[REPLAY] Deep Basin – Earning Alpha in Energy - [Invest Like the Best, EP.81]

Below is the analysis of the Deep Basin Capital interview chapter, based on the transcript and instructions you provided.

At a Glance

Matt Smith and Ian Singer are portfolio managers at Deep Basin Capital, a hedge fund focused on the energy sector. This episode delves into how they use a hybrid "fundamental + quantitative" process to construct a long/short portfolio in energy that is almost entirely neutral to commodity prices, interest rates, and market risk, exposing only company-specific risk. Their core thesis is that the energy sector (especially upstream exploration) features rapidly changing assets, rich data, and high complexity, which creates unique, repeatable alpha opportunities for investors who can systematically process this data, while market consensus often errs by over-extrapolating "baselines."

Topic Sections

The Energy Sector: A Complex "Playground" Built for Idiosyncratic Risk Investing

Matt Smith argues that the energy sector, particularly upstream exploration, is an ideal arena for building a portfolio with high idiosyncratic risk. The primary reason is that the sector's complexity scares away most investors, and this complexity stems precisely from the rapid changes and abundant data associated with its assets (oil wells).

• Unique Asset Characteristics: Upstream companies are essentially "depleting assets, price takers," making them "bad businesses." They cannot control product prices, their assets (wells) naturally decline, and the industry is deeply cyclical.
• Data Accessibility and Complexity: Unlike many industries, energy has an exceptionally rich and constantly updated set of underlying data (e.g., well-level production data). This data serves as the "building blocks" for company models, but "having the data itself is not the solution." The key lies in how to integrate, standardize, and transform it into low-variance forecasts of a business's future prospects.
• Constructing "Clean" Alpha: Through systematic modeling, one can precisely quantify each company's "sensitivity" to oil and gas prices (similar to how financial stocks are sensitive to interest rates). By pairing long and short positions, a portfolio can be constructed that is almost neutral to commodity prices, interest rates, and even style factors, thereby isolating pure, company-specific alpha.

The Market's Systematic Error: Over-Extrapolating the "Baseline" and Ignoring the "Second Derivative"

Ian Singer points out that a systematic error the market makes in the energy sector is a tendency to over-extrapolate a "baseline" case far into the future, while ignoring the "second derivative" of changes occurring within the asset base that will determine future cash flow changes.

• Decline Curves and Baselines: An upstream company's asset base consists of numerous constantly declining wells, making its "baseline" (the production decline rate of existing assets) critically important. The market often underestimates or misunderstands this baseline.
• The Value of the Second Derivative: When well-level data is updated, the most important insight is not the current production level, but how the productivity of wells drilled in different periods is changing. If new well costs remain constant but output declines, the company's economic returns and valuation must decrease. This "change in change" is the root of future cash flow divergence.
• Understanding via the "Factory" Lens: Matt Smith compares energy companies to "factories." Using well-level data, one can precisely understand all the details of the "factory," such as its capacity, costs, and required manpower. This "atomic-level" understanding makes it possible to build low-variance corporate models, revealing significant gaps between market pricing and objective asset value.

Value Traps and "Longevity": Why Low P/E Isn't Always a Good Investment

Matt Smith and Ian Singer jointly challenge traditional value investing notions, arguing that in the upstream energy sector, a low P/E or low EV/EBITDA multiple can be a "value trap," while high-multiple companies might be more investable. The key lies in assessing the "longevity" of a company's assets and the sustainability of its future cash flows.

• The Trap of Low Multiples: A company with a low multiple may have assets with no remaining geological potential, exhausting its inventory of high-quality drillable locations within a few years. To maintain production, it might be forced into value-destructive acquisitions. Therefore, its seemingly cheap valuation is "structural," not driven by market sentiment.
• The Opportunity in High Multiples: Conversely, a high-multiple company with a large, high-quality asset base capable of supporting years of high-return reinvestment will see its cash flow grow rapidly. This will significantly compress its forward valuation, making it cheap in the end.
• Core Metric: Longevity: Therefore, Deep Basin's investment decisions are not based on static valuation multiples but on an assessment of each company's cash flow and reinvestment capacity over the next 50 years (modeled quarterly). They look for companies where the market has mispriced the "longevity" of their assets and future growth potential.

