Reflexivity in Financial Bubbles
An Alternative Theory of How Markets Work
This was my undergraduate economics thesis on reflexivity in financial markets, inspired by George Soros’s theory of reflexivity. I thought I’d share it, in case anyone would be interested to read parts of it, or use it as a foundation for their own work. Please attribute where appropriate.
Content
Introduction
What is a bubble?
Why has nobody noticed that a crisis was under way?
Efficiency in Financial Markets
The Theory of Reflexivity
Soros in Perspective
The Anatomy of a Bubble
Results
Conclusion
Bibliography
Introduction
The subprime mortgage crisis that led to the global meltdown of the financial system has potentially discredited the current paradigm of economic theory. The Efficient Market Hypothesis and Rational Expectations Theory are still the predominant way to understand the dynamics of financial markets, but the crisis has given rise to a need to look for alternative ways of how financial markets work.
George Soros’s theory of reflexivity is a kind of new economic thinking. Many of his insights are not fully recognized by economists and academics alike. For example, the observation that models that try to explain the dynamics of financial markets need to distinguish between mechanical and social constructs. In addition, his more impressionistic observation that philosophy rather than science should be emphasized in order to better understand financial markets has not been fully appreciated yet. As a speculator, Soros has been incredibly successful, but as a philosopher, his ideas are still not widely known nor fully appreciated. Many academics and economists can learn from Soros’s conceptual framework if they overlook the fact that he is not one of them. He has six decades of experience in the financial markets as a speculator and distilled that experience into a very rich alternative way to efficient markets hypothesis. An alternative way of how markets work, drawn from Soros’s in-depth understanding that he needed to have to succeed as a speculator in the markets, can only enhance our understanding of how financial markets interact with policy and politics. The thesis will test Soros’s theory of reflexivity as it applies to financial markets, and determine whether or not it can provide a credible alternative way of understanding the dynamics of financial markets.
The structure of this thesis will be organized in the following way: First, an account of what determines a financial bubble will be given, and handful of definitions by economists and scholars will be provided. As financial bubbles stand at the center of this discussion, it seems appropriate to define the laboratory, namely financial bubbles, that will serve as a way to test Soros’s model. The thesis will then move into a section, which will seek to explain why we need alternative ways to understand financial markets. In 2009, Queen Elizabeth II asked the following question: why had nobody noticed that the credit crunch was on its way? The answer will show why looking for an alternative model is appropriate. In any good parliamentarian debate, the model that is being debated is sufficiently defined at the beginning. As the current paradigm of economic theory mainly consists of the Efficient Market Hypothesis and the Rational Expectations Theory, those two theories shall be presented as objective as possible. After having presented the status quo, an account will be given of Soros’s theory of reflexivity and then his work will be assessed through the lenses of scholars and academics. Finally, his theory shall be tested with the help of one case study that can determine whether or not his theory can be referred to as an alternative way to understand financial markets and bubbles. The case study, the dot-com bubble, will begin with two existing models by Minsky and Brunnermeier that explain financial bubbles. These models will serve somewhat as a way to compare them to Soros’s model and discover what elements within his theory are distinct. Finally the aspects that make Soros’s theory distinct will be highlighted in the results section and further questions will be asked for future research.
What is a bubble?
In search of recognizing patterns and recurring themes in a bubble, it seems appropriate to provide an account of alternative definitions from scholars who have studied financial bubbles in the past. The meaning of a bubble is very elusive and ambiguous, and not very well understood in general, so a handful of definitions will give us a better understanding of what a bubble consists of. What follows is a set of working definitions from which the analysis that follows can be build. A bubble can develop in any kind of asset, but for the purpose of this thesis when speaking of bubbles I shall refer to bubbles in financial markets, focusing in particular on equities. The analysis will entail a search of a better understanding of the nature of those financial bubbles. To fully understand financial markets, one needs to understand how bubbles operate and function. Presidents have come and go; states have disappeared from the map, yet bubbles have existed since the onset of financial markets. When we think of a bubble, thoughts come into our mind of an object that grows slowly, ever increasingly and exponentially before it reaches a peak and pops. Brunnermeier defines a bubble as “a large, sustained mispricings of financial or real asset.” (Brunnermeier 2012, 12) However he also cautions that not every mispricing that is temporary in nature can be called a bubble. Further he argues that the term bubble may refer to “periods in which the price of an asset exceeds fundamentals because investors believe that they can sell the asset at an even higher price to some other investor in the future.” (Brunnermeier 2012, 12) It was Keynes that distinguished between investors and speculators. Investors buy an asset so that they can collect its dividend stream, whereas a speculator buys an asset in hope of selling it back to the market at a higher price. In general, the price of an asset is the present value of all future expected cash flows. Siegel explains how economists have tried to link asset price movements to fundamentals, those economic factors such as cash flows and discount rate, to derive a better definition of a bubble. (Siegel 2003, 11) Siegel, therefore, proposes the following definition of an asset market bubble:
It is based on whether the future realized return of the asset justifies the original price over a time period long enough so that the present value of cash flows received by investors during this period constitute at least one-half of that price. A simple measure of this length of this time is the duration of the asset, or the time-weighted average of all future expected cash flows. If the realized return is more than two standard deviations from the expected return, given the risk and return conditions present up to the time when the price is being examined, then a bubble has been confirmed. (Siegel 2003, 13–14)
Kindleberger provides another, quite common definition of bubbles. He defines a bubble as “an upward price movement over an extended range that then implodes.” (Kindleberger 1978, 53) This might be too general though, so the Palgrave dictionary of economics provides a more detailed definition:
A bubble may be defined loosely as a sharp rise in the price of an asset or a range of assets in a continuous process, with the initial rise generating expectations of further rises and attracting new buyers — generally speculators interested in profits from trading in the asset rather than its use or earnings capacity. (Eatwell, Milgate and Newman 1987, 281)
Another definition by behavioral economist Shiller is also telling:
The essence of a speculative bubble is a sort of feedback, from price increases, to increased investor enthusiasm, to increased demand, and hence further price increases. The high demand for the asset is generated by the public memory of high past returns, and the optimism those high returns generate for the future. The feedback can amplify positive forces affecting the market, making the market reach higher levels than it would if it were responding only directly to these positive forces. (Shiller 2001, 3)
Finally, Mackay in his classic Extraordinary Popular Delusions and The Madness of Crowds defines the process of a bubble as follows:
We find that whole communities suddenly fix their minds upon one object and go mad in its pursuit; that millions of people become simultaneously impressed with one delusion, and run after it… Money, again, has often been a cause of the delusion of multitudes, Sober nations have all at once become desperate gamblers, and risked almost their existence upon the turn of a piece of paper. (Mackay 1841, xix-xx)
It is conventional wisdom that bubbles are part of our capitalist society, and inherent in the financial system. This would mean that there is only little one can do ex ante, before the bubble pops. Economist Robert Lucas suggests that: “the main lesson we should take away from the Efficient Market Hypothesis for policymaking purposes is the futility of trying to deal with crises and recessions by finding central bankers and regulators who can identify and puncture bubbles.” (Lucas 2009) In anticipation to the recent financial crisis, central bankers and regulators were not able to identify and puncture the bubble. By their very nature bubbles are only fully recognizable in retrospect. Besides, not every mispricing in valuation for equities will turn into a bubble. However, agents that are affecting financial markets such as central bankers and regulators have often shown that despite their good intentions sometimes their actions fuel instead of dampen a bubble. In other spheres such as natural catastrophes there are early warning systems, a method to dampen the impact, and in aviation the use of black boxes helps investigators to determine the cause of an airplane crash.
