A random walk down wall street pdf download

A random walk down wall street pdf download

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17/04/ · a-random-walk-down-wall-street Identifier-ark ark://t5bd4kh0p Ocr tesseract alphag PDF download. download 1 file. SINGLE PAGE 05/09/ · According to the Wall Street Journal, “But the company also runs a mutual fund, and in one of Wall Street’s odder paradoxes, it has performed terribly. Investors following the A random walk down Wall Street by Malkiel, Burton Gordon. Publication date Topics Pdf_module_version Ppi Rcs_key Republisher_date A random walk down Wall Street: including a life-cycle guide to personal investing / Burton G. Malkiel. p. cm. Rev. ed. of: a random walk down Wall Street. c Includes bibliographical 05/03/ · Brief Summary of Book: A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing by Burton G. Malkiel. Here is a quick description and cover ... read more

edu no longer supports Internet Explorer. To browse Academia. edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Download Free PDF. A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing. Anthony Tarasio. Download Download PDF Full PDF Package Download Full PDF Package This Paper. A short summary of this paper. Download Download PDF. Download Full PDF Package. MALKIEL W. All rights reserved. Republication or redistribution of Thomson Reuters content, including by framing or similar means, is expressly prohibited without the prior written consent of Thomson Reuters. Thomson Reuters and its logo are registered trademarks or trademarks of the Thomson Reuters group of companies around the world.

Thomson Reuters journalists are subject to an Editorial Handbook, which requires fair presentation and disclosure of relevant interests. All rights reserved For information about permission to reproduce selections from this book, write to Permissions, W. ISBN: 1. Random walks Mathematics I. M com W. THE MADNESS OF CROWDS The Tulip-Bulb Craze The South Sea Bubble Wall Street Lays an Egg An Afterword 3. THE EXPLOSIVE BUBBLES OF THE EARLY S The Internet Bubble A Broad-Scale High-Tech Bubble Yet Another New-Issue Craze TheGlobe.

The U. Part Two HOW THE PROS PLAY THE BIGGEST GAME IN TOWN 5. The Rationale for the Charting Method Why Might Charting Fail to Work? From Chartist to Technician The Technique of Fundamental Analysis Three Important Caveats Why Might Fundamental Analysis Fail to Work? Using Fundamental and Technical Analysis Together 6. Just What Exactly Is a Random Walk? Appraising the Counterattack Implications for Investors 7. The Views from Wall Street and Academia Are Security Analysts Fundamentally Clairvoyant? The Influence of Random Events 2. Errors Made by the Analysts Themselves 4. The Loss of the Best Analysts to the Sales Desk, to Portfolio Management, or to Hedge Funds 5. The Conflicts of Interest between Research and Investment Banking Departments Do Security Analysts Pick Winners? Avoid Herd Behavior 2. Avoid Overtrading 3. If You Do Trade: Sell Losers, Not Winners 4.

Other Stupid Investor Tricks Does Behavioral Finance Teach Ways to Beat the Market? Why Even Close Shots Miss And the Winner Is… The Performance of Professional Investors A Summing Up Part Four A PRACTICAL GUIDE FOR RANDOM WALKERS AND OTHER INVESTORS A LIFE-CYCLE GUIDE TO INVESTING Five Asset-Allocation Principles 1. Risk and Reward Are Related 2. Your Actual Risk in Stock and Bond Investing Depends on the Length of Time You Hold Your Investment 3. Dollar-Cost Averaging Can Reduce the Risks of Investing in Stocks and Bonds 4. Distinguishing between Your Attitude toward and Your Capacity for Risk Three Guidelines to Tailoring a Life-Cycle Investment Plan 1. Specific Needs Require Dedicated Specific Assets 2. Recognize Your Tolerance for Risk 3. The message of the original edition was a very simple one: Investors would be far better off buying and holding an index fund than attempting to buy and sell individual securities or actively managed mutual funds.

I boldly stated that buying and holding all the stocks in a broad stock-market average was likely to outperform professionally managed funds whose high expense charges and large trading costs detract substantially from investment returns. I can make the case with great simplicity. The difference is dramatic. Why, then, a tenth edition of this book? The answer is that there have been enormous changes in the financial instruments available to the public. A book meant to provide a comprehensive investment guide for individual investors needs to be updated to cover the full range of investment products available. In addition, investors can benefit from a critical analysis of the wealth of new information provided by academic researchers and market professionals—made comprehensible in prose accessible to everyone with an interest in investing.

Over the past forty years, we have become accustomed to accepting the rapid pace of technological change in our physical environment. Financial innovation over the same period has been equally rapid. Much of the new material in this book has been included to explain these financial innovations and to show how you as a consumer can benefit from them. This tenth edition also provides a clear and easily accessible description of the academic advances in investment theory and practice. In addition, a new section has been added to present practical investment strategies for investors who have retired or are about to retire. So much new material has been added over the years that readers who may have read an earlier edition of this book in college or business school will find this new edition rewarding reading.

This edition takes a hard look at the basic thesis of earlier editions of Random Walk—that the market prices stocks so efficiently that a blindfolded chimpanzee throwing darts at the stock listings can select a portfolio that performs as well as those managed by the experts. Through the past forty years, that thesis has held up remarkably well. Nevertheless, there are still both academics and practitioners who doubt the validity of the theory. And the stock-market crash of October , the Internet bubble, and the financial crisis of —09 raised further questions concerning the vaunted efficiency of the market. I will, however, review the evidence on a number of techniques of stock selection that are believed to tilt the odds of success in favor of the individual investor.

The book remains fundamentally a readable investment guide for individual investors. It is also the case that the risk involved in most investments decreases with the length of time the investment can be held. For these reasons, optimal investment strategies must be age-related. This chapter alone is worth the cost of a high-priced appointment with a personal financial adviser. My debts of gratitude to those mentioned in earlier editions continue. In addition, I must mention the names of a number of people who were particularly helpful in making special contributions to the tenth edition. I am also grateful to John Devereaux, Christopher Philips, and Cheryl Roberts of the Vanguard Group for their important assistance in providing data. Ellen DiPippo made an extraordinary contribution to this edition. She was somehow able to decipher my inpenetrable scribbles and turn them into readable text.

She also provided research assistance and was responsible for most of the graphic presentations in the book. My association with W. Norton remains a superb collaboration, and I thank Drake McFeely and Jeff Shreve for their indispensable assistance in bringing this edition to publication. Patricia Taylor continued her association with the project and made extremely valuable editorial contributions to the tenth edition. My wife, Nancy Weiss Malkiel, has made by far the most important contributions to the successful completion of the past six editions.

In addition to providing the most loving encouragement and support, she read carefully through various drafts of the manuscript and made innumerable suggestions that clarified and vastly improved the writing. Most important, she has brought incredible joy to my life. No one more deserved the dedication of a book than she and her second- best friend. Burton G. Here, I acknowledge the many individuals who offered extremely valuable suggestions and criticisms. Many research assistants have labored long in compiling information for this book. Especially useful contributions were made by John Americus, Shane Antos, Costin Bontas, Jonathan Curran, Barry Feldman, Ethan Hugo, Amie Ko, Paul Messaris, Matthew Moore, Ker Moua, Ellen Renaldi, Barry Schwartz, Greg Smolarek, Ray Soldavin, Elizabeth Woods, Yexiao Xu, and Basak Yeltikan.

Elvira Giaimo provided most helpful computer programming. I am also grateful to Arthur Lipper Corporation for permission to use its mutual-fund rankings. A vital contribution was made by Patricia Taylor, a professional writer and editor. She read through complete drafts of the book and made innumerable contributions to the style, organization, and content of the manuscript. She deserves much of the credit for whatever lucid writing can be found in these pages. The contribution of Judith Malkiel was of inestimable importance. She painstakingly edited every page of the manuscript and was helpful in every phase of this undertaking. Finally, I would like to acknowledge with deep gratitude the assistance of the following individuals who made important contributions to earlier editions.

