'ETH Beta' - a Recipe for Disaster?

Is buying ETH beta a fools errand or a viable strategy ahead of the ETH ETFs?

Introduction

In just a few days, the ETH ETFs are scheduled to go live. While most are speculating on the short- and long-term flows for these products, another question arises: Can this catalyst for ETH be captured with increased exposure through levered ETH beta?

ETH betas are a reference to altcoins within the Ethereum ecosystem that, in theory, should act as levered exposure to ETH. Common examples include LDO or ENS, and traders trade these on the idea that they have more volatile moves relative to ETH itself. The term ‘ETH betas‘ has mostly been a meme as of late, however, due to the general underperformance of altcoins. Picking an ETH-correlated alt as levered exposure has been like finding a needle in a haystack and often leads to traders and investors underperforming ETH on a higher time frame.

So, is this time really different? Moving towards the launch of ETH ETFs, is the best strategy to bet on altcoins with higher beta relative to ETH? Today’s article explores this question from a quantitative standpoint.

[Bullets]

• Price Performance

• Correlation

• Beta

• Sharpe Ratio

• Conclusion

---

Price Performance

The TOTAL3 (altcoin market cap) against the ETH market cap is at around 1.48. Since 2020, this chart has only been this low on a few rare occasions, signalling the outperformance of ETH against most alts.

There are several ways to interpret this chart. One, these alts have historically bounced around this level. Given the recent highly bearish sentiment around altcoins, this could be a potential scenario. It is, however, pretty evident that this chart is in a multi-year decline, which indicates that it is difficult to find the right alts that will outperform ETH. What this chart doesn’t capture is the fact that altcoin market caps can increase but prices can decline due to the low float nature of many of these coins and their large unlocks. With this in mind, it is even harder to find solid ‘ETH beta’.

The sample of coins analysed as potential ETH beta consist of the following:

[L2’s]

• OP, ARB, MANTA, MNT, METIS, GNO, CANTO, IMX, STRK

[Alt L1’s]

• SOL, AVAX, BNB, TON

[DeFi]

• MKR, AAVE, SNX, FXS, LDO, PENDLE, ENS, LINK

[Memes]

• PEPE, DOGE, SHIB

Zooming in, the charts below depict the performance of ETH and these four categories year-to-date (past 198 days).

Notably, not a single L2 token has outperformed ETH YTD, with the best performing token, GNO, up 34%, whereas ETH has seen a 44% gain. Worst performers include MANTA, STRK, and CANTO, all down more than 60% this year.

The top alt L1 tokens have faired far better with both TON and BNB outperforming ETH significantly. AVAX is the only one of these down on the year.

Of the 8 DeFi tokens in this basket, 3 have outperformed ETH, namely PENDLE (+254%), ENS (+163%) and MKR (+78%). The remaining 5 are all down on the year with FXS as the worst performer down 73%.

2024 has been characterized by meme dominance and this can also be seen in the performance of the largest Ethereum-native memecoins. Pepe is the largest gainer of the sample, up +708% while SHIB is up 74% and DOGE 31%.

Summed up:

---

Correlation

The sample of altcoins has not been chosen at random but consists of tokens usually assumed to be correlated with the performance of ETH. It makes sense that, for example, random DEX tokens on Solana or Sui are less correlated with ETH than the ERC-20 tokens on the Ethereum network.

The individual YTD performances shown above are insightful, and while past performance doesn’t guarantee future results, there might be some signal there. If we are to analyze whether these tokens actually act as levered beta exposure to ETH and this YTD performance is not just idiosyncratic (individual) behavior, we need to dive deeper. There is no perfect way to model this, and it’s clear that the crypto market is far from efficient. The obtained data must, therefore, be taken with a grain of salt. One way to investigate this behavior, however, is by looking at the correlation between these alts and ETH.

Correlation measures the strength and direction of the relationship between two assets and can help explain how they move in relation to each other. Correlation values range from -1 to 1, with 1 being perfect correlation and -1 being inverse correlation.

The figure below depicts the correlation between the various coins on the left and ETH. Correlation between ETH and ETH is obviously perfect and therefore is 100%. The alts most correlated with ETH are GNO, SNX, METIS, AAVE, and ARB.

Amongst the highest performers YTD, namely PEPE, TON, PENDLE, ENS, and BNB, these are all 60% or less correlated with ETH, indicating that more of their performance is a result of other factors (potentially BTC correlation or idiosyncratic variables). TON is the least correlated with ETH, and so buying this asset with the intention of capturing leveraged ETH exposure is therefore a suboptimal idea according to this analysis.

---

Beta

Moving a step further, we can calculate the YTD beta coefficients of these alts in relation to ETH. Beta is used to denote the volatility of an asset compared to the underlying market, in this instance, ETH. ETH has a beta value of 1, where alts with higher volatility have a beta value greater than 1, and alts with lower volatility have a beta value lower than 1.

From this analysis, it’s clear that only a few alts have a high beta coefficient in relation to ETH, namely PEPE, METIS, ENS, and PENDLE. Alts that have a high beta coefficient can be interpreted as being more volatile relative to ETH itself. Combining our results from the correlation and beta analysis, one might suggest that PEPE acts as one of the better ETH beta assets and could yield solid returns should ETH appreciate as a consequence of the ETFs going live. It is, however, important to remember the limits of this analysis. There are a lot of outside factors impacting the behavior of these assets not included in this analysis, so I must once again remind you to view this as a theoretical exercise and not data to trade on directly.

---

Sharpe Ratio

Finally, we can calculate the YTD Sharpe ratio for these assets as another way of determining their recent performance. The Sharpe ratio provides a way of measuring the volatility-adjusted return and is calculated by taking the return, subtracting the risk-free rate, and dividing this by the volatility (standard deviation). The risk-free rate used for this analysis is the 8% APY that can be earned from Maker’s ‘DAI Savings Rate.’ The higher the Sharpe ratio, the better.

---

Conclusion

So what is the main takeaway from this analysis?

• First, only a small handful of altcoins that are categorized as ‘ETH beta’ on Crypto Twitter have been able to outperform ETH itself.

• Second, a significant amount of the altcoin performance cannot be attributed to ETH correlation/beta. These are not only correlated to other assets besides ETH but also impacted by individual variables.

Buying these altcoins as a way to get leveraged exposure to ETH is, in my opinion, a foolish game as you’re taking on a lot of additional risk you might not be aware of. If you’re looking for leveraged ETH exposure, simply putting on a 2x ETH long on e.g., Aave is more sensible. Here, you achieve a 100% correlation and a beta value of 2.

A final remark is that the thesis around ETH performing well post-ETFs going live involves the potential positive inflows from new ETH ETF buyers. These altcoins will not experience this positive buying pressure (they are not the ones with ETFs going live) and in many situations have large token unlocks over the next weeks/months. Don’t overcomplicate it, anon.

---

Disclaimer: The information provided is for general informational purposes only and does not constitute financial, investment, or legal advice. The content is based on sources believed to be reliable, but its accuracy, completeness, and timeliness cannot be guaranteed. Any reliance you place on the information in this document is at your own risk. On Chain Times may contain forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those expressed or implied in such statements. The authors may or may not own positions in the assets or securities mentioned herein. They reserve the right to buy or sell any asset or security discussed at any time without notice. It is essential to consult with a qualified financial advisor or other professional to understand the risks and suitability of any investment decisions you may make. You are solely responsible for conducting your research and due diligence before making any investment choices. Past performance is not indicative of future results. The authors disclaim any liability for any direct, indirect, or consequential loss or damage arising from the use of this document or its content. By accessing On Chain Times, you agree to the terms of this disclaimer.