William F. Sharpe

Bio: William F. Sharpe is an academic researcher from Stanford University. The author has contributed to research in topics: Portfolio & Asset allocation. The author has an hindex of 41, co-authored 102 publications receiving 32139 citations. Previous affiliations of William F. Sharpe include University of Washington.

Capital asset prices: a theory of market equilibrium under conditions of risk*

Abstract: One of the problems which has plagued thouse attempting to predict the behavior of capital marcets is the absence of a body of positive of microeconomic theory dealing with conditions of risk/ Althuogh many usefull insights can be obtaine from the traditional model of investment under conditions of certainty, the pervasive influense of risk in finansial transactions has forced those working in this area to adobt models of price behavior which are little more than assertions. A typical classroom explanation of the determinationof capital asset prices, for example, usually begins with a carefull and relatively rigorous description of the process through which individuals preferences and phisical relationship to determine an equilibrium pure interest rate. This is generally followed by the assertion that somehow a market risk-premium is also determined, with the prices of asset adjusting accordingly to account for differences of their risk.

A Simplified Model for Portfolio Analysis

Abstract: This paper describes the advantages of using a particular model of the relationships among securities for practical applications of the Markowitz portfolio analysis technique. A computer program has been developed to take full advantage of the model: 2,000 securities can be analyzed at an extremely low cost—as little as 2% of that associated with standard quadratic programming codes. Moreover, preliminary evidence suggests that the relatively few parameters used by the model can lead to very nearly the same results obtained with much larger sets of relationships among securities. The possibility of low-cost analysis, coupled with a likelihood that a relatively small amount of information need be sacrificed make the model an attractive candidate for initial practical applications of the Markowitz technique.

The Sharpe Ratio

Abstract: . Over 25 years ago, in Sharpe [1966], I introduced a measure for the performance of mutual funds and proposed the term reward-to-variability ratio to describe it (the measure is also described in Sharpe [1975] ). While the measure has gained considerable popularity, the name has not. Other authors have termed the original version the Sharpe Index (Radcliff [1990, p. 286] and Haugen [1993, p. 315]), the Sharpe Measure (Bodie, Kane and Marcus [1993, p. 804], Elton and Gruber [1991, p. 652], and Reilly [1989, p.803]), or the Sharpe Ratio (Morningstar [1993, p. 24]). Generalized versions have also appeared under various names (see. for example, BARRA [1992, p. 21] and Capaul, Rowley and Sharpe [1993, p. 33]).

Asset allocation: management style and performance measurement

Abstract: is widely agreed that asset allocation accounts for a large part of the variability in the return on a typical investor’s portfolio. This is especially true if the portfolio is invested in multiple funds, each including a number of securities. Asset allocation is generally defined as the allocation of an investor’s portfolio across a number of ”major” asset classes. Clearly such a generalization cannot be made operational without defining such classes. Once a set of asset classes has been defined, it is important to determine the exposures of each component of an investor’s overall portfolio to movements in their returns. Such information can be aggregated to determine the investor’s overall effective asset mix. If it does not conform to the desired mix, appropriate alterations can then be made. Once a procedure for measuring exposure to variations in returns of major asset classes is in place, it is possible to determine how effectively individual fund managers have performed their functions and the extent (if any) to which value has been added through active management. Finally, the effectiveness of the investor’s overall asset allocation can be compared with that of one or more benchmark, asset mixes. An effective way to accomplish all these tasks is to use an asset class factor model. After describing 7 5 w 8

Portfolio Theory and Capital Markets

Abstract: William Sharpe's influential Portfolio Theory and Capital Management is as relevant today as when it was first published in 1970. McGraw-Hill is proud to reintroduce tiffs hard-to-Find classic in its original edition. Dr. Sharpe's groundbreaking approach to the Capital Asset Pricing Model (CAPM) laid tile foundation for today's most important investment tools and theories, gave the investment world the stillvital Sharpe Ratio -- and made him the co-recipient of the 1990 Nobel Prize in Economics!A new foreword helps place Dr. Sharpe's synthesis of portfolio and capital markets theories into today's financial environment, while his rules for the intelligent selection of investments tinder conditions of risk remain as fresh today as in 1970. Serious investors and students of finance will respect its history ... as they reabsorb its timeless lessons.

The Pricing of Options and Corporate Liabilities

Abstract: If options are correctly priced in the market, it should not be possible to make sure profits by creating portfolios of long and short positions in options and their underlying stocks. Using this principle, a theoretical valuation formula for options is derived. Since almost all corporate liabilities can be viewed as combinations of options, the formula and the analysis that led to it are also applicable to corporate liabilities such as common stock, corporate bonds, and warrants. In particular, the formula can be used to derive the discount that should be applied to a corporate bond because of the possibility of default.

Efficient capital markets: a review of theory and empirical work*

Abstract: Efficient Capital Markets: A Review of Theory and Empirical Work Author(s): Eugene F. Fama Source: The Journal of Finance, Vol. 25, No. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York, N.Y. December, 28-30, 1969 (May, 1970), pp. 383-417 Published by: Blackwell Publishing for the American Finance Association Stable URL: http://www.jstor.org/stable/2325486 Accessed: 30/03/2010 21:28

The Cross‐Section of Expected Stock Returns

Abstract: Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market 3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in 3 that is unrelated to size, the relation between market /3 and average return is flat, even when 3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972) has long shaped the way academics and practitioners think about average returns and risk. The central prediction of the model is that the market portfolio of invested wealth is mean-variance efficient in the sense of Markowitz (1959). The efficiency of the market portfolio implies that (a) expected returns on securities are a positive linear function of their market O3s (the slope in the regression of a security's return on the market's return), and (b) market O3s suffice to describe the cross-section of expected returns. There are several empirical contradictions of the Sharpe-Lintner-Black (SLB) model. The most prominent is the size effect of Banz (1981). He finds that market equity, ME (a stock's price times shares outstanding), adds to the explanation of the cross-section of average returns provided by market Os. Average returns on small (low ME) stocks are too high given their f estimates, and average returns on large stocks are too low. Another contradiction of the SLB model is the positive relation between leverage and average return documented by Bhandari (1988). It is plausible that leverage is associated with risk and expected return, but in the SLB model, leverage risk should be captured by market S. Bhandari finds, howev er, that leverage helps explain the cross-section of average stock returns in tests that include size (ME) as well as A. Stattman (1980) and Rosenberg, Reid, and Lanstein (1985) find that average returns on U.S. stocks are positively related to the ratio of a firm's book value of common equity, BE, to its market value, ME. Chan, Hamao, and Lakonishok (1991) find that book-to-market equity, BE/ME, also has a strong role in explaining the cross-section of average returns on Japanese stocks.