No downside for Flipside Crypto with $3.4m funding grab

Data-crunching algorithms have become a popular – and controversial – tool on Wall Street in recent years. Now, they’re starting to be used to guide investments in cryptocurrencies, too, reports Xconomy (FinTech Futures’ sister publication).

The emerging strategy raises a number of interesting questions for the young and volatile cryptocurrency market.

Among them: What types of data should be considered when trying to predict the future value of cryptocurrencies, which – unlike the decades of information available to stock traders – didn’t really take off until the past several years?

Will the algorithms be sufficiently transparent for investors and regulators (a criticism that often dogs their developers)? How predictive can algorithms actually be in this sector? How might this all affect traditional stock markets and the rest of the financial sector?

It’s hard to say how things will play out, but Flipside Crypto will be one of the early test cases. The Boston-based start-up helps wealthy individuals invest in cryptocurrencies, and it develops algorithms to help steer the investment picks.

The company has revealed a $3.4 million venture funding round led by True Ventures, money that Flipside says will help it hone its algorithms and improve its services.

The Chernin Group, Resolute Ventures, Boston Seed Capital, Converge, and Founder Collective also contributed to Flipside’s funding round. True Ventures partner Adam D’Augelli will join Flipside’s board.

To date, Flipside has operated as a sort of data-driven angel network, but instead of making equity investments in start-ups, investors are pouring money into cryptocurrencies.

Flipside has devised algorithms – some modeled on lines of code that equity hedge funds use to guide trades, says co-founder and CEO Dave Balter – to recommend investments in “baskets” of about 15 cryptocurrencies.

The firm also manages the process of acquiring cryptocurrency and storing it – handling potentially confusing things like encryption and digital wallets, for example.

The idea is to find the mix of cryptocurrencies most likely to deliver the best return on investment. That means backing not just the two most popular cryptocurrencies, Bitcoin and Ethereum’s ether coins, but also potentially overlooked and lesser-known digital assets.

For example, Flipside’s first “investment club” also put money into Siacoin, the digital token that powers the blockchain-based cloud data storage service run by Boston-based Nebulous, and LBRY, a New Hampshire-based venture that operates a blockchain-enabled content sharing and publishing platform.

Flipside says its strategy is paying off so far – though it’s early, of course. In its first five months, the group of cryptocurrencies that Flipside’s first “investment club” invested in delivered a 141% return, compared with 92% for Bitcoin and 115% for the Coinbase Index, Flipside says.

It says its second investment vehicle, launched in November, has delivered a 79% return in that time, versus 43% for the Coinbase Index and 11% for Bitcoin itself.

In Flipside’s early investment vehicles, once investors agreed which cryptocurrencies to put their money into, the mix of investments didn’t change. But now, Flipside is becoming an investment manager that will actively buy and sell cryptocurrencies for each of its funds, Balter says.

Balter notes that the firm will not operate like a day trader, but it might “re-balance” each fund’s mix of cryptocurrencies once a month, say. “When we see a trend in data, we make a change,” Balter says.

Flipside’s algorithms analyse three metrics, Balter says. The first is a “speculation” analysis adapted from hedge fund trading algorithms, he says. Basically, it runs simulations of about 40 different trading strategies to see which ones might perform the best, based on historical and real-time cryptocurrency pricing data.

The second algorithm examines the activity of software developers working on cryptocurrencies. “The philosophy is follow the engineers – where people are building, good things will come,” Balter says. Conversely, when the level of developer activity fades early on, it might signal a doomed digital token – or even a scam, he adds.

The third algorithm tries to gauge the “utility” of the cryptocurrency by tracking transactions executed by the network of computers running the blockchain system underpinning the digital currency.

Part of the idea is to identify when a small number of users are executing a large number of transactions, which could indicate a “pump and dump” scheme, where there are “a few people trading between each other in order to make it look like there’s movement,” Balter says.

Some of these data points are starting to prove themselves, but “there is still quite a bit of work to do to create longer-term, sophisticated models,” Balter admits. Still, he says, there’s a “huge opportunity if you can get all of the algorithmic data working together”.