Quantitave Value Investing in Europe: What Works for Achieving Alpha

There is a growing literature on statistical methods to beat the market inspired by the original classics, Dremen‘s Contrarian Investment Strategies and Greenblatt‘s Little Book, but a new report uniquely focuses on Europe and adds momentum to the mix of factors tested. Like other studies, it shows simple value measures beat the market, but with a surprising twist.

Many traditional value and fundamental statistics are tested, and combined with each other and momentum, in a study that goes back twelve years. Here’s the list:

• Earnings yield,
• Free cash flow yield,
• Price-to-book
• Price-to-sales,
• Piotroski F-score
• Return on invested capital (ROIC)
• Return on assets (ROA)
• Net debt
• Relative strength / price index

Although price to book performed best overall, for smaller companies, with market capitalisations between 15m euros and 100m euros, the most profitable factor was momentum: how much a company’s price had risen over the previous six months. All of the top-ten two-factor combinations, applied to companies of all sizes, included a momentum factor. The best two-factor combination, six-month price index and price to book, returned 23.5% compound versus 2.25% for the market.

There’s something quite gratifying in the two best known anomalies in the efficient market hypothesis, price to book and momentum, combining to make it look inefficient.

I’m not as surprised as I might be for two reasons. I believe investors are slow to recognise good news, an improvement in company fundamentals say, so it should be possible to piggy-back on price rises. The effect is most pronounced in smaller companies because they’re ignored by many investors, which is how Piotroski rationalised the extraordinary performance of his F_Score, effectively a fundamentals based momentum indicator (it tells you if a company’s performance is improving, not its share price).

But, although the F_Score emerges from the study well, price momentum appears to work better.

The second reason my eyebrows are only half raised is Keith Anderson, who wrote his Ph.D. thesis on improving the PE ratio, uses momentum in his personal trading to judge the timing of purchases of very cheap companies he’s identified with his Naked PE measure. Cheap shares can always get cheaper, so he prefers to wait for the price to start rising.

The report covers 1,500 companies in the 17 country eurozone market between 13 June 1999 and 13 June 2011. It excludes financial and investment companies and companies which trade in very small volumes. To avoid survivorship bias the authors use the last stockmarket price available for companies that delisted during the study. They arranged each factor and combination into performance quintiles benchmarked against the 250 most traded companies in the test, which they also rebalanced annually.

I can think of a few quibbles that my statistically-minded collaborators may leave in the comments, so let me jump the gun:

To test whether long-term averages, which the authors also tested, work better than single year ratios, maybe the authors should have averaged over periods longer than five years. Keith’s tests found that only averaging six or more years improved the performance of his PE statistics.

Graeme will remind me twelve years is not long enough.

And the authors Philip Vanstraceele and Tim Du Toit recognise that the strategies that won in the past won’t necessarily win in the future, though they counter:

For the next 10 years the top performing strategy we tested of buying the lowest 20% of companies by book value of the 20% of companies that have increased the most in price over the past six months will most likely not be the best strategy. But it will still give you outstanding market beating returns. In the past 12 years the strategy returned just under 1160%, compared with the market portfolio 30.54%. Does it really matter if the strategy falls to position 20 of the strategies we tested and generated a total return of 670%?

Tim sent me the report on-spec, and I’ve shared what I can because backtests in markets other than the US are relatively rare, and investors will be interested to see how their pet ratios perform.

If you’re interested, you’ll have to buy it I’m afraid. Quantitave Value Investing in Europe costs ''83.94 in PDF format, contains 54 pages and includes data and commentary on each factor and the combinations, judging them not just on the basis that the top quintile outperforms the bottom, but also that each quintile is better than the one below it and the factor or combination performs consistently over time.

It also touches on earlier academic and popular work on the performance of financial ratios and mechanical strategies and tests two strategies, Philip’s ERP5 and Joel Greenblatt‘s Magic Formula.