In my analysis, I explored the relationship between stock volatility and returns within the S&P 500 over the past 10 years. The common belief in trading is that higher risk leads to higher reward. To test this, I backtested portfolios built from the least and most volatile stocks, examining their performance using daily price data sourced from the EODHD API.
By calculating rolling volatility and ranking stocks monthly, I constructed equal-weighted portfolios of high- and low-volatility stocks and compared their returns against an equally weighted S&P 500 benchmark. Additionally, I analysed how this relationship varies across sectors like Technology, Financial Services, and Healthcare to uncover possible anomalies.
The results confirmed that high-volatility stocks generally deliver higher returns on average, supporting the traditional risk-reward idea. However, specific sectors, such as technology, challenged this norm, where low-volatility stocks outperformed their riskier peers. Other sectors, such as Healthcare, showed irregular patterns influenced by regulatory events and fundamentals.
This study that I published on Medium, highlights that the impact of volatility on returns is complex and sector-dependent. For those interested in the technical details, including the full Python code and methodology behind this analysis, I invite you to read the complete article. It provides comprehensive insights and practical tools for traders and analysts to further explore volatility’s role in investment strategies.