Classical technical structure computed on this coin: moving-average relationships, Bollinger squeezes, where price sits in its recent range, and RSI on both the daily and hourly.

Range position shows where today's price sits between its recent low and high. A squeeze means the price has gone unusually quiet, which often comes just before a big move — though it does not tell you which direction. RSI shows whether a move has run hot or cold; overbought means stretched, not that it is about to turn around.

Everything here is a standard textbook signal. Golden cross and death cross come from the moving-average relationship, Bollinger squeeze breakouts come from the volatility compression, and RSI divergence — price making a new high while RSI does not — is one of the oldest reversal warnings there is. Range position is the basis of simple mean reversion back to the 20-period average.

Design a new technical strategy for QNT using /api/v1/indicators/technical/QNT. Combine at least two of the structure signals — moving averages, Bollinger squeeze, range position, RSI — into one rule set rather than trading any single one. Write out entry, exit, stop and sizing. Validate on /api/v1/backtesting/klines with fees, and report which of the component signals actually contributed and which you could drop.

Every technical reading is archived per symbol in the daily bundle: the technical_regime block of /backtesting/daily-snapshots/{date}. If you want a different lookback than the one we publish, rebuild the indicators yourself from /backtesting/klines — minute bars for Hyperliquid perps and 450+ Binance markets.

Using CryptoDataAPI, backtest the classic technical signals on QNT. Pull price bars from /api/v1/backtesting/klines and compute a 50/200 moving-average cross, a Bollinger squeeze breakout, and RSI divergence. Test each separately with taker fees and a fixed stop. Report win rate, profit factor and max drawdown per signal, and tell me which ones fail to beat buy-and-hold.

A three-state trend classifier, red / grey / green, built on ADX and DMI with hysteresis so it does not flip back and forth on noise the way a raw crossover does.

Three colours, and that is the whole indicator. Green means a clear uptrend, red a clear downtrend, grey means no real trend and probably not worth trading. It waits for solid evidence before changing colour so it does not flicker back and forth. Days since the last flip matters: a colour that has only just changed is the least settled.

ADX and DMI, which drive this indicator, are most often used as a trend FILTER rather than an entry: run moving-average crossover or breakout systems only when the colour is red or green, and stand aside in grey. That single filter is what keeps trend-following systems from bleeding out during sideways markets.

Design a new trend strategy for QNT around the SIGNUM state at /api/v1/indicators/signum-rgg/QNT. Treat the red/grey/green colour as the filter and invent the entry trigger yourself, including what you do during grey. Define stops and how you re-enter after a flip. Validate against the signum_rgg block of /api/v1/backtesting/daily-snapshots/{date} plus /api/v1/backtesting/klines, and report how much of the return came from simply avoiding chop.

The signum_rgg block inside /backtesting/daily-snapshots/{date} holds the recorded red/grey/green state per symbol per day, so you can test the colour changes without recomputing ADX. Raw price history for your own version is at /backtesting/klines.

Using CryptoDataAPI, test the SIGNUM red/grey/green state as a trend FILTER on QNT. Pull the signum_rgg block from /api/v1/backtesting/daily-snapshots/{date} across the archive and price bars from /api/v1/backtesting/klines. Run a moving-average crossover strategy twice: once unfiltered, once trading only while the state is red or green. Report how much the filter improved profit factor and drawdown.

Scheduled and unscheduled catalysts for this coin: news scored for real price impact, security incidents, and upcoming token unlocks that add supply.

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 QNT using /api/v1/event/regime/QNT 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 QNT 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.