Liquidity Proxies are measurable variables or indicators used to estimate the liquidity of a financial asset or market when direct, real-time order book depth information is unavailable or incomplete. This is particularly relevant in fragmented crypto markets.
Mechanism
These proxies often encompass trading volume, observed bid-ask spread (even if derived from aggregated data), transaction frequency, market impact of orders, and historical volatility. For OTC or RFQ markets, the quantity and responsiveness of quotes received also serve as proxies.
Methodology
Quantitative analysis applies statistical models to historical data and available market metrics to infer underlying liquidity conditions. The precise selection and calibration of these proxies enable algorithmic trading systems to make informed decisions regarding trade sizing and execution venue selection.
Quantitatively modeling slippage for illiquid assets involves building a dynamic, multi-factor econometric engine to forecast the cost of friction in information-poor environments.
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