I run most of my analysis in spreadsheets. Old habit from the desk. When I started trading Kalshi markets seriously, copying and pasting prices into Excel felt absurd. So I built a pipeline to pull live quotes directly into my sheets. It took some trial and error, but the setup is straightforward once you understand the moving parts.
Primary sources I checked: Kalshi API Documentation for endpoint specifications and authentication requirements, and CFTC press release confirming Kalshi's status as a designated contract market.
Prediction markets move differently than equity futures. There's no continuous liquidity pool, and spreads can widen without warning. Having live (or near-live) quotes in a spreadsheet lets you:
I'm not promising this gives you an edge. Most of the time, I'm just watching. But watching efficiently beats watching sloppily.
Before you connect anything, you need to know what the API actually provides. Kalshi splits its endpoints between live market data and historical data. For spreadsheet use, you'll mostly care about the live orderbook and market endpoints.
Key points from the current docs:
Do not invent endpoint paths based on old tutorials you find online. Some readme.io URLs from 2022 are dead. Go to docs.kalshi.com and verify the current structure before you write any code.
Google Sheets is easier for most people because Apps Script handles HTTP requests natively. Here's the general process:
Log into Kalshi, go to account settings, and create an API key. Store the key ID and secret somewhere secure. You'll need both for authentication.
Open your Google Sheet, click Extensions, then Apps Script. You'll write a function that:
A minimal example fetches the market summary for a single contract and extracts the yes_bid and yes_ask fields. I won't paste full code here because the authentication flow changes occasionally. Check the current docs for the exact header format.
Google Sheets doesn't auto-refresh custom functions like it does with GOOGLEFINANCE. You can set a time-driven trigger in Apps Script to run every minute or every five minutes. Be careful with rate limits. Pulling 50 markets every 60 seconds will burn through your allowance fast.
Excel is trickier because it doesn't have a native scripting layer for REST APIs. Your options:
Power Query can pull JSON from web sources, but it doesn't handle bearer token authentication gracefully. You'd need to write an M query that manually constructs the authorization header. It works, but it's brittle. Every time the auth flow changes, you fix it manually.
This is what I actually use. A Python script runs in the background, calls the Kalshi API, and writes the results to an Excel file or a local CSV that Excel reads. xlwings lets you push data into open workbooks in real time. It's more setup, but it's also more flexible.
You can write VBA that uses the WinHTTP library to make REST calls. I've seen people do this. I don't recommend it unless you already know VBA well. Debugging HTTP errors in the VBA editor is painful.
A few things I learned the hard way:
If you run into issues or want to compare notes with other traders, I post occasional updates in the Telegram channel I run. No promises I'll debug your code, but sometimes someone else already hit the same wall.
Once you have live quotes in a spreadsheet, the obvious next step is building alerts or simple models. Some things that work for me:
None of this is magic. It's just organization. But organization matters when you're watching 20 markets and need to act fast on one of them.
Kalshi provides API access to account holders, and as of this writing there's no separate fee for API use beyond standard trading fees. You need a verified Kalshi account to generate API keys. Rate limits apply, and exceeding them temporarily blocks requests. Check the current terms at docs.kalshi.com since policies can change.
The exact rate limits are documented in the Kalshi API docs and can change. In practice, refreshing every one to five minutes for a handful of markets usually stays within bounds. If you're polling dozens of markets every 30 seconds, expect throttling. Build in error handling so a 429 response doesn't crash your sheet.
Kalshi separates live market data from historical data endpoints. Historical tick data may require different access or permissions. The current orderbook endpoints give you real-time snapshots, not historical archives. Check docs.kalshi.com for the latest on historical data availability and any associated requirements.
When a market settles, the ticker stops returning live quotes. Your API call will likely return an error or a settled status. Build your spreadsheet to handle this gracefully. Either check the market status field before displaying prices, or use error handling to show "Settled" instead of crashing the formula.
Not financial advice. I trade my own money and you can lose yours. Do your own research.