We have to be mindful of the fact that a bubble does not cause every financial crisis and it is unlikely that bubbles can ever be fully prevented; yet a study of the anatomy of bubbles and a consideration of alternative theories explaining the dynamics of financial markets seems appropriate. Lastly, as Soros says, reflexivity manifests itself the most dramatic within bubbles and therefore deserves special attention. (Soros 2008)
Why has nobody noticed that a crisis was under way?
When Queen Elizabeth II visited the London School of Economics in 2009, she asked why nobody had noticed that the credit crunch was on its way. After the British Academy convened a forum in search of the answer, they summarized their answer as follows:
The failure to foresee the timing, extent and severity of the crisis to head it off, while it had many causes, was principally a failure of the collective imagination of many bright people, both in this country and internationally, to understand the risks to the system as a whole. (British Academy 2009)
The panel recognized that some people were aware of the individual problems, but only very few could predict the problems to the system as a whole. Niall Ferguson was one of the few who was able to predict the subprime mortgage crisis of 2007, but he also acknowledges that “what was much harder to predict was the way a tremor caused by a spate of mortgage defaults in America’s very own, home-grown emerging market would cause a financial earthquake right across the Western financial system.” (Ferguson 2008, 336) Further, the British Academy alluded to the problem that people did foresee the crisis, but nobody was able to predict the timing of its onset and ferocity. Another issue was that while some of the best mathematical minds were being employed at calculating financial risk, the risk to the system as a whole was neglected. They acknowledged that it was a cycle fuelled “not by virtue but by delusion”. (British Academy 2009) Another conclusion from the panel that included economists from the best universities in the world was that there was a broad consensus that it was better to deal with the problem afterwards by bailing out the economy than trying to prevent the problem from getting so big in the first place. Thus, this led everyone to miscalculate the risk to the system as a whole.
It is therefore out of this dissatisfaction that the crisis has not been noticed that mainstream economics has come under attack and the need arose to look for alternative ways to explain the dynamics of financial markets. There is a clash between economists, who on the one side of the spectrum believe in an ergodic stochastic process that dictates that the future is already predetermined by existing parameters, and on the other side by the ones who believe in a non-ergodic stochastic process, in which future probabilities cannot be calculated from past probability calculations. In his seminal work, Paul Samuelson has written that in order for economics to move from the realm of history into the realm of science the “ergodic hypothesis” needs to be imposed on economic theory. (Samuelson 1969) Samuelson and following his lead, economists such as Robert Lucas, Greg Mankiw, and Myron Scholes have assumed that an ergodic stochastic process generates observable economic events. (Davidson 2011) According to their view, the future is predetermined and in Davidson’s words “can be discovered today by the proper statistical probability analysis of past and today’s data.” (Davidson 2011, 4) The economists that have imposed the ergodic axiom on economic theory have tried to put economics in the same class as the hard sciences. A quote by Lucas illustrates this thinking: “progress in economic thinking means getting better and better abstract, analogue models, not better verbal observations about the real world.” (Lucas 2009) Two further examples of theories based on the ergodic system are Nassim Taleb’s concept of black swans, an already predetermined outcome on the far out tail of the statistical distribution, and Frank Knight’s concept of uncertainty from his book Risk, Uncertainty and Profits, where he distinguishes between risk and uncertainty. (Knight 1921) The economists on the other side of the spectrum, the ones that believe that economics is a non-ergodic system, reject those axioms for understanding the world. Among them, Keynes, who in his General Theory stated that classical economists:
resemble Euclidean Geometers in a non Euclidean world who, discovering that in experience straight lines apparently parallel often meet, rebuke the lines for not keeping straight — as the only remedy for the unfortunate collisions which are occurring. Yet in truth there is no remedy except to throw over the axiom of parallels and to work out a non Euclidean geometry. (Keynes 1936, 15)
He further noted that classical theorists “offers us the same supreme intellectual achievement, unattainable by weaker spirits, of adopting a hypothetical world remote from experience as though it were the world of experience and then lived in it consistently.” (Keynes 1936, 192) In regards to Keynes’s concept of uncertainty about the economic future, Davidson agrees with Keynes that the economic system needs to be generated by a non-ergodic process. Soros also objects in his theory of reflexivity to the idea of the ergodic axiom, as in his own words it does not allow “the reflexive interaction between participants’ thinking and the actual state of affair.” (Soros 2012) In other words, the future path of the market is determined in part by the way people think about the market. (Davidson 2011) Between Soros and Keynes, Davidson finds a similarity in that their imperfect understanding about the future is essential in understanding how our economic world operates. Every science simplifies and makes assumption in their models to explain, but it seems that many economic theories that are based on the ergodic axiom seem to have lost their relationship to the real world. Davidson suggests that Keynes’s liquidity theory of the operation of financial markets is a “rigorous, logically deductive system that appears to be applicable to the real world in which we live…” (Davidson 2011, 6) Soros’s theory of reflexivity therefore seems to build on Keynes’s work.
Efficiency in Financial Markets
A story about two people walking down the street spotting a $100 bill illustrates the debate on efficiency of financial markets. As one of them is about to pick up the bill, the other person replies that he should not bother picking it up for if it were a real $100 bill someone else would have picked it up already. There is the debate to what extent financial markets are efficient, and whether they are efficient all the time or just sometimes. It is a debate between ergodic axioms and non-ergodic axioms systems. The current paradigm of economic theory: the Efficient Market Hypothesis and the Rational Expectations Theory represent the ergodic axioms, while Soros’s theory of reflexivity represents the non-ergodic axioms systems. Soros believes that his theory stands in opposition to the current paradigm, which means that if one is correct, it must necessarily follow that the other is wrong, and vice versa. (Soros 2010) However, since Soros is neither an economist nor an academic, he acknowledges that he never fully studied those theories and the knowledge of his own theory largely stems from his vast experience as a speculator in the financial markets.
