TickerRisk
Options scanner that scores every S&P 500 stock 0–100 for earnings, FDA, legal and SEC events inside your expiry window, so you don't sell a put into a hidden catalyst. Wheel and covered-call screeners included.
A startup from Lithuania.
Options scanner that scores every S&P 500 stock 0–100 for earnings, FDA, legal and SEC events inside your expiry window, so you don't sell a put into a hidden catalyst. Wheel and covered-call screeners included.
A startup from Lithuania.
This page is designed to help you find out whether TickerRisk is good and if it is the right choice for you.
TickerRisk answers one question before you sell an option: is anything scheduled to happen to this stock before my expiry?
A fat option premium is often the market pricing in a known event, like earnings, an FDA decision, a court ruling or an SEC filing. Earnings flags are common. TickerRisk combines all of these event types into one 0–100 risk score for the exact expiry window you pick, and you can filter on it.
What's included:
Ticker scan: risk score, expected move, IV and IV Rank, options chain, and a timeline of upcoming catalysts Wheel / cash-secured put scanner: finds put candidates across the S&P 500 and filters out ones with a catalyst in the window Covered call scanner: the same catalyst check for the call side, with in-the-money, at-the-money and out-of-the-money strikes S&P 500 market scanner, earnings and events calendar, risk heat map, watchlist and alerts An MCP server, so you can run scans from Claude, ChatGPT or Cursor
The risk score depends on the time window. The same stock can be LOW risk for a weekly option and HIGH risk for a monthly one, because a monthly window can include an earnings report.
You can try it with no signup for 24 hours, then get a 14-day full trial with no credit card.
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Most screeners show you the premium. TickerRisk shows you why the premium is fat. It rolls earnings, FDA decisions, clinical trials, court cases and SEC filings into one 0–100 risk score, measured over the exact window until your option expires. Legal exposure from court records is an input almost no other options tool uses. The score also changes with the time window: the same stock can be LOW risk for a weekly option and HIGH risk for a monthly one, because the monthly window includes an earnings report.
Choose it if you sell premium (cash-secured puts, the wheel, covered calls) and your main fear is getting assigned into a big gap. Tools like Barchart and Option Samurai are great for screening by yield and Greeks, and Barchart can flag earnings. TickerRisk adds the full event check on top of that: FDA, legal and SEC events as well as earnings, all combined into one score you can filter on. If you mainly want broad fundamental screening or advanced strategy modelling, those other tools go deeper. We focus on one question: is anything scheduled to hit this stock before my expiry?
Retail options traders who sell premium for income: people running the wheel, selling cash-secured puts or writing covered calls on S&P 500 stocks. They're usually self-directed, trade monthly or weekly options, and care more about avoiding one bad assignment than squeezing out the last bit of yield.
I trade options myself. I wanted one place to check whether anything was scheduled to hit a stock before my option expired: earnings, FDA decisions, court cases, SEC filings. I couldn't find a tool that combined all of that, so I built one for myself. Over time I added wheel, cash-secured put and covered-call scanners so I wouldn't need Option Samurai alongside it, and it became the only tool I used for finding trades. After a few months of using it on my own trades, I decided to make it public so other premium sellers could use it too.
Python and FastAPI on the backend, SQLite, and vanilla JavaScript on the frontend, running behind Nginx on a Linux server. Market and options data comes from yfinance and Polygon. Event data comes from SEC EDGAR, CourtListener, ClinicalTrials.gov and earnings calendars. Billing runs on Stripe. There's also an open-source MCP server in Python, so AI assistants can call the scanner.
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Check the traffic stats of TickerRisk on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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