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- The Earnings Playbook: November 10-14, 2025
The Earnings Playbook: November 10-14, 2025
A probability-driven look at volatility, expectations, and opportunity during earnings season.

📊 The Weekly Earnings Season Playbook
Here’s a clear, scan-friendly earnings playbook for Nov 10-14 (ET). Use it to interpret the data, not as advice.
Schedule at a glance
Monday 11/10 - After Close: OXY, RGTI, RKLB
Tuesday 11/11 - Before Open: NBIS · After Close: OKLO
Wednesday 11/12 - After Close: CSCO
Thursday 11/13 - Before Open: DIS
Friday 11/14: None
Quick data highlights (IV / IV Rank / IV Percentile / Options Vol / Total OI)

Earnings Week of November 10-14
How to Read This Week
1) Liquidity lens (easier markets to study):
CSCO and OXY show the largest open interest (1.12M and 1.06M). Higher OI and steady volume usually mean tighter bid/ask spreads and more reliable fills, useful for practicing mechanics around earnings.
2) Volatility lens (bigger potential moves):
RGTI, RKLB, NBIS, and OKLO all print with triple-digit IV. These are good case studies for watching how implied volatility “crushes” after results and how spreads behave when stocks gap.
3) Rank vs. absolute IV (a common confusion):
CSCO: low absolute IV (33%) but high IV Rank (76.5%), IV is low in level, yet high relative to its own year.
OXY: moderate IV (35.8%) with low IV Rank (21.1%) but high Percentile (86%), shows how Rank (position between 1-yr high/low) and Percentile (distribution over the year) can tell different stories.
4) Timing effects:
After Close (Mon, Tue PM, Wed PM): price discovery often starts in the evening and continues next morning.
Before Open (Tue AM: NBIS; Thurs. AM: DIS): early prints can have wider spreads right at the bell, watch how they tighten in the first 15 to 30 minutes.
5) Study prompts for your journal:
What happened to IV (and IV Rank) from 30 minutes pre-print to the first hour after?
Did options volume concentrate in weekly expirations or spill into monthlies?
How did bid/ask width change at-the-money versus 10 to 20-delta strikes?
For pre-open names, how long did it take spreads to normalize?
Which names showed the biggest difference between expected move (from IV) and the actual gap?
Bottom line
Use CSCO and OXY to observe cleaner option markets and IV normalization. Use RGTI, RKLB, NBIS, OKLO to observe high-IV behavior (gaps, wider spreads, faster IV crush). DIS offers a classic pre-open large-cap example to watch how spreads and IV settle shortly after the bell.
Understanding the Setup
Before diving into specific trades, it’s important to understand what drives the opportunity each quarter.
Leading up to an earnings announcement, speculators and hedgers rush to buy options to position for potential surprises. This surge in demand inflates implied volatility (IV), increasing the cost of options on both sides of the market.
As sellers of options, that’s where we find our edge. We’re not trying to predict direction; we’re trying to capitalize on temporary overpricing. Once the report is released, volatility often collapses, a phenomenon known as IV crush, and that’s when time decay and probability work in our favor.
How I Approach Earnings Trades
My earnings approach is grounded in probability, structure, and risk management, not prediction.
Here’s how I typically frame each trade:
📈 Probability of success: 80% or higher
🎯 Strike placement: Outside of the expected move
🧩 Strategy choice: Short strangle (undefined risk) or iron condor (defined risk)
I prefer to stay outside the expected move because roughly 80% of stocks trade within their implied move immediately following earnings. This allows us to consistently position for high-probability outcomes while maintaining appropriate risk controls, mostly seen through proper position-size.
Final Thoughts
Earnings trades are a small but valuable part of my overall approach. They teach precision, patience, and the discipline to size positions appropriately. These are typically one-day trades, so position sizing and risk management are paramount.
For weekly updates and detailed earnings alerts check out The Implied Perspective.
Probabilities over predictions,
Andy Crowder
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