In this undergraduate course, Professor Steve Keen exposes students to the emerging field of market analysis that examines financial decision making through the lens of cognitive and behavioral psychology.
This is the first of about 20 videos of my lectures in Behavioural Finance at the University of Western Sydney (2 videos per lecture). This first lecture presents the Neoclassical theory of consumer behavior-known as Revealed Preference-and an experiment that invalidated it by the German economist Reinhard Sippel.
In this second half of the first lecture, I explain Sippel's result that most people aren't "rational" as Neoclassical economists define it-because the Neoclassical definition of rational behavior is computationally impossible. The next lecture-which I'll post next week-explains that even if the Neoclassical model of individual behavior was sound (which I've just shown it isn't), the market demand curve derived by aggregating the demand functions of "rational utility maximizing individuals" could have any shape at all. The "Law of Demand",a cornerstone of Neoclassical thought, is false.
In the last lecture I showed that the Neoclassical model of consumer behavior doesn't work, and is computationally impossible. In this lecture, I show that even if it did work, a market demand curve derived by aggregating the demands of numerous utility-maximizing individuals can have any shape at all. The so-called Sonnenschein-Mantel-Debreu conditions (first discovered in 1953 by Gorman) show that even market demand can't be represented by the demand of a single utility-maximizing consumer-yet Neoclassical DSGE models treat the entire economy as a single utility maximizer.
In this half of the lecture, I show that even if there was a downward-sloping demand curve, Neoclassical supply and demand analysis is still invalid because: (a) Equating marginal cost and marginal revenue doesn't maximize profits; and(b) A market supply curve can't be derived independently of the demand curve.
The CAPM and EMH stick to the neoclassical script of believing that the economy and finance markets are stable, at or near equilibrium, and on this basis argue that "you can't beat the market". But there is an alternative view, far more aligned with the actual data, that says that markets are chaotic, far from equilibrium systems, and for that reason it's very hard to beat the market.
Eugene Fama was an enthusiastic promoter of CAPM and the Efficient Markets Hypothesis, arguing that despite their absurd assumptions, the data supported the theories. But was this a fluke, the result of the narrow data range he used-from 1950 till 1966? He has since disowned the theory in 2004, stating that "the theory has never been an empirical success", and that "most applications of the theory are invalid". But somehow these honest statements don't seem to have made it into the finance textbooks.
The Fractal Markets Hypothesis and the Inefficient Markets Hypothesis are two of several attempts to provide a realistic theory of how finance markets actually behave. In this first half of the lecture, I explain what a fractal is, and discuss their basic characteristics.
In this second half of the lecture, I outline the Fractal Markets Hypothesis and the Inefficient Markets Hypothesis (IEH). The IEH suggests precisely the opposite investment strategy to the EMH on how to maximize returns on the stock market: invest in low volatility, high Book to Market stocks.
One year after the start of the greatest economic crisis since the Great Depression, the editor of the American Economic Review: Macroeconomics claimed that "the state of macro [theory] is good". How could be be so deluded? Macroeconomics has been distorted by appalling scholarship and a misguided belief that macroeconomics and microeconomics should be consistent. The best critics of this, ironically, are given by the authors most responsible for the state of macroeconomics, John Hicks and Robert Solow.
Given how appallingly bad neoclassical economics is, an alternative economics that is at least roughly capable of reproducing the actual performance of the economy is badly needed. One of the best studies of the empirical data about the economy was ironically undertaken by the two neoclassical economists who developed Real Business Cycle theory, Kydland and Prescott. This lecture reports their findings, focusing on the conclusion that "credit should play a larger role" in future analysis of the business cycle. I then outline the basic propositions in the theory of endogenous money.
Endogenous money is an established empirical fact, but a seriously underdeveloped concept in economics. In this lecture I cover some of the foundational disputes that marked the development of the concept, and then introduce Graziani's brilliant concept of the Monetary Circuit as a foundation for a monetary model of capitalism.
Though the basic ideas of the Monetary Circuit are brilliant, when it came to turning these into a model of the monetary circuit, the Circuitists made numerous errors that were the result of them not knowing how to model a dynamic process. I outline these errors and then introduce the basic tool of dynamic modelling, the differential equation.
Explaining the "Monetary Circuit Theory" of capitalism. I show that the dilemmas that hobbled Circuit Theory for so long were simple mistakes in dynamic modelling, which reflect poorly not so much on Circuit theorists themselves, but economists in general, since even non-orthodox economists are locked into the static ways of thinking they were taught by neoclassical lecturers.
Extending the model developed in the first half of the lecture to include payment of wages and consumption. The resulting model "works" in that it is possible for capitalists to borrow money, produce output, and make a profit.
I continue the development of the QED model of a pure credit economy began in the last lecture, including modelling production and developing a pricing equation to produce a combined monetary-physical model. The initial model has a fixed wage, population and labor productivity. To prepare the way for making these variables, I explain what Bill Phillips of "The Phillips Curve" was really trying to do: to drag economists into the modern era by teaching them how to model the economy dynamically.
I use the model developed in the first half to show that money is not neutral in a credit-based economy-a higher rate of money creation results in a fall in unemployment-and also model a credit crunch. I also model two government policies to counter a crunch: giving money to the banks (which Obama did) and giving it to the debtors (which the Australian government did). Conventional money multiplier theory argues that the former is more effective; I show that the latter is about three times better than the former.
I discuss the economists who influenced Minsky-Marx, Fisher, Schumpeter and Keynes-as a prelude to outlining Minsky's Financial Instability Hypothesis.
Having outlined Minsky's Financial Instability Hypothesis, I explain the mathematical model I developed of it, on the foundation of Richard Goodwin's "Growth Cycle" model of capitalism.
The remarkable thing was not that I and a handful of others saw this crisis coming, but that so many neoclassical economists had no idea it was approaching. I explain why they failed to see it (by ignoring private debt and believing in a fantasy of economic equilibrium), discuss the empirical dimensions of this crisis in comparison with the Great Depression, and present my explicitly monetary macroeconomic model.
John von Neumann developed Expected Utility theory to wean economists off indifference curve analysis and onto a numerical basis for utility. Instead, they combined indiffiference curves with absurd assumptions about individual behavior in asset markets and a confusion of risk with uncertainty to develop the Capital Assets Pricing Model.
CAPM appeared to fit the statistical evidence for a the period prior to its development, enabling its supporters to champion it and leading to it taking over the profession? But was this just a fluke, resulting from the short time period considered by the statisticians? It has since been challenged by Behavioral Finance, but it seems that this school has also misunderstood John von Neumann's work. Once objective probability is used as he intended, rather than subjective probability, all the so-called paradoxes of Behavioral Finance disappear. I also outline John Blatt's method of accounting to some extent for uncertainty, and show that-contrary to conventional opinion-the Payback Period is superior to Net Present Value because it takes account of uncertainty as well as the time value of money.