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7.1: The Theory of Rational Expectations

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    Learning Objectives
    • When are expectations rational and when are they irrational?

    Market volatility, the constantly changing prices of financial instruments,[1] tricks some people into thinking that financial markets, especially stock markets, are flim-flams or gigantic roulette wheels. Stock prices, they suspect, are at best random and at worst rigged. In fact, financial markets are typically more efficient, and hence fairer, than other markets. The direction of price movements (up or down) is indeed random, but price levels are usually based on the rational expectations of a large number of market participants. While financial scams certainly exist, the stock and bond markets are not rigged. Except perhaps for some penny stocks, securities prices are usually based on economic fundamentals and are not systematically manipulated by insiders or conspirators. Investing in corporate equities certainly entails risk, but it is not akin to playing the lottery. Luck can play a role in investing, as in anything in life, but unlike a Powerball drawing, Lady Luck is not the whole of the game by a long shot. Far from being gamblers, investors are switches in the most advanced computing devices in the history of the world, financial markets. Prices in those markets help to determine what gets made and what doesn’t, how much gets produced and how, and where and how those goods are sold.

    Financial markets, in the world’s most economically advanced countries anyway, have been rational and efficient decision-making machines for several centuries. In 1688, a broker in Amsterdam, Netherlands, named Joseph de la Vega, left posterity with vivid descriptions of the Dutch securities market.[2] The market, he claimed, was just a game of misinformation and spin management that pitted bulls (those who profited from an increase in prices) against bears (those who profited from a decrease in prices):

    “The bulls are like the giraffe which is scared by nothing. . . . They love everything, they praise everything, they exaggerate everything. . . . The bulls make the public believe that their tricks signify wealth and that crops grow on graves. When attacked by serpents, they . . . regard them as both a delicate and a delicious meal. . . . They are not impressed by a fire nor perturbed by a debacle. . . . The bears, on the contrary, are completely ruled by fear, trepidation, and nervousness. Rabbits become elephants, brawls in a tavern become rebellions, faint shadows appear to them as signs of chaos. . . . What is there miraculous about the likelihood that every dwarf will become a giant in the eyes of the bears?”[3]

    Joseph de la Vega went on to detail a dozen different ways in which cabals of bears and herds of bulls tried to influence securities prices. The net effect of such machinations, though, was unclear. Sometimes the bulls won, sometimes the bears won, but their activities often canceled each other out. “Numerous brokers are inexhaustible in inventing involved maneuvers,” de la Vega explained, “but for just this reason do not achieve their purposes.” Systematic manipulation of the market was impossible because the bulls and bears competed against each other, each tugging at the price, but ultimately in vain. Also, as rational investors learned the tricks of trading, they came to expect hyperbole, false rumors, sham sales, and the like. So, in the final analysis, market fundamentals, not the whims of nefarious individuals, determined prices. Exactly the same could be said of most of today’s securities markets. Generally speaking, stock and other securities prices fluctuate due to genuine changes in supply or demand, not because of the machinations of bulls and bears.

    Joseph de la Vega’s 300+-year-old description of what was then the world’s most advanced securities market also made clear that expectations, rather than actualities, moved prices. “The expectation of an event,” he noted, “creates a much deeper impression upon the exchange than the event itself.” As noted in the preceding chapters, expectations are still paramount today. People invest based on what they believe the future will bring, not on what the present brings or the past has wrought, though they often look to the present and past (sometimes even the distant past) for clues about the future.

    Rational expectations theory posits that investor expectations will be the best guess of the future using all available information. Expectations do not have to be correct to be rational; they just have to make logical sense given what is known at any particular moment. An expectation would be irrational if it did not logically follow from what is known or if it ignored available information. For the former reason, investors expend considerable sums on schooling, books, lectures, seminars, and the like, to learn the best ways to reason correctly given certain types of information. (This textbook and course are a good start, but competition for the best model is keen. Investment models and strategies constantly morph, adapting to changes in the real world.) For the latter reason, investors update their expectations, or forecasts, with great frequency, as new information becomes available, which occurs basically 24/7/365.

