Long-run Factor Premium Returns

Long-run Factor Premium Returns

For most people, a long-term investment approach works best. Recent stock market volatility demonstrates the futility of attempting to time the market.

Over time, a handful of key equity factors including Size, Value and Momentum, have risen to prominence as drivers of portfolio returns in excess of returns available from passively tracking the stock market index (see our guide below for a reminder of the terminology). These excess return premiums, or factors, embody specific characteristics and those factors combine to explain past returns in excess of the market return.

To help display and compare pure factors over time, our new chart includes data from the most impeccable sources we could find, two well known datasets – the “Fama/French 3 factor model” and “AQR Momentum”. We include the longest time periods available. Data of the two best known Fama/ French factors (the Value and Size factors) can be seen in our chart along with several versions of the Momentum factor using data from both Fama/ French and AQR. Whilst our data is predominantly US, the reason that researchers typically use US stockmarket data is because this dataset is most accurate and readily available.

Asset 3@10x 8

Reading the Chart

The bottom (black) line of our chart, and the foundation of any low cost long term equity portfolio, is the exposure to the world’s largest equity market and this is represented by the cap-weighted return of all firms incorporated in the US and listed on the NYSE, AMEX, or NASDAQ. (1)

The next lines above the market return are the two classic equity factors, the Size factor (coloured turquoise) and the Value factor (coloured yellow), which emerged from the research of Kenneth French and Eugene Fama of University of Chicago in the early 1990s. (2)

Starting from two different dates, the top three lines in our chart (coloured dark blue, purple and light blue) represent variants of the Momentum factor including an international data series. Clifford Asness, one of Fama’s doctoral pupils, developed the field of research around the Momentum factor, and the interaction of Value and Momentum strategies, from the mid-1990s before launching AQR, now an eponymous investment firm. AQR publish their Momentum Indices on their website with monthly updates. AQR Momentum indices start at different dates to the Fama/French Momentum index which is also displayed. (3)

If you find the chart useful we hope to provide updated versions in the future, perhaps with other additional factors or regions included.

Factors 101

What is the Value Factor? Value refers to a range of fundamental metrics which determine relative cheapness. For example, stocks priced closer to their book value have higher expected returns than stocks priced above their book value.

What is the Size Factor?
The size factor suggests that small companies have higher expected returns than larger companies.

What is the Momentum Factor? Momentum is the phenomenon where winning securities continue to outperform whilst losers underperform. A 12 month time frame, excluding the most recent month, is typically used to isolate strong Momentum stocks.

Who are Fama/French? Eugene Fama and Kenneth French were professors at the University of Chicago Booth School of Business (where Fama remains). Fama is best known as the “father of the efficient markets hypothesis” as well as for his work on asset pricing models. In 2013, Fama shared the Nobel Memorial Prize in Economic Sciences.

Who is Clifford Asness?
A doctoral student of Fama, Asness had more of a practitioner mindset than Fama and founded the Goldman Sachs Global Alpha Fund, one of the first quantitative investment funds, before setting up AQR Capital Management in 1998.

Mixing Factors

Combining factors to harvest performance and control risks coming from different sources and directions offers opportunities to accrue additional benefits from diversification (4). Factors perform differently in different time periods and market regimes. For example, Momentum typically has a negative correlation to Value and behaves in an opposite manner.

Factor performance, popularity and even definitions tend to evolve over time. The Size premium went out of fashion around 2000 but staged a remarkable recovery to 2015. More recently the Value factor has experienced long periods of underperformance, although it also had long periods of outperformance up to the mid-1980s and around the turn of the century.

Factor definitions can also mushroom. For example, distortions in US GAAP book values meant that traditional book value was sometimes less useful as a Value metric than trailing earnings yields (the opposite of P/E). Several definitions of Value are now popular.


(1) Whilst the Fama French data is a regression-based exercise built around the Fama French three factor asset pricing model, AQR is a dynamically sorted index using market pricing data. For capital market returns we adjust Fama French’s market data to add back the risk free rate using the Ibbotson U.S. 30 Day Treasury Bill Total Returns.

(2) The Fama/French factors are constructed using six Value-weighted portfolios formed on Size and book-to-market. HML is the equal-weight average of the returns for two high Book to Market (B/M) portfolios for a region minus the average of the returns for two low B/M portfolios. Fama/French publish their research with monthly updates on the website of Dartmouth University. SMB (Small Minus Big) is the average return on three Small stock portfolios minus the average return on three Big stock portfolios.

(3) AQR’s investment universe is screened based on market capitalization, liquidity and other considerations. To form the indices, the stocks in the investment universe are ranked by their total return over the previous twelve months, excluding the last month. The top 33% of stocks with the highest rank are included, and weighted based on their market capitalization. The indices are re-balanced quarterly.

(4) Roger Clarke, Harindra de Silva & Steven Thorley, Risk Management and the Optimal Combination of Equity Market Factors, Financial Analysts Journal, 2020.