They include: Peter Asch, Leo Bailey, Howard Baker, Jeffrey Balash, David Banyard, William Baumol, Clair Bien, G. Gordon Biggar Jr. Johnston, Kay Kerr, Walter Lenhard, James Litvack, Ian MacKinnon, Barbara Mains, Jonathan Malkiel, Sol Malkiel, Whitney Malkiel, Edward Mathias, Jianping Mei, Melissa McGinnis, Will McIntosh, Kelley Mingone, William Minicozzi, Keith Mullins, Gabrielle Napolitano, James Norris, Gail Paster, Emily Paster, H. Bradlee Perry, George Putnam, Donald Peters, Michelle Peterson, Richard Quandt, James Riepe, Michael Rothschild, Joan Ryan, Robert Salomon Jr. Barton Thomas, Mark Thompson, Jim Troyer, David Twardock, Linda Wheeler, Frank Wisneski, and Robert Zenowich.

A man who knows the price of everything, and the value of nothing. They point to professional investment strategies using complex derivative instruments and high- frequency trading. Nothing could be further from the truth. You can do as well as the experts—perhaps even better. It was the steady investors who kept their heads when the stock market tanked in March , and then saw the value of their holdings eventually recover and continue to produce attractive returns. And many of the pros lost their shirts in buying derivative securities they failed to understand, as well as during the early s when they overloaded their portfolios with overpriced tech stocks. This book is a succinct guide for the individual investor. It covers everything from insurance to income taxes. It tells you how to buy life insurance and how to avoid getting ripped off by banks and brokers.

It will even tell you what to do about gold and diamonds. But primarily it is a book about common stocks—an investment medium that not only provided generous long-run returns in the past but also appears to represent good possibilities for the years ahead. WHAT IS A RANDOM WALK? A random walk is one in which future steps or directions cannot be predicted on the basis of past history. When the term is applied to the stock market, it means that short-run changes in stock prices are unpredictable. Investment advisory services, earnings forecasts, and complicated chart patterns are useless. It is an epithet coined by the academic world and hurled insultingly at the professional soothsayers. Taken to its logical extreme, it means that a blindfolded monkey throwing darts at the stock listings could select a portfolio that would do just as well as one selected by the experts.

Now, financial analysts in pin-striped suits do not like being compared to bare-assed apes. This last includes a concept called beta, and I intend to trample on that a bit. By the early s, even some academics had joined the professionals in arguing that the stock market was at least somewhat predictable after all. It has all the ingredients of high drama —including fortunes made and lost and classic arguments about their cause. But before we begin, perhaps I should introduce myself and state my qualifications as guide. I have drawn on three aspects of my background in writing this book; each provides a different perspective on the stock market. First is my professional experience in the fields of investment analysis and portfolio management. These perspectives have been indispensable to me. Some things in life can never fully be appreciated or understood by a virgin. The same might be said of the stock market.

Second is my current position as an economist. Specializing in securities markets and investment behavior, I have acquired detailed knowledge of academic research and findings on investment opportunities. I have relied on many new research findings in framing recommendations for you. Last, and certainly not least, I have been a lifelong investor and successful participant in the market. How successful I will not say, for it is a peculiarity of the academic world that a professor is not supposed to make money. Academics are supposed to be seekers of knowledge, not of financial reward. It is in the former sense, therefore, that I shall tell you of my victories on Wall Street. This book has a lot of facts and figures. It is specifically intended for the financial layperson and offers practical, tested investment advice. You need no prior knowledge to follow it. All you need is the interest and the desire to have your investments work for you.

It is the definition of the time period for the investment return and the predictability of the returns that often distinguish an investment from a speculation. An investor buys stocks likely to produce a dependable future stream of cash returns and capital gains when measured over years or decades. Let me make it quite clear that this is not a book for speculators: I am not going to promise you overnight riches. I am not promising you stock-market miracles. Indeed, a subtitle for this book might well have been The Get Rich Slowly but Surely Book. Remember, just to stay even, your investments have to produce a rate of return equal to inflation.

Inflation in the United States and throughout most of the developed world fell to the 2 percent level in the early s, and some analysts believe that relative price stability will continue indefinitely. They suggest that inflation is the exception rather than the rule and that historical periods of rapid technological progress and peacetime economies were periods of stable or even falling prices. It may well be that little or no inflation will occur during the first decades of the twenty-first century, but I believe investors should not dismiss the possibility that inflation will accelerate again at some time in the future. Moreover, productivity improvements are harder to come by in some service-oriented activities. Thus, it would be a mistake to think that upward pressure on prices is no longer a worry.

If inflation were to proceed at a 2 to 3 percent rate—a rate much lower than we had in the s and early s—the effect on our purchasing power would still be devastating. The following table shows what an average inflation rate of approximately 4 percent has done over the — period. My morning newspaper has risen 3, percent. Investing requires work, make no mistake about it. Romantic novels are replete with tales of great family fortunes lost through neglect or lack of knowledge on how to care for money. Free enterprise, not the Marxist system, caused the downfall of the Ranevsky family: They had not worked to keep their money.

Even if you trust all your funds to an investment adviser or to a mutual fund, you still have to know which adviser or which fund is most suitable to handle your money. Armed with the information contained in this book, you should find it a bit easier to make your investment decisions. Most important of all, however, is the fact that investing is fun. A successful investor is generally a well-rounded individual who puts a natural curiosity and an intellectual interest to work to earn more money. INVESTING IN THEORY All investment returns—whether from common stocks or exceptional diamonds—are dependent, to varying degrees, on future events.

Traditionally, the pros in the investment community have used one of two approaches to asset valuation: the firm-foundation theory or the castle-in-the-air theory. Millions of dollars have been gained and lost on these theories. To add to the drama, they appear to be mutually exclusive. An understanding of these two approaches is essential if you are to make sensible investment decisions. It is also a prerequisite for keeping you safe from serious blunders. When market prices fall below rise above this firm foundation of intrinsic value, a buying selling opportunity arises, because this fluctuation will eventually be corrected—or so the theory goes.

It is difficult to ascribe to any one individual the credit for originating the firm-foundation theory. Eliot Guild is often given this distinction, but the classic development of the technique and particularly of the nuances associated with it was worked out by John B. In The Theory of Investment Value, Williams presented an actual formula for determining the intrinsic value of stock. Williams based his approach on dividend income. Discounting basically involves looking at income backwards. Williams actually was serious about this. He went on to argue that the intrinsic value of a stock was equal to the present or discounted value of all its future dividends. It received a further boost under the aegis of Professor Irving Fisher of Yale, a distinguished economist and investor. The logic of the firm-foundation theory is quite respectable and can be illustrated with common stocks. It stands to reason that the greater the present dividends and their rate of increase, the greater the value of the stock; thus, differences in growth rates are a major factor in stock valuation.

Now the slippery little factor of future expectations sneaks in. Security analysts must estimate not only long-term growth rates but also how long an extraordinary growth can be maintained. When the market gets overly enthusiastic about how far in the future growth can continue, it is popularly held on Wall Street that stocks are discounting not only the future but perhaps even the hereafter. The point is that the firm-foundation theory relies on some tricky forecasts of the extent and duration of future growth. The foundation of intrinsic value may thus be less dependable than is claimed. The firm-foundation theory is not confined to economists alone. It was that easy. Of course, instructions for determining intrinsic value were furnished, and any analyst worth his or her salt could calculate it with just a few taps of the personal computer.

