CPD: Factor investing in action, across regions, cycles and asset classes


Factor investing is underpinned by the premise that the performance of a portfolio is often largely attributable to the presence of one or more observable ‘factors’ or characteristics, rather than the skill of the individual fund manager.

In article one of this two-part series Factor investing – an introduction[1], we introduced the concept of factor investing, exploring its origins and academic basis, the nature of commonly used factors, and the various ways investors can access factor-based strategies.

In this second part we take a more in-depth look at factor investing in action, exploring the effectiveness of factor strategies across regions, asset classes and business cycles. We also examine the shortcomings of ‘generic’ factor approaches and consider optimal ways to ‘combine and harvest’ factor premia.

Factor investing – a brief recap

Factor investing is underpinned by the premise that the performance of a portfolio is often largely attributable to the presence of one or more observable ‘factors’ or characteristics, rather than the skill of the individual fund manager. Examples of these factors – known as factor premia – include Low Volatility, Value, Quality, and Momentum.

As well as its extensive academic grounding, the effectiveness of factor investing is supported by overwhelming quantitative evidence, and as a result, factor investing continues to grow in popularity, accounting for more than USD 1.5 trillion in invested assets[2], and experiencing an average growth rate of 17% per annum since 2010.

Factor performance – a deeper dive

The increasing popularity of factor strategies is driven largely by the strong body of evidence around the historical outperformance of factors, relative to the market. Of course, not all factors are created equally, and nor do they perform in the same way at the same time. Unlocking the power of factor investing necessitates more understanding of how factors have performed across different business cycles and market phases. To help illustrate this, Figure 1 depicts the performance of five widely accepted factors over the last 20 years[3], whilst Figure 2, identifies which factors tend to excel across different phases of the economic cycle, as defined by the rate of economic growth[4].




During times of economic recovery – characterised by weak or accelerating growth – smaller, more agile companies tend to perform better, as do Value stocks that are already trading at a discount.

As would be expected, Momentum strategies have excelled during long running bull markets (as can be seen from 2009 onwards in Figure 1) but have tended to lose some of their lustre in recessions.

Quality stocks with stronger balance sheets – more defensive in nature – have tended to perform best at the peak of an economic cycle, when growth is strong but decelerating, or at the very beginning of a slowdown.

Once in the midst of a crisis/recession, Quality and Low Volatility factor strategies have worked particularly well.

Another key concept in comparing factor performance in different economic regimes is the ‘spread’ between high and low relative performance. In this context, spread can serve as a quantitative proxy for an active managers’ ability to generate excess return by deviating from the market.

Typically, as economic growth takes hold and consumer confidence rises (represented by the recovery phase seen in Figure 2), the market places less emphasis on differentiation between managers and stocks, and the ‘spread’ tends to get smaller. A rising tide lifts all boats, as the saying goes. Conversely, in difficult times when market returns are on average negative or the future is uncertain, the ability to generate positive return is predicated on an investor’s skill of choosing wisely, and spreads tend to expand.

This tendency for Factor spreads to expand in and around recessions, suggests there is greater potential for disciplined active managers to deliver outperformance during those periods.

COVID 19 and Factor Investing

Discussion of any aspect of investment strategy would clearly be incomplete if it failed to acknowledge the impact of the COVID 19 wrecking ball on economies around the world.

Whilst the different status of the virus in different countries makes it hard to assess the short term outlook for economic recovery, and the recent resurgence in markets – unsupported by fundamentals – is downright confusing, factor performances in the lead up to, and following the declaration of, the COVID 19 pandemic, unsurprisingly exhibited an overwhelming desire for safety, and the avoidance of specific sectors (e.g. consumer discretionary, financials).

Amid the widespread losses since equity markets peaked in mid-February, defensive Quality and Low Volatility factors have strongly outperformed riskier Value and Size, accelerating trends in place for the past 12 months. This is shown[5] in Figure 3.



To the extent that so many aspects of COVID 19 are unprecedented, it is clearly too early to say, with any confidence, whether factor performances will behave as they have on the road out of previous recessions.

Factor performance in Australia and across regions

Different markets with different structures, economies, and populations tend to support the performance of different factors. Figure 4 shows[6] how different these returns can be. Size, Value, and Momentum all work to some extent in the US (the source of much factor research), but this is not the case for other markets around the world. In Germany, for example, Size has returned -5% annually since 1987, whereas in Japan, Value has been the best performing factor.



