James Murray, Senior Analyst, and Amadeo Alentorn, Head of Systematic Equities, tease out some of the subtleties involved in value investing, and explain why this is important to investors.

 

Value investing has been around for a long time – at least as long as Security Analysis, the famous book by Benjamin Graham and David Dodd, first published in 1934. The overarching philosophy of value investors is to select shares that are cheap relative to the intrinsic value of the underlying companies’ business operations. The value style of investing has come under criticism in recent years and has faced challenging performance. In this note, we provide an overview of our implementation of value investing, as one part of our investment process, and we explain some of the important design decisions we take in our systematic approach.

 

One of our team’s core beliefs is that factor returns are time varying. We believe that over a long horizon, factors tend to generate returns in excess of the risk they take. However, the path is bumpy: individual factors experience periods of both strength and weakness. To cushion against bumps in the road we allocate to a wide and diverse array of factors, and dynamically adjust our allocations depending on the prevailing market environment. 

Recent rotations in value 

To demonstrate the time varying nature of factor returns, we follow academic research in constructing factor portfolios. Every month we split the entire universe of investible stocks into five equally weighted portfolios depending on our proprietary assessment of value. Stocks are ordered from most expensive to cheapest, with the most expensive 20% of stocks placed in portfolio 1, the next 20% of stock are placed in portfolio 2, and so on until portfolio 5 which contains the cheapest 20% of stocks in the investible universe.

 

The black line in the chart below plots the historic performance of buying the portfolio of cheap stocks while short selling the portfolio of expensive stocks, resulting in a market neutral portfolio tracking returns to the value factor. The blue line follows the same approach but ranks stocks using our proprietary quality score and represents the performance of a quality factor.

 

As the full extent of the Covid pandemic became apparent to financial markets in early 2020, the fortunes of both value and quality factors diverged substantially. Cheap stocks struggled relative to their expensive counterparts, resulting in poor performance for a “value” portfolio. On the other hand, high quality stocks performed well during this period, while their low quality counterparts struggled, resulting in an attractive return profile for a “quality” portfolio.

 

On the announcement of positive vaccine news, the converse held true. Expensive and high quality names struggled, and cheap, lower quality names did well. Through the summer of 2021, news of new variants tempered the value factor’s gains, and positive (negative) Covid news benefited (hurt) value relative to quality.

 

This is a very clear illustration of the differing performance of factors across different market environments. It also explains why we rotate between value and quality within our dynamic valuation stock selection criterion: we do this because each of the two sub-components tends to perform well at a different time.

Systematic approach to value investing chart one

Source: Jupiter, as at 31.12.21. Date range Sep 2019-Dec 2021. 

Rotating between factors requires the ability to robustly identify periods of time when a factor will perform well or poorly. The chart below shows our proprietary evaluation of risk appetite, which we use to rotate between the value and quality sub-components of our dynamic valuation stock selection criterion. Here we evaluate the willingness of investors to trade off a unit of risky value for a unit of more expensive, but more certain, future cashflow.

 

As the full impact of the Covid pandemic was becoming apparent, risk appetite fell materially, moving from around 50% to below 20%, according to our measure. We observed that risk appetite remained low for much for 2020, until positive vaccine news caused a material improvement in investors’ willingness to take risk. Risk appetite remained high for the first half of 2021 until news of new Covid variants tempered reopening expectations, putting the environment in a more balanced position. 

Systematic approach to value investing chart two

Source: Jupiter, as at 31.12.21. Date range Sep 2019-Dec 2021. 

Understanding value drivers 

Although we rotate between value and quality, it is more common to hear the terms value and growth being contrasted. To understand why we believe value and quality is a better pairing than value and growth, we need to understand why value investing offers attractive returns. There are two preeminent theories for why value investing should offer strong returns.

 

The first is a behavioural explanation, arguing that cheap stocks are excessively unloved by the market. Investors anchor expectations on past outcomes and over-extrapolate past poor performance into the future. Investors’ expectations for cheap stocks are systematically too low, relative to the set of possible outcomes that cheap companies might achieve.

 

The second argument for the strong long-term performance of value investing makes the case that cheap stocks are riskier than their more expensive counterparts. This view of value argues that additional returns from buying cheap stocks represents compensation for taking additional risk.

 

In contrast to the often polarized arguments found within academia, we find empirical support for both points of view. In our view, some of the returns available from value strategies are due to behavioural biases, while others are driven by additional risk. We believe that understanding the drivers of value returns helps us to design better valuation strategies.

 

To demonstrate both schools of thought, we split the investible universe into five portfolios based on the naive price to book valuation ratio. Stocks are ordered from most expensive to cheapest, with the most expensive 20% of stocks placed in portfolio 1, the next 20% in portfolio 2, and so on until portfolio 5 which contains the cheapest 20% of stocks in the investible universe.

 

The chart below shows the average historic earnings growth of each of these five portfolios. Cheap stocks have typically had poor historic earnings growth, and expensive stocks have had particularly strong historic earnings growth. However, the lower chart also shows that cheap stocks typically beat expectations about their future growth in earnings. Expensive stocks typically underperform future earnings expectations1. Taking the observations together, we can say that cheap stocks tend to have lower actual growth than expensive stocks, but they also have more positive growth surprises than expensive stocks.

 

This suggests that in order to capture the mispriced behavioural component of value, we need to incorporate the future growth prospects of the firm. Our sustainable growth stock selection criterion incorporates measures of value to identify mispriced growth in the market. Value and growth are complements not substitutes. You cannot evaluate one without considering the other.

