Testing a Magic Formula Value and Quality Strategy in A-Shares

Summary

This research summary adapts Joel Greenblatt’s value-and-quality stock-ranking idea to China’s A-share market. It uses EV/EBITDA as a valuation measure and ROIC as a business-quality measure in place of the original formula’s measures. The described screen uses valuation data dated April 30 and ROIC from the prior year’s financial statements, applies stated data-cleaning filters, and ranks companies on both measures. It combines the ranks and forms equal-weight portfolios from the best-ranked 10, 20, or 30 stocks, rebalanced annually.

The summary reports that the top-10 portfolio outperformed the larger portfolios and the market over the backtest period from 2001 to 2018, including a stated cumulative return. It provides no details here on transaction costs, survivorship or look-ahead bias, benchmark construction, or robustness across periods. The reported results are therefore a historical test of this particular dataset and implementation, not evidence that the strategy will continue to outperform.

Key ideas

• The study combines valuation and quality ranks to select A-share stocks.
• It uses EV/EBITDA and ROIC, with valuation data from April 30 and prior-year ROIC data.
• The method forms equal-weight portfolios of the top 10, 20, or 30 ranked stocks and rebalances annually.
• The summary reports that the top-10 portfolio outperformed the larger portfolios and market over its historical test.
• The summary does not address transaction costs or key backtest biases.

Tags

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