Low-Volatility Strategies

🧭 Background & Context 📏 Low-volatility strategies are based on the empirical observation that stocks with low price fluctuation often perform better on a risk-adjusted basis over long periods than volatile securities. The economic core lies in the so-called „low-volatility anomaly,“ which contradicts the classic risk-return relationship, as defensive sectors such as utilities or healthcare often deliver stable earnings with below-average beta. For private investors, this means a reduction in emotional decision-making errors, as calmer price movements significantly decrease the tendency for panic selling during crises. At the same time, the strategy allows for a higher allocation to stocks within the portfolio without excessively increasing overall risk, which strengthens the compound interest effect over the long term. However, returns are often weaker in strong bull markets, which is why a pure implementation without adding growth-oriented stocks leads to opportunity costs. For investors with a long horizon and low risk tolerance, low-volatility ETFs are therefore a sensible foundation, but one that should be regularly rebalanced to maintain the desired stability. 🔍 How It Works in Detail Low-volatility strategies focus on stocks whose prices move up and down only slightly compared to the overall market. Investors therefore select securities that have performed particularly calmly and steadily in the past, rather than betting on highly volatile growth stocks. The goal is not to achieve the highest return, but to attain solid, long-term performance with the lowest possible price fluctuations. Due to lower fluctuation, interim losses during crises are usually smaller, which provides psychological relief and helps avoid panic selling. At the same time, one forgoes the chance of large price jumps, which can lead to below-average performance in strong upward markets. The strategy works particularly well when investors have a long investment horizon and value reliability. Selection is often based on mathematical metrics such as the standard deviation of returns, with r …