Saturday, August 31, 2019

Compare miss Havisham and Lady Macbeth Essay

?Compare the presentation of Lady Macbeth and Miss Havisham. Explore how Shakespeare and Dickens present them as disturbed women. Disturbed is a definition of someone who has emotional or mental problems; both Lady Macbeth and Miss Havisham are presented as disturbed characters in one way or another. These two leading women both have characteristics that were not stereotypical of woman at the time periods that the play and the novel were set in; making them immediately appear strange to the audience or reader of that time. Shakespeare and Dickens both present their leading women in very different ways; however some aspects of their characters show similarities. The play Macbeth was set in Elizabethan times, where there was a patriarchal society in which men were superior to women. Women were known by their husbands’ names and were seen more as their husbands’ property than their partners. Elizabethan women were treated badly and disobedience on their behalf was a crime against religion as the society of that time believed that women were made to serve men. However, it was also believed that women were incapable of having evil thoughts or committing devilish crimes. The character of Lady Macbeth goes entirely against the typical Elizabethan woman as she is portrayed as strong and controlling over her husband Macbeth, and is the one to persuade him to commit an act of regicide. This would be shocking to an Elizabethan audience as regicide was known as the worst possible thing you could do, as they believed that their monarchs were sent from God. Miss Havisham is also the opposite of what women in her society were like; she was a spinster. This meant she was seen as a failure as in Victorian times, a woman’s proper purpose was to suitably marry; it was what they were born for. In most of Charles Dickens’ novels, the spinsters and old maids who appear are usually mad, desiccated, boring or secluded. Miss Havisham in Great Expectations is an example, a woman who fell in love and was jilted on the day of her wedding. She lived for the rest of life in her wedding dress, with one shoe on, a wedding cake uneaten on the table, and the clock stopped at the time she found out that her husband-to-be had deserted her. In Shakespeare’s play Macbeth, Lady Macbeth is first introduced in Act 1 Scene 5. She is reading a letter from her husband, immediately the audience see her as a determined and power-hungry character. In her soliloquy she reveals that Macbeth ‘shalt be what thou art promised’ her ambition for her husband to be king and indeed perhaps for herself to be queen is evident here. Shakespeare’s use of the imperative ‘shalt’ displays her controlling nature, showing her strength and masculinity which would appear unusual to the audience of that time. Although at first Lady M/acbeth would seem to be a rather queer character, the audience would not immediately class her as disturbed. Miss Havisham, however, is portrayed as a disturbed character right from when we first meet her in Chapter 8. Dickens first describes Miss Havisham through Pips eyes as he first sets foot in Satis House. The way the house and the room in which Miss Havisham sits is described, ‘no glimpse of daylight was to be seen in it’ immediately lets the reader know that she is extremely disturbed’ the whole house is stopped, including the clocks at the exact time she turned into a spinster. The idea of showing Miss Havisham first through Pip, allows the reader to see what is wrong, however, not fully understand why this is. Miss Havisham appears to be a much weaker character when she is first introduced as Pip describes her as ‘a skeleton in the ashes of a rich dress’. Dickens use of death imagery gives the reader an impression that Miss Havisham’s life is already over and she is just waiting to die. This makes the reader feel somewhat sorry for her at first and wonder why she is living in such a way. Although it is soon evident that Miss Havisham is not as weak as she first appears when she speaks to Pip for the first time; ‘â€Å"Come nearer; let me look at you. Come close. †Ã¢â‚¬â„¢ Dickens also uses imperatives in Miss Havisham’s speech ‘come’ showing that although regarded by all in that era as a failure she still has power to make others do whatever she wants. Both Lady Macbeth and Miss Havisham are both portrayed as evil characters throughout the play and the novel. Some people may argue that Miss Havisham is less evil as she does not murder anyone, however, she does ruin the lives of others, using Estella to break the hearts of men the way hers was once broken. Lady Macbeth does come across as more wicked than Miss Havisham most of the time however she might not be as evil and sinister as we are lead to believe. We realise this when she says ‘stop up the access and passage to remorse’. This shows the audience that maybe she does have some conscience because she knows she will feel guilty. However, another way to look at it is that she just wants to stop this from happening so that she can live happily as queen without guilt pulsing through her. This makes the reader think of her as a selfish woman who is used to getting exactly what she wants without any of the bad consequences that come along side it. The use of the modal verb ‘stop’ is strong and commanding and it doesn’t give the person she is talking to an option to say no. The idea of not being able to say no is repeated at the end of Act 1 Scene 5 where she tells Macbeth to ‘Leave all the rest to me’. Lady Macbeth is saying that no matter what anyone says no one will persuade her to change her mind about the murder of King Duncan. The language shows that she feels like she has the upper hand over Macbeth. Lady Macbeth uses her power to manipulate Macbeth into committing an act of regicide. Miss Havisham also manipulates people into doing things that they do not wish to do. She brings Estella up to get revenge on mankind and at the same time makes it impossible for Estella to love. Miss Havisham uses Pip for Estella to practice on and is delighted when Pip falls in love with her. ‘Well you can break his heart’ she tells Estella when she does not want to play cards with a ‘common labouring boy’. Miss Havisham says this in such a calm way that it seems to the reader that breaking someone’s heart is not a big deal to her, which it isn’t since she just wants revenge on all men. Although both of these women are ‘horribly cruel’ towards the end of the play and the novel they do realise what they have done wrong and feel guilty about it. Although the way they react to the guilt differs hugely. Miss Havisham becomes more normal with guilt and tries to put her wrongs right. ‘†Oh† she cried despairingly. â€Å"What have I done? What have I done? †Ã¢â‚¬â„¢ she becomes a weak, pitiable creature who begs Pip for forgiveness ‘on her knees and is desperate to do something ‘useful and good’ Her regret makes the reader feel sorry for her rather than blame her. Lady Macbeth becomes more and more disturbed with guilt, up until a point where she cannot take it anymore and commits suicide. Her grief must have been extremely bad for her to do this since she would know that she would be going to hell.

Friday, August 30, 2019

My School Essay

School is a temple of learning and a training ground for future citizens. The name of my school is Penang Chinese Girls High School. It was set up in 19-an by a land-lord in our area. He donated land and money for the school. The atmosphere in which our school is situated is very pleasant. It is surrounded by a big field on one side and a small garden with flowers on the other. The school has three rows of big buildings. The name of the school is written on the front building. There are many classrooms in the front building. Other rooms in the back building are used for different purposes such as the Head Master’s Office, Library, the Clerk’s Office, the Science Laboratory, the Teachers’ Common-room, the N. C. C. and etc. There are 80 teacher, a specific teacher for librarians, a clerk and several peons in our school. All the teachers are qualified and experienced. The Head Master is a learned woman,she solved problems of the pupils efficiently. The total number of students of our school is about 20thousand hundred. We go to school in uniform,our school consisits of girls only,therefore girls wear blue skirt and white blouse. The school functions from for 2 sessions. During the recess hour we go to the canteen to relax and savour some mouth-watering food. Some students also go to library and read newspaper there. In games period we play badminton, volley ball, etc. Girl students play ring ball too. The library of our school is a medium one. There are about two thousand books on different subjects; we did not have a library period in our weekly routine,so we borrow books from our library and refund them after a week in our free time. We observe the Republic Day, the Independence Day, the Teacher’s Day in our school. We also hold debate competitions and games and sports every year. The school magazine is published every year. In annual examinations the students from our school show brilliant performance. Many students from this school have occupied glorious position in our state. Our school always holds book fair for students to have a chance to explore the advantages of reading. This year a classical teacher from our school retired formally. The discipline, the study atmosphere and the brilliant academic result of our school attract many meritorious students from distant parts of our state. It is an ideal school in all respects.

