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GLOBAL RESEARCH ARCHIVE

COST - We Have Nothing to Fear…But A Risk-On Backdrop Itself—June Momentum to Persist But We Stay NEUTRAL-Rated On Valuation

Published: 2026-07-02Institution: Guggenheim Securities LLCCompany / ticker: COST.OQPages: 19Original language: 英语Evidence page: 1

Research evidence excerpt

COST - We Have Nothing to Fear…But A Risk-On Backdrop Itself—June Momentum to Persist But We Stay NEUTRAL-Rated On Valuation

Exhibit 2. We would note that, for the first time, COST ran a five-day Member Appreciation

Price Target NA event—see Exhibit 3—to counter the Amazon Prime (AMZN) days, although it is hard to

tell how impactful it was. We estimate 6.5% Other International and 5.0% Canada “core”

comps, respectively, with the latter moderating in the face of difficult compares and strong

EPS ($) AUVs. As detailed in Exhibit 4, we see product category top-line breadth with non-foods and

(FY AUG) 1Q 2Q 3Q 4Q FY fresh foods comps growing 8% and foods and sundries up 5%, in line with the trendlines.

2025 4.04 4.02 4.28 5.87 18.21 Industry-leading discretionary comps were likely paced by jewelry and home furnishings.

P/E 50.8x Ancillary comps likely grew 35%, primarily due to gas inflation and high-single digit gallon

2026 4.50 4.58 4.93 6.56E 20.57E increases—core ancillary may have risen 5%.

Prior — — — 6.62E 20.63E

P/E 45.0x 2027, Another Year of the Low-Double Digit EBITDA Algo. Our detailed quarterly 2027

forecasts, now completed and laid out in Exhibit 5, bolster the case for a sustainable 2027 4.99E 5.15E 5.53E 7.24E 22.92E

10-12% EBITDA algo, primarily driven by gross margin expansion stemming from mix shifts. Prior — — — — 23.02E

Reflecting difficult compares, especially in non-foods, we model a moderation in “core” P/E 40.3x

comps to 6.0-6.5% in the 2H from 6.5-7.0% in the 1H with reported comps softening even

EBITDA($M) more, by 250 basis points, due to the cycling of gas price inflation and a normalization (FY AUG) 1Q 2Q 3Q 4Q FY

in Fx. However, we do not expect this to compromise the bottom-line algo, with projected 2025 2,725 2,856 3,212 4,158 12,951

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