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Most economists think that the value of a stock should be equal to the present value of the stream of income that the stock is expected to generate. Easier said than done. The problem with this simple and sensible orientation is that we live in a world of uncertainty, where expected income over time is unknown. Moreover, different analysts will have different expectations and hence different assessments of “correct” values. Put another way, no objective estimate is universally accepted as the correct price for a stock. Judgments are inherently required.  Listed stocks, however, have the attribute of having observable stock prices, but price and value are two different things. We should all be able to agree on an observable price, but we won’t necessarily agree on value.

Value investors pick stocks by implicitly or explicitly comparing their sense of the value of a stock relative to its current market price. Making the assessment that the value is higher than the current price justifies the determination that the stock is undervalued, and vice versa. As understandable as this theoretical orientation may seem, it flies in the face of the efficient market hypothesis. 

The efficient market hypothesis suggests that the invisible hand of the market synthesizes all the available information, and the market price of a stock reflects the best assessment of the present value of expected future earnings.  The judgment that a stock is over- or undervalued reflects a certain amount of hubris – that the analyst knows better than the market.  The efficient market hypothesis essentially rejects that proposition, with the consequent corollary being that any effort to identify over- or undervalued stocks is a fool’s game.   

Even assuming the efficient market hypothesis to be valid, information is constantly evolving, and new information will inevitably foster adjustments to earnings forecasts and hence stock prices.  Thus, one way of thinking about whether stocks are cheap or rich requires correctly anticipating how future earnings will change relative to current forecasts. A stock’s price would be expected to rise if future earnings forecasts are revised upward, and vice versa. Thus, the determination of a value different from the current stock price essentially reflects an expectation that the current implied forecasted earnings will be adjusted in a particular direction.  If you’re right, you win; if you’re wrong, you lose.

I look to the price-to-earnings (P/E) ratio as being a useful – albeit flawed – metric that helps in comparing relative stock values.  These ratios are typically constructed by dividing the price of the stock by the earnings of the prior year.  In a world with static earnings flows, a P/E of 5 suggests a 5-year payback if earnings stay at the prior year’s level, while a P/E of 30 reflects a 30-year payback. Given this perspective, at first glance you might expect a listing of stocks by P/E ratios to offer a basis for ranking these stocks by their relative values. Those with lower P/Es would seem to be better values, and hence better buys, than those with higher P/Es. 

Not necessarily so, however. One could justify a stock having what would seem to be an outlying P/E if the most recent earnings were an aberration or if future earnings were expected to be markedly different from past earnings. The prevalence of high P/E ratios is indicative of investors’ willingness to bid up the price of a stock in anticipation of higher earnings yet to come, often (to my mind) with insufficient consideration of how much those higher earning flows should be worth.  Over time, however, either by an adjustment of stock prices or an adjustment of realized and anticipated earnings, P/E ratios should be expected to retreat from extremes.

Whatever stock one might buy, it’s reasonable to anticipate the price to rise if and when consensus earnings estimates are exceeded, and vice versa, irrespective of whether the stock has a high P/E or a low one.  In either case, the universal danger is paying too much for the anticipated earnings. My own sense is that that risk is particularly appropriate for stocks that post especially high P/E ratios, where the pace of expected earnings growth may be overly optimistic.

In considering stock selection, value considerations are one thing, but we can’t ignore the psychological considerations that also influence the way stock prices behave.  Like all market prices, stock prices are determined by supply and demand. At any point in time, supply is fixed by the number of shares outstanding.  Demand, on the other hand, can increase or decrease as a function of changing information, marketing efforts by institutions that are incentivized to generate order flow stock, market gurus in the public square, and even inside information. These institutional aspects influence the behavior of investors and affect stock prices. 

Besides these institutional features, I expect AI programs to have an increasing impact in this regard in the future, as well.  Unquestionably, a host of investment-oriented organizations are already trying to harness AI to help them trade by using pattern recognition to better forecast and then trade on the coming stock price moves. To the extent that these systems evolve in a way that coalesces around consensus forecasts, those forecasts could likely become self-fulfilling.  The consequence of AI in this realm is that it may push stock prices away from more rational fair values.  Additionally, these programs could end up contributing to a destabilizing, higher degree of market volatility.  Not that we’re able to put this genie back into the bottle, but these are the dangers that concern me.

Derivatives Litigation Services assists legal teams with litigation when derivative contracts play a role in disputed transactions. The firm offers advice and counsel on a best efforts basis but bears no responsibility for outcomes dictated by mediation or court judgments.

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