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A multifaceted approach to value investing with stock valuation based on intrinsic value estimated from cash returns, appraised value of assets, and other facets of value.

 

 

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Major additions to the web site will be announced here. The most recent additions to the web site will be posted on the Site Map. If you've visited us before and want to know what's changed, take a look there first for new additions and updates. All major pages, topics, and links will be posted on the Site Map. All pages are subjected to an ongoing process of review and editing.

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The DCF
Valuator is available for free access! This online interactive application calculates intrinsic economic value and has an intuitive dialogue-style user interface that walks the user through the calculations and asks for the necessary data at each step. Several valuation models are available. The application calculates a deterministic single-point estimate of intrinsic value and safety margin based on expected dividends or free cash flow to common stock equity owners according to different dividend or cash return forecast patterns. The rate of return calculation optionally includes brokerage fees, income taxes, and currency exchange rate fees for investments in foreign stock markets. The application also optionally calculates a probabilistic estimate of a range of intrinsic value using Monte Carlo simulation, sensitivity analysis of changes in intrinsic value resulting from changes in key variables, and graphical and tabular presentation of results. For more information, go to the DCF Valuator.


Upcoming

Look here for upcoming original book reviews and other features. Completed book reviews can be found in the section that follows this list.


See below The Motley Fool Investment Guide: How the Fool Beats Wall Street's Wise Men and How You Can Too, David and Tom Gardner, 1996, New York: Simon & Schuster.

In reviewing of The Motley Fool, we consider the questions, Is the so-called Fool Ratio (Price-to-Earnings divided by Earnings Growth Rate, or PE/EGR) just another financial fad? and if not, Can it be used to select stocks for purchase?


See below The New Finance: The Case Against Efficient Markets, 1995, Robert A. Haugen, paperback 146 pages, $26.00, Englewood Cliffs, NJ: Prentice Hall.

In this review, we consider the questions, When is it correct to use the Capital Asset Pricing Model and its associated beta coefficient for risk? When is the Efficient Market Hypothesis valid? When is it appropriate to specify book-to-market value, size, or other circular variables in an asset pricing model to explain total return?


Upcoming The Witch Doctor of Wall Street: A Noted Financial Expert Guides You Through Today's Voodoo Economics, 1996, Robert H. Parks, Ph.D., Amherst, NY: Prometheus Books.

In this review, we consider the questions, Can the world of investing really be reduced to the roles of Prostitutes (Pros) and Parrots? and if so, Where does the Witch Doctor belong?


Upcoming The Alchemy of Finance: Reading the Mind of the Market, George Soros, 1994, 2nd edition, New York: John Wiley & Sons.

In this review, we consider the questions, Is George Soros a financial alchemist? and if so, Can he make people more successful investors?


Upcoming Investor Capitalism: How Money Managers are Changing the Face of America, Michael Useem, 1996, New York: BasicBooks, a division of HarperCollins.

In this review, we consider the questions, Does corporate governance contribute to corporate performance? and if so, Under what conditions?, and How much impact does it have?

As a preview, we quote Graham & Dodd (Security Analysis, 1934): On page 26, "It is a matter of great moment to the analyst that the facts be fairly presented, and this means that he must be highly critical of accounting methods. Finally, he must concern himself with all corporate policies affecting the security owner, for the value of the issue which he analyzes may be largely dependent upon the acts of the management. In this category are included questions of capitalization set-up, of dividend and expansion policies, of managerial compensation, and even of continuing or liquidating an unprofitable business." And on page 330, "But if stockholders' opinion were properly informed, it would insist upon curtailing the despotic powers given the directorate over the dividend policy. Experience shows that these unrestricted powers are likely to be abused, and for various reasons. Boards of directors usually consist largely of executive officers and their friends. The officers are naturally desirous of retaining as much cash as possible in the treasury, in order to simplify their financial problems; they are also inclined to expand the business persistently for the sake of personal aggrandizement and to secure higher salaries."

Money managers or institutional investors, unlike most individual investors, have the wherewithal to influence company management when it diverges from the interests of the company stockowners. Corporations have available a number of defensive mechanisms called "shark repellents" that can be included in their charter or a bylaw. These mechanisms serve to make an unfriendly takeover more difficult and costly. The deterrent effect had mixed results and so led to the "poison pill." These delaying tactics share the common purpose to obstruct the market for corporate control by either precluding bids or increasing the expense of buying a controlling interest in a target company. In a poorly performing company, the current stockowners lose at the expense of an entrenched management that has not efficiently used the assets under its control to enhance stockowner value and thus discourage such takeover attempts. The best defense is operational performance that is superior to competitors.


