...in the returns stocks and bonds* Eugene F. Fama and Kenneth R. French 1992 Unirrrsit.v 01 Chicayo. Chiccup. I .L 60637, C;S;L Received July 1992. final version received September on This paper identities five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors. related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates. the bond-market factors capture the common variation in bond returns. Most important. the five factors seem to explain average returns on stocks and bonds. 1. Introduction The cross-section of average returns on U.S. common stocks shows little relation to either the market /Is of the Sharpe (1964tLintner (1965) assetpricing model or the consumption ps of the intertemporal asset-pricing model of Breeden (1979) and others. [See, for example, Reinganum (198 1) and Breeden, Gibbons, and Litzenberger (1989).] On the other hand, variables that have no special standing in asset-pricing theory show reliable power to explain the cross-section of average returns. The list of empirically determined averagereturn variables includes size (ME, stock price times number of shares), leverage, earnings/price (E/P), and book-to-market equity...
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...Chapter 6. Risk, Return, and CAPM Dollar return: Amount to be received-Amount invested Rate of return: Amount received-Amount investedAmount invested Stand-alone risk is the risk an investor has in just holding the one asset Expected rate of return: r=i=1npiri Where P is probability of i outcome and r is the rate of return The more leptokurtic the distribution, the more likely the actual outcome will be closer to the expected return. Measuring Standalone Risk: Standard Deviation 1. Expected Rate of return 2. Deviationi= ri-r 3. Variance=σ2=i=1n( ri-r)2Pi 4. Standard Deviation=σ=Variance 5. Or use Excel of Financial calculator Using Historical Data to Measure Risk: Realized Rates of Return: rAvg=t=1nrtn Standard Deviation of the Sample Returns: σ=S=t=1n(rt-rAvg)n-1 In Excel use =Average and =STDEV functions Measuring Standalone Risk: Coefficient of Variation Coefficient of variation = CV=σr Risk Aversion and Required Rate of Return Assume risk aversion for investors Textbook Example: Basic Food’s Price up to $150 from $100 Sale.com Price down to $75 from 100. Difference in return, 20%-10%= Risk Premium Risk in Portfolio Context Expected return on portfolio=Weighted expected return=rp=i=1nwiri Portfolio Risk Stocks can be combined into portfolios which then become less risky to riskless depending on the correlation of the assets. Stocks with a ρ=-1 are perfectly negatively correlated. The inverse is positively correlated. Expected...
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...of capital market in Bangladesh mainly started with the beginning of trading activities of Dhaka Stock Exchange. It first incorporated as East Pakistan Stock Exchange Association Ltd in 28 April 1954 and started formal trading in 1956. It was renamed as East Pakistan Stock Exchange Ltd in 23 June 1962. Again in 13 May 1964 it was renamed as Dacca Stock Exchange Ltd. After the liberation war in 1971 the trading was discontinued for five years. In 1976 trading restarted in Bangladesh. In 16 September 1986 was started. The formula for calculating DSE all share price index was changed according to IFC in 1 November 1993. The automated trading was initiated in 10 August 1998. In 1 January 2001 was started. Central Depository System was initiated in 24 January 2004. As of November 16, 2009, the benchmark index of the Dhaka Stock Exchange (DSE) crossed 4000 points for the first time, because of the debut of Grameen Phone in DSE. From the year 2007 the market capitalization is growing at a constant pace. The market is growing both in capitalization and trading volume. The growth is fueled by increased demand for financial assets and influx of liquid money. The growth is outpacing the growth of the national economy. Sudden rise of capitalization in DSE has raised the question, whether the growth has been healthy and market is functioning in a justifiable manner. [pic] Because economic development of a country is deeply related the development of country. If the market grows and...
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...management to describe stock returns. Unlike the CAPM, which uses only the market risk factor, in the Fama and French Model, two more factors are identified that cause stocks to do better than the market as a whole – the size factor and the value factor. This paper will first describe the methodology behind the size and value factor calculations. We will then discuss possible explanations as to why the two factors explain stock returns. Finally, we determine on the basis of academic evidence whether the two factors capture systematic risk. The three-factor model is mathematically expressed as follows: Where: ------------------------------------------------- r = portfolio expected return ------------------------------------------------- Β3 = “three factor” beta (conceptually analogous to the CAPM beta but not equal to it due to the presence of the two other coefficients in the regression) ------------------------------------------------- (Km- Rf) = market risk premium ------------------------------------------------- bs = sensitivity of expected return to size factor ------------------------------------------------- SMB = Small (market capitalisation) minus big ------------------------------------------------- bv = sensitivity of expected return to value factor HML = high (book to market ratio) minus low Fama and French (1992a) found that the historical-average returns on stocks with small market capitalisations and higher book-to-market ratios are higher than...
