Tachyon Flare
04-03-2003, 06:13 PM
Response To Hultberg’s Editorial of 30 March 2003
I have no idea whether the "Plunge Protection Team" exists at all, let alone whether it is acting as alleged in the Hultberg’s Safehaven editorial of 30 March 2003. On the other hand, I do know quite a lot about optimal control theory for stochastic processes, a topic of which Hultberg is doubtless completely unaware. Here are some relevant historical observations.
Adam Smith began writing "Wealth of Nations" in 1767, during the first century of the Industrial Revolution. He was one of the first, if not actually the first, to recognize the stock market as an institution with unique capabilities for determining prices. His methods were philosophical rather than mathematical; necessarily so because the mathematics of his era were utterly incapable of comprehending systems for coping with randomness, or even randomness itself. Estimation by least squares, for example, was not invented until 1794 by Carl Friedrich Gauss. The discovery that the sum of a myriad small independent changes is almost always representable by a bell-shaped "normal" distribution came even later: 1820, also by Gauss. Under the circumstances, it is truly remarkable how well Smith comprehended the essential qualities of the stock market.
Karl Marx published "Capital" in 1867; this work is often seen as the first major objection to Smith's theory of the free market. In his research, Marx had the benefit over Smith of 100 years of advancement in mathematics. His methods were still primarily philosophical, but he and other economists of the day were at least able to use primitive mathematical methods to guide their intuitions and test (however badly) some of their conclusions. However, even the simplest statistical tests in use today were unknown to Marx and his contemporaries. The correlation coefficient and the chi-square test were still 30 years in the future, small-sample tests like the t-test and anova were 50 years away. Regression itself appeared gradually over many decades, and was not properly understood for at least 80 years. Like Marx, all social philosophers and economists of the 19th century were deeply confused on the subject of causation, particularly the all-important case in which an effect has multiple causes and some random variation.
Political conflict between economic theories of the right (Smith) and left (Marx) began in earnest in the early 20th century. There were pitched battles fought between armed ideological militias on the streets of Germany in the 1920s, and intense conflict between fascists and communists throughout the world. Neither proponents nor opponents of the free market had any quantitative tools with which to settle their arguments, because they still had not been invented. Time series analysis was in its earliest infancy, the theory of random processes was limited to physics (Brownian motion), and many mathematicians still harbored a visceral dislike of stochastic processes (because they were nowhere differentiable, hence unthinkably ugly). There were no statistical tools for causal analysis, hence no statistical way of sorting out cause and effect from complex data. As usual, most governments fell back on political repression and military might as their preferred means for resolving socio-economic arguments.
Military developments in World War II, especially guidance systems for weapons and control systems for complex machinery, inspired the creation of what we now call optimal control theory and the theory of stochastic processes. Alas for the world, this occurred many decades too late for politics: positions on the left and right with respect to free markets had long since been frozen into rigid forms, protected on all sides by intense political repression of dissent or even rational discussion. Only the very bravest engineers or mathematicians dared even to hint that their theories might shed some light on the politically charged question of whether free markets could be regulated.
When calculus was invented by Isaac Newton, one hundred years before Adam Smith, it revolutionized our ability to understand mechanics and physical processes -- as long as they were non-random. The creation of a calculus powerful enough to handle mechanical processes with a random component had to wait three long centuries, until the 1960s when Kyoshi Ito finally placed the stochastic calculus on a firm foundation. Even so, it took another 30 years before financial analysts became comfortable with the use of stochastic calculus, for example in the option price theory of Black and Scholes.
When we read articles on economics of government regulation, such as the highly political article by Hultberg, it would be wise to bear in mind the history I have recounted above. Regulation of systems that have substantial random input is not today the black art that it was even 50 years ago when Milton Friedman was writing, let alone 150 years ago when the operation of free markets was first questioned by Marx. Most of the "authorities" quoted on both sides of the political spectrum were writing at a time when neither theory nor statistical analysis was up to the task of resolving the political issues. Times have changed! We now live in an era in which economic regulation can be quantitatively analyzed with some hope of reaching the correct conclusion. Now it would be wise finally to draw back from the intense rhetoric and passion that has so badly damaged our discourse on this matter for so many long decades of war and conflict, and let the data begin to speak for itself. Let us allow regulatory economics to develop and mature without ideological interference, and let us be guided by its conclusions.
I long for the day when ideologues like Hultberg will no longer feel compelled to write editorials like the one cited. That day is dawning, let us all enjoy the warmth and glow of the rising sun.
Loren Cobb, PhD.
Ætheling International Consultants
Loren Cobb received his PhD in mathematical sociology from Cornell University in 1973. For 15 years he was a professor of statistics at the Medical University of South Carolina and the University of New Mexico Medical Center, working as a research consultant in every area of medicine and public health. For the last ten years he has been an independent consultant on modeling and simulation for the US Joint Staff (J8), the British and Swedish Ministries of Defense, and US Southern Command. He is the author of numerous simulation models for Peacekeeping and Humanitarian Operations. His current project is a simulation model of future United Nations peacekeeping and humanitarian operations in Afghanistan.
