A new paper proposes that emerging technologies (blockchains, Big Data and artificial intelligence) have increased pressure on the traditional hedge fund fee structure of 2 + 20.
Its author is Wulf A. Kaal, an Associate Professor at the University of St. Thomas and director of the Private Investment Fund Institute.
Kaal, who worked for both Cravath Swain and Goldman Sachs (NYSE:GS) before beginning his academic career, operates from the generally acknowledged fact that fees are of late under downward pressure. The historical annualized management fee of 2% of assets under management has become just 1% for new managers, and has fallen into a range between 1.5% and 1.8% even for established managers.
There is pressure on the incentive fee side, the 20% on returns, as well, although it shows itself in different ways. There is a trend for example, especially within the PE world, toward “blackened carry.” This means that managers cannot collect their “carry” until all the LPs have had their capital returned to them. “A similar trend,” Kaal writes, “is observable in the hedge fund industry.”
Ways to Use Blockchains
Another important data point, then, is the recent trend in the private investment industry toward the use of blockchains, a technology associated with (but broader than) cryptocurrencies such as bitcoin. Kaal writes, “While some funds simply focus on trading bitcoins (GDAXUSD) … to avoid market fluctuations…others go much further by fully automating a hedge fund secured by blockchain technology to improve administrative procedures of private equity dealmaking.” In February 2017, for example, Northern Trust (NASDAQ:NTRS) partnered up with IBM (NYSE:IBM) to create a blockchain that would offer a more efficient approach to the administration of PEs.
The current deal practice in much of the PE world, Kaal says, involves the reconciliation of a lot of copies of documents, whereas the new Northern Trust/IBM blockchain allows all the involved parties to look at a single tamper-resistant compiled version of the transaction and related data.
Incentives and Game Theory
Another use of blockchain is as a way of awarding and co-ordinating incentives. February also saw an example of this use: a press release by Numerai, a hedge fund with a global equity strategy. Numerai operates on the Ethereum blockchain, and the press release said it had issued one million crypto-tokens to its data scientists by way of encouraging competitive cooperation among them to make the predictions out of which it will in time create a meta-model.
Numerai itself has explained its system as akin to a solution to the “prisoner’s dilemma” at the foundations of game theory. In that dilemma, each prisoner has a simple choice: rat on the other prisoner, or keep silent. The interrogators keep the prisoners isolated, so each thinking of his own options in isolation comes to think of ratting as the opimal solution. If each rats on the other, though, they get the worst possible result. Thus, in the classic PD scenario individual self interested behavior harms the interest of both parties.
Numerai, in an article posted on its website, says that in order to understand its own plans, one should “suppose the prisoners are issued a cryptocurrency similar to normal money except for one small change: it is programmed to self-destruct whenever anyone goes to prison.” This would change the incentives by making it impossible for either prisoner to consider his own options in isolation from those of the other.
Numerai, likewise, believes its currency “Numeraire,” makes collaboration compatible with self-interest. So says the website.
Theoretically and Empirically
But let us return to Kaal. Although his paper is a brief one, Kaal looks at the consequences of blockchains for fees both theoretically and empirically. Theoretically, the use of blockchain and related technologies enables the hedge funds that make use of it to undercut their competitors on fees, and thus contributes to the downward fee pressure. One way it does this is by allowing manmagers to switch to a transaction-fee model, which prior to the development of this technology involved “a prohibitive amount of work” and the risk of human error in calculation or settlement.
Empirically, matters go as theory indicates they should “The majority of private fund advisors that use blockchain technology, artificial intelligence, and big data in different aspects of their operations or strategy charge their investors lower fees,” Kaal concludes.
The bad news, then, for those who derive their income from those fees, is that if Kaal is at all correct, the downward pressure will intensify.