Valuein

For Analysts & event-driven PMs

Pro tier

Trade the earnings surprise before consensus reprices it

Pull the newly filed quarter as standardized statements, compare it with the quarters before it, and keep a link to the filing behind every figure.

Standardized spread, ratio deltas, and a first-take read the instant a 10-Q or 8-K hits — inside the reaction window.

Jump to the code you can copy

The pain

Edge in earnings decays in minutes. By the time you've hand-spread the filing and recomputed the ratios, the surprise is already in the price. Manual workflows can't clear the reaction window.

  • “The print is out and I am still spreading the 10-Q by hand.”

    Hand-mapping line items into a model takes longer than the reaction window lasts.

  • “Was that a beat or just a different line-item name?”

    Companies rename and regroup lines; without standardized concepts you compare apples to labels.

  • “My model has last quarter's number, not what was reported.”

    Restated and as-filed values get mixed, and nobody can say which one the screen used.

The solution

  1. 1

    Pull the standardized numbers the moment it files

    get_company_fundamentals returns the income statement, balance sheet, and cash flow already mapped to 350+ canonical concepts — no XBRL wrangling, every figure traced to the accepted filing.

  2. 2

    Read the surprise, not just the print

    get_earnings_signals surfaces the TTM EPS trend and YoY revenue surprise; compare_periods deltas this quarter against last and against guidance so you see the inflection, not the absolute.

  3. 3

    Arm it for next time

    create_signal on a filing-event condition pings you (dashboard / email / webhook) the next time the name files — or fires an agent via the agent_run channel, so the first-take work starts before you've seen the signal.

Copy this

Real code and a ready prompt. Each block says what it needs before it runs.

APython SDK

No token needed: runs on the free sample

trade-the-earnings-surprise.pypython
from valuein_sdk import ValueinClient with ValueinClient() as client:  # no key: the free sample    # The latest quarters as the market knew them, one column per quarter.    fin = client.financials("AAPL", freq="Q", periods=5)    print(fin.summary())    print(fin.statement("income").head(8))     # Links to the SEC filings behind the numbers.    links = client.filing_links("AAPL", form_types=["10-Q"], limit=3)    print(links[["form_type", "filing_date", "document_url"]])

Runs on the free sample (S&P 500, recent years) with no token. Add VALUEIN_API_KEY for your plan's full range.

pip install valuein-sdk

BPrompt for Claude or ChatGPT

Works without a token on the free sample; your token unlocks your plan

prompt.txttext
AAPL just filed its 10-Q. Use get_company_fundamentals to spread it, then compare_periods against the last four quarters and get_earnings_signals for the trend. Quote every figure exactly as returned and cite its filing. Do not compute anything yourself.

Tools it uses: get_company_fundamentals, compare_periods, get_earnings_signals

CConnect your AI client

No token? Delete the headers block and it runs on the free sample

mcp configjson
{  "mcpServers": {    "valuein": {      "url": "https://mcp.valuein.biz/mcp",      "headers": {        "Authorization": "Bearer YOUR_VALUEIN_TOKEN"      }    }  }}

What you get

You act on the surprise inside the window instead of catching up to it — with numbers you can defend because each traces to the filing.

  • A quarter-over-quarter spread in the same concepts every time, so a change is a change and not a relabel.
  • A filing link beside each figure, so you can defend the number to your PM.
  • A Signal that tells you the next time the name files.

Related use cases

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Frequently asked

How fast is the data after a filing?

Pro fundamentals are released weekly (Saturday) and prices every weekday; Institutional adds intraday accepted_at timestamps and filing-event webhooks for near-real-time reaction to new filings.

Is every number traceable to the source filing?

Yes. Each fact carries its EDGAR acceptance timestamp and an identity hash; verify_fact_lineage links any value back to the exact filing it came from.

Try it on your own ticker.

The free sample needs no token and no card. One token works across your AI agent, your code and the Workspace.

Start free — no cardSee pricing