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Neoclassical Finance and Reality Lecture 1: The relative strengths of neoclassical and behavioral finance for understanding bubbles and systemic crises. Robert Shiller, Yale University Princeton Bendheim Lectures in Finance, October 8, 2013. Neoclassical Finance and Reality.
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Neoclassical Finance and RealityLecture 1: The relative strengths of neoclassical and behavioral finance for understanding bubbles and systemic crises Robert Shiller, Yale University Princeton Bendheim Lectures in Finance, October 8, 2013
Neoclassical Finance and Reality • The title of these three lectures is inspired by the first Princeton Bendheim Lectures in Finance, Stephen Ross “Neoclassical Finance” and by Christopher Sims’ 1980 Econometrica article “Macroeconomics and Reality”
Stephen A. Ross Neoclassical Finance, Lecture 2001, PUP 2004 • No arbitrage opportunities • “Information efficiency” • “Private information that is relevant and has yet to be revealed” explains volatility
Ross, Neoclassical Finance, Continued • “Since it [neoclassical finance modeling] has fewer degrees of freedom in its unspecified parameters, it should be easier to reject in empirical estimation. Most importantly, though, is the question of what the theory does not allow. The appeal to investor sentiment seems almost limitless in its ability to explain just about anything. Once we have jettisoned the discipline of a market in which arbitrage is eliminated, we can reverse-engineer any observed pattern of prices and deduce a demand structure that would support it. Furthermore, psychology is sufficiently imprecise in its predictions of human behavior that it places no brake on this activity. P. 93.
Christopher A. Sims Macroeconomics and Reality 1980 • “..though large scale statistical macroeconomic models exist and are by some criteria successful, a deep vein of skepticism about the value of these models runs through that part of the economics profession not actively engaged in constructing or using them. • “I will argue that the style in which their builders construct claims for a connection between these models and reality—the style in which ‘identification is achieve—is inappropriate, to the point at which claims for identification in these models cannot be taken seriously.”
Outline of the Three Lectures • (Today) The relative strengths of neoclassical and behavioral finance for understanding bubbles and systemic crises • (Tomorrow) Why don’t sound financial innovations get adopted? • (Thursday) Phishing for Phools: the economics of manipulation and deception (forthcoming book with George Akerlof)
Some Components of Neoclassical Finance Have Been Rejected • Edward Miller 1971 pointed out that short sales restrictions eliminate possibilities for “smart money” to bring overpriced stocks down • There are many short-sale barriers [Jones and Lamont JFE 2002] • In absence of barriers, short-sale strategies do work [Diether Lee and Werner JFE 2001] • Many other behavioral anomalies • Value investing has paid off for century • Higher test-scoring institutional investors have better average performance (Chevalier and Ellison)
Neoclassical Economics • First use of term: Thorstein Veblen “Preconceptions of Economic Science” QJE 1900 “It is no longer that certain phenomena belong within science, but rather that the science is concerned with any and all phenomena as seen from the point of view of economic interest.” (pp.262-3) • Wikipedia: “Neoclassical economics is a term variously used for approaches to economics focusing on the determination of prices, outputs, and income distributions in markets through supply and demand, often mediated through a hypothesized maximization of utility by income-constrained individuals and of profits by cost-constrained firms employing available information and factors of production, in accordance with rational choice theory”
Neoclassical Economics and Neoclassical Finance, Google Ngrams
Thomas Sargent “Interpreting Economic Time Series” JPE 89(2):213-48 1981 • “The private agents are assumed to face nontrivial dynamic and stochastic optimization problems. . . It seems that there is potential for specifying dynamic preferences, technologies, constraints and rules of the market game that roughly reproduce the serial correlation and cross-correlation patterns in a given collection of time series measuring market outcomes.” p. 215
Epidemics and Word of Mouth • Spread of ideas is similar to spread of infectious diseases • “Memes” (Richard Dawkins, The Selfish Gene, 1976) and “thought viruses” replicate as do viruses • Mathematics of epidemiology is therefore relevant to economics
SIR Model (Susceptibles, Infectives, Removed) Kermck and McKendrick, 1927 • n individuals, x susceptibles, y infectives, z no longer contagious, n=x+y+z. Infection rate is β, removal rate is γ, and define the relative removal rate ρ=γ/β. • dx/dt=-βxy • dy/dt=βxy-γy • dz/dt=γy
Properties of SIR Model • No epidemic can start unless relative removal rate ρ < x0 (the initial number of susceptibles) • In an epidemic, number of infectives first rises, then falls. • Epidemic peaks when x falls below ρ • “Size of epidemic” z∞ is the total number of people who eventually contract the disease • Size relative to population is determined by ρ, low ρ promoting large size
