uEASE: A synthetic token tracking short-term stock price inflation at the expense of long-term company stability

Hey all! This is an idea that I’ve been working on for a while, but I think it has the best chance of success and reaching the right people via DeFi than the more-traditional pathways. I used a modified XIO accelerator competition structure to present it below. Enjoy!

Title of your idea
Calling out poor corporate governance with the Executive Actions for Self-Enrichment (EASE) US equity strategy

Summary Description
Back in March 2020 when the COVID-19 pandemic had thrown the entire world into disarray, the blog Epsilon Theory wrote a piece called “Do The Right Thing”. In it, the author brings to light the actions of the “Big 4” US airline industries and their use of company debt and free cash flow to issue stock buybacks, at the expense of EBITDA and Cash From Operations. Buybacks in of themselves aren’t evil or malicious, but when you’re using debt and FCF to inflate the share price of your company in the short term at the expense of long-term success, that is a sign of a tool being used for nefarious purposes. Why inflate the stock price? Many corporate executives receive compensation in the form of company shares. By issuing buybacks and inflating stock prices, executives are able to sell their shares at higher prices, thus literally enriching themselves at the cost of their company and its non-executive employees. To top it all off, this practice left the Big 4 US airlines without emergency cash reserves in the face of a market downturn…or a global pandemic. Rather than face the consequences of their greedy, myopic governance, the Big 4 US airlines had the bald audacity to ask the US government for bailout funds after bleeding their companies dry. Epsilon Theory was furious. A close friend of mine read the ET article and was furious. He sent it along to me, and I got angry…and then we got to work.
Armed with the idea that “knowledge is power”, we set off to find a way to call out these companies using fact-based research and data. We settled on a scoring system that would attempt to rank US companies by their corporate governance as related to placing more importance on short-term stock prices versus long-term company profitability. We combined US equity pricing data and quarterly financials with SEC Form-4 data. SEC Form-4s are required to be filled out by company executives within 48 hours of any corporate stock being bought or sold. This additional data source allowed to us to complete the thread between buybacks, over leverage of debt/FCF, and executives cashing out post-buyback and extrapolating its effect on long-term performance. This resulted in a research paper as well as our EASE Score, which we publish quarterly on our website free of charge.
While developing EASE, we also looked into its feasibility as an investment strategy. EASE in of itself wasn’t great, but by adding in some new factors into our model, we were able to tweak the output to include a focus on near-term returns in addition to corporate governance. This strategy was dubbed the Near-term Response to Corporate Heuristics (NRCH) and has been paper-trading for almost a year. It’s doing…pretty well. We were considering an ETF for it, but despite the ETF being of the great democratizations in finance over the last half-century, they are 1) cost-prohibitive to start up for those not fully entwined into the finance industry, 2) are beholden to middlemen who are the true profiteers of structured products like ETFs, 3) over reliant on successful marketing rather than successful strategy in order to succeed, and 4) geared toward the wealthier end of investors, further cutting out the low- and middle-class individuals whose retirements/savings/capital could greatly benefit from an ESG strategy that performs well. Unfortunately, popular investment apps like Robinhood have turned the market experience into a twisted gamification of “investing”, ushering individual investors toward active speculative trading instead of long-term buy-and-hold investing, ultimately leading to lower overall returns (and more money for the market makers). A tokenized version of NRCH aligns with both Novatero’s ethos as well as individual investors: hand the control to the many, not the fortressed few. The creation of uEASE (NRCH is already claimed by another token, dang) will allow for a proof-of-concept in our ESG strategy that would be readily available to anyone without gates, barriers, or centralized control. Given the establishment of a pathway to success via uEASE, Novatero would look to expand other strategies into synthetics: we already have a global equity strategy building a track record, but there are others currently in R&D that would benefit greatly from the wide and deep pool of knowledge in the DeFi space.

Which metric will your synth track?
uEASE is a synthetic token that would represent the top quantile (~40-50) of US equities from the Russell 3000 as determined by a variation of our quarterly EASE model that focuses on maximizing short-term returns.

