Can Electricity Use Predict Industrial Stock Returns?

A factory’s electricity bill can tell two very different stories. It may be rising because machines are producing more goods, or because the same production now costs more. For investors, confusing those explanations can mean mistaking growth for pressure on profits.

A new study by Anna Pirogova, accepted for publication in the International Review of Economics and Finance, investigates whether separating these forces reveals information about future industrial stock returns.¹ Its findings suggest that electricity data can be useful, but that usefulness changes across countries, sectors, and periods of market stress.

The broader opportunity extends beyond forecasting share prices. As manufacturers install connected meters and digital monitoring systems, electricity becomes a measurable record of operations. Understanding that record could help investors ask better questions about productivity, expansion, and resilience.

How Electricity Data Reveals Industrial Activity

Electricity is both a production input and a financial expense. Motors, furnaces, pumps, and processing equipment consume power to turn materials into saleable products. However, rising consumption does not automatically mean rising profitability, just as falling consumption does not automatically mean a struggling business.

Consider a hypothetical manufacturer that produces 10% more goods while using 5% more electricity. Its total demand rises, but electricity use per unit falls. Another manufacturer might cut power consumption by closing a production line. Their business implications differ substantially.

Pirogova constructs two signals. One captures changes in industrial electricity consumption after removing its statistical relationship with relevant energy prices. The other captures efficiency changes beyond those associated with those prices. These adjustments aim to distinguish operational developments from responses to energy-market conditions.

The framework also treats production as generating both useful output and emissions. Carbon allowances therefore enter the analysis alongside forward electricity prices. A factory can improve its operations while still facing rising costs from the wider energy and carbon markets.

What The Italy And Sweden Study Found

The research compares industrial electricity and equity-return data in Italy and Sweden. It examines different forecasting lags and applies statistical safeguards, including adjustments for testing multiple relationships. A complementary analysis covers 144 Italian foundries.

The strongest result appears in Italy’s Construction & Materials sector. The adjusted electricity-consumption signal positively predicts returns at the annual horizon and remains significant after correction for multiple testing. Italy’s Basic Resources result is weaker, while the pooled foundational-sector analysis also identifies a positive relationship.

Sweden provides an important counterweight. Annual operational consumption and efficiency signals are largely insignificant in sector and pooled models. Carbon costs weigh on Chemicals returns, while forward electricity prices matter in some pooled specifications.

The foundry analysis further limits any simple interpretation. Consumption effects are positive but statistically imprecise for real returns, then become significantly negative in excess-return models using a different lag. These comparisons show how financial adjustments and model choices affect the findings.

These are conditional forecasting relationships, not evidence that increasing electricity use causes share prices to rise. The paper leaves portfolio construction and the economic value of trading on these signals for future research.

Why Energy Efficiency Does Not Guarantee Higher Returns

One potentially confusing finding is the negative coefficient on physical efficiency in some Italian pooled specifications. It should not become a headline claiming that efficiency damages businesses.

An operating improvement and a stock-market return answer different questions. Efficiency can reduce costs, but investors may already have priced that improvement into the shares. Subsequent returns also depend on the purchase price, financing conditions, demand, and the risks investors require compensation to bear.

Meanwhile, efficiency indicators differ. Electricity per tonne of output measures something different from energy relative to value added or emissions. Selling prices and product mix can affect financial measures without equivalent changes in machinery performance.

The International Energy Agency’s Energy Efficiency 2025 analysis places efficiency within a wider discussion of competitiveness, affordability, and energy security. Operational savings can matter commercially even when they do not produce a consistent stock-return signal.

Electrification Makes Power Data Harder To Interpret

Technological change adds another complication. A manufacturer replacing a gas-fired process with electric equipment may increase electricity consumption while reducing fossil-fuel use. Looking only at its power meter could obscure the improvement.

The IEA’s Electricity 2026 outlook describes growing demand supported by industrial electrification, transportation, buildings, and data centres. As those changes progress, historical relationships between electricity use and production may evolve.

A new electric furnace, an additional production shift, and an inefficient compressor can all raise demand. Their implications for earnings are different. Useful disclosures would connect consumption to output, equipment changes, and the prices companies actually pay.

• Compare electricity consumption with production volumes and product mix.
• Check whether electrification explains changes in demand.
• Examine power contracts, hedging, and carbon-cost exposure.
• Assess whether efficiency savings exceed implementation costs.

Long-term power contracts add another layer. Two otherwise similar factories may experience the same wholesale-price shock differently because one has secured its supply costs. The study identifies more granular information on hedging and power-purchase agreements as an important direction for further research.

Digital Monitoring Connects Energy Use To Productivity

Industrial technology offers a practical extension of the research. A monthly sector total provides a broad signal. Machine-level monitoring can help explain the causes behind it.

Connected meters can reveal whether demand rises during productive work or persists when equipment should be idle. Combined with output and maintenance records, that information can support investigations into wasted energy, equipment deterioration, and production bottlenecks.

The emerging meta-factory approach to industrial AI connects sensors, digital models, and operational systems. Energy information becomes more valuable when interpreted alongside those other records, although collecting more data does not automatically improve decisions.

There is also a physical side to efficiency. Recent coverage of better power conversion chips illustrates how equipment design can address energy losses. Monitoring identifies problems; effective hardware and process changes determine whether insights translate into savings.

Eaton Offers Exposure To Intelligent Power Management

For investors interested in the technologies behind this transition, Eaton provides a relevant company to examine. Its power management business connects the physical infrastructure of electrification with tools for understanding and managing electrical systems.

Eaton’s Brightlayer electrical power monitoring software provides real-time and historical visibility into electrical and environmental systems, including industrial sites. The company also describes monitoring capabilities for water, air, gas, electricity, and steam, helping operators identify consumption patterns and plan reductions.

This connects directly to the article’s central idea: better measurement can make energy management more informed. Eaton represents exposure to infrastructure and software enabling that process, rather than a direct investment in the study’s forecasting model.

The investment case still requires scrutiny of valuation, competitive positioning, margins, and customer spending. Electrification can expand demand for power management products, but industrial investment remains cyclical. The paper neither evaluates Eaton’s shares nor establishes that its products create excess investment returns.

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Reading Factory Power Use As An Investment Signal

The study’s most useful contribution is a framework for asking what electricity consumption represents. In certain Italian industries, adjusted consumption contains information about later returns. Sweden and the foundry analysis show why that finding cannot be applied universally.

The larger opportunity is to connect physical operations with financial analysis. As electrification and monitoring improve visibility, investors can assess whether companies are producing more, using resources better, or simply paying more for the same activity. Electricity data becomes useful when those explanations are distinguished and tested against the rest of the business.

References:

¹ Pirogova, A. (2026). Watts to wealth: Electricity, efficiency, and industrial asset pricing. International Review of Economics and Finance. Advance online publication. https://doi.org/10.1016/j.iref.2026.105924