Thursday, August 29, 2019

Company Delamere Pottery Limited Essay

Company Delamere Pottery Limited, which produces earthenware tableware, founded in 1997 after obtaining assets of T.G. Delamera & Co ltd. Company acquired a functional structure to better support the increase in turnover (Williamson et al., 2004, p. 53) in new markets areas that offer greater margins. To enhance the competitiveness, company launched a new strategies in business, marketing and finance mainly to increase gross margins by 10% and increase customer satisfaction together with a reduction of inventory (Williamson et al., 2004, p. 207). Business strategy is mainly based on the more efficient use of existing resources of the company. With implementation of the ERP system, the company promises to improve the planning, transparency and shortening process times and increasing the performance. ERP systems are often used by manufacturing companies to achieve a competitive advantage (Zhang et al, 2005, p. 69). ERP system helps companies create a strong information infrastructure, more accurate decision-making thanks to always actual data, enhance the overall quality and streamline the exchange of information between departments, suppliers and customers (Shatat & Udin, 2012, p. 577). Further costs reductions, the company tried to streamline production by reducing the overall waste. Basically to become  ´Ã‚ ´lean ´Ã‚ ´ and build an efficient, just-in-time manufacturing system to increase the overall quality. According to Lewis (2000, p. 962), company which is lean, is effective in transforming inputs resources into outputs, this reduces the costs and increase overall business financial performance. Becoming more  ´Ã‚ ´lean ´Ã‚ ´ (having lower costs) is one of the advantages over the competition (Lewis, 2000, p. 964). Source: Lewis (2000, p. 962) One of the main asset of the company are employers. To increase the overall success of the company can be achieved by: increase communications, increasing cooperation and following common goals, raising creativity and innovation, emphasizing on continuous development, empowering people (Kourdi, 2003, p. 84). Marketing strategy relies mainly on improving quality of products, service and so increase the overall brand reputation. Delamere Pottery Limited wanted to differentiate from competition through their products, supply chain and marketing (Williamson et al., 2004, p. 90) and so obtained higher saleability. The achievement of this strategic plan had five segments: Quality, Design, Service, Reliability, Brand awareness (Williamson et al., 2004, p. 210). Marketing strategy was closely linked to business strategy, with emphasis on the lean production. Improvement of manufacturing processes has a direct positive impact on the quality of the products and also thorough better controlling of the packaging, labeling and delivery of products can reduce costs. The company sought to be recognized as a progressive and innovative (Williamson et al., 2004, p. 210), therefore been given a lot of emphasis on design. Decisions in product design can have a large impact on cost, but also with design can be achieved the differentiation from the competition and getting higher profits (Desai et al, 2001, p. 37). Be credible among customers, the company tried to improve service, improve communication and improve the performance in the delivery of finished products to the customers on time. To support this plan has been introduced customer relationship management (CRM). Another tool how to increase turnover is to enhance the brand awareness. Greater brand awareness among customers increase the differentiation from competition and gives firm the possibility to increase the prices of products. Financial Strategies Delamere Pottery Limited was divided into two main parts: increasing gross margin and additional turnover (Williamson et al., 2004, p. 211). The results of gross margins depended on the success of the implementation of ERP system, lean manufacturing and improved distribution and getting the brand into public awareness. Additional turnover was possible made by sale of selected products for specially selected markets and the gradual-depth sales to particular markets. In company Delamere Pottery Limited the main emphasis has been taken on comprehensive manufacturing strategy. To support this strategy, in year 1999 was presented the system MPC (Manufacturing, Planning, Control). MPC should be associated with the other main functions such as finance, purchasing, sales and marketing (Williamson et al., 2004, p. 216). According to Williamson et al. (2004, 216-218), the implementation of MPC system, company received the following benefits: -With connection to ERP system is possible to have more efficiently planning and greater control of the production. -With connection to CRM system improve communication and service with customers. Significant improvement of delivering products on time. Increase of  £2M in turnover. -Better inventory management, increased stock turns. Reduction in working capital  £120.000. -Better recognition of loss-making and non-contribution products. Enhance in pre-tax profits of  £150.000.

Wednesday, August 28, 2019

Business and Government Customer Decision Making Essay

Business and Government Customer Decision Making - Essay Example Often, straight rebuy is a purchase from an "approved list" of suppliers which satisfactory met the standard set buy the buyer. In order for the suppliers to maintain its relationship with the business buyer, it maintains its product or service quality. Companies utilizing straight rebuy are often automated in order to save reordering cost and time. Globally, Dell, Inc. is recognized as an organization which pursues strategic partnership with its various suppliers. Through the use of technology, the company shares the level of its material inventory with its current suppliers. These enables it to facilitate straight rebuy once its input goes below the optimum quantity. Aldi, the international retailer is also using a straight rebuy in replenishing its grocery shelves. It should be noted that the retailer has an extensive network of supplier for its merchandise. The company employs a Point of Sale system which tells suppliers when to deliver the needed goods. Modified rebuy happens when a business organization wants to purchase a component but would like to alter product specifications, prices, delivery requirement, or other terms (Widing 2002, p.155). As opposed to straight rebuy this buyclass may consider new suppliers to provide its new needs. The company also gathers information in its quest of finding the appropriate supplier.

Tuesday, August 27, 2019

Education in Britain 1979 to Present Essay Example | Topics and Well Written Essays - 2250 words

Education in Britain 1979 to Present - Essay Example The period from 1979-1997 can be referred as neo-liberalism era as it was characterised by marketisation especially of public services. According to Gillard (2011) it was also a period of social and economic restructuring whereby Thatcher applied her unpopular aggressive policies earning her the title of ‘iron lady’. Prior to conservative government taking over office tremendous changes had been made in the education sector especially resulting from the 1944 Education Act. This Act saw the introduction of free and compulsory education to pupils aged 5-16 and also the famous selection tests known as 11+ (Jones, 2003: 25). The schools were put on Local Education Authorities who were involved in funding and management of schools. Parents, in this case, did not have much choice as to what schools their pupils should attend. Although the Act was aimed at creating equal opportunities for students’ social class differences were still apparent as students from the middle class attended good schools while those from poor backgrounds ended up in technical schools. It was a three tier system comprising of grammar schools, technical school, and secondary modern. Exclusion thus persisted. While in office, the secretary for education James Callaghan had instituted a youth opportunity program for 16-18-year-olds in 1978 after a great debate on the nature and purpose of education. When Thatcher came into office she did not abolish the system but rather expanded it in 1980 and renamed in 1983 to be the Youth Training Scheme. However, the debate in her time was one sided ads she did nit involve other actors such as parents, teachers and governors. In 1980 she also started the Assisted Places Scheme to help those poor students who passed entrance exams to get free places (Chitty, 2004: 45; Gillard, 2011). The first agenda for Thatcher concerning education was to do away with the 11 plus selection exam but her efforts were thwarted since comprehensive schooling still enjoyed great popularity (Richmond, 2007). The curriculum in place is determined by the government of the day hence prone to a lot of changes. The selection exam was

Architecture and Communication Term Paper Example | Topics and Well Written Essays - 2000 words

Architecture and Communication - Term Paper Example The Empire State Building is located on Fifth Avenue, in New York City, New York, and was touted to have been completed in the span of a mere sixteen months. It has 102 floors, and has a height of 381 meters, or 1252 feet. At the time of its completion, it was the tallest building on earth, taking that title away from the Chrysler Building. As well, apart from the World Trade Center, the Empire State Building remains the tallest architecture in all of New York. In terms of general architecture, it is said that the building deviated from the strict European standards of the time, showing more flair and panache in comparison to the more staid European buildings of the time, even as it conveyed the appearance of something that has been sculpted, or else something that was deliberately molded rather than erected with the use of conventional architectural and building methods, and those aspects of the public building became in time one of its defining architectural signatures. Moreover, d eviating from the tail end of the Art Deco style’s sensibilities, the architecture is said to be less frivolous even as it showed its own character in an understated manner. In the decade of the 1920’s, when this style was in vogue, the Empire State Building designers stuck to something that is uniquely the character of the building itself, away from the zigzag designs of the time, and towards something that can be considered as more staid and more business-like. Functionally, too, it showed its practical aspects by having four differing facades, deviating from the convention of just having one, as is common, on the side of the buildings facing the avenue. All this gave the Empire State Building, from an architectural and design perspective, a unique identity (Artifice). II. Style of the Design of the Empire State Building, History The style of the building’s design is characterized as being Art Deco that is muted, or low key in its approach as well as in its ex ecution. That means being more understated and less done with flair, in comparison to the traditional conception of Art Deco and in comparison to the style execution of buildings in the same era and immediately prior. On the other hand, what differentiates Art Deco architecture from other forms of architecture is its depiction as being Modernistic, and this depiction applies to the Empire State Building too, in common with Art Deco executed buildings of the time (Artifice). The simplicity of the design coupled with its height is what marks the design sensibilities of the Empire State Building, it is said, and these twin characteristics are in a way set apart from the architectural design sensibilities of Art Deco in general. It is muted and not overt in its design sensibilities, which all the more highlights its more business-like and functional characteristics. Where the design reflects a certain bareness, this also is reflected in the way form yields to function. Among the conside rations in the design is in the ability of the building to house productive work, with tenants that are businesses in orientation, in the shortest possible time, and making maximum use of the available facilities and space. The emphasis on the modernistic aspects of the design, on the other hand, extend to its facades being characterized

Monday, August 26, 2019

Alzheimer's Research Paper Example | Topics and Well Written Essays - 2500 words

Alzheimer's - Research Paper Example During the autopsy the doctor noted dense deposits of neuritic plaques surrounding nerve cells and twisted bands of nerve fibers inside the cells. The presence of plaques and tangles during a brain autopsy is now taken as a definitive diagnosis of the condition. There have been several additional researches that have been carried out by scientist around the world since the discovery of the disease. In the 1960s researchers found connectivity between the cognitive decline and the number of plaques and tangles present in the brain. Since the 1970s scientists have made major discoveries pertaining to the complex functioning of the nerve cells in these patients and also with increasing developments in the field of genetics, genes responsible for susceptibility to this disease both in the early stages and later in life have also been unraveled. Apart from the genetic factors other lifestyle related and environmental risk factors are also being widely being explored (A History, 2009; Alzhe imer’s disease, 2010). Alzheimer’s is a progressive disease and before the symptoms are noticed sufficient damage to the brain would have already taken place. Studies reveal that this damage could occur anywhere between 10 to 20 years before the onset of the clinical signs and symptoms. Beginning with the development of tangles within the entorhinal cortex and plaques in other regions of the brain, the disease affects the functioning of neurons that eventually results in lost communication between the brain cells. When such damage occurs within the hippocampus region of the brain as the disease progresses, it affects the memory and processing skills of the individual (Alzheimer’s disease, 2010). Thus most prominent early sign of the disease is memory loss (Alzheimer’s disease, 2010; Alzheimer’s symptoms, 2009; Symptoms, 2009). Other common early symptoms include confusion, attention disorders, personality changes, difficulty with languages