THE CASTLE-IN-THE-AIR THEORY The castle-in-the-air theory of investing concentrates on psychic values. John Maynard Keynes, a famous economist and successful investor, enunciated the theory most lucidly in It was his opinion that professional investors prefer to devote their energies not to estimating intrinsic values, but rather to analyzing how the crowd of investors is likely to behave in the future and how during periods of optimism they tend to build their hopes into castles in the air. According to Keynes, the firm-foundation theory involves too much work and is of doubtful value. Keynes practiced what he preached. In the depression years in which Keynes gained his fame, most people concentrated on his ideas for stimulating the economy. It was hard for anyone to build castles in the air or to dream that others would. Nevertheless, in his book The General Theory of Employment, Interest and Money, Keynes devoted an entire chapter to the stock market and to the importance of investor expectations.

With regard to stocks, Keynes noted that no one knows for sure what will influence future earnings prospects and dividend payments. The smart player recognizes that personal criteria of beauty are irrelevant in determining the contest winner. A better strategy is to select those faces the other players are likely to fancy. This logic tends to snowball. After all, the other participants are likely to play the game with at least as keen a perception. So much for British beauty contests. The newspaper-contest analogy represents the ultimate form of the castle-in-the-air theory of price determination. An investment is worth a certain price to a buyer because she expects to sell it to someone else at a higher price. The investment, in other words, holds itself up by its own bootstraps.

The new buyer in turn anticipates that future buyers will assign a still higher value. In this kind of world, a sucker is born every minute—and he exists to buy your investments at a higher price than you paid for them. Any price will do as long as others may be willing to pay more. There is no reason, only mass psychology. All the smart investor has to do is to beat the gun—get in at the very beginning. Robert Shiller, in his best-selling book Irrational Exuberance, argues that the mania in Internet and high-tech stocks during the late s can be explained only in terms of mass psychology.

At universities, so-called behavioral theories of the stock market, stressing crowd psychology, gained favor during the early s at leading economics departments and business schools across the developed world. In an exchange economy the value of any asset depends on an actual or prospective transaction. He believed that every investor should post the following Latin maxim above his desk: Res tantum valet quantum vendi potest. A thing is worth only what someone else will pay for it. My first task will be to acquaint you with the historical patterns of pricing and how they bear on the two theories of pricing investments. It was Santayana who warned that if we did not learn the lessons of the past we would be doomed to repeat the same errors.

Therefore, in the pages to come I will describe some spectacular crazes— both long past and recently past. Some readers may pooh- pooh the mad public rush to buy tulip bulbs in seventeenth- century Holland and the eighteenth-century South Sea Bubble in England. This is one of the peculiarly dangerous months to speculate in stocks in. The others are July, January, September, April, November, May, March, June, December, August and February. In their frenzy, market participants ignore firm foundations of value for the dubious but thrilling assumption that they can make a killing by building castles in the air. Such thinking has enveloped entire nations. The psychology of speculation is a veritable theater of the absurd. Several of its plays are presented in this chapter. In each case, some of the people made money some of the time, but only a few emerged unscathed.

History, in this instance, does teach a lesson: Although the castle-in-the-air theory can well explain such speculative binges, outguessing the reactions of a fickle crowd is a most dangerous game. It would appear that not many have read the book. Skyrocketing markets that depend on purely psychic support have invariably succumbed to the financial law of gravitation. Unsustainable prices may persist for years, but eventually they reverse themselves. Such reversals come with the suddenness of an earthquake; and the bigger the binge, the greater the resulting hangover. Few of the reckless builders of castles in the air have been nimble enough to anticipate these reversals and to escape when everything came tumbling down. THE TULIP-BULB CRAZE The tulip-bulb craze was one of the most spectacular get- rich-quick binges in history. Its excesses become even more vivid when one realizes that it happened in staid old Holland in the early seventeenth century.

The events leading to this speculative frenzy were set in motion in when a newly appointed botany professor from Vienna brought to Leyden a collection of unusual plants that had originated in Turkey. Over the next decade or so, the tulip became a popular but expensive item in Dutch gardens. Many of these flowers succumbed to a nonfatal virus known as mosaic. It was this mosaic that helped to trigger the wild speculation in tulip bulbs. Slowly, tulipmania set in. Then they would buy an extra-large stockpile to anticipate a rise in price. Tulip-bulb prices began to rise wildly. The more expensive the bulbs became, the more people viewed them as smart investments. People who said the prices could not possibly go higher watched with chagrin as their friends and relatives made enormous profits. The temptation to join them was hard to resist. Bulb prices reached astronomical levels. Part of the genius of financial markets is that when there is a real demand for a method to enhance speculative opportunities, the market will surely provide it.

A call option conferred on the holder the right to buy tulip bulbs call for their delivery at a fixed price usually approximating the current market price during a specified period. He was charged an amount called the option premium, which might run 15 to 20 percent of the current market price. An option on a tulip bulb currently worth guilders, for example, would cost the buyer only about 20 guilders. If the price moved up to guilders, the option holder would exercise his right; he would buy at and simultaneously sell at the then current price of He then had a profit of 80 guilders the guilders appreciation less the 20 guilders he paid for the option.

Thus, he enjoyed a fourfold increase in his money, whereas an outright purchase would only have doubled his money. Such devices helped to ensure broad participation in the market. The same is true today. The history of the period was filled with tragicomic episodes. One such incident concerned a returning sailor who brought news to a wealthy merchant of the arrival of a shipment of new goods. The merchant rewarded him with a breakfast of fine red herring. It was a costly Semper Augustus tulip bulb. The sailor paid dearly for his relish—his no longer grateful host had him imprisoned for several months on a felony charge. Historians regularly reinterpret the past, and some financial historians who have reexamined the evidence about various financial bubbles have argued that considerable rationality in pricing may have existed after all.

One of these revisionist historians, Peter Garber, has suggested that tulip- bulb pricing in seventeenth-century Holland was far more rational than is commonly believed. Garber makes some good points, and I do not mean to imply that there was no rationality at all in the structure of bulb prices during the period. The Semper Augustus, for example, was a particularly rare and beautiful bulb and, as Garber reveals, was valued greatly even in the years before the tulipmania. But Garber can find no rational explanation for such phenomena as a twenty-fold increase in tulip-bulb prices during January of followed by an even larger decline in prices in February. Apparently, as happens in all speculative crazes, prices eventually got so high that some people decided they would be prudent and sell their bulbs. Soon others followed suit.

Like a snowball rolling downhill, bulb deflation grew at an increasingly rapid pace, and in no time at all panic reigned. Government ministers stated officially that there was no reason for tulip bulbs to fall in price—but no one listened. Dealers went bankrupt and refused to honor their commitments to buy tulip bulbs. And prices continued to decline. Down and down they went until most bulbs became almost worthless—selling for no more than the price of a common onion. THE SOUTH SEA BUBBLE Suppose your broker has called you and recommended that you invest in a new company with no sales or earnings—just great prospects. Right you are, but years ago in England this was one of the hottest new issues of the period. And, just as you guessed, investors got very badly burned. The story illustrates how fraud can make greedy people even more eager to part with their money. At the time of the South Sea Bubble, the British were ripe for throwing away money.

A long period of prosperity had resulted in fat savings and thin investment outlets. In those days, owning stock was considered something of a privilege. They reaped rewards in several ways, not least of which was that their dividends were untaxed. Also, their number included women, for stock represented one of the few forms of property that British women could possess in their own right. The company took on a government IOU of almost £10 million. As a reward, it was given a monopoly over all trade to the South Seas. The public believed immense riches were to be made in such trade and regarded the stock with distinct favor. From the very beginning, the South Sea Company reaped profits at the expense of others.

