The capital asset pricing model - Free Essay Example

Sample details Pages: 9 Words: 2800 Downloads: 4 Date added: 2017/06/26 Category Economics Essay Type Research paper Did you like this example? Introduction The Capital Asset Pricing Model (CAPM) is being used since the 1960s   to measure portfolio performance and to calculate the cost of capital.   In the 1990s Eugene Fama and Kenneth French tried to improve the performance of the CAPM by adding two factors to the model. The first factor is the book-to-market ratio of stocks in the portfolio and the second factor is the stocks underlying company size. This model was to be superior to the CAPM. Don’t waste time! Our writers will create an original "The capital asset pricing model" essay for you Create order However, Graham and Harvey (2001) proved that in 2001 the CAPM was still used by 73,5% of the U.S. CFOs to calculate the cost of capital and portfolio performance. In Europe, Brounen, de Jong and Koedijk (2004) showed that this percentage was still 45%. Why do CFOs still rely on an inferior model, or isnt the Fama French Three Factor Model superior to the CAPM? The goal of this paper is to determine whether the CAPM or the Fama French Three Factor Model is superior to one another in size and book-to-market portfolios.   Theory The Capital Asset Pricing Model The Capital Asset Pricing Model is a model that describes the relationship between risk and expected return. It is mainly used by investors to value assets and to determine expected returns. The main idea behind the model is that investors need to be compensated for their exposure to systematic risk, because not all of the investments are truly risky. By diversifying a portfolio, it is possible to reduce risk. The risk reduced is called the Risk Free Rate. In other words, the expected return of a security or a portfolio is formed by the risk free rate plus a risk premium. The CAPM by Sharpe (1964) and Lindtner (1965) is in fact an extension of the one period mean variance portfolio models of Tobin (1958) and Markowitz (1959). It builds on the model of portfolio choice, where an investor selects a portfolio that minimizes the variance of portfolio return and maximizes the expected return, given this variance. This is often referred to as the â€Å"mean variance model†. The CAPM is in fact a prediction test about the coherence between risk and expected return and identifies a portfolio that is efficient if asset prices are to clear the market of all assets. The two added assumptions to this mean variance model identify a mean-variance-efficient portfolio are â€Å"complete agreement† and â€Å"borrowing and lending at risk free rate†. Complete agreement stands for the agreement amongst investors on the joint distribution of asset returns from which the returns we use to test the model are drawn. Borrowing and lending at a risk free rate exists and is equal for all investors and does not depend on the amount borrowed or lent. The relationship between risk and the expected return for portfolios is apparent. The higher the risk, the higher the payoff and vice versa according to Fama and French (2004). The Sharpe-Lindtner CAPM equation: E(Ri) = Rf + bim * (E(Rm) Rf) Where E(Ri) is the expected return on asset i, Rf is the risk-free rate, bim is the market beta of asset i, E(Rm) is the expected return on the market. Where bim consists of the following factors: bim = cov(Ri, Rm)/s2(Rm) Where cov(Ri, Rm) is the covariance risk of asset i in m and s2(Rm) is the variance of the market return. In words, the expected return on asset i is the risk-free rate (Rf) times the unit premium of beta risk, E(Rm) Rf. The expected return on an investment portfolio is equal to the weighted average of all of the assets expected returns in the portfolio, thus is linearly combined. The standard deviation of a portfolio is nonlinearly combined, because of the diversification of risk that takes place when a portfolio is formed as seen in Figure 1. For example, when a portfolio of two equally risky assets is formed, with equally expected returns, the expected return on the portfolio will be equal to the expected return of one of the assets, though the standard deviation of the portfolio will be lower than the standard devia tion of each of the underlying assets because of the diversification effect. In other words, diversification leads to a risk reduction without diminishing the expected return. Figure 1 describes the various portfolio possibilities and explains the CAPM further. On the horizontal axis portfolio risk is set and on the vertical axis expected return is set. The curve is called the minimum variance frontier, and