The absolute value of the delta is also the approximate probability that the option will finish in-the-money. For example, the delta on a put with a $73 strike price (LOU4 73 P) is -0.15:  the options market is implying that on July 22, 2024, there was about a 15% chance the crude oil price would be below $73 by the expiration of the September option on August 15.

Use case: A trader believes that support from OPEC and the SPR refill in the low $70s makes it highly unlikely (<10%) that the September WTI futures contract settles below $75.  However, the $75 put reflects a 25% probability oil settles below $75. The trader considers selling the put and collecting $0.80 in premium.

As no calculations are required and option deltas are readily available, option deltas are often the quickest way to understand implied price expectations.

2. Finding the implied probability oil is within a range with an option butterfly

Options butterflies provide an alternative look at option-implied probabilities for the oil market. A butterfly is an options strategy that buys and sells puts or calls with different strike prices but the same expiration. A long butterfly involves buying a call at a lower strike, selling two calls at a higher strike and buying a fourth call at an even higher strike. In a standard butterfly, the differences between the high and low strikes and the center strike price must be equal.

Using Table 1 above, a butterfly could include buying the $79 strike call (LOU4 79C) for $1.50, selling two $80 calls (LOU4 80C) for $1.11, and buying the $81 call (LOU4 81C) for $0.82.  The cost of this butterfly is $0.10. The butterfly allows you to profit if the price of LOU4 is between $79 and $81, with a maximum payout of $1 if the price is $80, as shown in the graph below.

The approximate implied probability that oil is priced within the $79 to $81 range is the price of the butterfly divided by the payout when the September 24 WTI contract is in that range:  $0.10/$1 = 10%.

Use case: A trader notes the market has fallen close to the 200 day moving average of $79.24. The trader believes this level is unsustainable: either it will rebound back into its range or push significantly lower through this support. The trader examines the options market via Table 2 using the $78/$79/$80 call butterfly and finds it is priced at $0.15 or 15% probability. The trader feels this is too high and begins to look at buying a $78 put and an $80 call (strangle) to profit from price moves outside of this range.

The cost of an option butterfly provides the implied probability oil is near the center strike of the butterfly. The trader could compare this probability to his own view: if he believes the probability is significantly higher or lower, he may have identified a trading opportunity.

3. Estimating an expected distribution of oil prices with a series of butterflies

While the price of a single butterfly shows the probability that oil is within a narrow band, a series of overlapping butterflies can provide a more complete distribution of probabilities for the oil price.

We can calculate a series of butterflies across the set of strike prices. Starting on the low side, we calculate the price of the $65/$66/$67 and calculate each subsequent butterfly until we reach the $94/$95/$96. The resulting chart shows the probability for each oil price outcome, also referred to as the probability density function (PDF).¹ In this case, the implied distribution of outcome is fairly normal, with just a slightly higher concentration of probability to the upside.

Use case: A proprietary trading model forecasts an expected price of $85 per barrel for WTI over the next week, with greater than 10% probability it exceeds $92. The trader notes that this is materially more bullish than the options distribution and considers buying call spreads and WTI Crude Oil futures.

Examining the implied distribution from a series of butterflies can be particularly useful when trying to understand or evaluate market expectations around specific events, such as an OPEC meeting or when geopolitical events are driving uncertainty.

4. Comparing expectations for an event with Weekly WTI options 

Crude Oil options that expire on different days of the week are actively traded on CME Group.  The prices and deltas for Weekly options are available similarly to the monthly options on CME Direct, or on common third-party vendors like Bloomberg.  By looking at the price probability distribution for options expiring before an event compared to those expiring after an event, a trader can determine the market expectation for a price move from the event.

CME Group’s OPEC Watch Tool uses this methodology to assess the market expectation for OPEC outcomes ahead of their regular meeting. By comparing the values of the closest Weekly Crude Oil option contract with the values of the next monthly contract, the tool calculates the probability that the options market expects for a large up or down move following the meeting. Going into the June 2, 2024 OPEC meeting, the market was not pricing a significant move in price, with approximately 80% probability of “no change” to their policy. Historical analysis of the OPEC Watch Tool and the Oil market shows that the options market usually correctly predicts OPEC activity, but that oil price does not necessarily respond accordingly.  

Use case: A trader believes OPEC is likely to announce additional cuts at the upcoming meeting. He checks the OPEC Watch Tool, and notes that the options market does not agree with him, showing a 20% likelihood of more cuts. He considers buying a call on the Monday WTI Weekly option expiring after the meeting or taking an outright long position in WTI futures.

The addition of WTI Weekly options expiring each day of the trading week allow for greater depth of analysis around specific events and expressing expectations for crude oil over a wide range of time frames.

Options pricing is an essential tool for understanding the oil market and assessing the distribution of outcomes for trades. The CME Direct platform offers access to extensive options analytics and pricing, adding transparency and accessibility to options markets to help all types of oil traders turn ideas into action.  

¹ The probability density function constructed via the series of butterflies can be compared to an approximate cumulative distribution function that can be constructed from the series of deltas on puts or calls as shown in part 1.