More Buyers Than Sellers? Why Stock Prices Move When Every Trade Has Both

“Stocks fell today because there were more sellers than buyers.” The sentence shows up in market wrap-ups, group chats and reply threads, and it invites an obvious objection: every share sold was bought by someone. A trade needs both sides. Count the shares that changed hands on any day, in any stock, and the shares bought equal the shares sold, exactly.

The objection is correct, and it still leaves the question open. If purchases and sales always match, what pushed the price down? The answer sits in the orders that were waiting to trade, the orders that were pulled before they could, and the prices each side would accept. Those need not balance, and some of them move prices without any trade at all.

Short version: executed shares always balance. Three other things can be lopsided: the number of people on each side, the shares people want to trade at the current price, and which side is in a hurry. A seller who wants out now trades against the best bids and then the next-best ones, so the price falls while every share sold still has a buyer. Quotes can also drop with no trade when buyers withdraw their bids. For your own trades, the useful lessons are about execution: check the spread, size orders against the displayed depth, and use limit orders in thinly traded funds.

What has to balance, and what can be lopsided

“More sellers than buyers” can mean four different things, and only one of them is impossible.

What you count	Must buyers equal sellers?	Example of an imbalance
Shares traded	Yes, always	None is possible
People or accounts	No	One fund buys 10,000 shares from 40 different sellers
Shares people want to trade at the current price	No	Holders want to sell 500,000 shares at $100; bids total 50,000
Who initiated the trade	No	Most of the day’s volume came from sellers hitting bids

The last two are measured and published. Exchanges report the third one by rule before their opening and closing auctions. Nasdaq’s closing cross feed reports “Paired Shares,” defined as “the number of on-close shares that Nasdaq is able to pair off at the current reference price,” next to an “Imbalance Quantity,” “the number of closing shares that are seeking additional liquidity at the current reference price,” and an imbalance side of buy or sell.¹ NYSE’s imbalance feed carries the same fields.² When a market reporter says there is a sell imbalance into the close, this is usually the number behind it: shares offered at the expected auction price that no buy order has yet matched. The auction price then moves until enough of them are paired.

The fourth meaning is what researchers call signed order flow. Each trade has two sides, but one side was waiting with a limit order and the other arrived and accepted that price. A trade at the bid is classed as seller-initiated, a trade at the ask as buyer-initiated. Lee and Ready’s 1991 algorithm assigns the sign from trade and quote data,³ and studies that could check it against true trade signs found it right about 81% of the time on Nasdaq in the 1990s and about 87% to 94% in a 2010s Nasdaq sample, depending on timestamp precision.⁴⁵ So “sellers outnumbered buyers” is defensible shorthand for “most volume was seller-initiated.” It is wrong only when it claims that more shares were sold than bought.

Walk the book: one seller, four buyers

Exchanges match stock and ETF orders in a limit order book: a list of standing offers to buy (bids) and to sell (asks), each with a price and a size. Here is a small synthetic book. The best bid is $100.00, the best ask is $100.05, so the spread is 5 cents and the midpoint is $100.025.

Bids (buy orders)	Shares	Asks (sell orders)	Shares
$100.00	100 (one order)	$100.05	100
$99.95	150 (two orders)	$100.10	200
$99.90	300 (two orders)	$100.15	300
$99.85	400	$100.20	400

A holder sends a market order to sell 400 shares. The order takes the best price first and works down:

100 shares at $100.00 from one buyer
150 shares at $99.95 from two buyers
150 shares at $99.90, part of a 200-share order from one buyer

The seller receives $39,977.50, an average of $99.94375 a share. That is $22.50 less than 400 shares at the $100.00 bid the seller saw on screen, and $32.50 less than 400 shares at the starting midpoint. The last trade prints at $99.90, the best bid is now $99.90, and the midpoint has moved from $100.025 to $99.975. Four buyers bought exactly the 400 shares one seller sold. The price fell because the seller wanted to trade more shares right away than the buyers were offering to take at $100.00.

