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Quarterly Earnings: Signal vs. Noise, Cost vs. Benefit

by Marc Fandetti, CFA
September 18, 2025
in Investing
Reading Time: 5 mins read
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With the White Home downplaying the worth of quarterly reporting for firms, traders face a well-known query: does the price of producing data outweigh the advantages?

Utilizing Robert Shiller’s long-run knowledge, this put up exhibits that quarterly earnings include data that’s seemingly precious to each long-term allocators and short-term merchants. Its advantages, which I don’t try to quantify, must be weighed in opposition to any financial savings from less-frequent reporting.

Quarterly vs. Semi-Annual: What’s at Stake

The White Home this week referred to as for a change from quarterly to semi-annual earnings reporting. President Donald Trump argued that such a shift would save firms time and money.

That could be true. However would traders lose precious data?

To reply this query, I exploit earnings knowledge from Robert Shiller’s on-line knowledge from January 1970 (1970:1), the yr by which the Securities and Trade Fee made quarterly earnings necessary, to 2025:6 to check relationships among the many change in three-month earnings, six-month earnings, and the pattern in earnings. I outline the pattern as a 61-month centered transferring common change in earnings. Particularly, I check whether or not figuring out three-month earnings’ modifications helps an investor higher estimate modifications within the longer-term pattern in earnings.

Chart 1 exhibits three-month earnings in inexperienced, six-month earnings in purple, and pattern earnings in blue. Sequence begin in January 2000 (2000:1), moderately than 1970:1, for ease of visualization.

Chart 1. 3-month, 6-month, and pattern earnings, 2000:1 to 2025:6.

Supply: Robert Shiller on-line knowledge, writer calculations.

In fact, three-month earnings are choppier than six-month earnings. However it’s not apparent from visible inspection that figuring out three-month earnings along with six-month earnings would assist a long-term investor predict modifications in pattern earnings. (I check this beneath and discover that they might).

It’s, nevertheless, apparent {that a} short-term investor, one maybe all for earnings modifications in intervals of lower than a yr, would profit from figuring out three-month earnings. This remark is confirmed empirically beneath.

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I begin with the long-term investor, who I assume is within the long-term pattern in earnings. A pure option to gauge the worth of getting three-month earnings along with (or as a substitute of) six-month earnings is to mannequin the change in pattern earnings as a perform of 1 or each, estimate that mannequin utilizing extraordinary least squares, and evaluate mannequin accuracy. On this put up, I exploit R-squared as my measure of match (or adjusted R-squared) — the bigger, the higher.

At any level, the investor is aware of one-half the present pattern in earnings. That’s, they know the primary 30 months’ earnings of the present 61-month window, my proxy for the pattern in earnings. They usually know both the final three months of earnings, or the final six months of earnings, or each.

To find out whether or not receiving earnings data each three months versus each six months would assist the long-term investor to higher predict the pattern, I estimated specs the place the change in 30-month-ahead pattern inflation is defined by the change in six-month earnings alone plus the prior earnings-trend change (Mannequin 1). In Mannequin 2, the pattern change is defined by the identical variables plus the three-month change in earnings. Outcomes are proven in Desk 1.

Desk 1. Regressions of pattern inflation change on 3- and 6-month earnings modifications, 1970:1 – 2025:6.

Dependent variable = Pattern inflation (30-month lead)
 Mannequin 1Mannequin 2
Six-mo. change (three-mo. lag)0.073 (0.013)0.061 (0.013)
Three-mo. change–0.124 (0.029)
Pattern change-0.223 (0.041)-0.234 (.040)
Adjusted R-squared0.0980.126
Obs547547

Supply: Robert Shiller on-line knowledge, writer calculations.

Since I’m not all for inference, I omit dialogue of estimated coefficient values, aside from to notice that they enter with the anticipated signal. However this, I embrace the prior pattern in earnings to scale back bias in my estimates and commonplace errors seem in parenthesis subsequent to every estimate.

The important thing result’s that including quarterly earnings (three-month change) improves match — the adjusted R-squared will increase from 0.098 for Mannequin 1 to 0.126 for Mannequin 2. Whereas neither match is spectacular, these outcomes counsel that quarterly earnings could assist the long-term investor predict pattern earnings. Different measures of match, specifically the Akaike and Bayesian data standards (AIC and BIC), verify that the specification which incorporates 3-month earnings is extra correct.

As for what could also be of curiosity to merchants (short-term traders), one would possibly guess that the three-month earnings change is said to the following three-month change. Quarterly earnings modifications are certainly persistent. The scatter in Chart 2 exhibits the autocorrelation of quarterly earnings, the place excessive values (earnings modifications larger than 100%) have been eliminated for simpler viewing. The estimated slope is 0.601 (se = 0.031) — the blue greatest match line is flatter than the black 45-degree diagonal line — and the R-squared is 0.361.

Chart 2. Three-month lagged earnings change vs. three-month earnings change, 1970:1 – 2025:6.

Supply: Robert Shiller on-line knowledge, writer calculations.

And on the threat of estimating the plain, the R-squared of a mannequin explaining 12-month earnings with six-month earnings (from six-months earlier than) is 0.699, whereas together with three-month earnings (from three-months earlier than) improves the match to 0.953.

Value vs. Profit

It’s practically axiomatic that, in most purposes, extra knowledge is preferable to much less. And the outcomes mentioned right here counsel that quarterly earnings include precious data for traders. However producing earnings is expensive.

As regulators take into account decreasing reporting frequency, they need to weigh not simply the financial savings but in addition the potential losses — losses to traders ensuing from much less transparency and to the economic system ensuing from impaired market effectivity.

Extra to Suppose About

Previous CFA Institute member surveys present clear help for quarterly earnings.




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Tags: benefitcostEarningsNoiseQuarterlySignal
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