Whale Wallet Tracking & Signal Extraction

You are a blockchain intelligence analyst who tracks whale wallets and institutional flows to generate trading signals. You have built alert systems that have identified major accumulation and distribution events days before they affected price.

CONTEXT: Whale wallets (holding $1M+ in crypto) often move markets and their behavior can foreshadow major price movements. I want to systematically track whale activity across Bitcoin, Ethereum, and top altcoins to generate trading signals. I am not interested in random noise — I want to identify patterns that have genuine predictive value. I have intermediate experience with blockchain explorers and on-chain tools.

TASK: Build a whale tracking and signal extraction system:
1. Whale identification and categorization: define whale tiers (Shark: $1-10M, Whale: $10-100M, Humpback: $100M+) and categorize wallet types — known exchange wallets (hot/cold), known institutional wallets (Grayscale, MicroStrategy, etc.), DeFi protocol treasuries, early miners/OG holders, and unknown whales. Explain how to identify and label wallets using Arkham Intelligence, Nansen, and Etherscan labels.
2. Signal-worthy movements: not all whale movements matter. Define which activities generate tradeable signals: (a) Large exchange deposits (potential selling), (b) Exchange withdrawals to new wallets (accumulation), (c) Dormant wallet activation (old holder waking up), (d) OTC desk flows (institutional activity), (e) DeFi position changes (large deposits/withdrawals from Aave, MakerDAO), (f) Cross-chain bridge movements (capital rotation). Specify minimum transaction sizes for each signal.
3. Pattern recognition: describe repeatable whale patterns with trading implications — distribution campaigns (gradual selling over days/weeks), accumulation patterns (buying dips in consistent size), liquidity positioning (providing or removing LP before major moves), and collateral management (adding/removing collateral signals confidence/fear).
4. Alert system design: build a monitoring stack using Whale Alert, Nansen Smart Alerts, Arkham Intel, and DeBank whale tracking. Define specific alert criteria for each signal type, minimum transaction thresholds, and how to filter noise (exchange internal transfers, contract interactions that are not actual transfers).
5. Signal validation framework: how to confirm whether a whale movement is actually significant — check if the sender/receiver is an exchange (often internal transfers), verify the movement in context (single transaction vs. part of a pattern), cross-reference with price action (has price already moved?), and assess the whale's historical accuracy (some whales consistently buy tops).
6. Integration with trading: how to translate confirmed whale signals into trade entries — what time delay between signal and entry (immediate vs. waiting for price confirmation), position sizing based on signal strength, stop-loss placement, and track record keeping to measure signal reliability over time.