is a line that describes the minimum variance at different risk levels of multiple risky portfolios, when there is no opportunity of risk free borrowing. For example, when an investor is looking for a high expected return, this automatically brings a high risk along with it. The optimal choice of a portfolio for an investor lies on the minimum variance frontier, since it maximizes the expected return for a given volatility. By adding the opportunity to borrow at a risk free rate, the mean variance efficient frontier comes into being. This is now the efficient set, in stead of the minimum variance frontier according to Fama and French (2004). The Pros And Cons Of The Capital Asset Pricing Model The main advantage of the CAPM over any other pricing mode is its simplicity to use. However, there are some anomalies. During the 80s and 90s, several deviations in the CAPM were discovered which show anomalies in the CAPM and question its correctness. According to Basu (1977) future returns on high Earnings to Price ratios are in reality higher than the ratios predicted by the CAPM. Banz (1981) finds that the low market value stocks actually had a higher return than predicted by the CAPM. Bhandari (1988) showed that leverage high debt equity stocks had returns that were too high relative to their betas according to the CAPM. He also shows that there is a positive relation between between leverage and average return in the CAPM. Leverage could be associated with risk and expected return, but according to Bhandari (1988), the leverage risk should be explained by the market b. The Fama French Three Factor Model. Fama and French (1992) criticize the empirical adequacy of the CAPM and claim to improve the model by adding two empirically based factors. The factors are a product of empirical data research and there is no underlying theory to explain these factors. Of all the researched factors, these turn out to be the most effective. Fama and French (1992) used the cross-sectional regression approach of Fama and MacBeth (1973) to show that b doesnt suffice to explain average return. Size captures differences in average stock returns where b misses them. To improve the predictive value of the CAPM they added two factors to the model. According to the model the risk premium or excess return above the risk free rate is a composition of three factors, namely v The risk premium on the market portfolio (Rm RF). v The difference in returns between the small stock portfolios and the big stock portfolios (SMB). v The difference in returns between the high book to market stock portfolios and the low book to market stock portfolios (HML). The Fama and French Three Factor Model: E(Ri) Rf = bi * (E(Rm) Rf) + si E(SMB) + hi E(HML) Where: E(Rm) is the expected return on the market, Rf is the risk free rate,   E(SMB) and E(HML) are the expected premiums and bi, si and hi are the regression slopes. The first factor is Small Minus Big (SMB) which is designed to measure the excess return investors have historically received by investing in company stocks with small market capitalization. This excess return is most commonly known as the ‘size premium . Fama and French (2006) compose six value weight portfolios, SG, SN, SV, BG, BN, and BV. They state that: â€Å"The portfolios are intersections stocks of NYSE, AMEX (after 1962) and Nasdaq (after 1972) into two size groups, Small and Big and three book to market (B/M) equity groups Growth (firms in the bottom 30% of NYSE B/M), Neutral (middle 40% of NYSE B/M) and Value (high 30% of NYSE B/M). † The SMB factor is the average returns on the small stock portfolios minus the average returns on the big portfolios according to Fama and French (2006) and is computed as follows: SMB =1/3 (Small Value + Small Neutral + Small Growth) 1/3 (Big Value + Big Neutral + Big Growth) Where: Small Value are the firms with the June market cap below the NYSE median that are at the high 30% of NYSE B/M. Small Neutral are the firms with the June market cap below the NYSE median that are at the middle 40% of NYSE B/M. Small Growth are the firms with the June market cap below the NYSE median that are at the bottom 30% of the NYSE B/M. Big Value are the firms with the June market cap value above NYSE median that are at the high 30% of NYSE B/M. Big Neutral are the firms with the June market cap value above NYSE median that are at the middle 40% of NYSE B/M. Big Growth are the firms with the June market cap value above NYSE median that are at the bottom 30% of NYSE B/M. When thi s value is positive, the small caps have outperformed the large caps in the particular month and vice versa. The second is High Minus