Sunday, August 25, 2019

Article Review on Technology in Education Assignment

Article Review on Technology in Education - Assignment Example Videoconferencing at present is a medium for learning partnerships both in the local scene and in the international setup. Reynard (2012) cited â€Å"the inclusion of video increases the sense of presence,† and considers this as a means of collaboration. This educational tool has evolved in the recent years to include media tools, such as chat, as well as interactive whiteboards, which increase the exchange of ideas and resources alike, taking learning and the accumulation of knowledge to new heights (Reynard, 2012). This promotes access to what is otherwise accessible – locations which are commonly not that open to the public and expert educators who are too geographically distant; in reference to inaccessible locations, virtual tours are utilized (Reynard, 2012). Another advantage of this modern day educational tool is that it can make available the unavailable, such as classes not normally offered in the school, or those beyond the normal hours of school, which would be highly advantageous for those who are not able to avail of normal class hours (Reynard, 2012). Another important benefit of videoconferencing is that it helps students go the extra mile – tutoring and enrichment activities online, in real time, and without geographical constraints (Reynard, 2012). ... Furthermore, technology like videoconferencing may bridge the gap between different cultures as it provides worldwide reach to all students; this would yield better-informed students and well versed in aspects in which traditional students are not due to limited access to resources. There would be constant updates of any advancement or modification in education across the globe, as this education tool goes beyond geographical boundaries. In the future, students would be more interested and involved to learn as videoconferencing offers them interactive learning. It would give new meaning to the term – experience – since this teaching strategy would make the learners feel as if they are in that particular scenario, hence, making them believe like it was their own personal experience. There would probably be an increase in the number of students, as those who do not have the luxury of time could avail of such dynamic and effective education made very convenient to them sin ce it is not bound by normal school hours. Personal Opinion: How Technology will Shape Education in the Future Technology is evolving, as it is used in the field of education, so will the latter evolve, as well. Education will be better, as technology will constantly upgrade, so will the skills of the students. Thus, to keep up with complex learning needs brought about by modernized educational tools utilized by students, educators will adapt to such modernity. They will be well equipped with modern strategies to address learning needs. In the process, education will reach new heights. The standard of education would be further uplifted, producing more competitive

Saturday, August 24, 2019

Summary of article Essay Example | Topics and Well Written Essays - 750 words

Summary of article - Essay Example The article focuses on a comprehensive discussion of the market at the bottom of the pyramid. Unique characteristics of this market form a significant part of the explanation. According to Prahalad and Hart, bottom of the pyramid market segment has an estimated 4 billion people who live in abject poverty. Notably, the population in this market segment represents a potential market for goods and services. Active involvement of private firms at the BOP is a significant factor in generating inclusive capitalism (6). Private firms’ engagement in the BOP segment of the market enhances completion of the market will redirect attention to the poor as consumers. Prahalad and Hart assert that each group that gives close attention on poverty eradication such as the World Bank, developed countries offering aid, charitable organizations, federal governments, and private firms – has its an overriding justification. Prahalad and Hart explain that MNCs suffer the effect of strongly est ablished reason in relation to cost structure, consumers and BOP sector (12). As a result, donors view the private sector as malicious and exploitative of low-income society members. None of the well-known organizations perceive that market inclined solutions can result into poverty alleviation and economic growth. Prahalad and Hart turn to a discussion of products and services for the BOP. They assert that it requires an innovation perspective of product development and creativity in accordance with the realities of the BOP market. Based on this assertion, the writer identifies a number of principles that should guide innovations for the BOP market segment (9). The aspect is price performance. It is essential for quantum jumps in the price performance. The second factor focuses on hybrid solutions: advanced and evolving technologies that innovatively merge with available and increasingly developing infrastructure. Another important aspect is focusing on conservation of resources

Friday, August 23, 2019

Are all pressure ulcers avoidable Essay Example | Topics and Well Written Essays - 1250 words

Are all pressure ulcers avoidable - Essay Example At all times, nurses should observe the law and ethics related to informed consent (Selinger, 2009). Assuming that the patient has severe dementia or some kind of severe mental illnesses, it would be difficult for the nurse to seek permission from the patient prior to the delivery of care. Therefore, the nurses should at all times make sure that their decision-making gives justice and will not harm the patient in any way (i.e. physically, psychologically, etc.) (Selinger, 2009). To avoid facing ethical or legal problems, all nurses should regularly upgrade their knowledge concerning all legal and ethical aspects that defines the nursing profession (Barnard, Nash and OBrien, 2005). Action 2 – In relation to the NMC (2002) Code of Professional Conduct, the patient’s real name should be kept confidential at all times in order to protect the patient’s privacy and avoid the risks of unintentionally causing harm to the patient. Action 3 – Brian, who is 55 years old, refuses to accept the nurse’s advice and equipment that should be used for his treatment. In relation to nursing ethics, the case of Brian should be addressed by examining the principles of autonomy. Since the patient refuses to accept the nurse’s advice and equipment that should be used for his treatment, the nurse should respect the patient’s decision (Selinger, 2009). To avoid facing any legal problem in the future, perhaps it is best for the nurse to get the patient to sign a form stating about his decision not to accept the nurse’s advice and equipment that should be used for his treatment. Action 4 – Brian, aged 55 years suffers from multiple sclerosis. Multiple sclerosis is a health condition wherein the patient’s immune system could adversely affect the main function of the myelin (Falvo, 2014, pp. 109–110). As the disease progresses, the

Thursday, August 22, 2019

Japanese Art Essay Example for Free

Japanese Art Essay For the GOY* project, I chose to visit The Pavilion of Japanese Art in the Los Angeles County Museum of Art (LACMA) and look at Japanese artworks, especially from the Jomon to Heian period. There were no event focusing on Japanese Art on LACMA, so I opted to join a Sunday tour of the Japanese art collection instead. Knowing at once that it would only last for 50 minutes, I wondered at first how the guide would condense the lecture of thousands of years of Japanese history and Japanese art, especially that it entails a lot of explaining and translating to do. But the explanations as we went along the way were brief and concise and focused on the artworks, but were enough for us to take note of. What I intended to focus on were paintings from the Jomon to Heian period of Japanese Art, but instead I took note of different forms of Japanese artworks which I found interesting. There were several pieces that caught my attention, but those that I focused on were a ceramic vessel from the middle Jomon period, Jizo Bosatsu, which is carved wood sculpture from the late Heian period, and Seated Warrior, a sculpture from the Kofun period. Japanese art on the Jomon period are mostly earthenware vessels, mostly deep pots made of clay. Potteries made from the Jomon period are characterized by rope markings, incised lines and applied coils of clay (Kleiner 91). These vessels, however psychedelically figured, have a variety of uses. They serve different purposes, from storage to burial (Kleiner 91). The vessels on the Japanese Art Tour on the LACMA mostly have textured bases, the incised rope markings very apparent, and have castellated rims. Japanese art on the Kofun period is completely different. According to the Minneapolis Institute of Arts Website, the art on this period is characterized by tombs furnished haniwa, or cylinders which are used as adornment for tombs on the era. The forms of the haniwa later evolved to simple geometric forms of houses, animals, birds, and other figures. The sculpture on the LACMA, however, resembles a Seated Warior form, hence, its title. The Heian period is characterized with artworks representing or illustrating Esoteric Buddhism (Kleiner, 2010). Most of the artworks are Buddhist deities sculptures carved from wood, to which people worship. The sculpture of deities were characterized by a wardrobe of a monks, and all of them stood on top of a lotus, which symbolizes rebirth, according to the tour guide. I have expected Japanese art to be intricate, except maybe those from the Jomon period. But it turned out that even from the Neolithic period, the Japanese already had a sense of aesthetics that their vessels are adorned with rope markings. For me, the abstract form of Jomon period art is its strength. The Kofun period art was indeed very interesting for me because the artworks were used to decorate tombs, and the decorations symbolizes the person in that tomb. Meanwhile, as expected, Heian art is deeply rooted on Buddhism, and has Chinese influences. At the end of the day, I realized that the evolution of Japanese art relied on what happened in Japan at the time these artworks were constructed. The colorful events strongly influences the frame of mind of the artists. History is what shapes art.

