curl -H "X-API-Key: cdk_live_…" \
"https://cryptodataapi.com/api/v1/market-data/klines?symbol=MUSDT&interval=1d&limit=90"
Scheduled and unscheduled catalysts for this coin: news scored for real price impact, security incidents, and upcoming token unlocks that add supply.
Market-Moving News & Events →Things that could move the price: news, security problems, and token unlocks — dates when a batch of new coins is released to early investors and team members, adding to the supply. An empty panel genuinely means nothing is scheduled, rather than data failing to load.
This feeds event-driven and catalyst trading. Token unlocks support a supply-shock trade — the size and date are public, so the weakness often arrives before the unlock rather than on it. Scheduled news drives the buy-the-rumour, sell-the-news pattern, where the move happens into the announcement and reverses on it.
Design a new event-driven strategy for M using /api/v1/event/regime/M and the unlock schedule. The rules must be executable in advance — no reacting to news after the fact — so define how many days before a catalyst you act and what closes the position. Validate on /api/v1/backtesting/news-events and /api/v1/backtesting/snapshots?data_type=token_unlocks, and be explicit about any lookahead you had to avoid.
/backtesting/news-events is the archived catalyst tape with the same scoring you see here. Token unlocks have their own snapshot type, /backtesting/snapshots?data_type=token_unlocks, which matters because unlock dates are known ahead of time and are therefore testable without lookahead.
Using CryptoDataAPI, test how M trades around scheduled catalysts. Pull /api/v1/backtesting/news-events and /api/v1/backtesting/snapshots?data_type=token_unlocks, then measure returns from 7 days before each unlock to 7 days after, using price bars from /api/v1/backtesting/klines. Report whether weakness arrived before or on the date, and whether unlock size relative to float predicted the size of the move.
curl -H "X-API-Key: cdk_live_…" "https://cryptodataapi.com/api/v1/event/regime/M"
Positions force-closed in this coin over the last 24 hours, split by side. A long liquidation is forced selling; a short liquidation is forced buying.
Crypto Liquidations →A liquidation is a trader being forced out of a bet because the price moved too far against them. Longs being liquidated means forced selling; shorts being liquidated means forced buying. Judge the size against what is normal for this coin: $5M is enormous for a small coin and barely noticeable for Bitcoin.
Liquidation-cascade fades are built on this: forced selling overshoots, so the sharpest bounces tend to follow the biggest one-sided prints. Long and short squeeze plays work the same mechanism in reverse, and stop-hunt reversals look for price being pushed into a cluster of stops precisely to trigger them.
Design a new strategy for M that trades around forced liquidations, using /api/v1/market-intelligence/liquidations?symbol=M live. Define what counts as a cascade, which side you take, how quickly you exit, and how you avoid being liquidated yourself. Validate on the per-event tape at /api/v1/backtesting/hl-liquidations plus /api/v1/backtesting/klines, and report the worst single loss, not just the average.
/backtesting/liquidations gives the aggregated series, and /backtesting/hl-liquidations gives the exact per-event Hyperliquid tape — every individual fill, with its venue. For the price levels where liquidations cluster, use /backtesting/snapshots?data_type=liquidation_map.
Using CryptoDataAPI, backtest the liquidation-cascade fade on M. Pull the per-event tape from /api/v1/backtesting/hl-liquidations and price bars from /api/v1/backtesting/klines. Define a cascade as a 5-minute bucket in the top 1% of one-sided liquidation size, then measure forward returns at 15m, 1h and 4h from taking the opposite side. Charge taker fees and report the hit rate and worst loss.
curl -H "X-API-Key: cdk_live_…" "https://cryptodataapi.com/api/v1/market-intelligence/liquidations?symbol=M"
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