Upcoming The Theory of Investment Value, John Burr Williams, 1938, 1997 (reprint, paperback), Burlington, VT: Fraser Publishing (800-253-0900).

In this review, we consider the questions, Does the appraisal of absolute intrinsic economic value still stand as the most authoritative method of common stock valuation? and if so, Why does it not become popular and thereby lose its competitive advantage like other approaches to investment strategy?

Williams explains the need for theory to support any practical valuation method in terms of traditional scientific methodology (1938: 188): "Without the hypothesis, how should we know what data to look for, what constants to determine, what properties to measure? ... It shows us what is relevant and why." The failure to skip theory and go straight to data analysis in search of so-called significant relationships is known euphemistically as "data snooping."

This book is required reading for any serious intrinsic value investor. This is the only known book about the theory and practice of true, pure, intrinsic value investing. True value refers to long-run economic value. Pure value refers to the absence of accretions such as market timing and beta coefficients. Intrinsic value refers to the present value of discounted cash flows generated by a company for its stockholders. Book II contains the basic principles and concepts of investment value theory. Book II contains case studies in the application of this theory to the practical valuation of stocks. The cases are timeless in their method even though dated in their specific data.

See the
theory page for the preface, author biography, and contents of this classic book.


Book Reviews

The following reviews are listed in reverse chronological order.


July 19, 1997. Robert A. Haugen, The New Finance: The Case Against Efficient Markets, 1995, paperback 146 pages, $26.00, Englewood Cliffs, NJ: Prentice Hall.

This trade paperback book is targeted at individual investors. Written in a tone of evangelical fervor, the book is replete with religious metaphors. Professor Haugen professes to truly believe in the findings of Professors Eugene F. Fama and Kenneth R. French (FF) in their "celebrated study" presented in the academic journal article entitled "The Cross-Section of Expected Stock Returns" [The Journal of Finance, Vol. XLVII, No.2, June 1992: 427-465] announcing that the book-to-market equity ratio (used to distinguish between so-called "value" stocks and so-called "growth" stocks) and to a lesser degree so-called "firm size" (market capitalization of equity, used to distinguish between small-cap and large-cap stocks) are each superior to the CAPM beta in the explanation of the variation in expected return on equity or investment in common stocks. Book-to-market equity is a combination of accounting and market measures, and size is a market measure. Neither of these is an economic measure.

The author focuses on a single measure, the book-to-market equity ratio (BV/MV) which is used to distinguish between "value" stocks, those with higher BV/MV, and "growth" stocks, those with lower BV/MV. A value stock is defined here as a stock for which future earnings-per-share (EPS) are expected to grow at slower than average rate. A growth stock is defined here as a stock for which future EPS are expected to grow at faster than average rate. The author informs individual investors that they now have a "Golden Opportunity" (GO) to invest in low BV/MV stocks which miraculously provide both higher returns and lower risks. Risk in this case is measured by the beta coefficient of the conventional Capital Asset Pricing Model (CAPM). According to the author, the GO premium is still present after accounting for the effect of firm size. This adjustment is necessary because "We now know that value stocks tend to be small stocks." We are also told that value and growth have many faces; to wit, low market price to current EPS (P/E ratio), high dividend per share to market price (dividend yield or D/P ratio), and low trailing growth rates in EPS are facets of value, and their opposites are facets of growth.

FF extend this study in a second academic journal article entitled "Common Risk Factors in the Returns on Stocks and Bonds" [Journal of Financial Economics 33, 1993:3-56]. They elaborate the study further in a third article entitled "Multifactor Explanations of Asset Pricing Anomalies" [The Journal of Finance, Vol. LI, No. 1, March 1996:55-84], and the three multiple factors are beta, book-to-market equity, and size. All three FF articles are fundamentally and fatally flawed due to circularity on theoretical, methodological, and empirical grounds as explained in new research (see the Screening, Fads, and Author pages).

