Trading Necessitates Speed Along Every Step of the Data Pipeline

Posted by Jon Millis

10.06.2015 01:43 PM

We just returned from Terrapinn’s The Trading Show, a data-driven financial services conference that brings together thought leadership in quant, automated trading, exchange technology, big data and derivatives. With more than 1,000 attendees and 60 exhibitors gathering at the Navy Pier in Chicago, this year’s event was an excellent way not only for us to educate the market about using AI to scale data science initiatives, but for us to learn about the most pressing needs faced by financial services companies.

The first day, Jay Schuren, our Field CTO, presented to an audience of 50 executives. His demo used publicly available data from Yahoo Finance – such as cash flow, valuation metrics and stock prices – to predict which NYSE companies were the most over- and undervalued compared to the rest of the market. To say the least, Jay’s discoveries, as well as the seamless and automated way in which he created his financial models, spurred heavy booth traffic for the rest of our trip.*

Finance is an interesting animal. Many industries have relatively straight-forward applications for machine intelligence. Utilities companies are often interested in daily demand forecasting. Manufacturing companies look to optimize processes and design new materials. Retailers want to determine the best locations to build new stores, while healthcare providers want to preemptively detect and treat diseases. But finance is a bit different.

Let’s take a timely analogy. As I was walking home last Friday, I saw probably half a dozen limos of Boston high-schoolers posing for photos and heading to prom. Most of our customers purchase Eureqa and just can’t help but gush to us how excited they are to go to prom with us. Leading up to the big day, we show off our dance moves (give them a live demo), and take them out for a few dates (send them a free two-week trial), and by the end of our brief tryout, they’re bursting with energy and telling us all about their plans for the big dance with us. Trading firms, on the other hand, are the stunning mystery girls.** They’re smart, they’re confident, and you don’t think they should be shy, but when you ask them to prom, they shrug their shoulders and indifferently and say, yeah, I guess that sounds cool. You raise an eyebrow unsure if you just got a date or got slapped in the face with a frozen ham. But then she sees you drag racing around the neighborhood, and all of a sudden, you’re the biggest heartthrob on the planet. What in the world just happened?

In the trading world, everything is about speed. It’s not only about the speed at which a company can execute a trade (though there were plenty of vendors there offering to shave off fractions of a second to do this), but it’s also about the time it takes for a firm to arrive at an answer about how their market works, whether that’s determining when a currency is undervalued, an asset is likely to significantly appreciate, or a large loan is too risky. Everything in the trading game revolves around timing. And everyone. Loves. Speed. Where Eureqa instantly became interesting to attendees was the automation from raw data to accurate analytical/predictive model, a process that Eureqa consolidates – and accelerates discovery – by orders of magnitude.

A majority of trading technology on display was new hardware and software that incrementally improves time-to-execution. Milliseconds are important, but implementing a trading strategy that no one else has thought of or discovered could be game-changing. Nutonian will never compete with these other products and services directly. But we’re bringing more than one date to prom.


* Email us at for a live demo of this particular application. We’d love to share our current use cases in financial services and explore how we might be a fit for others. 

** We’ll ignore the fact that, in reality, it seems like a “trading” prom would be about 95% guys. Woof.

Topics: Big data, Eureqa, Financial Services, Machine Intelligence, The Trading Show

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