--- title: "Trade Size Distribution: Formula" description: "The trade size distribution shows how trades (or volume) are spread across size buckets, such as under 100 shares, 100 to 499 and so on. It describes the..." canonical: https://www.getswoopr.com/indicators/market-microstructure/trade-size-distribution/ source: "Swoopr Investment: https://www.getswoopr.com" --- ## Direct Answer > The trade size distribution shows how trades (or volume) are spread across size buckets, such as under 100 shares, 100 to 499 and so on. It describes the full shape of trade sizes, unlike a single average. Trade counts are normally concentrated in small sizes while volume has a heavier share in larger sizes. # Trade Size Distribution: Formula, Meaning, Signals, Examples and How to Use It ## How Is Trade Size Distribution Calculated? The trade size distribution shows how trades (or volume) are spread across size buckets, such as under 100 shares, 100 to 499 and so on. It describes the full shape of trade sizes, unlike a single average. **Formula:** `Share in bucket k = number of trades (or volume) with size in bucket k / total number of trades (or total volume)` **Inputs:** - Trade prints with sizes - Size bucket boundaries - Count-based or volume-based shares **Worked example.** 7,200 trades in the smallest bucket out of 10,000 total mean that bucket holds 72.0% of trades. The inputs are illustrative numbers, not market data. **Reading it.** Trade counts are normally concentrated in small sizes while volume has a heavier share in larger sizes. A shift of mass toward small trades often accompanies order slicing and growth in retail activity, and a fatter tail points to block trading. **Limits.** The buckets are a choice, and count-based and volume-based views tell different stories. A single parent order split into many child trades is indistinguishable from many unrelated small traders in the print data. ## What is Trade Size Distribution? The trade size distribution shows how trades (or volume) are spread across size buckets, such as under 100 shares, 100 to 499 and so on. It describes the full shape of trade sizes, unlike a single average. ## How to use Trade Size Distribution Trade counts are normally concentrated in small sizes while volume has a heavier share in larger sizes. A shift of mass toward small trades often accompanies order slicing and growth in retail activity, and a fatter tail points to block trading. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime. ## Strengths - Reporting every bucket shows whether volume comes from many small or few large trades, which an average hides. - Shares in buckets sum to one, so the distribution is comparable between stocks and periods of different volume. - Reproducible when the formula and data convention are fixed. ## Weaknesses and limitations - Bucket edges are conventional, such as 100 or 500 shares, so changes near an edge show up as large shifts between neighboring buckets. - Round numbers dominate trade sizes, as in 100 or 200 shares, so a distribution reflects human order habits as well as market structure. - Correlated indicators can create false confidence by repeating the same underlying information. ## Editorial and risk note This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance. ## Frequently Asked Questions Is Trade Size Distribution a buy or sell signal? No. Trade counts are normally concentrated in small sizes while volume has a heavier share in larger sizes. The buckets are a choice, and count-based and volume-based views tell different stories. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions. What is the best setting for Trade Size Distribution? Trade Size Distribution is computed from trade prints with sizes; size bucket boundaries; count-based or volume-based shares, so the choices that matter are the data convention and the window it is read over. Test those across instruments, regimes and out-of-sample periods instead of fitting one historical winner. Can Trade Size Distribution be used by itself? The buckets are a choice, and count-based and volume-based views tell different stories. A single parent order split into many child trades is indistinguishable from many unrelated small traders in the print data. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone. Does Trade Size Distribution work on every timeframe? The calculation (Share in bucket k = number of trades (or volume) with size in bucket k / total number of trades (or total volume)) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it. Why does Trade Size Distribution give false signals? Bucket edges are conventional, such as 100 or 500 shares, so changes near an edge show up as large shifts between neighboring buckets. Round numbers dominate trade sizes, as in 100 or 200 shares, so a distribution reflects human order habits as well as market structure. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated. How should Trade Size Distribution be backtested? Rebuild Trade Size Distribution from trade prints with sizes using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline. S Swoopr Editorial Team The Swoopr Editorial Team produces independent investment education, research, and tools for understanding markets, evaluating opportunities, and managing risk. All content is educational only and does not constitute personalized investment advice. See our [editorial policy](https://www.getswoopr.com/legal/editorial-policy/) and [corrections policy](https://www.getswoopr.com/legal/corrections-policy/).