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Review of Accounting Studies
Erschienen in: Review of Accounting Studies 1/2021

18.08.2020

Oil prices, earnings, and stock returns

verfasst von: Steve Crawford, Garen Markarian, Volkan Muslu, Richard Price

Erschienen in: Review of Accounting Studies | Ausgabe 1/2021

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Abstract

Research has failed to document a consistent association between oil prices and stock prices. We propose and examine whether that failure is due to the need to link oil price changes to firm-level changes in earnings and investments. We find that the impact of oil prices on a firm’s earnings and investments varies significantly by industry and by whether the firm is an oil producer or oil consumer. Nevertheless, firm fixed effects explain more than 10 times the variation between oil prices and a firm’s earnings and investments than industry and time fixed effects combined, indicating that aggregation by industry and time can mask the unique impact of oil prices on an individual firm’s earnings and investments. We also find that investors react more strongly to oil-related earnings than non-oil-related earnings, particularly for oil consumers. Investor reaction to oil-related earnings also spills over to the stock prices of industry peers. By providing a firm-level mapping of the impact of oil prices on earnings, investments, and stock prices, our paper extends studies that have examined the impact of oil prices on the aggregate economy and stock markets.
Vorheriger Artikel Analysts’ role in shaping non-GAAP reporting: evidence from a natural experiment
Nächster Artikel CDS trading and nonrelationship lending dynamics

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Fußnoten
1
See “U.S. Stocks Rise as Oil Prices Rally” (The Wall Street Journal, Sept. 28, 2016), “Stocks Pare Gains as Oil Prices Slide” (Morningstar, Jan. 3, 2017), “Stocks slide as jump in oil prices renews worries” (Fox News, March 1, 2011), and “World stocks rise, but Wall Street dips with oil ahead of jobs report” (Reuters, July 7, Reuters 2016).
 
2
Energy expenditures as a percentage of GDP in the United States have fluctuated between 6% and 14% since 1970 (https://​www.​eia.​gov/​todayinenergy/​detail.​php?​id=​36754).
 
3
The authors also find that, except for the energy and transportation industries, stock returns in all industries follow oil prices with a lag of two to five days, consistent with the underreaction to oil price news.
 
4
Firms’ hedges complicate these relations. If an individual firm hedges its oil exposure, changes in oil prices may affect the firm’s earnings differently than otherwise expected. For instance, oil and gas drillers and major fuel consumers, such as airlines, aggressively hedge their exposure to oil prices. In robustness analysis, our inferences remain unchanged when conducting analysis using the set of firms that hedge.
 
5
The WTI price is the leading oil price indicator in the United States and strongly correlates with international oil price series, such as Brent oil.
 
6
We considered including changes in oil future prices in Equation (2) and found that changes in oil future prices are highly correlated with changes in current oil prices during a quarter. (Spearman correlation coefficient is 90%.) Consequently, we do not include changes in oil future prices to avoid multicollinearity.
 
7
Yet another strand of literature predicts oil prices using various macroeconomic variables, such as past oil prices, crude oil production, and global economic activity (Kilian and Murphy 2014; Baumeister and Kilian 2016a). Even if oil prices are predictable, the accuracy of those predictions relies on the predictability of its determinants (Baumeister and Kilian 2016a, p.16). Expectations of oil prices that seem reasonable at a time may easily be rendered obsolete by unforeseen political and economic events.
 
8
If ΔOilk is replaced with daily oil price volatility during quarter k, sales, expenses, management forecasts, and investments decrease with oil price volatility. This finding, which contrasts with the reported relations, is expected given that oil price volatility should increase uncertainty and reduce economic activity and investments, in line with the literature (Bernanke 1983; Elder and Serletis 2010; Cherif and Hasanov 2013).
 
9
The median (ΔEarnings/ΔOil)t of firm-quarter observations with management forecasts is 0.11%. This median is larger than the overall sample median of −0.01% reported in Table 2, Panel A, suggesting that firms with management forecasts exhibit earnings that are more sensitive to oil prices. Yet this median is statistically lower than median (ΔMF/ΔOil)t, 0.23%, suggesting that managers overestimate the effects of oil prices.
 
10
We count the number of times the following words are mentioned in 10-K filings: oil, gas, natural gas, petroleum, and gasoline. We exclude mentions of oil preceded by the following food-based words: hydrogenated, fruit, palm, corn, fish, soybean, flax, cooking, vegetable, canola, and shortening.
 
11
We also calculated median (ΔEarnings/ΔOil)t and (ΔMF/ΔOil)t for the lowest tercile of (ΔEarnings/ΔOil)t to see whether managers are pessimistic for the firms that experience severe decreases in earnings when oil prices rise. Median (ΔMF/ΔOil)t is −0.26%, suggesting that managers indeed make lower forecasts when oil price increases severely reduce corporate earnings.
 
12
In unreported analysis, we separate firm-quarter observations based on terciles of (ΔEarnings/ΔOil)t. For firms in the lowest (highest) tercile, sales decrease (increase), expenses increase (decrease), management forecasts decrease (increase), capital expenditures increase (increase substantially), and R&D increases (stays constant). Interestingly, R&D increases the most for firms negatively affected by oil price increases.
 
13
In response to higher oil prices, R&D expenditures increase the most among firms in holding and investment industry and decrease the most among firms in utilities, eating and drinking, and finance industries. However, these firms do not have high levels of R&D expenditures (less than 0.1% of sales).
 
14
The internet appendix contains a table showing the results for all 117 SIC four-digit industries that have at least 750 observations.
 
15
The upstream sector refers to the exploration of crude oil and natural gas fields as well as drilling and operating wells that bring crude oil and raw natural gas to the surface. The downstream sector refers to the refining of petroleum crude oil and processing and purifying of raw natural gas as well as marketing and distribution of products derived from crude oil and natural gas. Sometimes, transportation, storage, and wholesale marketing of crude or refined petroleum products are distinguished from other downstream activities and called the midstream sector. We do not distinguish the midstream sector from the downstream sector.
 
16
Inferences are unchanged if we calculate CAR using the Fama-French three-factor methodology.
 
17
The remaining econometric problems of the Collins et al. model, such as errors in measuring earnings expectations or the risk profile of a firm, also exist for the firm’s oil-related and non-oil-related components of ΔEarningsk. This diminishes the severity of econometric problems in our comparisons.
 
18
Equation (7) does not include Invk, which proxies for managers’ earnings expectations in the Collins et al. model, because values are missing for a large number of observations. Sensitivity checks show that including Invk in Equation (7) reduces the sample size but does not alter inferences.
 
19
The average difference, 0.90, is statistically insignificant. However, we focus on the median to discuss the effects of oil prices on a typical firm in the sample.
 
20
In a separate set of tests, we re-estimate the above equations after inflation-adjusting all raw variables. We find similar results to those tabulated.
 
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Metadaten
Titel
Oil prices, earnings, and stock returns
verfasst von
Steve Crawford
Garen Markarian
Volkan Muslu
Richard Price
Publikationsdatum
18.08.2020
Verlag
Springer US
Erschienen in
Review of Accounting Studies / Ausgabe 1/2021
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-020-09556-7

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