Price To Tangible Book Value Backtest

I recently reported on the results of my price-to-book ratio backtest. Shortly after running that backtest, I realized that many value investors probably actually prefer using price to tangible book value. The price to tangible book value ratio is simply the current price of the stock divided by the latest quarterly tangible book value per share. Tangible book value  is defined as book value minus goodwill and intangible assets.

Often goodwill and intangible assets end up on a balance sheet as a result of an acquisition, and unfortunately the more a company overpays for an acquisition, the higher those assets (goodwill and intangibles) end up being reported on the balance sheet. The price to tangible book value ratio to some degree overcomes this issue and more closely represents what common shareholders can expect to receive if the firm goes bankrupt and all of its assets are liquidated at their book values.

Let’s see how well the price to tangible book value ratio performs. I used the data and backtesting tool provided by Portfolio123. This backtest uses the same filtered universe of stocks as my recent P/B ratio backtest. I’ve designed the filtering criteria for this backtest specifically for individual investors and with a focus on enhancing data quality. The filters include the following criteria:

  1. No OTC stocks. Stocks not traded on the New York Stock Exchange, NASDAQ, or American Stock Exchange markets are excluded. The quality of fundamental stock data for OTC can be somewhat lower and less timely that that for stocks traded on major exchanges.
  2. No ADRs. Fundamental data for foreign American Depositary Receipt can include errors due to currency exchange, different accounting standards, and share count.
  3. Exclude miscellaneous financial services industry. This is mainly to filter out closed-end funds.
  4. Liquidity test. The average daily total amount traded over the past 60 trading days must be larger than $100,000.  This amount was selected so that a $1 million dollar portfolio could hold 100 positions and that each new $10,000 position would not exceed 10 percent of a day’s trading volume. The liquidity test also ensures that the backtest has reliable market price information for any of the stocks that are being tested.
  5. Market Cap > $50 million. Nano cap stocks are excluded to help improve data quality. This filter also ensures that positions in a modest sized portfolio never exceed one percent of shares outstanding or the available float for a company.
  6. Price > $1. True penny stocks are excluded due to various information issues and manipulation of these stocks.
  7. Price to Tangible Book Ratio > 0. This filter insures we are looking at stocks that actually have price-to-tangible-book value ratio data.

After these filters are applied, we are left with approximately 2,800 to 3,700 stocks. These are then ranked by the criteria being tested; in this case, we are testing the price to tangible book value ratio. The top 20 percent of stocks ranked by  price to tangible book value are placed in the first quintile and the next 20 percent in the second quintile and so forth until we have five portfolios of stocks. The portfolios are rebalanced every 12-months and compounded annually to more realistically replicate what an individual investor might be expected to do to avoid higher short-term capital gains tax and trading costs. To help ensure that the test is not impacted by seasonal or statistical effects, the backtest is also started at four different points during the calendar year.  The results of the quarterly tests are used to calculate the average excess returns for each quintile. The results for the 10-year price to tangible book value ratio backtest are as follows:

Price to Tangible Book Value: Average Excess Returns vs. Universe

Price to Tangible Book Ratio: Rolling 3-Yr Periods Excess Returns vs. Universe

The results are similar to those for the P/B Ratio backtest. The top quintile once again clearly outperformed the market by a significant margin. Moreover, the average excess returns from 2001 to 2011 for the top quintile for price to tangible book value (5.23%) exceed that of the price-to-book ratio (4.89%).  The Sharpe Ratio and Sortino Ratio were also both higher for the 1st quintile of the price to tangible book value versus the P/B ratio. I thought the 5th quintile would also result in lower average excess return for price to tangible book value given that it outperformed in the 1st quintile.  However, the P/B ratio had average excess returns of -3.84% from 2001 to 2011 versus -3.62% for the price to tangible book value ratio.

While I thought the price to tangible book value ratio would be clearly superior to the standard price-to-book ratio, that ended up not being so clear in this backtest.  The only conclusion that could be gleaned from this 10-year backtest is that price to tangible book value might be slightly better at identifying value opportunities than the standard price-to-book ratio for stocks with the lowest price ratios.

One thought on “Price To Tangible Book Value Backtest

  • March 30, 2012 at 11:13 am

    Thanks for this great post. Can you share the numbers for top 1 percentile i.e. what was the performance of the top 25 to 30 stocks based on this filter?

    Thank you.

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