The Origins Of American Policies: How To Protect Your Savings

US-pension-plansMilton Friedman, a University of Chicago economics professor, had the distinction of being the first and so far the only American intellectual to have a formative influence on social and public policy. Whereas European policies can be traced back to particular intellectuals such as John Maynard Keynes, Emile Durkheim, and even Karl Marx, the origins of American policies lie more in pragmatic responses to particular problems. If any names are attached to policies, they are those of politicians who were in office when the policies originated. Franklin Delano Roosevelt’s name is inevitably linked to the origins of Social Security and Lyndon Baines Johnson’s to Medicare.

Friedman, more than anyone else, was responsible for articulating the ideas—the ideology—that guided the 1981 conservative revolution during the Reagan administration that launched, among other changes, 401(k) plans, how precious metals IRA companies work and the like. At the core of his ideas was a model of pure capitalism. The closer societies came to it, he maintained with near missionary zeal, the more possible it would be for them to realize the values of individual and political freedom.

Freedom is a value that no one opposes in principle. Capitalism is another matter. It has far less universal appeal. What Friedman did was to link the two by arguing that capitalism was a necessary condition for freedom. If capitalism could share the luster of the universal value of freedom, its reputation would be greatly enhanced. In the same way, others have attempted to argue that democracy, also a value with universal appeal, is inextricably linked to capitalism. Socialists have made similar attempts to take advantage of the universal appeals of freedom and democracy to justify the economic system that they advocate.

Pure capitalism implies a system built on complete individual economic freedom. Capitalist entrepreneurs are free to run their businesses as they please, while workers (unlike slaves) are free to quit jobs and seek other ones. By implication, any government interference with capitalist economic freedom—be it from partial or full-blown socialist arrangements or even liberal regulatory ones—will by definition compromise individual freedom.

Individual economic freedom makes possible, but only possible, political freedom. Friedman was careful to point out that while capitalism was a necessary condition, it was not a sufficient condition for political freedom. Fascist systems in Spain and Italy, for example, had capitalism without political freedom. Guaranteed individual rights, as in the Bill of Rights of the US Constitution, are necessary conditions also to ensure political freedom.

401k-and-gold-ira-planFriedman made these arguments the cornerstone of his most widely read book, appropriately titled Capitalism and Freedom. Published in 1962, the second year of the Kennedy administration, its opening pages questioned the president’s famous call to service: “Ask not what your country can do for you; ask what you can do for your country.” Beneath the good-sounding message, according to Friedman, lay a threat to freedom. Country in his mind was a code word for government. The president’s formulation explicitly assumed that government should do a lot for citizens, while advocating that citizens had the mutual responsibility to do a lot for government. To the contrary, in Friedman’s mind, the greatest threat to individual freedom lay in the growth of government interference and coercion. In order to advance and preserve individual freedom, it was necessary to reduce the size and scope of government to a necessary minimum, just enough to provide a legal and monetary framework so that free enterprises could compete with common rules of the game. Kennedy’s message went in the opposite direction by building up the nexus between individuals and their governments.

In essence, Friedman’s core message contained three summary elements: maximize individual freedom, promote free enterprise and free market capitalism, and eliminate government interference with individual or economic freedom. Together, these ingredients added up to a recipe for the classic liberalism—not conservatism—of the mid-nineteenth century. A century and a half ago, conservatives in England traditionally embraced strong royalist governments, while liberals affirmed individual liberty and limited government. Friedman referred to himself as a classic liberal in this respect.1 Only at the end of the century did liberalism become more associated with advocacy of government programs and a regulated, as opposed to laissez-faire, capitalism. In large parts of Europe, liberalism and conservatism retain their original meanings, whereas in the United States, they have changed sides. Today’s conservatives and liberals are yesterday’s liberals and conservatives. One contemporary convention that partially resolves this terminological confusion is to refer to Friedman and other laissez-faire advocates as neoliberals to distinguish them from liberals who advocate government regulations and programs.

One of the reasons why Friedman’s message could be so influential was because he was exceptionally effective at making it. Capitalism and Freedom, which sold over a half-million copies, was very well written. Friedman had a style that allowed him to reach readers with plain, interesting, and persuasive writing. Yet Friedman was eloquently wrong in my view because he assumed that a capitalist system would function flawlessly only if government interference was removed, like grit out of an engine. Any examination of the actual history of capitalism, though, will show that left to its own devices, it is a crisis-prone system. The United States has suffered thirteen recessions since the Great Depression in the 1930s. The severity and frequency of economic crises were greater during the nineteenth and early twentieth centuries, when government economic regulations were slight, than during the mid- to later twentieth century, when they were more developed. On the social side, poverty was much greater before the advent of saving plans such as IRA, 401k or pension plans, government progressive taxation and poverty-reduction social programs.