Holders of the government securities to be assumed by the company simply exchanged their securities for those of the South Sea Company. Those with prior knowledge of the plan quietly bought up government securities selling as low as £55 and then turned them in at par for £ worth of South Sea stock when the company was incorporated. Not a single director of the company had the slightest experience in South American trade. But even this venture did not prove profitable, because the mortality rate on the ships was so high. The directors were, however, wise in the art of public appearance. An impressive house in London was rented, and the boardroom was furnished with thirty black Spanish upholstered chairs whose beechwood frames and gilt nails made them handsome to look at but uncomfortable to sit in.

In the meantime, a shipload of company wool that was desperately needed in Vera Cruz was sent instead to Cartagena, where it rotted on the wharf for lack of buyers. To further his purpose, Law acquired a derelict concern called the Mississippi Company and proceeded to build a conglomerate that became one of the largest capital enterprises ever to exist. The Mississippi Company attracted speculators and their money from throughout the Continent. At one time the inflated total market value of the stock of the Mississippi Company in France was more than eighty times that of all the gold and silver in the country. Meanwhile, back on the English side of the Channel, a bit of jingoism now began to appear in some of the great English houses. Why should all the money be going to the French Mississippi Company? What did England have to counter this?

This was free enterprise at its finest. In , the directors, an avaricious lot, decided to capitalize on their reputation by offering to fund the entire national debt, amounting to £31 million. This was boldness indeed, and the public loved it. When a bill to that effect was introduced in Parliament, the stock promptly rose from £ to £ On April 12, , five days after the bill became law, the South Sea Company sold a new issue of stock at £ The issue could be bought on the installment plan—£60 down and the rest in eight easy payments. Fights broke out among other investors surging to buy. To ease the public appetite, the South Sea directors announced another new issue—this one at £ But the public was ravenous. Within a month the stock was £ On June 15 yet another issue was floated. This time the payment plan was even easier—10 percent down and not another payment for a year. The stock hit £ Half the House of Lords and more than half the House of Commons signed on. Eventually, the price rose to £1, The speculative craze was in full bloom.

Not even the South Sea Company was capable of handling the demands of all the fools who wanted to be parted from their money. Investors looked for other new ventures where they could get in on the ground floor. Just as speculators today search for the next Google, so in England in the early s they looked for the next South Sea Company. Promoters obliged by organizing and bringing to the market a flood of new issues to meet the insatiable craving for investment. Increasingly the promotions involved some element of fraud, such as making boards out of sawdust. There were nearly one hundred different projects, each more extravagant and deceptive than the other, but each offering the hope of immense gain. Like bubbles, they popped quickly—usually within a week or so.

The public, it seemed, would buy anything. New companies seeking financing during this period were organized for such purposes as the building of ships against pirates; encouraging the breeding of horses in England; trading in human hair; building hospitals for bastard children; extracting silver from lead; extracting sunlight from cucumbers; and even producing a wheel of perpetual motion. Not being greedy himself, the promoter promptly closed up shop and set off for the Continent. He was never heard from again. Not all investors in the bubble companies believed in the feasibility of the schemes to which they subscribed. Whom the gods would destroy, they first ridicule. Signs that the end was near appeared with the issuance of a pack of South Sea playing cards. Each card contained a caricature of a bubble company, with an appropriate verse inscribed underneath.

One of these, the Puckle Machine Company, was supposed to produce machines discharging both round and square cannonballs and bullets. Puckle claimed that his machine would revolutionize the art of war. Many individual bubbles had been pricked without dampening the speculative enthusiasm, but the deluge came in August with an irreparable puncture to the South Sea Company. Realizing that the price of the shares in the market bore no relationship to the real prospects of the company, the directors and officers sold out in the summer. The news leaked and the stock fell.

They sound so all knowing and sure of themselves—how can they be wrong? The best way for you to short-circuit the panic that you will inevitably feel over the course of your investment program is to focus on all the other panics and what happened afterwards. Remember that not even the Great Crash and Depression of the s would have destroyed a long-term investor who stuck with a superior investment strategy. But it is our ability to look beyond short-term losses that will help us succeed in the future and enjoy the long-term fruits of stock market investing. On January 1, , I published a commentary on the attractiveness of small-cap stocks entitled Looking Back to the Future: History Says Buy Small-Cap Stocks Now. Value and small-cap stocks have suffered terribly. And if you want to see really bad, all you have to do is take a look at small-cap stocks. Those laggard big-cap value strategies look positively wonderful when compared to the plight of small-cap stocks.

Look at history. I believe this week marks an historical opportunity for small stock investors. For the first time since the mids, large stocks The Unreliable Experts: Getting in the Way of Outstanding Performance 29 will outperform small stocks over the year period ending December 31, So, rather than being distraught about the market, I find myself delighted! It takes foresight and courage to buck the big-cap growth trend, yet that is what history is telling us to do. Over the next several days, most of them bounced back almost to the levels from which they fell, leading many to believe that Monday was just a one-day event. For while the Internet stocks may make a short-term come back, current Internet stock prices make absolutely no sense. It seems to me that the only successful business model found to date is to create a web company, do an IPO, and get rich quick selling your shares to gullible investors. We are currently witnessing the biggest bubble the stock market has ever created.

When the Internet insanity ends, truckloads of 30 WHAT WORKS ON WALL STREET books will be turned out; endless comparisons to Dutch Tulip bulbs and Ponzi schemes will be made; and a whole generation of ex—day-traders will rue the day they were seduced by the siren song of the Internet. This mania is a creation of fantasy and ludicrous expectations and of the childlike notion that hope can prevail over experience. com and watch the profits roll in. For the patient, educated, long-term investor who knows that over time the market is bound by the rules of economics, the last year and a half has been pretty sickening. The current myopia cannot and will not last. After every other market mania—from tulip bulbs in 17th century Holland, to radio stocks in the s, to aluminum stocks in the 50s, to computer stocks in the mid s, and the biotech craze of the early s—those boring laws of economics always rear their very sane heads. And the same thing that drove Internet prices up—lack of liquidity married to irrational investors—will drive them down, only more quickly.

Note: Since the publication of this commentary through December 31, , the Dow Jones Internet Index is down — Yet the point of these commentary excerpts is not self aggrandizement. Any investor with access to long-term data who also understands that markets are ultimately rational will be able to make similar forecasts. The key, as always, it holding fast to the efficacy of the long-term data and to the belief that regression to the mean is bound to occur. We do, of course, have charts showing the long-term price movements of stock groups and individual stocks. But there is no real classification here, except by type of business. Where is the continuous, ever growing body of knowledge and technique handed down by the analysts of the past to those of the present and future? When we contrast the annals of medicine with those of finance, the paucity of our recorded and digested experience becomes a reproach.

We lack the codified experience which will tell us whether codified experience is valuable or valueless. In the years to come we analysts must go to school to learn the older established disciplines. We must study their ways of amassing and scrutinizing facts and from this study develop methods of research suited to the peculiarities of our own field of work. Now, however, real strides are being made. The first version of What Works on Wall Street, published in , covered many of the variables that Graham was looking for 50 years earlier. Over the past several years, many academ- I 31 Copyright © by James P. Of particular note is the brilliant Triumph of the Optimists: Years of Global Investment Returns, by Elroy Dimson, Paul Marsh, and Mike Staunton, which catalogs returns over the last years in 16 different countries.

The book also looks at the results by country for various investment strategies, such as growth and value. Other academics, such as Eugene Fama and Ken French, have built growth and value indices for small- and large-cap stocks going back to Fama and French use the price-to-book ratio of a company to assign the stock to the value or growth camp, with stocks with low price-to-book ratios falling into the value index and stocks with high price-to-book ratios going into growth. Their data give us the longest return history on the two main styles of investing available today. Many academics took their own research to heart and started money management firms to take advantage of the results of their research. After publishing their seminal paper, Contrarian Investment, Extrapolation and Risk, professors Josef Lakonishok, Andrei Shleifer, and Robert W.

