Amplifying Noise or Delivering Alpha? Performance Evaluation of Finfluencer Stock Recommendations

• Stock tips from social media influencers earn brief gains but lose value over time • Long-term returns of influencer stock picks lag behind the market benchmark • Influencer portfolios are riskier and deliver poorer risk-adjusted performance • Recommendations earn short-term abnormal returns but no medium-term outperformance. • Followers, posting activity, and account age do not predict abnormal returns. We study whether financial influencers (“finfluencers”) deliver alpha or merely amplify noise. Using a manually collected sample of 1,056 stock recommendations by 44 Instagram-based finfluencers in the DACH 1 1 The DACH region comprises Germany (D), Austria (A), and Switzerland (CH). This region is particularly suitable for our analysis because it combines a shared language with broadly comparable institutional and regulatory frameworks, allowing for a homogeneous examination of Instagram-based finfluencer stock recommendations. The DACH region constitutes one of the largest and most economically significant retail investor markets in Europe. region, we construct buy-and-hold portfolios and benchmark-adjusted abnormal returns over short-, medium-, and long-term horizons: 30 calendar days, 365 calendar days (one year), and 1,095 calendar days (three years). Across both benchmarks, finfluencer recommendations generate a small positive abnormal return in the short term, no economically meaningful medium-term outperformance, and a pronounced long-run underperformance. Portfolios formed from finfluencer recommendations exhibit substantially higher volatility, larger downside risk, and markedly lower Sharpe ratios than the benchmark, indicating that followers are exposed to elevated risk without commensurate compensation. Observable influencer characteristics, such as follower counts, posting activity, and account age, do not systematically correlate with abnormal performance. Overall, our evidence is consistent with attention-driven noise trading rather than persistent informational advantage and suggests that finfluencer stock recommendations function more as digital financial entertainment than as a reliable source of alpha.