It was in 1978 when American economist Michael Jensen declared that: “there is no other proposition in economics which has more solid empirical evidence supporting it than the efficient-market hypothesis.” (Jensen 1978, 95) It has been wildly influential forming “the basis of the federal securities law, court decisions interpreting them and the financial engineering that takes place on Wall Street.” (de Glossop 2012, 17) The Efficient Market Hypothesis, made prominent by Eugene Fama, of the University of Chicago, defined its essence: that the price of a financial asset reflects all available information that is relevant to its value. (Scholes 2009) A more elaborate definition states:
An ‘efficient’ market is defined as a market where there are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future… in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value. (Fama 1965, 3)
In other words, financial markets tend towards equilibrium, in which assets are priced correctly. This would make it very difficult for market participants to outperform the markets, because whenever new information comes forth, news is spreading in such a quick manner that without delay it is being priced into the underlying securities. (Malkiel 2003) Within the Efficient Market Hypothesis there are three different versions: (Bodie, Kane and Marcus 2009, 231) First, the weak-form EMH asserts that stock prices already reflect all information in the history of past trading. Second, the semi-strong EMH asserts that stock prices already reflect all publicly available information. Third, the strong-form EMH asserts stock prices reflect all relevant information, including inside information. While Soros seems to refer to the strong-form EMH, economists and academics look at the EMH more comprehensively. This already leads to a problem from the beginning.
In regards to the Theory of Rational Expectations, John Muth first proposed it in the early 1960s. Economist Sargent defines the Rational Expectations Hypothesis as follows:
He [John Muth] used the term to describe the many economic situations in which the outcome depends partly on what people expect to happen. The price of an agricultural commodity, for example, depends on how many acres farmers plant, which in turn depends on the price farmers expect to realize when they harvest and sell their crops. As another example, the value of a currency and its rate of depreciation depend partly on what people expect that rate of depreciation to be. That is because people rush to desert a currency that they expect to lose value, thereby contributing to its loss in value. Similarly, the price of a stock or bond depends partly on what prospective buyers and sellers believe it will be in the future. (Sargent 2008, 1)
Soros generally disagrees with the Rational Expectations Hypothesis, but does not specify what aspects exactly he disagrees with.
In another regard, efficiency is also often being associated with the random walk theory, which states that in any given price series the future prices are randomly being extrapolated from past prices. In his book Fooled by Randomness
Nassim Taleb suggests that most actions, believed to be the result of skill, talent, and rationality, are actually lucky and coincidental happenings. (Young 2009) Burton Malkiel in his book A Random Walk Down Wall Street draws another analogy, in which he compares the performance of a blindfolded chimpanzee throwing darts to that of an expert. He concludes that on account of his theory, which says that markets follow a random walk the performances of the two are rather similar. (Malkiel 2003) From this theory we can extrapolate that stocks already reflect all available information and without adding additional risk unto the portfolio it seems impossible to outperform the markets by looking for undervalued securities. Thus that markets are rational and tend towards equilibrium are important properties of the current paradigm of economic theory.
Goldberg (2012) finds this postulate absurd because the EMH is based on the idea that individuals engage in profit-seeking behavior, but whenever market participants collectively do so, they are merely wasting their time. Goldberg refers to the observation that change within modern economies is to a large extent non-routine. This is something not accounted for by economists who vehemently support the Efficient Market Hypothesis. Goldberg cites the work of Knight, who emphasized that the ability to earn profits is coming from taking advantage of non-routine change. He also cites Keynes’s critique of Tinbergen’s attempt to build a fully predetermined econometric model of the US economy to show the importance of non-routine change. He argues that those non-routine changes alter the correlations in the data, and present temporary profit opportunities for those investors that are able to quickly act on them.
Frydman (2012) is also critical of economists, who in search of scientific worthiness sought economic models that attempted to generate sharp predictions, which “determine exactly all potential changes in outcomes and the probabilities with which they might occur — in the past, present and future all at once.” Those economists sought after a model that is able to predict the complete set of future market outcomes in probabilistic terms. And so he references Keynes to show that this kind of modeling is rather limited. Keynes wrote that we “cannot depend on strict mathematical expectations, since the basis for making such calculations does not exist.” He also cites Hayek whose work implies that mathematical models can only have a limited function in mimicking what financial markets do, and as Hayek confessed that he “prefer[s] true but imperfect knowledge… to a pretense of exact knowledge that is likely to be false.” (Frydman 2012)
Shi Chen (2007) in examining the efficiency of markets explores alternative approaches to modeling financial markets. He questions the assumptions that modern economics has set out that markets are efficient and humans act rationally. The conclusion that is then reached is that “under these conditions… competition among the many intelligent participants leads to an equilibrium where actual prices of individual securities already reflect the effects of information based both on past events and on future events expected to occur.” (Chen 2007) The problem then, according to Chen, is that economists generally believe in market efficiency and a lack of speculative opportunities. There he refers to a sub branch of economics, behavioral finance. This includes that agents sometimes do act in their self-interest to help others, and the observation that stock prices are not simply a function of all the available information, but also of how investors perceive that information.
According to Soros, the current paradigm of economic theory is trying to model itself after Newtonian physics and imitate the natural sciences by trying to establish, as he writes, “timelessly valid generalizations that can be used reversibly to explain and predict economic phenomena.” (Soros 2008, 53) One theme running through Soros’s work is the assumption of imperfect understanding, which he has derived from the works of Karl Popper. In his own words, “participants in financial markets act on the basis of imperfect understanding, which can lead their actions to have unintended consequences.” (Soros 2010, 57) Everyone who is active in financial markets will know that decisions that are made are being made in light of uncertainty. Soros also references game theory, which has taught us that human beings create uncertainties for one another. This uncertainty leads to differences in opinion, which in turn promotes communication, which synchronizes perceptions, which leads to trends ending in mispricing of assets and trend reversals. (Günter 2012) We also have to acknowledge, as Soros writes, that participants thinking is time-bound instead of timeless. Soros also criticizes mainstream economics in so far as they do not account for non-random price deviations from a theoretical equilibrium and generally there is no consideration for deviations away from equilibrium that are self-reinforcing.
Soros’s ideas have been confirmed through the works of other scholars. For example, de Glossop (2012) argues that the view that a capitalist economy resembles a stable general equilibrium system is inadequate to the reality of the nature of an economy that is harbored by the possibility of serious instability. Beinhocker asserts that the economy is not a closed equilibrium system, but a complex adaptive system. (Beinhocker 2007)
The Santa Fe Institute, under the leadership of Waldrop, builds on that assertion:
Instead of emphasizing decreasing returns, static equilibrium, and perfect rationality, as in the neoclassical view, the Santa Fe team would emphasize increasing returns, bounded rationality, and the dynamics of evolution and learning. Instead of basing their theory on assumptions that were mathematically convenient, they would try to make models that were psychologically realistic. (Waldrop 1993, 252)
It seems that in order for markets to be truly efficient, investors need to either share the same view of the future, or need to reach their views independently of each other. As we can assume that there is communication between investors, it seems that the latter criterion cannot be fulfilled. (Günter 2012) We can further point out that leading up to the bubble that popped in 2008, there have been many bubbles in the past in which the stock market often remained at levels far from intrinsic value. (Ford 2008) While economics is often perceived as a field predominated by mathematics, in which agents are independent and rational, many other disciplines have shown that economics cannot only be reduced to numbers. This is not saying that every economist does, but there is not yet a widespread acceptance that economics can benefit from other disciplines in a significant way.
