Comps for Cyclical Stocks

The steel industry trades at an EV/EBITDA multiple of 5x in a down cycle and 12x in an up cycle. The same company, generating similar returns, commands a 7x multiple swing depending on where we are in the economic cycle. For the analyst valuing a cyclical business using comparables, this volatility is the central challenge: which year's earnings do I use? Do I apply the current multiple or a normalized multiple? Is the company undervalued, or is the market correctly pricing in a cycle downturn?

Cyclical stocks—those whose earnings rise and fall with the economy (materials, energy, industrials, financials during credit cycles)—require a different approach to relative valuation than stable, non-cyclical companies. Using peak-year earnings in a valuation multiple creates the illusion of cheapness in a down cycle; using trough earnings overstates value in an upturn. The solution is to normalize earnings around a midpoint in the cycle, then compare to peers using the same normalization.

Quick definition: For cyclical stocks, a normalized or cycle-adjusted earnings metric is the average or midpoint earnings level expected over a full business cycle (typically 5–10 years), used in place of the current year's reported or forward earnings to derive valuation multiples that are comparable across cycle phases.

Key Takeaways

• Cyclical companies are most dangerous to value at peaks and troughs; at peaks, multiples are lowest and confidence is highest; at troughs, multiples are highest but fundamental value is uncertain.
• Normalized EBITDA multiples are more useful than EV/Earnings for cyclical stocks because they are less affected by interest, taxes, and one-time charges.
• The cycle midpoint (average earnings over a 5–10 year period) is a defensible normalization approach, though it can be misleading if the industry structure has changed.
• A cyclical company's value should reflect not just where we are in the cycle today, but where we are likely to be over the holding period.
• Comps for cyclical stocks should be screened by cycle phase: compare a company in a down cycle to peers also in a down cycle, not to the same peers in an up cycle.

Why Cyclical Stocks Break Normal Valuation Rules

Valuation multiples and underlying fundamentals move in opposite directions in cyclical industries:

In an up cycle:

• Earnings rise quickly (operating leverage kicks in)
• Confidence is high, sentiment is positive
• Multiples expand (P/E ratios rise)
• Stock prices typically outpace earnings growth
• Valuations appear cheap based on forward multiples (but are actually expensive on a normalized basis)

In a down cycle:

• Earnings fall sharply (fixed costs do not decrease proportionally)
• Confidence is low, sentiment is negative
• Multiples contract (P/E ratios fall)
• Stock prices underperform earnings declines
• Valuations appear expensive based on current multiples (but are actually cheap on a normalized basis)

The danger: an analyst using a standard relative-valuation approach (current year's forward earnings divided into the stock price) will conclude a cyclical stock is cheap when it is actually expensive (peak cycle), and expensive when it is actually cheap (trough cycle).

Example: Steel company valuation

• Steel company at peak cycle: $3B market cap, $300M net income (peak), trading at 10x P/E. Multiples look reasonable.

  • But normalized earnings (5-year average) are $150M, implying a true P/E of 20x. The stock is expensive.

• Same steel company at cycle trough: $3B market cap, $50M net income (trough), trading at 60x P/E. Stock appears expensive.

  • But normalized earnings are $150M, implying a true P/E of 20x. The stock is actually reasonably valued or cheap.

Identifying and Characterizing Cyclicality

Before you normalize earnings, you need to confirm the business is truly cyclical.

Characteristics of cyclical businesses:

• Revenue and earnings fluctuate with GDP growth, credit cycles, or commodity prices
• Operating leverage is high (fixed costs do not scale with volume)
• Asset intensity is high (capital-light businesses can adjust more flexibly)
• Customer demand is discretionary or delayed (not essential)

Industries with high cyclicality: Steel, mining, oil and gas, chemicals, automotive, construction materials, commercial real estate, banking (credit cycles), semiconductors, airlines.