Our ongoing research and product refinement are conducted by Josef Lakonishok, Robert Vishny, and Menno Vermeulen. Their research indicates that not only decades of U. data show that certain factors are consistently associated with superior returns, but that the same is true in Europe and Japan as well. Yet, all this research is valuable precisely because it covers returns over decades—not days. Performance was the Rules of the Game 33 name of the game, and buying stocks with outstanding earnings growth was the way to get it. In hindsight, look at how misleading a five-year period can be. More recently, the mania of the late s provided yet another example of people extrapolating shorter term results well into the future.

In both cases, things ended very badly. Markets are now computerized, block traders dominate, the individual investor is gone, and in his place sit huge mutual funds to which he has given his money. Some people think these masters of money make decisions differently, and believe that looking at how a strategy performed in the s or s offers little insight into how it will perform in the future. But not much has really changed since Isaac Newton—a brilliant man indeed—lost a fortune in the South Sea Trading Company bubble of And as long as people let fear, greed, hope, and ignorance cloud their judgment, they will continue to misprice stocks and provide opportunities to those who rigorously use simple, time-tested strategies to pick stocks.

Newton lost his money because he let himself get caught up in the hoopla of the moment; he invested in a colorful story rather than the dull facts. Names change. Industries change. Styles come in and out of fashion, but the underlying characteristics that identify a good or bad investment remain the same. Each era has its own group of stocks that people flock to, usually those stocks with the most intoxicating story. The point is simple. Far from being an anomaly, the euphoria of the late s was a predictable end to a long bull market, where the silliest investment strategies do extraordinarily well, only to go on to crash and burn.

A long view of returns is essential, because only the fullness of time uncovers basic relationships that short-term gyrations conceal. It also lets us analyze how the market responds to a large number of events, such as inflation, stock market crashes, stagflation, recessions, wars, and new discoveries. From the past, the future flows. History never repeats exactly, but the same types of events continue to occur. Investors who had taken to heart this essential message in the last speculative bubble were those least hurt in the aftermath. ANECDOTAL EVIDENCE IS NOT ENOUGH Investment advice bombards us from many directions, with little to support it but anecdote. Many times, a manager will give a handful of stocks as examples, demonstrating how well they went on to perform.

Unfortunately, these managers conveniently ignore the many other stocks that also possessed the preferred characteristics but failed. This leaves them with the strongest memories centered on the few stocks that performed very well for them, and the faintest memory for those that performed poorly. They also have demonstrated a consistent tendency to equate a good company with a good stock, assuming that because the company is highly thought of, it also will turn out to be an excellent investment. We, therefore, must look at how well overall strategies, not individual stocks, perform. To do this, I have tried to stay true to those scientific rules that distinguish a method from a less rigorous model. All models must use explicitly stated rules. There must be no ambiguity in the statement of the rule to be tested. No allowance is made for a private or unique interpretation of the rule. The rule must be stated explicitly and publicly so that anyone with the time, money, data, equipment, and inclination can reproduce the results.

The rule must make sense and must not be derived from the data. Someone using the same rules and the same database must get the same results. Also, the results must be consistent over time. Long-term results cannot owe all their benefit to a few years. I have attempted to use only rules that are intuitive, logical, and appeal to sensibility, but in all cases the rules are objective. They are independent of the social position, financial status, and cultural background of the investigator, and they do not require superior insight, information, or interpretation. Many problems exist with backtesting, and the quality of data is the top concern. All large collections of historical data contain many errors. Nevertheless, problems remain. Undoubtedly, the database contains stocks where a split was unaccounted for, where a bad book value persisted for several years, where earnings were misstated and went uncorrected, where a price was inverted from 31 to 13, etc.

These problems will be present for any test of stock market methods and must not be discounted, especially when a method shows just a slight advantage over the market in general. For this version of the book, we continue to use the Compustat Active and Research database. But for the period of through , we are using a new backtesting engine to generate results. For forward, we use the FactSet Alpha testing engine to determine results. We have also maintained real-time portfolios since , and the FactSet engine closely duplicates them over the same period. It takes approximately 42 minutes for an express train to go from Greenwich, Connecticut to Grand Central Station in Manhattan. In that time, you could look around your car and find all sorts of statistically relevant characteristics about your fellow passengers. Perhaps a huge number of blondes are present, or 75 percent have blue eyes, or the majority were born in May.

When you went looking for these relationships, you went data-mining. If you torture the data long enough, they will confess to anything. The best way to confirm that the excess returns are genuine is to test them on different periods or subperiods or in different markets, such as those of European countries. Preliminary research we have conducted in EAFE Europe, Australasia, and the Far East countries show the strategies performing with a similar level of excess returns as those in the United States. Another frequently used technique is to separate the database by random number, ticker symbol, or subperiods to make certain that all follow the same return pattern. Anything can look good for five or even 10 years.

Innumerable strategies look great during some periods but perform horribly over the long-term. Even zany strategies can work in any given year. This is referred to in the literature as the small sample bias, whereby people look at a recent five-year return and expect it to hold true for all five-year periods. The more time studied, the greater the chance a strategy will continue to work in the future. Statistically, you will always have greater confidence in results derived from large samples than in those derived from small ones. Many studies are deeply flawed because they include tiny stocks that are impossible to buy. Unfortunately, no one can realistically buy these stocks at the reported prices. They possess virtually no trading liquidity, and a large order would send their prices skyrocketing. They found that the majority of the issues had virtually no trading volume and that the difference between the bid and the asked price was many times more than percent!

More, the trading costs incurred, even if the stocks could be bought, would be enormous. More recently, a liquidity study conducted by my Systematic Equity Group at Bear Stearns Asset Management continues to find liquidity constraints similar to those found in , with the smallest issues being virtually impossible to buy or sell without huge impact on the underlying prices. Most academic studies define small capitalization stocks as those making up the fifth smallest market capitalization quintile of the New York Stock Exchange. Yet many of these stocks are impossible to trade. Thus, although many small cap funds use academic studies to support their methods, no fund can actually buy the stocks that fuel their superior performance. On paper, these returns look phenomenal, but no way exists to capture them in the real world.

This is vital to keep in mind when you are looking at results that show astonishing returns. Numerous companies disappear from the database because of bankruptcy, or more brightly, takeover. Although most new studies include a research file made up of delisted stocks, many early ones did not. Many studies assumed that fundamental information was available when it was not. For example, researchers often assumed you had annual earnings data in January; in reality, it might not be available until March. This upwardly biases results. These 52 years of data are, to my knowledge, the longest period ever used to study a variety of popular investment strategies. Although the Fama and French data series on growth and value investing go back to the s, they only use a single variable—price-to-book ratio—to segregate stocks into the growth and value categories. I cannot overstate the importance of testing strategies over long periods.

Any study from the early s to the early s will find strong results for value investing, just as any study from the s and s will favor growth stocks. Styles come in and out of fashion on Wall Street, so the longer the period studied, the more illuminating the results. From a statistical viewpoint, the strangest results come from the smallest samples. Large samples always provide better conclusions than small ones. Some pension consultants use a branch of statistics called reliability mathematics that use past returns to predict future performance. This avoids survivorship bias. I developed most of the models tested herein between and Thus, the period — serves as the time when no modifications were made on any of the strategies.

Other studies call this the out-of-sample holdout period. For this Rules of the Game 39 edition of the book, all the Compustat data from to is being accessed through FactSet through their Alpha Testing module. Except for specific small capitalization tests, I review stocks from two distinct groups. Table shows how I created the deflated minimums. The second group includes larger, better-known stocks with market capitalizations greater than the database average usually the top 15 percent of the database by market capitalization. Table shows the number of stocks having market capitalizations above the database mean.

