The original text is from Presto Research
Compiled by Odaily Bit Golem (@web3_golem)
Key points:
Whale alerts are popular because large on-chain transactions are often seen as a precursor to an impending token sell-off and a sell signal. To evaluate these claims, Presto Research analyzed the price changes of BTC, ETH, and SOL after large deposits were made to Binance.
According to the regression analysis, the R-squared values between large transaction deposits and subsequent price changes are low (ranging from 0.0017 to 0.0537). Narrowing the data to deposits from VCs and MMs slightly increased the R-squared values, but their actual utility as trading signals remains limited. The research findings strongly suggest that whale deposits to exchanges lack predictive power as reliable trading signals.
On-chain indicators are effective in other aspects, such as analyzing blockchain fundamentals, tracking illicit fund flows, or explaining price volatility. They will better serve the industry only when investors have more realistic expectations about their capabilities and limitations.
One of the key differences between crypto assets and other assets is the public availability of their transaction records, which are stored on a distributed ledger. This blockchain transparency has given rise to various tools that leverage this unique feature, collectively known as "on-chain data" tools. One such tool is "Whale Alerts", an automated service that notifies of large crypto transactions on-chain. They are popular because large transactions are often seen as a precursor to an impending sell-off, and thus viewed as a "sell signal" by traders.
This report evaluates the validity of this widely accepted assumption. After briefly outlining the popular Whale Alert services in the market, we will analyze the relationship between large transaction deposits and the prices of BTC, ETH, and SOL. We will then present the analysis results and provide the key conclusions and recommendations.
Overview of Whale Alerts
Whale Alerts refer to services that track and report large crypto transactions. These services have emerged as the crypto ecosystem has evolved, reflecting the high degree of recognition of the blockchain's transparency feature by market participants.
History
As early Bitcoin adopters, miners, and investors (such as Satoshi Nakamoto, the Winklevoss Twins, F2 Pool, Mt. Gox) accumulated large amounts of Bitcoin, the term "whale" became popular. Initially, blockchain enthusiasts monitored large transactions through blockchain explorers (like Blockchain.info) and shared this information on forums like Bitcointalk or Reddit. This data was often used to explain significant Bitcoin price fluctuations.
During the 2017 bull market, with the increase in whale transactions and large transaction volumes, the market urgently needed automated monitoring solutions. In 2018, a European development team launched a tool called "Whale Alert" that could track large crypto transactions in real-time across multiple blockchains and send alerts via X, Telegram, and a web interface. The tool quickly gained the favor of market participants and became the preferred service for those seeking actionable trading signals.
Source: Whale Alert (@whale_alert)
Underlying Assumption
Following the success of Whale Alert, many platforms providing similar services have emerged over the years, as shown in the image below. While many new platforms have added more features to provide context for the alerts, the original Whale Alert remains focused on simple, real-time notifications and is still the most popular service, as evidenced by its large following on X. A common feature of all these services is that they rely on the assumption that large on-chain transactions (especially exchange deposits) signal an impending sell-off.
Mainstream Whale Alert services, data source: Whale Alert, Lookonchain, Glassnode, Santiment, X, Presto Research
Evaluating Signal Validity
Supporters of Whale Alert services believe that on-chain asset transfers to exchanges often precede liquidations, making them an effective sell signal. To verify this hypothesis, we analyzed the price changes of digital assets after large deposits were made to exchanges, with the key parameters of the analysis shown in the image below. The assumption is that if large transaction deposits can serve as a reliable trading signal, there should be a clear relationship between the deposits and the corresponding asset prices.
Key parameters of the analysis, source: Presto Research
Assets, Exchanges, Analysis Period, and Deposit Thresholds
Our analysis focused on the prices of the three major crypto assets - BTC, ETH, and SOL - on Binance during the period from January 1, 2021, to December 27, 2024. This time range was chosen to align with the operational duration of the wallet addresses currently used by Binance to aggregate deposits.
