SNOWNEUTRAL

SNOW EV/EBITDA Analysis

-97.4x

Updated 83h ago·SEC filings & market data

Key Takeaway

EV/EBITDA compares a company’s total value to its earnings before interest, taxes, depreciation, and amortization, and a negative value means EBITDA is negative.

Sector Performance

1th percentile

SNOW

-97.4x

Sector Median

13.6x

Sector Avg

-62.3x

Prior Period

-102.2x(Aug 2026)

↓ Declining

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Deep Analysis

EV/EBITDA compares a company’s total value to its earnings before interest, taxes, depreciation, and amortization, and a negative value means EBITDA is negative.

At -97.3x, Snow’s multiple sits far below the sector median of 13.6x, placing it in the 2th percentile among peers. The metric is decreasing, with a quarter-over-quarter change of -8.0% and a year-over-year change of N/A, and the last eight quarters show a continued downward path from -80.3x to -97.3x. The deeply negative level combined with a worsening trend indicates higher financial risk, as the company’s operating losses are increasing relative to its valuation. This contradicts the overall NEUTRAL verdict by tilting toward a bearish interpretation of current fundamentals.

Frequently Asked Questions

What does the EV/EBITDA tell investors about SNOW?

A valuation multiple preferred by analysts for capital-intensive or leveraged businesses. Useful for cross-sector comparisons where earnings can be distorted by debt.

How is the EV/EBITDA calculated?

EV/EBITDA is calculated as: Enterprise Value / EBITDA.

Who are SNOW's closest peers by EV/EBITDA?

The closest peers by EV/EBITDA include: SG (-17.2x), FLNC (-22.5x), EVGO (-22.6x), LSPD (-26.9x), BRZE (-29.6x).

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Learn More About EV/EBITDA

EV/EBITDA Explained: The Valuation Metric Pro Investors Actually Use

Learn what EV/EBITDA is, why it beats P/E for capital-heavy companies, typical sector ranges, and key limitations every serious investor should know.

The Formula

Enterprise Value / EBITDA

Why It Matters

A valuation multiple preferred by analysts for capital-intensive or leveraged businesses. Useful for cross-sector comparisons where earnings can be distorted by debt.