The worst strategy that you could have adopted was to buy last year's losers each year. The message is clear - losers carried on being losers. Sometimes the weak beats the strong, but it's not the way to bet your money.
The next ten worst strategies involved buying Companies on high multiples such as high price to sales ratio companies. These companies were generally on high multiples because they were thought to be high growth or sexy companies with lots of potential. They were the then current stock market darlings that investors were prepared to pay up for in order to join in with the latest investment fad or fashion.
As far as the best performing strategies are concerned, he found that the top 6 strategies all involved buying companies with high relative strength in combination with a value factor such as low p/e or low price to sales ratio. These companies were generally on low multiples because they were in out of favour sectors or old economy share that had been overlooked. By combining it with high relative strength (i.e. shares which were rising), these strategies caught those shares whose under-valuation was finally starting to be recognised by the market.
The book found that over long periods, adopting the following rules would have proved to be more profitable than buying the S&P 500: Low price to sales stocks out-perform the higher p/s stocks. Low price to cash flow stocks do better than high p/cfl stocks. Low price to book stocks tend to perform better than high p/b stocks. Other conclusions reached in the book are as follows: Price to sales ratio is the best single value ratio to use for buying market beating stocks. Last years biggest losers are the worst stocks you can buy. Last years earnings gains alone are worthless when determining if a stock is a good investment. You can do four times as well as the S&P 500 by concentrating on large well known stocks with high dividend yields. Relative strength is the only growth variable that consistently beats the market.
Buying Wall Street's current darlings with the highest price to earnings ratios is one of the worst things you can do.
Other lines from the book: Growth investors believe in a Company's potential and think a stock's price will rise with its earnings.
Value investors believe in a company's balance sheet, thinking a stock's price will eventually rise to meet its intrinsic value.
The S&P 500 tracker strategy is a strategy making disciplined bets on large cap companies. This strategy is just one of hundreds of strategies which could exist. For example another strategy might be to measure the performance of all stocks that begin with the letters h,l,m,n, and p. There are many other strategies which have given higher returns in the past than the S&P 500 strategy, some for no logical reason, others with a certain logic. Examples of logical strategies include a disciplined small cap strategy, or a disciplined low price to sales strategy or a disciplined high yield strategy etc. Some of those strategies also performed more consistently than the S&P 500 strategy, ie with less risk.
For example if in the 1950s the editors at Dow Jones had decided to revamp the index buying the 50 stocks with the lowest price to sales ratio, then the Dow Jones Industrial Index would be at 4 times the level of today.
People want to believe the present is different from the past. The price of a stock is still determined by people. As long as people let fear, greed, hope and ignorance cloud their judgement they will continue to mis-price stocks and provide opportunities to those who rigorously use simple time tested strategies to pick stocks. Names change, industries change. Styles come in and out of fashion, but the underlying characteristics that identify a good or bad investment remain the same.
What the author does is use year-end prices covering 45 years to "prove" all sorts of useless things about various simple strategies centering around value investing. Forty-five data points, whether it be daily data or yearly data, is not enough (by more than at least a factor of ten!) to reach any significant conclusion about anything such as the financial markets, where any signal present is swamped by noise. But O'Shaughnessy is quite tickled that he's proven all the experts wrong with his measly sample.
What's even worse is that the spuriousness of his "profound" results is right there staring him in his face: he frequently comes up with numbers like 14.59%, with a standard deviation of 23.24% -- not realizing that this means the real answer is likely anywhere between -8.65% and +37.83%; in other words, it's consistent with a 0% return for that particular strategy. To compound the folly, O'Shaughnessy then goes on to continually draw conclusions based on differences of a few percent or less (a small fraction of the standard deviation) between competing strategies, not realizing that this is utterly meaningless.
On top of these fatal flaws, O'Shaughnessy also commits the most common sin of model testing: he fails to forward-test his strategy on data which the model hasn't yet seen. This just about guarantees that future results will disappoint, as indeed has been the case the last several years with the mutual funds which he launched based on the ideas in this book after its first edition.
I give it 1 1/2 - 2 stars because even a crummy strategy is better than none at all.
Now if I were you I'd just go to the library and check out the book since only the results are really the important part of the book.
Reed Floren