online business resources

Financial theory tends to focus on a notion of risk limited to what we might be termed ‘‘trivial perils’’, those having to do with price fluctuations liable to appear in a relatively stable overall environment. Doesn’t history frequently show that radical alterations in the environment provoke price variations comparable to mood swings? Maybe we just do not know how to analyze major risks. Maybe we do not know how to prevent them.
Examples have demonstrated that rather than base their expectations on past mathematical averages, investors tend to detect correlations between past events. At the beginning of his chapter on ‘‘the state of long-term expectation’’, Keynes wrote:
It would be foolish, in forming our expectations, to attach great weight to matters which are very uncertain. It is reasonable, therefore, to be guided to a considerable degree by the facts about which we feel somewhat confident, even though they may be less decisively relevant to the issue than other facts about which our knowledge is vague and scanty. For this reason the facts of the existing situation enter, in a sense disproportionately, into the formation of our long-term expectations; our usual practice being to take the existing situation and project it into the future, modified only to the extent that we have more or less definite reason for expecting a change.
How is such a judgment to be formulated? Investors tend to make a fetish out of economic ‘‘factoids’’, such as for how many months, at some time in the past, did the market anticipate and predict economic recovery. And yet they interpret such anecdotal data by connecting the ‘‘dots’’ that get their attention in accordance with the ‘‘paths’’ they map out. As with the Impressionists (and most especially with Georges Seurat), investors spend a great deal of their time connecting details. The brain is organized in order to detect correlations. Numerous studies have shown that investors revise their predictions by overemphasizing new information in relation to pre-existing and long-term data.
Curiously enough, the mechanism of risk analysis is altogether different. Rather than behave as they do when forming expectations, investors often use historical (mathematical) volatility to assess the risk of a possible investment. Experience shows that volatility constitutes an excellent basis for risk evaluation; what skyrockets may plummet just as precipitately.
That said, the relationship between risk and return is not as fluid as theory would have it (we shall return to this point). The connection between risk and return is not a detail. It is not because a portfolio presents high risk that one may reasonably expect to win the ‘‘sweepstakes’’. Moreover, unforeseen correlations do crop up; they merely were not noted in the past. Last but not least, volatility evolves along with time. One may think that the dispersion of returns (additional volatility) would increase in times of economic and political uncertainty. The sensitivity of a financial asset to market variations may be estimated historically, but this should only be the basis of ongoing anticipation. Volatility also must be anticipated.