Published: 22-01-2013, 15:15

Speculation

The economist John Maynard Keynes (1936) defined speculation as the purchase of securities at a price above their fundamental value with a view to sell them at yet a higher price in the subsequent trading periods. Ever since the economist Milton Friedman (1953) argued that such destabilizing speculation would be unprofitable and thus unsustainable in the long run, economists generally have discounted the possibility that speculation could cause asset prices to deviate fromfundamental values, that is, prices warranted by the true earning potential of firms. The intuition behind Friedman’s argument rested on a simple view of arbitrage. In amarket that includes both smart traderswho knowthe true values and those who make whimsical and misinformed trades, generally referred to as noise traders, the latter create riskless arbitrage opportunities from which smart traders could profit.

The rise of behavioral finance theory has made economists more receptive to studying the limitations of arbitrage in real-world markets. Informed traders with a ‘‘short’’ trading horizon who sell overvalued assets short can find that by the time they are supposed to close their position, the true value has increased, or the assets in question have become even more overpriced.Because the smart traders who have sold securities short could make losses in either situation, they limit the initial positions they take in an over- or undervalued asset, preventing the current price from smoothly adjusting to its true value as Friedman had envisioned. It might even be the case that it pays for smart traders to act like noise traders themselves in the short run, bidding prices further away fromtrue values rather than helping to close the gap between the two (De Long et al. 1990; Griffin, Harris, and Topaloglu 2003). Thus an increasing number of economistsnowhold that riskless arbitrage is not always effective (Shleifer 2000).

This view is reminiscent of Keynes’s (1936, chapter 12) famous beauty contest analogy, where speculators base their expectations of future asset prices not only on what they think the true value is, but, more important, on what they think the average opinion about the average opinion is. In other words, noise is at least as important as information about true values in causing asset price changes, rendering the resale price uncertain (Black 1986). This, in turn, implies that traders must not only form higher-order expectations (i.e., onwhat others think others think) but also decide howmuch weight to assign them relative to what they themselves think the true value is (Hirota and Sunder 2003).

If a trader observes that the price of an asset (or an asset group) which she thinks is already overvalued is still rising in price, she is led to surmise that either her opinionabout the true value is wrong or that the price is rising on account of market sentiment (Abreu and Brunnermeier 2003). In either case, the information and opinion of others, as revealed in current price changes, are likely to gain in importance in how the trader forms his/her expectation about the future price. Such information becomes either a proxy for the higher-order expectations or a corrective on opinions about the true value, or some combination of both.Under these conditions whether speculation is stabilizing or not crucially depends on the relative weight traders assign to their higher-order expectations (i.e., what they think others think others think) relative to their own assessment ofwhat the true value is. Though it appears to be long forgotten, this basic idea in its simplest formgoes back to Kaldor (1939), where whether speculation is stabilizing or not depends on the elasticity of future price expectations with respect to current price changes. In this early formulation, stability requires a less than unitary elasticity of expectations, where traders revise their expected future price proportionally less than the change in the current price.

In the modern literature, much more elaborate analyses of cases where agentsmake trades relying on information revealed by the past decisions of other traders rather than their own abound and are generally discussed under the heading of herding behavior. These generally model ‘‘momentum-investor’’ or ‘‘positive-feedback’’ strategies, where traders tendtobuy assetswhose pricehas been on the rise and sell those that have been falling in price. Short trading horizons, the sequential nature of trades, and information costs are the real-worldmarket attributes that are emphasized in this body of work.

In contrast to standardmodels of asset pricing that implicitly assume long-term horizons, short-term trading horizons play an important role in persistent deviations of asset prices from true values (Dow and Gorton 1994). In these models, it is argued that the incentive structure that defines money managers’ employment gives rise to agency problems (Allen and Gorton 1993), making it rational for speculators to have short trading horizons. In a world characterized by market imperfections and uncertainty, speculators who tie their resources to long-terminvestments would fail to exploit profitable investment opportunities that would unexpectedly arise (Shleifer and Vishny 1997).

Second, in real-world markets trading is sequential, which implies that traders observe and can learn from one another. Early action can enable traders to rationally exploit information revealed by the actions of other agents. Profit-maximizing traders can thus successfully focus on what other traders also know rather than trying to learn information others do not have. A narrow set of information can then become the primary focus of attention even when it has little bearing on fundamentals (Scharfstein and Stein 1990).

Finally, especially in international markets, gathering information requires large fixed costs which generate economies of scale for large investors. Thus the greater the cost of acquiring information, the higher is the incentive for uninformed small traders to imitate large investors (Calvo and Mendoza 2000). This also causes small investors to be much more aggressive, especially in their selling in markets where large investors have a significant presence (Corsetti et al. 2001), giving rise to increased volatility and likelihood of abrupt shifts in capital flows, leading to currency and financial crises.