In Australia, Momentum and Value stocks have excelled.

Several experts have observed[7] how Australian factors don’t necessarily behave like the rest of the developed world, and there are several possible explanations for this, including the fact that our equity market is relatively more concentrated (the largest stock in the ASX 300 accounting for a much higher proportion of total index value than seen in other markets), the tendency of Australian companies to pay higher dividends and our higher weighting towards financials.

Macro-economic effects, such as commodity prices and the acceleration of GDP growth in China, are also likely to have a bigger impact on Australian equities than other equity markets.

Factor definitions – when simpler does not equal better

Simplistic factor definitions typically used in generic factor strategies may be suboptimal if they lead to significant exposures to unrewarded risks. In this regard, efficiently capturing factor premia requires robust, enhanced factor definitions which address potential issues.

The Value factor, for example, is premised on the tendency of inexpensive securities, relative to their fundamentals, to outperform over the longer term. The pitfall in an overly simplistic approach here is that some ‘cheap’ stocks may be cheap for very good reason.

Whilst prominent academics, such as Fama and French, have argued[8] that the

Value premium is a compensation for risk, in particular distress risk, research by Robeco9 found no such linkage, arguing that it is not necessary to take on distress risk to profit from the Value premium. Figure 5 illustrates clearly that high-risk Value stocks identified using different measures of distress risk, do not achieve higher returns than low-risk Value stocks.



While conventional Value strategies are typically exposed to distress risk, Robeco’s research findings prove it is therefore possible to design a value strategy that explicitly avoids financially distressed firms. In other words, that avoids buying stocks that are cheap for good reasons.

Similarly, the Momentum premium is one of the largest factor premia, but its sensitivity to market reversals and high turnover are two well-known issues that can challenge the implementation of an efficient strategy. A focus on stock-specific momentum can considerably reduce the general market reversal risk seen in conventional Momentum strategies, whilst tempered trading patterns can help contain costs.

Generic Low Volatility strategies are often based on a single backward-looking historical risk measure, such as volatility or beta. This construction, however, may expose the strategy to some pitfalls, such as miscalculated downside risk. Not all Low Volatility stocks are equal and some are destined to perform better than others. This is especially true when they become expensive.

A more sophisticated approach can overcome these issues, by taking a multi-dimensional view of risk. This means using several low-risk variables, that include both long- and short-term statistical data. This also means taking into account backward- and forward-looking measures of risk[10], such as changes in a company’s capital structure or credit default indicators.

These elements have a more forward-looking nature and helps to avoid investing in companies that have a high probability of going into default. For example, Figure 6 shows how distance-to-default, a measure of distress risk, was a much better predictor of Lehman Brothers’ problems in the run-up to its bankruptcy than its stock’s three-year volatility.



An oft-cited downside with generic Quality strategies is their use of use poor definitions. Traditional industry Quality measures such as earnings growth and stability and ROE have actually been shown to have weak or no predictive power. More academic-based Quality definitions tend to be more multi-dimensional, incorporating governance and management indicators as well as earnings quality measures.

Factor strategies work in credit markets too

Whilst most of the focus, activity, and research relating to factor investing relates to its application in equity markets factors, the rationale behind the ‘core’ investment factors are not asset class specific, and factors have also been observed in credit markets, currency markets, commodities and even real estate. Figure 7 illustrates the outperformance of factors in credit markets between 1994 and 2017.



There is increasing interest in applying factor strategies to credit markets, undoubtedly spurred on by the results achieved in equity markets, and the growing body of academic work in this area. One example of such work is ground-breaking paper ‘Factor Investing in the Corporate Bond Market’ by Patrick Houweling and Jeroen van Zundert[11]. Their paper reports extensive empirical evidence that factors similar to those used in equity markets generate economically meaningful and statistically significant alphas in the corporate bond market.

Notwithstanding this evidence, the use of a factor-based approach in credit markets is not without challenges.

When it comes to government and corporate bond indices, for example, high index weightings are assigned to the most highly indebted countries and companies, meaning investments made in line with market capitalisation will be disproportionately invested in issuers with the highest debt burden (as opposed to those with the best ability to repay).

Furthermore, credit indices can be less balanced than equity indices, with many global government bond indices having a strong US and Japanese bias, while many corporate bond indices primarily contain bonds from the financial sector.