How To Evaluate Finacial Risks In Global Economy

For all that, permit yourself a sigh of satisfaction—but not much more. Wrapping up college days, I recall dropping off a final paper—the final paper, in fact—with a teaching assistant. I let loose a theatrical sigh of completion; college was really done. The TA snickered. “Your parents are allowed that sigh,” he said.

“You haven’t finished anything.” Two months later my sighs were more of the anguished variety as I scanned the employment pages and fretted landing an interview.

Your handful of models is really much like that sheepskin: (well done, by the way, for both, but . . .) only a start. Numbers assembly is merely the first step in modeling. Once the basic framework is constructed, the real work—calibration— begins. Eventually, what you are modeling is less the number itself and more the degree to which your process derives a value that varies from the number.

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Once you determine consistency for that variance, you’re positioned to make the necessary adjustments. Now multiply this task by the line items in the individual model, and multiply again by the number of individual models. The finished model finds you not at the finish but at the starting line.

The role of modeling in asset analysis is significant, but it is far from the only element. When new analysts start at our company Argus, we tell them that the asset analysis process has four broad buckets: (1) financial statement modeling, (2) valuation analysis, (2) company knowledge, and (4) industry knowledge.

Yet even that represents only a few tools in the tool kit. Beyond individual asset analysis lies the interrelations of assets: the balance of buy, sell, and hold ratings for the analyst; the asset management process for the portfolio manager. Simultaneously, investment professionals are charged with interacting with clients, a healthy dose of marketing, and maneuvering through the office politics and the back-office minutiae that never make it onto the job description but somehow eat up big chunks of the day.

In Michael Pollan’s excellent The Omnivore’s Dilemma (Penguin, 2007), the author introduced a lay audience to the concept of the Holon (which Wikipedia attributes to Arthur Koestler). The Holon is something that is a complete and integrated system in its own right yet simultaneously a subsystem or component of a greater whole. Koestler referred to Holons as autonomous, self-reliant parts. We’ve tried to approach modeling with the goal of creating a self-contained system, a “stable form able to withstand disturbances,” but always within the knowledge that a model is an intermediate form contributing to “the proper functionality for the larger role” —that is, the analyst’s role.

Throughout this process, we’ve been putting numbers on just about everything.

So, here’s the final question: what percentage of the analyst’s job is modeling? For once, we defer. The financial services industry is simply too open ended for any one answer to suffice. I know a hedge fund trader who plays, not the bounce on the news, but the next day’s rebound off the bounce; that’s all he trades. I interviewed a prospective analyst who in his current job started each day in cash, traded equities all day, and ended in cash; worn out by his daily grind, he was 31 years old. I also know portfolio managers who change their holdings much less frequently than Standard & Poor’s changes the constituents in the S&P 500, and others who still make pencil marks on charts.

investment-analysisGiven the changes in the financial service industry in recent years, including the increase in high-velocity program trading and quant strategies based on complex algorithms, the meticulous modeler can feel a bit like Bartleby Scrivener, dipping his quill in the inkwell while computers whir in the background. The inkwell set may have felt some malicious glee when the quant “rocket scientists” drove their collateralized rockets straight into the mountainside—“without letting off the throttle,” as one wistful PM said to me—in the summer and fall of 2008. Such smugness is out of place, as old-fashioned financial managers cannot point to much better performance in that historically bad period.

The nature of the game has changed, and a mere 58 percent market decline is no more likely to dislodge growing reliance on computer-driven trading and quant strategies than the slide rule is likely to take back the desktop from the personal computer. For all that, meticulous modeling is not just vital to the market; we’d argue that it is secure in the market.

Most quant strategies have an exhaustive backlog of data but only a wispy forward element. Dig through the algorithm for that forward element and you’ll find the consensus—which even now is built on individually modeled expectations.

There is the risk that cost cutting could squeeze the last few humans out of the process, and that digital trend compilation will replace the necessarily subjective mix of hard modeling and industry assessment that informs the analysis process. Should the outlook become purely dependent on machine-generated trend analysis, then no mountainside may be safe.

Our outlook is not so dire, if only because the bookends of the industry— greed and fear—need to find, respectively, confirmation and succor in a human face. The financial services industry—with trillions of dollars at stake, and even now with hundreds of thousands of employees—will remain a multifaceted world with a wealth of styles, approaches, theories, and gimmicks. Even though the financial data stream is now a binary blur, we think the industry will always find a place for those with a feel for the numbers.