Up / down ticks

Before exchanges provided taker-side classification, researchers had only the sequence of transaction prices to infer trade direction. The tick test — classifying trades based on whether the price rose or fell — remains a surprisingly informative signal even when full trade-side data is available.

The Lee-Ready algorithm and its legacy

Lee & Ready (1991) formalized the tick test as part of their trade classification algorithm: a trade at a price above the previous trade (uptick) is classified as buyer-initiated; a trade below (downtick) is seller-initiated. For trades at the same price (zero tick), the previous non-zero tick determines classification.

While modern crypto exchanges directly report the aggressor side, making the tick test unnecessary for classification, the statistics of uptick/downtick sequences capture something distinct from the aggressor label: how many price levels a trade swept through.

The subtle distinction from trade side

A single large buy can result in multiple consecutive upticks as it walks through the order book — clearing the ask at one level, then the next, then the next. The aggressor-side label reports one buy. The uptick sequence reports three price-improving ticks. This difference captures depth penetration: how far into the book the aggressive order reached.

This is directly related to the market impact literature. Kyle (1985) modeled impact as proportional to signed volume, but Bouchaud et al. (2009) showed that the number of price levels crossed by a single metaorder is an independent predictor of permanent impact, beyond volume alone.

What we compute

• Uptick/downtick count — number of trades at prices above/below the previous trade
• Uptick/downtick volume — total volume transacted on price-improving/declining ticks
• Uptick ratio — fraction of trades that were upticks (range 0 to 1)
• Uptick volume ratio — fraction of total volume occurring on upticks

The momentum quality signal

The volume-on-upticks ratio is a momentum quality metric. When most of an interval's volume occurred on price increases, the move was directionally endorsed by actual trading — not a thin-market drift. This distinction matters:

• High uptick volume ratio with concentrated trade count → a few large aggressive orders clearing multiple levels. Deep market impact, potentially informed.
• High uptick volume ratio with dispersed trade count → many small buyers sustaining incremental upward pressure. Broad-based demand.

French & Roll (1986) showed that prices are more volatile during trading hours than non-trading hours, partly because of the information content of trades. The uptick/downtick decomposition helps identify which trades are carrying that information: those that move price (upticks/downticks) versus those that don't (zero ticks, volume at unchanged prices).

References:

• Lee, C.M.C. & Ready, M.J. (1991). "Inferring Trade Direction from Intraday Data." Journal of Finance, 46(2), 733–746.
• Kyle, A.S. (1985). "Continuous Auctions and Insider Trading." Econometrica, 53(6), 1315–1335.
• Bouchaud, J.-P., Farmer, J.D. & Lillo, F. (2009). "How Markets Slowly Digest Changes in Supply and Demand." In Handbook of Financial Markets: Dynamics and Evolution, 57–160.
• French, K.R. & Roll, R. (1986). "Stock Return Variances: The Arrival of Information and the Reaction of Traders." Journal of Financial Economics, 17(1), 5–26.