- 5m ·
15m · 1h · 1dTimeframes - All fourPer asset
- Shared clockAligned
- BTC /
ETH / SOL / XRPAssets
A signal that looks great on the 5-minute book can be fighting the daily trend without you knowing. Multi-timeframe analysis fixes that: use the slow timeframe for context and the fast one for timing, so your entries line up with the bigger move instead of against it.
Each crypto asset is captured at 5m, 15m, 1h, and 1d simultaneously. That means you do not have to choose a single resolution, you can read the same market at several scales at once and let them check each other.
Each timeframe has a job
Slow for context
The 1-hour and daily markets tell you the prevailing direction, the trend you do not want to fight.
- Prevailing bias
- Trend filter
- Bigger picture
Fast for timing
The 5- and 15-minute books give precise entries and exits once the slow timeframe has set the direction.
- Sharp entries
- Tighter stops
- Less guesswork
Agreement filters noise
Acting only when fast and slow agree cuts out the marginal trades that quietly bleed an account.
- Confluence required
- Fewer false starts
- Higher conviction
Keeping the timeframes aligned
Because all four timeframes for an asset come from the same pipeline with consistent timestamps, lining them up is straightforward, the slow series provides the backdrop for each fast snapshot with no awkward resampling. The result is a clean confluence check rather than a manual eyeballing of separate charts.
- 5mEntry timing, sharpest, noisiest
- 15mNear-term momentum, smooths the 5m chop
- 1hSession context, the working trend
- 1dPrevailing bias, the move not to fight
A signal is only as good as the context around it. The fast timeframe tells you when; the slow timeframe tells you whether you should be looking at all.
A practical confluence workflow
Multi-timeframe analysis is less a single indicator than a sequence of checks. The order matters: establish the backdrop before you go hunting for entries, so the fast timeframe is filtering a trend you already trust rather than inventing one from noise.
- 1Read the daily and 1-hour markets first to fix the prevailing direction.
- 2Drop to the 15-minute book to confirm momentum is pointing the same way.
- 3Use the 5-minute book only for the entry, once the slower frames agree.
- 4Stand aside when the timeframes disagree, the absence of confluence is itself a signal.
- 5Re-check the slow frame periodically; context drifts, and a stale backdrop is worse than none.
One market, four lenses
Each crypto asset is captured at every timeframe at once, so you read one market through four resolutions without stitching feeds.
- No feed-merging
- Consistent fields
- Same Up/Down market
Shared capture clock
Millisecond timestamps from one pipeline mean the slow series lines up against each fast snapshot exactly.
- Millisecond stamps
- No resampling guess
- Clean overlays
A durable filter
Requiring agreement across frames is a simple rule that survives regime change, it is method, not a fitted parameter.
- Confluence over curve-fitting
- Fewer marginal trades
- Holds across regimes
Trade with the bigger move
Most marginal losses come from taking a clean fast-timeframe signal that happens to be against the prevailing trend. Requiring the slow timeframe to agree is a simple, durable filter, and the same data exposes both, so there is nothing to stitch together.
Pull the timeframes
The crypto data page lists every timeframe; the historical guide shows how to query each and align them.
Frequently asked questions
Which timeframes are available per crypto market?
Each crypto asset, BTC, ETH, SOL, XRP, is captured at 5m, 15m, 1h, and 1d simultaneously, so you can read the same market at multiple resolutions and combine them for multi-timeframe analysis.
Why use multiple timeframes instead of one?
The slow timeframe gives you the prevailing direction (the trend to trade with), and the fast timeframe gives precise entry timing. Acting only when they agree filters out marginal trades that go against the bigger move.
Is it hard to align the timeframes?
No. All four timeframes for an asset come from the same capture pipeline with consistent timestamps, so the slow series lines up against each fast snapshot cleanly, no special resampling needed to build a confluence check.
What should I do when the timeframes disagree?
Treat disagreement as a reason to stand aside, not a coin toss. If the daily and hourly markets point one way while the 5-minute book points the other, the marginal trade is the one most likely to bleed. The durable rule is to act only when the slow context and the fast timing line up, and to re-check the slow frame periodically so you are filtering against current context rather than a stale one.