Practical Option Valuation with Negative Underlying Prices

Industry Mentor: Scott Dalton, Director of Risk Management, Ovintiv

In March 2020, the prompt month WTI futures contract settled below zero for the first time in the contract’s history. Many market participants apply the Black 76 model model or some variation when calculating the value of the options on this futures contract as a relatively straightforward, parametric valuation method. This calculation model is hard wired into many Commodity Trading and Risk Management Systems. Traders and risk managers rely on its straightforward and reproducible output.

However, Black 76 requires positive underlying market prices. The negative prompt month settlement price caused considerable consternation among energy traders and risk managers.

More generally, OTC options are also available on basis or differential prices. These transactions are options on the difference between two published indexes such as NYMEX Henry Hub and AECO (for natural gas) or Cushing WTI and Houston (for crude oil). As such, these instruments frequently have negative underlying market prices.

While commodity producers, processors, transporters and consumers frequently use derivatives to hedge their underlying physical exposures, many of these organizations do not maintain significant quantitative expertise in-house. Being able to perform this type of analysis and then explain the approach and results to non-quant specialists is a useful and valuable skillset.

The task

• Review available alternatives to Black 76 for valuing commodity-based European options.

• Identify alternatives that can accept negative underlying pricing (Bachelier is one example).

• Assess the suitability of alternatives in terms of:

  • Ease of use

  • Validity of assumptions

  • Reasonableness of results

  • Proximity of results to Black 76 when underlying market prices are positive

• Identify recommended alternative(s)

Student background

People interested in applied quantitative finance, commodity trading and marketing, and bridging the gap between quantitative experts and non-experts.

A sample market data set will be available that includes historical forward market prices, implied volatilities or option premiums, risk free interest rates