Stanley Black

Dimensions of Equity Returns in Europe

Size, value, and profitability premiums are well documented in the returns of stock markets around the world. This paper extends the evidence of these cross-sectional return patterns to European equity markets and finds that they are pervasive and persistent in Europe. Investors can seek higher expected returns in well-diversified portfolios that target these dimensions of equity returns.


A dimension of expected returns identifies systematic differences in expected stock returns. It must be sensible, persistent through time, pervasive across markets, robust to alternative specifications, and cost-effective to capture in well-diversified portfolios. Decades of rigorous theoretical and empirical research have identified four dimensions of expected returns in equity markets: market, company size, relative price, and profitability.

The market dimension reflects the premium of stocks over bills. Within equities, there are
also differences in expected returns. Securities with smaller market capitalization, lower relative prices, and higher profitability have had higher average returns than those with larger market capitalization, higher relative prices, and lower profitability. There is extensive empirical evidence that these premiums exist in equity markets around the world: See Fama and French (1992, 1993, 1998, 2006, 2012, 2015a, 2015b), Novy-Marx (2013), O’Reilly and Rizova (2013).

Have there been market, size, value (relative price), and profitability premiums in European markets similar to those documented for US and aggregated non-US developed and emerging markets? This paper examines 15 European markets generally classified as developed (Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and the UK) over the period 1982–2014. We show that over the past 30 plus years, there have been market, size, value, and profitability premiums in European markets.


There have been market, size, value, and profitability premiums in Europe over the past three decades. Investors can target these dimensions to improve the expected returns of European equities by (1) using multiple dimensions of expected returns and (2) over-weighting firms with higher expected returns using a measured, controlled, low-turnover weighting schema that incorporates current price. Reliability of outcomes may be increased by using diverse sources of value added (profitability, relative price, and size) and broad diversification across securities and sectors. Low turnover, combined with that broad diversification, allows for a disciplined and patient approach that helps control implementation costs.

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The Cost of a Perfect Market Timing Strategy

What if we could construct a strategy with a correlation close to 1 with a perfect market timing strategy? Can we estimate what its returns would have been? Can we use these estimates to understand what the market would have “charged” for a perfect market timing strategy?

To answer these questions, first let’s define what a perfect market timing strategy needs to know and what it is. A perfect market timing strategy needs to know, with certainty, the future returns of the assets that are eligible for investment. Armed with this information, the perfect market timing strategy always chooses the highest returning asset to invest in. For example, imagine a strategy that can invest in US stocks [for simplicity, the S&P 500 Total Return (TR) Index] and One-Month US Treasury Bills. It rebalances once per month and on that day knows with certainty the return of US stocks and US Treasury bills over the following month. This perfect market timing strategy would then invest all in equities or all in the One-Month US Treasury Bill, depending on which one will have the higher return over the following month. The challenge here is obvious. How can we know with certainty what the future returns on any asset class will be? Without that knowledge, there is no way to create a perfect market timing strategy. Or is there?