See also contagion; currency crisis; exchange rate volatility; financial crisis; spillovers

FURTHER READING

  • Abreu, D., and M. Brunnermeier. 2003. ‘‘Bubbles and Crashes.’’ Econometrica 71: 173 204. Shows that a bubble can exist despite the presence of rational arbi trageurs.
  •  Allen, F., and G. Gorton. 1993. ‘‘Churning Bubbles.’’ Re view of Economic Studies 60: 813 36. Argues that agency problems caused by asymmetric information in financial markets cause financial assets to trade at prices different than fundamentals.
  • Black, F. 1986. ‘‘Noise.’’ Journal of Finance 41 (July): 529 43. Argues that noise in financial markets plays a pro found role in shaping our views of the world.
  • Calvo, G., and E. Mendoza. 2000. ‘‘Rational Contagion and the Globalization of Securities Markets.’’ Journal of International Economics 51: 79 113. Argues that the large fixed costs of gathering information in foreign ex change markets incentivize small traders to imitate large investors.
  •  Corsetti, G., A. Dasgupta, S.Morris, and H. S. Shin. 2001. ‘‘Does One Soros Make a Difference? A Theory of Currency Crises with Large and Small Traders.’’ Review of Economic Studies 71: 87 113. Argues that the very existence of large investors in foreign exchange markets of emerging countries increases the vulnerability of these countries to speculative attacks.
  •  De Long, J. B., A. Schleifer, L. Summers, and R. Wald mann. 1990. ‘‘Positive Feedback Investment Strategies and Destabilizing Rational Speculation.’’ Journal of Fi nance 45 (2): 379 95. Shows that rational speculation might entail rational traders to act as noise traders, jumping on the bandwagon of an asset price bubble the latter might create.
  • Dow, J., and G. Gorton. 1994. ‘‘Arbitrage Chains.’’ Journal of Finance 49: 819 49. Explores how and why limited trading horizons can give rise to inefficient asset prices.
  • Friedman, M. 1953. ‘‘The Case for Flexible Exchange Rates.’’ Essays in Positive Economics. Chicago: Chicago University Press. In this famous paper, Friedman argued that speculation had to be stabilizing for it to be profit able.
  • Griffin, J., J. Harris, and S. Topaloglu. 2003. ‘‘The Dy namics of Institutional and Individual Trading.’’ Journal of Finance 58 (6): 2285 2320. Summarizes the findings of studies that examine the relationship between insti tutional ownership and stock returns.
  • Hirota, S., and S. Sunder. 2003. ‘‘Price Bubbles sans Divi dend Anchors: Evidence from Laboratory Stock Mar kets.’’ Working Paper. Downloadable from http:// www.som.yale.edu/faculty/Sunder/research.html. Tries to model higher order expectations about what the av erage opinion expects what the average opinion expects and on and on.
  • Kaldor, N. 1939. ‘‘Speculation and Economic Stability.’’ Review of Economic Studies 6 (3): 1 27. Specifies the conditions under which speculation can be stabilizing.
  • Kemp, M. C. 1963. ‘‘Speculation, Profitability, and Price Stability.’’ Reviewof Economics and Statistics 45: 185 89. Provides an early criticism of Friedman’s argument that profitable speculation must be stabilizing.
  • Keynes, J. M. 1936. The General Theory of Employment, Interest, andMoney. Reprint, 1964. NewYork:Harcourt Brace Jovanovich. Keynes’s major theoretical work where he lays out his theory of effective demand.
  • MacDonald, R. 2000. ‘‘Expectations Formation and Risk in Three Financial Markets.’’ Journal of Economic Surveys 14 (1): 70 100. An overview of the empirical literature on expectations formation in financial markets.
  • Scharfstein, D., and J. Stein. 1990. ‘‘Herd Behavior and Investment.’’ American Economic Review 80 (3): 465 89. Examining the conditions under which herd be havior occurs in financial markets, the paper shows why it can be rational for some traders to mimic other traders rather than relying on substantive private information.
  •  Shleifer, A., and L. Summers. 1990. ‘‘The Noise Trader Approach to Finance.’’ Journal of Economic Perspectives 4 (2): 19 33. Argues that riskless arbitrage is severely limited not only in relation to the prices of shares or bonds as a whole but also in relation to the prices of individual assets.
  •  Shleifer, A., and R. Vishny. 1997. ‘‘The Limits of Arbit rage.’’ Journal of Finance 52 (1): 35 55. Discusses how anomalies in financial markets can appear and why ar bitrage would fail to eliminate them.

 KORKUT A. ERTURK

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