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You Can't Become Rich In Your Pocket Until You Become Rich In Your Mind | ||||
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Most people are nervous about the economy, and consequently nervous about the stock marketNEW LOGIC Reading the Messages and Using the Tools of the New Investment Culture Numbers alone confer no advantage. Sun Tzu, The Art of War Existing theories about the behavior of stock prices are remarkably inadequate, says George Soros, by way of explaining how he has made billions in the financial markets. They are of so little value that the fact that I could get by without them speaks for itself.1 That the methods Soros uses, which make him the planets most successful investor, do not derive from some rigorous application of what we have been told to accept as basic fundamental principles of financial analysis demonstrates just how wispy these supposedly fundamental principles can be. The reason for this is the evolutionary nature of the financial markets, the path of which we showed in earlier chapters. Soros explains that the momentum behind the markets perpetual state of transformation is caused by the bandying between two forces: (1) market events that affect supply and demand and (2) peoples perceptions and reactions to these events. He calls this reflexivity.2 Reflexivity renders the financial markets the epitome of change. People, as a rule, do not like change. In the especially change-averse investment community, the reluctance to move on can slow progress. An example of how an institution for understanding can turn into a cult of justification is the consensus formed by economists about the incubation interval of 1870-1896. Ideas and forces were being churned up in those years that would reinvent the global economy. But rather than see the volatility this created as a by-product of evolutionary renewal, the opposite view was promoted and it prevailed. This view held that instead of being the inevitable precursor to positive change, volatility was a necessary agent of the status quo, putting everyone in their place, fighting each new idea, and moving toward an ordered world of theoretical equilibrium. It seems that equilibrium theories stem less from actual fact than from a very human desire to believe in some inevitable conventional condition to which we will eventually always return: Wont we be glad when things get back to normal! The seize the day before approach is exacerbated today by our ability quickly to collect, organize, and transmit heaps of data about the financial markets to anyone who wants it. Unrestricted access to information is a necessary ingredient of the new investment culture, but we have not learned to use it very well especially when statistics are involved. That we should be less preoccupied with data and more concerned about the set of circumstances from which they issue becomes disconcertingly obvious when we examine numbers that update us on the health of the economy. MIXED SIGNALS When we talk about data explaining changes in the growth of businesses, the productivity of various sectors of the economy, or any combination of these, we are talking about numbers gathered by the federal government. These data are projected to us on a daily basis and cause us to reach conclusions about the countrys present and future financial health. It moves or does not move markets. It may cause us to build or not build a new home, change jobs, retire, have a child, buy a new washing machine, or invest in stock. As these words are being written, most people are nervous about the economy, and consequently nervous about the stock market. If not the sole instigator of the uncertainty, the economic numbers definitely tend to support it. Here is the joke: The output of most of the companies of the new dominant investment system is not included in these economic numbers that are broadcast to us daily. The types of companies whose productivity and growth are not counted in measurements of economic health include computer software reproduction, fiber-optic cable manufacturing, cellular telecommunications, environmental consulting, credit card companies, and shopping warehouse clubs.3 Even this short list represents products and services that most of us are intimately connected with each day and that can be viewed as necessities. They are important drivers of national economic health. Why dont they count? The economic data we receive most often receive come from the Standard Industrial Classification (SIC) system that was put in place in 1930. Except for an update in 1987, the methodology for collecting data has not changed since. It is an accurate measure of the fading take it, make it, break it economy. With the old dominant investment system in critical condition, the SIC system has become the monitor of its vital signs. The Office of Management and Budget (OMB) has begun replacement of the old SIC system with the North American Industry Classification System (NAICS). The intent is to make the system relevant to the twenty-first century, but implementing it is arduous and timeconsuming. The transition will occur in stages. The Federal Reserve will be using some of the new NAICS data in 2002. The Bureau of Labor Statistics will initiate reporting of employment numbers under the new system some time in 2003. Producer price indexes will be revamped and reported under a new system in 2004. The schedule could be too optimistic. Substantial reclassification of U.S. businesses will be necessary. This raises the issue of how breaks