In all cases, I remove the smallest stocks in the database from consideration. In the same year, only 1, stocks had market capitalizations exceeding the database average. I use this figure to avoid micro-cap stocks and focus only on those stocks that a professional investor could buy without running into liquidity problems. I use only publicly available, annual and monthly information. For the period —, I also time lag the data by a minimum of 11 months for the annual data and 45 days for the monthly data, so only data available at the time the portfolio was constructed are used.

Although 11 months may seem excessive on the annual data, it conforms to what you would find using the current database on an annual basis. For the new data from to , we are using the FactSet Alpha Tester, suitably time-lagged, to generate returns. One potential problem with the earlier data is the changing nature of the Compustat database. Many smaller stocks have been added, including up to five years of retroactive data. And because these firms were usually added because they were successful, the likelihood of a look-ahead bias becomes a real concern. Though What Works on Wall Street may suffer from this bias, I think because I eliminate the smallest stocks from consideration, the problem is greatly diminished. I construct and rebalance portfolios annually. the annual rebalance proved optimal. The annual rebalance also allows us to use the data from through , where all we have available is annual data.

Stocks are equally weighted with no adjustments for beta, industry, or other variable. Foreign stocks in the form of American Depository Receipts, or ADRs included in the Compustat Universe are allowed. Due to data limitations, for the period —, I was forced to add dividend returns to capital appreciation to arrive at a total return for the year. This results in a slight understatement of the compounding effect of dividend reinvestment. From on, the results reflect total returns, with full dividend reinvestment. In this edition of the book, I am also including risk statistics obtained through the monthly data, thus allowing me to focus on things like: How often did the strategy do well? What was the worstcase scenario? How long did it take the strategy to recover? I assume no trades are made throughout the year. This may bias my results slightly, because it rewards trade-averse strategies, but I believe many excellent strategies that require numerous trades turn mediocre once trading costs are included.

I also examined annual returns and removed stocks with extreme returns or data that were inconsistent with outside information. Risk-adjusted returns take the volatility of a portfolio—as measured by the standard deviation of return— into account when considering absolute returns. Generally, investors prefer a portfolio earning 15 percent a year, with a standard deviation of 20 percent, to one earning 16 percent a year, with a standard deviation of 30 percent. I use the well-known Sharpe ratio of reward-to-risk for my calculations, with higher numbers indicating better risk-adjusted returns.

To arrive at the Sharpe ratio, simply take the average return from a strategy, subtract the risk-free rate of interest, and then divide that number by the standard deviation of return. Table gives an example. The ratio is important because it reflects risk. I will also show downside risk—which is measured by the semi-standard deviation below zero—allowing me to measure how risky a strategy is when stock prices are declining. I believe that this is a more exact measurement with which to measure risk. Risk-adjusted ratio for the strategy equals 9. Also, in all summary information about a strategy, I provide the maximum and minimum projected returns, as well as the actual maximum and minimum over Rules of the Game 45 the past 52 years.

This is extremely useful information, because investors can glance at the worst loss and decide if they can stomach the volatility of any particular strategy. For each strategy, I now include a number of measurements not available in earlier editions of this book. I generate all the summary statistical information using the Ibbotson EnCorr Analyzer program. In addition to the concepts already covered, each summary result report includes the following: — Arithmetic Average: The average return over the period — Geometric Average: The average annual compound return over the period — Median Return: The return that has 50 percent of all returns above it and below it — Standard Deviation of Return: The extent to which observations in a data series differ from the average return for the entire series. But since approximately 70 percent of all observations are positive, I think that using this to measure overall risk in a portfolio can be misleading. Typically, a T-statistic of ±1.

Thus, a T-statistic exceeding ±1. You can test this by generating a series of random numbers over the period being analyzed. For example, a randomly generated list of numbers over the period — generated a T-statistic of —1. Except for Chapter 4, which reviews returns by market capitalization, all portfolios contain 25 to 50 stocks. In the original edition of the book, we used only 50 stock 46 WHAT WORKS ON WALL STREET portfolios, but we learned in real time that many of our investors preferred more concentrated portfolios to enhance overall returns. Thus, for several of the strategies featured in this edition, we also report on the results of a more concentrated stock portfolio. A cursory review of private and institutional money managers reveals that 50 stocks are a common portfolio minimum. Next, I considered the benefits of diversification. Researchers Gerald Newbould and Percy Poon are professors of Finance at the University of Nevada.

They studied the effect that the number of stocks held in a portfolio has on overall volatility and total return. Rather, they found that to be within 20 percent of the commonly quoted risk and reward figures, an investor has to expand the number of stocks she owns to at least And, if your portfolio contains smaller capitalization stocks, you should hold 50 or more. I test investment disciplines, not trading strategies. My results show that United States equity markets are not perfectly efficient. Investors can outperform the market by sticking with superior strategies over long periods. Simple, disciplined strategies—such as buying the top yielding stocks in the Dow Jones Industrial Average, for example—have worked over the last 75 years because they are immune to the emotions of the market and force investors to buy industrial stocks when they are under distress. No one wants to buy Union Carbide after the Bhopal explosion or Exxon after the Valdez oil spill, yet it is precisely these times that offer the best buys.

Transaction costs are not included. Each reader faces different transaction costs. Institutional investors making million dollar trades face costs substantially different from an individual, odd-lot trader. Thus, each will be able to review raw data and remove whatever costs fit their situation. Since the first edition of this book was published in , however, online brokers have seriously reduced the transaction costs that individual investors pay for trading stocks. This makes buying a large number of stocks a far more realistic idea for the individual, because he now faces costs similar to those of large institutional investors.

Some innovative new brokers also allow clients to trade groups of stocks in baskets, thus you Rules of the Game 47 can now implement many of the strategies featured in this book in an economical fashion. This page intentionally left blank. These benchmarks are based on market capitalization and are called All Stocks and Large Stocks. Large Stocks are those with a market capitalization greater than the Compustat database average usually the top 15 percent of the database by market capitalization. I also look at a universe of small capitalization stocks that have liquidity adequate to allow large-scale trading, and I look at a universe of large capitalization stocks comprised of market-leading companies. In addition to these investable groups, I also focus on shares by various levels of market capitalization.

As with all my tests, the stocks are equally weighted, all dividends are reinvested, and all variables such as common shares outstanding are time-lagged to avoid look-ahead bias. I will also use the monthly data from January forw a rd to establish worst-case scenarios that look at how badly all the various strategies did over the last 40 years. F 49 Copyright © by James P. Table summarizes the results for each universe. You can find the annual returns for all universes at www. The performance was not without bumps, however.

The All Stocks portfolio had a higher standard deviation of return, as well as a higher downside risk, than the Large Stocks portfolio. Also, if you look at the year-by-year results at www. com, you will see that during several periods, All Stocks significantly outperformed Large Stocks and, other times, the reverse was true. better between December 31, and December 31, The All Stocks Universe also had a larger worst-case scenario than Large Stocks: Between January and December , All Stocks had 11 peak-to-trough declines exceeding 10 percent, with the largest occurring between November and September , when the group lost The most recent decline occurred between February and September , with All Stocks losing Table summarizes the results for each group for the period and Table shows the returns by decade.

than 10 percent; how long the decline lasted, and how long it took them to get back to solid ground. The information in Table shows the best and worst returns using the annual data, whereas Table uses the monthly data. The monthly data capture all interyear movements in the various strategies. These data should serve as a framework for investors trying to determine what the worst and best case might be over the periods indicated. For example, an investor with a five-year time horizon who wanted to invest in the All Stocks Universe might see that in all monthly periods over the last 40 years, the worst five years saw a loss of 8.