The average price the seller gets is the volume-weighted average of the fills, where $q_i$ is the number of shares filled at price $p_i$ :

\bar{p} = \frac{\sum_i q_i \, p_i}{\sum_i q_i} = \frac{100(100.00) + 150(99.95) + 150(99.90)}{400} = 99.94375

Try it below. Change the order size and side, send several orders in a row, or cancel the best bid instead of trading.

Prices move without a trade

Press “Cancel the best bid” in the book above on a fresh book. The buyer at $100.00 withdraws 100 shares. Nobody trades. The best bid falls to $99.95 and the midpoint to $100.00, while the last trade price stays wherever it was. A quote screen now shows a lower price, and no seller accepted anything.

This is the normal state of a modern market. The SEC publishes daily exchange data on how much displayed order volume ever trades. Averaging those daily figures for the second quarter of 2026, we found that of every 100 shares posted in displayed stock orders on exchanges, about 4.3 traded during continuous trading. The rest were canceled or expired. For exchange-traded products the figure was 0.21 per 100. On a count basis, exchanges logged about 17 cancellations per trade in stocks and 139 per trade in ETPs.⁶ The SEC suggests the lower ETP figure reflects arbitrage: traders keep an ETP’s price in line with its underlying holdings by canceling and replacing their limit orders as those holdings move, “whether the ETP trades or not.”⁷ These figures cover exchange order books only. Trades routed to wholesalers and other off-exchange venues are not in the denominator.

Withdrawn and repriced orders also carry information. Brogaard, Hendershott and Riordan traced price discovery, the process of prices moving toward their eventual level, in 15 large Canadian stocks from October 2012 to June 2013. About 45% came through limit orders and about 30% through market orders, with the remainder not assigned to either.⁸ One reason limit orders matter: a liquidity provider who suspects the next trader knows something about the stock protects itself by quoting a wider spread or pulling its order. Glosten and Milgrom’s 1985 model shows how that risk alone produces a bid-ask spread.⁹

Four prices on one screen

A brokerage screen can show four numbers that people loosely call “the price”: the last trade, the best bid, the best ask and the midpoint between them. They answer different questions. The last trade tells you what happened. The bid is what you could sell for now, for the displayed size. The ask is what you would pay. The midpoint is the usual benchmark for what the stock is worth at that moment.

The last trade can move while the quotes stand still. If the bid is $99.99 and the ask $100.01, a buyer-initiated trade prints at $100.01 and the next, seller-initiated, at $99.99. The last price fell two cents and the midpoint never moved. Roll showed in 1984 that this bid-ask bounce makes successive trade-price changes negatively correlated, and used that to estimate spreads from prices alone.¹⁰ The SEC’s investor site warns that “the last-traded price is not necessarily the price at which a market order will be executed.”¹¹

Pressure without news still moves prices

If prices only reflected information, a buyer with no new information should be able to buy a large block at the prevailing price. The evidence says otherwise. When Standard & Poor’s adds a stock to the S&P 500, index funds have to buy it, and the addition says nothing new about the company’s profits. Shleifer found that additions from 1976 to 1983 gained 2.79% on the announcement day on average, with more than 95% of them positive, and that the gain did not disappear for at least ten days.¹² Harris and Gurel found a rise of more than 3% that was “nearly fully reversed after 2 weeks.”¹³ The effect has since shrunk, from an average of 7.4% in the 1990s to less than 1% over the past decade, according to Greenwood and Sammon.¹⁴

Forced selling shows the same pattern in the other direction. Mutual funds hit with large redemptions have to sell what they hold, and Coval and Stafford found that this pushes down the prices of the stocks those funds share, and that investors who take the other side earn significant returns for providing liquidity. In the working-paper version, covering 1980 to 2003, stocks under the heaviest forced selling had abnormal returns of about −10% in the quarter of the selling and recovered about 7.7% over the next three quarters, most but not all of the loss.¹⁵

