Step 1
Run the 10-minute triage (before touching the order button)
Write a one-line answer for each: (a) What was the *expectation* going into earnings? (b) What changed in fundamentals vs guidance vs narrative? (c) W...
Keyword: panic selling after earnings
Use Case: Stop Panic Selling After Earnings Volatility
A decision playbook for earnings-day volatility: separate thesis breaks from noise, reduce risk by rules, and avoid emotional exits.
Earnings-day moves often feel like “new truth”, but price is a mix of information, positioning, and expectations reset. This page helps you decide what to do *without* improvising: first test whether the thesis actually broke, then apply a staged risk protocol (size caps, time delay, evidence checklist), and only then decide to hold, trim, or exit. The goal is not to predict the next candle—it is to protect decision quality under volatility and keep your process consistent across quarters.
30-second action
Turn this page into one decision step
Pick the smallest next action now: test your bias pattern, run a scenario, or copy a prompt before making a portfolio move.
Quick Take
- Run the 10-minute triage (before touching the order button)
- Thesis-break test: what must stay true?
- Apply the “position-size boundary” rule
Visual Playbook
Step 2
Thesis-break test: what must stay true?
List 2–4 thesis invariants (unit economics, moat signal, balance-sheet safety, reinvestment runway). Then ask: did earnings *falsify* any invariant, o...
Step 3
Apply the “position-size boundary” rule
Volatility becomes dangerous when a single position is too large to think clearly. Before deciding “buy vs sell”, check size: if the position breaches...
Use-Case Playbook
1) Run the 10-minute triage (before touching the order button)
Write a one-line answer for each: (a) What was the *expectation* going into earnings? (b) What changed in fundamentals vs guidance vs narrative? (c) What is the single biggest new risk item? If you cannot state these plainly, you are reacting to emotion and volatility, not evidence.
2) Thesis-break test: what must stay true?
List 2–4 thesis invariants (unit economics, moat signal, balance-sheet safety, reinvestment runway). Then ask: did earnings *falsify* any invariant, or did it only change near-term optics? If an invariant broke, you plan a risk reduction. If not, you treat the move as a stress test of your holding rules.
3) Apply the “position-size boundary” rule
Volatility becomes dangerous when a single position is too large to think clearly. Before deciding “buy vs sell”, check size: if the position breaches your maximum weight or drawdown risk budget, trim mechanically to get back inside policy. This is risk control, not a forecast.
4) Choose one of three actions (hold, trim, exit) with a pre-committed trigger
Hold if: invariants intact and you can write one next-review date. Trim if: invariants intact but risk rose (uncertainty, leverage, dilution, guidance quality) and size is uncomfortable. Exit if: an invariant is falsified or the business model assumptions changed materially. Avoid adding on day one unless you have a written plan *before* the event.
5) Post-earnings debrief (so next quarter is easier)
Record the earnings takeaway in your journal: what surprised you, what you would watch next, and what would change your mind. If you changed the position, document the rule you followed. The goal is to convert one volatile event into a reusable decision protocol.
Template Snapshot
Decision fields to lock before execution
- Thesis in one sentence
- Invalidation trigger and evidence threshold
- Risk budget and position-size boundary
- Review date and expected catalyst window
Action Checklist (Shareable)
- Write your decision objective in one sentence before reading price action.
- Run at least one relevant case in KeepRule Scenarios (/scenarios).
- Tie the action to one principle and one invalidation trigger (/prompts).
- Set position size from downside tolerance first, then expected upside.
- Schedule a 7-day post-mortem using the same checklist before any new change.
Share Kit
Why KeepRule
- Structured decision system across Scenarios, Principles, Masters, and Prompts.
- Built for repeatable execution, not one-off opinions.
- Designed for long-term investors who want fewer emotional mistakes.
Recommended KeepRule Paths
FAQ
Should I always wait 24 hours after earnings?
A waiting rule usually improves clarity because it reduces adrenaline-driven decisions and lets the market digest. The exception is when your policy says you must act immediately (for example, leverage risk, accounting integrity issues, or a thesis invariant being clearly falsified).
What data matters most post-earnings?
Focus on what changes the long-term distribution: guidance quality and repeatability, unit economics trend, pricing vs volume, margin durability, and balance-sheet risk. A single quarter miss matters less than a structural change in demand or profitability.
What counts as “thesis-breaking” evidence?
Thesis-breaking evidence is something that invalidates your core assumptions: the product loses pricing power, the moat signal erodes, leverage becomes unsafe, dilution becomes likely, or management behavior changes the capital-allocation story. If you cannot name the broken assumption, you do not have a thesis-break—you have volatility.
How do I avoid revenge trades after a gap down?
Use a hard delay plus a checklist gate. For example: no new trade for X hours, then you must complete (a) triage summary, (b) thesis-break test, (c) size-boundary check. If you cannot complete the writing, you cannot trade.
Is it better to use a stop-loss around earnings?
Only if it is a pre-committed rule that matches your strategy. Stops can prevent catastrophic losses, but they can also force exits during gap moves and high-volatility noise. Many long-horizon investors prefer thesis-based exits plus strict sizing so they can hold through volatility without breaking rules.
Install an earnings-day decision protocol
Before your next result season, define one hold rule, one reduce rule, and one add rule tied to evidence.