Do value attributes add value?

In one of our earlier blogs, we looked at one of the most mentioned financial metrics, price to earnings ratio, and backtested strategies using the large-cap S&P 500 equity basket. We found that high price to earnings ratio stocks – often regarded as expensive and inherently riskier by financial media – may outperform the benchmark index over long investment periods.

Besides price to earnings ratio, price to book values is another often quoted value attribute, including the seminal quantitative investing research of Fama and French.  In this blog, we examine more closely these value attributes. Specifically, we will backtest and compare four strategies:

1. (High P/E) the highest 100 (relative vs peers) price to earnings ratio

2. (Low P/E) the lowest 100 (relative to peers) price to earnings ratio

3. (High P/B) the highest (relative to peers) price to book value ratio

4. (Low P/B) the lowest (relative to peers) price to book value ratio

For each of these strategies, we choose one hundred stocks from the universe of historical S&P 500 basket at the start of each quarter with the highest (or lowest) price to earnings ratio¹ (or price to book value ratio). We then form relevant portfolios using market cap weights. Using OdinUltra, the no-code specialized financial AI platform developed by Big Data Federation Inc., we can build and evaluate these strategies in minutes with data-driven analytics support.

As a first test, we compared the Low P/E and Low P/B strategies with the large-cap SPDR® Portfolio S&P 500® Value ETF (SPYV) for the period of Nov 2013 to Nov 2023. In the following chart, we show the NAV curves of these three strategies. Note both low P/E and low P/B strategies track SPYV well until recently. From November 2020, the low P/B strategy outperformed while low P/E strategy only started to deviate slightly from SPYV from early March 2023.

How do high P/E or P/B strategies compare with low P/E or P/B strategies? Both high relative price to earnings and price to book value ratio strategy outperformed in total returns, albeit with higher maximum drawdowns in 2022 as the following NAV curves charts show:

High P/E and high P/B strategies have similar performances, and both outperformed the S&P 500 Total Return Index benchmark for this period, while low P/B strategy performed inline and low P/E strategy underperformed:

Detailed risk and performance metrics are available in OdinUltra.

1 Year Bear Market Performance (2022)

In the 2022 bear market scenario, the low P/E and low P/B both outperformed the S&P 500 Total Return Index benchmark with smaller maximum drawdowns. High P/B strategy performed similar to the benchmark, and high P/E strategy had the worse drawdown.

Backtesting these strategies requires our calculation engine to accurately trace the historical S&P 500 composition and identify the correct list of filtered 100 stocks historically. Data cleansing, modeling, and validation are essential parts of the process. Generating the above results can take anywhere from a few hours to several weeks for a typical researcher, depending on data availability and technology infrastructure. With OdinUltra, these tasks can be accomplished with just a few clicks and no-coding. Users can also download position and NAV details for further study from OdinUltra if so desired.

In conclusion, while stocks with low price to earnings ratio or price to book ratios – often regarded as value stocks and inherently less risky by financial media – can outperform the S&P 500 benchmark during short bear markets, for investors with long investment horizon they are better off with high price to earnings or high price to book value stocks.

To learn more about these strategies or to build your own, request a trial at OdinUltra.ai