speculative bubble

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Course history of the dot-com bubble on the NASDAQ
Stock market crash after the US real estate bubble burst in autumn 2008

In macroeconomics , a market situation is referred to as a speculative bubble ( also known as a financial bubble or bubble ) in which the prices of one or more commodities (e.g. commodities or food ) , assets ( real estate and securities such as for example stocks or bonds ) with high turnover above theirsintrinsic value (also: fundamental value or intrinsic value).


In the case of speculative bubbles, markets show a recurring pattern of prices that rise sharply when sales are high and then collapse, up to and including a stock market crash ( bubble-and-crash pattern ). This price movement pattern is not limited to modern, highly interconnected financial markets , but has been documented as early as the 17th and 18th centuries as a result of the tulip mania , Mississippi and South Sea bubbles.

With increasing networking of the international financial markets , the interest of economics in the analysis of these phenomena also increased, especially because these (extreme) price movements are seen as problematic for the entire economy. Market prices influence the investment decisions of market participants and have a direct impact on companies ' capital costs . As a result, extreme price movements, such as those observed in bubble-and-crash patterns in the financial sector , can spread to the real economy and have a negative impact on it. This connection is also known as the spillover effect .

causes and emergence

The reasons for the emergence and bursting of speculative bubbles are not clear and are the subject of controversial economic discussions. The basic problem is the determination of the fundamental value , since there is no uniform determination method. Speculative bubbles cannot be explained within the framework of models based on the market efficiency hypothesis and the theory of rational expectations , such as modern portfolio theory or the capital asset pricing model . If market participants have complete information and act rationally, the market generally strives for equilibrium and volatilities are normally distributed . According to the theory, the price of an asset corresponds to the present values of future expected cash flows. Accordingly, markets are efficient and in equilibrium if prices only change as a result of changed expectations regarding future cash flows based on new information. In the short term, overvaluations could arise, which would be recognized by some market participants and ended by appropriate action (e.g. short selling ).

A market based on the models mentioned shows a so-called random walk , random price movements. However, trends that tend to show distributions with heavy margins are observed empirically in real markets. Benoit Mandelbrot described in his work on price changes in stocks, cotton and other commodities that these follow a Lévy distribution , are scale-free and self-similar (fractal). In distributions of this type, bubbles and crashes are rare but expected events. The work of Mandelbrot is largely ignored in economics, and extreme market movements are attributed to abnormal events or shocks.

The assumption is widespread that speculative bubbles are evidence of a lack of market efficiency , irrational behavior on the part of market players and high levels of uncertainty in real markets.

The following possible causes for the formation of bubbles are discussed in the literature.

Bounded rationality

In behavioral economics , market participants are assumed to have limited rationality . This assumption leads to the hypothesis that cognitive difficulties in the implementation of theoretical price models lead to short-term incorrect valuations and thus bubbles. Starting with the work of Kahnemann and Tversky , and later De Bondt and Thaler , it was found that people are unable to react quickly and rationally to changing circumstances, in this case market trends. They prefer to believe what they believed before the trend change because otherwise they would have to question their basic assumptions and behaviors. In their prospect theory , Kahnemann and Tversky postulate an asymmetry between gains and losses. Economic benefit is not derived from absolute wealth, but from relative gains and losses. If investors are confronted with certain profits, they behave risk-aversely, while with certain losses they become more willing to take risks.

great fool

The Greater Fool hypothesis assumes that there is always someone in the market willing to pay an even higher price . So if an individual investor has already knowingly paid a price above the intrinsic value, he assumes that he can sell the investment again at an even higher price, ie he finds an even bigger fool . In order to generate a cumulative effect, i.e. a longer-term continuation of this mechanism, an overestimation of the investors' own ability to correctly value investment objects must be implied. As a result, investors overestimate the number of people willing to pay even higher prices. If no one is willing to accept these inflated prices, the hypothesis is that prices will correct. The systematic overestimation of one's own abilities is referred to in social psychology as self -serving bias .

Institutionalization and herd behavior

In the social science literature, institutionalization is described as the binding of individual behavior to social norms. Individual investors do not rely on their own perception, but orientate themselves at least partially on their environment and follow the behavior of others ( herding ) . This doesn't have to be through established or agreed-upon rules (such as the legal system), but can arise spontaneously and persist over a longer period of time, even if this behavior is irrational. A mechanism described is the so-called English positive feedback trading , where investors make their decisions based on historical performance, i. H. they buy when prices rise and sell when they fall. Investors follow the market or the herd.

The research on herd behavior in the financial market can be divided into four overlapping categories:

  1. Informational cascades : Investors ignore or downplay their own information and choose to imitate the behavior of other investors. The aggregate information of the crowd outweighs any private information that the individual has. This effect can be transferred to other investors and can thus lead to a domino effect .
  2. Reputational herding : Investors follow other investors with a high reputation or reputation.
  3. Investigative herding : Investors or analysts investigate things with the assumption that others will do so in the future.
  4. Empirical herding : Investors follow the herd with no specific model or explanation, relying instead on the momentum generated by others . In terms of positive feedback trading , for example, investors rely on investments that have already gone well in the past.


