Morning Options Walkthrough: Oil Volatility & HOOD Earnings
Audio Brief
Show transcript
This episode analyzes options market strategies during high-volatility events, with a specific focus on navigating geopolitical risks in oil and decomposing earnings volatility for individual stocks like Robinhood.
There are three key takeaways for traders looking to identify pricing discrepancies in complex market environments. First, traders must contextualize volatility skew before making directional bets. Second, accurate pricing requires calculating residual volatility by isolating event risk. Finally, running sensitivity analyses on expected earnings moves can reveal tradable edges where the market may be mispricing risk.
Regarding the first takeaway, analyzing the skew is critical before trading commodities like oil. In the current market, the volatility term structure for funds like USO has inverted, where short-term implied volatility is significantly higher than long-term volatility. This signals fear of an immediate supply shock. However, the data shows that downside puts are trading at a massive discount compared to calls. This implies the market has already priced in bearish scenarios. Therefore, simply buying puts may offer a poor risk-reward ratio because the trade is already crowded and discounted.
The second concept involves properly valuing options around binary events like earnings. Traders often make the mistake of looking only at the headline implied volatility number. A more sophisticated approach is to decompose the option's price into two parts. These parts are the specific volatility of the event itself and the background volatility of the regular trading days. Because variance is additive but volatility is not, traders must square the volatility to find the variance, subtract the expected event variance, and then convert back to volatility. This process reveals the true implied volatility for the non-earnings days. If this residual volatility is lower than the stock's typical realized volatility, the options may actually be underpriced.
The final insight centers on stress-testing these calculations. By adjusting the expected earnings move percentage, traders can find the break-even point where the residual volatility aligns with normal trading behavior. For example, if the market pricing requires an unrealistically large earnings move to justify the current premium, an edge exists. Understanding the glide path of implied volatility is also essential here. As an expiration date approaches, headline volatility will naturally rise mathematically even if the dollar cost of the option decays, simply because the fixed event risk consumes a larger portion of the remaining time.
This analytical framework provides a robust method for separating specific event risk from general market noise to find true value in options pricing.
Episode Overview
- This episode demonstrates how to analyze options markets during high-volatility events, specifically focusing on geopolitical risks in Oil (USO) and upcoming earnings for Robinhood (HOOD).
- The narrative moves from identifying macro market anomalies—such as inverted term structures and extreme skew in oil—to a granular case study on decomposing earnings volatility to find "cheap" or "expensive" premiums.
- This content is highly relevant for options traders who want to learn how to mathematically separate specific event risk from general market noise to identify pricing discrepancies.
Key Concepts
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Inverted Volatility Term Structure as a Fear Gauge
- In normal markets, longer-dated options have higher implied volatility (IV). In USO (Oil), the term structure is inverted (short-term IV is higher than long-term) and heavily skewed toward calls. This indicates the market is pricing in an immediate, violent upside risk (e.g., supply shocks from Iran/Venezuela) rather than general uncertainty.
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Decomposing Event Volatility
- The price of an option expiring after an earnings event contains two distinct components: the volatility of the event itself (the "jump") and the background volatility of the regular trading days before and after the event.
- To understand if an option is truly expensive, one must isolate the earnings move. If you subtract the expected earnings variance from the total variance, what remains is the implied volatility for the non-earnings days.
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Variance is Additive, Volatility is Not
- When calculating "leftover" volatility, you cannot simply subtract percentages. You must square the volatility to get variance, subtract the event variance, and then take the square root to return to a volatility figure. This mathematical nuance is critical because small changes in the expected earnings move can drastically change the implied volatility of the remaining days.
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The "Glide Path" of Implied Volatility
- As an expiration date approaches an earnings event, the headline IV number will naturally rise, even if the price of the straddle (the dollar cost) decays slightly due to theta. This is because the fixed event risk (e.g., a 9% move) represents a larger and larger portion of the remaining time's annualized volatility.
Quotes
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At 8:12 - "Oil is like [a] really smart market and it's discounted the hell out of the puts already... that 25 delta put is a 20% discount to the at the money... it's so heavily discounted that I really don't like that trade anymore." - Explaining how to use skew data to avoid crowded trades; even if you are bearish, buying puts might be bad value because the market has already priced in the downside scenario.
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At 10:05 - "How do we compare that with like a regular volatility? Because some part of the volatility there is attributed to the fact that we're going to move a bunch on February 10th." - Identifying the core problem in options pricing: distinguishing between the premium paid for a specific binary event versus the premium paid for general time duration.
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At 15:00 - "If we take less variance for that day... instead of a 9% move, we have only an 8% move, then we have more volatility left in that straddle that needs to be divided amongst the non-earnings days." - Teaching the sensitivity of the model; if the market overestimates the earnings move, the residual days are actually priced cheaper than they appear, and vice versa.
Takeaways
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Contextualize Skew before Directional Betting
- Before buying puts or calls on commodities like Oil, check the skew (Risk Reversal). If downside puts are trading at a massive discount to calls (as seen in USO), the market has likely already priced in your bearish thesis, making it a poor risk/reward entry.
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Calculate the "Residual" Volatility
- When trading earnings, do not just look at the headline IV. Estimate the expected earnings move (e.g., the average of the last 8 quarters), subtract that specific variance from the expiration's total variance, and analyze the "residual" volatility. If the remaining volatility is significantly lower than the stock's realized volatility, the straddle might be cheap.
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Run Sensitivity Analysis on Earnings Moves
- Use a spreadsheet or calculator to test different earnings move percentages (e.g., 6% vs 9%). Determine what the "break-even" earnings move is that aligns the residual volatility with the stock's normal trading behavior. If the market requires an unrealistic earnings move to justify the current option price, you have identified a tradeable edge.
