Ethereum Could Reach $8,000 in Coming Years

Summary

Trading View (next 2-4 weeks): We like to buy ethereum

Investment View (next 1-3 years): We like to hold ethereum

Macro Signals

• Ethereum and equity correlations are at new highs of 86%.
• There is greater certainty around the Fed’s hiking path.
• Risks remain around the Russia-Ukraine war and a potential recession, but overall, the macro backdrop moves from bearish to neutral.

On-Chain/Flow Signals

• Bullish signals across all seven of our metrics.

Overall View

• With the macro backdrop moving to neutral and on-chain/flow metrics very positive, our overall signal is bullish ethereum.

Macro: Where Can Prices Go Amid Tech Correlations at All-Time Highs?

We still believe the dominant driver of crypto and ethereum in the near term is the broader risk environment. That is especially so given ethereum’s correlation to the NASDAQ is now at new all-time highs of 86% (Chart 2). But what is the outlook for ethereum under these conditions? This week, we present several scenarios based on the historical performance of ethereum and the NASDAQ.

The Outlook in Three Scenarios

We look at historic Sharpe ratios of ethereum and the NASDAQ to work out what future returns might look like if such Sharpe ratios persisted. Ethereum, like most crypto assets, is very volatile. However, its volatility has settled at a median annualised rate of around 86% since 2020 (Chart 3). Assuming annualised daily volatility stays at this level, we can derive the following possible scenarios:

• Aggressive. Three-year target = $51,000
  Ethereum’s lifetime Sharpe ratio is around 1.8. Were this to persist, and using the median annualised volatility from 2020 onward (86%), it could lead to a compound annual growth rate (CAGR) of around 156%. At current prices, this would mean ethereum could go to $7,800 in a year and a staggering $51,000 in three years. Given this Sharpe ratio was mainly achieved by very high returns early on in ethereum’s lifetime, this scenario is less likely.

• Reasonable. Three-year target = $8,100
  Another scenario is ethereum’s performance since 2018. After the crypto boom in 2017 and its subsequent capitulation, bitcoin and ethereum became more mainstream. From 2018 onward, its Sharpe ratio has been around 0.45. This would lead to a CAGR of around 39%, which would put ethereum prices at $4,200 and $8,100 in one and three years, respectively.

• Converges to NASDAQ. Three-year target = $7,300
  Given the very high correlation to the NASDAQ, our final scenario is the NASDAQ Sharpe ratio since 1990 – around 0.4. Assuming ethereum follows suit going forward, it would lead to a CAGR of around 34%, which would put ethereum prices at $4,000 and $7,300 in one and three years, respectively.

Determining the long-term outlook for ethereum will take time. But, if history is anything to go by, and in the presence of a high correlation to tech, the potential upside could be substantial.

On-Chain/Flow: ETF Outflows Return

We have bullish signals across the board this week:

• Return of ETF inflows.
• Significant bias for exchange outflows.
• Futures open interest rising and funding rates positive.
• Longer-term HODLer vintage jumps.
• Increased profitability of the coin supply and realised profits on-chain.
• Hash rate increasing and gas fees historically low.
• Ethereum outperforming other protocols for gains in total value locked in DeFi.

On balance, on-chain/flow metrics are giving a very bullish signal for ethereum (Chart 1). Here are the details of each metric (with explanations in the Appendix).

Institutional Demand: Bullish Ethereum

Our preferred metric to track institutional demand is flows into ethereum ETFs. After a period of sustained outflows, ETF flows have returned to net inflows (Chart 4). We want to see a sustained period of inflows to turn more bullish, but this is a bullish sign nonetheless.

Demand for Liquidity and Exchange Activity: Bullish Ethereum

In the short term, a bias for outflows from exchanges exists. Net 280,000 and 536,000 coins left exchanges over the past seven and 14 days, respectively (Chart 5). On 15 March alone, we saw outflows of 320,000 coins. This is the largest number of coins exiting exchanges on a single day since 2 July 2021. This can be viewed as bullish.

Longer term, the 30-day change in the exchange balance reveals fluctuations in the supply held on exchanges month on month. Relative to the last 30 days, the exchange balance is decreasing (Chart 6). Indeed, only 18% of the total coin supply currently sits on exchanges. This is bullish ethereum.   