While behavioral science suggests that our emotions exert more control than our cognitive sense, history shows that we tend to run in herds, and social psychology has observed that when we are faced with something unfamiliar, we copy each other. (Young 2009) This lies also at the heart of Soros’s critique that in order to derive a model that accounts for what is happening in the real world, economics needs to take from and consult with other social sciences as they hold much value in explaining trends and forces that were largely left unexplained by the mathematical-based economics models. While the current paradigm of economic theory still has value, there is nonetheless enough evidence or reason to support the introduction of an alternative theory that may better explain the dynamics of financial markets.
The Theory of Reflexivity
The origins of the theory of reflexivity dates to 1987 when George Soros’s first published The Alchemy of Finance. Back then it did not receive much critical consideration. With the onslaught of the recent financial crisis, however, and Soros’s continued efforts, reflexivity has been made increasingly prominent. Reflexivity, in general is defined as “a two-way connection between thinking and reality which, when it operates simultaneously, introduces an element of uncertainty into the participants’ thinking and an element of indeterminacy into the course of events.” (Soros 2008, 60) In more abstract terms, “thinking constitutes the subjective aspect, events the objective aspect… in other words, the subjective aspect covers what takes place in the minds of the participants, the objective denotes what takes place in external reality. There is only one external reality, setting up two-way feedback loops between them.” (Soros 2008, 62) Soros seeks to redefine what an economic model can and cannot predict:
The theory [of reflexivity] cannot hope to gain scientific acceptance, however, without a fundamental reconsideration of what is to be expected from a theory dealing with social phenomena… if reflexivity introduces an element of indeterminacy into social events, then those events cannot possibly be predicted in a determinate fashion… we cannot expect reflexive events to be determined according to timelessly valid generalizations when reflexivity contains an element of uncertainty and indeterminacy. (Soros 2008, 73)
Markets, as Soros writes, always operate with a prevailing bias, and in normal times markets tend to correct their own excesses, while at other times they tend to reinforce on that prevailing bias. Soros acknowledges that not every prevailing bias, or self-reinforcing trend will lead to a boom-bust cycle. Soros then argues that when that happens the prevailing bias can actually validate itself by influencing not only market prices but also the so-called fundamentals. When he is referring to the fundamentals it can be inferred that he is most likely referring to the perceptions of the fundamentals. For example, if earnings per share are one indicator of the fundamentals, then when the prevailing bias gets reinforced, the earnings per share will be perceived in a different way leading to higher market prices. This can then lead to an initially self-reinforcing trend, which is also known as the greater fool theory, meaning that investors purchase the stock only in anticipation that they can sell it to someone who will buy it at a higher price. However, this trend eventually ends as the boom ends in a bust. For Soros there are two kinds of feedback mechanisms. The first one is negative and self-correcting, while the second one is positive and self-reinforcing. While negative feedback sets up a tendency toward equilibrium, positive feedback produces dynamic disequilibrium. Soros then summarizes his two insights as follows: a) market prices distort the perception of the fundamentals and b) instead of playing a purely passive role in reflecting an underlying reality, financial markets also have an active role: they can affect the so-called fundamentals they are supposed to reflect. (Soros 2008)
Soros illustrates his theory of reflexivity and applies it to the recent financial bubble. First, every bubble has two components: an underlying trend that prevails in reality and a misconception relating to that trend. During the subprime boom, the increasing use of credit and leverage constitutes the prevailing trend, while the belief that financial markets are self-correcting and should be left to their own devices constitutes the prevailing misconception. According to Soros, the belief that markets could be safely left to their own devices was false, which gave rise to a series of financial crises prior to the subprime bubble. He references the international banking crises in the early 1980s, followed by the portfolio insurance debacle in October 1987, the S&L crises in 1989 and 1994, the emerging market crises of 1997/98 and the internet bubble in 2000. The prevailing misconception that markets should be left to their own devices was left intact or reinforced after each of these financial crises. Whenever the financial system was at the brink of collapse, the authorities rescued the system through monetary and fiscal stimuli. So in order for a boom-bust sequence to be set in motion there needs to be some form of credit or leverage being used and a misconception or misinterpretation employed.
For example, we can roughly illustrate the reflexive effects of the credit process. As the availability of credit widens, higher profits will yield higher asset prices, which will increase the amounts that are borrowed by investors and that money will find its way eventually into the financial markets. (de Glossop 2012) Another example of the reflexive process: “as borrowing stimulates economic activity, higher profits and asset prices also raise the value of collateral.” (Glossop 2012, 490) Glossop (2012) argues that borrowers’ creditworthiness can be positively affected by more lending, which may lead the borrowers to borrow even more. This in a nutshell represents Soros’s theory of reflexivity as it applies to financial markets.
Soros in Perspective
“To say something has failed you have to have something to replace it, and so far we don’t have a new paradigm to replace efficient markets.” writes Scholes (2009), of the famous Black-Scholes model. Eichengreen claims that Soros’s work is not adequately grounded in scholarly literature. Soros acknowledges that his theory does not qualify as scientific because it does not provide deterministic explanations and predictions. However, this already constitutes Soros’s criticism on the current paradigm of economic theory that economics cannot make predictions. It is for the simple reason that within a social science we are dealing with human beings, instead of objects that are fixed and contain predictable variables in hard sciences such as physics.
