What is float in stocks? Float vs shares outstanding explained

A stock's float, also called free float or public float, is the number of its shares that the public can actually trade. It equals shares outstanding minus the shares held by insiders, controlling or strategic holders and anyone under a lock-up. Coca-Cola has 4.303 billion shares outstanding and a free float of about 3.874 billion, so 90% of the company trades freely.

Float is one of the few company figures that traders and developers both care about. It drives how violently a price reacts to news, it is the denominator of every short-interest ratio, and index providers use it to weight their members. This explainer works through each idea with real figures from the fundamentals endpoint of TickerLayer's stock API, captured on 2026-09-28 for seven large US companies.

What is float in stocks: float vs shares outstanding

Think of a company's shares as nested sets. Authorized shares are the legal maximum in the company's charter. Outstanding shares are the ones actually issued and held by anyone, excluding shares the company has bought back. The float is the part of the outstanding shares that can trade without restriction.

The gap between outstanding shares and the float is the set of holders who are not expected to sell: founders, executives, board members, parent companies, governments and long-term strategic shareholders. For most large US companies that group is tiny. Coca-Cola is the exception in this sample. Holders the data classifies as insiders own about 9.9% of the company, which is why its float ratio is 90% while the other six sit above 98%.

How free float is calculated

You can check the arithmetic yourself. With insider ownership at 0.099, Coca-Cola's float should be about 4,303,000,000 × (1 − 0.099) = 3,877,003,000 shares, within 0.08% of the reported 3,874,015,338. A small gap is normal, because the inputs come from documents filed on different dates.

That dating problem is why two data sources rarely agree on a float to the share. TickerLayer's fundamentals data handles it explicitly: when a reported float runs up to 5% above shares outstanding, a sign the two figures come from different reporting dates, it is rebuilt as shares outstanding less insider holdings, and when it cannot be reconciled at all the field is omitted rather than guessed. Every item also carries as_of, the time its share-structure figures were last refreshed.

Float across seven large US stocks

One batch request returns all seven. This script sorts them by float ratio and prints the short-side figures next to it:

import os

import requests

API = "https://api.tickerlayer.com"
HEADERS = {"x-api-key": os.environ["TICKERLAYER_API_KEY"]}

resp = requests.get(
    f"{API}/fundamentals/stocks",
    params={"symbols": "US:KO,US:JPM,US:DIS,US:GE,US:IBM,US:PG,US:XOM"},
    headers=HEADERS,
    timeout=15,
)
if resp.status_code == 403:
    raise SystemExit("Fundamentals is an add-on: enable it for this key first.")
resp.raise_for_status()

print(f'{"symbol":<8}{"float":>10}{"ratio":>9}{"short":>8}{"days":>6}')
for item in sorted(resp.json()["items"], key=lambda i: i.get("float_ratio", 1)):
    if "free_float" not in item:  # omitted when it cannot be reconciled
        print(f'{item["symbol"]:<8}{"n/a":>10}')
        continue
    print(
        f'{item["symbol"]:<8}'
        f'{item["free_float"] / 1e9:>9.3f}B'
        f'{item["float_ratio"]:>9.2%}'
        f'{item.get("short_float_ratio", 0):>8.2%}'
        f'{item.get("days_to_cover", 0):>6.2f}'
    )

symbol       float    ratio   short  days
US:KO       3.874B   90.03%   1.05%  2.77
US:DIS      1.724B   98.39%   1.14%  2.58
US:JPM      2.644B   99.47%   0.91%  3.88
US:GE       1.034B   99.62%   1.52%  3.97
US:IBM      0.940B   99.79%   2.39%  4.58
US:XOM      4.104B   99.80%   0.97%  2.84
US:PG       2.320B   99.84%   1.04%  2.57

Six of the seven have more than 98% of their shares in the float. Short interest is small everywhere, between 0.91% and 2.39% of the float, and would take 2.6 to 4.6 days of average volume to buy back. These are what ordinary large-cap numbers look like, which makes them a useful baseline when you meet a stock whose figures are not ordinary.

Short float and days to cover

Short interest is the number of shares sold short and not yet bought back. On its own it says little: 40 million shares short means one thing for a company with 4 billion shares and something very different for one with 40 million. Two ratios put it in context:

High readings on both ratios are what traders mean by squeeze risk: if the price rises and short sellers rush to buy back at once, normal daily volume may not absorb them. Short interest is reported periodically rather than streamed, so treat both ratios as slow-moving context rather than a live signal. Nothing here is investment advice.

Low float stocks and why they move fast

There is no official definition, but traders usually call a stock low float when fewer than about 10 to 20 million shares are free to trade. With so few shares available, one large order or a burst of attention can move the price a long way, and a single day's volume can exceed the entire float. Float turnover makes the comparison concrete: daily volume divided by free float.

That volatility shows up in the data feed as well as on the chart. Low-float stocks trip US volatility pauses far more often than large caps, and while a stock is paused no trades print; how trading halts work explains what a feed shows during one. Float also changes over time: share offerings add to it, buybacks and new lock-ups shrink it, and the end of a post-IPO lock-up can release a large block of shares at once. The daily volume used for turnover comes from the bars described in the historical stock data guide.

Get stock float data from the API

Float is company data, not price data, so it has its own endpoint: GET /fundamentals/stocks/{symbol} for one listing, ?symbols= for up to 100 at once, or ?market=US to page through a whole market with a cursor. Fundamentals is a data add-on ($39 a month on Individual, $349 on Business) covering US, German, Spanish and French listings; without it the endpoint answers 403.

{
  "symbol": "US:KO",
  "company": "The Coca-Cola Company",
  "market_cap": 377806849027,
  "shares_total": 4303000000,1
  "free_float": 3874015338,2
  "float_ratio": 0.9003,3
  "short_interest": 40584069,
  "short_float_ratio": 0.0105,
  "days_to_cover": 2.77,
  "insider_ownership": 0.099,
  "institutional_ownership": 0.6823,
  "adv_10d": 16257190,4
  "as_of": "2026-09-28T09:34:31.857Z"5
}

The market cap is a built-in check on the share count: 377,806,849,027 ÷ 4,303,000,000 = 87.80, within a cent of Friday's 87.81 close. On depositary receipts, where reported counts often describe home-market shares rather than the listing, the API can withhold free_float and serve an estimate in free_float_est instead, so check which field is present. For how listings and symbols relate across markets, see the ticker symbol explainer. To screen a whole market for low float, page through it:

def low_float(market="US", below=20_000_000):
    """Yield (symbol, free_float) for listings with a float under `below` shares."""
    params = {"market": market, "limit": 1000}
    while True:
        r = requests.get(f"{API}/fundamentals/stocks", params=params, headers=HEADERS, timeout=30)
        r.raise_for_status()
        page = r.json()
        for item in page["items"]:
            if item.get("free_float", below) < below:
                yield item["symbol"], item["free_float"]
        if not page.get("next_cursor"):
            break
        params["cursor"] = page["next_cursor"]


for symbol, shares in low_float():
    print(symbol, f"{shares:,}")

Each page of up to 1,000 listings costs one request, so a screen costs one call per thousand listings rather than one per symbol. Share counts change slowly, so running it once a day is enough. For the price side, Coca-Cola's symbol page shows its 15-minute delayed quote.