Factoring in factors to your investing | BetaShares

Factoring in factors to your investing

BY Isaak Walkom | 28 April 2021
Factoring in Factors to your Investing

Reading time: 3 minutes

In the realm of investing, a ‘factor’ can be described as any characteristic that helps explain the long-term risk and return performance of an asset.

Factor investing is an investment approach that involves targeting specific drivers of return across asset classes. There are two main types of factors that have driven asset class returns: macroeconomic factors and style factors. The former captures broad risks across asset classes while the latter aims to explain returns and risks within asset classes.

Some common macroeconomic factors include:

  • the rate of inflation
  • GDP growth, and
  • the unemployment rate.

Commonly recognised style factors include:

  • growth versus value
  • yield
  • momentum
  • quality
  • volatility
  • liquidity, and
  • size.

Some active managers rely on one of these style factors in an attempt to ‘beat the market’ (and in the process, justify high management fees).

However, investors can also target one or more factors through a low-cost, rules-based index approach. ‘Smart beta’ indices measure the performance of portfolios which tilt toward various style factors, or a combination of factors.

Why take a factor-based approach?

Factor-based investments or smart beta products, when used effectively, can help to improve portfolio outcomes, reduce volatility, and enhance diversification. Factor investing has arisen as a means to potentially offset investment risks by targeting broad, persistent, and long recognised drivers of returns.

Factors can also be used to help build portfolios that better suit individual needs.

Investors looking for downside protection in a volatile market environment might consider increased exposure to low-volatility strategies to reduce their risk, while investors who are comfortable accepting increased risk might look to higher return-seeking strategies like momentum or tilts to smaller size.

It is important to point out that some factors have the potential to generate additional returns because they involve bearing additional risk, and therefore may underperform in certain market conditions.

Factors and smart beta

Let’s discuss the strategy behind some of these factors and smart beta.

Smart beta strategies are those that take a rules-based approach that is not based on market capitalisation weighting, usually with the goal of outperforming a market cap-weighted benchmark. Smart beta strategies are now widely available in ETFs and other managed funds, making factor strategies more affordable and accessible to every investor.

Value – Value aims to capture excess returns from stocks that are judged to have low prices relative to their fundamental value. This is commonly tracked by metrics such as price to book, price to earnings, dividends, and free cash flow.

Yield – A yield (or high dividend yield) investment strategy seeks exposure to companies that appear undervalued and have demonstrated stable and increasing dividends.

Momentum – Momentum is based on the premise that stocks that have outperformed in the past tend to exhibit strong returns in the future. A momentum strategy is commonly grounded in relative returns to the broader market over a three-month to one-year time frame.

Quality – Quality is defined by high profitability, low debt, stable earnings and strong corporate governance. Investors aim to identify quality stocks by using common financial metrics such as return on equity, debt to equity and earnings variability.

Volatility – Low-volatility investing has become an investment style in its own right with the launch of a number of low-volatility equity funds. These funds invest in low-risk stocks, with fund managers using a range of different risk measures to identify the stocks the fund can buy. Measuring standard deviation over a one- to three-year time frame is a common method of capturing beta. A beta greater than one indicates greater volatility than the overall market, and a beta less than one indicates less volatility than the benchmark. If, for example, a fund has a beta of 1.05 in relation to the S&P 500, the fund has been moving 5% more than the index over the relevant comparison period.

Liquidity – Liquidity can be defined as the ease of executing a transaction without incurring excessive costs. When executing a transaction, investors pay explicitly for the prevailing bid-ask spread, and implicitly for any adverse price swings due to the removal of liquidity from the market. All else being equal, the more illiquid a stock, the more difficult and expensive it is to trade it, and this property can make illiquid stocks less attractive than liquid stocks.

Size – Historically, portfolios consisting of small-cap stocks have tended to exhibit greater returns than portfolios holding just large-cap stocks (but have also involved increased levels of investment risk e.g. reflected in increased price volatility). As an example, over the last 20 years (to 28 Feb 2021), the Russell 1000 Index (large-cap) has returned 6.12% p.a. compared to the Russell 2000 Index (small-cap) return of 7.32% p.a.1

What are some examples of ETFs taking a factor approach?

The BetaShares Global Quality Leaders ETF (QLTY) aims to track an index (before fees and expenses) that comprises 150 global companies (ex-Australia) ranked by highest quality score. The quality score rankings used to select the stocks in the index are based on a combined ranking of four key measures – return on equity, debt-to-capital, cash flow generation ability and earnings stability.

As can be seen from the below comparison of the factor profiles, QLTY is tailored to provide a ‘quality’ exposure when compared to a broad global shares index*.

QLTY vs Solactive Global Shares - Factor Profile


Source: Bloomberg.

The below illustrates the performance of QLTY against the same broad global shares index*.

QLTY vs Solactive Global Shares - Historical Returns

Source: Bloomberg. Returns for periods longer than one year are annualised. Past performance is not indicative of future performance.

It’s important to note that all funds will have a weighting (whether high or low) to the above factors, even if they do not explicitly target a specific factor in name.

The BetaShares S&P 500 Equal Weight ETF (QUS) aims to track the performance of the S&P 500 Equal Weight Index (before fees and expenses). QUS provides exposure to 500 leading listed U.S. companies, with each holding weighted equally at each quarterly rebalance. Although not specifically targeting this particular factor, equal weighting has the effect of more heavily weighting smaller companies compared to the market cap-weighted S&P 500 Index.

QUS vs S&P 500 - Factor Profile

Source: Morningstar Direct.

The below illustrates the performance of QUS’ Index against the S&P 500 Index.

QUS vs S&P500 - Historical Returns

Source: Morningstar Direct. Past performance is not indicative of future performance.


Factor-based investments or smart beta products, when used effectively, can help to improve portfolio outcomes. It’s important investors understand all investments will exhibit differing degrees of the above factors even if the fund does not explicitly target those factors. A fund exhibiting a small style bias may not be suitable for retirees, while a fund tilted more towards high yield may not be the most desirable for accumulators. It’s important to understand the factor exposure you are taking on and to compare this to your investment objectives.

There are risks associated with investment in the BetaShares Funds, including market risk, index methodology risk and foreign currency risk, as well as international investment risk and concentration risk (for QLTY) and country risk (for QUS). For more information on risks and other features of each BetaShares Fund, please see the Product Disclosure Statement, available at www.betashares.com.au.

*Broad global shares index is the Solactive GBS Developed Markets Large & Mid Cap Index.
1. Morningstar Direct. Past performance is not indicative of future performance.

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