The Hasbrouck Information Share (HIS) is an econometric measure that quantifies the contribution of a specific trading venue or market participant to the overall price discovery process of an asset. In crypto markets, HIS determines the proportion of permanent price impact attributable to trades executed on a particular exchange, within an RFQ system, or by a specific algorithm. Its purpose is to assess the informational efficiency and influence of different liquidity pools or trading strategies on the true underlying price of a digital asset. A higher HIS suggests a greater role in establishing the fair market value.
Mechanism
The calculation of HIS involves decomposing observed price changes into transient and permanent components, using high-frequency trade and quote data. This often utilizes vector autoregression (VAR) models to analyze the dynamic interaction between trades and quotes across multiple venues. For crypto, the mechanism requires aggregating granular order book data and executed trade data from various centralized exchanges and decentralized protocols. The model estimates how much a trade on one platform moves the asset’s efficient price, independent of temporary liquidity effects.
Methodology
Applying the Hasbrouck Information Share requires a robust data infrastructure capable of capturing and synchronizing high-frequency data from diverse crypto venues. The methodology involves econometric modeling to estimate the information content of trades and to attribute price changes to specific market activities. For institutional crypto options trading, HIS can inform decisions about optimal execution venues, identify influential liquidity providers, and assess the true cost of market access. Strategically, it aids in understanding which platforms are price leaders versus price takers, guiding smart order routing and RFQ strategies to capture or provide liquidity effectively.
A committee quantifies RFQ information leakage by measuring post-trade price reversion and quote volatility to build a systemic cost model for execution.
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