The deposit thresholds were set based on an exchange data analysis. Specifically, using the thresholds of $50 million, $50 million, and $20 million for BTC, ETH, and SOL whale alerts set by Whale Alert, we adjusted the deposit thresholds to $20 million, $20 million, and $8 million, respectively, which aligns with Binance's 40% share of global spot trading volume.
Entity Types
We also specifically analyzed the deposits of known entities and performed the same analysis on a narrower data sample to check if the deposits of certain entity types show a stronger relationship with price movements. These entities were identified through Arkham Intelligence and supplemented by our own investigation, as shown in the image.
Entities with known addresses, source: Arkham Intelligence, Presto Research
Measuring Market Impact
To assess the potential sell-off pressure from whale deposits, we made the following assumptions:
After on-chain confirmation of deposits above the threshold, sell-off pressure would manifest within a specific time frame. We analyzed two time periods: one hour and six hours.
The maximum drawdown (MDD) within the specified interval was used as an indicator to measure the impact of the deposits on prices (if any), effectively filtering out the noise in that period.
Results
The analysis results are shown in the following figures
Impact of BTC Whale Deposits (All):
Source: Binance, Dune Analytics, Presto Research
Impact of BTC Whale Deposits (VC and MM only):
Source: Binance, Dune Analytics, Presto Research
Impact of ETH Whale Deposits (All):
Source: Binance, Dune Analytics, Presto Research
Impact of ETH Whale Deposits (VC and MM only):
Source: Binance, Dune Analytics, Presto Research
Impact of SOL Whale Deposits (All):
Source: Binance, Dune Analytics, Presto Research
Impact of SOL Whale Deposits (VC and MM only):
Source: Binance, Dune Analytics, Presto Research
Key Takeaways
Source: Binance, Dune Analytics, Presto Research
The above figure summarizes the results of the above statistics and draws the following 3 conclusions:
The predictive power of large exchange deposits and price declines is relatively weak: The R-squared values of all 12 scenarios show that their predictive power is extremely weak, ranging from 0.0017 to 0.0537.
Deposits from VCs and MMs may be slightly better predictive signals: In this part of the data, the R-squared values have improved, but this improvement may only be the result of reduced sample noise, rather than a truly stronger correlation. In addition, the absolute values are still relatively low, indicating that their actual effectiveness as trading signals is limited.
The whale deposits of ETH mainly come from VCs and MMs: They account for 61% of ETH whale deposits (879 out of 538 transactions), while BTC accounts for only 13% and SOL for 32%. This reflects the characteristics of different assets: ETH has a higher turnover rate due to its diverse Web3 applications (e.g., gas fees, staking, DeFi collateral, and swap medium), while BTC is a more stable value storage asset.
Conclusion
Admittedly, our analysis method has certain limitations, and regression analysis has its inherent constraints, and relying solely on R-squared values to draw conclusions may sometimes be misleading.
However, this analysis, combined with the background and individual observations, strongly indicates that whale deposits to exchanges lack sufficient predictive power to be a reliable trading signal. This also provides us with deeper insights into the broader use of on-chain indicators.
On-chain indicators are undoubtedly valuable tools, especially for analyzing blockchain fundamentals or tracking illicit fund flows, and they may also be useful in retrospectively explaining price movements. However, using them to predict short-term price changes is a completely different matter. Prices are a function of supply and demand, and exchange deposits are just one of many factors affecting the supply side, even if they are truly useful. Price discovery is a complex process, also influenced by fundamentals, market structure, behavioral factors (such as sentiment, expectations) and random noise.
In the highly volatile cryptocurrency market, participants are constantly seeking "foolproof" trading strategies, and there will always be audiences attracted by the "magic" of on-chain indicators. On-chain indicators can better serve the industry when investors have realistic expectations of their capabilities and limitations, rather than when some "overly enthusiastic" data providers are eager to exaggerate the promises of their platforms.
