Built an "Earnings Radar": One-click view of "Earnings Date + Option Pricing Volatility" for watchlist stocks | Includes half-day development process

(Background) During earnings season, two recurring questions always pop up: ① When is the earnings date? Pre-market or post-market? ② How much volatility has the options market actually priced in for this earnings report?

The information is either scattered across various sources or requires manually pulling option chains to calculate the ATM straddle to get a sense of it. So I built a small tool: Earnings Radar — input your watchlist, and it outputs an earnings calendar + implied volatility + historical actual volatility distribution.

[What It Outputs]

Next earnings: ET date, pre/post-market, expected EPS/Revenue

Implied Volatility Range = ATM Straddle of the first available expiration after earnings ÷ Current Price (e.g., NKE this time ±8.3%)

🕰 Actual volatility distribution on earnings dates over the last 8 quarters (Red bars for drops / Green bars for gains)

Interpreting Implied/Historical Ratio: Historical High Zone → Above Normal → Near Normal → Below Normal

Hidden HTML report + CSV (viewable directly in Excel)

[How It Was Built in Half a Day] The tool was developed using "AI Agent (Hermes) + Longbridge CLI", taking about half a day. Key milestones (including two real pitfalls): First, establish calibration anchors: Use NKE for validation — the tool calculated ±8.3%, matching public market data, before proceeding; Pitfall 1: The first expiration date after earnings might only have contract codes, no quotes → Added fallback logic to "automatically roll to the next available expiration date" (this saved MU); Pitfall 2: Some stocks haven't officially announced their earnings dates → Established rule to "only recognize confirmed data": If not announced, display 'No confirmed earnings within window', no guessing, no fabricating; Design trade-offs: Single file, pure standard library, zero dependencies; No account permissions needed (uses only public market data); For IV, used the latest option price rather than the mid-price — this is a classic approximation, clearly noted in the report.

[Usage (Two Steps)]

Install and log in to Longbridge CLI (open.longbridge.com)

python3 earnings_radar.py --tickers NKE,MU,STZ,CCL

(This week's scan 实录 · Data as of 9/28: CCL IV 7.3% vs historical median 4.9% (1.50x, Historical High Zone), CMG 1.44x, NKE 1.22x, MU 1.13x (Near Normal) — In the same earnings week, the market assigns completely different "temperatures" to each company.)

Open Source URL (MIT): https://github.com/flamingo1998/earnings-radar

Feel free to critique, raise Issues, or fork and modify.

@LongbridgeAI