Industries with lower cyclicality: Consumer staples, utilities, healthcare, insurance (underwriting cycles are real but muted), railroads, telecommunications.

To quantify cyclicality, calculate the coefficient of variation (COV) of earnings over a 10-year period:

COV = Standard Deviation of Earnings / Average Earnings

A COV above 0.3 suggests high cyclicality; 0.1–0.3 is moderate; below 0.1 is low (non-cyclical).

Normalizing Cyclical Earnings: Approaches

Approach 1: Simple average or median.

Calculate the average (or median) net income (or EBITDA) over the past 5–10 years. Use that as the normalized earnings.

Pros: Simple, transparent, historically grounded.

Cons: Assumes the past cycle is representative of the future (dangerous if industry structure has changed). Also weights all years equally, which may not reflect expectations for the upcoming cycle.

Worked example: XYZ Steelmaker

Earnings over 10 years:

Year	Net Income ($M)
2015	$50
2016	$30
2017	$120
2018	$200
2019	$90
2020	$10 (COVID)
2021	$250
2022	$350 (peak cycle)
2023	$180
2024	$60

Simple average: $133M Median: $105M

Either could be used as normalized earnings. The median is lower and excludes 2020 (COVID outlier) and 2022 (exceptional peak).

Approach 2: Regression trend.

Fit a linear regression line through historical earnings. The trend line represents the underlying growth trajectory, filtering out cycle noise.

Use the trend line's value at the "current" point as normalized earnings.

Pros: Statistically sound, removes outliers, incorporates a growth assumption.

Cons: Assumes a linear trend (rarely true for cyclical businesses). Can be misleading if the industry is in secular decline or growth.

Approach 3: Analyst cycle forecast.

If the consensus among sell-side analysts is that earnings in 2026 (midpoint of the cycle) will be $140M, use that as normalized earnings. This embeds forward-looking expectations and is more defensible than backward-looking averages.

Pros: Forward-looking, incorporates expectations about demand, capacity, and pricing.

Cons: Depends on analyst accuracy and consensus, which can be wrong. Also, consensus often swings with sentiment.

Applying Normalized Multiples to Peers

Once you have normalized earnings for your target company, compare it to peers using their normalized earnings.

Worked example: Cement company valuation

Target company: CemenCo

• Current year (2024) net income: $80M (late-cycle peak)
• Normalized earnings (5-year average): $55M
• Market cap: $1.1B
• Net debt: $200M
• Enterprise value: $1.3B

Peer comparables (all on normalized earnings basis):

Peer	Market Cap	Net Debt	EV	Normalized NI	EV/NI Multiple
CementGiant	$5.0B	$1.5B	$6.5B	$520M	12.5x
RegionalCement	$800M	$100M	$900M	$65M	13.8x
GlobalBuild	$2.2B	($100M)	$2.1B	$180M	11.7x
				Median	12.5x

If CemenCo's normalized earnings are $55M and the median multiple is 12.5x, the implied enterprise value is $687M. With net debt of $200M, the implied equity value is $487M.

But CemenCo's market cap is $1.1B. The stock appears overvalued by ~55% at a normalized earnings basis. This suggests:

1. The market is betting on a cycle up-cycle that pushes earnings well above normalized levels, or
2. CemenCo is overvalued, or
3. The normalized earnings estimate is too conservative

An analyst should then stress-test: if the cycle moves up and earnings rise to $75M (above the 5-year average), the valuation becomes more reasonable. If the cycle turns down and earnings fall to $40M, the stock becomes very expensive.

Adjusting for Cycle Phase

A critical but often-overlooked adjustment: at what point in the cycle are we?