There is a bias for outflows in both the short and long term. Overall, this is bullish for ethereum.

Futures Activity: Bullish Ethereum

Futures open interest is trending up – it is currently $8.3bn, up 15% WoW (Chart 7). Around $6.6bn (80%) of this comes from perpetual futures contracts, so a large majority of leverage sits in perpetuals.

Perpetual funding rates reveal the directional bias of investors. On average, they have been positive every day over the past week (Chart 8). Additionally, they have been positive for all but three days over the past 14 days. This is bullish ethereum, as it means investors are paying a premium to keep open long positions. Overall, futures open interest mostly sits in perpetuals, which have a bias for positive funding rates. This is bullish ethereum.

HODLers: Bullish Ethereum

The 30-day moving average of the coin days destroyed (CDD) metric still shows muted movement of older coins (Chart 9). Splitting HODLers into those who have held for under one year and those for one year or more confirms this – the 1y+ vintage has jumped to 62% (Chart 10). This suggests around 8% of those in the <1y vintage have moved into the 1y+ vintage and reaffirms the conviction that HODLers remain in an accumulation phase. This could change if prices keep rising as some older hands will probably start distributing into market strength to realise profits.

We monitor the number of addresses with at least 32 ETH in the run-up to the official switch of consensus protocol from proof-of-work to proof-of-stake as these are potential validators for ETH 2.0. There are currently 109,466 (Chart 11). This metric has been in an uptrend since the start of 2022 and will be useful to monitor as the merge nears.

On balance, we view these HODLer metrics as bullish ethereum in the short term as longer-term HODLers are still accumulating amid the rally. This suggests they see further upside ahead.

Investor Profit and Loss: Bullish Ethereum

The percentage of circulating supply in profit (PSIP) is now 78% (Chart 12) – up 8pp over the past week.   

Net unrealised profit/loss (NUPL) is now 0.46 (46% of market cap) (Chart 13) – up 7pp over the past week. We still wait for any sustained break above 0.5 for this metric to confirm a longer-term bullish sentiment.

Since Thursday last week, SOPR has remained above one (Chart 14). This moves the recent on-chain spent output bias from losses to profits.

Mining Activity: Bullish Ethereum

The hash rate resumes an uptrend and is again approaching new all-time highs (Chart 15). It is currently up 2% WoW and 9% year to date. Gas fees have started to tick up slightly (Chart 16). However, they remain low relative to the last six months and are still down a staggering 54% year to date.  Elevated hash rates and (relatively) low gas fees are bullish ethereum.

DeFi: Bullish Ethereum

DeFi markets have been leading gains in the recent crypto market rally. Indeed, our latest Crypto Index Tracker revealed our DeFi Index is up the most (14%). The total value locked (TVL) in DeFi across all protocols is currently around $213bn – this is up 11% WoW. We have seen an increase in TVL across all the top five chains (Charts 17 and 18), but ethereum has eclipsed the rest with an impressive 16% increase in TVL WoW (Chart 18).

Bottom Line

We have introduced a framework for understanding the flow and microstructure dynamics of ethereum markets. The seven key metrics are:

1. Institutional demand: return of inflows to ETFs. Bullish ethereum.
2. Liquidity demand: bias for exchange outflows. Bullish ethereum.
3. Futures activity: increasing futures open interest and positive perpetual funding rates. Bullish ethereum.
4. HODLer behaviour: Longer-term HODLers rise. Bullish ethereum.
5. P&L of investors: increased profitability of the coin supply and realised profits on-chain. Bullish ethereum.
6. Mining activity: hash rate increasing and gas fees remaining historically low. Bullish ethereum.
7. DeFi activity: TVL increasing and ethereum leading the gains. Bullish ethereum.

Appendix

Institutional Demand

Perhaps the largest institutional vehicle for ethereum is the Grayscale ETHE Trust, with over $27bn in assets. It invests solely in ETH, and so many investors, notably institutional, who cannot hold ETH directly can get exposure through investing in Grayscale. Consequently, if the trust trades at a premium to ETH prices, it may imply ‘excess’ demand from institutions, but ‘excess’ supply if it trades at a discount. Alternatively, the discount may suggest investors have found other ways to get exposure to ETH, whether through ETFs or directly holding ETH. We therefore focus on how the discount has changed in recent months to gauge investor interest.  Alternatively, investors may be using other vehicles to get exposure such as ETFs or holding ETH directly. We put more weight on ETF flows than the Grayscale premium.

