July 11th, 2014
But how reliable are these sorts of claims? Those promoting the approach offer lists of stocks that are considered undervalued typically when they meet such financial criteria as low price/sales, low price/book value, or high, stable and growing dividends. However, they rarely attach timeframes or price targets.
So I decided to do some “back testing”. By searching the term “value stock lists”, I gathered a small random sample of such lists published in 2012-13; stocks in these lists met one or more of criteria that qualifies them as “value stocks” at the time. I then compared their stock price on the publication date with that of twelve months later; as a benchmark, those changes were compared with against the S&P 500 change over the same period. These were selected at random and space limitations prevented including more, I suspect others would show similar results:
- MagicDiligence.com: “Top 10 Dividend Yields, Lowest P/S, and Lowest P/B Stocks” – 1/5/2012: “Every so often, MagicDiligence compiles a list of Magic Formula® Investing stocks sorted by their dividend yield, price-to-sales ratio, and price-to-book ratio for investors that like to use those metrics. The result produces a list of attractive value stocks for additional research.” The top 10 in each of the three metrics were:
- Valueline: “Value Line’s 6 Safe Dividend Stocks” – 11/22/12 : “Value Line is an independent investment research and analysis company that has developed a safety ranking methodology which focuses on the long-term stability of company’s stock price and financial standing. The fund invests in companies that carry Value Line’s ratings of 1 and 2, representing the most stable and financially-sound dividend-paying companies and higher-than-average dividend yield, as compared to the indicated dividend yield of the S&P 500 Composite Stock Price Index.” The top picks were:
- Forbes: “Return To Value Stocks: Cisco And Three Others To Buy” – 10/7/13 : “At ValuEngine.com we show that 77% of all stocks are overvalued, 40.8% by 20% or more. 15 of 16 sectors are overvalued 13 by double-digit percentages, seven by more than 20%. This week there are four Dow components on this week’s ValuTrader watch list.” The list included:
- SeekingAlpha: “12 Large-Cap Stocks Selling Below Book Value” : “Price-to-book ratio is used to compare a stock’s market value to its book value and it is calculated by dividing the stock price by the book value per share. The higher the price-to-book ratio, the higher the premium the market is willing to pay for the company above its assets. A low price-to-book ratio may signal a good investment opportunity, as book value is an accounting number and rarely represents the true value of the company.”
- 24/7 Wall St.: “Value Search: Dirt Cheap Tech Stocks” – 7/10/10:…” when you get companies that trade under 10-times believable forward earnings expectations and which have low multiples of sales and even a low implied book value, this is where value investors tend to focus. Whether a turnaround comes or not might not even matter if stocks get “cheap enough” for the value investors.”
The hit rate (performance exceeding that of the benchmark S&P 500 Index) of the 60 stocks for this random sample of five lists was 50%, not much better than randomly selecting 60 stocks from any or combination of the major Indexes.
We’re continually subjected to academic studies purporting to show the failure of technical analysis. For example, Stockopedia had a piece entitled “Technical Analysis? 5 Reasons To be Sceptical about Charting in which they quoted an academic study that back tested the effectiveness of “5000 technical trading rules” grouped into four categories:
- Filter Rules – prices move of various percentages.
- Moving Average Rules – prices move above or below a long moving average
- Channel Break-outs – prices move above or below a channel (trading range)
- Support or Resistance Rules – prices move a certain percentage above or below a maximum or minimum price a number of periods back.
;The study concluded that “no evidence that the profits to the technical trading rules we consider are greater than those that might be expected due to random data variation.”
I’ve now turn the tables and measured the effectiveness of some fundamental trading rules. Although perhaps subject to criticism for being insufficiently rigorous, I convinces me that there is “no evidence that the profits to the fundamental trading rules are greater than those that might be expected due to random data variation“.