    If everyone’s expectations are rational, then why don’t investors agree on how much assets are worth? One investor may think gold a steal at $900/ounce, while another wouldn’t touch the stuff for a penny over $750. One investor might think $943.40 just right for a zero coupon bond, but another might think it a good deal only at $942.51. One may think that XYZ stock is overpriced at $22.57 a share, while another would buy a small quantity of it at that price, and yet another would buy all she could at that price. Such differences in valuation are important because they allow trades to occur by inducing some investors to sell and others to buy.

    As it turns out, investors sometimes have different sets of information available to them. Some investors may have inside information, news that is unknown outside a small circle. Others may lack certain types of information because they think it is too costly to obtain. Other times, investors think of the information they know in common differently because their utility functions (their goals and aspirations, if you will) differ. So they have different time horizons, different holding periods, and different sensitivities to risk.

    At yet other times, investors use different valuation models, different theories of how to predict fundamentals most accurately and how those fundamentals determine securities prices. For example, some investors foresee long causal chains more clearly than other investors do. Recall from Chapter 5 that the demand for asset X is partly a function of its expected return relative to all assets not-X. So investors must consider information directly related to asset X and all other assets. A new piece of information half a world away that alters expectations about a nation’s ability to repay its debts, a sector’s future prospects, or a single company’s profits regularly ripples through the entire financial world. Ripple indeed evokes the right metaphor. Like throwing a pebble into a pond, the disruption is greatest at the epicenter, the spot where the rock hits the water, but it dissipates over time and space. The bigger the pebble (the bigger the news), the bigger the splash and the larger and longer lasting the disruption. Most days, the world’s financial pond is pelted with millions of little pebbles, little pieces of news that cause prices to jiggle up and down. Every now and again, a big stone, even a boulder, hits the pond, causing significant price changes throughout the pond for quite a long time. (Economists call such boulders shocks, and they include financial crises like that of 2007–2008. Financial crises almost always follow asset bubbles, which we will discuss in more detail below.)

    Some investors understand the effect of some ripples more quickly and clearly than others. This shouldn’t be taken to mean that some investors are smarter than others, only that they understand the types of ripples particular pebbles will make better than others do. The roles could reverse with the next pebble, with the next bit of news. Moreover, investors constantly strive to improve their understanding of the ways that certain types of news affect securities prices. They emulate successful people and develop new models and theories of their own, not for the joy of learning but for the clink of cold hard cash. For example, investors who understood that oil prices hitting $50 per barrel would increase the share price of home insulation manufacturers merely stayed up with the crowd. It’s pretty obvious that higher home heating costs would induce people to buy insulation. The investors who quickly figured out that the share price of a Canadian shingle manufacturer would jump too were the ones that earned above-market returns. (High oil prices made it profitable to extract oil from Canada’s oil sand fields, but not enough people lived in the area around Fort McMurray, Alberta, to meet labor demands. People flocking to the region to work needed new homes, the roofs of which needed shingles, lots of them.[4])

    For all those reasons, investors often have a wide variety of opinions about the value of different assets. More mechanically, investors might have different opinions about bond valuations because they must have different views about the applicable discount or interest rate. To review,

    \[P V = F V / ( 1 + i )^n\nonumber\]

    If this is a one-year zero coupon bond, FV = $1,000, and i = 6%, then the bond price = ($1,000/1.06) = $943.40. But if one believes i = 6.01, then the bond price = ($1,000/1.0601) = $942.51. To understand how investors can value the same stock differently, we must investigate how they value corporate equities.

    • Expectations are rational when they logically follow from all available relevant information.
    • Expectations are irrational if some available pertinent information is ignored or if conclusions do not flow logically from available information.



    [3] Joseph de la Vega, Confusion de Confusiones.


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