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We asked 7 alt data leads at big names like Bridgewater, Point72, and Man Group how to pitch them on new data feeds. Here’s how to win them over.

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Here’s what gatekeepers at banks, hedge funds, and other financial firms look for when they’re buying alt data sets.

Shayanne Gal/Business Insider


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  • The alternative data industry, which sells the unique datasets used by investors to gain an edge, has seen a boom in recent months due to the coronavirus pandemic.
  • Business Insider profiled seven executives at some of the leading hedge funds, banks, and trading shops that are handling their firms’ consumption of alternative data. 
  • Those profiled detailed how they use alternative data, what types of data they are interested in, and how they like to be pitched by data vendors.
  • Visit Business Insider’s homepage for more stories.

It’s been an interesting 12 months for alternative data.

After a red-hot 2018, the industry faced some growing pains in the latter half of 2019, as multiple alt-data providers restructured their organization. The space overall was going through a massive expansion, and hedge funds were quick to cut feeds that they weren’t getting value from.

The same privacy concerns that have nipped at the heels of big tech firms made its way to the industry as well, and consumers of alternative data now had to grapple with data sets suddenly going dark overnight.

However, for all the issues the industry has faced, the coronavirus pandemic — and its impact on the markets — has reinvigorated interest in alternative data. Unhappy with traditional market data, which has failed to keep up with rapidly-changing markets and proved less valuable, investors have turned to these wonky data sets, which include everything from credit-card data to satellite images, for what they believe are timely, unique insights. 

While traditional market data, which totaled $32 billion, still dominates Wall Street’s data spend, alternative data continues to require more resources devoted to it.

See more:Credit-card data is broken. Here’s how hedge funds and banks are being forced to rethink one of the earliest alt-data plays.

And so with interest in alternative data arguably back at its highest, Business Insider reached out to some of the biggest banks, hedge funds, and trading firms in the world to get a sense of what their alternative data strategy is, the type of data they want, and how they want to be pitched. 

Here are the seven executives handling some of Wall Street’s top firms’ alt-data consumption. 

At Balyasny, data serves both quants and fundamental traders

Carson Boneck, chief data officer at Balyasny Asset Management

Balyasny Asset Management


For Balyasny Asset Management, a centralized approach is the key to its alternative data strategy. 

Carson Boneck, the chief data officer at the $7.7 billion hedge fund, said in early 2017 several teams focused on big data, data engineering, and sourcing were all brought together to create the firmwide Data Intelligence Group. The goal of the group is to “help improve the hit rate and velocity of our team’s investment ideas and to provide our PMs the very best data platform on the Street,” Boneck told Business Insider via email.

The group works with those on both the fundamental and quantitative side of the business. And while the two sides are typically using alternative data in different ways, there are benefits to pooling resources.

In doing so, Boneck said the firm avoids duplicating efforts, instead making the most of its investment. All teams are able to access and share data. 

“With one data team to collaborate with, we’ve uncovered a multiplier effect in our use of alternative data,” he added. “For example, risk arb portfolio managers might use alternative data to track potential M&A transactions and share this with our index [rebalance] portfolio managers to aid in their process.” 

Boneck said the firm views any dataset with that same lens, looking at how it can be used in different ways by multiple portfolio managers. 

Not unlike others, Boneck said Balyasny’s preference for data formats is to be as raw as possible, leaving the opportunity for the hedge fund’s various teams to uncover relationships. It’s not uncommon for the manager to work with new data providers on formatting data.

Data history is also critical, he added.

“One important characteristic of all the data we leverage is ensuring the data’s history reflects its original form at any historical point-in-time,” Boneck added. “When vendors don’t provide point-in-time data our Data Intelligence Group creates an in-house version.”

Boneck declined to disclose Balyasny’s alt data budget, beyond saying it’s “significant.” 

As for the best way to pitch the hedge fund, details around how data is collected from the source are important, as is its coverage and timeliness. In short, you should know your data back-to-front. 

The firm actually created a self-serve portal, called Antenna, for alt data providers to be quickly evaluated; providers “are able to see descriptive statistics and even the results of risk-aware back tests.”

“Datasets which score well in Antenna are fast-tracked for further internal evaluation,” he added.

Read more:The chief data officer at $6 billion hedge fund Balyasny explains how to merge quantitative and fundamental trading strategies — and the importance of ‘translators’ to bridge the gap

Barclays leans on alt data for the nuance it provides

Ryan Preclaw, co-leads Barclays’ data-science research group

Barclays


The devil is in the details. 

