Marc Andreessen famously said “software is eating the world”, and nowhere is this truer than in the hedge fund industry.
Niche strategies are being replaced
A decade ago, my colleague Tammer Kamel was a portfolio manager at a large hedge fund company.
In this role, Tammer got to inspect and dissect the strategies employed by the world’s leading hedge funds at close range – the perfect job for a curious quant.
One common strategy he investigated at the time was called factoring, which capitalised on the large windows of firms’ accounts receivable.
Hedge funds would advance the creditor 90 per cent of the receivable instantly, wait three months for the full 100 per cent payment from the debtor and pocket the 10 per cent spread.
It’s a low-risk, high-return way to make profits, and at the time dozens of hedge funds did it, but that’s no longer a common strategy and technology is one of the main reasons this is happening.
Start-ups like C2FO, FundThrough and Fellow follow a classic factoring strategy, but they use the internet to reach a wider range of creditors than a single hedge fund manager could ever hope to, and they use scoring technology to offer better interest rates.
Software has disrupted this source of alpha.
Another common strategy from the early 2000s was litigation financing.
Hedge funds would lend cash to plaintiffs in cases with large potential payouts, in return for a share of the winnings.
Legalist, a Y-Combinator 2016 start-up, plans to do exactly that and has already started building a database of past case results that will allow them to invest scientifically in high-probability outcomes.
YieldStreet, a similar start-up on the east coast, has already launched a number of litigation investment vehicles.
It’s not just plaintiffs and creditors whose income hedge funds would like to anticipate.
Securities linked to the earnings of athletes, entertainers and celebrities (‘Bowie Bonds’) have long been part of the hedge fund playbook – and now there’s a start-up for that too.
Fantex is a brand management start-up that advances cash to athletes in return for a fixed share of their lifetime income, and it already has NFL and MLB stars as clients.
These examples are just the tip of the iceberg. What’s happening is that Wall Street’s used-to-be-clever money-making activities have been disrupted.
Core activities are being disrupted
Consider securitisation, perhaps the single most important financial innovation of the past 40 years.
The key premise of securitisation is that while it’s impossible to accurately forecast the behaviour of a single asset, it’s possible to bundle many assets together and slice them into smaller tranches with predictable behaviours.
Investment banks have made tons of money by packaging assets this way and hedge funds have made tons of money exploiting inefficiencies in the securitised credit market.
This is not the case anymore.
With the rise of start-ups offering financing for individuals (Avant, Prosper, Borrowell), for small businesses (OnDeck, BondStreet, Kabbage) and for students (SoFi, CommonBond, Earnest), the ecosystem that allowed credit-focused hedge funds to thrive is slowly withering away.
The distribution power of the internet is replacing the old network of loan officers and underwriters, while data science is replacing tranching as the best way to manage risk.
Same for the now (in)famous currency carry trade, where hedge funds would profit by borrowing in one country at a low interest rate and lending in another at a high interest rate. There’s a start-up for that too –Berlin’s WeltSparen.
Equities are not unscathed. Consider technical investing. In the past, it took a skilled and experienced trader to discern repeating patterns or detect underlying trends in the market.
Today, start-ups like Kensho, Sentient and EidoSearch use natural language and image/signal processing, machine learning and other sophisticated data science techniques to analyse billions of historical records and replicate the insights found by these traders, but they do it faster, cheaper and better.
Fundamentals-based investing may be equally vulnerable, thanks to start-ups like AlphaSense, that generate investment ideas from community predictions and by searching through research documents.
Additionally, even if a new hedge fund manager were to devise a brand new trading strategy, the emergence of algorithmic platforms like Quantopian, Darwinex and Rizm, along with community sites like SumZero, eToro and StockTwits, means that ideas don’t stay proprietary for long.
It’s only a matter of time before they are replicated at low cost by a start-up, and robo-advisers like Aspiration could soon do to hedge funds what Betterment and Wealthfront are already doing to mutual funds.
How will hedge funds react?
The phenomenon of knowledge, skills and technology diffusing through a market is not a new one. We talk about it all the time, but how will the hedge funds themselves react?
“The best firms have realised that the time to adapt was a few years ago,” said Adam Honore, founder and CEO of MarketsTech, LLC.
“And there’s not just one way to do that. Some funds are becoming the best data science firms in the world. Others are focusing on non-quantitative efforts, which aren’t easily disrupted or replicable in code,” Mr Honore said.
“We’ve even seen funds diversify into higher barrier-to-entry domains like market making. Lastly, many funds have started venture groups of their own to capitalise on the disruption in their own space.”
Finally, a number of funds have changed the battlefield altogether.
If technology no longer offers them an advantage, they will shift operations to an area where they do have an edge. Increasingly, that edge is data.
Hedge funds are increasingly reaching to ‘alternative data’ and other sources of esoteric informational advantage to drive their investment strategies.
Having information that others do not has always been a reliable method of making money.
As long as the information remains unique and protected, this method is immune to disruption or alpha dissipation, either from other hedge funds or from software start-ups.
Preferential access to alternative data could be what finally replaces proprietary skills, technology or models as the differentiating factor for successful, long-lived and disruption-proof hedge funds.
Abraham Thomas is the chief data officer and co-founder Quandl.