Why one asset has many prices
An asset rarely trades in only one place. Each source has its own buyers and sellers, its own liquidity, and its own moment-to-moment supply and demand, so quotes differ slightly even for the same instrument at the same instant. A single source reflects only that venue's view, including conditions such as thin liquidity, a brief dislocation, or a stale quote. Aggregation addresses how to combine these partial views into one reliable value.
How aggregation produces one value
Aggregation collects quotes from several independent sources and combines them into a single price. Rather than a simple average, a well-constructed fair price weights each source by its reliability and liquidity and excludes values that deviate too far from the consensus before combining the remainder. The result tracks the broad market rather than any one venue and updates continuously as new quotes arrive. The specific weighting and filtering distinguish a robust fair price from a plain average.
Why it is more robust
A single feed represents a single point of failure. If that source lags, becomes thin, or prints a bad quote, anything relying on it inherits the error. An aggregated price is resistant to all three: an outlier is filtered before it affects the result, a thin source is down-weighted, and the loss of any one input still leaves a usable consensus. This robustness also makes aggregated prices harder to manipulate, since influencing the result would require moving many sources at once rather than one.
Where a fair price applies
An aggregated fair price is the natural reference wherever a single defensible value is required rather than a venue-specific quote, including portfolio valuation, settlement, alerting, and headline price display. It is not a statement about the price at which a transaction can be executed on a particular venue, which depends on that venue's own order book. It is a representative market price designed to be stable and resistant to distortion.
Fair price on SiftingIO
Fair-price aggregation is central to SiftingIO. The platform ingests quotes from multiple independent sources across crypto, forex, and commodities, computes a weighted, outlier-filtered fair price on a continuous clock, and publishes it under one schema over REST and WebSocket. The full method, including how sources are weighted and how the calculation behaves under stressed market conditions, is documented in the data methodology.