Classify macro liquidity environment as expanding, contracting, or stable
Answers whether the crypto liquidity backdrop is expanding, contracting, or stable. It reads the global market data (total market cap, BTC dominance, 24h change) and top stablecoin supply versus the prior day to gauge stablecoin supply entering or leaving circulation. A rules-based classifier sets the regime, and an analyst pass explains what the reading describes. It is a top-down description of market-wide liquidity conditions, not a signal to add or reduce exposure.
A liquidity regime read - and an entry mostly about what its inputs can and cannot support.
THE IDEA. Liquidity conditions - how much money is available and how willingly it is deployed - bear on asset prices, and in traditional macro that intuition is supported by decades of study of monetary aggregates and financial conditions indices. Applying it to crypto is reasonable in principle.
THE INPUTS. Total market capitalisation, BTC dominance, 24-hour change, and top stablecoin supply against the prior day.
EXAMINE EACH, because the composite is only as good as they are.
WHAT A GENUINE LIQUIDITY MEASURE WOULD LOOK AT - and first, WHICH liquidity, because two distinct concepts share the word. MARKET liquidity is the capacity to absorb trading, measured by order-book depth and bid-ask spreads across venues. FUNDING liquidity is the availability of capital and leverage, spoken to by stablecoin supply, funding rates, credit conditions and flows into the asset class. This analysis estimates the second, and its inputs are mostly price and supply aggregates: it reads no order books or spreads, so it does not measure market liquidity.
A RULES-BASED CLASSIFIER THEN AN ANALYST PASS is a sound division: thresholds are deterministic and reproducible, and the model explains rather than decides. The thresholds are the analysis - move them and every regime label changes - and they are our own convention.
AND THE GENERAL DISCIPLINE THIS FAMILY TEACHES. When a composite is built from several inputs, ask of each one what it measures, whether it is independent of the others, and whether it contains the thing the composite is trying to explain. Here two of the inputs are price in different clothing, which is exactly the situation where a composite looks more informative than its parts and is not.
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