A framework for decentralized index funds performance analysis and design
Using the Sharpe & Sortino ratios to optimize risk-adjusted returns
What are the Sharpe and Sortino ratios ?
The Sharpe and Sortino ratios are 2 fundamental indicators widely used in traditional finance to help investors understand the adjusted return of an investment compared to its risk.
The Sharpe ratio is the average return earned in excess of a risk-free rate per unit of volatility, or total risk. Volatility is a measure of the price fluctuations of an asset/portfolio, and is characterized by the standard deviation of the portfolioâs excess return :
Here is an convenient way to memorize how this formula works when evaluating the performance of an asset, or comparing in with another :
- The larger the average return and the smaller the volatility, the bigger the Sharpe ratio.
- For two assets with the same average return, the asset with the smallest volatility has the biggest Sharpe ratio.
The Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the assetâs standard deviation of negative portfolio returns âi.e. downside deviation onlyâ instead of the total standard deviation of portfolio returns.
Therefore if we adapt the above phrasing, the mnemonic becomes :
- The larger the average return and the smaller the downside volatility, the bigger the Sortino ratio.
- For two assets with the same average return, the asset with the smallest downside volatility has the biggest Sortino ratio.
Both indicators can be used to weigh an entire portfolioâs / index performance against its intrinsic volatility :
âĄď¸ The higher the Sharpe ratio of a portfolio / index, the better the historical return on investment relative to overall volatility â both up and down.
âĄď¸ The higher the Sortino ratio of a portfolio / index, the better the historical return on investment relative to overall volatility â only to the downside.
What crypto investors are ideally looking for is making most of the explosive growth phases, while minimizing drawdown when the market is bearish : thatâs why my personal preference goes to using the Sortino ratio, because I find it better suited to the highly volatile nature of digital assets.
One might argue that these indicators are mainly suitable to evaluate an assetâs / portfolioâs historical performance, but not to build a strategy that can help optimizing its future performance. Letâs dig a bit further into this !
What this framework is and isnât about
Before we go any deeper, some important things to mention : the whole point here is not to pretend that a methodology based on the Sharpe & Sortino ratios miraculously predicts any market move, or automatically picks-up the best performing & risk-proof assets. There are already several interesting machine learning approaches which attempt to do this.
Fundamental research is another way to uncover high potential crypto projects â sometimes even before they get listed on any exchange â which makes it difficult to compute any metrics for them.
However, a vast majority of crypto investors often bid randomly on projects, either because they are somehow convinced of their explosive growth potential, or because they have exploded alreadyâŚ
Few beginners develop a longer term approach, and aim to build a portfolio with long-lasting performance while minimizing the effects of volatility. This is where index funds and rebalancing techniques get interesting, gaining exposure to a wide range of assets while reducing the downside impact of the least performing ones.
Decentralized index funds, which composition is governed and revenues shared among blockchain-based communities, are developing at a quick rate and enable investors to do precisely this, with different baskets of digital assets.
I strongly believe that they will play a major role in the establishment of the open, trustless financial ecosystem of the future. Not only they provide, like ETFâs in traditional finance, an easy exposure to the sectorâs mind-blowing growth, but they also entice shareholders to gain revenues or governing power from their initial investment. Thatâs where the magic of composability and programmable money kicks in.
Hence the idea to use the Sharpe and Sortino ratios to not only characterize the performance of the existing decentralized index funds, but also to explore new ways of optimizing an index composition. Everything required is just a daily price feed of DeFi crypto assets and a good spreadsheet editor !
The state of the art
Letâs cut a long story short : in the table below are summarized the annualized Sharpe & Sortino ratios of the 6 biggest decentralized index funds since their respective inceptions:
Note : the calculation was started on October 19th for DEFI+L, and manuelly corrected for sDEFI to avoid a big price jump due to the $AAVE migration.
So you could argue that, due to its earlier inception right in the middle of the DeFi summer, $sDEFI benefited from more upside of its underlying tokens than the indexes that were built after that.
Letâs take a look at the same metrics again, but this time calculated with the same starting point (December 1st to accommodate for the latest addition, which is PowerPoolâs PIPT):
This version is more flattering for $DPI but doesnât change the overall picture in terms of rankings with $sDEFI / $DEFI+L / $PIPT showing the best risk-adjusted performances.
Interestingly, DEFI+S is lagging quite a lot behind, suggesting that the bet on low-cap / high growth potential tokens currently isnât the most risk-proof.
But another interesting aspect is why DPI âs performance isnât as good on the longer timespan ? This can be explained by the fact that the composition of this capitalization weighted index has long been dominated by the Synthetix ($SNX) and Maker ($MKR) tokens, which do not have the best Sharpe or Sortino ratios. Even Compound ($COMP) & Uniswap ($UNI) are showing good performance metrics, but it turns out theyâre not the bests in their class :
Proposal to optimize the risk-adjusted return of a decentralized index fund
In fact, a lot of DeFi tokens have shown much better risk-adjusted returns since their inception :
What would have happened if a fund equally composed of these 17 tokens, had been launched on November 6th (as soon as $ALPHA listed on the market) ?
Well, to date the annualized Sharpe & Sortino ratios would be respectively 5.07/7.93, which would put us just shy of the sDEFI index in the overall rankings above !
If we did the same calculation only for the month of December, the Sharpe & Sortino ratios would be respectively 0.74/1.14 which is less encouraging but gives less scope for the lower cap, high growth potential coins to recover from downside volatility.
In the coming weeks / articles, I will be further tracking this portfolio and propose an optimum rebalancing threshold to cut this downside volatility. Stay tuned, stay safe, enjoy your dear ones and the holidays as much as the current situation make it possible !
Julien
Who am I and what am I doing ?
Everything started at the end of summer 2019, when I decided to take a break from my engineering career. Having worked for several prestigious car companies, I wanted to explore new perspectives and fell deeper in the DeFi rabbit hole.
Passionate about blockchain and cryptos since 2018, I have indeed been through a steep learning curve, starting from noob to overcoming my beginnerâs mistakes by professionalizing and educating myself relentlessly.
Doing so, I especially became aware of the incredible potential of decentralization in building a more open, more transparent, fairer financial system and society as a whole.
Today, I want to create an environment which allows traditional investors to experience all of this in the safest and most accessible way possible, while also preparing their portfolio for the next 100 years.
Thatâs what Iâm building for the French community with Monportefeuille.digital. Because I enjoy writing and reading so much, I have created bloom.finance to share a part of this work with an international audience.