If the company is at or near a cycle peak:

• Multiples are compressed (earnings are high, multiples are low)
• The stock appears cheap on current-year earnings basis
• Adjust downward: Use a conservative normalized earnings estimate, or apply a haircut to the current valuation to reflect mean reversion

If the company is at or near a cycle trough:

• Multiples are expanded (earnings are low, multiples are high)
• The stock appears expensive on current-year earnings basis
• Adjust upward: Use optimistic normalized earnings or apply an upside case assuming recovery

If the company is at the midpoint:

• Multiples are near their long-term average
• Valuation is most reliable

Building a Scenario Analysis for Cyclical Stocks

Rather than a single point estimate, cyclical stocks warrant multiple scenarios:

Scenario 1: Base case (midpoint cycle).

• Earnings at normalized level: $55M
• Multiple: 12.5x (median peer multiple)
• Enterprise value: $687M
• Equity value (less net debt): $487M
• Probability: 50%

Scenario 2: Upside (strong cycle).

• Earnings rise 25% above normalized: $69M (assume industry capacity is tight, pricing power improves)
• Multiple: 13.5x (multiple expands as confidence improves)
• Enterprise value: $930M
• Equity value: $730M
• Probability: 25%

Scenario 3: Downside (weak cycle).

• Earnings fall 25% below normalized: $41M (assume recession, competition, or excess capacity)
• Multiple: 11.0x (multiple contracts as confidence falls)
• Enterprise value: $451M
• Equity value: $251M
• Probability: 25%

Probability-weighted valuation: (50% × $487M) + (25% × $730M) + (25% × $251M) = $507M

This approach acknowledges the uncertainty inherent in cyclical valuation and forces the analyst to consider multiple paths forward.

Real-World Example: Auto Parts Supplier in Cycle Downturn

SupplyCo is an automotive parts supplier with:

• 2024 revenue: $2B (down 8% from 2023 due to lower vehicle production)
• 2024 net income: $120M (down 35% from 2023's $185M)
• 2024 FCF: $95M (down 40% from prior year)

Current market cap: $1.8B, Net debt: $300M, Enterprise value: $2.1B

Naive valuation (using current-year earnings):

• EV/EBITDA (estimated 2024): $2.1B / $180M = 11.7x (appears reasonable to expensive)
• P/E: 15x (appears cheap relative to history)

Normalized valuation:

Over the past 5 years, SupplyCo's net income has averaged $160M. Analysts expect 2026 net income of $155M (assuming stable vehicle production and pricing). Use $157M as normalized earnings.

Peer multiples (on normalized basis): 10.2x–12.0x EV/EBITDA, median 11.1x

Normalized enterprise value: $157M × 11.1x = $1.74B

Normalized equity value: $1.74B − $300M = $1.44B

The stock trades at $1.8B, implying a 25% premium to normalized valuation. Conclusion: The stock is fairly valued or slightly expensive, not cheap. The market has already discounted the cycle downturn into the share price.

Common Mistakes in Cyclical Valuation

1. Using peak-year earnings as forward guidance. Peak earnings are useful for calculating peak leverage (debt-to-EBITDA ratios), but should never be used as a base for relative valuation.

2. Assuming mean reversion will happen faster than it does. Cycles are longer and more persistent than analysts expect. A trough can last 3+ years, not 12 months. Do not buy a "cheap" cyclical stock expecting a quick bounce if the industry backdrop has not actually changed.

3. Confusing normalized earnings with "earning power." A steelmaker's normalized earnings of $150M does not mean it can sustainably earn $150M per year. If industry dynamics have shifted (permanent excess capacity, structural decline in demand), normalized earnings from the past is not predictive.

4. Ignoring leverage through the cycle. A company with 2x debt-to-EBITDA at cycle midpoint might have 4x+ at a trough (earnings fall, debt stays constant). Does the company have the liquidity to survive a severe downturn? Check covenant compliance and refinancing risk.

5. Applying a peer multiple without adjusting for quality differences. A high-quality operator with stable costs, strong balance sheet, and customer relationships may deserve a premium multiple even on a normalized basis. A low-cost but fragile operator may deserve a discount.

6. Overfitting the cycle model to recent history. If the past two cycles lasted 6 years each, do not assume the next cycle will too. Industries evolve. Capacity dynamics change. Competitive positions shift.

