The majority of a firm’s assets, such as inventories or equipment, are physical, and their value can be easily recorded into the books. On the other hand, the firm also owns assets like workforce skill or production methods that are less tangible and have uncertain value. One of the aptest examples of such intangible assets are expenditures on Research & Development.
One of the research papers investigating whether the market appropriately accounts for firms’ expenditures on R&D has been conducted by Chan et al. (1999). In this research, the authors have found that two similar firms, one with significant R&D expenditures and the other with absent R&D, might appear to be equally expensive when considering traditional measures such as price-to-earnings or price-to-book ratios. However, the market tends to underestimate the future opportunities associated with the first firm’s R&D spending relative to the growth opportunities of the second. Simply relating the amount of the past 5 years’ R&D expenditures to the firm’s market equity value, the researchers show that stocks of firms with a high amount of R&D expenditures relative to their Market cap earn greater average returns in the future.

Fundamental reason

Under the efficient market hypothesis, the investor should be able to recognize the value of less-tangible assets. However, in conditions of an inefficient market, the presence of such intangible assets could possibly lead to mispricing. One of the reasons for possible mispricing lies in the US GAAP and IFRS accounting standards. Under these standards, the costs of R&D must be expensed in the same fiscal year as they occur and therefore could significantly influence the reported earnings of a company in the current year. However, the R&D expenditures usually represent a long-term investment that implies a possible future revenue and cash flow.

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Markets Traded
equities

Backtest period from source paper
2003-2020

Confidence in anomaly's validity
Strong

Indicative Performance
4.67%

Notes to Confidence in Anomaly's Validity

Notes to Indicative Performance

The backtested performance of the paper is substituted by our more recent backtest in Quantconnect.


Period of Rebalancing
Yearly

Estimated Volatility
8.2%

Notes to Period of Rebalancing

Notes to Estimated Volatility

The backtested volatility of the paper is substituted by our more recent backtest in Quantconnect.


Number of Traded Instruments
1000

Maximum Drawdown
-39.3%

Notes to Number of Traded Instruments

NYSE, NASDAQ and AMEX stocks. The exact number of traded instruments depends on individual needs for diversification.


Notes to Maximum drawdown

The backtested maximal drawdown of the paper is substituted by our more recent backtest in Quantconnect.


Complexity Evaluation
Simple strategy

Sharpe Ratio
0.51

Notes to Complexity Evaluation

Region
United States

Financial instruments
stocks

Simple trading strategy

The investment universe consists of stocks that are listed on NYSE NASDAQ or AMEX. At the end of April, for each stock in the universe, calculate a measure of total R&D expenditures in the past 5 years scaled by the firm’s Market cap (defined on page 7, eq. 1). Go long (short) on the quintile of firms with the highest (lowest) R&D expenditures relative to their Market Cap. Weight the portfolio equally and rebalance next year. The backtested performance of the paper is substituted by our more recent backtest in Quantconnect.

Hedge for stocks during bear markets

No - Although the strategy has a low beta of 0.006, the strategy suffers during bearmarkets.

Source paper
Out-of-sample strategy's implementation/validation in QuantConnect's framework (chart+statistics+code)
Other papers

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