How to efficiently harvest factor benefits

Whilst our earlier article[12] noted the incremental lift in portfolio performance when multiple factors were used – as opposed to single factor strategies – there are certainly circumstances where a single factor approach is appropriate. One example is the incorporation of a single factor into an existing portfolio to achieve a specific goal, such as lowering volatility.

Regardless of whether a strategy is based on single or multiple factors, it is critical to understand the cross-relationships – positive and negative – that may exist between some factors at various times. For example, a Low Volatility strategy may have a negative relationship with Value where such stocks are expensive. Similarly, a Quality stock can have reverse momentum.

Efficient factor strategies are designed in such a way that premia do not clash with each other. Combining factors in a portfolio needs to reflect these potential factor cross-effects, and take a more holistic approach, likely reflected in more dynamic, tailored weighting of factors within a portfolio, rather than a more equal, simplistic, ‘naïve’ weighting. Figure 8 illustrates the extent to which more holistic – less naïve – approach to combining factors can improve the prospects for a portfolio to outperform13, as well as highlighting typical cross factor relationships.



A word about ESG

Growing demand for sustainable investment solutions means asset managers are increasingly expected to take ESG criteria into account in their investment processes, without sacrificing returns.

Factor-based strategies are particularly suitable for smart sustainability integration.

Their rules-based nature makes it relatively easy to integrate additional quantifiable variables in the security selection and portfolio construction process. From this perspective, a factor-based approach that integrates sustainability aspects in the investment methodology is not very different from a standard factor-based approach, where securities are included in a portfolio solely based on their factor characteristics.


The popularity of factor investing continues to grow, driven by sustained outperformance relative to market, and a growing body of academic research proving its effectiveness.

However, harvesting the benefits of factor premia is not without its challenges, and investors need to take into account complex cross relationships between individual factors, and differences in factor behaviour observed across different economic and market cycles, different regions and different asset classes.

The optimisation of a factor-based strategy is also reliant on the robustness of the factor definitions used, and in this respect, investors should be wary of the pitfalls inherent in the simplistic definitions used by many generic factor products.

Rather than sounding a death knell for active management, the imperative to ensure a more integrated, dynamic and comprehensive approach to designing and executing factor strategies suggests there is more opportunity – and indeed more need – for active managers to clearly differentiate themselves from mere factor providers.

There are many different ways investors can access factor investment strategies. Understanding the complexities involved in optimising a factor-based approach and appreciating the benefits and pitfalls of the many options available in the market, will leave Financial Advisers better equipped to help their clients achieve their investment and lifestyle goals.


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Read Part one: CPD: Factor investing – an introduction


1. https://www.adviservoice.com.au/2020/06/cpd-factor-investing-an-introduction/
2. Morningstar, Hedge Fund Research (HFR), Morgan Stanley ETF trading desk, Morgan Stanley Research, morganstanley.com/ideas/quant-fundamental
3. ‘Foundational Concepts for Understanding Factor Investing’, B. Warren & S. Quance, invesco.com
4. ‘Where are the factors?’, H. Fremsted, blackrock.com, December 2019.
5. ‘Factors in Focus: Risk sentiment and factor dynamics in a crisis’, H.D. Varsani, W. Virgaonkar, R. Mendiratta, MSCI.com, April 2020.
6. ‘Indexing and Factor Investing’,com.au, February 2018.
7. ‘Australia the odd man out in factor investing’, Michael Hunstad, Investor Strategy News, ioandc.com, August 2015.
8. ‘The cross section of expected stock returns’, E. Fama and K. French, The Journal of Finance, June, 1992.
9. ‘Are the Fama-French factors really a compensation for distress risk?’, W.de Groot and J. Huij, Journal of International Money and Finance, September 2018.
10. ‘How distress risk improves low-volatility strategies: lessons learned since 2006’, J. Huij, P. van Vliet, W. Zhou and W. de Groot, Robeco Research Paper, 2012.
11. ‘Factor Investing in the Corporate Bond Market’, Houweling and J. van Zundert, Financial Analysts Journal, Vol 73, No. 2, 2017.
12. https://www.adviservoice.com.au/2020/06/cpd-factor-investing-an-introduction/
13. ‘Foundational Concepts for Understanding Factor Investing’, B. Warren & S. Quance, invesco.com

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