Oil & Gas Stock Pitch: How to Research and Present It (22:10)
In this tutorial, you’ll learn how to research, structure, and present an oil & gas stock pitch.
Why is the company mis-priced? How does the market view it, and why is everyone else wrong?
Here, we cite 3 reasons:
1. The company has overstated its average EUR per well in some regions, which means its reserves may be overstated or otherwise inaccurate.
2. Cutting capital expenditures (D&C Costs) and operating expenses (LOE) over time makes less of an impact on the company’s implied value than they claim it does – being a low-cost producer is nice, but even substantial reductions over time don’t boost the value by all that much.
3. Drilling in Pennsylvania may be stopped or reduced due to the company’s JV partners, and the market hasn’t yet factored in the chances of that happening and the impact on the company’s implied value.
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A few examples of potential catalysts:
Oil & Gas-Specific: Reserve Reports / Drill Results, Well Drilling Schedules / Expanded or Reduced Drilling, Produce / No Produce Decisions, New Technology Deployment to reduce D&C Costs, Improved Well Spacing, Pipeline Developments, Hedging Contract Changes
More Generic: Geographic Expansion, Acquisitions or Divestitures, Earnings Announcements, Competitors’ Activities, Financing Activities
For UPL, we use these 3 catalysts:
1. The close of the $650 million Uinta Basin acquisition.
2. The release of new reserve reports from the company’s existing regions.
3. The possible halt to drilling in the Marcellus shale of Pennsylvania.
For each one, we show the implied per share impact on the company based on the NAV model.
We use the NAV model here, lay out our assumptions in the beginning, and then mostly focus on the OUTPUT of the model to avoid pasting in sheets and sheets of Excel.
With the NAV Model, you split the company into existing production (PDP and PDNP) and new production (PUD, PROB, and POSS), make “high-level” estimates for the existing production, and assume a decline rate over time.
For the others, assume that a certain # of new wells are drilled each year, assume that they start producing at a certain level and then decline to 0 over time, and then project the revenue, expenses, CapEx, and cash flow for each region and reserve type…
Finally, you sum up everything at the end.
The main point is to show that the assumption we’re MOST uncertain of – EUR per well – makes a huge difference on the valuation…
…While other assumptions, such as the D&C Costs and LOE per well, make a smaller difference and so it doesn’t matter much even if the company can reduce those costs.
You can “reverse” the catalysts and ask, “What happens if this catalyst does NOT happen, or what if the results are different than expected?”
Our top risk factors are:
1. The $650 million Uinta Basin acquisition fails to close.
2. Even if the acquisition does close, initial drilling reports might be positive and indicate higher-than-expected reserve levels.
3. Full drilling continues in the Marcellus shale as natural gas prices recover.
4. The company’s improved well spacing pilots prove successful, and it is able to increase its effective EUR per well.
So the first 3 are “reversals” of the catalysts, and we therefore also assess the implied per share impact from them.
The last risk factor is more of an “X Factor” type of item that might cause the company’s reserves to jump up dramatically if executed well.
Why This Recommendation Was Wrong
First off, gas prices spiked up to very high levels ($7.00 – $8.00) due to an unusually cold winter.
That killed the “Short” recommendation since all oil & gas companies become more valuable when commodity prices spike up.
Next, the company beat revenue and EPS consensus estimates twice in the past 6-7 months after this pitch; equity research analysts also upgraded their ratings on the stock.
Finally, the stock had already fallen substantially in the past 2-3 years before this… so our timing wasn’t great.
How to Avoid Disaster: We recommended setting a buy-stop order at $23.00 – $24.00 / share to limit our losses. That would have limited our losses to ~25%.