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Quant Investing: Is It Time To Get Rid Of Price/Book?


The performance of value factors varies over time. Sometimes value is in favor. Sometimes it is out of favor. But overall, value is one of the two single factors, along with momentum, that has withstood the test of time. But what if one way of expressing value in stocks has simply stopped working, or is just nor working as well as in the past? That’s is what I’ll consider in this brief post. In particular, I’ll look at whether it is still worthwhile to use P/B in individual quant stock portfolios.

Many of the quant stock models discussed on the blog use a composite of value factors to find the best value stocks. One of the factors is Price-to-Book, probably the oldest and most used of the value factors. It is well documented that Price-to-Book is not as effective as it used to be. One way to look at the effectiveness of value factors is to rank stocks by a certain factor and then look at the spread between the most expensive and cheapest stocks. For example, the charts below show the spread between the cheapest and most expensive stocks for three value factors (see this OSAM paper for details).

A narrower spread between the cheapest and most expensive stocks means lower performance for the value factor. The chart below shows rolling excess returns for the value factors above.

Something changed in the 1999-2000 downturn. Price-to-Book ceased to match the effectiveness of the other value factors. Great. Let’s dump Price to Book from the value composite and be done with it. Sounds like a good plan. Let’s see how that works out in various quant portfolios.

I created a new value composite that eliminates P/B and compared it to the original VC2 in the VC2 Value portfolio, the Utilities Value portfolio, and the Trending Value portfolio. I calculated returns of the portfolios in Portfolio123 from 1999 through 2016. A lucky coincidence is that the earlier Portfolio123 backtest data happens to align with the time Price-to-Book started underperforming. All portfolios consist of 25 stocks and a 1-year holding period as usual. Below are the results of the various backtests I performed, with the best-performing portfolio highlighted in green.

Hmm. Not as straightforward as you would expect. As originally constructed, the returns are higher for portfolios formed with the value composite that does not contain Price-to-Book as a factor. This confirms what the graphs above told us. But a few things to note. One, the outperformance is not as high as you might expect. The analysis presented above is for large-cap stocks. whereas the quant portfolios are run using the All Stocks universe. The inclusion of small-caps changes things a bit. Also, the quant portfolios are equal-weighted instead of market cap-weighted, which also seems to influence the results.

Most importantly, real-world portfolios usually combine other factors that, when combined with value, may influence the performance of value. For example, many of the quant portfolios I present here use some quality factor to either improve returns and/or reduce drawdowns. In the table above, you see the strategies implemented with a quality metric, and then run with and without Price-to-Book in the value composite. These results change the conclusion. When quality is incorporated into the portfolios, Price-to-Book is still quite effective in two of the three portfolios, with only a very slight advantage in the Utilities Value portfolio. Maybe we shouldn’t be too quick to throw our Price-to-Book?

In summary, based on the recent performance of Price-to-Book as a single factor, it makes sense to discard it in quant portfolios. However, when combined with other factors, the decision is not so clear. You need to run through the analysis in your own portfolios. For mine, I will continue to use Price-to-Book in the VC2 Value portfolio and the Trending Value portfolio. On the next rebalance of the Utilities Value portfolio, I will switch to using the value composite without Price-to-Book.

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