24 Jul 2024 4 min read

Quality explained: is profit a prophet?

By Archimidis Fotopoulos

In the first instalment of a new series on the quality factor, we consider the various definitions and the common denominator that allows investors to access the factor.

Money-stacks.jpg

After more than a decade of strong economic growth, the post-pandemic investment landscape has been characterised by a heightened perception of risk. In an environment vulnerable to inflation spikes and geopolitical conflict, investors may understandably turn to resilient companies, aiming to mitigate the risk of losses and benefit from their long-term value.

Yet while value investing is widely understood both as a longstanding investment strategy and as a factor that can be accessed systematically, quality is more elusive. Despite outperforming value in recent decades,1 quality’s broad and inconsistent definition can be a barrier to access.

In the market today you’ll find varying quality investment strategies, albeit with some common attributes. Since quality is rooted in fundamental analysis, it can typically be derived from financial statement attributes such as profitability, quality of earnings and leverage. This is in addition to secondary characteristics such as low asset growth, which is not as intuitive and is often classified as an anomaly,2 and corporate governance, which is more of a qualitative measure of the robustness of a company.

The common denominator of quality

Although there are many characteristics that comprise the quality factor, there is a common denominator of fundamentals. This can provide systematic exposure to high-quality companies with high profitability, a good capital structure and high repeatability of profitability. Investors can therefore access the historical risk premium attached to quality, which has been established through academic research.3

It’s important to note that not all characteristics extracted from a company’s balance sheet, cash flow and income statement are equally associated with a historical premium. One commonality in all approaches that access the quality premium, however, is profitability, which stems from the idea that consistently profitable companies should outperform the market over the long term.

Although there is no single profitability measure to which the profitability premium can be attributed, the income statement captures all levels of revenues/expenses. As shown in the income statement breakdown below, both top-line and bottom-line profitability measures can be linked to the persistence and the pervasiveness of the quality premium in the long term.4

Quality-factor-part-1-chart-1.png

Following that premise, in most cases there are two classes of profitability measures:

  1. Those based on profitability from investments such as return on equity, return on assets and return on invested capital
  2. Those based on profit margins such as gross profit, operating profit, operating cash flow or net profit margin

The question then arises of how major quality factor strategies in the market today interpret balance sheet items. The charts below summarise the similarities in definitions of the quality factor in the market, showing the frequency of particular terms.5

Quality-factor-part-1-chart-2.png

In the next instalment of this blog we’ll examine the performance of quality strategies in more detail, focusing on the relationship between quality and value.

 

Sources

1. As per LGIM analysis of 2002-2023 performance data.

2. Cooper et al 2008.

3. Asness, Frazzini, Pedersen (2014) Quality Minus Junk.

4. Novy-Marx (2013) The other side of value: The gross profitability premium.

5. Methodology documents of eight index providers & asset managers with definitions on the quality factor. The frequency of each term is calculated as the number of occurrences of the term in the definition of the quality factor over the number of strategies reviewed.

Archimidis Fotopoulos

Index Researcher, Index Solutions

Archimidis is a member of the Index Solutions team, working on systematic index research and strategy. He joined LGIM in 2021, initially working in the Analytics Solutions team. Prior to LGIM, he worked at an Airbus start-up where he developed financial indices for air transportation. He previously worked as a Quantitative Analyst at HSBC and Credit Suisse, and began his career as a Computer Engineer at ARM. Archimidis has an MEng in Electrical & Computer Engineering from the University of Patras, an MSc Microelectronics Systems Design from the University of Southampton, and an MSc in Mathematical Trading & Finance from Bayes Business School (formerly Cass). When he’s not too busy getting degrees, Archimidis enjoys exploring French and Thai cuisine.

Archimidis Fotopoulos