The graph above shows a clear connection between a leading indicator and future stock returns. That leading indicator is not related to anything technical analysts measure, and there’s a twist in the data that reveals everything that is wrong with technical analysis and day-trading.
I set out on this project a few days ago to test whether the market is truly random (as efficient market theorists contend). I was able to demonstrate that the market is not totally random, and then I sought to find whether chart-based (technical) analysis of price changes might bear fruit as a practical investment strategy.
In the last article, I demonstrated that the stock market, when taken as a whole, is not completely random, but changes in stock price are random enough that it would be hard to make much money off any patterns that may exist. Yesterday I looked at individual stocks to see if price fluctuations followed any monetizable pattern.
The most surprising thing I found is that, for certain periods of time, individual stocks do exhibit a pattern (say, investors are more likely to purchase a stock following a down day), but those patterns can change at any time, without warning. Also, those patterns do not apply to all stocks, but only to a majority of stocks. As a day trader, you’re basically betting that you’re smart enough to pick the stocks that will follow the pattern, and you’re also smart enough to pull your money out of the market before the pattern changes.
If we’re able to dismiss the efficient market theory on the one hand, and the usefulness of price patterns on the other, are we also able to dismiss any attempt to beat the market? Luckily for us, the answer is no. As the above graph demonstrates, there is a clear correlation between Price to Earning ratios and future returns so long as (here’s the twist) investors are in for the long-haul.
This graph is the work of the Yale economist Robert Shiller, who has demonstrated that, over the long-run, the fundamental value of a company (even if it is measured by the crude yardstick of the price to earnings ratio) exerts a pull on the price of the stock. Shiller also warns that this rule may break down if investors put their money in the market at a time when PE ratios are high across the board, so you should be wary of stocks when the market is over-valued.
Happily, the present stock market is not overvalued historically (March PE ratio of the market was 13 relative to the historic average of 16). Graham and Dodd, it appears, are alive and well.
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2 Comments
One year’s earnings performance relative to the market perception of that performance correlates with returns over the next twenty? Returns on what? It looks from the chart that the higher the P/E correlates with lower returns. Am I reading that right?
Sorry, I should have provided a little more background on the Shiller study. You read the graph correctly, Stephen, high PE correlates to lower returns, but the data are phase shifted ten years. So what this says is that a basket of low PE stocks will perform better than the general market over the long-term. What’s most interesting about this study is that Shiller and his team found this to be the case for every decade since the 1890s.
Isn’t it amazing that this inefficiency never went away? There was an Economist article a few weeks back that attempted to explain this. The gist was that there is a giant paradox inherent in the Efficient Market Hypothesis: The more efficient a market becomes, the less incentive investors have to gather all the information about the assets in that market, because price captures all. But if no one is bothering to do the work, than the price will reflect less and less information, making the market less efficient. As the crowds become wise, they become lazy and lose their wisdom!