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...THE JOURNAL OF FINANCE • VOL. LVI, NO. 6 • DEC. 2001 The Stock Market Valuation of Research and Development Expenditures LOUIS K. C. CHAN, JOSEF LAKONISHOK, and THEODORE SOUGIANNIS* ABSTRACT We examine whether stock prices fully value firms’ intangible assets, specifically research and development ~R&D!. Under current U.S. accounting standards, financial statements do not report intangible assets and R&D spending is expensed. Nonetheless, the average historical stock returns of firms doing R&D matches the returns of firms without R&D. However, the market is apparently too pessimistic about beaten-down R&D-intensive technology stocks’ prospects. Companies with high R&D to equity market value ~which tend to have poor past returns! earn large excess returns. A similar relation exists between advertising and stock returns. R&D intensity is positively associated with return volatility. THE MARKET VALUE OF A F IRM’S SHARES ultimately ref lects the value of all its net assets. When most of the assets are physical, such as plant and equipment, the link between asset values and stock prices is relatively apparent. In modern economies, however, a large part of a firm’s value may ref lect its intangible assets, such as brand names. Under generally accepted U.S. accounting principles, many types of intangible assets are not reported in firms’ financial statements. When a firm has large amounts of such intangibles, the lack of accounting information generally complicates the task of...
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...3 1. Design a multifactor model with at least 2 factors besides the market factor, and answer the following questions. a) What makes your choice of factor a “factor” in multifactor model? b) Does the factor of your choice co-move with the market factor? If yes, should you include it along with the market factor? c) Describe how the stock return would be affected when the factor of your choice changes. d) Describe a scenario where one can benefit from trading on the factor of your choice. a) There is a variety of factors that can determine the returns on security. The market based factor is the return on the broad market index such as S&P 500. This market return is one of the factors in the model. Other factors include the following: • GDP growth rate. This factors shows overall macroeconomic conditions that tend to affect a stock’s performance. • Risk free rate of return. • 10 year T-bond interest rate that shows the required return on 10-year government bonds. • A company’s ROE as an indicator of its profitability. Therefore, the model will look like this: [pic], where betas show the sensitivity of return to the factor, rm is the market rate of return, rf is the risk-free rate, T-bond is the 10-year T-Bond rate and ROE is the return on equity (ROE). Generally, GDP has a positive effect on a stock return. Higher economic growth leads to more business opportunities and potentially...
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...Regression Analysis of Verizon Communications, Berkshire Hathaway, and Wyndham Worldwide The stock market plays a pivotal role in the world today, bringing together investors with companies looking to raise funds. The government, organizations, and individual shareholder’s all have a stake in actively following and participating in the stock market. The problem that hinders common traders and professional investors alike becomes differentiating between the thousands of publicly traded companies in the U.S. alone to pick the best investments. By comparing three large, but very different companies to the market as a whole this paper will demonstrate how Beta can be used to measure the volatility of a stock. The three dependent variables will be acquired from historical stock returns from the communications conglomerate Verizon Communications (VC), Berkshire Hathaway Inc. (BRK-A) the multinational holding company best known its chairman Warren Buffet, and Wyndham Worldwide Corporation (WYN) one of the world’s largest hotel and resort chains. After comparing relevant statistical factors to each other a regression analysis will be done for each company comparing the excess market returns for each company (found by subtracting out the market free rate) to the market excess return. Table 1: Stock Return Statistics | Average Price/Share | Mean Return | Largest Gain | Largest Loss | Standard Deviation | Coefficient of Variation | VZ | $34.73 | 1.43% | 12.58% | -10...
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...that well-performed stocks continue to outperform their peers while poor-performed stocks continue to underperform. Thus, more mutual funds use this powerful strategy to draw a broad range of investors by getting higher risk-adjusted returns. AQR is a hedge fund based in Greenwich, Connecticut, offering investing products that applies price phenomenon known as momentum. This case study enables investors to get a closer look at AQR’s momentum fund. Comparison of momentum specifications In order to analyze the momentum effect of different specifications, stocks were divided into ‘winner’ stocks and ‘loser’ stocks according to their rankings. From the data we can see that the decile spread portfolio return is the highest among these momentum specifications. One may argue that the spread between decile 10 and decile 1 is largest and it also has the highest volatility. After adjusting for volatility (using Sharpe Ratio), the decile spread momentum advantage is reduced but still very significant. According to Figure 1.1 and 1.2, raw spread returns witness a sharp decrease as the chosen percentile of highest and lowest stock return increases. After adjusted by volatility, the difference becomes flatter but still significant. From the graphs we can see that the volatility-adjusted return of decile spread is higher than the UMD spread, which means buying top 10% winner stocks and shorting bottom 10% loser stocks earns more profit than buying top 30% winner stocks and shorting bottom...