I have no idea whether the "Plunge Protection Team" exists at all, let alone whether it is acting as alleged in the Hultberg’s Safehaven editorial of 30 March 2003. On the other hand, I do know quite a lot about optimal control theory for stochastic processes, a topic of which Hultberg is doubtless completely unaware. Here are some relevant historical observations.
Adam Smith began writing "Wealth of Nations" in 1767, during the first century of the Industrial Revolution. He was one of the first, if not actually the first, to recognize the stock market as an institution with unique capabilities for determining prices. His methods were philosophical rather than mathematical; necessarily so because the mathematics of his era were utterly incapable of comprehending systems for coping with randomness, or even randomness itself. Estimation by least squares, for example, was not invented until 1794 by Carl Friedrich Gauss. The discovery that the sum of a myriad small independent changes is almost always representable by a bell-shaped "normal" distribution came even later: 1820, also by Gauss. Under the circumstances, it is truly remarkable how well Smith comprehended the essential qualities of the stock market.
Karl Marx published "Capital" in 1867; this work is often seen as the first major objection to Smith's theory of the free market. In his research, Marx had the benefit over Smith of 100 years of advancement in mathematics. His methods were still primarily philosophical, but he and other economists of the day were at least able to use primitive mathematical methods to guide their intuitions and test (however badly) some of their conclusions. However, even the simplest statistical tests in use today were unknown to Marx and his contemporaries. The correlation coefficient and the chi-square test were still 30 years in the future, small-sample tests like the t-test and anova were 50 years away. Regression itself appeared gradually over many decades, and was not properly understood for at least 80 years. Like Marx, all social philosophers and economists of the 19th century were deeply confused on the subject of causation, particularly the all-important case in which an effect has multiple causes and some random variation.
Political conflict between economic theories of the right (Smith) and left (Marx) began in earnest in the early 20th century. There were pitched battles fought between armed ideological militias on the streets of Germany in the 1920s, and intense conflict between fascists and communists throughout the world. Neither proponents nor opponents of the free market had any quantitative tools with which to settle their arguments, because they still had not been invented. Time series analysis was in its earliest infancy, the theory of random processes was limited to physics (Brownian motion), and many mathematicians still harbored a visceral dislike of stochastic processes (because they were nowhere differentiable, hence unthinkably ugly). There were no statistical tools for causal analysis, hence no statistical way of sorting out cause and effect from complex data. As usual, most governments fell back on political repression and military might as their preferred means for resolving socio-economic arguments.
Military developments in World War II, especially guidance systems for weapons and control systems for complex machinery, inspired the creation of what we now call optimal control theory and the theory of stochastic processes. Alas for the world, this occurred many decades too late for politics: positions on the left and right with respect to free markets had long since been frozen into rigid forms, protected on all sides by intense political repression of dissent or even rational discussion. Only the very bravest engineers or mathematicians dared even to hint that their theories might shed some light on the politically charged question of whether free markets could be regulated.
When calculus was invented by Isaac Newton, one hundred years before Adam Smith, it revolutionized our ability to understand mechanics and physical processes -- as long as they were non-random. The creation of a calculus powerful enough to handle mechanical processes with a random component had to wait three long centuries, until the 1960s when Kyoshi Ito finally placed the stochastic calculus on a firm foundation. Even so, it took another 30 years before financial analysts became comfortable with the use of stochastic calculus, for example in the option price theory of Black and Scholes.
When we read articles on economics of government regulation, such as the highly political article by Hultberg, it would be wise to bear in mind the history I have recounted above. Regulation of systems that have substantial random input is not today the black art that it was even 50 years ago when Milton Friedman was writing, let alone 150 years ago when the operation of free markets was first questioned by Marx. Most of the "authorities" quoted on both sides of the political spectrum were writing at a time when neither theory nor statistical analysis was up to the task of resolving the political issues. Times have changed! We now live in an era in which economic regulation can be quantitatively analyzed with some hope of reaching the correct conclusion. Now it would be wise finally to draw back from the intense rhetoric and passion that has so badly damaged our discourse on this matter for so many long decades of war and conflict, and let the data begin to speak for itself. Let us allow regulatory economics to develop and mature without ideological interference, and let us be guided by its conclusions.
I long for the day when ideologues like Hultberg will no longer feel compelled to write editorials like the one cited. That day is dawning, let us all enjoy the warmth and glow of the rising sun.
Loren Cobb, PhD.
Ætheling International Consultants
Loren Cobb received his PhD in mathematical sociology from Cornell University in 1973. For 15 years he was a professor of statistics at the Medical University of South Carolina and the University of New Mexico Medical Center, working as a research consultant in every area of medicine and public health. For the last ten years he has been an independent consultant on modeling and simulation for the US Joint Staff (J8), the British and Swedish Ministries of Defense, and US Southern Command. He is the author of numerous simulation models for Peacekeeping and Humanitarian Operations. His current project is a simulation model of future United Nations peacekeeping and humanitarian operations in Afghanistan.