A Study Of Neo Austrian Economics Using An Artificial Stock Market

An agent-based artificial financial market (AFM) is used to study market efficiency and learning in the context of the Neo-Austrian economic paradigm. Efficiency is defined in terms of the excess profits associated with different trading strategies, where excess is defined relative to a dynamic buy and hold benchmark in order to make a clean separation between trading gains and market gains. We define an Inefficiency matrix that takes into account the difference in excess profits of one trading strategy versus another (signal) relative to the standard error of those profits.

An agent-based artificial financial market (AFM) is used to study market efficiency and learning in the context of the Neo-Austrian economic paradigm. Efficiency is defined in terms of the excess profits associated with different trading strategies, where excess is defined relative to a dynamic buy and hold benchmark in order to make a clean separation between trading gains and market gains. We define an Inefficiency matrix that takes into account the difference in excess profits of one trading strategy versus another (signal) relative to the standard error of those profits (noise) and use this statistical measure to gauge the degree of market efficiency. A one-parameter family of trading strategies is considered, the value of the parameter measuring the relative informational advantage of one strategy versus another. Efficiency is then investigated in terms of the composition of the market defined in terms of the relative proportions of traders using a particular strategy and the parameter values associated with the strategies. We show that markets are more efficient when informational advantages are small (small signal) and when there are many coexisting signals. Learning is introduced by considering copycat traders that learn the relative values of the different strategies in the market and copy the most successful one. We show how such learning leads to a more informationally efficient market but can also lead to a less efficient market as measured in terms of excess profits. It is also shown how the presence of exogeneous information shocks that change trader expectations increases efficiency and complicates the inference problem of copycats.

The Austrian School of Economics is an intellectual tradition in economics and political economy dating back to Carl Menger in the late-19th century. Menger stressed the subjective nature of value in the individual decision calculus. Individual choices are indeed made on the margin, but the evaluations of rank ordering of ends sought in the act of choice are subjective to individual chooser. For Menger, the economic calculus was about scarce means being deployed to pursue an individual's highest valued ends. The act of choice is guided by subjective assessments of the individual, and is open ended as the individual is constantly discovering what ends to pursue, and learning the most effective way to use the means available to satisfy those ends. This school of economic thinking spread outside of Austria to the rest of Europe and the United States in the early-20th century and continued to develop and gain followers, establishing itself as a major stream of heterodox economics. The Oxford Handbook of Austrian Economics provides an overview of this school and its theories. The various contributions discussed in this book all reflect a tension between the Austrian School's orthodox argumentative structure (rational choice and invisible hand) and its addressing of a heterodox problem situations (uncertainty, differential knowledge, ceaseless change). The Austrian economists from the founders to today seek to derive the invisible hand theorem from the rational choice postulate via institutional analysis in a persistent and consistent manner. Scholars and students working in the field of History of Economic Thought, those following heterodox approaches, and those both familiar with the Austrian School or looking to learn more will find much to learn in this comprehensive volume.

The form of ‘reflexivity’ – defined by the dictionary as that which is ‘directed back upon itself’ – that is most relevant to economic methodology is that where observation of the economy leads to ideas that change behavior, which in turn changes (is directed back upon) the economy itself. As George Soros explains: "if investors believe that markets are efficient then that belief will change the way they invest, and that in turn will change the nature of the markets they are observing ... That is the principle of reflexivity". Although various versions of reflexivity have long been discussed, in recent years George Soros has been particularly effective in bringing ideas about reflexivity to the attention of the economic and financial communities. In a series of writings he has systematically argued that reflexivity is not only an important aspect of economic life, it is an aspect that is neglected in most mainstream theorizing; and in addition, that the neglect of reflexivity has been responsible for the failure of economists to predict, explain, or offer a solution for events such as the recent financial crisis. Soros’ ideas about reflexivity have important methodological significance, and his chapter in this book summarizes and clarifies his arguments. His contribution is joined by those of thirteen scholars from a wide range of relevant fields, who provide a commentary on the idea of reflexivity in economics. This book was originally published as a special issue of The Journal of Economic Methodology.

Risk management is a foundation discipline for the prudent conduct of investment management. Being effective requires ongoing evolution and adaptation. In The World of Risk Management, an expert team of contributors addresses the important issues arising in the practice of risk management. A common thread among these distinguished articles is a rigorous theoretical or conceptual basis as well as their practical significance. The topics include not only broad policy considerations but also detailed how-to prescriptions.

A group history of the Austrian School of Economics, from the coffeehouses of imperial Vienna to the modern-day Tea Party The Austrian School of Economics--a movement that has had a vast impact on economics, politics, and society, especially among the American right--is poorly understood by supporters and detractors alike. Defining themselves in opposition to the mainstream, economists such as Ludwig von Mises, Friedrich Hayek, and Joseph Schumpeter built the School's international reputation with their work on business cycles and monetary theory. Their focus on individualism--and deep antipathy toward socialism--ultimately won them a devoted audience among the upper echelons of business and government. In this collective biography, Janek Wasserman brings these figures to life, showing that in order to make sense of the Austrians and their continued influence, one must understand the backdrop against which their philosophy was formed--notably, the collapse of the Austro-Hungarian Empire and a half-century of war and exile.

Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems. This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer’s Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.

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