First, let us consider the theoretical flaws. Both the book-to-market ratio and market capitalization (firm size) are members of a group of variables that are circular in their explanation of total return because they are not independent of return. The circular explanatory variable and the explained variable, return, must be either contemporaneous or non-contemporaneous. Models that include circular variables are tautological when the circular variable and return are contemporaneous. Such models are autoregressive when the circular variable and return are non-contemporaneous or lagged. Autoregressions are an example of market timing as in the charting of moving averages. A model can be specified as a combination of tautology and autoregression. In the case of either tautology or autoregression, a vicious circle exists. A tautology contributes no new information. And as Benjamin Graham succinctly writes in Security Analysis: "Chart reading cannot possibly be a science". Attempting to predict future prices from past prices goes by various names including charting, technical analysis, market analysis and market timing.

These are not merely mathematical arguments. The symbolic logic of mathematics is superior to the language of ordinary social discourse for purposes of expressing the underlying economic arguments. It helps to demystify the obfuscation. The recourse to proxies is exemplified, without the technobabble, as follows: The specified, identified, circular factor somehow, somewhere, sometime may, under some conditions, be a highly-correlated proxy for some other unspecified, unidentified, unknown factor that somehow, somewhere, sometime may, under some conditions, contribute to the explanation of the variation in expected total return. The mystery factor is invoked in an attempt to evade the rigors of Karl Popper's criterion of falsifiability in scientific inquiries. If a statement can be neither proved nor disproved, then it is merely an assertion. If an hypothesis cannot be falsified or rejected in a statistical test, then it is not amenable to scientific study. An appeal to intuition goes beyond the scope of both science and philosophy.

Next, let us consider the methodological flaws. The model testing in these articles involves indirect data snooping due to the prior extensive testing of these variables by other researchers using the CRSP database of monthly returns. In addition, there is specification of circular variables, not directly in the formulation of the model estimating equation, but indirectly as a result of the method of grouping the data observations into portfolios.

Last, let us consider the empirical flaws. Firm size is defined not in terms of a stable measure such as sales, assets or number of employees but rather in terms of the market value of equity which changes with share price. In addition, the operational definition of firm size is end of contemporaneous calendar month of June each year rather than end of fiscal year which is not only readily available without calculation but also more accurate due to Treasury stock transactions that are captured only in the fiscal year end data. Therefore, the size factor is not only circular but also biased toward statistically significant results, and there is no report of testing for robustness on this obvious important point. In addition, the data sample is misused in such as way as to result in double counting, again biasing the statistical tests toward significant results. Both the unexpected silences and the unusual careful choice of words indicate that FF know exactly what they are doing. Their statistical hypothesis tests are highly dubious. Retesting after removing these and other sources of avoidable bias is clearly warranted. Their professional colleagues and others alike have to read very attentively and think critically for themselves or risk the consequences.

For these reasons, Professor Haugen's recommended investment strategy, the Golden Opportunity of the new finance represented by the premium for so-called value stocks, is neither rigorous, robust, nor valid. Rather, it is tantamount to closet market timing.

These articles may be well written by the guidelines and templates of academic journals, but they still remain fanciful fabrications and sheer speculation. It is interesting to note that Professor Fama is the Advisory Editor of the Journal of Financial Economics, and Professor French is an Associate Editor of both The Journal of Finance and the Journal of Financial Economics. In addition, Professor René M. Stulz, the Editor of The Journal of Finance, in the title-page footnote of each of the two articles appearing in that journal, is listed among the academic colleagues whose helpful comments were acknowledged by Professors Fama and French. Similarly, Professor G. William Schwert, an Associate Editor of The Journal of Finance and an Editor of the Journal of Financial Economics, is so credited in the latter two FF articles, one in each of these journals. Likewise, other Associate Editors of both journals are so credited.

The stock market is indeed inefficient (see new research at Author page) but not because of circular factors in an asset pricing model. Valid scientific research using justifiable factors properly defined without avoidable biases might identify statistically significant pricing anomalies. Claiming to be an empiricist is not a license to ignore either established scientific theory or sound scientific methodology. Purely ad hoc data-instigated factors, blind (not prespecified) factor fishing, data snooping, and biased use of data are not science, but rather scientism or science fiction. Furthermore, valid findings of market pricing anomalies which indicate informational inefficiencies have nothing necessarily to do with the independent valuation process (see the Safe Margin page). The Capital Asset Pricing Model (CAPM), as its name implies, is merely a pricing model and not a valuation model. Market price quotations are not intrinsic economic value.

