Factor Investing – Investment success by targeting specific drivers of return across asset classes

Investing in factors can improve portfolio outcomes, reduce volatility and enhance diversification

Stock Market Analysts
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Factor investing is a rapidly growing approach to evidence based and quantitative investing. It is now estimated that over $1.9 trillion in assets are managed globally using factor-based strategies. Investment strategies based on factors that have historically led to outperformance are ideally suited to products like exchange traded funds, as well as segregated portfolios. In this article we outline the history of factor investing, what it entails and some prominent examples of factor investing. We also look at the pros and cons of factor investing.

What is factor investing?

Definition Factor Investing
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Factors are specific attributes of stocks that have historically proven to have driven returns. An example of a commonly tracked factor is the price-to-book ratio which is a measure of value. Portfolios of stocks with low price-to-book ratios have outperformed market indices over most time periods in the last 50 years. Mutual funds and ETFs (exchange traded funds) based on factor investing strategies are now commonplace.

Institutional investors have also turned to factor investing strategies which are in several ways cheaper to manage than traditional active management strategies. Factors are usually combined to build portfolios that are expected to generate excess returns when measured against a benchmark. Factors are also used to manage risks within asset classes. Factor investing is typically focussed on factors specific to individual companies and their expected returns.

However, macroeconomic factors can also be used to describe market environments and how they might affect asset classes and sectors. If a macro factor describes and captures broad risks across asset classes, it can be helpful to the asset allocation process. Factor investing is also referred to as risk premia investing, as the objective is to select securities that are expected to earn a larger than average risk premium.

A brief history of factor investing

Factor Investing History
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The concept of investment factors has its roots in the capital asset pricing model which was developed in the 1960s. This model suggested that returns were largely related to risk, which was measured by beta. The higher a stock’s beta, the higher the expected return. The next step came in 1981 when a research paper showed that smaller stocks outperformed larger stocks over the long term.

Then, in 1992 two professors at the University of Chicago, Eugene Fama and Kenneth French, showed that value could also be used to estimate future returns. The following year another paper showed that stocks with high momentum could outperform market indices. Since then, research has showed that a range of other factors related to profitability, yield, leverage and external financing could also be used to explain long term outperformance.

Although BlackRock launched the first factor fund in 1971, the approach has only become popular in the last two decades. This is largely because factor investing lends itself so well to low cost products like exchange traded funds. According to Morningstar, there are now 771 ETFs based on factors. These provide a wide range of tools with which to build a factor-based ETF investing strategy.

Foundations of factor investing

Factor Investing Foundations
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Six types of attributes are widely accepted as key drivers of returns that can explain outperformance. These include:

  • Value: Stocks with low prices relative to their fundamental value have historically outperformed more expensive stocks.
  • Size: Smaller companies, as measured by market capitalization, have historically outperformed larger companies.
  • Momentum: Strong past performance over the preceding 3 to 12 months tends to lead to outperformance over the following 12 to 24 months.
  • Volatility: Stocks with lower than average volatility have historically outperformed over the long term.
  • Quality: Stocks with strong profitability characteristics have proven to outperform over time.
  • Yield: Stocks with higher than average and growing dividend yields tend to beat stocks with low yields over time.

There are several different metrics that can be used to identify stocks with each of these attributes. In addition, other factors are constantly being identified to find new sources of edge for investors.

Examples of investment factors

Investment Factor Examples
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Some factors are easier and less subjective when it comes to measurement than others. Size, volatility and momentum are straightforward to identify and measure on a relative basis.

Value, quality and yield are more nuanced, and subject to ongoing research. While value has traditionally been measured using price-to-earnings and price-to-book ratios, other measurements are also widely used now.

In particular, the growth in large asset-light tech companies has rendered price-to-book ratios less relevant. As a result, revenue and free cash flow are widely used. Enterprise value is also being used instead of price to give a truer reflection of the market price of a company.

A common measure of value is the CAPE ratio, or cyclically adjusted price earnings ratio. This ratio uses long term, inflation adjusted earnings to remove the effect of economic cycles from a company’s earnings.

Growth
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Quality is also a factor open to interpretation. Commonly used measurements include ROE, earnings stability, dividend growth and balance sheet strength. Some investors also consider accounting policies and corporate governance to fall under quality. There are an infinite number of ways these metrics can be combined to create a quality score, making this one of the more subjective factors.

Yield has traditionally been measured by dividend yield. However, there are other ways a company’s management can improve a stock’s yield. Shareholder yield is a more modern metric that includes share buy backs and debt reduction as well as dividend yield.

Growth and liquidity are not widely regarded as factors that can explain outperformance. However, some investors do include these factors based on their own proprietary research.

ESG investing

ESG Investing Criteria
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A rapidly growing area of the investing landscape is ESG investing, which encompasses environmental, social and corporate governance issues. As it becomes more apparent that companies have a responsibility to a range of stakeholders, more money is flowing into funds that take these factors into consideration. ESG factor investing is a very new area, and a range of factors are being developed to meet demand.

