Fairvalue-Calculator Fairvalue-Calculator

Karat Packaging Inc (KRT) Fair Value & Analysis

Consumer Cyclical · US · Market cap $604M

Price$29.80
Fair Value$26.80
Upside-10.1%
Quality91/100
Evidence: High Range $16.98 – $33.51

Analysis

Karat Packaging Inc (KRT) currently trades at $29.80, while our model-based Fair Value estimate is $26.80 — implying the stock looks roughly 10.1% overvalued today. We read business quality at 91/100 (high quality), in the Consumer Cyclical sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).

About the company

Karat Packaging Inc., together with its subsidiaries, engages in the manufacture and distribution of single-use disposable products in plastic, paper, biopolymer-based, and other compostable forms used in various restaurant and foodservice settings. It offers food and take-out containers, bags, boxes, tableware, cups, lids, cutlery, straws, specialty beverage ingredients, gloves, utensils, janitorial and warehouse supplies, and other products under the Karat Earth brand. The company also distributes food and beverage items, such as syrups, boba tea, and coffee drinks; and provides new product development, design, printing, and logistics services. It offers its products to national and regional distributors, restaurant chains, retail establishments, and online customers. Karat Packaging Inc. was founded in 2000 and is based in Chino, California.

Open the full interactive analysis →

Similar stocks

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.