Low (HML) which is designed to measure the ‘value premium   investors get for investing in high book-to-market companies. The HML factor is the average returns on value portfolios minus the average returns on growth portfolios according to Fama and French (2006) and is computed as follows: HML =1/2 (Small Value + Big Value)- 1/2 (Small Growth + Big Growth) When this value is positive, the growth stocks outperformed the value stocks in that particular month and vice versa. The market risk premium (Rm-Rf) that is used is the value to weight return on all NYSE, AMEX and Nasdaq stocks diminished by the one-month Treasury bill rate. The Pros Aand Cons Of The Three Factor Model The additional two factors in the Fama and French Three factor model are purely empirical. There is no underlying theory as there exists in the CAPM. Though the three factor model needs additional date compared to the CAPM (the SMB factor and the HML factor) the higher costs in using the three factor model compared to the CAPM is not justified according to Bartholdy (2002), because the three factor model doesnt seem to outperform the CAPM significantly on individual stock returns estimation. The Momentum Factor Carhart (1997) adds another factor to the equation, creating his Four Factor Model. This fourth factor describes the effect of Jegadeesh and Titmans (1993) one year momentum anomaly. This model is a market equilibrium-based four-risk factor model. Carharts factor (PR1YR) brings the one-year momentum return to the equation, which enlarges the explanation of the model compared to the three factor model, so the fourth factor substantially improves the performance of the model according to Carhart (1997). In the three factor model, errors concerning last years stock portfolios are observably reduced. Carhart managed to reduce most of the patterns in pricing errors. This indicates a well performing model on describing cross sectional variation in average stock returns. The Carhart four factor model: E(Ri) Rf = bi * (E(Rm) Rf) + si E(SMB) + hi E(HML) + pi E(PR1YR) Research Questions And Hypotheses Which of the two models, the CAPM or the Three Factor Model, is superior to one another for the different portfolios of size and book-to-market in the time period between 1993 and 2009? Hypotheses: 1. The Three Factor model is superior in predicting the value of securities in the portfolio size in the time period 1993-2009. 2. The Three Factor model is superior in predicting the value of securities in the portfolio book-to-market in the time period 1993-2009. 3. Not all the factors of the three factor model are contributing to the adequacy of the model in valuing the portfolios size and book-to-market in the time period 1993-2009. 4. The momomentum factor helps explain returns. Methodology And Data Collection Data This paper uses the data gathered by Fama and French and published on the website of Kenneth R. French. According to Fama and French (1992) this data consists of all non-financial firms in the intersection of the NYSE, AMEX and NASDAQ files and the merged COMPUSTAT annual industrial files of income statement and balance sheet data, maintained by the Center for Research in Security Prices (CSRP). They have excluded the financial firms from their dataset because high leverage in these firms is quite normal in opposition to high leverage in non-financial firms. In non-financial firms this high leverage could possibly indicate distress. In the Small-Minus-Big factor in the Three Factor Model, accounting variables play a role, and to ensure that these accounting variables are known before the returns they are used to explain, the accounting data for all fiscal year-ends t, are calculated after a minimum of 6 months has passed the fiscal year-end. Estimating Market This paper uses the market b provided by Fama and French and published on the website of Kenneth R. French. The asset pricing tests performed in this paper use the cross sectional regression approach of Fama and MacBeth (1973). The market bs for portfolios are more precise than the individual bs, so the approach of Fama and MacBeth (1973) is to estimate the portfolios b and then assign this b to each stock in the underlying portfolio. By using this method, the useage of individual stocks in the asset-pricing tests of Fama and MacBeth is enabled. Methodology SPSS 15 will be used for the data analysis in this paper, which will consist of multivariate regression analysis to answer the research question and hypotheses. To determine whether the two additional factors of the Three Factor Model add extra predictive value to the CAPM, this paper uses multiple linear regression in