Technology has progressively changed the dynamics of financial markets. Decentralized Finance (DeFi) is sending seismic waves through the landscape of finance. The active asset management space is no exception to this disruption.
In the early 2000’s, it became clear that computer systems had completely reshaped the market from its days on physical trading floors (1, 2). Stock exchanges and trading portals found themselves in an arms race to build and enable more sophisticated technology around data throughput and availability, order matching capabilities, and execution speeds.
On the new highly-technical playing field, market participants themselves became ever-more savvy. Smart order routing, high frequency trade execution, and availability of live order flow data now tilt the financial markets in favor of large, highly technical, players. Michael Lewis’ book, Flash Boys, helped bring public attention on how wall street was being reshaped by asymmetric access to information and execution of trading decisions.
In furthering the sophistication of trading techniques, machine learning is now a regularly leveraged tool for assisting or automating strategies. These algorithms are used to predict or forecast price action (1, 2), respond to breaking events, and automate the implementation of trading strategies. In an age of near instant information transfer, many hedge funds and prop shops rely on artificial intelligence (AI) to interpret and act on news sentiment, shifting capital flows, or market inefficiencies to stay competitive.
Alexander Fleiss, CEO of Rebellion Research, an AI think tank, financial advisory group, and hedge fund, shared his experience and insight on AI augmented investing and capital management. Two of the most important aspects to establishing a successful AI investment strategy, he said, are choosing the right data and methodology of processing that particular data. “Decent input can be turned into a good product with an inferior algorithm, but bad data can not be made into a worthwhile product, no matter how powerful or awesome the machine learning or math behind your algorithm,” explained Fleiss.
The advent of distributed ledger technology (DLT), namely in the form of a blockchain, has brought yet another wave of innovation which is disrupting the global financial markets. Bitcoin, the first DLT, is competing with central bank fiat currencies and attempting to serve as an alternative monetary base settlement layer. Higher complexity blockchains like Ethereum are enabling decentralized finance, and are broadly competing with today’s commercial banks, legacy financial institutions, and fintechs.
Open blockchains, as opposed to centralized databases, render data on financial activity available to the public. This data can then be leveraged by active investment strategies; “funds will be able to see in more real time fashion the movements of a number of industries. Funds pay to have forward knowledge and blockchain is ideal for showing inflection points in consumer or society behavior as soon as possible” added Fleiss.
But blockchain implicates the active investment space more than just changing what type of data is available to investors. DeFi applications, built of composable open source protocols, open the possibilities for new types of products and funds entirely. Many decentralized applications function by virtue of aggregating capital into liquidity pools which serve the role of a market maker. Liquidity providers (LPs) lock funds into a contract and then earn yield generated from the fees or other incentives associated with it. Other applications which facilitate lending markets or derivative instruments similarly provide a mechanism to earn yield. Additional incentives, such as distribution of governance tokens to LPs and users, are used to attract capital away from competing protocols, keep capital within the system, and to give participants a say and stake in the application itself.
Even less exotic fixed-rate USD stablecoin lending protocols, such as Yield protocol or Notional Finance offer far more attractive rates than banks give. It’s no wonder then, with such attractive yields on more passive investments, that capital continues to pour into DeFi; according to DeFiPulse.com, there is over $113 billion in value locked (as of Nov 15th) in DeFi protocols. Although TVL is a crude metric, and susceptible to some forms of manipulation, we can tell that the ecosystem is growing dramatically quickly.
Given how rapidly the space moves, the volatility of rates, the technical risks associated with various protocols, and how steeply rewards often decline – investors must be quite savvy to compete in getting the best return.
Projects like YVaults by Yearn Finance or BentoBox by Sushi, are ways which allow investors to make a single deposit which then routes through various strategies attempting to capture the highest yield. Vault products help mitigate costs associated with rebalancing or moving between protocols, especially for smaller balances. They also help engage in more exotic strategies, such as those leveraging options, without having to manually execute them yourself.
As more and more protocol-agnostic vault strategies emerge, competing platforms need to even further incentivize users to choose them. Convex Finance (token CVX) has capitalized on this by allowing these platforms to “bribe” CVX holders to provide liquidity to their system. CVX holders can simply buy, stake, and even lock up their tokens (for boosted rewards) and attempt to capture more yield and flexibility than their would otherwise as Curve.fi liquidity providers while simultaneously earning additional rewards through this feature.
As the DeFi ecosystem becomes ever more complex, saturated with more capital, and markets become more interconnected/efficient, we may expect to see similar trends to those we have seen in traditional finance. Alexander M. Ineichen in his 2006 book, Asymmetric Returns: The Future of Active Asset Management, which predicted a paradigm shift from buy and hold to active management focused on absolute return, wrote that “as markets become more and more efficient, carving out all the alpha will be increasingly difficult without using all of the risk management tools available.”