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Investors often use quarterly earnings results to decide whether to buy or sell individual stocks; however, investors who focus on past results will likely miss out on the blow-out positive quarters when looking at upstream energy producers.

Here’s what to look for instead, and what to look for…

Upstream energy companies are oil and gas producers. These companies drill wells to generate revenue from selling the oil and natural gas they produce. The variable nature of energy prices means that profits will swing up and down with changes in energy commodity prices.

The cost of producing a barrel of oil remains relatively steady. And natural gas, often an associated byproduct, provides extra revenue with little additional expense. The chart below shows the price of oil for the last year, which steadily declined from a year ago until the start of the 2023 third quarter. As a result, quarterly earnings in the upstream sector have also dropped.

Note that it was right at the end of the second quarter that oil bottomed in the $60s; it has since climbed into the low $80s. Upstream producers have been taking drill rigs out of service, leading to lowered production and likely continuing the price appreciation.

When the upstream energy companies report their third quarter in late October, I expect most will post positive earnings surprises. Several companies in this group pay variable dividends, and the higher profits will result in significant dividend boosts compared to the second quarter payouts.

Here is a list of the major U.S.-based upstream producers, market caps, second-quarter production levels, and dividend policies:

EOG Resources, Inc. (EOG) has a market cap of $76 billion. Second-quarter production came in at 970,000 barrels of oil equivalent per day. EOG pays a stable dividend, which increases annually.

Occidental Petroleum Corporation (OXY) has a market cap of $56 billion. Second-quarter production was 1.22 million BOE/D. OXY pays a stable dividend with a low current yield, which grows by more than 30% per year.

Pioneer Natural Resources Company (PXD) has a $55 billion market cap. Second-quarter production of 711,000 BOE/D. PXD pays a variable dividend.

Devon Energy Corporation (DVN) has a $32 billion market cap. For the second quarter, Devon produced 662,000 BOE/D. DVN pays a variable dividend.

Diamondback Energy, Inc. (FANG) has a $32 billion market cap. In the second quarter, FANG produced 450,000 BOE/D. The company pays a growing regular dividend and occasional supplemental dividends.

Marathon Oil Corporation (MRO) has a $16 billion market cap. For the second quarter, MRO produces 399,000 BOE/D. Marathon Oil pays a stable dividend, which has doubled over the last two years.

APA Corporation (APA) has a market cap of 13.5 billion. For the second quarter, the company produced 325,000 BOE/D. APA slashed its dividend during the pandemic, but is now up to the pre-pandemic level.

In the current energy environment, these companies are committed to growing production using free cash flow, not debt. They are also committed to returning capital to shareholders through cash dividends and share buybacks.

It’s a good time to invest in these upstream energy stocks. It will be too late when they report third-quarter earnings.
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When a technology is billed as something that will transform the entire global economy, the primary impulse of investors is often fear—specifically, fear of missing out (FOMO). And that’s exactly what we’ve seen so far in 2023, with regard to artificial intelligence (AI).

However, for investors, the most obvious play to profit from generative AI is already a very crowded trade. One of the best-known investing adages is to “invest in shovel-makers when there’s a gold rush,” and that’s just what investors have done so far in 2023.

Shares in Nvidia (NVDA), which makes the graphics processing units (GPUs) facilitating generative AI, have already more than tripled in value this year.

So if not Nvidia, or Microsoft (MSFT)—which has invested $13 billion into ChatGPT creator Open AI—then what? Microsoft stock is up over a third year-to-date.

There is no doubt that, when it comes to AI, the genie is out of the bottle. Artificial intelligence is a technological opportunity, as well as a risk for a wide range of industries, just as the internet was in the mid-1990s.

That brings us to the question for investors: should we just forget about the gold rush and shovel analogy? After all, companies are adopting AI at higher rates than they had in the past, with 50% of companies reporting using AI for at least one application in 2022 compared to just 20% in 2017, according to a report put together by Mastercard (MA).

The best investments may well be those companies that are well placed to actually utilize AI in their businesses—especially if they don’t have same lofty valuation as Nvidia does. Let’s look at one example…

AI Will Pay Its Way in Payments

We now have growing expectations of “soft landings” for major economies like the U.S., as well as markets pricing in the end of interest rate hiking cycles. This is ideal both for the valuations and earnings outlooks of companies for companies in growth businesses, such as payments.

Visa (V) shares have now recovered all the ground lost since the middle of 2021, and Mastercard has recently seen its share price at all-time record highs. These companies will benefit greatly from the use of AI. The opportunities in AI for payment businesses center around more robust fraud detection, personalized user experiences, and automated customer support.

Of these opportunities to improve their business, using AI in detecting fraud is the most important. Already, Mastercard estimates it has thwarted $35 billion worth of fraud in the last three years, primarily by utilizing AI technologies to spot authorized push payment (APP) scams. This is where criminals focus on conning consumers into sending them money by posing as legitimate entities. And the AI is getting more sophisticated, which is necessary to keep up with the criminals.

Given the vast quantities of data Visa and Mastercard have, there ought to be lots of opportunities to apply AI learning, with which they can drive user engagement.

Let’s look more specifically at what Mastercard is doing with AI.

Mastercard and AI

For one great example of what Mastercard is doing, we look across the pond to the U.K. and nine major British banks.

The payments giant has launched its Consumer Fraud Risk technology in the U.K., using large-scale payments data to help identify scams before funds leave a victim’s account. The project is happening at a time when players on both sides of the law are using AI.

The tool builds on insights from Mastercard’s work with U.K. banks to follow the flow of money mule accounts over the last few years. Overlaying this information with specific analysis factors—such as account names, payment values, payer and payee history, and the payee’s links to accounts associated with scams—helps provides banks with the intelligence necessary to intervene in real time and stop a payment before funds are lost.

Mastercard says that the system could have a significant impact on the aforementioned APP fraud, which has been rapidly rising in recent years and now accounts for 40% of U.K. bank fraud losses. The company estimates such fraud could cost $4.6 billion in just the U.S. and U.K. by 2026.

Mastercard decided to roll out Consumer Fraud Risk in the U.K. first because it has a lot of experience of tracing and stopping financial crime across the country’s real-time banking system and has helped to coordinate banks into sharing their fraud data. It is now assessing the next most appropriate markets to adopt the technology. So, there is a lot more to come on this front, with the U.S. being the biggest market.

With Mastercard being a leader in using AI in its industry, the company is one of the most prominent, but undiscovered, beneficiaries of AI.

The stock is still trading near its all-time high—up 15% year-to-date—and is a buy on any weakness, at around $400 a share.
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