Building a Diversified Portfolio with Volatility-Based Rebalancing

Summary

The article recounts a portfolio project that selects 22 stocks from 11 sectors of the S&P 500. It assigns weights using each asset’s standard deviation and rebalances quarterly: riskier stocks receive less exposure, while less volatile stocks receive more. The project also explores a hedge that shorts the benchmark in proportion to the portfolio’s beta, extending the allocation approach toward market-risk management.

The account reports that, during the COVID-19 period, the portfolio had lower volatility, better drawdown characteristics, and a higher Sharpe ratio than its benchmark, although it did not outperform on returns. This is a student project summary, not a full research paper: the article does not give the sample dates, weighting formula, benchmark comparison details, or transaction costs. Its reported results therefore offer a case example rather than strong evidence that the rules will work elsewhere. The approach also relies on standard deviation as its risk measure, and the description does not explain how other risks or practical trading constraints were handled.

Key ideas

• The example portfolio selects stocks across 11 sectors of the S&P 500.
• Quarterly rebalancing increases weights in lower-volatility stocks and reduces weights in higher-volatility stocks.
• The project adds a benchmark short sized according to portfolio beta.
• Reported results show lower volatility and better drawdowns than the benchmark, but weaker returns.
• The account omits implementation details needed to assess costs or repeat the reported comparison.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.