Investors should search for strategies that have the best upside with the lowest downside, so we feature these data for all of our main strategies. Tables , , and show various worst-case scenarios. The average decline for all losing periods was a loss of nearly 25 percent, and it took 13 months on average to post the decline. This information is extremely useful to review whenever we next find ourselves in a bear market, for it also shows that stocks always go on to recover from even the nastiest of declines. Table shows the base rate for All Stocks versus Large Stocks. Looking at returns for rolling five- and year periods to establish a base rate, we see that All Stocks outperformed Large Stocks in 33 of the 48 rolling five-year periods, or 69 percent of the time. All Stocks also outperformed Large Stocks in 30 of the 43 rolling year periods, or 70 percent of the time.

Most academic studies of market capitalization sort stocks by deciles 10 percent and review how an investment in each fares over time. The studies are nearly unanimous in their findings that small stocks those in the lowest four deciles do significantly better than large ones. We too have found tremendous returns from tiny stocks. Table illustrates the problem. On December 31, , approximately 8, stocks in the active Compustat database had both year-end prices and a number for common shares outstanding. If we sorted the database by decile, each decile would be made up of stocks. A review of the Morningstar Mutual Fund database proves this. When you look at the returns to the All Stocks Universe by market capitalization decile, a fairly different picture emerges. Here, the smallest two deciles by market capitalization had the highest compound return between December 31, and December 31, , and the largest two deciles had the lowest compound returns, but the amounts are not huge: The ninth decile had the highest return Ranking Stocks by Market Capitalization: Size Matters 57 December 31, —December 31, at This conforms to how active managers look at stocks.

They even manage to overcome their breathtaking risk—an annual standard deviation of return of Compounded Annual Return Average Arithmetic Return As I mentioned in the previous chapter, these micro-cap stock returns are an illusion. The only way to achieve these stellar returns is to invest only a few million dollars in over 2, stocks. Precious few investors can do that. The stocks are far too small for a mutual fund to buy and far too numerous for an individual to tackle. So there they sit, tantalizingly out of reach of nearly everyone. Market Leaders are like Large Stocks on steroids. They come from the Large Stocks universe but 60 WHAT WORKS ON WALL STREET also possess characteristics beyond mere size.

To be a market leading company, you must be a nonutility stock with a market capitalization greater than the average, shares outstanding greater than the average, cashflow greater than the average, and finally, sales 50 percent greater than the average stock. Applying these factors to the overall Compustat database leaves just 6 percent of the database qualifying as Market Leaders. SMALL STOCKS ARE THE WINNERS, BUT NOT BY MUCH If we ignore the micro-cap stocks in Figure as unobtainable, the results show that investors who pay no heed to risk or other factors are best off concentrating on smaller stocks from the Compustat database.

These results confirm the academic studies showing smaller stocks beating large stocks, but once micro-caps are removed, by not nearly the large margins that many studies have found. They perform nearly the same as Large Stocks and considerably worse than All Stocks, Small Stocks, and Market Leaders. This contradicts the belief that, simply because a stock is in the smaller category, it offers the greatest potential to investors. Ironically, we have found that when you use strategies like those featured in this book that are looking for maximum return, they inevitably lead you to stocks in the small- and mid-cap category. I believe this is not because of market capitalization alone, but rather because the stocks in this category are the least efficiently priced.

Currently, around stocks account for approximately 75 percent of the U. stock market capitalization, whereas literally thousands of stocks make up the remaining 25 percent. The sheer number of names in the small- and mid-cap category makes them far more difficult for analysts to adequately cover, providing great opportunities to investors willing to use a systematic, disciplined approach to finding those names that possess the factors that have a long association with higher returns. Tables and summarize the findings for these stocks. MARKET LEADERS AND SMALL STOCKS: A BETTER WAY TO CREATE AN INDEX Two additional universes bear special note.

These universes offer a good approximation for the category of blue chip and small stocks. Table shows the returns of each against our All Stocks and Large Stocks universes, and Tables through feature worst-case scenarios; best and worst returns by holding periods; returns by decades; and base rates for Market Leaders versus Large Stocks and Small Stocks versus All Stocks. That compares favorably with the minimum and maximum generated by the All Stocks universe. And when you compare the summary 66 WHAT WORKS ON WALL STREET results featured in Table , you see that Market Leaders supplied double the return of Large Stocks at virtually the same level of risk.

The Russell Indexes are widely used capitalization and style-specific indexes created in Many institutional clients compare their managers to these indexes. Between and , Market Leaders provided nearly double the return of the other two large-cap Ranking Stocks by Market Capitalization: Size Matters 67 indexes and did so with a lower standard deviation of return and significantly lower downside risk. The Market Leaders universe beta was lower than either index, and its Sharpe ratio was much higher. Table shows the annual results since the Russell was created, and Table summarizes the return and risk results for Small Stocks and the Russell I think these results demonstrate that creators of indexes can do a better job than the current committee selection structure that drives much of index creation. If firms that create broad indexes were to use more explicitly stated rules, they could both test the index historically and build a better index for investors who prefer a broad index to a style-specific or conventionally managed portfolio.

Small-cap stocks do outperform larger stocks on an absolute basis but are virtually indistinguishable when risk is taken into account, having Sharpe ratios similar to those of Large Stocks. Remember that higher Sharpe ratios are better. The big surprise is the performance of Market Leaders. They had the highest Sharpe ratio of all stocks that you can actually invest in and proved to be excellent performers over a variety of market cycles. As of December 31, , the All Stocks universe included 3, stocks, ranging from General Electric at the top to Sirenza Microdevices Inc. at the bottom. Each provides an excellent indication of what you can achieve in each capitalization class. For tests that expressly begin with either the Market Leaders universe or the Small Stocks universe, we will include those as benchmarks as well. The higher the PE, the more investors are paying for earnings, and the larger the implied expectations for future earnings growth. Audio Software icon An illustration of a 3.

Software Images icon An illustration of two photographs. Images Donate icon An illustration of a heart shape Donate Ellipses icon An illustration of text ellipses. Search Metadata Search text contents Search TV news captions Search archived websites Advanced Search. A random walk down Wall Street Item Preview. remove-circle Share or Embed This Item. EMBED for wordpress. com hosted blogs and archive. Want more?

edu no longer supports Internet Explorer. To browse Academia. edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Download Free PDF. A RANDOM WALK DOWN WALL STREET W. Norton Company, Gursharanjeet singh. Burton Malkiel. Download Download PDF Full PDF Package Download Full PDF Package This Paper. A short summary of this paper. Download Download PDF. Download Full PDF Package. A RANDOM WALK DOWN WALL STREET The Time-Tested Strategy for Successful Investing BURTON G. MALKIEL W. Investing as a Way of Life Today Investing in Theory The Firm-Foundation Theory The Castle-in-the-Air Theory How the Random Walk Is to Be Conducted 2.

THE MADNESS OF CROWDS The Tulip-Bulb Craze The South Sea Bubble Wall Street Lays an Egg An Afterword 3. The Japanese Yen for Land and Stocks 4. The U. Housing Bubble and Crash of the Early s The New System of Banking Looser Lending Standards The Housing Bubble Bubbles and Economic Activity Does This Mean That Markets Are Inefficient? Part Two HOW THE PROS PLAY THE BIGGEST GAME IN TOWN 5. The Rationale for the Charting Method Why Might Charting Fail to Work? From Chartist to Technician The Technique of Fundamental Analysis Three Important Caveats Why Might Fundamental Analysis Fail to Work? Using Fundamental and Technical Analysis Together 6. TECHNICAL ANALYSIS AND THE RANDOM-WALK THEORY Holes in Their Shoes and Ambiguity in Their Forecasts Is There Momentum in the Stock Market? Just What Exactly Is a Random Walk?

