Power sector players, including cooperatives, municipalities, and power generators (both renewable and fossil-fuel-based) incurred staggering financial losses. Chapter 11 filings resulting from the crises have been in the news as have attempts by the Texas legislature to address “what went wrong?”.
Was the Texas power crisis unforeseen? Was it also unforeseeable?
Opportune Risk Management Series
In the summer of 2019, we began a series explaining our views on the essential capabilities enterprises need to effectively manage commodity price risk. That initial article (CLICK HERE) was premised on the notion that energy prices have displayed persistent volatility since deregulation in the 1980s.
READ MORE: A Perfect Storm: Born Out Of Market Dynamics
Our second installment (CLICK HERE) provided an overview of those essential capabilities and discussed the importance of keeping the elements of an overall risk management environment aligned over time in reaction to changes in markets, corporate strategy, regulations, and other factors.
The Texas power crisis serves as a useful springboard for our next risk management discussion, namely the importance of building resiliency in the face of chaos.
Risk Appetite, Risk Policy & Commercial Strategies
Commodity risk management is generally a reaction—that is, an enterprise has assessed the inherent risk in its operations absent any risk management and judged such risk to be unacceptably high and then proceeds to authorize activities to mitigate its inherent risk.
The step of determining risk appetite is important and sets the stage for the concurrent development of risk policies (and limits), along with commercial strategies to manage risk. The core question in evaluating inherent risk could be stated as “what could go wrong?”.
The Texas power crises exposed weaknesses in high-level corporate strategies (witness the troubles of generating utility co-ops dependent on open market purchases from ERCOT for a significant portion of their load), as well as ordinary hedging strategies (witness the issues with wind generators with hub-based hedges and resulting losses from the inability to deliver electricity for a few days).
In the latter case, the irony is that a core risk management activity (hedging wind production) itself produced significant losses. What happens if the blades don’t turn?
Accordingly, once companies evaluate the inherent risk in their operations, and decide to manage that risk through risk management strategies, the next core question should be “what could go wrong with our strategies?”.
We recommend enterprises employ rigor and learning.
- Rigor – Implies a commitment to thinking deeply about commercial strategies and related risk management strategies. Data-driven rigor implies that enterprises will consistently test strategies using scenarios and stress testing that challenge assumptions across the widest range of risk factors possible. Price risk, basis risk, and credit risk are often the primary drivers of volatility, but the underlying range of risks that can affect outcomes is always much larger. The losses incurred in ERCOT-based wind farms revealed an underlying operational risk that companies’ risk management strategy overlooked.
- Learning – Scrutinizing expected results from actual results (back-testing) is essential for ferreting out risks that weren’t identified or were misunderstood. When helping enterprises establish risk management functions, we say that if the company hasn’t identified new risks in the past year, then something is missing. The concept of continuous learning applies strongly to commodity risk management.
On a tangible basis, a risk oversight function with a mandate to deploy scenarios, stress testing, and back-testing is essential to effective commodity risk management. Oversight, with good collaboration from commercial personnel, is a sound defense against the unknown.
The 2021 Texas power crisis is, sadly, a reminder that unforeseen risks can be devastating. One lesson should be that managing commodity risk is complex and that markets can do what they’ve not done. Companies are well served to expect volatility and, occasionally, chaos. Understanding exposures with historic data is foundational; contemplating what could go wrong is the next level.
Our next installment will specifically address valuation and the challenges and payoffs to the analysis of commodity portfolios.