This paper investigates how Bitcoin’s price reacts when Tether (USDT) is minted or burned, and specifically examines the impact of Whale Alert Twitter announcements. The author finds that Bitcoin’s price response to Tether minting is significantly stronger when the event is publicly announced by Whale Alert on Twitter. In fact, investors do not react much to the minting itself until Whale Alert tweets about it, at which point Bitcoin sees a short-term price increase, especially under bullish market sentiment. This study is the first to demonstrate that Whale Alert’s real-time large-transfer alerts can influence cryptocurrency markets.

An academic study focusing on extreme volatility in Bitcoin, which integrates on-chain metrics with Whale Alert’s large-transaction tweets. The authors use a deep learning Transformer model and show that incorporating Whale Alert tweet data alongside on-chain analytics improves the prediction of next-day Bitcoin volatility spikes. The authors conclude that Whale Alert’s feed of big crypto movements serves as a valuable signal, helping the model outperform baselines in forecasting volatility.

This paper explores Bitcoin price volatility prediction by combining blockchain on-chain data with Whale Alert’s Twitter data. The authors employ a reinforcement learning approach (Q-learning) to classify and leverage Whale Alert tweets about large transactions. They report that merging Whale Alert tweet signals with on-chain metrics enhances the model’s ability to predict Bitcoin price trends and volatility. The results indicate that large-transfer alerts (like Whale Alert’s notifications) provide useful information for anticipating market movements, thereby confirming the practical value of Whale Alert data in volatility forecasting.

This study examines how Twitter post sentiment and user engagement affect daily price moves of top cryptocurrencies (BTC, ETH, DOGE, ADA, XRP) during 2021–2022. While the paper’s main focus is on overall sentiment metrics, it mentions Whale Alert in a broader context as an example of influential crypto-related Twitter activity. The authors cite prior findings that tweets from accounts like Whale Alert, which broadcasts large crypto transfers, can move markets. In their analysis, however, they find mixed results for sentiment’s effect on price and introduce an “engagement index” for tweets. Whale Alert is brought up as part of the discussion on market-moving news on Twitter, highlighting that high-impact alerts (e.g. large transaction announcements) are a notable component of crypto Twitter sentiment, even if the paper’s quantitative results focus on aggregated sentiment rather than individual accounts.

An industry whitepaper that evaluates whether alerts of large crypto transactions (such as those from Whale Alert) can be used as reliable trading signals. The report provides an overview of Whale Alert services – noting that Whale Alert (launched in 2018) became the pioneering tool for real-time tracking of large on-chain transactions across multiple blockchains. The authors analyze a dataset of big Bitcoin, Ether, and Solana transfers into exchanges (e.g. Binance) and measure subsequent price changes. The key finding is that there is little predictive power in these Whale Alert-type signals – the correlation between large deposits and short-term price movement is very weak (R² on the order of 0.1% to 5%). Even filtering for transactions by known venture capital or market-maker wallets only marginally improves predictability. In summary, while Whale Alert’s notifications are popular among traders, this study concludes that such whale alerts have limited value as forward-looking sell signals, though they remain useful for transparency and forensic analysis. The paper also discusses Whale Alert’s history and how its success spurred many copycat, underscoring Whale Alert’s prominence as the go-to crypto whale tracker.