On the back cover, it states that Professor Haugen is the "author of more than fifty articles in the leading journals in finance and five books ...". The author, in praising the FF book-to-market finding as the Holy Grail, writes that the "study was voted as the best article published in the Journal of Finance in 1992 by the widest margin in history! The Journal of Finance is the oldest and most prestigious journal in academic finance."

How could this book happen? Finance and financial economics (itself a blend of macroeconomics, microeconomics, and finance) are highly specialized and technical fields of study. They share the occupational hazards of other professions that require many years of advanced formal education. For a long time, scholars have recommended a liberal education as an antidote for the narrowness of specialization. In addition finance and financial economics academicians, like most professionals, tend toward insularity. One academician was quoted in the Wall Street Journal as saying that academic conferences were invitations to group think. In order to understand what is really going on behind the easily observable phenomena, one must turn from economic science and sociology to political science. That is another story.

What is wrong with this picture? The publisher expects to make a commercial profit, and the author expects to advance his academic career. But from the perspective of the real-world practitioner of investing, the book misses the mark. Investors cannot reasonably expect to improve their investment performance by following the explicit investment strategy recommended by Professor Haugen on the basis of fatally flawed academic research. Writing about investment strategy is qualitatively different from placing your lifetime savings at risk in the stock market.

Who cares? The promotional material dated January 15, 1997, for one mutual fund explains its investment strategy as follows. "Selecting [stock] positions involves adhering to our strict value methodology, which has foundations in empirical research done by academia including: smaller market capitalizations and low price-to-book ratios." A portfolio manager with CFA, CMA and CFA designations at this mutual fund was asked what particular academic research served as their foundation, and he instantly replied that it was the Fama and French 1992 article in the Journal of Finance.

What is the impact? The cost in terms of societal welfare of the misallocation of savings to inappropriate investments is reflected in the total net asset value of small-cap mutual funds in excess of $100 billion in the first quarter of 1996, and size is only one of the circular variables alleged to explain total return. Of course these negative externalities usually are either ignored or downplayed, common symptoms of a case of psychological denial.

Does it matter? Better-informed and more-rational investors lead to more transparent and efficient capital markets which in turn lead to greater economic, political, and societal stability which in turn leads to enhanced global competitiveness with resulting increases in economic growth, opportunities and hope for all humanity in the future. Some people believe that anything that interrupts this process is harmful rather than beneficial.


April 1, 1997. Gardner, David, and Tom Gardner. The Motley Fool Investment Guide: How the Fool Beats Wall Street's Wise Men and How You Can Too, 1996, New York: Simon & Schuster.

The co-authors recommend two investment strategies. One is the Dow Dividend Strategy which is based on the highest dividend-yields among the 30 common stocks comprising the Dow Jones Industrial Average (DJIA). Dividend yield is equal to dividends per share divided by share price. The other is the Small-Cap Growth Strategy which is based on the lowest Fool Ratios among all market traded stocks. The capitalization of a firm is the market value of its common stock equity.

These investment strategies and criterion seem to implicitly assume that public market quoted price equals private appraised intrinsic value. They are concerned with average prices of all stocks across a number of historical trading sessions as opposed to the appraised value of the stock of an individual operating enterprise at the present point in time.

The Dow Dividend Strategy rationalization is that companies whose price has been depressed due to recent bad news yet which continue to pay dividends at the same or higher level tend to rebound. This, of course, presumes that any of the 30 DJIA stocks is depressed as such at all times, let alone the five DJIA stocks with the highest dividend yields at the time of selection. This is also implicitly a large-cap investment strategy because the 30 DJIA stocks are the largest of the large stocks.

More importantly, the dividend-yield strategy is fallaciously based on the dividend factor which is logically circular when specified in any capital asset pricing model designed to explain total return. Total return (R) is the sum of capital gain/loss or price change (P2-P1) and dividend income (D), divided by share price, i.e., R=[(P2-P1)+D]/P1, where P2 is the ending price and P1 is the beginning price. Dividends (D) and dividend yield (D/P) are circular because the alleged explanatory variable, say D, cannot be isolated from the explained variable, R. Thus D cannot
independently explain R. No variable can explain itself in any meaningful or useful sense. Thus, a factor cannot be both the explained and the explanatory variable in a model at the same time.