Portfolio Construction and Leverage: Process is Paramount, Exploiting Distortions from Passive Flows

The Deep Basin team emphasizes that their portfolio construction and leverage usage strictly follow a systematic process, and they actively exploit market distortions caused by non-fundamental factors like passive fund flows.

• Portfolio Construction: The core is a "forced ranking" of each company's market price relative to its net asset value. Building on this, they not only consider the valuation gap but also place high importance on "quality" and "longevity." The ultimate goal is to build a portfolio neutral to style and commodity risks, with returns derived entirely from judgments on company-specific value.
• Leverage Usage: Leverage levels depend on two factors: 1) Breadth and conviction of investment ideas: More ideas and higher conviction allow for greater leverage; 2) Stability of the macro environment: During periods of "extreme regime uncertainty" (e.g., market turmoil in early 2019), leverage should be reduced.
• Exploiting Passive Flows: Matt Smith observes that passive fund flows (e.g., into energy ETFs) can "overwhelm most fundamental factors in the short term," creating significant pricing distortions. Deep Basin monitors these flows and trades on the resulting mispricings, for example, by shorting a company after passive flows have pushed its stock price up, waiting for disappointing earnings.

Position Moves

Ticker	Guest Stance	Key Data
EOG Resources	Bullish (as a positive example)	Can generate "tens of billions" in free cash flow at $60 oil and reinvest it for future growth.
Schlumberger	Neutral (mentioned as industry tech leader)	Described as a "technology leader," distinct from traditional "iron" service companies.
Pioneer Natural Resources	Not explicitly stated	Mentioned as a positive example of "longevity" and reinvestment capacity.
Diamondback Energy	Not explicitly stated	Same as above.
QEP Resources	Not explicitly stated	Mentioned as an example of "longevity" and reinvestment capacity.

Memorable Takeaways

1. "The energy sector is an ideal place to build a high idiosyncratic risk portfolio because its complexity scares away most people." — Matt Smith. This complexity, stemming from rapidly changing assets (wells) and rich data, creates unique alpha opportunities for investors who can systematically process it.

2. "A systematic error the market makes in energy is over-extrapolating a 'baseline' case, ignoring the 'second derivative' that determines future cash flow changes." — Ian Singer. Understanding the trend in asset productivity changes (second derivative) is more important than knowing current production levels (first derivative).

3. "In upstream energy, a low P/E can be a 'value trap,' while a high P/E company might be more investable. The key is asset 'longevity'." — Matt Smith & Ian Singer. A low-multiple company might destroy future value due to asset depletion, while a high-multiple company might become cheap due to its capacity for sustained high-return reinvestment.

4. "Modeling an upstream energy company, if you're willing to use the available data, is essentially an objective exercise." — Matt Smith. Most required information (like well-level data) is public. The key is systematically integrating it into financial models without injecting subjective guesses about commodity prices.

5. "Pricing distortions caused by passive fund flows are a more obvious source of mispricing today than we've ever seen before." — Matt Smith. Deep Basin monitors and exploits short-term price deviations caused by passive flows (e.g., from ETFs).

6. "We use an 'expectations investing' framework, reverse-engineering the market's implied assumptions (like production growth, costs, oil price) from the stock price to find large gaps between our view and market expectations." — Matt Smith. This is their core method for finding investment opportunities, derived from Michael Mauboussin's book of the same name.

7. "The core of our firm's culture is 'intellectual honesty,' meaning people aren't afraid to be wrong, and changing your mind when new information arrives doesn't bruise your ego." — Ian Singer. This culture is the foundation for the team's continuous learning and adaptation to market changes.

8. "Extreme adherence to process is the most important pillar for sustainable, repeatable investing in the energy sector." — Matt Smith. Resisting the temptation to bet on commodity prices and strictly following a systematic process is key to long-term success.