Recently, I crunched the numbers in order to answer the question everyone seemed to be assuming they had the answer to - “what’s the best way to capture ETH beta?”. People think ETH will trend up with time, but they aren’t satisfied with its relatively muted price volatility now that Ethereum’s market cap is well into twelve figures.
The TL;DR of the post was that PEPE came away as the most consistent outperformer of ETH when ETH had positive daily movements. Of course, that came with some caveats:
Even though it had the highest “hit rate” in terms of outperforming ETH, you’d still be better off holding ETH on 36% of green days. None of these beta plays perfectly outperform the base asset. In general, it often makes sense to just lever long ETH if you really want more ETH exposure.
On days that ETH prints a red candle, beta plays tend to get rekt (e.g. the average -1% ETH day results in a -3.13% PEPE day).
Investigating how often Ethereum altcoins out/underperform ETH during positive (green days) and negative (red days) daily movements. Average multiples show the magnitude of the altcoins’ out/underperformance on green and red days, compared to ETH.
All of this got me thinking - could we do the same thing for SOL? Sure, it already has a lot of volatility. But there’s plenty of overlap between crypto traders and the TikTok generation of dopamine-chasers who will always crave more, so let’s dive in.
ETH and SOL altcoin ecosystems are inherently different
The birthplace of DeFi Summer has the most prolific altcoin ecosystem in the entirety of crypto. Go ahead and stack L2 (and now L3) governance/gas tokens on top, and you’ve got a smorgasbord of options to choose from. Since many of these projects originated in 2020-22, there’s a ton of tokens that have matured to the point of becoming market mainstays (on top of minimal remaining inflation).
That’s why it was so difficult to nail down which tokens to pick for the analysis above.
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Recently, I crunched the numbers in order to answer the question everyone seemed to be assuming they had the answer to - “what’s the best way to capture ETH beta?”. People think ETH will trend up with time, but they aren’t satisfied with its relatively muted price volatility now that Ethereum’s market cap is well into twelve figures.
The TL;DR of the post was that PEPE came away as the most consistent outperformer of ETH when ETH had positive daily movements. Of course, that came with some caveats:
Even though it had the highest “hit rate” in terms of outperforming ETH, you’d still be better off holding ETH on 36% of green days. None of these beta plays perfectly outperform the base asset. In general, it often makes sense to just lever long ETH if you really want more ETH exposure.
On days that ETH prints a red candle, beta plays tend to get rekt (e.g. the average -1% ETH day results in a -3.13% PEPE day).
Investigating how often Ethereum altcoins out/underperform ETH during positive (green days) and negative (red days) daily movements. Average multiples show the magnitude of the altcoins’ out/underperformance on green and red days, compared to ETH.
All of this got me thinking - could we do the same thing for SOL? Sure, it already has a lot of volatility. But there’s plenty of overlap between crypto traders and the TikTok generation of dopamine-chasers who will always crave more, so let’s dive in.
ETH and SOL altcoin ecosystems are inherently different
The birthplace of DeFi Summer has the most prolific altcoin ecosystem in the entirety of crypto. Go ahead and stack L2 (and now L3) governance/gas tokens on top, and you’ve got a smorgasbord of options to choose from. Since many of these projects originated in 2020-22, there’s a ton of tokens that have matured to the point of becoming market mainstays (on top of minimal remaining inflation).
That’s why it was so difficult to nail down which tokens to pick for the analysis above.
There’s like a dozen L2/3 network tokens
There’s countless application tokens
And there are even some memes
Solana is a different story. It’s a newer chain, and naturally has fewer household names when it comes to application tokens. Sure, there are a couple like JUP, JTO, and PYTH, but the oldest of these launched less than a year ago.
But, what does Solana have a lot of? Memes. How many of them? Too fucking many of them. Pump.fun has seen to that.
But, since a meme (PEPE) won out in the ETH beta analysis, I’ll do my best to cast a wide net on Solana memes. It will just take a bit more of a detailed analytical approach.
The contenders
For this analysis, I’ve chosen the following tokens as contenders:
Application tokens:
Jupiter (JUP) - The front-page of Solana, and in my opinion, a very slick DEX.
The problem with the application tokens on Solana is that they generally fall into the dreaded (and over-memed) “low-float high-FDV” category. This is partially due to insider greed and partially just because they are so darn new - they haven’t had time to dilute to the same magnitude as tokens on Ethereum.
And sorry if I didn’t include your favorite memecoin. There are simply too many for my small brain to wrap around. But this should give us a broad understanding of the ecosystem.
How closely these tokens track SOL
If we want “SOL beta,” it makes sense to look at which of these actually tend to track with the price movements of SOL. Hence, let’s look at a correlation analysis first.
Now, this gets a little tricky. I opted for coins >1 year of age in the Ethereum analysis because that helps clean up the results, but that isn’t really possible when it comes to these tokens, as most are younger than a year.
So with that in mind, we’re going to:
Ignore the first month of activity of the tokens (this incubation period is extremely volatile and the initial price discovery is not predictable - unless you are Grant).
Have to take into account the age of the tokens. Older tokens will give us more data, and therefore higher confidence in their correlations.