Speculative behavior is motivated by the pursuit of (financial) gain. The prices on the market reflect these expectations. Speculative trading participants assume that not all market participants behave rationally and that future profits are independent of intrinsic value. This is essentially a bet on rising prices.


Some economists believe that speculative bubbles have the same causes as inflation. However, the theory is not consistent with the observation that speculative bubbles can also form during periods of low inflation.


Robert Shiller describes the hallmarks of speculative bubbles:

  • a sharp rise in prices
  • circulating information about suspected reasons and justifications for the high prices
  • a significant number of people reporting how much money they make in the stock market
  • a significant number of people who are envious and upset that they didn't get on
  • media coverage reinforcing these trends

Experimental Markets

Experimental markets are model studies that are used to test the possible causes for the creation and bursting of speculative bubbles in the laboratory. In the literature, Smith , Suchanek, and Williams' 1988 study entitled Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets is cited as seminal and fundamental to subsequent experimental investigations. The aim is to investigate which parameters and conditions influence the formation of bubbles. Among other things, the qualification and composition of the participants, the dividend structure , the market mechanisms, the information available to the market participants, the monetary incentives and the number and type of markets that work simultaneously or sequentially are varied. In most cases, blisters form and clear causes for this have not yet been identified. The frequency of dividend payments, the process of determining the fundamental value and the experience of the market participants are named as parameters with the greatest potential for preventing speculative bubbles.



See also


  1. N Gregory Mankiw : Brief Principles of Macroeconomics. South-Western College, 5th edition, 2008, p. 194, ISBN 978-0-324-59037-1
  2. a b Peter M. Garber: Famous First Bubbles. The Journal of Economic Perspectives, Volume 4, Number 2, 1990, pp. 35-54.
  3. Ronald R King, Vernon L Smith , Arlington W Williams, Mark van Boening: The Robustness of Bubbles and Crashes in Experimental Stock Markets in RH Day and P Chen: Nonlinear Dynamics and Evolutionary Economics. 1993, New York: Oxford University Press. ISBN 0-19-507859-4
  4. ^ a b Stefan Palan: Bubbles and Crashes in Experimental Asset Markets. Springer, 2009, p. 2 ff., ISBN 978-3-642-02146-6
  5. a b Harold L. Vogel: Financial Market, Bubbles and Crashes. 2018, Palgrave Macmillan, pp. 189 ff, ISBN 978-3-319-71527-8
  6. Vernon L Smith, Gerry L Suchanek, Arlington W Williams: Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets. 1988, Econometrica 56 (5): pp. 1119-1151
  7. Efficiency and beyond. The Economist , July 16, 2009
  8. Per Bak: How Nature Works. Springer, 1996, p. 14 ff, ISBN 978-0-387-98738-5
  9. Harold L. Vogel: Financial Market, Bubbles and Crashes. 2018, Palgrave Macmillan, pp. 271 ff, ISBN 978-3-319-71527-8
  10. Karlheinz Bischofberger: Theory and empiricism of flexible exchange rates: Alternative theoretical explanations and empirical evidence for eight western industrialized countries. Duncker & Humblot, 1986, pp. 78-79, ISBN 978-3-428-05988-1
  11. Sheen Levine, Edward Zajac : The Institutional Nature of Price Bubbles. 2007, Social Science Research Network
  12. John R Nofsinger, Richard W Sias: Herding and Feedback Trading by Institutional and Individual Investors. 1999 Journal of Finance, 53
  13. Alexander Kurov: Investor Sentiment, Trading Behavior and Informational Efficiency in Index Futures Markets. 2008, The Financial Review 43 pp. 107-127
  14. Didier Sornette : Why Stock Markets Crash: Critical Events in Complex Financial Systems. 2017, Princeton University Press, pp. 81ff, ISBN 978-0-691-17595-9
  15. Didier Sornette : Why Stock Markets Crash: Critical Events in Complex Financial Systems. 2017, Princeton University Press, pp. 95 ff, ISBN 978-0-691-17595-9
  16. Vivian Lei, Charles N Noussair, Charles R Plott: Nonspeculative Bubbles in Experimental Asset Markets: Lack of Common Knowledge of Rationality vs Actual Irrationality , 2001, Econometrica, 69 (4): pp. 831–859
  17. Stasys Girdzijauskas1, Dalia Štreimikienė, Jonas Čepinskis, Vera Moskaliova, Edita Jurkonytė, Ramūnas Mackevičius: Formation of Economic Bubbles: Causes and Possible Preventions. 2009, Baltic Journal on Sustainability, 15(2): p. 269
  18. Patrick Herger: Warnings of a stock market bubble have been circulating for years - but why investors shouldn't ignore them now. NZZ from September 25, 2020