What is factor investing?

Factor investing means building a portfolio around characteristics of stocks that have historically explained differences in returns — factors — instead of simply holding the market by size. The best-known factors are:

Value: stocks that are cheap relative to their earnings, book value or cash flow.
Momentum: stocks that have risen more than others over the past months.
Quality: companies with high profitability, stable earnings and little debt.
Size: smaller companies.
Low volatility: stocks that have fluctuated less than the market.

Factor ETFs, often marketed as "smart beta", tilt their holdings toward one or more of these characteristics.

The idea behind it

Academic research — most influentially by Eugene Fama and Kenneth French in the early 1990s — found that a few factors explain a large part of the differences between the returns of stock portfolios. A portfolio's return above the risk-free rate can be broken down as:

R_p - R_f = \alpha + \beta_{\text{mkt}} (R_m - R_f) + \beta_{\text{size}} \, \text{SMB} + \beta_{\text{value}} \, \text{HML} + \varepsilon

where $R_m - R_f$ is the market's return above the risk-free rate, SMB ("small minus big") the extra return of small companies over large ones, HML ("high minus low") the extra return of cheap stocks over expensive ones, and each $\beta$ the portfolio's exposure to that factor. Later models added profitability, investment and momentum.

A simple illustration

In a period in which the market returns 8% above the risk-free rate, cheap stocks beat expensive ones by 3 points and size adds nothing, a portfolio with a market beta of 1.0 and a value exposure of 0.5 would be expected to earn:

1.0 \times 8\% + 0.5 \times 3\% = 9.5\%

above the risk-free rate — 1.5 points of it from the value tilt. In a period in which value stocks lag by 3 points, the same tilt costs 1.5 points.

Why factors might pay

Risk: cheap and small companies may be more vulnerable in bad times, and investors demand compensation for holding them.
Behaviour: investors overreact and underreact to news, creating patterns such as momentum.

What to keep in mind

Long droughts. Factors can underperform for a decade or more; value lagged growth stocks for much of the 2010s.
Crowding and costs. Once a pattern is widely known and traded, part of it may disappear, and factor ETFs cost more than plain index funds.
Combining helps. Different factors tend to work at different times, so multi-factor funds spread the bet.
It is still an active choice. A factor tilt is a decision to deviate from the market, with the tracking error that comes with it.

See these numbers for your own portfolio

Floreo works out every figure on this page from your own holdings — returns, risk, allocation, currencies — and the assistant explains them the way this page does. Import from your broker, or try it on the sample portfolio first.

Start Demo

The demo opens straight away on a sample portfolio — no account needed.