# US Stock Filings Analysis (`fifthrow/prod-us-stock-filings-analysis-cf8f2718`) Actor

Analyze SEC filings for a ticker/period. Deliver a cited brief: filing selection, financial/operating trends, comparability, earnings quality, cash-flow bridge, financing, cost of capital, backlog, counterparties, valuation, dilution, risks, scenarios, gaps, confidence, implications, what flips it.

- **URL**: https://apify.com/fifthrow/prod-us-stock-filings-analysis-cf8f2718.md
- **Developed by:** [FifthRow](https://apify.com/fifthrow) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.50 / fifthrow app run

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

Analyze a company’s SEC filings for a specified stock ticker and timeframe, then produce a cited decision brief covering filing selection, financial and operating trends, comparability, earnings quality, cash-flow reconciliation, financing and cost of capital, backlog and counterparty quality, valuation and dilution, risks, scenarios, evidence gaps, confidence, implications, and what could change the conclusion. The analysis uses SEC filing data and qualitative source triangulation, with market-price inputs when supported.

### Runtime

This is a long-running FifthRow App. The Actor waits until the App finishes and then returns the output.
Do not treat it as a quick scrape, and keep the run timeout at least one hour.

- Typical runtime: about 19 minutes
- Flows: 1
- Agents: 1

### Summary

This analysis evaluates {STOCK\_TICKER} during {ANALYSIS\_TIMEFRAME}, focusing on comparable financial and operating trends, earnings quality, cash-flow mechanics, liquidity, financing, backlog durability, counterparty exposure, valuation, dilution, strategic developments, and material risks. It distinguishes reported facts, management expectations, calculated trends, and analyst interpretation while identifying evidence conflicts, unavailable data, and confidence limits.

Decision-makers receive a cited SEC filing brief with filing-selection rationale, a comparability and accounting-basis review, financial-trend and three-statement cash-reconciliation tables, financing and cost-of-capital analysis, backlog and contract-quality assessment, valuation and dilution analysis, ranked risks, and base, downside, and upside scenario matrices. The report highlights implications, evidence gaps, coverage limitations, and developments that could change the conclusion, supporting investment review, diligence prioritization, and resource allocation.

### Methodology

The process first resolves {STOCK\_TICKER} to the correct SEC entity and interprets {ANALYSIS\_TIMEFRAME} as the relevant date range, fiscal period, or reporting window. Available 10-K, 10-Q, 8-K, ownership, governance, and other relevant filings are inspected before selection. SEC extraction supplies filing metadata, normalized financials, XBRL facts, and filing text; qualitative retrieval supports narrative interpretation, while market-price data is used only when supported.

The review applies a strict comparability gate across reporting basis, periods, units, currency, scope, segments, and accounting classifications. It reconciles earnings and three-statement cash flows, tests capitalized-interest and depreciation mechanics, evaluates financing terms and cost of capital, and underwrites backlog, counterparties, contract protections, valuation, and dilution. Conflicting disclosures, missing inputs, and evidence quality are documented, while calculations show cited inputs and confidence is calibrated to source consistency, reconciliation, and coverage.

### Catalog

[Open in FifthRow](https://www.fifthrow.com/marketplace/apps/us-stock-filings-analysis)

### Example outputs

- [US Stock Filings Analysis](https://app.fifthrow.com/public/apps/2d056ad9-596a-47c1-9523-64a565c9b420)

### Outputs

This Actor stores a self-contained HTML report (`REPORT.html`), portable markdown (`REPORT.md`),
structured JSON (`OUTPUT`), and default-dataset rows: a run overview (duration, timestamps, full markdown)
plus one row per summary, company impact, visible answer, and Q\&A.

# Actor input Schema

## `ANALYSIS_TIMEFRAME` (type: `string`):

ANALYSIS\_TIMEFRAME Examples: 2025-01-01 to 2025-12-31; Last three months; Last six months.

## `STOCK_TICKER` (type: `string`):

STOCK\_TICKER Examples: AAPL; Microsoft; 0000320193.

## Actor input object example

```json
{
  "ANALYSIS_TIMEFRAME": "2025-01-01 to 2025-12-31",
  "STOCK_TICKER": "AAPL"
}
```

# Actor output Schema

## `OUTPUT` (type: `string`):

Complete structured JSON result stored as KVS OUTPUT.

## `markdown` (type: `string`):

Portable markdown report stored as KVS REPORT.md.

## `overview` (type: `string`):

Run overview plus summary, company impact, answers, and Q\&A as default dataset items.

## `report` (type: `string`):

Self-contained HTML report stored as KVS REPORT.html.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "ANALYSIS_TIMEFRAME": "2025-01-01 to 2025-12-31",
    "STOCK_TICKER": "AAPL"
};

// Run the Actor and wait for it to finish
const run = await client.actor("fifthrow/prod-us-stock-filings-analysis-cf8f2718").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "ANALYSIS_TIMEFRAME": "2025-01-01 to 2025-12-31",
    "STOCK_TICKER": "AAPL",
}

# Run the Actor and wait for it to finish
run = client.actor("fifthrow/prod-us-stock-filings-analysis-cf8f2718").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "ANALYSIS_TIMEFRAME": "2025-01-01 to 2025-12-31",
  "STOCK_TICKER": "AAPL"
}' |
apify call fifthrow/prod-us-stock-filings-analysis-cf8f2718 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fifthrow/prod-us-stock-filings-analysis-cf8f2718"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/RpHqivRlhFuvkSLoT/builds/ETGop6HIpSXki7R7l/openapi.json