At the scale of seconds, Cont, Kukanov and Stoikov measured the same mechanism in the order book itself. For 50 randomly chosen S&P 500 stocks in April 2010, the net change in buy and sell interest at the best quotes over 10-second intervals, counting new limit orders, cancellations and market orders, explained 65% of midpoint changes on average. Imbalance in executed trades alone explained 32%. The same imbalance moved prices more when the book was thin: the price response was inversely proportional to depth.¹⁶ Part of that fit is mechanical, because some of the events counted are the ones that change the best price. The authors report that removing them still left 35% to 60% explained.

For large orders worked over a day, the cost grows with size, though less than proportionally. The empirical rule, called the square-root law, relates the price impact $\Delta$ of buying or selling $Q$ shares to the stock’s daily volatility $\sigma$ and daily volume $V$ :

\Delta \approx Y \, \sigma \sqrt{\frac{Q}{V}}

Tóth and coauthors report $Y$ “of order unity” and estimated exponents between 0.4 and 0.7 rather than exactly one-half.¹⁷ With $Y = 1$ , an order equal to 1% of a day’s volume moves the price by about a tenth of a day’s volatility. Aggregate market flows are a separate and more contested question; Who Moves the Stock Market? covers Gabaix and Koijen’s estimate that $1 of new money into stocks raises total market value by about $5, and the case against it.

Liquidity can also disappear faster than sellers arrive. On May 6, 2010, a mutual fund complex began selling 75,000 E-mini S&P 500 futures contracts, worth about $4.1 billion, through an algorithm that targeted 9% of the previous minute’s volume “without regard to price or time.” Buy-side depth in the E-mini fell to about $58 million, less than 1% of its level that morning. The joint SEC and CFTC staff report drew a lesson that applies well beyond that day: “high trading volume is not necessarily a reliable indicator of market liquidity.”¹⁸

Market value moves more than the cash that trades

Take a hypothetical company with 1 billion shares at $100, a market value of $100 billion. A downgrade comes out, and over the day 15 million shares trade at an average of $97 while the price closes at $95. Market value fell by $5 billion. The dollars that changed hands were about $1.5 billion, and every one of them went from a buyer to a seller. The $5 billion is a repricing of all 1 billion shares, including at least 985 million that did not trade that day. It did not “leave the market.”

John Hussman puts the accounting plainly: a share, once issued, “must be held by some investor at every moment in time, until that share is retired,” and “every share that’s sold by one investor is bought by another.”¹⁹ The exceptions are the transactions with the company itself. A stock offering or IPO adds shares and moves cash from investors to the firm, and a buyback does the reverse. The same identity sits behind the “cash on the sidelines” phrase that Cliff Asness lists among his pet peeves.

What this changes for your own trades

None of this produces a trading signal for an individual investor. Chordia, Roll and Subrahmanyam studied aggregate order imbalance for NYSE-listed S&P 500 stocks from 1988 to 1998. They found that imbalances moved market returns the same day, and that returns tended to reverse after days of heavy selling and large declines, but they found no evidence that imbalances predict the next day’s market return.²⁰ A 2023 deep-learning study of 115 Nasdaq stocks found real predictive information in order flow, with an effective horizon of about two average price changes.²¹ A signal that fades within a couple of price ticks is gone long before it can show up in a headline.

What the mechanics do change is how you place orders:

Look at the spread before you trade. A market order sells at the bid or buys at the ask, so half the spread is a cost against the midpoint on every trade. For a large, heavily traded fund the spread is often a penny, and it hardly matters. For a small or new ETF, a thinly traded stock, or any security in a fast market, it can be much wider.
Compare your order with the displayed size. A quote is good only for the shares shown. As the SEC puts it, “price quotes are only for a specific number of shares,” so a larger order can fill partly at worse prices, as in the book above.²²
Use a limit order when the spread is wide. A market order guarantees execution at whatever price the book offers; a limit order guarantees your price or better at the risk of no fill.¹¹²³ Stop orders become market orders when triggered, with the same exposure to a thin book; see our stop-loss guide.
Read “selling pressure” headlines as description. They report what already happened to prices. In a taxable account, selling in response can also realize capital gains, a cost that no order type avoids.