Wednesday, August 21, 2019

All characters in the novel Essay Example for Free

All characters in the novel Essay All characters in the novel Of Mice and Men are either lonely, bored or in need of escaping from the soulless existence of the itinerant labour. It is based on a society of men leading empty lives, trapped in a lonely life, consisting mainly of hard physical work. There was not enough happiness, love and affection in their lives. The novel is set in California, the Southern states of America, in the 1930s around the time of the Great Depression. The ranch is based in Soledad; which is the Spanish word for Loneliness. The bunkhouse that the men sleep and live in is a long and rectangular building. The walls are white washed and the floor unpainted. In three of the four walls are small, square windows. In the fourth one was a solid door with a wooden latch. There are eight bunks, all with a nailed apple box over them with the opening forward. This made two small shelves for the personal belongings of each ranch hand occupying the certain bunk. On these shelves were little articles, soap, razors, talcum powder, Western magazines, medicines, little vials, combs and a few neckties. There was also a black cast iron stove, and a big square table in the centre of the room, with scattered playing cards across it, and surrounding the table were boxes for the men to sit on. The bunkhouse also had lice and roaches in it! Carlson and the other ranch hands all dream of owning their own land and living and working from this, resulting in wealth and happiness. This was known as the American Dream, this is shown as an opportunity to all people no matter how rich or poor they are. There is a lot of government propaganda, informing people that if they work hard and push their ambitions to the limit, they can make this dream reality. However they all knew, no matter how hard they worked or how successful they were, it was very unlikely of this dream ever becoming reality. Their way of escaping this disappointment was to collect their fifty bucks at the end of the month and of a weekend spend all of it on women and alcohol, usually at the nearest cat-house. During the week they play cards games or horseshoes. Crooks is very lonely, this is due to the fact that he is coloured and everyone knows him as a nigger! He is treated completely differently to all the others, an outsider. He is also crippled, after a horse kicked him and severely damaged his back. In the 1930s it was very racist in America and the coloured people werent allowed to speak up or were too scared to defend themselves in fear of what the white people would do to them. This is the situation Crooks is in. However he is the only coloured person at the ranch, so he has to accept all racial comments on his own. He has his own separate room, which isnt even a room it is a shed that leans off the side of the barn wall. He is isolated from everyone else, therefore unable to socialise. On one occasion Lennie entered the barn to see his pup. He saw Crooks light shining and stood in the doorway of Crooks room. Crooks saw him and said sharply you got no right to come in my room. This heres my room. Nobody got any right in here, but me. He then followed with I aint wanted in the bunkhouse and you aint wanted in my room, they play cards in there, but I cant play because Im black. They say I stink. Well, I tell you all of you stink to me. Crooks reads to amuse himself when he has nothing better to do. This keeps his mind off of the atmosphere and situation he is surrounded by in his everyday life. Curleys wife is perhaps one of the loneliest characters, trapped in her strict and original womans/wifes role. Her daily routine only ever consists of her doing housework, such as cooking Curleys dinner, washing Curleys clothes, making Curleys bed, cleaning Curleys house, etc. If Curley catches her talking to the ranch hands he is always very annoyed by it, she is to stay in the house. She is known as Curleys wife, no one knows her name so they cannot call her by it. One time when she enters the bunkhouse and begins to talk to the ranch hands, Crooks suggests Maybe you better go along to your own house now. We dont want no trouble. It is this idea that she is trouble that makes Curleys wife so upset and angry. Well, I aint giving you no trouble. Think I dont like to talk to somebody ever once in a while? Think I like to stick in that house alla time? Having a husband even makes her loneliness worse, because Curley is so strict about whom she socialises with and what she does. She calls him sarcastically a Swell guy, who Spends all his time sayin what hes gonna do to guys he dont like, and he dont like nobody. Curleys wife tries to escape her loneliness and sadness by dreaming of being an actress or a model. She had been offered the chance before I tell you I could of went with shows An a guy tol me he could put me in pitchers. Curleys wife is also very good at flirting, this attracts male attention. Therefore just for a moment she is listened to and is the centre of attention, this moment matters so much to her because she is being paid attention to for once, that she makes a very bad habit of it. However the ranch hands have got used to her scheming ways and do not want to risk getting canned because of a tart. However Lennie and George are different to the other ranch hands, they may live a lonely existence, but they have each other. Other than the other ranch hands expressing their feelings about their hopes, dreams, lonely lives etc, George and Lennie are the only characters we really get to know. All other ranch hands havent got a family or anything to look forward to, but it is different with George and Lennie; they believe they have a future and as long as they have got each other, it doesnt matter whether they have a family or not. These men love each other. They talk to each other and know that the other cares for them, because George looks after Lennie, and Lennie looks after George. However, George has a much greater job in looking after Lennie, than Lennie has in looking after George. Lennie is a bit of a dunce and is always forgetting things, but George has the brains. They both are physically well built, but Lennie does not realise his own strength sometimes, he is dangerously strong. Lennie is the physical side of the pair, whereas George is the mental. The fact that they have each other gives them more of a chance of success, than the other ranch hands. Lennie loves George to tell him what; one-day things will be like. Their dream is to one day buy a little house, with a ten acres, a winmill, a kitchen, an orchard to grow cherries, apples, peaches, cots, nuts, and a few berries, a section on the land to grow alfalfa that Lennie will use to feed the rabbits with, hutches and pens full with pigs, chickens, cows, goats, cats, pigeons, a dog and rabbits that Lennie could pet, a smoke house so they could kill the pigs and then smoke it, for smoked ham and bacon etc, and for them to literally live off the fatta the lan'. They would only work six or seven hours a day. Lennie likes to pet, smooth, soft, furry things, as a kind of comfort. Other than for George and animals, love and affection are withheld, not only from Lennie, but also for all the ranch hands. This is why they have their own individual comfort or way of escaping from the repetitive daily routine and loneliness. Candy is a dissimilar character from the other ranch hands. He is very lonely and sad. He has no hand, but a very old dog that he cares for very much. This dog is similar to Candy. They are both very old and when Carlson shoots the dog, because it smells, has no teeth, he cannot eat, is stiff with rheumatism, is nearly blind and Carlson thinks it will be better to put the dog out of his ageing misery. Candy wants people to treat him once he is canned like this. This is because he wont have no place to go, an he cant get no more jobs. The other ranch hands say that he can replace the dog with one of Lulus pups, but of course that wouldnt be the same, never is anyone or anything the equivalent, everyone and everything is unique. Candy seems to think that when he is dead, people will say the same thing about him. When a new ranch hand comes and replaces him, hell be forgotten. For obvious reasons Candy is upset and hurt by this. It is as if the characteristics of his dog and the way the other men treat the dog, symbolises Candy. Candy wants to join George and Lennie in their dream. Candy has already got three hundred bucks and another fifty coming at the end of the month, when the men get paid. He explains that he aint much good, but I could cook, tend the chickens, and hoe the garden some. Then when George and Lennie get their fifty bucks each at the end of the month, they will have four hundred and fifty bucks, and although the woman wants six hundred bucks, George thinks she will accept their offer as a deposit and then George will get a job and start to collect the rest, while Candy and Lennie could work on the land as well as sell eggs etc, making more money. This is Candys route of escaping. Everything seems to be falling into place and their dream looks like it could become reality. This is everything a man wants and Candy is thrilled he is part of it. However much their dream looks real, it all ends when Curleys wife tries her old tricks with Lennie. Curleys wife enters the barn, as Lennie sits there mourning over his pup, he has just accidentally killed! George has already warned Lennie about Curleys wife, says she is trouble, so Lennie refuses to talk to her, George says I aint to have nothing to do with you- talk to you or nothing. Curleys wife says in a innocent voice, All the guys got a horse-shoe tenement goin on, so Why cant you talk to me? She eventually persuades Lennie that it is safe to talk to her. They talk for ages and Lennie tells her how he likes to pet nice things with my fingers, sof things. She tells Lennie to feel right here, on her hair. Lennie was enjoying stroking her hair until she warned him not to muss it up. She then got angry because Lennie wasnt listening to her. She went to pull away and Lennie clasped his fingers tightly in her hair and wouldnt let go. She began to shout, you let go. Lennie began to get scared because he thought George would hear and go mad. He covered her mouth and nose to prevent her screaming, and continued to beg her to be quiet. She continued to struggle and he shook her. Suddenly her body flopped like a fish. She was dead! Lennie ran to the brush that George had told him to hide in when they first arrived in Soledad if he ever got into trouble. When Candy found Curleys wife dead and told all the ranch hands, they all knew it was Lennie! Most of the men wanted to kill Lennie, but George got there first. George knew that Lennie would be scared if half a dozen men ran towards him shooting, but if George was to do it at the back of his head, just like Candys old dog it would be pain free. When George found him, Lennie asked for the story of their dream to be told to him and questioned George why he wasnt mad at him, but obviously if this was Georges last moments with Lennie he didnt want to be mad at him. As George told the story and paused every so often, Lennie would say go on or Gonna do it soon as if he knew what George was about to do and was encouraging George to get it over and done with. George finally shot Lennie. Lennie jarred forward and the settled peacefully as he lay on the sand. George just sat stiffly and silently n the bank, looking at his hand that had just pulled the trigger disgustedly. George knew it was for the best, where ever they were to go Lennies unrecognised strength would lead to trouble; it had already, both in Weed and Soledad. Lennie was trapped by his strength. Although, Lennie has now been released from pain by no longer being able to kill others and from not getting shot by half a dozen men cruelly, but peacefully by George. The upsetting thing is, that Lennie was so afraid of being alone and away from George, and now he was just that. It was all over!!! George is now free; he is no longer trapped by his want of freedom, of constantly looking after Lennie. I think the novel tries to give us the message that people try to lead their lives as successfully as possible, in order to result in the best possible outcome. However this is very hard to succeed. The ranch hands wanted the American Dream to become reality, but is very unlikely and as shown does not happen. The novel gave a very positive view of the American dream, but this is erroneous and does not come true. The chances of finding true, lasting friendship and happiness are also very unlikely as it is always spoilt by misfortune, arguments, inconveniences and sometimes death, as in this case.