Confidence intervals of SOL correlation for various altcoins. Yes, you monsters made me dust off my stats textbooks (jk I asked ChatGPT) because these coins have varying ages, and hence sample sizes. Higher correlations mean that a coin tracks closely to the price movements of SOL.
The bars above show the 95% confidence intervals of where the “true” correlation between SOL and these alts lies. Note how older coins (like BONK, which has ~520 days of data) and less volatile coins (like JUP) tend to have tighter ranges than newer and more volatile assets like RETARDIO (87 days) and MICHI (39 days).
For reference - Coins investigated, alongside their respective ages. Note that we are ignoring the first month of price action.
In the end, JUP seems to give the clearest signal. When SOL goes up/down, JUP is usually right alongside it. But, of course, this doesn’t tell the whole story. We don’t want our “beta” to go up ~1% when SOL goes up 1% - we want more volatility. “Correlation” is only one aspect.
Finding the outperformers
As we mentioned, when someone on Crypto Twitter says they’ve found the best “SOL Beta,” what they mean is that on any given day where SOL pumps 3%, their chosen token pumps harder (or maybe they want beta to the downside, for pair trading or something).
To find which tokens act this way, I looked at the price histories of these projects and noted how they performed on days that SOL price was green/red. The results will (probably not) shock you!
This chart shows the percentage of days where each token outperformed and underperformed SOL price movement, split between positive and negative SOL days.
From the looks of it, the following coins are cucked. They underperformed SOL on the majority of green AND red days:
JTO
PYTH
BONK
BOME
But by how much did these tokens outperform or underperform SOL? To answer that, let’s look at their performance over the past 120 days.
Median price multiples for tokens of interest. For example, on any given day when SOL is +1%, we expect JTO to be up about +1.11% and MICHI +3.364%. If SOL is down 1%, we expect JTO to be down 1.407% on the day, on average.
When we compare against SOL, some things become clear quickly:
Memes drastically outperform projects with “fundamentals,”, on a whole (this hurts my soul to type)
Older/weaker memes fall into obscurity (BONK, BOME) and newer memes take the spotlight (POPCAT, MICHI, RETARDIO)
Median multiples for tokens compared to their age, with a linear trend line to show a rough correlation between the two variables.
We see that there’s a (albeit rough, low R value) correlation between a token’s age and its expected multiple against SOL. This tells us that there is more volatility/up-side for newer coins.
While this is somewhat expected, it is interesting to see that the “cucked coins” mentioned above (note how they hang below multiples of 1.5) range from: as new as BOME (79 days) and as old as BONK (520 days). Stay in the spotlight, or step out of the way.
Since BONK is a bit of an outlier, here’s the chart zoomed into the newer set of coins.
Same chart as above, but with BONK removed
Taking a look at which coins outperformed on a daily level, here’s how it broke down over the past 120 days:
Number of times and percentage of days where each coin was the top performer. The starred projects (*) were available for fewer than 120 days, so hence the percentages will not all add up to be 100%.
Again, we see that the newer coins tend to be the top performers. Surprisingly, only 4 out of the past 120 days had SOL as the top performer, the lowest (3.3%) out of the entire field examined. In fact, just blindly picking the newest coin worked 18% of the time, or 23% of the time if you only included memecoins.
To visualize this shiny-object tendency, let’s graph the top performer on the price chart of SOL.
The price chart of SOL, with the price bar colored by the daily leading performer. Note where the newest coin “launches” (30 days after their actual launch) by the text callouts.
The chart above shows that the new-and-exciting coins tend to steal the spotlight from the others in the group. Notice how a new launch will dampen the coins that came before them.
And if the above chart is too confusing, here it is zoomed into only the last 60 days. Note how many days MICHI steps in and BOME steps back after the newer coin launches.
Same data as above, just zoomed into the second half of the days
Conclusions and plan of attack
For many, I’m sure the conclusions come as little surprise:
If you want SOL beta, betting on memes tends to work better than betting on big ecosystem projects for the time being. This may change in the future (maybe a few years) when more projects become established and their tokens diluted.
When picking memes, it generally helps to lean more towards new-ish projects that give hints of their staying power. If a new memecoin starts underperforming established ones (WIF, POPCAT), it’s time to cut it.
When picking medium/long-term meme holds, picking ones with staying power is a must. Just look at how BOME massively underperforms WIF, even though it is much newer.
Personally, I plan on changing my strategy a bit when it comes to SOL beta. Up to now, I’ve basically only used WIF as my SOL beta play. This analysis shows that this should be somewhat solid, but I’m missing out on a lot of the potential upside of newer tokens.
My memecoin picking is admittedly quite poor, but I will be watching which projects break into the top 500. If any of them make me laugh, I’ll probably rotate a bit of my WIF into them. Another strategy I might try is to just close my eyes and buy a couple hot new memes if I expect the market to continue higher - to capture the shiny-object tendency.
Alternatively, I could see myself just manually applying a small amount of leverage by borrowing stables against some SOL and just buying more SOL. Remember, it’s all fun and games until you pick the wrong memecoin and you aren’t getting the exposure you want. The worst outcome is being right about the ecosystem while being in the wrong bags.
563
This piece was written by our Head of Research, 563, a DeFi researcher and analyst interested in exploring true innovation taking place in crypto. An engineer by education, he enjoys cutting through the noise and simplifying complex topics.
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