Appraising the Counterattack Implications for Investors 7. Why the Crystal Ball Is Clouded 1. The Influence of Random Events 2. Errors Made by the Analysts Themselves 4. The Loss of the Best Analysts to the Sales Desk, to Portfolio Management, or to Hedge Funds 5. The Conflicts of Interest between Research and Investment Banking Departments Do Security Analysts Pick Winners? Avoid Herd Behavior 2. Avoid Overtrading 3. If You Do Trade: Sell Losers, Not Winners 4. Other Stupid Investor Tricks Does Behavioral Finance Teach Ways to Beat the Market? Four Tasty Flavors: Their Pros and Cons 1. Value Wins 2. Smaller Is Better 3. Momentum and Reversion to the Mean 4.

Foreign Bonds Exercise 7A: Use Bond Substitutes for Part of the Aggregate Bond Portfolio during Eras of Financial Repression Exercise 8: Tiptoe through the Fields of Gold, Collectibles, and Other Investments Exercise 9: Remember That Investment Costs Are Not Random; Some Are Lower Than Others Exercise Avoid Sinkholes and Stumbling Blocks: Diversify Your Investment Steps A Final Checkup Four Historical Eras of Financial Market Returns Era I: The Age of Comfort Era II: The Age of Angst Era III: The Age of Exuberance Era IV: The Age of Disenchantment The Markets from through Handicapping Future Returns A LIFE-CYCLE GUIDE TO INVESTING Five Asset-Allocation Principles 1. Risk and Reward Are Related 2. Your Actual Risk in Stock and Bond Investing Depends on the Length of Time You Hold Your Investment 3. Dollar-Cost Averaging Can Reduce the Risks of Investing in Stocks and Bonds 4.

Rebalancing Can Reduce Investment Risk and Possibly Increase Returns 5. Distinguishing between Your Attitude toward and Your Capacity for Risk Three Guidelines to Tailoring a Life-Cycle Investment Plan 1. Specific Needs Require Dedicated Specific Assets 2. Persistent Saving in Regular Amounts, No Matter How Small, Pays Off The Life-Cycle Investment Guide Life-Cycle Funds Investment Management Once You Have Retired Inadequate Preparation for Retirement Investing a Retirement Nest Egg Annuities The Do-It-Yourself Method The message of the original edition was a very simple one: Investors would be far better off buying and holding an index fund than attempting to buy and sell individual securities or actively managed mutual funds. I boldly stated that buying and holding all the stocks in a broad stock- market average was likely to outperform professionally managed funds whose high expense charges and large trading costs detract substantially from investment returns.

I can make the case with great simplicity. The difference is dramatic. Why, then, an eleventh edition of this book? The answer is that there have been enormous changes in the financial instruments available to the public. A book meant to provide a comprehensive investment guide for individual investors needs to be updated to cover the full range of investment products available. In addition, investors can benefit from a critical analysis of the wealth of new information provided by academic researchers and market professionals—made comprehensible in prose accessible to everyone with an interest in investing. Over the past forty years, we have become accustomed to accepting the rapid pace of technological change in our physical environment.

Innovations such as e-mail, the Internet, smartphones, iPads, Kindles, videoconferencing, social networks, and new medical advances ranging from organ transplants and laser surgery to nonsurgical methods of treating kidney stones and unclogging arteries have materially affected the way we live. Financial innovation over the same period has been equally rapid. Much of the new material in this book has been included to explain these financial innovations and to show how you as a consumer can benefit from them. This eleventh edition also provides a clear and easily accessible description of the academic advances in investment theory and practice. Chapter 10 describes the exciting new field of behavioral finance and underscores the important lessons investors should learn from the insights of the behavioralists.

In addition, a new section has been added to present practical investment strategies for investors who have retired or are about to retire. So much new material has been added over the years that readers who may have read an earlier edition of this book in college or business school will find this new edition rewarding reading. This edition takes a hard look at the basic thesis of earlier editions of Random Walk—that the market prices stocks so efficiently that a blindfolded chimpanzee throwing darts at the stock listings can select a portfolio that performs as well as those managed by the experts. Through the past forty years, that thesis has held up remarkably well. More than two-thirds of professional portfolio managers have been outperformed by unmanaged broad-based index funds. Nevertheless, there are still both academics and practitioners who doubt the validity of the theory.

And the stock-market crash of October , the Internet bubble, and the financial crisis of —09 raised further questions concerning the vaunted efficiency of the market. I will, however, review the evidence on a number of techniques of stock selection that are believed to tilt the odds of success in favor of the individual investor. The book remains fundamentally a readable investment guide for individual investors. It is also the case that the risk involved in many investments decreases with the length of time the investment can be held. For these reasons, optimal investment strategies must be age-related. This chapter alone is worth the cost of a high-priced appointment with a personal financial adviser. My debts of gratitude to those mentioned in earlier editions continue. In addition, I must mention the names of a number of people who were particularly helpful in making special contributions to the eleventh edition.

I am especially indebted to Michael Nolan of the Bogle Research Institute, to my Princeton colleagues Harrison Hong and Yacine Aït-Sahalia, and to my research assistants, David Hou, Derek Jun, Michael Lachanski, and Paul Noh. I am also grateful to John Devereaux, Francis Kinniry, Ravi Tolani, and Sarah Hammer of the Vanguard Group for important assistance in providing data. Karen Neukirchen made an extraordinary contribution to this edition. She was somehow able to decipher my inpenetrable scribbles and turn them into readable text. She also provided research assistance and was responsible for many of the graphic presentations in the book. Sharon Hill added invaluable assistance in the final preparation of the manuscript. My association with W. Norton remains a superb collaboration, and I thank Drake McFeely, Otto Sonntag, and Jeff Shreve for their indispensable assistance in bringing this edition to publication.

Patricia Taylor continued her association with the project and made extremely valuable editorial contributions to the eleventh edition. My wife, Nancy Weiss Malkiel, has made by far the most important contributions to the successful completion of the past seven editions. In addition to providing the most loving encouragement and support, she read carefully through various drafts of the manuscript and made innumerable suggestions that clarified and vastly improved the writing. She continues to be able to find errors that have eluded me and a variety of proofreaders and editors. Most important, she has brought incredible joy to my life. No one more deserved the dedication of a book than she and her second-best friend, Piper.

Burton G. A man who knows the price of everything, and the value of nothing. They point to professional investment strategies using complex derivative instruments and high-frequency trading.

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing,Item Preview

A Random Walk Down Wall Street written by Burton G. Malkiel and has been published by W. W. Norton this book supported file pdf, txt, epub, kindle and other format this book has been 17/04/ · a-random-walk-down-wall-street Identifier-ark ark://t5bd4kh0p Ocr tesseract alphag PDF download. download 1 file. SINGLE PAGE A random walk down Wall Street: including a life-cycle guide to personal investing / Burton G. Malkiel. p. cm. Rev. ed. of: a random walk down Wall Street. c Includes bibliographical 05/03/ · Brief Summary of Book: A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing by Burton G. Malkiel. Here is a quick description and cover 05/09/ · According to the Wall Street Journal, “But the company also runs a mutual fund, and in one of Wall Street’s odder paradoxes, it has performed terribly. Investors following the Book is a A Random Walk Down Wall Street Epub Free Download book that will help you learn the skills and techniques necessary to be successful. If you are A Random Walk Down ... read more

It then took them four years to regain their old highs Tables and com, Crayfish, Zap. What follows is a sampling of several commentaries written in the late s. But the whole mechanism is a kind of Ponzi scheme where more and more credulous investors must be found to buy the stock from the earlier investors. Then they would buy an extra-large stockpile to anticipate a rise in price. The data in this book give perspective. All models must use explicitly stated rules.

In fact, Jones shows no improvement at all. In earlier times, one needed actual revenues and profits to come to market with an IPO. download 15 Files download 6 Original. Dollar-Cost Averaging Can Reduce the Risks of Investing in Stocks and Bonds 4. Here, I acknowledge the many individuals who offered extremely valuable suggestions and criticisms. Buying houses or apartments appeared to be risk free as house prices appeared consistently to go up.