How to build a P/E ratio calculator in Google Sheets

1. Manual ways to calculate P/E ratios

Let’s start with how most people learn it: by hand. The core formula is simple:

P/E ratio = Share price ÷ Earnings per share (EPS)

Here are a few traditional methods, with clear steps:

Method 1: Plain calculator and notepad

1. Pick a stock and note its current price from any finance site.
2. Look up its EPS (usually listed on the same page as key stats).
3. Divide price by EPS on a calculator.
4. Write the result and the date in a notebook or simple text file.

Pros: Teaches intuition. Zero setup.
Cons: Painful to scale beyond a few tickers. No history, no charts.

Method 2: Manual Google Sheets table

1. Open a new sheet in Google Sheets.
2. In row 1, add headers: Ticker | Price | EPS | P/E.
3. For each stock, type price in column B and EPS in column C.
4. In D2, type =B2/C2 and drag down to compute P/E for all rows.
5. Update prices and EPS manually whenever you want fresh numbers.

Official docs on creating and editing sheets:

• https://support.google.com/docs/answer/6000292

Pros: Easy to understand; flexible formatting and charts.
Cons: You still have to fetch prices and EPS by hand.

Method 3: Copying from a web P/E calculator

1. Search for an online P/E calculator.
2. For each stock, copy in the current price and EPS.
3. Hit calculate, then copy the result into your own notes or sheet.

Pros: Fast for one-off checks.
Cons: Still manual copy/paste; hard to maintain a portfolio view.

Method 4: Basic desktop spreadsheet (Excel)

1. Mirror the Google Sheets structure in Excel.
2. Use the same Price, EPS, P/E column pattern.
3. Refresh numbers by typing in new data from finance sites.

Pros: Works offline; good if your company standardizes on Excel.
Cons: Collaboration is harder; no native web automations.

These methods are fine when you’re curious about one or two tickers. The moment you’re tracking a portfolio, a content creator index, or public comps for a fundraising deck, the friction becomes obvious.

2. No‑code automation methods

You don’t have to jump straight to full AI agents. A lot can be done with lightweight automations.

Method 5: GOOGLEFINANCE in Google Sheets

1. In column A, list your tickers (e.g., AAPL, GOOGL, MSFT).
2. In column B, fetch live prices with:
   =GOOGLEFINANCE(A2, "price")
3. In column C, fetch EPS (if available) with:
   =GOOGLEFINANCE(A2, "eps")
4. In column D, calculate:
   =IFERROR(B2/C2, "N/A")
5. Drag formulas down. Your P/E column now updates whenever Google refreshes data.

Official GOOGLEFINANCE documentation:

• https://support.google.com/docs/answer/3093281

Pros: No code, fully inside Sheets, auto‑refreshing data.
Cons: Ticker coverage and EPS fields can be patchy for some markets.

Method 6: Importing data from web tables
If a site posts updated P/E ratios in an HTML table, you can pull it directly.

1. Find the URL of a page with a table of stocks and their P/E.
2. In a cell, use:
   =IMPORTHTML("https://example.com/page", "table", 1)
   (Replace with your real URL and table index.)
3. Use formulas (e.g., INDEX, VLOOKUP) to map imported data into your own model.

Docs for IMPORTHTML and related functions:

• https://support.google.com/docs/answer/3093335
• https://support.google.com/docs/answer/3093318

Pros: Great when someone else maintains the data; you just subscribe to it.
Cons: Breaks if the site layout changes; limited control.

Method 7: Zapier/Make integrations into Sheets
Use a no‑code platform (Zapier, Make, etc.) plus an API‑friendly data provider.

1. Set up a sheet with columns: Ticker, Price, EPS, P/E, Last Updated.
2. In Zapier, create a Zap that triggers on a schedule (e.g., hourly).
3. Add an action that calls your data provider’s API to fetch price and EPS for each ticker.
4. Add a Google Sheets action to update the relevant row with fresh numbers.
5. In the sheet, keep P/E as a formula (=B2/C2) so it recalculates automatically.

Docs for Google Sheets integration:

• https://support.google.com/docs/answer/139706

Pros: Reliable scheduled updates; no manual browsing.
Cons: You must manage API keys and rate limits; setup is more involved.

3. Scaling with Simular AI agents

No‑code automations are powerful, but they assume APIs are perfect and pages never change. In reality, marketers, agencies, and founders work across messy websites, custom dashboards, and exports. That’s where a Simular AI agent becomes your digital analyst.

Simular Pro is designed to automate nearly anything a human can do on a desktop: open the browser, log in, click through dashboards, copy data, and update Google Sheets. Learn more:

• https://www.simular.ai/simular-pro
• https://www.simular.ai/about

Method 8: Agent as your P/E data collector
Imagine you maintain a Google Sheet of 40 public comps to benchmark your SaaS brand or portfolio companies.

Workflow:

1. You keep a master Google Sheet with tickers and formula columns for P/E.
2. In Simular Pro, you create an agent with instructions like:
   • Open browser and navigate to a chosen finance site.
   • For each ticker in column A of the sheet, search the symbol.
   • Read current price and EPS from the page.
   • Switch back to the sheet and paste values into columns B and C.
3. Schedule the agent to run every morning or trigger it via webhook from your pipeline.

Pros:

• Works across any site, even without an API.
• Every action is transparent, inspectable, and modifiable.
• Handles long, multi‑step workflows reliably.

Cons:

• Requires an initial “teaching” pass to show the agent what “good” looks like.

Method 9: Agent for multi‑source P/E sanity checks
Maybe your investors want conservative numbers. You can have the agent cross‑verify P/E from two different sites.

Workflow:

1. Agent opens Site A, records price and EPS for each ticker.
2. Agent then opens Site B, records the same values.
3. Agent writes both values into separate columns in Google Sheets.
4. Formulas flag any large discrepancy (e.g., >5% difference) for manual review.

Pros:

• Reduces the risk of relying on a single, possibly stale data source.
• Gives you an audit trail directly in Sheets.

Cons:

• Slightly longer run times; you trade milliseconds for robustness.

Method 10: Agent‑driven P/E alerts for your team
Take it one step further—let the agent not only update the sheet but also notify sales or leadership when valuations move.

Workflow:

1. Agent updates P/E ratios in your Google Sheet as above.
2. The sheet has conditional formatting to highlight P/E above or below certain thresholds.
3. At the end of the run, the agent:
   • Exports the sheet or a filtered view.
   • Drafts an email or Slack message summarizing key changes.
   • Sends it to your team.

Pros:

• Your team gets story‑ready numbers each morning with zero clicks.
• Perfect for agencies reporting to multiple clients on market comps.

Cons:

• You’ll want to iterate on the agent’s prompts to tune the summary you like.

A Simular AI agent essentially becomes the operations person you wish you had: patient, precise, and happy to click through 100 pages to keep your P/E ratios honest and up to date—so you can focus on narratives, pitch decks, and strategy instead of data chores.