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...really had to watch the markets in order to obtain a successful portfolio. The way we approached this task was through constant watching of the securities market to find out current trends as well as picking up stocks we thought were undervalued at that time. The latter, of course, applies to our managed portfolio, where we were able to select stocks we deemed were good investments. We observed that this specific portfolio gave us more stable returns, which we attributed to the lower betas of these stocks. One can also conclude that the worst performers of the same portfolio were due the same cause. Based on the returns of our managed portfolio, one can conclude that we chose to take a safe approach and invest in stocks that had low, but steady returns and growths. At the end of the semester, our strategy proved to be successful based on our overall returns. On the other hand, our control portfolio, which takes a passive management approach, had a different outcome. In this type of management, it is imperative that one waits a longer period of time to receive the expected returns. However, we had surprising results as our stocks for this portfolio had large returns. We believe that this exceptional result was due our clever choice of industry. Also, the worst performers of this portfolio presented larger negative returns than we predicted. We also attribute these results to the betas of the stocks that were relatively high, therefore yielding a higher stock price volatility. Another...
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... independently developed by John Lintner (1965), Jan Mossin (1966) and William Sharpe (1964). In equation form the model can be expressed as follows: E (Ri) = Rf + (i [E(rm) – Rf] = Rf +(im / (m (E(Rm) – Rf / (m) Where E(Ri) is expected return on asset i, Rf is the risk-free rate of return, E(Rm) is expected return on market proxy and (i; is a measure of risk specific to asset i. This relationship between expected return on asset i and expected return on market portfolio is also called the security market line. If CAPM is valid, all securities will lie in a straight line called the security market line in the E(R), (i frontier. The security market line implies that return is a linearly increasing function of risk. Moreover, only the market risk affects the return and the investor receive no extra return for bearing diversifiable (residual) risk. The set of assumptions employed in the development of the CAPM can be summarized as follows [Sears and Trennepohl (1993)]: 1. Investors are risk-averse and they have a preference for expected return and a dislike for risk. 2. Investors make investment decisions based on expected return and the variances of security returns, i.e. two-parameter utility function. 3. Investors behave in a normative sense and desire to hold a portfolio that lies along the efficient frontier. These three assumptions were also made in the development of the Markowitz and Sharpe single-index portfolio analysis...
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...Journal of Financial Economics 49 (1998) 283—306 Market efficiency, long-term returns, and behavioral finance Eugene F. Fama* Graduate School of Business, University of Chicago, Chicago, IL 60637, USA Received 17 March 1997; received in revised form 3 October 1997 Abstract Market efficiency survives the challenge from the literature on long-term return anomalies. Consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction to information is about as common as underreaction, and post-event continuation of pre-event abnormal returns is about as frequent as post-event reversal. Most important, consistent with the market efficiency prediction that apparent anomalies can be due to methodology, most long-term return anomalies tend to disappear with reasonable changes in technique. 1998 Elsevier Science S.A. All rights reserved. JEL classification: G14; G12 Keywords: Market efficiency; Behavioral finance 1. Introduction Event studies, introduced by Fama et al. (1969), produce useful evidence on how stock prices respond to information. Many studies focus on returns in a short window (a few days) around a cleanly dated event. An advantage of this approach is that because daily expected returns are close to zero, the model for expected returns does not have a big effect on inferences about abnormal returns. * Corresponding author. Tel.: 773 702 7282; fax: 773 702 9937; e-mail: eugene.fama@gsb.uchicago. edu. The comments...
