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An hourly crypto “market thermometer” can summarize selected market measurements without placing a single order. That was the boundary in this project: build an observational indicator, not a trading bot. The distinction matters because an indicator is a view of chosen data—not a diagnosis of the whole market, a price forecast, or proof of a profitable strategy.
What an hourly crypto market thermometer can—and cannot—tell you
A thermometer turns several readings into a compact picture of conditions. For crypto, those readings might describe price movement, derivatives positioning, funding, liquidity, or sentiment. Combining them can make a dashboard easier to scan, but the resulting score reflects the inputs and rules selected for it.
That makes the indicator useful as a monitoring aid: it can help a reader notice that several measurements have changed together. It does not establish why they changed, what prices will do next, or whether a trade is warranted. The available project information does not specify the assets, sources, formula, weights, display, or validation results, so none of those details—or any trading performance—can be inferred here.
How to think about hourly data inputs
One concrete example of an hourly-capable source is Binance’s official USDⓈ-M Futures REST API documentation. Its historical open-interest statistics endpoint lists 1h as a supported period, while limiting retrievable history to the latest month. That is an endpoint specification, not evidence that this project used Binance or that every relevant field updates hourly.
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| Input or source | What it describes | Cadence and lookback established here | Scope and interpretation |
|---|---|---|---|
| Binance historical open-interest statistics | Open interest, a derivatives-market measure | 1h is a documented period; only the latest month is available from this endpoint, according to Binance documentation. |
Futures-market data, not a measure of the entire crypto market. |
| Binance funding-rate history | Funding rates, a derivatives-market measure | The API documents a funding-rate history endpoint; an hourly refresh cadence is not established by the cited documentation details. | Funding conditions on the relevant futures market, not broad market sentiment by itself. |
| CoinGecko Fear & Greed Index | A composite sentiment indicator | The page describes the index and its components; an hourly refresh cadence is not established here. | Its stated dimensions include market structure, on-chain activity, liquidity and capital flows, volatility, and momentum. |
| Alternative.me Crypto Fear & Greed Index API | Programmatic access to its index | An API is identified; hourly refresh cadence is not established by the cited page. | An index access point, not proof of a particular refresh schedule or a complete market measure. |
Binance documents open interest and funding rate as distinct data fields and endpoints. They can add context about derivatives positioning and funding conditions, but they say nothing directly about every spot market, asset, or participant. A score that uses them should be understood as a selected view of market conditions rather than a universal crypto sentiment reading.
Why a composite score needs an explanation
Published indexes illustrate how different a “market mood” score can be depending on its ingredients. CoinGecko describes dimensions including market structure—with perpetual-market funding, open interest relative to its recent average, and the spot/perpetual spread—as well as on-chain activity, liquidity and capital flows, volatility, and momentum. This is one publisher’s methodology, not a formula that can be attributed to the project described in the title.
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Alternative.me identifies its Crypto Fear & Greed Index and an API on its index page. The existence of that API establishes programmatic access, not an hourly update schedule. Before treating any input as hourly, a builder needs to verify its actual publication cadence and timestamp behavior; otherwise a dashboard refreshed every hour may simply repeat an older reading.
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Keep the thermometer separate from the trading system
The title’s defining choice was to refuse to let the indicator trade. In practical terms, that keeps measurement and execution as separate jobs: an observational display can calculate or present readings without being authorized to submit orders. No implementation details are established here, so this is the design boundary to preserve, not a claim about a particular code architecture.
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- Monitoring: show selected measurements and when they were last updated.
- Interpretation: explain what each input measures and what market it covers.
- Execution: placing trades is a separate capability and is not implied by calculating a score.
This separation is especially useful when inputs have different scopes or update schedules. It prevents a compact number from being mistaken for an instruction and makes stale or venue-specific data easier to recognize.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Questions to settle before relying on an hourly reading
- What is the market scope? Identify the assets and venues represented. A single venue’s futures data should not be presented as if it describes every crypto market.
- Does each source really update hourly? Distinguish the dashboard’s refresh interval from the source’s publication interval, and show timestamps where possible.
- How much history is available? Binance’s cited historical open-interest statistics endpoint, for example, documents only the latest month. That constrains how far back that endpoint alone can support analysis.
- What happens when data is missing or late? A score should not silently imply that every input is current when one is unavailable or delayed.
- What does the score mean? State the inputs and combination logic. Without those, readers cannot tell whether a change reflects price momentum, positioning, funding, or another factor.
- Has it been evaluated? The cited API and index pages document data access and methodology, not the accuracy or investment usefulness of this particular thermometer.
Exchange documentation can change, including supported periods and access conditions. Check the live endpoint documentation before building around a data source; do not assume that a documented interval guarantees a particular update time or uninterrupted availability.
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