Despite the recent financial crisis, Soros’s theory of reflexivity is still not widely known. Most of the scholarly criticism that exists comes in the form of book reviews, and do not critique Soros’s theory in its entirety. Many critics use Soros’s son to discredit his theory:
My father will sit down and give you theories to explain why he does this or that. But I remember seeing it as kid and thinking, Jesus Christ, at least half of this is… I mean, you know the reason he changes his position on the market or whatever is because his back starts killing him. It has nothing to do with reason. He literally goes into a spasm, and it is this early warning sign. (Kaufman 2003, 45)
Economists and academics lament that occasionally Soros’s work is confusing. For example, when the bubble starts to develop and the earnings per share ratio increases, the stock price moves away from equilibrium. In the past, Soros has not always been clear on the distinction between far from equilibrium conditions and near equilibrium conditions. Today, Soros admits that the EMH can be valuable in conditions that are near equilibrium. This inconsistency may understandably have led to confusion. However this is nothing big to worry about. And it was no other than Ralph Waldo Emerson, who in his essay of self-reliance wrote: “foolish consistency is the hobgoblin of little minds, adored by little statesmen and philosophers and divines.” (Emerson 1841, 2)
Willett (2010) remarks that it is particularly unfortunate that in order to accept Soros’s theory, one must completely abandon traditional equilibrium economics. As financial markets can behave differently at different times, this proposition, according to Willett, appears sometimes narrow-minded. The problem Willet argues is that his theory of reflexivity has yet to be presented as a clearly defined concept. Economists also remark that Soros occasionally does not distinguish between economist’s different views. For example, they say that not many economists would adhere to the strong from EMH. It must also be stressed that many other non-economists share his dissatisfaction with how mainstream economic models are constructed. Others recognize that the financial system is in fact inherently unstable and usually due to credit that stability ends up in a self-reinforcing spiral towards instability. (de Glossop 2012, 489) Soros acknowledges that his theory has received no serious attention from academia since its inception and is rather ignored in department of economics. Economists say this is due to the fact that Soros’s is not writing in the language of an Economist. But then again, Soros is not an Economist to begin with, so it is hard to use that against him. Umpleby (2007) among the few, credits Soros’s theory by arguing that his theory provides links between cybernetics and economics, finance, and political science.
Soros’s theory draws from different fields and his experience to mold together his own theory that explains the dynamics of financial markets. For example, in sociology, reflexivity reflects the notion that individuals will act according to their calculations of how they believe others will act. (de Glossop 2012)
Mehrling gives Soros credit for his stance on imperfect knowledge, and his argument that the deliberate actions we take based on our understanding of the world can actually affect the world outside our window. (Mehrling 2012) Young (2007) also emphasizes a similarity between Soros and Minsky’s model of financial crises. Some of the criticism of Soros’s theory is rather harsh. Neely of the Federal Reserve Bank St. Louis regards his theory as “… full of long-winded philosophy and a naive critique of economics… [which] lacks detailed proposals for reform or analysis of the mechanics of financial markets.” (Neely 1998, 2) This comment seems to be ignorant of the rich value that can be found within Soros’s theory of reflexivity. Rather than providing the reader with his vast experience, Neely continues by saying that Soros “has deluged us with windy amateur philosophy and a profoundly mistaken critique of economics.” (Neely 1998, 3) Birshtein (2002) observed that Soros’s publication meet with constant annoyance among advocates of the orthodox economic and political theory. Soros himself has observed that many people regard his theory as nothing more than a common observation that the expectation of people is influenced by their perception. These accusations, however, do not seem to do Soros’s theory justice.
Kenneth Rogoff (2010) finds a similarity between the notion of self-fulfilling multiple equilibria and Soros’s notion of reflexivity. However, Soros thinks that equating self-fulfilling equilibria to reflexivity is not sufficient because the fallibility of market participants, regulators and economists must also be recognized. (Soros 2010) Soros does acknowledge that his theory builds on the work of others. He credits Robert Merton, who wrote about self-fulfilling prophecies and the bandwagon effect, and Keynes, who compared financial markets to beauty contests where the participants had to guess who would be the most popular choice. Keynes explains that concept in the following way:
“It is not a case of choosing those [faces] that, to the best of one’s judgment, are really the prettiest, nor even those that average opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth and higher degrees.” (Keynes 1936, 140)
Keynes believed that this analogy could be applied to the stock market, in which valuations of individual stocks are not necessarily always based on what the intrinsic value is but rather on what market participants think everyone else thinks their value is. There are many degrees one can extend this analogy, but this seems something that Soros is alluding to when he writes about the observation how reflexive processes can shift the perception of a fundamental, thus creating a bubble and move equities away of the equilibrium conditions.
Additionally Keynesian behavioral constructions of capital market behavior are clearly consistent with Soros’s theoretical interpretation. (Palley 2005) Jeffrey Frankel suggests that for many ideas that Soros puts forward theorists have actually developed models, to name a few: “bandwagon, rational speculative bubbles, second-generation speculative attacks, multiple equilibria and bank-runs.” (Frankel 1998, 4)
Eichengreen (1998) remarks that Soros’s boom-bust cycle resembles Kindleberger’s taxonomy of stages in financial speculation. Kindleberger in Manias, Panics and Crashes accounts for deviations from rationality occasionally when he writes: “mob psychology or hysteria is well established as an occasional deviation from rational behavior… optimism increases and may become self-fulfilling until it evolves into a mania.” (Kindleberger 1978, 43) Eichengreen argues that the portrayal of economics that Soros paints by which individuals are fully rational and markets characterized by stable equilibria seems far-fetched from how economics has developed. (Eichengreen 1998) Eichengreen shows the inadequacies by referring to “the work of behavioral economists like David Laibson at Harvard and Matthew Rabin at Berkeley on issues like impulsivity, procrastination, and risk aversion.“ (Eichengreen 1998) He also refers to Stiglitz, who made himself a name for his models of asymmetric information. He points to behavioral finance and Robert Shiller, and the work of Devanow and Welch that showed that market participants could still follow herding behavior despite rationality. They also show that emulating investment decisions of other investors can be in the self-interest of investors “when there exists information cascades… when there are payoff externalities, and when there is an incentive to engage in mimicking behavior.” (Eichengreen 1998, 10)
The Anatomy of a Bubble
Soros has tested his own theory of reflexivity against some of the major bubbles in financial history, but largely it has been tested against those bubbles when Soros was actively speculating in the financial markets. While it may have been useful to go further back in history to test his theory against financial bubbles such as the South Sea Bubble or Tulip Mania, there may not be enough data necessary to sufficiently analyze his theory. Therefore, a test of his theory against the dot-com bubble, a financial crisis that has not been expansively tested yet and presents enough rich data points to be worthwhile to be analyzed.
In the first part of this analysis, Soros’s theory of reflexivity will be explained in abstract terms as it applies to the financial markets. This will serve as a framework. Then, his model will be compared to two models from economists that have also analyzed the anatomy and nature of financial bubbles. This will put Soros’s theory into context. First, in Kindleberger’s Manias, Panics and Crashes, he illustrates Minsky’s model with the five distinct stages, which are in order of happening: disruption, boom, euphoria, profit taking and panic. Second, Economist Brunnermeier, who has specialized in financial crises and panics, has studied the anatomy of bubbles by dividing them up into two distinct phases: a run-up and a crisis phase.
