The biggest options mistakes usually happen before the order ticket.
The cleanest way to improve trade quality is to improve chain reading. Here is the exact options chain workflow I run in Auster before I decide between a credit spread, debit spread, or no trade at all.
Start with implied volatility before you look at strikes
Open Options Chain, set your expiration window, and read volatility first.
- Compare
implied volatilityto recent realized volatility - Check whether IV is expanding or compressing across nearby expirations
- Note where the skew is steepest between calls and puts
If implied volatility is rich relative to realized, premium-selling structures usually make more sense. If implied volatility is cheap, debit structures often carry better asymmetry.
Then read liquidity: open interest and volume are your execution map
Good structure with bad liquidity is still a bad trade. In Auster I map strike liquidity before sizing.
| Signal | What it tells you | Action |
|---|---|---|
| High open interest | Strikes with active positioning and tighter execution | Prefer for primary legs |
| Healthy daily volume | Current participation, not just legacy positioning | Avoid dead strikes unless intentional |
| Thin OI and thin volume | Higher slippage and noisy marks | Reduce size or skip |
Use Greeks to define risk behavior, not to predict price
In the Greeks view, I am looking for path risk:
- Delta tells me where I am directionally exposed right now
- Gamma tells me how fast that exposure can change near key strikes
- Theta shows how much time decay helps or hurts each day
- Vega tells me whether a volatility shock can overpower my thesis
For short-dated positions, gamma usually matters more than people expect. For longer-dated positions, vega often matters more than they think.
Strike selection in practice
I use a simple strike framework in Auster:
- Base case: where I expect spot to spend most of the holding window
- Stress case: one standard move against me
- Break case: where I am wrong and must reduce risk
The trade only passes if all three cases have a clear plan before entry.
Final check: model and scenario consistency
Before execution, I validate chain logic with Auster pricing and simulation tools:
- Black Scholes for fair-value sanity
- Monte Carlo for distribution risk and tail concentration
If expected value looks fine but downside concentration is too high for position size, I do not force it. Better setup, same thesis, less regret.