Fairvalue-Calculator Fairvalue-Calculator
EN DE

Qiiwi Games AB (QIIWI) Fair Value & Analysis

Communication Services · SE · Market cap 22.8M SEK

Pricekr 2.01
Fair Valuekr 1.55
Upside-22.9%
Quality95/100
Evidence: Low Range kr 1.02 – kr 1.94

Fair value as of: Jun 25, 2026

Analysis

Qiiwi Games AB (QIIWI) currently trades at kr 2.01, while our model-based Fair Value estimate is kr 1.55 — implying the stock looks roughly 22.9% overvalued today. We read business quality at 95/100 (high quality), in the Communication Services 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: low).

About the company

Qiiwi Games AB (publ) develops mobile games for casual gamers in Sweden. It sells its products through mobile platforms, such as Store, GooglePlay, Facebook, and Amazon. The company was incorporated in 2005 and is based in Alingsås, Sweden.

Open the full interactive analysis →

Similar stocks

Frequently asked questions

Is Qiiwi Games AB (QIIWI) undervalued?
As of Jun 25, 2026, our model estimates a fair value of kr 1.55 versus a price of kr 2.01 — about −23% (overvalued). Model-based estimate, not financial advice.
What is the fair value of QIIWI?
Our 21-model fair value for Qiiwi Games AB is kr 1.55 (as of Jun 25, 2026), built from audited fundamentals. The current price is kr 2.01.
What is the quality score of QIIWI?
Qiiwi Games AB has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.