THE R&D EDGE

By Shiv Patel , VP ETF Product Development

Numerous studies have been published over the decades concluding that, on average, firms with high and/or increasing research and development (R&D) expenditures go on to experience abnormal future positive returns. If this is a well- known outcome, then why does an ‘R&D edge’ persist? Two possible explanations may shed light on this phenomenon.

A Behavioral Bias Explanation

Consider two identical companies within a shared industry: Company A and Company B.

Company A has a growth mindset and has been utilizing its cash flow and/or taking on debt to subsidize its R&D initiatives. This has the potential to significantly reduce earnings (and consequently the stock price) of Company A – even though such expenditures represent a long-term investment expected to generate future revenue and cash flow.

Company B has a more conservative mindset (reflected in its budget and spending) and continues to do what has worked in the past opting instead to ‘let the market speak’ as to the direction of their product focus efforts.

Presented with only these two options, investors typically will favor Company B. Why? Because on paper Company B shows better fundamentals with more cash, higher profitability and/or little to no debt. It is the proverbial ‘A Bird in Hand is Worth More Than 10 in the Bushes’.

Now fast forward 5 years.

Company A, having spent heavily on R&D and taking more time to gain momentum, is finally seeing the payoff with tremendous growth in sales and profitability. Investors see this and flock to Company A’s stock. By contrast, Company B, deemed the better investment five years ago, is seeing sales stall while experiencing decreased revenue, and a steady decline in stock price.

The Behavioral Bias explanation purports that these types of mispricing or pricing anomalies occur because investors tend to underestimate and undervalue the future earning potential for companies with increased R&D spending. R&D is considered an intangible asset and that is often overlooked despite being vital to a company’s success (think skilled workers, patents, brand equity, reputation). Yet, when R&D expenditures finally become profitable and is generating abnormal positive returns, the market corrects the mispricing.

A Risk-Based Explanation

Those who lean toward a risk-based explanation say no. The risk-based explanation asserts that investors suspect the increased R&D spending may not pay off, if ever. Millions spent now could return out-sized gains in the future or could be a total loss if the R&D is unfruitful or abandoned. The market is believed to price in this risk by valuing the company at a discount to their steadier peers. Thus, companies with high R&D spending can be likened to gold exploration companies – maybe they will hit the jackpot and find gold or maybe they will find nothing. Still too, in an effort to mitigate this risk, some investors may allocate across numerous high R&D spending companies with the expectation that at least some of them will see their research come to fruition.

Another risk-based explanation for the R&D premium is due to the increased risk of abnormal drawdowns. Investors are generally compensated with higher returns in bull markets for the greater potential for losses in bear markets. After all, the future benefits of R&D spend is extremely uncertain and unpredictable and high R&D firms are generally associated with high-growth firms trading at higher multiples.

But is outperformance associated with R&D a free lunch?

R&D Outperformance in the S&P 500

So just how much outperformance can R&D unlock? To test, let us use the S&P 500 Index universe (no survivorship bias). We will retain any stock that has positive R&D over the trailing 12 months, which eliminates as much as two-thirds of the index. Next, we create 5 separate portfolios based on the ratio of R&D spending to market cap (Portfolio 1 = lowest ratio; Portfolio 5 = highest ratio). Since 1999, the portfolio with the highest R&D ratio has outperformed SPDR S&P ETF (SPY) by 10% annually. The portfolio with the lowest ratio has underperformed the benchmark by roughly 2% annually (See Exhibit 2 below).

EXHIBIT 2: Performance of Companies with Various R&D Spends (1/2/1999 - 4/20/2024

Conclusion

In summary, whether the R&D premium is due to investors undervaluing large amounts of spending or the increased risk of loss, the edge continues to persist. Interestingly, and as noted in the paper “R&D Premium: The Intangible Side of Value,” combining an R&D portfolio with a value portfolio has the potential to provide an effective counterbalance to the risks associated with an R&D strategy. This combination has historically resulted in an increase in the Sharpe Ratio and a decrease in the maximum draw-down relative to the high R&D portfolio alone. Given these dynamics, we believe investors wanting to gain exposure to this potential outperformance can do so while also lowering risk through a complementary value portfolio.

To learn more about AAM ETFs, contact your financial professional or visit www.aamlive.com/ETF or call us at 1.866.606.7220.

1. Zvi Griliches (Market value, R and D, and patents) Economics Letters (1981)

2. Li, CaiRicky, CooperDi He (R&D Premium: The Intangible Side of Value) The Journal of Investing (01 August 2023)

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Definitions: S&P 500 Index (SPXT) is an unmanaged market capitalization weighted index used to measure 500 companies chosen for market size, liquidity and industry grouping, among other factors. Pearson Correlation Coefficient is a statistical measure that evaluates the strength and direction of the relationship between two continuous variables. Sharpe Ratio is a measure of excess portfolio return over the risk-free rate relative to its standard deviation. Spearman’s rank correlation coefficient is often denoted by ρ, is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables). Survivorship Bias is a type of sample selection bias that occurs when a data set only considers “surviving” or existing observations and fails to consider observations that already ceased to exist.

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