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MARKET COMMENT
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How do you define stock market risk? If you were to ask an investment academic, then the subject of volatility would quickly crop up. According to the textbooks, shares that exhibit higher volatility than average are deemed the riskier. Risk in this way is measured by a share's beta. But such theories and measures should be left to the scholars. Out in the real world, ordinary investors have to go back to basics. What is a share purchase if it's not buying a part slice of a business? Over time, a company's valuation will run in tandem with its underlying business performance. The risk for investors, therefore, comes from numerous sources; notably, the company's products, industry rivals, management, accounts and valuation. It is the incorrect assessment of these variables that courts investment risk, not judging how the share price has performed in the past. That said, it's understandable why many people use historical prices to judge a share's future performance. With few investors ever beating the stock market average, many deduce that the stock market is always efficient. While beating the stock market is not easy, the follies of human nature regularly throw up the chance to do so. For instance, the sell-off of 'old economy' shares in early 2000, the market panic of September 2001 and the slump in mid-2002 all presented investment opportunities. During these times, the academic may have shied away from the stock market because the 'beta risk' had increased following the heavy -- and volatile -- share price declines. But in reality, buying quality businesses selling on cheap valuations during those two market falls would have presented little portfolio danger. Furthermore, share price statistics appear to provide clear-cut numerical 'answers', whereas evaluating companies, products, accounts and so on involves a lot of subjectivity. But just because these business-based factors involve a degree of interpretation, it doesn't negate their importance to investors. As Warren Buffett writes: "In their hunger for a single statistic to measure risk, however, [academics] forget a fundamental principle: It is better to be approximately right than precisely wrong." A version of this article first appeared in March 2002.