Money Forward, Inc (MNFYY) Fair Value & Analysis
Technology · US · Market cap $1.3B
Analysis
Money Forward, Inc (MNFYY) currently trades at $12.00, while our model-based Fair Value estimate is $2.48 — implying the stock looks roughly 79.3% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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: medium).
About the company
Money Forward, Inc. provides financial solutions for individuals, financial institutions, and corporations primarily in Japan. The company offers personal financial management services under the Money Forward ME, MONEY PLUS, Money Forward Personal Financial Consulting, and Money Forward Fixed Cost Review names; Money Forward Cloud, a software-as-a-service (SaaS) application for promoting back office operations; and accounting and tax solutions under the Money Forward Cloud Accounting, Money Forward Cloud Accounting Plus, Money Forward Cloud Tax Return, Money Forward Cloud Invoice Issuing, Money Forward Cloud Invoice Issuing Plus, Money Forward Cloud Receivables Management, Money Forward Cloud Expense, Money Forward Cloud Accounts Payable, Money Forward Cloud Invoice System, Money Forward Cloud Fixed Assets, Money Forward Cloud Project Cost, Money Forward Cloud Consolidated Association, and Money Forward Cloud Box names. It also provides human resource solutions under the Money Forwa…
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.