Tuesday, August 20, 2019

CAPM and Three Factor Model in Cost of Equity Measurement

CAPM and Three Factor Model in Cost of Equity Measurement 1.0 INTRODUCTION AND OBJECTIVES Central to many financial decisions such as those relating to investment, capital budgeting, portfolio management and performance evaluation is the estimation of the cost of equity or expected return. There exist several models for the valuation of equity returns, prominent among which are the dividend growth model, residual income model and its extension, free cash flow model, the capital asset pricing model, the Fama and French three factor model, the four factor model etc. Over the past few decades, two of the most common asset pricing models that have been used for this purpose are the Capital Asset Pricing Model (a single factor model by Sharpe 1964, Lintner 1965) and the three factor model suggested by Fama and French (1993). These two models have been very appealing to both practitioners and academicians due to their structural simplicity and are very easy to interpret. There have however been lots of debates and articles as to which of these two models should be used when est imating the cost of equity or expected returns. The question as to which of these two models is better in terms of their ability to explain variation in returns and forecast future returns is still an open one. While most practitioners favour a one factor model (CAPM) when estimating the cost of equity or expected return for a single stock or portfolio, academics however recommend the Fama and French three factor model (see eg. Bruner et al, 1998). The CAPM depicts a linear relationship between the expected return on a stock or portfolio to the excess return on a market portfolio. It characterizes the degree to which an assets return is correlated to the market, and indirectly how risky the asset is, as captured by beta. The three-factor model on the other hand is an extension of the CAPM with the introduction of two additional factors, which takes into account firm size (SMB) and book-to-market equity (HML). The question therefore is why practitioners prefer to use the single factor model (CAPM) when there exist some evidence in academics in favour of the Fama and French three factor model. Considering the number of years most academic concepts are adopted practically, can we conclude that the Fama and French three factor model is experiencing this so-called natural resistance or is it the case that the Fama and French model does not perform significantly better than the CAPM and so therefore not worth the time and cost? The few questions I have posed above form the basis for this study. It is worth noting that while the huge academic studies on these models produce interesting results and new findings, the validity of the underlying models have not been rigorously verified. In this paper, while I aim to ascertain which of the two models better estimates the cost of equity for capital budgeting purposes using regression analysis, I also will like to test whether the data used satisfy the assumptions of the method most academicians adopt, i.e. the Ordinary Least Squares (OLS) method. I will in particular be testing for the existence or otherwise of heteroscedasticity, multicollinearity, normality of errors serial correlation and unit roots, which may result in inefficient coefficient estimates, wrong standard errors, and hence inflated adjusted R2 if present in the data. I will then correct these if they exist by adopting the Generalised Least Squares (GLS) approach instead of the widely used Ordinary Least Squares (OLS) before drawing any inference from the results obtained. My conclusion as to which of the models is superior to the other will be based on which provides the best possible estimate for expected return or cost of equity for capital budgeting decision making. Since the cost of capital for capital budgeting is not observed, the objective here, therefore, is to find the model that is most effective in capturing the variations in stock returns as well as providing the best estimates for future returns. By running a cross sectional regression using stock or portfolio returns as the dependent variable and estimated factor(s) based on past returns as regressors, R2 measures how much of the differences in returns is explained by the estimation procedure. The model that produces the highest adjusted R2 will therefore be deemed the best. The Fama-French (1993, 1996) claimed superiority of their model over CAPM in explaining variations in returns from regressions of 25 portfolios sorted by size and book-to-market value. Their conclusion was based on the fact that their model produced a lower mean absolute value of alpha which is much closer to the theoretical value of zero. Fama and French (2004, working paper) stated that if asset pricing theory holds either in the case of the CAPM (page 10), or the Fama and French three-factor model (page 21), then the value of their alphas should be zero, depicting that the asset pricing model and its factor or factors explain the variations in portfolio returns. Larger values of alpha in this case are not desirable, since this will imply that the model was poor in explaining variation in returns. In line with this postulation, the model that yields the lowest Mean Absolute Value of Alpha (MAVA) will therefore be considered the best. But since alpha is a random variable, I will pro ceed to test the null hypothesis H0: ÃŽ ±i = 0 for all i, by employing the GRS F-statistic postulated by Gibbons, Ross and Shanken (1989). My third and fourth testing measures are based on postulates by econometricians that, the statistical adequacy of a model in terms of its violations of the classical linear regression model assumptions is hugely irrelevant if the models predictive power is poor and that the accuracy of forecasts according to traditional statistical criteria such as the MSE may give little guide to the potential profitability of employing those forecasts in a market trading strategy or for capital budgeting purposes. I will therefore test the predictive power of the two models by observing the percentage of forecast signs predicted correctly and their Mean Square Errors (MSE). One other motivation for this study is also to ascertain whether the results of prior studies are sample specific, that is, whether it is dependent on the period of study or the portfolio grouping used. Theoretically, the effectiveness of an asset pricing model in explaining variation in returns should not be influenced by how the data is grouped. Fama and French (1996) claimed superiority of their model over the CAPM using the July 1963 to December 1993 time period with data groupings based on size and book-to-market equity. I will be replicating this test on the same data grouping but covering a much longer period (from July 1926 to June 2006) and then on a different data grouping based on industry characteristics. Testing the models using the second grouping of industry portfolios will afford me the opportunity to ascertain whether the effectiveness of an asset pricing model is sample specific. I will also carry out the test by employing a much shorter period (5 years) and compari ng it to the longer period and then using the one with the better estimate in terms of alpha and R2 to carry out out-of-sample forecasts. The rest of this paper is structured as follows. Chapter 2 will review the various models available for the estimation of equity cost with particular emphasis on the two asset-pricing models and analysing some existing literature. Chapter 3 will give a description of the data, its source and transformations required, with Chapter 4 describing the methodology. Chapter 5 will involve the time series tests of hypothesis on the data and Chapter 6 will involve an empirical analysis of the results for the tests of the CAPM and the Fama and French three-factor model. Finally, Chapter 7 contains a summary of the major findings of my work and my recommendation as well as some limitations, if any, of the study and recommended areas for further studies. 2.0 RELEVANT LITERATURE The estimation of the cost of equity for an industry involves estimation of what investors expect in return for their investment in that industry. That is, the cost of equity to an industry is equal to the expected return on investors equity holdings in that industry. There are however a host of models available for the estimation of expected returns on an industrys equity capital including but not limited to estimates from fundamentals (dividends and earnings) and those from asset pricing models. 2.1 Estimations from Fundamentals Estimation of expected returns or cost of equity in this case from fundamentals involves the use of dividends and earnings. Fama and French (2002) used this approach to estimate expected stock returns. They stated that, the expected return estimates from fundamentals help to judge whether the realised average return is high or low relative to the expected value (pp 1). The reasoning behind this approach lies in the fact that, the average stock return is the average dividend yield plus the average rate of capital gain: A(Rt) = A(Dt/Pt-1) + A(GPt) (1) where Dt is the dividend for year t, Pt-1 is the price at the end of year t 1, GPt = (Pt Pt-1)/Pt-1 is the rate of capital gain, and A( ) indicates an average value. Given in this situation that the dividend-price ratio, Dt/Pt , is stationary (mean reverting), an alternative estimate of the stock return from fundamentals is: A(RDt) = A(Dt/Pt-1) + A(GDt) (2) Where GDt = (Dt Dt-1)/Dt-1is the growth rate of dividends and (2) is known as the dividend growth model which can be viewed as the expected stock return estimate of the Gordon (1962) model. Equation (2) in theory will only apply to variables that are cointegrated with the stock price and may not hold if the dividend-price ratio is non-stationary, which may be caused by firms decision to return earnings to stockholders by moving away from dividends to share repurchases (Fama and French 2002). But assuming that the ratio of earnings to price, (Yt/Pt), is stationary, then an alternative estimate of the expected rate of capital gain will be the average growth rate of earnings, A(GYt) = A((Yt Yt-1)/Yt-1). In this case, the average dividend yield can be combined with the A(GYt) to produce a third method of estimating expected stock return, the earnings growth model given as: A(RYt) = A(Dt/Pt-1) + A(GYt) (3) It stands to reason from the model in Lettau and Ludvigson (2001) that the average growth rate of consumption can be an alternative mean of estimating the expected rate of capital gain if the ratio of consumption to stock market wealth is assumed stationary. Fama and French (2002) in their analysis concluded that the dividend growth model has an advantage over the earnings growth model and the average stock return if the goal is to estimate the long-term expected growth of wealth. However, it is a more generally known fact that, dividends are a policy variable and so subject to changes in management policy, which raises problems when using the dividend growth model to estimate the expected stock returns. But this may not be a problem in the long run if there is stability in dividend policies and dividend-price ratio resumes its mean-reversion (although the reversion may be at a new mean level). Bagwell and Shoven (1989) and Dunsby (1995) have observed that share repurchases after 1983 has been on the ascendancy, while Fama and French (2001) have also observed that the proportion of firms who do not pay dividends have been increasing steadily since 1978. The Fama and French (2001) observation implies that in transition periods where firms who do not pay dividends increases steadily, the market dividend-price ratio may be non-stationary; overtime, it is likely to decrease, in which case the expected return will likely be underestimated when the dividend growth model is used. The earnings growth model, although not superior to the dividend growth model (Fama and French (2002)), is not affected by possible changes in dividend policies over time. The earnings growth model however may also be affected by non-stationarity in earnings-price ratio since it ability to accurately estimate average expected return is based on the assumption that there are permanent shifts in the expected value of the earnings-price ratio. 