How a tiny quant fund started by
It's one of the strange truisms in today's investment world: Traders are drowning in data and yet they still want more. In this age of so-called big data-the term marketers and solution providers call the huge sets of information from various sources-buyside firms continue to look for ways to exploit this endless stream of data to help score the next big deal. At
And they've been tested under fire. Shortly after opening their fund, the
They were "the smartest guys in the world with a really great strategy,"
All that has changed. After beating out the other hedge fund start-ups,
"We never want to be the majority participant in markets and focus on things that we cannot easily enter and exit fairly rapidly," said Barakat.
"Recently, we've been testing and applying the same strategy to cash equities and large market capital cash equities," the COO told Traders. "We have a number of trade strategies that are in the pipeline, as well. We expect to launch our fund vehicle in Q1 of 2014, and that it would be comprised of a basket of highly liquid traded instruments both on the future and cash equities side."
Asked whether they are long/short, Barakat admits his firm is agnostic with regard to direction. "Whatever the signal tells us to trade, we'll trade. We're as comfortable going long as we are short," he said.
THE BIG DATA SECRET SAUCE
Powered by 10 or so servers from a third-party IT service provider,
When asked how many sources of potential information and data the Flyberry Engine scours for new data, Barakat replied, "More than 350," and Chang chimed in with a confident, "Thousands."
Here's how the raw data is sorted: The Flyberry Engine finds the data from those "thousands" of global sources starting with low-latency news sources, and then looks for the best news source in order to obtain and parse the information in a rapid fashion in what they call a bucket. A second large data bucket consists of geosensory information that pertains to earthquakes, weather patterns, forecasts, etc. "Thanks to open-source initiatives from the U.S. and other governments, a lot of these [data sites] have just recently become available that can be highly reliable datasets to explore," Barakat said. Third, the Flyberry engine looks at different social media sources like Twitter and blogs "to see what global sentiment looks like and see if there are patterns that we can observe," he added.
"Using different data sources gives you a much better sense and a more complete picture of the markets than any individual data source can," Barakat said.
INTO THE FUTURE
The Flyberry Engine not only looks for events as they occur-in some cases it also looks at events, such as corporate earnings and national unemployment figures, before they are scheduled to be released. "Big data helps us to identify some potential trend. When a government figure comes out, for example, we can use data to give us better direction. We see all the numbers that might be coming out by aggregating a lot of [past information], and then we try to identify as many events as possible. And then when the information is announced, we try to implement it," said Chang.
For recurring events, the Flyberry Engine will search out the same event for the past five years and gather any and all information related to that event. Why five years? "We have years of data, but it's generally because the electronic market became efficient in the last five years," Chang said.
When it comes to a single, out-of-the-blue event-say, a fire at a factory or a devastating tsunami-the Flyberry Engine will have to work on the fly. "If it's a completely uncharacterized, unexpected event, it's likely that we wouldn't have a model that's been developed to trade off of that event. But in the same fashion, we can use the same big-data techniques to identify if this is sort of a high-risk event," Barakat said. "And that might signal to us when we want to not participate in the market. As a risk management hedge, that's another area where we use the same techniques."
According to Flyberry chief compliance officer David Nichtenhauser, even one-off events can be analyzed beforehand. "Most, if not all, of our models have had events that are recurring. Even infrequent events, like an earthquake, had to occur enough times such that we could test the veracity and robustness of those models."
Nichtenhauser continued, "So if it's a one-time event that's catastrophic or if it's an unusual event like a fire at a Ford plant, it is highly unlikely we'll pick up that event because it's so idiosyncratic and so rare that there is no way to test whether and how the market might respond to it. Now, that's not to say we won't in the future, but we don't have that kind of culling capacity to understand the market's behavior with regard to something that unusual."
DIFFERENT FROM CEP
This may sound like a new flavor of complex event processing (CEP)-the method of trading stocks instantly based on events reported in low-latency news feeds. CEP strategies have been in place in trading firms since the middle of last decade and work like this: If the sole parts manufacturer for the truck division of the
Chang and his team see a big difference between their strategy and CEP. CEP tries to identify those events the traders and portfolio managers already know. When the U.S. monthly jobless claims are announced, for example, a typical CEP trading desk enters in an internal code for jobless claims to look for every type of jobless claims that have occurred, said Chang. They ask for the impact and what would happen to the 10-year note. And that's all they do, he said.
With Flyberry's search engine, they search out various sources of information in relation to the monthly jobless claims. They would look, for example, to see if paycheck processor ADP announced its own private payroll numbers and other sources of information that could be very difficult for those traditional CEP solutions to gather. "You have to know those things in order to link these two things," Chang said.
"This data-intensive method of looking at the markets is still fairly new," said Chang. Further, he doubted that a larger, more established asset management firm-even one with a larger IT budget that Flyberry's-could come up with a system like theirs any time soon. "This is the engine we have been building for more than three years, and right now it's very powerful. I wouldn't be able to imagine some big company building all those things from scratch, because basically what they are relying on is something they had in the past, like high-frequency trading and other forms of infrastructure," he said.
NOT A SILVER BULLET
According to Barakat, the principals inside
"It's a very different approach to what we view it as the future of quant trading, since it's not dependent on price movements or not dependent on momentum. It's not dependent on volatility, but it's about taking surprise events, what's hitting the markets and what's causing major market reaction," he said from his
|Copyright:||(c) 2008 Source Media Inc. All Rights Reserved.|
|Source:||Source Media, Inc.|