That’s how Ryan Preclaw, who co-leads Barclays’ data-science research group, explained his approach to alternative data. The group, which is made up of an investment sciences team and data science team, publishing reports and analysis for the banks’ clients. 

“The most exciting thing alternative data offers over traditional data is its granularity,” Preclaw told Business Insider via email. “We can provide our clients with actionable insights and answer very specific research questions that would have been impossible in the past.”

From investment to retail banking, their is value across the firm in using obscure datasets, Preclaw said. But there is no specific type of alt data that the UK bank targets. Barclays uses everything from geolocation data, which has proved particularly useful in recent months, to open data, which is usually published by some kind of government entity.

However, when it comes to the format the data is in, Preclaw said Barclays made a strategic choice to have data be as raw as possible.

“We want to be maximally flexible in what we can do with it, even though that means a lot more upfront investment in infrastructure, storage, and algorithm development to turn it into useful information,” he said. “Raw data has two advantages for us: first, we can get answers to questions that might be impossible if we received data in a pre-processed form; second, it puts us into a position to talk to our clients about the nuances of how to work with alternative data.”

While Preclaw declined to disclose the bank’s budget for alt data, he did have some advice for prospective providers. First, it’s important to provide written material about the dataset before even trying to set up a conversation. When a chat does occur, Preclaw said the bank is eager to understand what the data set is offering “in a very specific way.”

“We want to see what a row of your data looks like, what all the features are that you have in it in as plain language as possible,” he added.

Transparency is also a top concern, as is simplicity, Preclaw said. Be prepared to explain the process in a concise way. Tech and salespeople are also encouraged to attend the first meeting to provide a 360-degree view of the data, he said. 

Preclaw also had a piece of advice for something to avoid.

“One thing we are NOT interested in seeing is a back test against returns,” he added. “Those are so easy to do incorrectly that we can’t put any dependence on it unless we’ve done it ourselves.”

See more:How a new Barclays data-science team is fast-tracking research and finding the most useful stats to measure the economic impact of the coronavirus

Bridgewater starts with government data — but has found alt data very useful

Matt Karasz leads the Bridgewater’s macro research team

Bridgewater


The world’s biggest hedge fund starts with government data; it’s got the longest history and often has clear macro implications.

But Bridgewater, the $160 billion hedge-fund manager run by Ray Dalio, is using alternative data more and more, as it helps “us to understand macro dynamics much more granularly and quickly than traditional government data sources would,” according to Matt Karasz, who leads Bridgewater’s macro research team.

“This has been particularly useful as we navigated the uncertainty over the last couple of months,” Karasz tells Business Insider.

“Large shifts in the economy have occurred outside of traditional ‘sector’ lines – e.g. consumers shifting from in-person purchases to online and shifting their basket of consumption in response to the virus – and alternative data has been critical to seeing these shifts play out and understanding how the economy is working under the coronavirus,” he added.

Alternative data does have limitations, he said; narrow focuses, limited track records, and difficulties ingesting it into systems are all obstacles.

But “all challenges worth overcoming if the data is shedding light on an important dynamic.”

See more:‘I’d rather turn them into robo cops’: Execs from Man Group, Bridgewater, and Schonfeld explain how they’re trying to blend humans and machines

Jump Trading is looking for vendors to have a dialogue with

Stewart Stimson, head of data strategy at Jump Trading

Jump Trading


For Chicago-based proprietary trading firm Jump Trading, data usage is all about refining an “existing predictive pattern or possibly present a new one on its own,” Stewart Stimson, head of data strategy for Jump Trading, told Business Insider via email. 

Specifically for alternative data, Stimson said while there is an inclination to focus on its use around equity statistical arbitrage — one of the longest-running quant strategies — it can be used across the firm. What’s key, he added, is balance between the number of observations that can be made from a data source and the frequency with which the data is able to help make accurate predictions.

“If the data is high quality, is unique, and has a large number of observations, there’s a good chance that we are interested in looking at it,” he added.

Jump has also streamlined its consumption of alternative data via a method that normalizes a variety of data structures. As a result, the trading firm has a sliding-scale approach to how quickly it can test a data set.

“While the dream is perfectly structured data in either flat files or a well-defined/architected database, we recognize that part of our ongoing mission in both analysis and talent recruitment is adapting to the curveballs in data structure,” Stimson said. 

As far as budget, Stimson said there is no established number. Every dataset is subject to the value established by it during testing. 