Soros’s theory of reflexivity in financial markets, as illustrated in Figure 1, displays time on the x-axis and money on the y-axis. It shows comparatively the development of a stock price and earnings per share over time. The stock price development comes in eight distinct stages, which Soros has labeled: inception, a period of acceleration, interrupted and reinforced by successful tests; a twilight period, and the reversal point or climax, followed by acceleration on the downside culminating in a financial crisis. (Soros 2011, 5)
The graph illustrated in Figure 1 displays the boom-bust model that Soros describes in the following way:
I have developed a theory about boom-bust processes, or bubbles, along these lines. Every bubble has two components: an underlying trend that prevails in reality and a misconception relating to that trend. A boom-bust process is set in motion when a trend and a misconception positively reinforce each other. The process is liable to be tested by negative feedback along the way. If the trend is strong enough to survive the test, both the trend and the misconception will be further reinforced. Eventually, market expectations become so far removed from reality that people are forced to recognize that a misconception is involved. A twilight period ensues during which doubts grow, and more people loose faith, but the prevailing trend is sustained by inertia. As Chuck Prince, former head of Citigroup said: we must continue dancing until the music stops. Eventually a point is reached when the trend is reversed; it then becomes self reinforcing in the opposite direction. (Soros 2009, 2)
Figure 1: Soros’s model of boom and bust
Brunnermeier’s work on financial crises acknowledges that there are recurring themes and common patterns, and he distinguishes between a run-up phase, in which bubbles and imbalances form and a crisis phase, during which the crisis erupts. (Note: Brunnermeier’s most recent work seems to be the clearest, but many of his concepts also feature in his earlier work) Brunnermeier (2012) recognizes that the imbalances that lead to a financial crisis are hard to detect at the beginning, and is usually being rationalized due to innovation such as technological change, financial innovation or financial liberalization. A bubble then forms when the increased price in valuation exceeds the fundamental improvements. What he calls rational distortions when the price moves beyond the fundamental value are incentives such as expectations for a bailout, policies such as the “Greenspan put”, or over-leveraging or over-investment. Belief distortions also play an important role, which may arise from extrapolative expectations when agents as they have done leading up to the recent financial crisis extrapolated that house prices will not decline because they have never done so on a nationwide scale. (Brunnermeier 2012) The work of Rogoff and Reinhart (2009) also suggests that there is often a rationale by which market participants think that this time around it is different. Rogoff and Reinhart in their study of financial crises show that whenever market participants claim that old valuations hold no longer true and something fundamentally has changed they are rarely right, and most of the time proven wrong once the bubble pops. Brunnermeier refers to the sudden transition from a bubble into a crisis when risk and imbalances that have been built up become apparent. The beginning of the crisis phase Brunnermeier labels as the “Minsky moment”. The Minsky moment occurs the bubble is increasingly fueled by credit. The three phases preceding the Minsky moment can also be found within Kindleberger’s account of financial crises. In the first phase, investors take on debt but it is not a problem because they are able to meet their capital and interest payments. During the second phase, investors increase their finances, which leads them only to be able to afford interest payments. The third phase, also known as the Ponzi phase, occurs when investors are only able to finance their debt through rising prices. Brunnermeier then attributes amplification mechanisms as a major factor determining the magnitude of the crisis phase. Amplification mechanisms can either be direct or indirect. Classic depositor runs and domino effects are a good example of direct amplification mechanisms. The fire-sale liquidation of assets by one bank is an example of an indirect amplification mechanism because that liquidation may affect the portfolio of another bank. Brunnermeier, as well as Rogoff and Reinhart (2009) argue that credit seems to be a recurring ingredient that fuels financial bubbles and eventually leads into a crisis. Lastly, Brunnermeier argues that a financial crisis erupts rather suddenly and the recovery from it is a long drawn out process as the crisis leads to a reduction in economic activity.
Kindleberger (1978) recounts in his account of financial crisis Minsky’s five-stage model of boom and bust. The stage of displacement happens when a new technology or innovation causes investor’s expectations to be hopeful for the future. This disruptive technology has to draw two historical examples the railways and the Internet. As a matter of fact something occurs that alters the economic outlook and brings forward new profit opportunities. The second stage occurs when low volatility, and expansion of credit and investment lead to the boom phase. However slowly the increases in prices begin to exceed the actual fundamental improvements from the innovation. This leads to an expansion of banking credit. The phase of euphoria begins when prices begin to increase exponentially, and investors begin to notice that a bubble might be forming. But this will not deter investors from investing more as Minsky writes “there is nothing so disturbing to one’s well being and judgment as to see a friend get rich”. A positive feedback mechanism ensues, by which new investment increases income, which in turn leads to higher levels of investment. Investors buy assets in hope of selling it to a greater fool. The fourth phase begins when some of the speculators, who have invested early, begin to take profits. Insiders begin to sell, and speculators realize that prices can no longer rise the way they did in the past. Eventually, the boom will culminate into the panic phase, when investors frantically dump assets. Brunnermeier argues that in the Minsky model margin calls and weakening balance sheets lead prices to spiral down, and if the run-up was financed with credit, amplification and spillover effects, this can also lead to severe overshooting in the downturn. The Minsky model generates its own cycles, causing waves of credit expansion and asset price inflation, which perpetuates themselves, and so boom and bust are inherent in the system and stable economies effectively sow the seeds of their own destruction. (de Glossop 2012) In de Glossop’s account of Minsky, stability leads to instability, so if the financial system is left to its own devices it is more likely to end in a self-reinforcing bubble than a stable equilibrium.
The two models by economist Minsky and Brunnermeier overlap in many ways with Soros’s theory of reflexivity, but there still seems to be something distinct within Soros’s model of how financial markets operate.
The bubble that will serve as a case study against which Soros’s theory of reflexivity will be tested is the dot-com bubble that occurred at the turn of the century. It will be necessary to look at a selection of stocks, and observe whether or not the relationship between the stock price and earnings per share follows the pattern from Soros’s theory of reflexivity as can be found in Figure 1. However, as many companies in the NASDAQ index did not report profits and their valuations were not supported from strong fundamentals, it will be necessary to use a proxy for NASDAQ stocks. Calandro (2003) in his study of business cycles and the new economy suggests that the blue chips of the DJIA can serve as a good proxy because there is actually a long-term trending consistency between the two indices. Therefore for the purposes of this analysis the same proxy will be used to test Soros’s theory of reflexivity.
Soros’s first stage is the inception period, in which the trend that is beginning to form is not yet recognized but is gently sloping upwards. The underlying trend was the Internet that by 1995 was not fully recognized by market participants. If we look at the NASDAQ market behavior during 1995, it was rather flat. Calandro also argues that this behavior was due to Greenspan’s soft landing doctrine in 1994 to counter expected price inflation by hiking up interest rates. When the Fed reversed their course of action and expanded credit by increasing the money supply, the DJIA began to what Soros calls gently slope upwards. According to Calandro (2003), the trend, or rather boom that came to be known as the “New Economy” began when consumer spending significantly increased through a new distribution channel, the Internet. Start-ups such as Amazon and eBay that were founded in 1995 and 1994, respectively, soon took the center stage in the boom that followed.