Circular models are either (1) mathematical identities known as tautologies, when the variables are contemporaneous, and or (2) data-instigated autoregressions, when the variables are time-lagged. Autoregressions of certain types can be mathematically inverted into equivalent moving averages, a common tool of momentum investors and chartists. In either case, there is no
a priori theoretical rationale for including a circular factor in a model and thus no scientific basis for it. The ad hoc market-generated factors that make these models circular are examples of feedback trading.

Similarly, but less obviously, the small-cap growth strategy is fallaciously based on the size factor. Firm size or capitalization equals share price times the number of shares outstanding. Size is thus logically circular with return, because share price is entailed in total return. See the
Fads page for more about the dividend and size factors, and also go to the Styles page for further information about the size factor.

Again similarly, but even less obviously, the Fool Ratio screening criterion is fallaciously based on the P/E factor (P/E) which is logically circular because it entails share price (P) which in turn is entailed in total return. The Fool Ratio is the ratio of price-to-earnings ratio (P/E) to earnings-growth-rate (EGR), expressed as a percentage, where P is share price, E is the historical 12-months trailing earnings per share, and EGR is the average annualized forecast 2-year earnings per share growth rate. Thus, the Fool Ratio is equal to (P/E)/(EGR). It is not clear that the Fool Ratio and Small-Cap Growth stocks are highly correlated. It is possible for a large-cap non-growth stock to have a relatively low Fool Ratio.

Circular models are most commonly and most directly manifested in the graphical analysis exemplified by charting techniques.. The visual interpretation of charts of fluctuations in economic time sequences such as common stock prices is often subjective, intuitive, and impressionistic. Chartists, for example, try to prophesy the timing of turns in the stock market between bull expansions and bear contractions.

The authors rightly ridicule charting or so-called technical analysis and other market timing techniques, but they unknowingly commit the same mistake by using circular factors in their attempt to explain and predict common stock returns. As every mutual fund prospectus states explicitly: "Past performance is no guarantee of future results."

An analogy to these two investment strategies and the selection criterion may be useful. It can be observed that on average turkeys eat regularly and get fatter day by day. But this does not explain the sudden drop in the turkey population in the days just before Thanksgiving each year. There is a November effect at work here, or more broadly speaking, a holiday and movable feast effect. There may be a more general Fowl effect that goes beyond turkeys. In addition, the smaller birds as a group appear to survive and thrive significantly more than the larger birds of each species. Clearly there is an observable Fowl Size effect at work.

The simultaneous application of a large-cap and a small-cap strategy reveals the ad hoc nature of these recommendations. There is no theoretical framework. The large-cap and dividend-yield strategy, the small-cap and earnings growth strategy, and the Fool Ratio selection criterion are fatally flawed on three levels: theoretical, methodological, and empirical. Failure on any of these levels renders the strategy or criterion unsound for investment purposes.

First, at the theoretical level, they fail to distinguish between price and value. Implicitly, they assume that price equals value for all stocks at all times. Simple observation shows this to be untrue. Several books cited in the
General Books discuss the history of U.S. stock market crazes. An investment strategy based on a circular factor can use a simple heuristic rule of thumb like the Fool Ratio or a highly sophisticated mathematical model akin to rocket science such as nonlinear stochastic dynamics or artificial intelligence as in neural networks or genetic algorithms. Regardless of the degree of complexity of the mathematics, models that specify a circular factor in the sense explained above are not logically valid.

Second, at the methodological level, studies that allege to prove the success of these investment strategies appear to be a product of so-called data snooping. The research design for the statistical testing of hypotheses is fatally flawed. Thus, the findings of such studies are not scientifically valid. Data snooping is not valid science, and it is not ethical science. One of the two co-authors reportedly once taught business and investing at the university level. If he has a Ph.D. degree, he should know better.
One must not verify an idea using the same data that suggested the idea in the first place.

Third, at the empirical level, in the best of samples these studies report statistical artifacts that result from ignoring sound established generally accepted theory and from violating scientifically-valid methodology. In any given historical sample of stock returns, some group of stocks will have outperformed other groups.

These arguments are not merely abstract mathematics. Probability theory, inductive statistics, hypothesis testing, and the symbolic logic of mathematics express underlying economic principles, concepts and arguments. Social languages are ambiguous and cumbersome by comparison. Those unfamiliar with these topics may need to study them to fully understand these arguments.

In conclusion, the co-authors offer investment advice that is foolish in the traditional sense of the word which they try their best to obfuscate. That they label and successfully market their book as foolishness may be an indication of the final stages of a long-running bull market.


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