Stock analysts may be even more enamored of statistics than fantasy football fans, but the key to using statistics successfully in evaluating stocks is to understand their limitations.
Here are five significant stock statistics to consider:
Price-to-earnings ratio (P/E) – probably the most common valuation statistic for stocks – puts price in the context of how much a company earns. A stock with a low price is not necessarily cheap if it also has very low earnings. There are many variations on P/E, but two important types of variation involve the distinction between reported and operating earnings, and the attempt to smooth out temporary fluctuations in earnings.
Operating earnings are the net profits derived directly from the normal operations of the firm, while reported earnings reflect the adjustment of those earnings for accounting treatments, such as the write-down of depreciated assets or the realization of new liabilities. Operating earnings give a clearer picture of a company’s success. But if companies have large and frequent discrepancies between reported and operating earnings, this could be a sign of accounting issues potentially undermining the stock’s value.
Fluctuations in earnings can cause major distortions in P/E, especially for cyclical stocks or companies that took a one-time charge against earnings. One way around this is to measure P/E based on a five-year or cyclical average of earnings, rather than on current earnings.
PEG, or price-to-earnings growth, is measured by the P/E ratio divided by the earnings growth rate. The PEG ratio accounts for the fact that faster-growing companies might justify higher P/E ratios than slower growing ones because their faster growth rate will help earnings catch up with the price over time.
Just remember past growth might not continue into the future. In particular, fast-growing companies early in their life cycles will find it difficult to sustain their growth rates as they mature.
Earnings are not always the best measure of a company’s success, especially for younger companies. In such cases, it may be necessary to get volume up to a certain critical mass in order to overcome initial investment costs. Even with older companies, new investments or temporary expenses can temporarily depress earnings in a way that does not really reflect the company’s success in the marketplace.
In such cases, the price-to-sales (P/S) ratio can be a useful measure. It acknowledges that top-line revenues can be more important for young companies than bottom-line earnings, providing a more stable basis for valuation comparisons than earnings.
Price-to-book ratio (P/B) provides a very stable valuation basis by measuring prices relative to the official value of the company’s assets. However, there are some caveats.
First, the book value of a company’s assets may be very different from their market value. For example, long-lasting manufacturing equipment may be fully depreciated from an accounting standpoint, but still have great operational value. Conversely, a company with outdated plant and equipment may still carry some book value for assets with little practical use and no resale value.
Second, some industries are more asset-intensive than others, so while P/B comparisons may be useful when evaluating companies within the same industry, they are less meaningful when comparing companies across industries.
It is normal, and often financially advantageous, for companies to carry some debt. However, a fast-rising debt-to-equity ratio can be a red flag that a company’s borrowing is getting out of hand.
As with P/B, debt-to-equity is one of those measures that tends to vary greatly depending on the nature of the business, so use a peer group of similar companies to put it in perspective, rather than expecting a universal standard to apply to every situation.
What is important about the above discussion is not just that it covers some of the most prominent valuation metrics, but that in each case, it describes the importance of context in using any of these metrics.
Metrics like the above are a good starting point that can help you identify outliers and start asking questions about whether the conditions that created those anomalies are favorable or unfavorable for the stock in question.
Do you invest in stocks? How do you look at stock stats?
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