SPSS to see if the R-squared value increases with these additional factors for each of the portfolios. . In the data library section on their site, Fama and French provide data about portfolios formed on size and portfolios formed on book-to-market. To investigate the size and book-to-market factors in the Three factor model, the data of these portfolios are used in the regression analysis. Literature v Brounen, D. Abe de Jong and K. Koedijk, 2004, Corporate Finance in Europe Confronting Theory with Practice, Financial Management 33, 71- 101. v Graham, J.R. and C.R. Harvey, 2001, The Theory and Practice of Corporate Finance: Evidence from the Field, Journal of Financial Economics 60, 187-243. v Litner, J., 1965, The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets, Review of Economics and Statistics 47, 13-37. v Sharpe, W.F., 1964, Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk, Journal of Finance 19,425-442. v Tobin, J., 1958, Liquidity Preference as Behaviour Toward Risk, Review of Economic Studies 25, 65-86. v Fama, E.F. and K.R. French, 2006, The Value Premium and the CAPM, Journal of Finance 61, 2163-2185. v Fama, E.F. and K.R. French, 2004, The Capital Asset Pricing Model: Theory and Evidence, Journal of Economic Perspectives 18, 25-46. v Fama, E.F. and K.R. French, 1 996, â€Å"The CAPM is Wanted, Dead or Alive†, Journal of Finance 51, 1947-1958. v Fama, E.F. and K.R. French, 1992, â€Å"Common risk factors in the returns on stocks and bonds†, Journal of Financial Economics 33, 3-56. v Fama, E.F. and K.R. French, 1992 â€Å"Cross-section of expected stock returns†, Journal of Finance 47, no 2, 427-465. v Fama, E.F. and K.R. French, 1997 â€Å"Industry cost of equity†, Journal of Financial Economics 43, 153-193. v Markowitz,H. 1952. Portfolio Selection. Journal of Finance.7:1, pp. 77-99. v Markowitz, Harry. 1959. Portfolio Selection: â€Å"Efficient Diversification of Investments† Cowles Foundation Monograph No. 16. New York, John Wiley Sons Inc. v Fama, E.F. and K.R. French, 2010 â€Å"Data Library† https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html v Basu, S., 1977, Investment Performance of Common Stocks in Relation to Their Price-Earnings Rations: A Test of the Efficient Market Hypothesis†, Journal of Finance 12, 129-156. v Banz, R.W., 1981, The Relationship between Return and Market Value of Common Stocks, Journal of Financial Economics 9, 3-18 v Bhandari, L., 1988, Debt/Equity Ratio and Expected Common Stock Returns: Empirical Evidence, Journal of Finance 43, 507-528 v Bartholdy, J. 2002, â€Å"Estimation of Expected Return: CAPM vs Fama and French†, Working paper series https://ssrn.com/abstract=350100 Nog te verwerken: Inleiding Smb gaat long in kleine aandelen en short in grote Fama, E.F. and K.R. French, 2004, The Capital Asset Pricing Model: Theory and Evidence, Journal of Economic Perspectives 18, page 27 Fama, E.F. and K.R. French, 2006, The Value Premium and the CAPM, Journal of Finance 61, p. 2166. https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

Marketing and Monsanto - 1349 Words

Monsanto: Linking Core Competencies to Market Opportunity Case Summary: Monsanto Co. is an innovative biotechnology company that is currently the world’s largest seed company. Since its inception in 1901, Monsanto has continually reinvented itself to realize growth opportunities in a wide spectrum of marketing environments. In 1981, a shift in strategic focus towards biotechnology has propelled the company to $11.7 billion in annual sales with over 20,000 people in 160 countries. As the world faces a growing population and declining natural resources, Monsanto’s technological innovations with genetically modified seeds have increased crop yields around the world. Although the company has enjoyed significant growth in recent†¦show more content†¦What are the major strengths, weaknesses, opportunities and threats (SWOT) associated with Monsanto? Monsanto’s strengths include technological innovations in biotechnology anchored by substantial investment in research and development that have produced many patents, and allow the company to react swiftly to changes in the strategic environment. Their presence in 160 countries provides favorable access to distribution networks around the globe. A major weakness for Monsanto is consumer perception that its products are unhealthy for human consumption and have negative consequences on the environment. Another major weakness for Monsanto is the expiration of their main patent in 2014 of their Roundup-ready soybean. JPMorgan estimates losses of up to $500 million in royalties that the company receives from licensing Roundup-ready soybean to