Albemarle Q3 net sales beat on Energy Storage pricing strength
Overview
US lithium and bromine supplier's Q3 net sales rose 19% yr/yr, beating analyst expectations
Adjusted EPS for Q3 beat analyst expectations
Q3 adjusted EBITDA slightly beat analyst estimates
Outlook
Albemarle raises 2026 Specialties adj EBITDA outlook to $350-$375 mln from $275-$325 mln
Company lowers 2026 capital expenditure forecast to $300-$350 mln from about $500 mln
Q4 2026 net sales and adj EBITDA expected to fall sequentially on lower market pricing
Result Drivers
HIGHER PRICING - Co said Q3 sales growth was primarily driven by higher prices in Energy Storage and Specialties, as well as volume growth in Specialties
COST AND PRODUCTIVITY IMPROVEMENTS - Co said ongoing cost and productivity improvements contributed to higher adjusted EBITDA
LITHIUM PRICING - Improved lithium pricing was a key driver of Energy Storage segment profitability, partly offset by higher input costs
Company press release:
Key Details
Metric | Beat/Miss | Actual | Consensus Estimate |
Q3 Net sales | Beat | $1.55 bln | $1.52 bln (12 Analysts) |
Q3 Adjusted EPS | Beat | $2.58 | $2.54 (15 Analysts) |
Q3 EPS | $2.15 | ||
Q3 Adjusted EBITDA | Slight Beat* | $645.50 mln | $639.76 mln (13 Analysts) |
*Applies to a deviation of less than 1%; not applicable for per-share numbers.
Analyst Coverage
The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 16 "strong buy" or "buy", 7 "hold" and no "sell" or "strong sell"
The average consensus recommendation for the specialty chemicals peer group is "buy"
Wall Street's median 12-month price target for Albemarle Corp is $155.00, about 71.9% above its November 3 closing price of $90.19
The stock recently traded at 9 times the next 12-month earnings vs. a P/E of 10 three months ago
Reuters Recommended Reads
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Nov 3 - Specialty chemicals supplier Innospec's Q3 revenue slightly misses estimates
Nov 3 - Rayonier Advanced Materials Q3 sales and EBITDA miss estimates on tariffs, impairments
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(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)