her work in this area.

Suzanne Cook is a Wharton School graduate and a seven-time Institutional Investor All Star Analyst.

According to her LinkedIn bio, “Mrs. Cook anticipates a new golden era of research – high frequency automated research – thanks to the trifecta of (1) cloud – cheaper and more accessible computing, (2) scale analytics – unifying vastly expanded data sets, and (3) autonomous pattern recognition via artificial intelligence.”

Here’s how our conversation went:

John Navin: When artificial intelligence experts talk about “natively intelligent portfolios,” what exactly are they referring to?

Suzanne Cook: Let’s compare natively intelligent portfolios to the current portfolio offerings – not smart (analytics not built in), not in the cloud and not intuitive, as they lack visualizations.

A modern portfolio offering, such as Ainstein Cubes, is considered natively intelligent for 3 reasons:

  1. Analytics are built in, and automated
  2. Delivered in the cloud
  3. Features visualizations, for instant comprehension of pertinent facts (including hidden risk) and guidance on the next best action.

Banks and brokerage firms can elevate their legacy portfolio offerings by adding Ainstein Cubes.

Navin: What type of complex multi-level information are we talking about here?

Cook: Ainstein takes in a lot of information – many sources and many feeds – and automatically does the work of creating institutional grade analytics for stocks, bonds, ETFs and mutual funds.

By contrast, today this work is done at great expense by in house experts, but without consistency, updated only periodically, not streaming live with latest data, and limited in breadth, not available for all ticker symbols.

Ainstein’s research and data assets are also connected to personalized portfolios, and displayed in Cubes. The detail is provided in the research gateway, so those who would like to drill through and learn more easily can.

Ticker symbols are rated, and color coded, so at a glance users can see red (risky) holdings and green (safe) holdings.

In contrast to Ainstein Cubes, legacy portfolios are generally displayed in tables, and ratings are rarely updated.

Navin: In your work, you mention”the rhythm of earnings season” — although I have a sense of what you mean, what specifically are you referring to that AI might help with?

Cook: Public companies report quarterly earnings 4 times per year. December quarter earnings hit in February, for instance. During the 4 reporting months, pressure is intense for both the company’s filing their earnings with the SEC and the armies of analysts, portfolio managers and investors trying to make sense of the dynamics and read thousands of press releases.

With the type of AI materials we provide people will no longer struggle mightily during earnings Season, as they now do. Nor will they endure intense time pressure during those dreaded four months. Nor will they face considerable do-or-die career risk and heavy expectations that they will somehow successfully navigate the flood of earnings reports and stay ahead of others.

Navin: When you mention “risk metrics,” which ones do you mean?

Cook: All risk metrics – the Ainstein system is highly tuned to look for risk from many sources and angles. The goal is to minimize risk and increase clarity – in order to improve decision making.

Navin: In your work, I’ve seen that you refer to “intuitive learning algorithms.” So, this is machine learning, right?

Cook: Yes. The key here is how the machine learning is accomplished. There are many forms and methods.

Navin: Is it simply matching to prior patterns or can the machine learning identify new patterns?

Cook: The former will be limited. The latter, which is the more forward looking system, will be superior for applications to Wall Street data, where past patterns may not be valid, applicable or informative.

Navin: You’ve written that DARPA “defines 3 waves of AI and the 3rd wave is the most promising” — tell me about this. What are the 3 waves and why is the 3rd considered promising?  

Cook: The 1st Wave was “handcrafted knowledge” – a rules-based systems.

The 2nd wave (now) is statistical knowledge…systems that can train on data currently available. DARPA calls this level “excel spreadsheet on steroids”

The 3rd wave is contextual adaptation — these are systems that themselves will over time build explanatory models to characterize classes of real world situations and phenomena. Autonomous platforms that generate explanations and create contextual models that can reason. Aka Ainstein.

Navin: Are you saying it’s better than basic fundamental analysis (ala Benjamin Graham) and basic chart pattern analysis (support/resistance levels, trend watching)?

Cook: All the traditional approaches (fundamental, technical, and more) are built into the Ainstein system as features and inputs to the decision making. Today, people prepare for a career working in finance and gain mastery by spending years of training to learn how to themselves individually collect data, comprehend it, and take action. Once in these jobs, they generally spend many hours on end staring into desktop workstations, in order to monitor and extract data and then draw conclusions.

Some succeed with this approach, but many fail. Considerable investor assets are put at risk with this old fashioned approach. Can technology provide a safer, better way?

With artificial intelligence programs like Ainstein, people have help at each step, and are able to shift some of the work load onto the technology. This simplifies the job and helps people see what to do in one step versus many.

Navin: Suzanne, thanks.

My Forbes interview with a professional poker player who beat artificial intelligence is right here.

I do not hold positions in these investments. No recommendations are made one way or the other.  If you’re an investor, you’d want to look much deeper into each of these situations. You can lose money trading or investing in stocks and other instruments. Always do your own independent research, due diligence and seek professional advice from a licensed investment advisor.

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