Frequently Asked Questions

Can there be more sellers than buyers in the stock market?

Not in shares traded: every share sold is bought. There can be more selling accounts than buying accounts, more shares offered than bid at the current price, or more trades initiated by sellers. Exchanges publish that second kind as an auction imbalance.

If every trade has a buyer, why does a stock fall on heavy selling?

Sellers in a hurry trade against the best bids first, then the next-best ones at lower prices, and buyers who see the selling lower or withdraw their own bids. Each trade still has a buyer; the buyers are paying less than the previous ones.

What does “order imbalance” mean in market news?

Usually the exchange-published auction figure before the open or the close: the number of shares on one side that are not yet matched at the expected auction price. A buy imbalance means more shares are bid than offered at that price, so the auction price tends to rise until more sellers join.

Why did the price change when the stock barely traded?

Quotes change when limit orders are added, repriced or canceled, which happens far more often than trades. The last-trade price can also hop between the bid and the ask while the midpoint is unchanged.

Does money flow into or out of the stock market when prices change?

Not on secondary-market trades. A buyer’s cash goes to the seller, so the total cash held by investors is unchanged. Cash moves between investors and companies only through issuance and buybacks.

Should I use a market order or a limit order?

For a large, liquid fund during normal trading, a market order usually fills at the quoted price. When the spread is wide, the security trades thinly, or your order is large compared with the displayed size, a limit order caps the price you pay or accept, at the risk of not filling.

Key Takeaways

Shares bought always equal shares sold. “More sellers than buyers” is wrong only if it means more shares were sold than bought.
Other things can be lopsided. People per side, shares wanted at the current price, and who initiated the trades can all differ, and exchanges publish auction imbalances by rule.
Urgent orders move prices through the book. In the worked example, one 400-share market sell traded with four buyers and moved the bid from $100.00 to $99.90.
Quotes move without trades. In Q2 2026, about 4.3 of every 100 shares posted in displayed stock orders on exchanges traded, by our average of SEC data.
Use the mechanics for execution. Check the spread, compare your order with the displayed size, and use limit orders in thin markets. Order-flow headlines are not a trading signal.

Related Guides

Should Long-Term Index Investors Use Stop-Loss Orders?: how stop orders become market orders, and what happened to them in the 2010 flash crash.
Who Moves the Stock Market?: the aggregate version of this question, from fixed-mix funds to the inelastic markets hypothesis.
Cliff Asness’s 10 Investing Pet Peeves, Revisited: why “cash on the sidelines” cannot enter the market in aggregate.
Mega-IPOs and Your Index Funds: index-inclusion buying and free float.
What It Actually Costs to Launch an ETF: market makers, authorized participants and how ETF spreads form.
Stock Valuation for DIY Investors: how expected cash flows set the level that order flow moves prices around.
The Stock Market Is Not the Economy: another case where the obvious explanation for price moves fails.