Book Yield Exposure to Historic EPS Growth

Source: Jupiter, as at 31.12.21. Date range Dec 1994-Dec 2021.

Book Yield Exposure to EPS Growth Beats

The chart below uses the same five portfolios as the chart above, but instead examines average company leverage (that is, the size of a company’s debt in relation to its balance sheet) within each book yield portfolio. (‘Book yield’ here means the equity on the balance sheet, per share, divided by the share price. Cheap companies have a high book yield.) We find evidence supporting the claim that cheap stocks are riskier than expensive stocks. The cheap portfolio carries materially more leverage than the expensive portfolio. 

Book Yield Exposure to Leverage

Systematic approach to value investing chart five

Source: Jupiter, as at 31.12.21. Date range Dec 1994-Dec 2021. 

Understanding which driver of value returns we are attempting to capture is crucial for designing successful value strategies. 

Finding cheap stocks 

Previous work uses price to book as a naive measure of valuation. The line chart below follows the market neutral performance of four different measures of valuation. This chart demonstrates how different measures of valuation have had very different levels of performance. How we assess stock level fundamental value is therefore very important.

 

Valuing a company on the basis of sales or revenues (shown in the blue line) has historically generated strong returns; however, it has also been accompanied by elevated levels of volatility. There are points in time, such as 2008, where performance was materially weaker than alternative measures of assessing value. Valuing a company on the basis of its balance sheet, or book, equity, is a quite different method. Book yield, the silver line in the chart below, has historically experienced lower returns than sales yield, but with lower volatility and lower drawdowns.

 

Assessing fundamental value using sales (income generated over one relatively short period of time) and using book value (an accountant’s view of a company’s net assets), represent opposite extremes of the financial data available to be analysed. In our view, both measures offer a myopic view of the company, and only partially capture the behavioural returns available from a more complete assessment of fundamental value. 

Source: Jupiter, as at 31.12.21. Date range Dec 1994-Dec 2021. 

Instead, we concurrently consider multiple fundamental inputs, including cost management, operating efficiency, and growth expectations, and combine them in an economically motivated way to holistically evaluate the fair value of an asset. 

Seeking value in practice 

The value component of our proprietary dynamic valuation stock selection criterion is considerably more sophisticated than a simple book yield factor. The chart below shows this. Each dot on the scatter plot represents one company in our investible universe at a point in time. The horizontal axis plots the book yield of the company. The vertical axis plots the value component of our dynamic valuation stock selection criterion.

 

The main takeaway is that there is very little relationship between the two measures2. Companies which are cheap on a book yield basis (far right on the horizontal axis) are not necessarily cheap according to our proprietary evaluation of value.

The value component of our dynamic valuation criterion versus book yield  

The value component of our dynamic valuation criterion versus book yield

Source: Jupiter, as at 31.12.21 

Companies in blue. The chart above shows pockets of agreement which are coloured in blue along the main diagonal. The companies shown in blue have a similar value profile, both when using both book yield and when using our proprietary methodology.

 

However, as we move off the main diagonal of the chart, the points move from blue to green to red indicating material differences in agreement between naïve book yield analysis of value and our own approach.

 

Companies in red. The red dots in the bottom right corner are companies which are cheap on a book yield basis, but expensive when using our proprietary valuation process. Conversely, red points in the top left highlight stocks that our approach assesses to be cheap, but which a naive book yield approach would consider expensive. Moving beyond naive valuation techniques results in us holding a materially different set of stocks.

Managing value risk 

Magnifying behavioural biases is just one way to enhance the returns of value. As discussed, part of the outsized returns on offer from value investing is due to cheap stocks being inherently risky. Managing this risk is another avenue for alpha generation.

 

This chart below again has dots corresponding to companies at a point in time. However, we are now plotting the value component of our dynamic valuation stock selection criterion against the quality component of that criterion.

 

The green dots represent companies which are both cheap and high quality and so are particularly attractive to buy. The red dots represent companies which are both expensive and low quality, being particularly unattractive to buy, or attractive to short sell (depending on the fund mandate – we manage both long-short and long-only funds).

 

However, there are many stocks that are reasonably priced along these two dimensions. The blue companies are either cheap and low quality, or expensive and high quality. It shows the tendency for value and quality to be negatively related.

 

Following our assessment of risk appetite, we manage the risk in value through selectively tilting towards quality in times of fear, and by tilting towards value in times of greed. Unlike value and growth, value and quality are substitutes. They perform well at opposite times and many stocks can be categorised as cheap and low quality, or expensive and high quality.

The value versus the quality components of our dynamic valuation criterion 

The value versus the quality components of our dynamic valuation criterion

Source: Jupiter, as at 31.12.21 

A dynamic model 

Then end result is a dynamic model, based on the understanding that to collect the alpha available due to behavioural mispricing in value, you also need to have exposure to some risk. We manage our exposure to this risk by dynamically moving to quality according to our evaluation of risk appetite.

 

The long run simulated performance of the two components of our dynamic valuation stock selection criterion (value and quality) is shown in the line chart below in black and blue respectively. They both have positive returns over a long-time horizon but perform well in different periods.

 

The third, silver line, incorporates dynamic rotation between the two components, demonstrating both enhanced returns and reduced risk. 

Systematic approach to value investing chart five

Source: Jupiter, as at 31.12.21. Date range Dec 1994-Dec 2021. 

Past performance is simulated and no guide to future performance. The data shown represents the total returns for hypothetical portfolios. The chart is for illustrative purposes only. It does not represent actual performance of any Jupiter fund or strategy, and is not indicative of future results.