Source: Calandro (2003)
(Note: The momentum below the chart refers to the rate by which the price of the stock is rising or falling)
The second stage is the period of acceleration, and starts when market participants begin to recognize the trend. This awareness, in turn, changes the perception of the underlying fundamental. Calandro (2003) tells the story of Netscape, and how its spectacular IPO and subsequent rise led other entrepreneurs to build similar companies. Soros argues that this leads to a self-reinforcing process, by which the positive bias pushes stock prices into a far from equilibrium state. The NASDAQ and DJIA rose subsequently until mid-1998 when a short-term price top had build up. The short-term price top is displayed in Calandro’s chart with the small arrow and it is important because it represents the first major test of whether or not the trend of higher prices will be continued or not. If the stock prices do not surpass this short-term top, then prices will not move further upwards, and it is likely that a bubble will not be formed. However, it is not entirely certain how the short-term top can be recognized in advance though.
Once the short-term price top has been made, this is when the third stage begins, where Soros writes that prices decline due to an external shock. In the dot-com bubble the short-term top occurred at the psychologically significant price level of 2000. Calandro argues that the upswing preceding the top occurred on low momentum, while the correction following the top occurred on strong momentum leading to a market correction of more than twenty five percent. According to Soros, if the bias and trend is strong enough, prices will mark new highs, which will lead to further self-reinforcement and higher prices. Although many tech companies at the time did not report earnings, it was the perception that their strong revenue growth in the future would continue that led many market participants to buy into the bubble. Calandro then argues that after the market bottomed out in mid-1998, the NASDAQ and DJIA marked a new all-time high.
In Soros’s model we then enter the fourth stage, a period of acceleration, which begins after the test has been successfully survived, the test being marking a new high after surpassing the short-term top. The trend and bias then become stronger, and the underlying trend becomes increasingly influenced by share prices, while share prices move further away from equilibrium. Calandro explains that after the short-term top was surpassed, technically oriented traders started to buy aggressively. Whether one believes in it or not, there are many traders who buy stocks based on technical analysis. Since the NASDAQ also recorded high momentum many traders were purchasing stocks simply because other people were purchasing them.
According to Calandro, the market entered the fifth stage in Mid-1999, when first the divergence between the NASDAQ and DJIA began to grow historically large, and second two popular fundamental substitutes emerged. Soros characterizes the fifth stage as one in which expectations drive stock prices to a level far from reality and fundamentals. The first fundamental substitute is called “eyeballs” valuation. In eyeball valuation, Calandro analyzed, a valuation of a stock would be based off how many times an individual Internet user visited the website of that company. The real options theory was used as a second theory of fundamental substitute that was in Calandro’s view abused by market participants.
Calandro also draws an analogy between the new economy and new era bubble by referring to Benjamin Graham’s work on security analysis. He finds similarities between the two bubbles, which shows that Soros’s model of reflexivity may possibly be applied towards the new era bubble, as well.
The “new era” doctrine — that “good” stocks (or “blue chips”) were sound investments regardless of how high the price paid for them — was at bottom only a means of rationalizing under the title of “investment” the well nigh universal capitulation to the gambling fever. We suggest that this psychological phenomenon is closely related to the dominant importance assumed in recent years by intangible factors of value, viz., goodwill, management, expected earning power, etc. Such value factors, while undoubtedly real, are not susceptible to mathematical calculation; hence the standards by which they are measured are to a great extent arbitrary and can suffer the widest variations in accordance with the prevalent psychology. The investing class was the more easily led to ascribe reality to purely speculative valuations of these intangibles because it was dealing in good part with surplus wealth, to which it was not impelled by force of necessity to apply the old established acid test that the principle value be justified by the income. (Graham and Dodd 1934, pp. 11–12)
What is also characteristic of the fifth stage is a phase of irrational exuberance, a term that was famously used by Alan Greenspan, and then used for a title of a book by Economist Shiller. Calandro also remarks that the momentum during that upswing was consistently positive, reflecting enormous buying on margin.
In what is known as the twilight period, or the sixth stage, participants slowly realize that expectations are too high, which brings a period of stagnation forth. This happened during the dot-com bubble when the Fed reversed their course of action by increasing the Fed Funds rate. According to Calandro, it was just a matter of time until the market would reverse given the change in policy of the Fed. The seventh stage, the climax or reversal, needs an external shock that reversed the course of the stock price. The market topped in March of 2000, and Enron and its fraudulent accounting practices, as Calandro remarks, marks one of the inflection point from which the market turned downwards. Eventually stock prices start to decline, Soros observes, and a financial crisis ensues, which constitutes the eighth and final stage. This occurred when the NASDAQ hit its all-time high in March.
Results
Ever since the global financial crisis that began with the subprime mortgage crisis in the United States in the fall of 2007, the current paradigm of economic theory has — at least partially — been discredited. After writing the thesis, I may acknowledge that it has not been fully discredited, but enough to warrant alternative theories to shed some light on explaining the dynamics of financial markets, and in particular financial bubbles. Soros (2009b) admits that despite the fact that his model has received increased attention, it still lacks serious attention from the economics profession. He attributes this to three reasons: First, his opponents claim that Soros is merely stating the obvious in that market prices reflect the participants’ biases. Soros, however, states that that is misunderstanding his theory. Second, Soros claims that his opponents accuse him that his theory is already incorporated within other existing models. This may be true to a certain degree as we have seen with the existing models of Brunnermeier and Minsky. As in regards to the case study, it has been very difficult to draw conclusive results not only because only one financial bubble, i.e. dot-com bubble, was being used but also on the account of the match that exists between the models of Brunnermeier and Minsky and Soros’s model.