How will you get data for your metric
The EASE Score model is created from pricing, financials, and SEC Form-4 data, but tracking uEASE can be done entirely via publicly-accessible pricing data for US equities across the various public exchanges that house these equities.

What collateral would you use for this synthetic
USDC fits well as collateral, as it is a stablecoin representation of USD, won’t fluctuate all that much, and is the base currency for this equity market.

Describe how you would create this synthetic
The work that YAM/Degenerative Finance has done with uSTONKS has been the big eye-opener to the feasibility of translating ETF strategies to synthetic tokens. Instead of reinventing the wheel, I’d propose an assist or collaboration with them. The 3-month uEASE is just the first stage of what I’m hoping to construct: ideally a new uEASE token will be created every quarter with additional functionality being integrated into the system. As for pricing data, the 2-hr TWAP seems to be the best foot forward and negates a lot of the issues of off-hour price flux.

What issues might you encounter in the development of the synthetic
I’m much more of a quant/MFE type than dev/engineer and am relatively new to the DeFi space, so a lot of my “known unknowns” are in the idea portion versus the structural portion (where there’s a bevy of “unknown unknowns” from my perspective). Based on what I know, I think there’s two issues that might crop up: 1) Transposing an equity investment strategy into the crypto/DeFi space is going to seem…boring? Crypto is to Equities as Equities were to Bonds decades ago: a higher-return vehicle with a higher level of risk and volatility to go along with the “faster” movement of the asset class. Will an equity-based strategy be exciting for anyone, even if it does well? It’ll all depend on the narrative: is corporate governance a fraction as interesting as WSB sentiment? 2) There will be a disconnect between EASE scores as posted on the website and the top quantile used in uEASE, again due to uEASE being a tweaked version of EASE that tilts toward short-term returns instead of corporate malfeasance (the strategy was originally NRCH [Near-term Response to Corporate Heuristics], but it seems that an NRCH token already exists, hence reusing the EASE name). Is the partial disconnect between the EASE scores and the uEASE token going to hurt the narrative? Am I overthinking this? Do I need to stop thinking about this 24/7?

How you would make sure that people who would find the synthetic useful could access it
I’d aim toward adding a simple page or two on the Novatero site as the platform for the token. In an effort to make things easier for investors unfamiliar with DeFi, I’d split “Trade” and “LP” paths and funnel newbies toward the former. Documentation for both paths would be provided; again, Yam/Degenerative’s documentation structure was clean and straightforward to the point that even I understood it, so that would be an ideal template.
In terms of getting the word out, I know a few well-known and respected individuals in the quant finance/FinTwit crowd that could help to spread the word. Ultimately, the best thing to spread the word of uEASE will be the performance of uEASE.

Website & Logo Mockup
There is already a Novatero Investments website up and running, so adding a platform for LP/Trading uEASE could potentially be hosted there, though outside assistance it setting up a platform would be needed due to my weak UX skillz. Logo ideas for uEASE haven’t been mocked up yet; any thoughts are welcomed!

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This looks like pretty interesting and challenging product to launch!
And it seems like a perfect fit for UMA where it could fill the gaps and access problems in the traditional finance world.
Before diving deeper into the subject, do you envision that UMA voters and liquidation/dispute bots would be able to independently calculate EASE scores from raw data and hopefully arrive at the same result or we would need to rely on Novatero provided endpoint as a single source of truth for that? Factors to consider here are availability/cost of raw input data vs having single point of failure. Also the compromise would be that Novatero is providing real-time & historical price API, but there are sufficient instructions available that in case of endpoint availability issues or suspicion of wrong data, one could still do failover and verify correct price for synthetic token independently.

Absolutely! That’s one of the big reasons to head down this path.

Good questions! I’ll attempt to answer them as best I can from my perspective and understanding. Feel free to correct or educate on any misconceptions or gaps in knowledge I might have.