competitors. According to the United States Department of Agriculture, only 11% of global land surface is considered suitable for agricultural production. With a surging global population and increased land degradation caused by human activity, higher yielding crops with resistance to various environmental conditions will become essential to maintaining an adequate food supply for the world. Monsanto’s technological innovations in biotechnology, and specifically genetically modified seeds, present a unique opportunity to capitalize on one of the world’s great challenges in the 21st century. Growing consumerShow MoreRelatedMarketing Schemes Of Monsanto, Major U.s. Pharmaceutical Corporations And Food Manufacturing Companies1572 Words   |  7 Pages(nongmo project, what is a gmo) Scientist insert, delete, or switch the DNA in certain organisms. Those organisms may be able to live longer, speed up the growth process, or withstand herbicides and pesticides. 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Cross-Cultural Communication Matrix Free Essays

Use the matrix to complete the country information. Write 3-4 sentences for each item. a. We will write a custom essay sample on Cross-Cultural Communication Matrix or any similar topic only for you Order Now Access the Business Around the World information by using the url: http://www. mhhe. com/business/buscom/bcommonline/. b. Click on the map on the lower left corner of the page. Select three regions of the world to research by clicking on the map. Select one country from each of the three regions you selected to research. The Web site provides you with a good starting point. You may also want to use a general Internet search to find additional information. . Include APA formatted references on a separate page. * * This assignment is due in Week Three. Cross Cultural Communication| Country| Preferred communication style | Non-verbal communication practices| Business communication norms| Strategies to increase cross-cultural communication| China| Style of communication is most paralinguistic meaning the speaker will change the tone of his or her voice to a higher pitch. Spoken/non-verbal| Eye contact, facial expressions, voice tone, gesture| A handshake, slot nod of the head is the beginning of greetings. All meetings are made in advance. Body posture is attentive and formal. | Pay attention to body language and to research the culture. Make sure to research facts and figures for accuracy. Canadians are logical and rational not convinced on emotions, passions, or feelings. Promises made are expected to be kept. Make sure all facts, numbers are accurate. Be polite, respectful and calm. | Canada| French and English are main languages spoken. Communication is Pragmatic and relies on common sense. Business people are polite and easy going. | Only used to add emphasis. Not used often. Meeting are on schedule, well organized and started with minimal small talk| | Australia| English is the language spoken. Communication style is casual and laid back. | Non-verbal communication is the style. A smile and simple handshake. | Prefer to address one by first name. Appointments are necessary. Facts and figures are important as well as punctuality. | | * References [ (www. cia. gov/library/publications/the-wi, 2010) ] Top of Form turn off anonymous marking Please state reason for turning off Anonymous Marking for: Warning: Administrator has access to this information.This setting is permanent. Bottom of Form This is a preview of the print version of your report. Please click â€Å"print† to continue or â€Å"done† to close this window. done Top of Form color-code matches: default mode: auto-navigation: Save Cancel Bottom of Form Top of Form * Word Count: words * Percentage: % or Cancel Bottom of Form * preferences * Help Document Viewer Turnitin Originality Report * Processed on: 12-13-10 11:39 PM CST * ID: 164099147 * Word Count: 324 * Submitted: 1 Cross-Cultural Communication Matrix By Lena Pargo Similarity Index 30% What’s this?Similarity by Source Internet  Sources: 30% Publications: 0% Student  Papers: N/A exclude quoted exclude bibliography exclude small matches download print mode: 25% match (Internet from 4/19/10) http ://www. brainmass. com/homework-help/business/other/254349 5% match (Internet from 6/6/10) http://studentoffortune. com/question/393521/COM-285-INTRODUCTION-TO-COMMUNICATION/678192-COM%20285%20Cross-Cultural%20Communications. doc University of Phoenix Material Cross-Cultural Communication Matrix Use the matrix to complete the country information. Write 3-4 sentences for each item. a.Access the Business Around the World information by using the url: http://www. mhhe. com/business/buscom/bcommonline/. b. Click on the map on the lower left corner of the page. Select three regions of the world to research by clicking on the map. Select one country from each of the three regions you selected to research. The Web site provides you with a good starting point. You may also want to use a general Internet search to find additional information. c. Include APA formatted references on a separate page. This assignment is due in Week Three. Cross Cultural Communication Country How to cite Cross-Cultural Communication Matrix, Papers