in data will be handled as one system transitions to another. It will not be as simple as drawing a line between the twentieth century and the twenty-first. Maybe we have missed it, but we have yet to see or hear in the general media any qualifying remarks that the economic statistics being reported are coming out of a time warp. No disclaimers and no explanations are offered. Does this mean that as we transition to the new system, and the numbers get better because they will be coming from companies of the new dominant investment system the companies of the old investment system will get the credit? Will it be as if the leads attached to a critical patient were furtively removed and reattached to some healthy body so that the doctor can point to the monitor and tell the grieving relatives, Dont worry about a thing hell be back to normal any day now? NUMEROLOGY The fact that in order to monitor corporate productivity accurately, the OMB found it necessary to rebuild the entire economic monitoring network by installing NAICS proves that the apparatus that makes businesses productive, and therefore profitable, has undergone a complete conversion. Setting this evidence of change aside, anyone who was invested in stocks or mutual funds as we entered the twenty-first century had to suspect that something important was going on, if only because of the contradictory explanations put forth to explain the transformation of the markets. Other than investors themselves, those in a position to experience that transformation most acutely are those of us whose career classifications fall under the umbrella of investment advisor. Ushering money every day among individuals and institutions and the stocks and mutual funds they invest in administers healthy doses of reality to our assumptions about the financial markets. This intimate contact with the markets often makes most of our colleagues and ourselves the first to discard ineffectual theories and the statistics that support them. But many in the financial services industry persist in relying on irrelevant and outdated information. It is curious that a government bureaucracy like the OMB would recognize a fundamental shift affecting investors and act upon it, long before some investment counselors who have the advantage of viewing the situation from a much better vantage point. Likewise, it is troubling when we see investment advisors relying on market data and investment statistics that are 5, 10, or 20 years old when assisting clients in making investment choices. In the academic world there is considerably more interest in rethinking old assumptions. The debate between Jeremy J. Siegel, professor of finance at the Wharton School of the University of Pennsylvania, and Robert J. Shiller, professor of economics at Yale University about how properly to evaluate the markets is a very public example. Less public is the important work being done by Robert D. Arnott and Ronald J. Ryan discussed in earlier chapters. Yet the application of old data to new sets of circumstances goes on. Irrelevant statistics are handed down like totems to clients and potential customers, becoming the source of much misguided investment advice. Past Performance Becomes Irrelevant in Analyzing Investment Talent When the Dow was strongly dominant it made some sense to look at the 5-, 7-, or 10-year track records of mutual funds. Until that old system began to weaken, there were two constants that made measurement of past performance somewhat useful. The first was the fact that the take it, make it, break it business model was the major source of corporate productivity; the second was that most methods of stock analysis revolved, in one way or another, around that business model. Any valid analytical comparison must have its set of controls. The two constants created that controlled environment where one money manager's methods could be compared against others during good times and bad. A 5- or 10-year track record that encompassed a manager s performance during the Dows dominance showed their strengths and weaknesses at different points in an economic cycle. As long as the constants remained in place, perhaps some assumptions could be made about how a manager s methods would work under similar conditions as the cycle repeated. It was even valid to compare a manager s performance against the Dow itself to establish how much value was added over the index. By the 1990s, as the Dows dominance was weakening, it was clear that past performance analysis was no longer able to offer any clues about what could be expected from a manager s methods of analyzing and buying securities. We can see now that the reason past data became invalid is that the constants had changed as a new dominant investment system took over. Several studies were done in the 1990s that prove how irrelevant historic performance data had become to the portfolio manager or mutual fund selection process. In 1994 Lipper Analytical Services examined the top-performing mutual funds the year after they were recognized as the best performers in their category. To conduct the study, Lipper used Morningstar, a company that ranks mutual funds between one (lowest) and five (highest) stars, based on past performance. The study looked at the list of five-star funds at the beginning of each year and measured their performance in the following twelve months.4 The study concluded that when most funds do so well that they are labeled top performers, their returns are below average the following year. |
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