ESG factors vary widely. They can be based on religious or ethical considerations, environmental impact, the way employees are treated, or on corporate governance. These too can be combined in an infinite number of ways, resulting in funds with very different goals. If there is a unifying theme in the ESG investing it may fall under sustainability. This can encompass environmental and ethical factors. The logic is that companies that consider all stakeholders are more likely to endure.

Factors as indicators of risk and return

Risk / Reward Ratio
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Investment factors are typically used to explain outperformance of certain stocks and to select stocks that are expected to generate strong long-term returns. Factors can also be useful for other investing strategies and for asset allocation. Factors can be used to estimate long term returns and volatility for a portfolio of assets. Factor investing strategies can also be used along with hedge funds and other assets to build a portfolio expected to generate long term returns with low volatility.

However, factors can also be used to avoid stocks, sectors and asset classes that carry more risk. This is of importance when it comes to asset allocation and building portfolios to achieve specific investment objectives. Long term investors are as concerned with volatility as they are with returns. Factors can therefore be used to limit volatility, while maximising the expected return for a given level of volatility.

Smart beta strategies seek to reduce risk and volatility by limiting exposure to potentially overvalued stocks. There are numerous smart beta strategies around, but at the core of many is the idea that market capitalization may not be the best way to weight the holdings in a fund.

Advantages and disadvantages of factor investing

Advantages / Disadvantages Factor Investing
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Most of the advantages of factor investing are easy to appreciate. Like other quantitative and evidence-based strategies, factor investing reduces the negatives effects of emotion and subjective factors in investment decisions. Factor based strategies also require fewer analysts to manage than a traditional active investing process. This makes the approach cheaper and ideally suited to passive and semi-passive portfolios.

Investment factors have fairly low correlation with one another. Investing in multiple factors can therefore reduce volatility. Factors can also give investors exposure to stocks that may otherwise be overlooked. The drawbacks of factor investing are a little more difficult to determine. For a start, investors need to realise that factor investing is a long-term investment strategy. Outperformance should not be expected over periods of less than at least a year, preferably even much longer.

Most quantitative strategies attempt to improve on the performance of market cap indices. While back testing often shows impressive results, actual results are often less impressive. The reality is that very few strategies have consistently outperformed their benchmarks with real money. There are several potential reasons for this.

Investing Decision
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The past decade which has been characterised by historically low interest rates has seen many factor funds underperform. At this stage it’s difficult to tell whether this underperformance is temporary or permanent. For anyone investing in a factor investing ETF, it will take a very long time to tell whether the strategy is working or not.

It’s worth noting that many factor funds have not been properly tested by a bear market, or a major change in the market environment. These funds may well outperform during such a period. Another potential problem is that factors with strong historical performance may underperform if too much capital attempts to capture the same underperformance. There is also a real risk that focussing too much on certain factors can result in a portfolio with concentration risk. For this reason, factor investing is best used to compliment other strategies.

Alternatives to factor investing

In time, factor investing may well prove to generate outperformance. However, as indicated it is not without its risks. There are several other ways similar results can be achieved.

Factor Investing Alternatives
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As mentioned, smart beta is a similar approach to factor investing and there is a lot of overlap between the two. When comparing factor investing vs. smart beta investing, the first attempts to capture returns, while the second attempts to avoid risk. Smart beta strategies generally use factors to reduce the risk of market cap weighted funds. They may therefore offer a slightly diluted way to include factors in a portfolio.

Traditional index ETFs are likely to achieve a lot of what factor investing will over time. They may generate slightly lower returns in the long run. But they are almost certain to have higher volatility from time to time.

If the primary goal of a portfolio is to avoid volatility, there are several other ways to achieve that. Diversification across multiple asset classes is the most effective way to reduce volatility. Alternative assets like hedge funds can therefore be added to a core portfolio of index ETFs. Market neutral hedge funds can generate alpha while almost eliminating market risk – which comes with beta. Thus, the overall volatility can be reduced, while returns can be enhanced. Strategies like this can reduce the need for low yielding cash in a portfolio.

Data Intelligence Fund
Data Intelligence Fund managed by Catana Capital

Catana Capital’s Data Intelligence Fund holds long and short positions, making it largely market neutral. Signals are generated using artificial intelligence and big data. The fund combines sentiment scores sourced from user generated data, with price action and other data. This approach to using real time data generates returns with a very low correlation to equity indices.

Another approach is to use robo advisors or target date funds to manage the asset allocation of a portfolio over time. Exposure to more volatile asset classes is then gradually reduced with time.

Conclusion

Factor investing provides another way to approach investing for long term investors. Most factor investing funds are quite new and have not been properly tested yet. This means they are not entirely without risk. Nevertheless, they can still be used as a complimentary strategy to reduce volatility while investing for long term outperformance.

About Richard Bowman
Richard Bowman is a writer at Catana Capital, analyst and investor based in Cape Town, South Africa. He has over 18 years’ experience in asset management, stockbroking, financial media and systematic trading. Richard combines fundamental, quantitative and technical analysis with a dash of common sense.

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