FAQ

Q1: How long should I look back to calculate normalized earnings?

A: For a typical business cycle of 5–10 years, use 5–10 years of historical data. If the industry is highly volatile or undergoing structural change, use 7–10 years. If the industry is more stable, 5 years may suffice. Shorter lookbacks (3 years) can be skewed by recent volatility; longer lookbacks (15+ years) may include obsolete competitive dynamics.

Q2: Should I use EBITDA or net income for cyclical stocks?

A: EBITDA is preferable because it strips out financing and tax effects, which distort earnings through cycles. A company with high debt carries larger tax shields and interest charges at cycle peaks (high earnings, high interest coverage) versus cycle troughs (low earnings, lower interest shields). EBITDA normalizes this. EV/EBITDA multiples are more stable across cycle phases than P/E multiples.

Q3: What if my company is in a secular decline, not a cycle?

A: That is a critical distinction. A secular decline (the industry is shrinking permanently) is not the same as cyclical downturn (the industry is temporarily weak). To distinguish:

• Look at 10-year revenue trends: are margins stable, or have they been compressed?
• Check capacity additions: are new entrants entering, or is the industry consolidating?
• Survey customer demand: is demand shifting to substitutes, or just temporarily weak?
• If you see secular decline, apply a haircut to normalized earnings and avoid using a simple cycle-based valuation.

Q4: How do I model synergies or operational improvements for a cyclical stock?

A: Factor them into normalized earnings. If management is implementing cost-reduction initiatives or a merger is eliminating overhead, and you believe the benefits are durable, fold them into the normalized EBITDA. But be conservative: assume they take 2–3 years to fully realize, and assume 50–70% of the promised benefits actually occur.

Q5: Should I avoid cyclical stocks as a long-term investor?

A: Not necessarily. Cyclical stocks can be excellent long-term holds if bought at the right price (trough or midpoint) and you have the patience to hold through cycles. The danger is buying at a peak and waiting years for recovery, or selling at a trough just before the cycle turns. Cyclical stocks reward discipline and contrarian thinking; they punish momentum-chasing.

Q6: What is the best time to buy a cyclical stock?

A: The worst point is at cycle peak (highest confidence, lowest returns). The best point is at cycle trough, when sentiment is most pessimistic, balance sheets are strained, and multiples are highest—IF the company has adequate liquidity to survive and the industry fundamentals (not company fundamentals) have not deteriorated structurally. The opportunistic investor buys cyclical stocks when fear is high, sentiment is low, and the normalized valuation looks cheap.

Related Concepts

• Operating leverage: The extent to which a business's earnings swing with volume changes; high leverage is typical in cyclical businesses.
• Mean reversion: The tendency of cyclical metrics (margins, ROIC, multiples) to revert toward historical averages; drives cycle modeling.
• Secular trends: Long-term, structural changes in an industry (e.g., decline of coal, growth of renewables) that distinguish from cyclical movements.
• Leverage through the cycle: The risk that a company's debt burden becomes untenable during a cycle downturn.
• Normalized multiples: Valuation ratios based on normalized (cycle-adjusted) earnings rather than current-year earnings.

Summary

Cyclical stocks require a different valuation approach than non-cyclical peers. The key is normalizing earnings around a midpoint in the cycle, then comparing valuation multiples on that normalized basis. Using current-year earnings for cyclical stocks creates systematic valuation errors: stocks appear cheap when they are expensive (at cycle peaks) and expensive when they are cheap (at troughs).

Normalize using a 5–10 year average or analyst consensus, adjust for where we are in the cycle today, and build scenario analysis to capture upside and downside paths. Avoid the peak-multiple trap, pay attention to leverage and liquidity through cycles, and remember that cyclical stocks reward patience and contrarian conviction—but only if you have correctly diagnosed where the cycle stands and where it is likely to go.

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