Liquidity Demand

Another measure of cryptocurrency bullishness is whether investors are willing to hold it in illiquid form (e.g., a private wallet) or prefer a liquid form (e.g., on an exchange). The former would suggest investors are bullish, as they are comfortable with being unable to sell easily. Conversely, holding it in liquid form would suggest investors are bearish, as they prefer being able to sell easily.

Therefore, large flows onto crypto exchanges would suggest investors want to convert their holdings to a more liquid form, implying more bearishness.

Futures Activity

We track the growing market of ethereum futures. Open interest – the sum of long and short contracts – is a good measure of investor interest.

Perpetual funding rates reveal the directional bias of investors. Exchanges set funding rates to prevent a lasting divergence in the price of the futures contract and the underlying since perpetual contracts have no expiry date so never settle in the traditional sense. Consequently, we can interpret funding rates as the cost of holding ethereum via perpetual futures. Positive funding rates imply longs pay shorts and vice versa. We use it as a proxy for trader sentiment since a positive funding rate implies traders are paying a premium to keep open long positions.

HODLers

In our introductory bitcoin flow framework, we explained ‘HODLers’ and ‘HODLing’. HODLing refers to buy-and-hold strategies in the context of bitcoin and other cryptocurrencies. Those who HODL for extended periods are die-hard adherents.

We can categorise HODLers by the length of time they have held ETH. We define long-term or staunch HODLers as those who bought ETH five or more years ago and have held it ever since, medium-term HODLers as those who bought 6-12 months ago, and short-term HODLers as those who bought 3-6 months ago.

The coin days destroyed (CDD) metric is defined as the number of coins in a transaction multiplied by the number of days since the coins were last spent. So, increasing CDD suggests older coins are being spent (more coin days are destroyed) and vice-versa.

Profit and Loss

• The percent supply in profit (PSIP). This tracks the share of circulating ETH supply in profit. That is the percentage of circulating ETH whose current price is higher than when it was last transacted (movement).
• Net unrealized profit and loss (NUPL). This is the ratio of unrealised profits over total market capitalisation. While PSIP just focuses on whether ETH coins are in profit or not, the NUPL focuses on the size of profits. So, we could have a situation where the PSIP is low – that is, a low share of supply is in profit – but the NUPL could be high if the size of those profits is large.
• Spent output profit ratio (SOPR). While PSIP and NUPL focus on unrealised profits or mark-to-market, this measure focuses on realised profits. SOPR is the realised value of a transaction divided by the value at initiation (or creation) – more simply, price sold divided by price paid. If SOPR is above one, investors in aggregate have realised profits, while below one means they have realised losses. In broad uptrends, SOPR spends a significant amount of time above one, whereas the opposite is true for broad downtrends.

When SOPR is rising, sellers are increasingly realising profits. The opposite is true when it is falling. A price rally with a flatter SOPR trend indicates investors are not yet realising their profits with the rally. The reluctance of investors to sell and realise a profit may be because they believe the price will increase further, which would be bullish. At the same time, more profit taking could precede a correction. Typically, buying as SOPR moves around one during bullish periods has proven to be a profitable strategy.

Mining Activity

Computing power is central to the crypto market. Miners use advanced computing hardware to solve complex problems that confirm ETH (and other coins) transactions on the public ledger or blockchain. The miners are rewarded with new coins for their efforts. A measure of the complexity of the problems and so the computing performance required to solve them is the hash rate. The higher this rate, the more computing performance is needed to maintain the blockchain. The rate can fluctuate depending on demand for crypto.

DeFi

We track the total value locked (TVL) in decentralized finance (DeFi) – the sum of all assets deposited in DeFi protocols, many of which use ethereum as the underlying protocol. The more DeFi products are created, the more ethereum gets locked into the DeFi system and removed from the broader market. This reduction in supply should lead to higher ethereum prices.

Dalvir Mandara is a Quantitative Researcher at Macro Hive. Dalvir has a BSc Mathematics and Computer Science and an MSc Mathematical Finance both from the University of Birmingham. His areas of interest are in the applications of machine learning, deep learning and alternative data for predictive modelling of financial markets.