The entire process of sourcing data has evolved greatly in the last few years, he added. Overall, he said Jump is always eager to find new data sources. 

During the initial conversation, Stimson said having a data dictionary, which typically details everything about the database, is crucial. He also highlighted two other key considerations.

“The baseline expectations that we look for in a vendor presenting their data is a representation of fidelity to time in their history first and foremost,” he said. “We also want an understanding of why the vendor is confident that their data is obtained in a way that grants them license to sell this data, as this helps us evaluate the compliance and source sustainability concerns that we need to understand.”

Even if a dataset isn’t right for Jump, Stimson said the firm is open to providing some constructive feedback. 

“We believe this two-way dialogue keeps the door open to hearing more from the vendor in the future,” he added.

Inside Man Group’s ‘data mosaic’

As Man Group’s head of data science, Hinesh Kalian is responsible for the massive firm’s data acquisition strategy

Man Group


Hinesh Kalian, head of data science for the world’s largest publicly traded hedge-fund manager, has a big and diverse organization to think about when he is buying outside data.

There’s quants and discretionary managers, both trying to understand things about companies, the markets, and the world — before they happen. 

“It’s becoming more apparent that traditional data sources typically cannot provide real-time insights into financial and economic health. We are not looking to tackle a specific problem, but rather we are creating solutions to build a data mosaic leveraging a variety of alternative data pieces,” Man Group’s Kalian told Business Insider.

Read more:‘I’d rather turn them into robo cops’: Execs from Man Group, Bridgewater, and Schonfeld explain how they’re trying to blend humans and machines

He views alternative data, broadly, as slotting into three groups: individuals, businesses, and sensors. 

“In the current environment, it’s no surprise that data sources that provide insight into changes in consumer behavior and economic health are very relevant. Data related to consumer spending, footfall traffic measures, consumer sentiment, supply chain dynamics, and employment data are particularly interesting in the current environment.”

While pre-packaged data can seem simpler, Kalian said the $108 billion firm has invested heavily in its ability to clean and sort data in all forms; for vendors looking to get Kalian’s ear, he recommends to “do your homework.”

“If you think you have an interesting product then reach out. It’s important to look at this landscape laterally, i.e. even if the data is used in non-financial industries, there is a chance it can be useful to the investment management community.”

PanAgora is trying to win a race, and uses data to do it

Lei Liu, as a senior portfolio manager at PanAgora, helps shape the firm’s alternative data strategy

PanAgora


Lei Liu views investing in equities as “a race to price in all the relevant information” — and sees alternative data as a way to get there first.

A senior portfolio manager for $34 billion PanAgora Asset Management, Liu is trying to use alternative to both find alpha and help with risk management, so the firm can avoid crowded trades.

Liu tells Business Insider that his firm prefers data in that can be plugged directly into Panagora, and the firm’s budget is based on a cost-benefit analysis — if the dataset is worth it, the company will consider it. 

For vendors looking for an in, Liu suggests that companies “tell us what is the uniqueness of this data and how useful is this data to gauge” businesses. 

Point72 is focused on answering questions

Jessica Fiegleman’s team at Point72 focuses on data acquisition

LinkedIn


Billionaire Steve Cohen’s $16 billion hedge fund uses a lot of data, from traditional sources to obscure, outside feeds.

Jessica Fiegleman, a member of the firm’s Market Intelligence team who runs the data acquisition group, told Business Insider in an email that she focuses “on the fundamental research questions that need to be answered about these companies” when evaluating data feeds.

“We’re careful not to narrow our focus on the signals generated from the data,” she said. 

The firm declined to disclose its budget for alternative data, but noted the infrastructure it has invested internally lets it take data in any format. Fiegleman notes the firm’s analysts, engineers, data scientists, and compliance team are key components to “a successful alternative data strategy.”

For people pitching the firm, Fiegleman advises data vendors look to speak on more than just an individual product.

“Our best vendor relationships are collaborative rather than transactional. We love when a data provider can educate us about their product, and in turn, we can be a part of the evolution of their offerings.”

Read more:

  • ‘A $35,000 data set that could have saved or made $100 million’: Alt data is back in the spotlight — here’s how providers and buyers have adapted.
  • Hedge funds are using these 10 alt-data sources to gain an investing edge and keep track of the coronavirus’ impact
  • Alt data’s Wild West days may be ending as Congress and privacy advocates zero in on the industry. Nearly a dozen insiders tell us how data streams going dark is an ‘unhedgeable’ risk.

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