Tackling DeFi Option Vaults And Our Quantitative Process
The Reaper Team is hard at work developing option vaults and champing at the bit looking to release the best product currently available on the market. Here’s a little primer on the quantitative research process the Byte Masons have been sculpting and a sneak peek at the future alpha users should be entitled to.
The world of DeFi options is rapidly evolving, and there is considerable opportunity for investors to take advantage of this development. On the other hand, the very nature of options entails additional risks to consider for investors and protocols alike in comparison to that of spot markets. Options are derivative agreements. Market participants use derivative agreements to exchange cash flows in the future based on an underlying value. Therefore any derivative market is reliant and impacted by the behavior of said underlying market’s characteristics. That being said, in many respects, that impact has a multiplication effect. Throughout this article we will touch on this in greater detail. As we look to take advantage of the opportunities and alpha options can generate for users and the Byte Masons alike we must ensure proper quantitative evaluation and processes of strategies and products we want to build.
Options PnL in DeFi and Building on Lyra AMM
Looking at the current state of DeFi Option Vaults, the strategy selection is limited in large part to covered calls and covered short puts. In other words: long spot + short calls and long spot + short puts. Both strategies have the same PnL payoff structure, in that the risk is substantial as the underlying can go to zero and and the reward is limited to the premium collected on the option, which simultaneously means the extent of covered downside is the value of the options premium. That is why these strategies are commonly used for sideways markets and lower implied volatility. As soon as volatility results in price moves over the coverage a premium will offer, these strategies create substantial downside risk and loss of opportunity by capping the upside. We strongly recommend reading Samneet Chepal, CFA’ s article A Quantitative Analysis of DeFi Option Vault Strategies who gives a detailed look into the strategies and their performance, to fully intuit these concepts.
Building on Lyra AMM
At the moment Lyra AMM, operating on Optimism and Arbitrum, is where Reaper gains to build options vaults on top of. Polynomial’s Earn V2 vaults for example, successfully deployed sETH and sUSD put and call selling vaults above Lyra’s tech stack. Many have recently come to find that although they are technologically proficient, they, at no fault of their own, aren’t exactly profitable to investors. Whether that is due to the current market structure or the baseline options contracts they’re working with, or a combination of both is still yet unknown, for us to speak on. However, Lyra recently announced a major update where they will be building with Synthetix’s V2 Perp vaults and that might be telling us a large share of the story in and of itself. Perpetuals inherently contain less constraints and variability then Calls and Puts. Their absence of built-in directionality presents a curious opportunity for Options Vaults collecting premiums from sellers or buyers. Whatever may be, Options present the opportunity for trade-volume-of-scale, unparalleled leverage and greater hedging abilities that spot just can’t offer… and joining ourselves at the hip to the tech stack that will make them common place investment vehicles, on-chain, seems like a net-net for our firm and the DeFi community.
Our Quantitative Analysis Timeline
It goes without saying, we need accurate reads on strategies for our vaults that will not only be secure and safe but also, profitable. Our best chances at achieving this is through quantitative analysis, modeling and backtesting. That’s why I’ll be breaking down the steps that will be needed to produce the necessary outputs to accomplish our quantitative goals, as well as the infrastructure that shall be used and produced throughout our project. As of now I will only include the pre-trade process of the analysis in this text. The trade and post-trade steps will come subsequently with more simulation and production testing.
We define our pre-trade process in the following three steps:
- Gathering, parsing, cleaning, and consolidating of relevant data.
- Modelling and computing of necessary parameters of strategy.
- Backtesting of parameters and retrofitting to historical data.
- Simulation of outcomes with parameters and calculation of probabilities.
- Implementation and design of vault strategy.
In the world of DeFi options, with the current readily available infrastructure, the hardest step is the first one. Running a Python script using price, liquidity and volume data can get us somewhere and produce some pretty sweet findings for the spot market. On the other hand, proper quantitative analysis for options requires rigorous financial math and just simply more variables to tabulate. With non-institutional open-source APIs, our ability to fetch this directly from the blockchain is limited and would require a sizable investment to establish.
As for points 2, through 4, the process will be iterative and lots of the financial math code we’ve already written or is readily accessible from reputable quants across the Python community. Altogether they will hold their own unique set of challenges and we will touch on some of them here and most on a touch-and-go basis.
Options versus Spot
In order to fully understand the where, what and why that is needed for this project let us just break down our challenges and the problems we’ll be solving. Options trading in the world of crypto bring in a new definition of being “stuck holding the bag”. For example, in 2021, the price of the YFI experienced a significant drop due to a flash loan exploit, resulting in significant losses for those holding option contracts on the token. DeFi has undergone violent liquidity expansions and crunches in the span of 2020 to 2022. The danger of holding agreements for asset-exchange at a future date stems, not only from the volatility and potential (dollar denominated) losses but also from the potential massive liquidity and network usage changes that the option vault may be faced with. This is when the multiplication effect of options is felt, through huge slippage and gas costs.
To effectively manage the risks associated with DeFi options trading, it is essential to have a thorough understanding of the underlying assets, as well as the various statistical measures and metrics used for evaluation. Moreover, it is crucial to evaluate this in the context and infrastructure of the blockchain we are planning to build or invest on. Centralized exchanges cannot provide us with the actual data from the on-chain vaults. Irregardless, by acquiring relevant data and computing these metrics, we can make more informed decisions about the potential risks and rewards of different options strategies.
Options Data in the World of Blockchain
Now what kind of data do we need to evaluate an option trade? For example, historical volatility can be used to measure the past volatility of a particular asset, while implied volatility can be used to estimate the future volatility of an asset based on market prices. Traders will use both types of volatility and their relationships to each other to value options. For example, if implied volatility is much lower than historical volatility, the option is undervalued, if the inverse is true, it’s overvalued. The greeks can also be used to measure the sensitivity of an option’s value to different factors, such as changes in the underlying asset’s price, time to expiration, and volatility.
Once we acquire historical data of the following, we can also compute and compare different models and parameters to historical data. Take strike price for example, Comparative analysis of different strike price models can give us valuable information about the potential profitability of different strategies. By comparing the fair value strike price, which is the price at which an option is expected to trade based on a fair-value model, to the actual historical strike price, we can see how closely the market is pricing in the expected value of the option. This can give us insight into market sentiment and the level of volatility in the market. Additionally, comparing different strike price models can also give us insight into the relative value of different options and help us identify potential arbitrage opportunities.
Next Up
On a more practical note, the next step for us is solving the on-chain data retrieval problem that comes with getting historical and real-time data for volatility, liquidity, strike price, time to expiration, volume and the actual order book from Lyra AMM. We are currently garnering a potential partnership with Amberdata who currently offers the most extensive ready-made suite of options data infrastructure across DeFi. Using centralized data can give us a feel for a strategy but foregoes very important variables that are much different in DeFi, such as liquidity and network usage.
All things considered, that is how our cookie is crumbling at the moment.
That said, we will be periodically updating you all on our analysis, so stay on the lookout for some sweet alpha and our upcoming Reaper Option Vaults!