The Elements of Design free essay sample

The basic elements of design are point, line, and color. Though these seem more related to 2D art, they play a huge role in stage theatre. Not only with stage design but also with lighting, prop decisions, and set dressing. When used correctly, these elements can make a show worth watching. Point is defined as a spot, place, or position in an area or on a map, object, or surface. When a spot light is shining on an actor the lighting director must find the exact point at which the actor or actress is standing on stage. If the light doesn’t hit the exact point on the stage, then the actor will be standing in the dark. Unless the show calls for it, an actor or actress should never be in the dark. Point is also used in directing. When in a director is telling an actor to move, the director must pay attention to point because if not then the actor/actress might end up in the wrong place for the situation or dialogue. We will write a custom essay sample on The Elements of Design or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Line is defined as a point moving in space. Lines can be vertical, horizontal, diagonal, or curved. They can be any width or texture. And can be continuous, implied, or broken. When lights are designed, or programmed, line must be considered because the line at which light travels can make or break a lighting scheme. If the line at which the light travels at is broken, then that which broke it will be in focus, unless the light is soft. If the light is softer, and has a softer line, then the focus will either be on the entire stage or that which breaks the line of light will be less focused on in comparison to something else on stage with stronger light. When actors move onstage, line plays a large role. The director must consider every direction each actor is moving in. If actors walk downstage in a diagonal line from opposite sides of the stage at the same speed then a collision will occur and unless it’s part of the scene, this should be avoided. The director must accommod ate while also ensuring each actor makes it to the intended location on stage. The director can change the line at which the actor travels, change the speed at which an actor travels, or postpone the actor from traveling until the needed space is available. When a set is being designed, line can change the entire mood of the setting. For example, when a background has lots of curvy lines then it is most likely a silly or childlike play, like Horton Hears a Who or Nemo. When a background has straight and rigid lines it’s most likely a serious or dramatic play, like Sweeny Todd or Heathers. To show significance in something in the background of a set, a director can use the technique of changing the line type used to make up they want the audience to focus on. This technique changes the mood of what it’s used on while at the same time retaining the mood of the whole play. If something has straight lines amid an entire set made of curvy lines it is more serious or importa nt. If something is made of curvy lines amid an entire set made of straight lines, it is silly or extravagant. Color is defined as the property possessed by an object of producing different sensations on the eye because of the way the object reflects or emits light. Color can completely change the mood of the show. Hot colors show happiness or childlike attitude; cooler colors show sadness. The use of certain colors can make or break a set. When a set designer uses a bunch of warm colors like yellows, pinks, oranges, etc. it gives off a feeling of excitement or energy which is optimal for a children’s show or a humorous show. When a set designer uses lots of cool colors like blues, purples, greens, etc. it gives off a feeling of sadness or calmness which is optimal for a sad or serious show. With lighting, warm colors can show nighttime while cool colors can show morning. Blue light can be used to show a passage of time or when used in combination with a spotlight, it can be used to deter attention from one part of the stage.