Sources

Nasdaq. Nasdaq Closing Cross FAQ. Definitions of Paired Shares, Imbalance Quantity and Imbalance Side, with worked examples.
NYSE. XDP Imbalances Feed Client Specification, v2.2c. PairedQty, TotalImbalanceQty and ImbalanceSide at the auction reference price, “the notional likely price of the auction trade.”
Charles M. C. Lee and Mark J. Ready, “Inferring Trade Direction from Intraday Data”, Journal of Finance 46(2), 1991, 733–746.
Katrina Ellis, Roni Michaely and Maureen O’Hara, “The Accuracy of Trade Classification Rules: Evidence from Nasdaq”, Journal of Financial and Quantitative Analysis 35(4), 2000, 529–551. Lee-Ready classified 81.05% of trades correctly.
Allen Carrion and Madhuparna Kolay, “Trade Signing in Fast Markets”, Financial Review 55(3), 2020, 385–404. Lee-Ready accuracy of 86.88% with one-second timestamps and 93.57% with millisecond timestamps.
U.S. Securities and Exchange Commission, Market Structure Metrics by Exchange, 2012 Q1 to 2026 Q2 download, file etp_stock_timeseries3.csv; definitions in the Market Activity Report Methodology. Our figures are simple means of the 62 daily values from April 1 to June 30, 2026. The SEC notes that the cancel-to-trade ratio “does not provide an exact numerical representation of what actually happens to orders.”
U.S. Securities and Exchange Commission, Data Highlight 2013-01: Trade to Order Volume Ratios, October 9, 2013. Defines the metric over displayed limit orders at all price levels, excluding opening and closing crosses.
Jonathan Brogaard, Terrence Hendershott and Ryan Riordan, “Price Discovery without Trading: Evidence from Limit Orders”, Journal of Finance 74(4), 2019, 1621–1658. Sample: 15 TSX 60 stocks not cross-listed in the U.S., October 15, 2012 to June 28, 2013, IIROC regulatory data. Author PDF, p. 1643.
Lawrence R. Glosten and Paul R. Milgrom, “Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders”, Journal of Financial Economics 14(1), 1985, 71–100.
Richard Roll, “A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market”, Journal of Finance 39(4), 1984, 1127–1139.
Investor.gov (SEC), Types of Orders.
Andrei Shleifer, “Do Demand Curves for Stocks Slope Down?”, Journal of Finance 41(3), 1986, 579–590. Table I, 1976–83 additions (N = 102).
Lawrence Harris and Eitan Gurel, “Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures”, Journal of Finance 41(4), 1986, 815–829.
Robin Greenwood and Marco Sammon, “The Disappearing Index Effect”, Journal of Finance 80(2), 2025, 657–698.
Joshua Coval and Erik Stafford, “Asset Fire Sales (and Purchases) in Equity Markets”, Journal of Financial Economics 86(2), 2007, 479–512. Magnitudes quoted from the 2005 NBER working paper 11357; the published version extends the sample to 2004.
Rama Cont, Arseniy Kukanov and Sasha Stoikov, “The Price Impact of Order Book Events”, Journal of Financial Econometrics 12(1), 2014, 47–88. arXiv version, Tables 2 and 4 and footnote 3.
Bence Tóth, Yves Lempérière, Cyril Deremble, Joachim de Lataillade, Julien Kockelkoren and Jean-Philippe Bouchaud, “Anomalous Price Impact and the Critical Nature of Liquidity in Financial Markets”, Physical Review X 1, 021006, 2011.
Staffs of the CFTC and SEC, Findings Regarding the Market Events of May 6, 2010, September 30, 2010, pp. 2–3.
John P. Hussman, “Marks of a Phase Transition”, Hussman Funds market comment, November 2019.
Tarun Chordia, Richard Roll and Avanidhar Subrahmanyam, “Order Imbalance, Liquidity, and Market Returns”, Journal of Financial Economics 65(1), 2002, 111–130.
Petter N. Kolm, Jeremy Turiel and Nicholas Westray, “Deep Order Flow Imbalance: Extracting Alpha at Multiple Horizons from the Limit Order Book”, Mathematical Finance 33(4), 2023, 1044–1081.
Investor.gov (SEC), Executing an Order.
FINRA, Order Types.

Editor’s note

The SEC order-volume averages are reproduced by summitward-research/more-buyers-than-sellers, which downloads the SEC file and prints every figure quoted here. The order book in the worked example and the interactive tool is synthetic. Its numbers are pinned by unit tests on the same code the tool runs.