2.2 Estimations from Asset-Pricing Models One of the most fundamental concepts in the area of asset-pricing is that of risk versus reward. The pioneering work that addressed the risk and reward trade-off was done by Sharpe (1964)-Lintner (1965), in their introduction of the Capital Asset Pricing Model (CAPM). The Capital Asset Pricing Model postulates that the cross-sectional variation in expected stock or portfolio returns is captured only by the market beta. However, evidence from past literature (Fama and French (1992), Carhart (1997), Strong and Xu (1997), Jagannathan and Wang (1996), Lettau and Ludvigson (2001), and others) stipulates that the cross-section of stock returns is not fully captured by the one factor market beta. Past and present literature including studies by Banz (1981), Rosenberg et al (1985), Basu (1983) and Lakonishok et al (1994) have established that, in addition to the market beta, average returns on stocks are influenced by size, book-to-market equity, earnings/price and past sales growth respecti vely. Past studies have also revealed that stock returns tend to display short-term momentum (Jegadeesh and Titman (1993)) and long-term reversals (DeBondt and Thaler (1985)). Growing research in this area by scholars to address these anomalies has led to the development of alternative models that better explain variations in stock returns. This led to the categorisation of asset pricing models into three: (1) multifactor models that add some factors to the market return, such as the Fama and French three factor model; (2) the arbitrage pricing theory postulated by Ross (1977) and (3) the nonparametric models that heavily criticized the linearity of the CAPM and therefore added moments, as evidenced in the work of Harvey and Siddique (2000) and Dittmar (2002). From this categorization, most of the asset-pricing models can be described as special cases of the four-factor model proposed by Carhart (1997). The four-factor model is given as: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]bi + si E(SMB) + hi E(HML) + wiE(WML) + ÃŽ µi (4) where SMB, HML and WML are proxies for size, book-to-market equity and momentum respectively. There exist other variants of these models such as the three-moment CAPM and the four-moment CAPM (Dittmar, 2002) which add skewness and kurtosis to investor preferences, however the focus of this paper is to compare and test the effectiveness of the CAPM and the Fama and French three-factor model, the two premier asset-pricing models widely acknowledged among both practitioners and academicians. 2.3 Theoretical Background: CAPM and Fama French Three-Factor Model There exist quite a substantial amount of studies in the field of finance relating to these two prominent asset pricing models. The Capital Asset Pricing Model (CAPM) of Sharpe (1964) and Lintner (1965) has been the first most widely recognized theoretical explanation for the estimation of expected stock returns or cost of equity in this case. It is a single factor model that is widely used by Financial Economists and in industry. The CAPM being the first theoretical asset pricing model to address the risk and return concept and due to its simplicity and ease of interpretation, was quickly embraced when it was first introduced. The models attractiveness also lies in the fact that, it addressed difficult problems related to asset pricing using readily available time series data. The CAPM is based on the idea of the relationship that exists between the risk of an asset and the expected return with beta being the sole risk pricing factor. The Sharpe-Lintner CAPM equation which describes individual asset return is given as: E(Ri) = Rf + [ E(RM) Rf ]ÃŽ ²iM i = 1,,N (5) where E(Ri) is the expected return on any asset i, Rf is the risk-free interest rate, E(RM) is the expected return on the value-weighted market portfolio, and ÃŽ ²iM is the assets market beta which measures the sensitivity of the assets return to variations in the market returns and it is equivalent to Cov(Ri, RM)/Var(RM). The equation for the time series regression can be written as: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]ÃŽ ²iM + ÃŽ µi i = 1,,N; (6) showing that the excess return on portfolio i is dependent on excess market return with ÃŽ µi as the error term. The excess market return is also referred to as the market premium. The model is based on several key assumptions, portraying a simplified world where: (1) there are no taxes or transaction costs or problems with indivisibilities of assets; (2) all investors have identical investment horizons; (3) all investors have identical opinions about expected returns, volatilities and correlations of available investments; (4) all assets have limited liability; (5) there exist sufficiently large number of investors with comparable wealth levels so that each investor believes that he/she can purchase and sell any amount of an asset as he or she deems fit in the market; (6) the capital market is in equilibrium; and (7) Trading in assets takes place continually over time. The merits of these assumptions have been discussed extensively in literature. It is evident that most of these assumptions are the standard assumptions of a perfect market which does not exist in reality. It is a known fact that, in reality, indivisibilities and transaction costs do exist and one of the reasons assigned to the assumption of continual trading models is to implicitly give recognition to these costs. It is imperative to note however that, trading intervals are stochastic and of non-constant length and so making it unsatisfactory to assume no trading cost. As mentioned earlier, the assumptions made the model very simple to estimate (given a proxy for the market factor) and interpret, thus making it very attractive and this explains why it was easily embraced. The CAPM stipulates that, investors are only rewarded for the systematic or non-diversifiable risk (represented by beta) they bear in holding a portfolio of assets. Notwithstanding the models simplicity in estimation and interpretation, it has been criticized heavily over the past few decades . Due to its many unrealistic assumptions and simple nature, academicians almost immediately began testing the implications of the CAPM. Studies by Black, Jensen and Scholes (1972) and Fama and MacBeth (1973) gave the first strong empirical support to the use of the model for determining the cost of capital. Black et al. (1972) in combining all the NYSE stocks into portfolio and using data between the periods of 1931 to 1965 found that the data are consistent with the predictions of the Capital Asset Pricing Model (CAPM). Using return data for NYSE stocks for the period between 1926 to 1968, Fama and MacBeth (1973) in examining whether other stock characteristics such as beta squared and idiosyncratic volatility of returns in addition to their betas would help in explaining the cross section of stock returns better found that knowledge of beta was sufficient. There have however been several academic challenges to the validity of the model in relation to its practical application. Banz (1981) revealed the first major challenge to the model when he provided empirical evidence to show that stocks of smaller firms earned better returns than predicted by the CAPM. Banzs finding was not deemed economically important by most academicians in the light that, it is unreasonable to expect an abstract model such as the CAPM to hold exactly and that the proportion of small firms to total market capital is insignificant (under 5%). Other early empirical works by Blume and friend (1973), Basu (1977), Reinganum (1981), Gibbons (1982), Stambaugh (1982) and shanken (1985) could not offer any significant evidence in support of the CAPM. In their paper, Fama and French (2004) noted that in regressing a cross section of average portfolio returns on portfolio beta estimates, the CAPM would predict an intercept which is equal to the risk free rate (Rf) and a beta coefficient equal to the market risk premium (E(Rm) Rf). However, Black, Jensen and Scholes (1972), Blume and Friend (1973), Fama and MacBeth (1973) and Fama and French (1992) after running series of cross-sectional regressions found that the average risk-free rate, which is proxied by the one month T-bill, was always less that the realised intercept. Theory stipulates that, the three main components of the model (the risk free, beta and the market risk premium) must be forward-looking estimates. That is they must be estimates of their true future values. Empirical studies and survey results however show substantial disagreements as to how these components can be estimated. While most empirical researches use the one month T-bill rate as a proxy to the risk-fr ee rate, interviews depicts that practitioners prefer to use either the 90-day T-bill or a 10-year T-bond (normally characterised by a flat yield curve). Survey results have revealed that practitioners have a strong preference for long-term bond yields with over 70% of financial advisors and corporations using Treasury-bond yields with maturities of ten 10 or more years. However, many corporations reveal that they match the tenor of the investment to the term of the risk free rate. Finance theory postulates that the estimated beta should be forward looking, so as to reflect investors uncertainty about future cash flows to equity. Practitioners are forced to use various kinds of proxies since forward-looking betas are unobservable. It is therefore a common practice to use beta estimates derived from historical data which are normally retrieved from Bloomberg, Standard Poors and Value Line. However, the lack of consensus as to which of these three to use results in different betas for the same company. These differences in beta estimates could result in significantly different expected future returns or cost of equity for the company in question thereby yielding conflicting financial decisions especially in capital budgeting. In the work of Bruner et al. (1998), they found significant differences in beta estimates for a small sample of stocks, with Bloomberg providing a figure of 1.03 while Value Line beta was 1.24. The use of historical data however requires th at one makes some practical compromises, each of which can adversely affect the quality of the results. Forinstance, the statistically reliability of the estimate may improve greatly by employing longer time series periods but this may include information that are stale or irrelevant. Empirical research over the years has shown that the precision of the beta estimates using the CAPM is greatly improved when working with well diversified portfolios compared to individual securities. In relation to the equity risk premium, finance theory postulates that, the market premium should be equal to the difference between investors expected returns on the market portfolio and the risk-free rate. Most practitioners have to grapple with the problem of how to measure the market risk premium. Survey results have revealed that the equity market premium prompted the greatest diversity of responses among survey respondents. Since future expected returns are unobservable, most of the survey participants extrapolated historical returns in the future on the assumption that future expectations are heavily influenced by past experience. The survey participants however differed in their estimation of the average historical equity returns as well as their choice of proxy for the riskless asset. Some respondents preferred the geometric average historical equity returns to the arithmetic one while some also prefer the T-bonds to the T-bill as a proxy for the riskless asset. Despite the numerous academic literatures which discuss how the CAPM should be implemented, there is no consensus in relation to the time frame and the data frequency that should be used for estimation. Bartholdy Peare (2005) in their paper concluded that, for estimation of beta, five years of monthly data is the appropriate time period and data frequency. They also found that an equal weighted index, as opposed to the commonly recommended value-weighted index provides a better estimate. Their findings also revealed that it does not really matter whether dividends are included in the index or not or whether raw returns or excess returns