Economics of Rumors Abhijit V. Banerjee REStud 1993 • [In earlier literature on epidemic models in economics], no attempt is made to derive an optimal decision rule for each decision maker. In this paper, the decision to believe in the rumour and to pass it on is based on optimizing behaviour.” • Banerjee wants to incorporate epidemic models into neoclassical economics, all players are true Bayesians
Individuals agreeing with the statement: “The stock market is the best investment for long-term holders, who can just buy and hold through the ups and downs of the market”
Individuals agreeing with the statement: “The Housing market is the best investment for long-term holders, who can just buy and hold through the ups and downs of the market”
How would one ever calculate the probability that the statements above are true? • The statements represents memes, that have intuitive sense of truthfulness • They are evaluated by Daniel Kahneman’s System 1, instantaneously, without computations, not System 2, Thinking Fast and Slow, 2011
Dawkins: Memes and Memetics • Term Meme was coined by Richard Dawkins in The Selfish Gene 1976 • A meme is the cultural analogue of a gene “good ideas,” “good poems,” “mantras,” any mutation that is spread by replication from brain to brain • Socrates genes may be gone, his memes live on • Dawkins 2013 says the term was “hijacked” with “Internet meme” which is different in that it they are deliberately altered, not result of mutation
Excerpts from WSJ Story on Shutdown & Markets Oct 5-6 2013 • “Many investors say stocks remain buoyant because they expect the Federal Reserve to continue its efforts to support the economy . .” [Rather than my metaphor: Ben Bernanke is like nothing more than the janitor who could turn down the thermostat in a conflictual conference room at a tense moment.] • “The reason [markets aren’t reacting] is, we’ve seen this coming from a mile away.”
Implications of Keynesian Beauty Contest Metaphor for Speculative Trading • On Aug. 4, 2011, the market, as measured by the Standard & Poor’s 500-stock index, fell by almost 5 percent. The next day was quiet, but the following Monday, the index dropped almost 7 percent. In successive days, it rose 4.7 percent, fell 4.4 percent and rose 4.3 percent. after the near-default. • Keynesian beauty contest • Peculiar timing of public reaction to near default may repeat this month
Alan Greenspan, Aug 7, 2011 (just before the nearly 7% drop) • “What I think the S.& P. thing did was to hit a nerve that there’s something basically bad going on, and it’s hit the self-esteem of the United States, the psyche.” “And it’s having a much profounder effect than I conceived could happen.” • He was talking about what other investors were thinking, not about the substance of the S.& P. downgrade.
Franklin Allen, Stephen Morris, and Hyun Song Shin “Beauty Contests and Iterated Expectations in Asset Markets” RFS 2006 • This paper attempts to transform Keynes beauty contest story into neoclassical economics, with a “fully rational asset pricing model” • Stresses failure of the law of iterated expectations for average belief
The Economist June 16, 2005 • “PERHAPS the best evidence that America's house prices have reached dangerous levels is the fact that house-buying mania has been plastered on the front of virtually every American newspaper and magazine over the past month.”
Time Magazine, June 13, 2005 • “HOME $WEET HOME: Why We’re going gaga over real estate • Will your house make you rich? • Super hot markets. • Is it time to buy or sell? • The case for renting”
Barrons, June 20, 2005 • “Economist Robert Shiller whose book predicting a stock market rout arrived just before the Nasdaq began its sickening slide in 2000, sees another bubble ready to burst. Home prices, he contends, could fall by as much as 50% adjusted for inflation.” • (Ex post: Actual US peak to trough decline was 43%, over 50% in many cities)
Percentage of Respondents’ Unprompted Use of “Housing Bubble” in Open-ended Questions
Percent of Respondents Unprompted Use of “Land” (usually as in “land shortage”) in Open-Ended Questions
Google Trends: Web Searches for “Housing Bubble” peak Aug 2005
Giorgio Vasari biography of Leonardo, smile “more divine than human” Vasari’s description of painting shows serious discrepancies with painting we view today Celebrities Example: Mona Lisa’s Smile
Two Events in 1910 Increase Infection Rate for Mona Lisa • Theft of Mona Lisa from Louvre, leads to international manhunt that results in capture of the thief in 1914. • Publication of book about Leonardo by Sigmund Freud said Mona Lisa’s smile was reaction to suppressed memory of Leonardo’s mother, who had an unnatural affection for her son • Newspaper references to Mona Lisa increased twenty-fold between 1899-1909 and 1915-1925
Conclusion • Epidemic models highly relevant to the kinds of things that shock the economy • Information cascades add a rational component • Information interacts with epidemic models to produce social changes • New information technology changes the kinds of ideas and trends that show high contagion rates