Value Investing Backtesting Greenblatt's Magic Formula

Posted: 08 Jun 2020 06:03 AM PDT

Over the past week I've been researching various systematic equity strategies and decided to backtest Joel Greenblatt's Magic Formula, discussed in The Little Book That Beats the Market.

https://preview.redd.it/di0tni8yno351.png?width=1386&format=png&auto=webp&s=26986813370b64376d6d530e7481d29d6322cdcd

Result: between 2003 and 2015, the Magic Formula strategy returned an annualised 11.4% (Sharpe ratio 0.60), versus 8.7% for the S&P500 (Sharpe ratio 0.54). This corresponds to a 3% alpha, so the Magic Formula does indeed outperform the market.

What is the Magic Formula?

A very brief summary is as follows (the exact procedure described in the link): rank stocks by Return on Capital (a measure of quality) and also by earnings yield (a measure of cheapness). Add the ranks to create a score that takes into account both quality and cheapness, then pick the top stocks.

In The Little Book, Greenblatt suggests that the Magic Formula returned an annualised 33% from 1988 to 2004 compared to 14% for the S&P500. My investigation shows that while there is some outperformance on a risk-adjusted basis, it is nowhere near as much as Greenblatt suggests. I think this is due to the arbitraging force of systematic equity ETFs as well as a possible regime shift post-2008.

Other insights from the backtest

The Greenblatt score is indeed correlated with higher future returns (adjusting for survivorship bias). The quantile plot below shows the mean return for different quantiles of the combined ranking score:

https://preview.redd.it/hlaw7e9ypo351.png?width=1426&format=png&auto=webp&s=529b0b6892aa1bb8447a0e5f1bf70ea7ed3a3413

Pre-2008, the annualised return was 26% vs 18% for the benchmark, consistent with Greenblatt's results. However, after 2008 the outperformance shrinks drastically.
The Magic Formula experienced deeper drawdowns than the SPY and is more volatile overall (but this is more than adequately compensated for by return, as seen in the higher Sharpe ratio).

About the backtest

I built the backtest in python on the Quantopian platform. I first analysed the predictive power of the Greenblatt score and since the results were good, moved on to construct a proper backtest that includes transaction costs and follows Greenblatt's accumulation procedure. The only reality not captured by the backtest is tax optimisation.

More information

I have written a blog post containing more information, including potential modifications if you wanted to use it for personal investing. The full backtest report is on GitHub – you can download the html and open it with any browser.

Always happy to hear any feedback, questions or criticism!

EDIT: backtest up until June 2019 as requested by u/flyingflail (can't go any further due to data limitations). It turns out that the 2015-2019 time period is terrible for the strategy. Significantly underperforms the market. A good reminder that past performance is not indicative of future results!

https://preview.redd.it/fcaqktxdmp351.png?width=901&format=png&auto=webp&s=9cc56ca00fa1587b5c5faac11203989ebdb2e435

submitted by /u/marvin182
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submitted by /u/Beren-
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