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...Calculating The Beta Coefficient And Required Rate Of Return For Coca-Cola John C. Gardner, University of New Orleans, USA Carl B. McGowan, Jr., Norfolk State University, USA Susan E. Moeller, Eastern Michigan University, USA ABSTRACT In this paper, we demonstrate how to compute the required rate of return for Coca-Cola using modern portfolio theory with data downloaded from the internet. We demonstrate how to calculate monthly returns for the index and Coca-Cola and how to use the returns to compute the beta coefficient and the required rate of return using the downloaded data. We show how to validate the data for the market index and the company and how to compute the returns using the dividend and stock split adjusted prices. We demonstrate how to graph the characteristic line for Coca-Cola and use the graph to check that the regression was run correctly. We use Coca-Cola and the S&P 500 Index in this paper, but any company listed on Yahoo! Finance can be used as the example. This paper can be used as the basis of a lecture on intermediate corporate finance or investments to demonstrate the process using a real company. Keywords: beta; characteristic line; required rate of return; Coca-Cola; teaching note INTRODUCTION M arkowitz1 (1952) began modern portfolio theory (MPT) which can be used to explain the relationship between risk and return for assets, particularly stocks. Stock of companies that have higher rates of return have higher levels of risk. In order to achieve...
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...THE JOURNAL OF FINANCE • VOL. LXIV, NO. 3 • JUNE 2009 Do Stock Mergers Create Value for Acquirers? PAVEL G. SAVOR and QI LU∗ ABSTRACT This paper finds support for the hypothesis that overvalued firms create value for long-term shareholders by using their equity as currency. Any approach centered on abnormal returns is complicated by the fact that the most overvalued firms have the greatest incentive to engage in stock acquisitions. We solve this endogeneity problem by creating a sample of mergers that fail for exogenous reasons. We find that unsuccessful stock bidders significantly underperform successful ones. Failure to consummate is costlier for richly priced firms, and the unrealized acquirer-target combination would have earned higher returns. None of these results hold for cash bids. THE LATE 1990S WITNESSED a large mergers and acquisitions wave. Many transactions involved equity as the mode of payment (Andrade, Mitchell, and Stafford (2001), Holmstrom and Kaplan (2001)), and this equity was usually very richly valued by historical standards. The positive correlation between market valuation and merger activity has also been documented in other periods (Martin (1996), Verter (2002)) and is especially strong for stock deals (Maksimovic and Phillips (2001)). One interpretation of this evidence is that managers try to time the market by paying with stock when they believe it is overvalued. Recently, a number of papers formally recognized this link between possible...
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...the philosophy of DFA. What sort of market behavior are they counting on? * DFA believes in three principles: 1. The Efficient Market Theory. That is, the stock market is efficient and no one has the ability to consistently pick stocks that will beat the market. Over any given period, some lucky investors will outperform the market while others will underperform. DFA felt that the market price of any firm’s stock incorporated all public information and therefore did not do any fundamental analysis on the firm in question. 2. The value of sound academic research. For example, DFA’s founders believed that small-stock investing could yield high returns to investors. They formulated this belief on the Ph.D. dissertation research of Rolf Banz of the University of Chicago, which showed that small stocks had consistently outperformed large stocks between 1926 and the late 1970s. 3. The ability of skilled traders to contribute to a fund’s profits even when the investment is inherently passive. DFA’s investment fund had a semi-active strategy between those of actively managed funds and those of pure index funds. * DFA counts on market behavior that reflects the following concepts: 1. The Beta is Dead. Stocks with high-beta do not have consistently higher returns than low-beta stocks. That is, greater risk does not guarantee greater reward. 2. The Size Effect (Small Minus Big). Based on the research that small stocks historically outperform large ones, DFA...
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...(S&P 500), for an astonishing 14 years in a row; and this marked the longest streak of success for any manager in the mutual-fund industry. By the middle of 2005, Value Trust is worth $11.2-billion. Bill Miller’s approach to investment management was research-intensive and highly concentrated. For instance, nearly 50 percent of Value Trust’s assets were invested in just 10 large-capitalization companies. While most of Bill Miller’s investments were value stocks, he was not averse to taking large positions in the stocks of growth companies. In other words, Bill Miller’s investing style is iconoclastic: “You simply can’t do what he’s done in the supremely competitive, ultra-efficient world of stock picking by following the pack…The fact is that Miller has spent decades studying freethinking overachievers, and along the way he’s become one himself.” Mutual Funds Definition A mutual fund is an investment vehicle that pooled the funds of individual investors to buy a portfolio of securities, stocks, bonds, and money-market instruments to meet specific investment objectives; investors owned a pro rata share of the overall investment portfolio (Bruner, 2007). The various investments included in a fund’s portfolio are handled by professional money managers in line with the stated investment policy of the fund. All mutual funds have a portfolio manager, or investment advisor, who directs the fund’s investments according to explicit investment objectives. Mutual Fund Types Investors...
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