🧠Investing strategies
Proven investing approaches — value, growth, dividends and smart-money following. How to pick a strategy that fits you.
Investing strategies — overview
An investing strategy is a rule-based framework that decides which stocks to watch, when to enter a position and when to exit. Without a strategy, investing becomes a reaction to emotion and headlines — with one, you have a repeatable process that can be backtested and compared to the market. QMA builds on several proven approaches: value (finding undervalued companies by fundamentals), growth (fast revenue and earnings growers), dividend growth (stable payers raising distributions) and smart-money following (tracking institutional, insider and 13F flows). Each approach has a different risk profile, horizon and cycle sensitivity. Value tends to be patient and works across cycles, growth carries higher return and higher volatility, dividend portfolios pay regular income, and smart-money following leans on publicly reported data (SEC EDGAR, 13F, Congressional trades). The point is not to find the single "best" strategy, but the one that fits your horizon, risk tolerance and available time. This section describes each strategy, its historical backtests (with trade counts and statistical significance) and how QMA scores it across the 5 pillars. A backtest describes the past — it does not guarantee future results, but it clarifies when a strategy worked and when it lagged.
Investing strategies articles
Multibagger Pro — ce que la recherche académique dit sur la recherche d'actions à rendement 10×
Consensus de 3 études académiques (Yartseva 2025, Mayer 2018, Alta Fox 2020) sur la chasse aux actions à rendement 10×. Composite de 7 facteurs + détection d'inflexion + filtre macroéconomique. Divulgation honnête des limites.
Fenêtres super saisonnières : comment interpréter le taux de réussite, le rendement et le nombre d'années
Pour environ 10 000 actions, QMA pré-calcule les fenêtres calendaires où les actions ont historiquement augmenté. Nous apprenons à lire le taux de réussite ainsi que le rendement — et avertissons fermement contre les petits échantillons.