Corwin-Schultz Spread Estimator

Install and import#

npm install fintech-algorithms

import { corwinSchultzSpread } from "fintech-algorithms/market-microstructure/liquidity-and-spreads/corwin-schultz-spread-estimator";

Signature#

corwinSchultzSpread(highDay1, lowDay1, highDay2, lowDay2, clipNegative)

Estimates the spread from daily high-low ranges over two days, exploiting that the range reflects both volatility and spread while volatility scales with time and the spread does not. Frequently returns negative values, which are theoretically impossible.

Parameters#

Returns#

{ spread, raw_spread, beta, gamma, alpha, clipped }

The estimate with every intermediate, and whether clipping was applied.

Errors#

• When any high is below its low — throws

Complexity: time O(1), space O(1).

Worked example#

executed Captured by running this function on the input its own test provides. Real output of real code — but not asserted against a published figure.

Input#

101

99

101.5

99.5

true

Call#

corwinSchultzSpread(highDay1, lowDay1, highDay2, lowDay2, clipNegative)

Returns#

object with 9 fields: model, beta, gamma, alpha_raw, alpha_used, spread_estimate_relative, spread_estimate_bps, clip_negative, …

{
  "model": "corwin-schultz-spread",
  "beta": 0.0007960826118720654,
  "gamma": 0.0006219511446669105,
  "alpha_raw": 0.007908933752463966,
  "alpha_used": 0.007908933752463966,
  "spread_estimate_relative": 0.007908892526591878,
  "spread_estimate_bps": 79.08892526591879,
  "clip_negative": true,
  "state": "estimated"
}

Other exports#

This module also exports quotedSpread, effectiveSpread, realizedSpread, rollSpread, amihudIlliquidity, calculate. Every module additionally exports run as an alias of its primary function, and a meta object carrying its catalog id, domain, family, shape and article URL.

Diagrams#

Calculation flow#

flowchart LR
    A["Question: Can two consecutive daily high–low ranges separate spread from fundamental volatility?"] --> B["Freeze instrument, scope, clock, units, and variant"]
    B --> C["Validate Corwin-Schultz Spread Estimator inputs"]
    C --> D{"Eligible and synchronized?"}
    D -- "No" --> E["Reject with topic-specific reason"]
    D -- "Yes" --> F["Apply the frozen High–low spread formula"]
    F --> G["Expose intermediate value and decision state"]
    G --> H{"Direct measure or model-based proxy?"}
    H --> I["Report result with its unit and limitation"]

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

• Corwin and Schultz (2012), A Simple Way to Estimate Bid-Ask Spreads — The Journal of Finance
• NYSE Daily TAQ product description — New York Stock Exchange

The rest of the Liquidity and Spreads family#

• Quoted SpreadAsk minus bid — what the book advertises.
• Effective SpreadTwice the signed distance from the midpoint to the trade price — what the trade actually paid.
• Realized SpreadThe effective spread measured against the midpoint *after* a horizon, which strips out the permanent price impact and leaves wh…
• Roll Spread EstimatorInfers the effective spread from the negative serial covariance of price changes alone — no quote data required.
• Amihud Illiquidity RatioAverage absolute return per unit of dollar volume — how much price moves per dollar traded.