I would defer to precedent when it comes to these things. For instance, were the 10 stocks for uSTONKS arrived at by solely one source, or what there a verification from a secondary source(s)? My base of knowledge comes from the stock index world, where any changes in portfolio assets/weighting are delivered by the index originator (investment company) to the index executor (index company). If it makes a solution any easier, EASE Scores are calculated once a quarter, once all pricing/financial/SEC Form-4 data for the prior quarter is available, so there would be no adjustments in the constituents over the course of the token’s 3-month period. On the pricing side, all of the stocks that would be in the EASE constituent list are publicly-traded US equities; I use “BatchGetSymbols” in R to attain historical daily prices for the quarterly calcs, which pulls pricing from Y!Finance. I’d be interested to know what real-time price sourcing was used for uSTONKS, as I’d imagine it’d be applicable here as well.

The price source was the Google sheets google finance function for uStonks.

It makes sense to use the quarterly calculated EASE score to derive the list of companies (40~50) to be included in the next uEASE creation.

To answer some of your questions:

  1. Transposing an equity investment strategy into the crypto/DeFi space is going to seem…boring?

For the crypto investors, yes. However, your main target audience is investors and funds in the traditional equity finance space, where a few percent returns is still high and desirable. This audience is much larger in term of size, and capital volume. This would be a very valid use case. However, you need to make sure its trading is not mixed up with all the other crypto related synths. Ideally, it should have its own landing page, and entry point for the target audience. UMA is developing something called “UMAverse”, which categorizes different synths into different universe. Before that, we will need you to create that entry point.

  1. Is the partial disconnect between the EASE scores and the uEASE token going to hurt the narrative?

Yes, it will hurt the narrative. However, it’s okay to do what’s practical, and not force something we are unable to support. The EASE score can be the first layer of selection for US companies. There are more considerations, such as, is the price source available for all of these companies? US Stonks use GoogleFinance and YahooFinance API for getting price feed (See here: https://github.com/UMAprotocol/UMIPs/blob/8f195b8d3c7737462d5127388ecfc1088cfe1419/UMIPs/umip-79.md). This means every company’s price information needs to be available through these APIs. In addition, since you’re listing “bad” companies, you will also need to define what happens if any company goes PRIVATE or gets de-listed during your contract duration.

Overall, I don’t see any technical blockers for launching this - implementation will be similar to US Stonks. However, I’m concerned about the incentive for providing liquidity. If a party mints UMA synths, and sells it immediately, the minter (or LP Provider) take a short position on the synth, while the buyer takes a long position on the synth, against the collateral currency. If you’re only listing “bad” companies, how do you plan to generate demand for providing liquidity?

I mentioned this in the UMA Discord, but I’ll add it here as well. The top quantile of uEASE is the companies that either have strong long-term growth factors or a high return probability for the upcoming quarter. The bottom quantile of uEASE are companies that are pumping their stock price up in the short term with buybacks (via overleveraged debt or FCF) to allow executives to reap higher returns on their stock compensation…at the expense of the long-term well-being of their company and its workers. I should have made that much clearer in the documentation. I think that helps clean up some of the narrative, though the addition of return-focused factors can muddy it a little (the top quantile of EASE will not always 100% match the top quantile of uEASE).

A synthetic short of the bottom quantile and/or a long/short strategy are very interesting ideas and ones I’ll run the numbers on in the near future as additional possibilities at a future date.

Agreed on the separate landing page for uEASE and similar synthetics of this nature. UMAverse sounds very promising, as well as Yam’s uSYNTH dashboard. Before those are completed, I can make sure the platform lives either on the Novatero site or on a fresh site away from crypto synth markets. Constructing a platform such as this is outside of my expertise, but I’m willing to learn from the experts and/or those that have done this before.

The Google Finance function in Sheets is very similar to GetBatchSymbols in R; pulling in EOD pricing data from a public source (GoogleFinance for Sheets, Y!Finance for GBS). Given the similarities between the two (GBS even had an option to choose b/t Google and Y! for pricing data in a previous version) and that I remove any tickers that aren’t public at the end of the period prior when calculating the newest EASE/uEASE quantiles, I don’t foresee too much of an issue here. However, a double-check of the uEASE constituents against the GoogleFinance function in Sheets will be run, and if a ticker isn’t showing up, we’ll go with a “next constituent up” substitution based on the output factor score.