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OTAS Technologies’ Tom Doris is creating machines to do (part of) a trader’s job

interview with fintech investor, Dan Ciporin

Tom Doris is CEO of OTAS Technologies

What’s OTAS all about?

Tom Doris, OTAS Technologies
Tom Doris, OTAS Technologies

At OTAS we use big data analytics, machine learning and artificial intelligence to extract meaning from market data and provide traders and portfolio managers with insights that would otherwise lay hidden. Our decision support tools help traders to focus on what’s important and interesting, you could say that we use machines to identify the areas that humans should be paying attention to.

I did my Ph.D. in artificial intelligence, and around 2009, it was clear to me that several of the more sophisticated hedge funds were converging on a set of approaches to market data analysis that could be unified and made more efficient and general by applying algorithms from machine learning and artificial intelligence.

Better yet, it quickly became clear that the resulting analysis could be delivered to human traders and portfolio managers using natural language and infographics that made it easy to absorb and action. At the same time, the role of the trader was becoming increasingly important to the investment process, while the problem of executing orders was becoming more difficult due to venue fragmentation, dark pools, and HFT, so it was clear to me that there would be demand for a system that helped the trader overcome these problems.

How does leveraging artificial intelligence for trading help traders and portfolio managers make better decisions and manage risk?

Experienced traders and PMs really do have skill and insight. With all human skills, it is not easy to apply the skill systematically. We can leverage AI to help humans scale their investment process to a larger universe of securities, and also to ensure they apply their best practices on every single trade.

In many professions, everyday tasks are too complex for a human to execute reliably, for instance, pilots and surgeons both rely on extensive checklists. Checklists aren’t sufficient in financial markets because hundreds of factors can potentially influence a trader’s decision, so the problem is to first find the factors that are unusual and interesting to the current situation. This is the task that AI is exceedingly good at, and it’s what OTAS does. Once we’ve identified the important factors for a given situation, machine learning and statistics help to quantify their potential impact to the human, and we use AI to generate a natural language description in plain English.

What is compelling the increased use of artificial intelligence and big data analysis in financial services?

A basic driver is that the volume of data that the markets generate is simply too much for a human to analyze, but the more compelling reason is that AI and machine learning are effective and get the results that people want. Intelligent use of these techniques gives you a real edge in the market, and that goes to the firm’s bottom line.

How do you see artificial intelligence and big data analysis playing a role in trade execution in the future? Any predictions for 2016?

AI is going to provide increased automation on the trading desk. Execution algorithms have already automated the task of executing an order once the strategy has been selected by a trader. Now we’re seeing a big push to automate the strategy selection and routing decision process. The next milestone will be to see these systems in wide deployment, and with it will come a shift in the trader’s role; traders will have more time to focus on the exceptional orders that really benefit from human input. Also, the trader will be able to drive the order book in aggregate according to changes in risk and volatility. Instead of manually modifying each order, you will simply tell the system to be more aggressive, or risk averse, and it will automatically adapt the strategies of the individual orders.

What’s the biggest challenge in acquiring new customers in your space?

Traders have largely been neglected in recent years as regards technology that helps them to make better decisions. Even when the benefits of a new tool are clearly established, it can be difficult for the trading desks to get it through their firm’s budget. Despite the recent hype around HFT and scrutiny of trading, there’s still a lag when it comes to empowering traders with the best information and tools to support them.

Photo credit: k0a1a.net via VisualHunt.com / CC BY-SA

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Tradestreaming Cascade: The news you need to know (week of October 2, 2011)

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Every week, I send out an email (free) to my subscribers summarizing the must-see events of the past week. It’s everything about the intersection of technology, social media and investing.

Sign up in the sidebar, at the end of this post, or by going here.

You’ll get your 1st issue on Sunday.

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A better solution to socially responsible investing (Larry Swedroe)
A recent study shows that there is a price to pay for socially responsible investing: namely, raising the cost of capital for sin stocks.  That said, Swedroe recommends avoiding SRI and donating the difference in returns to an investor’s favorite charity.

New jobs package should open up crowdfunding (Amy Cortese/NYT)
A friend of Tradestreaming, Amy Cortese penned a New York Times editorial describing some of the changes tabled in the Obama administration’s new jobs package.  This one — with rare bipartisan support — may change the way small businesses raise capital and how investors can tap these new sources of returns.

Continue reading “Tradestreaming Cascade: The news you need to know (week of October 2, 2011)”

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The Path: From Novice Investor to Master – with Adrienne Toghraie

retirement investing

Join Adrienne Toghraie, master trading coach, and me on Tradestreaming to discuss the psychology of trading as she shares practical, actionable tips to better investor performance.

In this special edition of Tradestreaming, we discuss:

  • finding and staying in your zone
  • 4 steps for bettering use of trading time
  • how to discover your ideal strategy
  • 10 rules to be more professional in your practice
  • how to learn and make mistakes well
  • much more!

Continue reading “The Path: From Novice Investor to Master – with Adrienne Toghraie”

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Tradestreaming Panorama (week ending September 18, 2011)

Every week, I send out an exclusive email (free) to my subscribers summarizing the events of the past week.  It’s everything about the intersection of technology, social media and investing.