Third, Soros acknowledges that the most sympathetic objection consists of the observation that his model cannot be formalized and modeled. However, therein lies Soros’s distinct point that financial markets, which consist of thinking participants, cannot be deduced to a purely quantitative model. He states that Knight and Keynes were aware of that fact, but rating agencies and regulators alike in order to calculate risks rely upon — sometimes even purely — quantitative models. (Soros 2009b) Its simple: reflexivity by its very nature cannot be modeled in the abstract. Soros, however, does not dismiss the quantitative models altogether, as he writes that they are quite useful for near-equilibrium conditions, but those same quantitative models cannot account for conditions when markets occasionally move away from equilibrium. That is also something underlined by Willett (2010), who notes that markets can behave in different ways at different times and conditions, therefore warranting different types of models that may be applicable to explain how markets function. Soros understands that his model is not entirely unique and certain aspects are similar to behavioral economics and theories based on evolutionary systems. According to Soros behavioral economics alone is insufficient as it leaves out important insights. For example, Soros argues that behavioral economics cannot explain why Long Term Capital Management blew up, whereas his theory can. According to Soros, financial markets are “far from being merely passive reflections of underlying conditions, constitute an active force that changes the course of history. Markets often force managements, and even governments to act in specific ways to address their concerns.” (Soros 2009b, 218)
In his work on financial bubbles Niall Ferguson (2008) has discovered that money’s ascent has rarely been a smooth one and he has identified three fundamental causal reasons. The first reason is that “so much about the future — or rather, futures, since there is never a singular future — lies in the realm of uncertainty, as opposed to calculable risk.” (Ferguson 2008, 342) To make his point, he references Knight and later Keynes, who wrote that:
… I do not mean merely to distinguish what is known for certain from what is only probable. The game of roulette is not subject, in this sense, to uncertainty… The expectation of life is only slightly uncertain. Even the weather is only moderately uncertain. The sense in which I am using the term is that in which the prospect of a European war is uncertain, or… the rate of interest twenty years hence… About these matters there is no scientific basis on which to form any calculable probability whatever. We simply do not know. (Ferguson 2008, 344)
The second reason is about human behavior. He argues “all financial institutions are at the mercy of our innate inclination to veer from euphoria to despondency; our recurrent inability to protect ourselves against ‘tail risk’; our perennial failure to learn from history.” (Ferguson 2008, 345s) The element of fallibility that is emphasized again and again in Soros’s work seems to be confirmed by Ferguson, who lists ten biases that display the cognitive traps humans commit. These are: availability bias, hindsight bias, the problem of induction, the fallacy of conjunction, confirmation bias, contamination effects, the affect heuristic, scope neglect, overconfidence in calibration, bystander apathy. (Ferguson 2008, 346) The last one ‘bystander apathy’, which leads people to dismiss responsibility of individuals when in a crowd, is similar to insights by behavioral economics such as herd behavior. Ferguson then concludes that these biases play an important role in contributing to the high volatility that is sometimes experienced in financial markets. Ferguson also cites Eliezer Yudkowsky who succinctly summarizes the fallibility of human beings in the following way:
People may be overconfident and over-optimistic. They may focus on overly specific scenarios for the future, to the exclusion of all others. They may not recall any past [liquidity crises] in memory. They may overestimate the predictability of the past, and hence underestimate the surprise of the future. They may not realize the difficulty of preparing for [liquidity crises] without the benefit of hindsight. (Ferguson 2008, 347)
Ferguson’s third reason is related to the theory of evolution in that certain aspects within finance are often equated as Darwinian such as the concept of the survival of the fittest. This is also picked up by Soros’s work, which acknowledges Andrew Lo’s work on the “Adaptive Markets Hypothesis”, or AMH in short. Scholes (2009) discusses how Andrew Lo’s work on the AMH neither assumes that humans are fully rational or irrational and therefore seems to constitute a compromise. Ferguson further cites Schumpeter who characterized industrial capitalism as an evolutionary process. Ferguson then gives an example by stating how much destruction occurs in modern economies: “around one in ten US companies disappears each year. Between 1989 and 1997, to be precise, 611,000 businesses a year vanished out of a total of 5.73 million firms.” (Ferguson 2008, 349)
Nevertheless, Soros in relation to the AMH is rather afraid of it in so far as it may overshadow his own theory since it possesses stronger modeling power. (Soros 2009b) He expresses his fear in the following way:
Central to my worldview is the idea that human affairs — events with thinking participants — have a fundamentally different structure from natural phenomena. The latter unfold without any interference from human thought; one set of facts follows another in the causal chain. Not so in human affairs. The causal chain does not lead from one set of facts to the next, but connects the situation and the participants’ thinking in a two way, reflexive feedback loop… since there is always a divergence between the participants’ view and the actual state of affairs, reflexivity introduces an element of uncertainty into the course of events that is absent in natural phenomena. I am afraid this idea may get lost in the AMH, because evolutionary systems theory does not distinguish between human and natural phenomena. It deals with the evolution of populations whether they consist of microbes or market participants… social systems are different: They may not serve their purpose well, yet they may survive indefinitely… In other words, markets may be maladaptive. This is the distinction that the AMH fails to recognize. (Soros 2009b, 284)
This seems to be one distinct element within Soros’s theory in that his conceptual framework makes a clear difference between mechanical and social constructs. Neither the EMH, nor the AMH do that. In fact, they are trying to apply to the social sphere “an approach that was successful in another field — the EMH draws from Newtonian physics, the AMH on evolutionary biology.” (Soros 2009b, 285) Ferguson seems to support Soros in a way that there is a big difference between nature and finance. He writes that in evolutionary biology change is random, whereas “evolution in financial services occurs within a regulatory framework where to borrow a phrase from anti-Darwinian creationists — intelligent design plays a part.” (Ferguson 2008, 350)
Finally Soros admits that reflexivity does not conform to the currently accepted standards of scientific theory. And therein lies the difference. Soros is arguing that we must modify or study financial markets in a nonscientific way — at least occasionally. What this would entail is a restoration of philosophy to its preeminent position. In his words, “my conceptual framework could then serve as the new philosophical paradigm for understanding human affairs in general and financial markets in particular. “ (Soros 2009b, 286) What Soros might then be suggesting is that to understand how financial markets operate we need a more philosophical, and less scientific approach.
Conclusion
It is impossible to draw conclusive results from a thesis with such a limited scope of research, and especially drawn from only one case study. This thesis had elements that were quantitative such as the case study with the dot-com bubble, and qualitative elements such as Soros’s work on reflexivity in financial markets overall. I have provided an account of what a bubble consists of, and set the thesis into the appropriate framework by asking the question that Queen Elizabeth II had asked: why had nobody noticed that the credit crunch was on its way? This led me to present and question the existing paradigm of economic theory: the Efficient Market Hypothesis and the Rational Expectations Theory. From there, I have analyzed and discussed Soros’s theory of reflexivity and evaluated his work through the lenses of other scholars and academics. It has been challenging to match and compare a purely academic theory such as the EMH with the theory of reflexivity that stems largely from Soros’s work as a financial speculator. I have successfully tested Soros’s model with the dot-com bubble, and compared his model to Brunnermeier and Minsky’s model. However, as the test stood only against one historical financial bubble, it is not appropriate to claim that Soros’s model can explain any financial bubble. Nevertheless, it has given interesting insights, and there is certainly value in certain aspects of Soros’s theoretical work on financial markets. In the results section, I have tried to show what aspects of his model and theory are distinct and make him different to others. The insight is very telling that models, which are trying to explain the dynamics of financial markets, need to distinguish between mechanical and social constructs. In addition, his more impressionistic observation that philosophy rather than science should be emphasized in order to better understand financial markets has not been fully appreciated yet. As a speculator Soros has been incredibly successful, as a philosopher, however, his ideas are still not widely known and appreciated. Many academics and economist can learn from Soros’s conceptual framework if they overlook the fact that he is not one of them. He has had many decades of experience in the financial markets as a speculator and distilled that experience into a very rich, even if sometimes hard to understand theory. An alternative way of how markets work, drawn from Soros’s in-depth understanding that he needed to have to succeed as a speculator in the markets, can only enhance our understanding of how financial markets work.
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