are used in the regression equation. The CAPM has over the years been said to have failed greatly in explaining accurate expected returns and this some researchers have attributed to its many unrealistic assumptions. One other major assumption of the CAPM is that there exists complete knowledge of the true market portfolios composition or index to be used. This assumed index is to consist of all the assets in the world. However since only a small fraction of all assets in the world are traded on stock exchanges, it is impossible to construct such an index leading to the use of proxies such as the SP500, resulting in ambiguities in tests. The greatest challenge to the CAPM aside that of Banz (1981) came from Fama and French (1992). Using similar procedures as Fama and MacBeth (1973) and ten size classes and ten beta classes, Fama and French (1992) found that the cross section of average returns on stocks for the periods spanning 1960s to 1990 for US stocks is not fully explained by the CAPM beta and that stock risks are multidimensional. Their regression analysis suggest that company size and book-to-market equity ratio do perform better than beta in capturing cross-sectional variation in the cost of equity capital across firms. Their work was however preceded by Stattman (1980) who was the first to document a positive relation between book-to-market ratios and US stock returns. The findings of Fama and French could however not be dismissed as being economically insignificant as in the case of Banz. Fama and French therefore in 1993 identified a model with three common risk factors in the stock return- an overall market factor, factors related to firm size (SMB) and those related to book-to-market equity (HML), as an alternative to the CAPM. The SMB factor is computed as the average return on three small portfolios (small cap portfolios) less the average return on three big portfolios (large cap portfolios). The HML factor on the other hand is computed as the average return on two value portfolios less the average return on two growth portfolios. The growth portfolio represents stocks with low Book Equity to Market Equity ratio (BE/ME) while the value portfolios represent stocks with high BE/ME ratio. Their three-factor model equation is described as follows: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]bi + si E(SMB) + hi E(HML) + ÃŽ µi (7) Where E(RM) Rf, , E(SMB) and E(HML) are the factor risk premiums and bi , si and hi are the factor sensitivities. It is however believed that the introduction of these two additional factors was motivated by the works of Stattman (1980) and Banz (1981). The effectiveness of these two models in capturing variations in stock returns may be judged by the intercept (alpha) in equations (6) and (7) above. Theory postulates that if these models hold, then the value of the intercept or alpha must equal zero for all assets or portfolio of assets. Fama and French (1997) tested the ability of both the CAPM and their own three-factor model in estimating industry costs of equity. Their test considered 48 industries in which they found that their model outperformed the CAPM across all the industries considered. They however could not conclude that their model was better since their estimates of industry cost of equities were observed to be imprecise. Another disturbing outcome of their study is that both models displayed very large standard errors in the order of 3.0% per annum across all industries. Connor and Senghal (2001) tested the effectiveness of these two models in predicting portfolio returns in indias stock market. They tested the models using 6 portfolio groupings formed from the intersection of two size and three book-to-market equity by examining and testing their intercepts. Connor and Senghal in this paper examined the values of the intercepts and their corresponding t-statistics and then tested the intercepts simultaneously by using the GRS statistic first introduced by Gibbons, Ross and Shanken (1989). Based on the evidence provided by the intercepts and the GRS tests, Connor and Senghal concluded generally that the three-factor model of Fama and French was superior to the CAPM. There have been other several empirical papers ever since, to ascertain which of these models is better in the estimation of expected return or cost of equity, most producing contrasting results. Howard Qi (2004) concluded in his work that on the aggregate level, the two models behave fairly well in their predictive power but the CAPM appeared to be slightly better. Bartholdy and Peare (2002) in their work came to the conclusion that both models performed poorly with the CAPM being the poorest. 3.0 DATA SOURCES T CAPM and Three Factor Model in Cost of Equity Measurement CAPM and Three Factor Model in Cost of Equity Measurement 1.0 INTRODUCTION AND OBJECTIVES Central to many financial decisions such as those relating to investment, capital budgeting, portfolio management and performance evaluation is the estimation of the cost of equity or expected return. There exist several models for the valuation of equity returns, prominent among which are the dividend growth model, residual income model and its extension, free cash flow model, the capital asset pricing model, the Fama and French three factor model, the four factor model etc. Over the past few decades, two of the most common asset pricing models that have been used for this purpose are the Capital Asset Pricing Model (a single factor model by Sharpe 1964, Lintner 1965) and the three factor model suggested by Fama and French (1993). These two models have been very appealing to both practitioners and academicians due to their structural simplicity and are very easy to interpret. There have however been lots of debates and articles as to which of these two models should be used when est imating the cost of equity or expected returns. The question as to which of these two models is better in terms of their ability to explain variation in returns and forecast future returns is still an open one. While most practitioners favour a one factor model (CAPM) when estimating the cost of equity or expected return for a single stock or portfolio, academics however recommend the Fama and French three factor model (see eg. Bruner et al, 1998). The CAPM depicts a linear relationship between the expected return on a stock or portfolio to the excess return on a market portfolio. It characterizes the degree to which an assets return is correlated to the market, and indirectly how risky the asset is, as captured by beta. The three-factor model on the other hand is an extension of the CAPM with the introduction of two additional factors, which takes into account firm size (SMB) and book-to-market equity (HML). The question therefore is why practitioners prefer to use the single factor model (CAPM) when there exist some evidence in academics in favour of the Fama and French three factor model. Considering the number of years most academic concepts are adopted practically, can we conclude that the Fama and French three factor model is experiencing this so-called natural resistance or is it the case that the Fama and French model does not perform significantly better than the CAPM and so therefore not worth the time and cost? The few questions I have posed above form the basis for this study. It is worth noting that while the huge academic studies on these models produce interesting results and new findings, the validity of the underlying models have not been rigorously verified. In this paper, while I aim to ascertain which of the two models better estimates the cost of equity for capital budgeting purposes using regression analysis, I also will like to test whether the data used satisfy the assumptions of the method most academicians adopt, i.e. the Ordinary Least Squares (OLS) method. I will in particular be testing for the existence or otherwise of heteroscedasticity, multicollinearity, normality of errors serial correlation and unit roots, which may result in inefficient coefficient estimates, wrong standard errors, and hence inflated adjusted R2 if present in the data. I will then correct these if they exist by adopting the Generalised Least Squares (GLS) approach instead of the widely used Ordinary Least Squares (OLS) before drawing any inference from the results obtained. My conclusion as to which of the models is superior to the other will be based on which provides the best possible estimate for expected return or cost of equity for capital budgeting decision making. Since the cost of capital for capital budgeting is not observed, the objective here, therefore, is to find the model that is most effective in capturing the variations in stock returns as well as providing the best estimates for future returns. By running a cross sectional regression using stock or portfolio returns as the dependent variable and estimated factor(s) based on past returns as regressors, R2 measures how much of the differences in returns is explained by the estimation procedure. The model that produces the highest adjusted R2 will therefore be deemed the best. The Fama-French (1993, 1996) claimed superiority of their model over CAPM in explaining variations in returns from regressions of 25 portfolios sorted by size and book-to-market value. Their conclusion was based on the fact that their model produced a lower mean absolute value of alpha which is much closer to the theoretical value of zero. Fama and French (2004, working paper) stated that if asset pricing theory holds either in the case of the CAPM (page 10), or the Fama and French three-factor model (page 21), then the value of their alphas should be zero, depicting that the asset pricing model and its factor or factors explain the variations in portfolio returns. Larger values of alpha in this case are not desirable, since this will imply that the model was poor in explaining variation in returns. In line with this postulation, the model that yields the lowest Mean Absolute Value of Alpha (MAVA) will therefore be considered the best. But since alpha is a random variable, I will pro ceed to test the null hypothesis H0: ÃŽ ±i = 0 for all i, by employing the GRS F-statistic postulated by Gibbons, Ross and Shanken (1989). My third and fourth testing measures are based on postulates by econometricians that, the statistical adequacy of a model in terms of its violations of the classical linear regression model assumptions is hugely irrelevant if the models predictive power is poor and that the accuracy of forecasts according to traditional statistical criteria such as the MSE may give little guide to the potential profitability of employing those forecasts in a market trading strategy or for capital budgeting purposes. I will therefore test the predictive power of the two models by observing the percentage of forecast signs predicted correctly and their Mean Square Errors (MSE). One other motivation for this study is also to ascertain whether the results of prior studies are sample specific, that is, whether it is dependent on the period of study or the portfolio grouping used. Theoretically, the effectiveness of an asset pricing model in explaining variation in returns should not be influenced by how the data is grouped. Fama and French (1996) claimed superiority of their model over the CAPM using the July 1963 to December 1993 time period with data groupings based on size and book-to-market equity. I will be replicating this test on the same data grouping but covering a much longer period (from July 1926 to June 2006) and then on a different data grouping based on industry characteristics. Testing the models using the second grouping of industry portfolios will afford me the opportunity to ascertain whether the effectiveness of an asset pricing model is sample specific. I will also carry out the test by employing a much shorter period (5 years) and compari ng it to the longer period and then using the one with the better estimate in terms of alpha and R2 to carry out out-of-sample forecasts. The rest of this paper is structured as follows. Chapter 2 will review the various models available for the estimation of equity cost with particular emphasis on the two asset-pricing models and analysing some existing literature. Chapter 3 will give a description of the data, its source and transformations required, with Chapter 4 describing the methodology. Chapter 5 will involve the time series tests of hypothesis on the data and Chapter 6 will involve an empirical analysis of the results for the tests of the CAPM and the Fama and French three-factor model. Finally, Chapter 7 contains a summary of the major findings of my work and my recommendation as well as some limitations, if any, of the study and recommended areas for further studies. 