Sign up in the sidebar, at the end of this post, or by going here.

Bogle’s Blunders, intellectual honesty and historical perspective (Dorsey Wright):
To the guys at technical analysis shop, Bogle appears as a rigid idealist and someone unwilling to admit that his ideas might have seen their time.  Apparently, Bogle believes investors only misuse ETFs and not index funds.

Should investors overweight companies with overweight CEOs? (Time):
Turns out fat CEOs equal fat profits according to a study in Psychological Today. There seems to be correlation between the width of CEO faces and financial performance. It’s like going long blockheads — but hey, the study posits all types of reasons for this (aggressiveness, imposing people don’t get as much pushback, etc.)

Continue reading “Tradestreaming Panorama (week ending September 18, 2011)”

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Insight into the Twitter hedge fund

This is interesting.  Here’s an interview with Paul Hawtin, founder of Derwent Capital Markets (the Twitter hedge fund).

the twitter hedge fundI find this compelling because it’s one of the first hedge funds that’s designed (so publicly, at least) to trade on changes in social media sentiment.

According to MoneyScience, you’ll learn:

  • How the Twitter hedge funds’s signals are computer
  • Operational set up and infrastructure of Derwent
  • Trade generation
  • The “Michael Jackson” Test: Is the Twitter hedge fund an automated black box?
  • Risk Management
  • Will large scale analysis of social media be part of quant trading and investing from now on?
  • Who is invested in the Twitter hedge fund?
  • Capacity, Target return

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Top Investment Resources for Sentiment Analysis

The holy grail for investors — and one being frantically searched for by technologists, entrepreneurs, and investors — is to find a way to program machines to decipher social media (or more accurately, unstructured text) and structure a trading system around it.

Sentiment analysis (the ability to pull out what people are feeling by the words they’re using online) is one of the next big things in investing. Here are a few of the resources investors may want to consider when learning about sentiment analysis and portfolio management.

Have any suggestions? Add your own below.

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Who needs the trading month? Just buy the first day

Tradestreaming (blog and book) is all about finding tested investment strategies that perform better/smarter.  They can perform better than us trying to outsmart Mr. Market (the majority of individual investors underperform the market) and they perform better than just buying an index fund and letting it fester away in your IRA.

I wrote recently about a strategy that entails just owning the market while it’s closed and selling when it opens (it rocks, by the way).  Continuing upon this meme of finding tested strategies that don’t require investors to just blindly buy-and-hold (or as some call it, buy and pray), I read a recent post on first of month trading results by the guys at Stock Trader’s Almanac.

It turns out the average returns on the first day of each month over the past 13+ years for the Dow Jones (DJIA) are greater than all the other days put together.  This is also documented in the newest version of  the 2011 Stock Trader’s Almanac (affiliate link) on page 62.  Check the book out.

According to the research:

Over the last 13.5 years the Dow Jones Industrial Average has gained more points on the first trading days of all months than all other days combined. While the Dow has gained 4417.74 points between September 2, 1997 (7622.42) and February 1, 2011 (12040.16), it is incredible that 6021.31 points were gained on the first trading days of 162 month

Resources

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Want to make money in the stock market? Own it only when it’s closed

Great piece from the guys at Bespoke on a strategy they call Close to Open. While owning the S&P500 or its proxy, the ETF $SPY, since its inception in 1992, investors would have seen  a 193% return.

Not too shabby.

But instead of just buying and holding (or “buying and praying” as I like to call it), if investors had bought the $SPY at the end of each trading day and sold it when markets opened the next morning, investors would have seen their holdings rise by almost 400%!

This raises the question — why even trade when the market is open?

You say, no frickin’ way.

Well, Bespoke says, way.

Like the fabled, flux capacitor, the implications of this are just mind-blowing.

Source

Who Needs the Trading Day (Bespoke Investment Group)

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The new new carry trade in the age of derivatives

Investors have made money for decades by borrowing in one currency with a low interest rate and exchanging it into a higher interest rate currency.  Called the carry trade, it made a lot of people of lot of money.

A new paper out by Della Corte, Sarno and Tsiakas has found another way to profit off the carry trade.  These economists use the forward volatility in foreign exchange to derive a very profitable strategy.  According to their research, Spot and Forward Volatility in Foreign Exchange, investors can buy and sell what’s called a forward volatility agreement (FVA).

Simply put (kinda), thes FVAs attempt to predict future volatility in a certain currency.  More specifically, the FVA sets a forward implied volatility by making a guess about future spot implied volatility.  These guesses tend to be wildly off:

Forward volatility is a poor predictor of future spot implied volatility

So, if forward vol is a bad predictor of future vol, investors can design strategies to take advantages of this.

For example, buying (selling) FVAs when forward implied volatility is lower (higher) than current spot implied volatility will consistently generate excess returns over time.

Interesting idea — as for me, I’ll stick with momo stocks like $AAPL and $PCLN but this sounds like a promising strategy for forex traders.

Source

Della Corte, P, L Sarno, and I Tsiakas (2010), “Spot and Forward Volatility in Foreign Exchange”, Journal of Financial Economics, forthcoming. Centre for Economic Policy Research Discussion Paper 7893.