2.0 RELEVANT LITERATURE The estimation of the cost of equity for an industry involves estimation of what investors expect in return for their investment in that industry. That is, the cost of equity to an industry is equal to the expected return on investors equity holdings in that industry. There are however a host of models available for the estimation of expected returns on an industrys equity capital including but not limited to estimates from fundamentals (dividends and earnings) and those from asset pricing models. 2.1 Estimations from Fundamentals Estimation of expected returns or cost of equity in this case from fundamentals involves the use of dividends and earnings. Fama and French (2002) used this approach to estimate expected stock returns. They stated that, the expected return estimates from fundamentals help to judge whether the realised average return is high or low relative to the expected value (pp 1). The reasoning behind this approach lies in the fact that, the average stock return is the average dividend yield plus the average rate of capital gain: A(Rt) = A(Dt/Pt-1) + A(GPt) (1) where Dt is the dividend for year t, Pt-1 is the price at the end of year t 1, GPt = (Pt Pt-1)/Pt-1 is the rate of capital gain, and A( ) indicates an average value. Given in this situation that the dividend-price ratio, Dt/Pt , is stationary (mean reverting), an alternative estimate of the stock return from fundamentals is: A(RDt) = A(Dt/Pt-1) + A(GDt) (2) Where GDt = (Dt Dt-1)/Dt-1is the growth rate of dividends and (2) is known as the dividend growth model which can be viewed as the expected stock return estimate of the Gordon (1962) model. Equation (2) in theory will only apply to variables that are cointegrated with the stock price and may not hold if the dividend-price ratio is non-stationary, which may be caused by firms decision to return earnings to stockholders by moving away from dividends to share repurchases (Fama and French 2002). But assuming that the ratio of earnings to price, (Yt/Pt), is stationary, then an alternative estimate of the expected rate of capital gain will be the average growth rate of earnings, A(GYt) = A((Yt Yt-1)/Yt-1). In this case, the average dividend yield can be combined with the A(GYt) to produce a third method of estimating expected stock return, the earnings growth model given as: A(RYt) = A(Dt/Pt-1) + A(GYt) (3) It stands to reason from the model in Lettau and Ludvigson (2001) that the average growth rate of consumption can be an alternative mean of estimating the expected rate of capital gain if the ratio of consumption to stock market wealth is assumed stationary. Fama and French (2002) in their analysis concluded that the dividend growth model has an advantage over the earnings growth model and the average stock return if the goal is to estimate the long-term expected growth of wealth. However, it is a more generally known fact that, dividends are a policy variable and so subject to changes in management policy, which raises problems when using the dividend growth model to estimate the expected stock returns. But this may not be a problem in the long run if there is stability in dividend policies and dividend-price ratio resumes its mean-reversion (although the reversion may be at a new mean level). Bagwell and Shoven (1989) and Dunsby (1995) have observed that share repurchases after 1983 has been on the ascendancy, while Fama and French (2001) have also observed that the proportion of firms who do not pay dividends have been increasing steadily since 1978. The Fama and French (2001) observation implies that in transition periods where firms who do not pay dividends increases steadily, the market dividend-price ratio may be non-stationary; overtime, it is likely to decrease, in which case the expected return will likely be underestimated when the dividend growth model is used. The earnings growth model, although not superior to the dividend growth model (Fama and French (2002)), is not affected by possible changes in dividend policies over time. The earnings growth model however may also be affected by non-stationarity in earnings-price ratio since it ability to accurately estimate average expected return is based on the assumption that there are permanent shifts in the expected value of the earnings-price ratio. 2.2 Estimations from Asset-Pricing Models One of the most fundamental concepts in the area of asset-pricing is that of risk versus reward. The pioneering work that addressed the risk and reward trade-off was done by Sharpe (1964)-Lintner (1965), in their introduction of the Capital Asset Pricing Model (CAPM). The Capital Asset Pricing Model postulates that the cross-sectional variation in expected stock or portfolio returns is captured only by the market beta. However, evidence from past literature (Fama and French (1992), Carhart (1997), Strong and Xu (1997), Jagannathan and Wang (1996), Lettau and Ludvigson (2001), and others) stipulates that the cross-section of stock returns is not fully captured by the one factor market beta. Past and present literature including studies by Banz (1981), Rosenberg et al (1985), Basu (1983) and Lakonishok et al (1994) have established that, in addition to the market beta, average returns on stocks are influenced by size, book-to-market equity, earnings/price and past sales growth respecti vely. Past studies have also revealed that stock returns tend to display short-term momentum (Jegadeesh and Titman (1993)) and long-term reversals (DeBondt and Thaler (1985)). Growing research in this area by scholars to address these anomalies has led to the development of alternative models that better explain variations in stock returns. This led to the categorisation of asset pricing models into three: (1) multifactor models that add some factors to the market return, such as the Fama and French three factor model; (2) the arbitrage pricing theory postulated by Ross (1977) and (3) the nonparametric models that heavily criticized the linearity of the CAPM and therefore added moments, as evidenced in the work of Harvey and Siddique (2000) and Dittmar (2002). From this categorization, most of the asset-pricing models can be described as special cases of the four-factor model proposed by Carhart (1997). The four-factor model is given as: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]bi + si E(SMB) + hi E(HML) + wiE(WML) + ÃŽ µi (4) where SMB, HML and WML are proxies for size, book-to-market equity and momentum respectively. There exist other variants of these models such as the three-moment CAPM and the four-moment CAPM (Dittmar, 2002) which add skewness and kurtosis to investor preferences, however the focus of this paper is to compare and test the effectiveness of the CAPM and the Fama and French three-factor model, the two premier asset-pricing models widely acknowledged among both practitioners and academicians. 2.3 Theoretical Background: CAPM and Fama French Three-Factor Model There exist quite a substantial amount of studies in the field of finance relating to these two prominent asset pricing models. The Capital Asset Pricing Model (CAPM) of Sharpe (1964) and Lintner (1965) has been the first most widely recognized theoretical explanation for the estimation of expected stock returns or cost of equity in this case. It is a single factor model that is widely used by Financial Economists and in industry. The CAPM being the first theoretical asset pricing model to address the risk and return concept and due to its simplicity and ease of interpretation, was quickly embraced when it was first introduced. The models attractiveness also lies in the fact that, it addressed difficult problems related to asset pricing using readily available time series data. The CAPM is based on the idea of the relationship that exists between the risk of an asset and the expected return with beta being the sole risk pricing factor. The Sharpe-Lintner CAPM equation which describes individual asset return is given as: E(Ri) = Rf + [ E(RM) Rf ]ÃŽ ²iM i = 1,,N (5) where E(Ri) is the expected return on any asset i, Rf is the risk-free interest rate, E(RM) is the expected return on the value-weighted market portfolio, and ÃŽ ²iM is the assets market beta which measures the sensitivity of the assets return to variations in the market returns and it is equivalent to Cov(Ri, RM)/Var(RM). The equation for the time series regression can be written as: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]ÃŽ ²iM + ÃŽ µi i = 1,,N; (6) showing that the excess return on portfolio i is dependent on excess market return with ÃŽ µi as the error term. The excess market return is also referred to as the market premium. The model is based on several key assumptions, portraying a simplified world where: (1) there are no taxes or transaction costs or problems with indivisibilities of assets; (2) all investors have identical investment horizons; (3) all investors have identical opinions about expected returns, volatilities and correlations of available investments; (4) all assets have limited liability; (5) there exist sufficiently large number of investors with comparable wealth levels so that each investor believes that he/she can purchase and sell any amount of an asset as he or she deems fit in the market; (6) the capital market is in equilibrium; and (7) Trading in assets takes place continually over time. The merits of these assumptions have been discussed extensively in literature. It is evident that most of these assumptions are the standard assumptions of a perfect market which does not exist in reality. It is a known fact that, in reality, indivisibilities and transaction costs do exist and one of the reasons assigned to the assumption of continual trading models is to implicitly give recognition to these costs. It is imperative to note however that, trading intervals are stochastic and of non-constant length and so making it unsatisfactory to assume no trading cost. As mentioned earlier, the assumptions made the model very simple to estimate (given a proxy for the market factor) and interpret, thus making it very attractive and this explains why it was easily embraced. The CAPM stipulates that, investors are only rewarded for the systematic or non-diversifiable risk (represented by beta) they bear in holding a portfolio of assets. Notwithstanding the models simplicity in estimation and interpretation, it has been criticized heavily over the past few decades . Due to its many unrealistic assumptions and simple nature, academicians almost immediately began testing the implications of the CAPM. Studies by Black, Jensen and Scholes (1972) and Fama and MacBeth (1973) gave the first strong empirical support to the use of the model for determining the cost of capital. Black et al. (1972) in combining all the NYSE stocks into portfolio and using data between the periods of 1931 to 1965 found that the data are consistent with the predictions of the Capital Asset Pricing Model (CAPM). Using return data for NYSE stocks for the period between 1926 to 1968, Fama and MacBeth (1973) in examining whether other stock characteristics such as beta squared and idiosyncratic volatility of returns in addition to their betas would help in explaining the cross section of stock returns better found that knowledge of beta was sufficient. There have however been several academic challenges to the validity of the model in relation to its practical application. Banz (1981) revealed the first major challenge to the model when he provided empirical evidence to show that stocks of smaller firms earned better returns than predicted by the CAPM. Banzs finding was not deemed economically important by most academicians in the light that, it is unreasonable to expect an abstract model such as the CAPM to hold exactly and that the proportion of small firms to total market capital is insignificant (under 5%). Other early empirical works by Blume and friend (1973), Basu (1977), Reinganum (1981), Gibbons (1982), Stambaugh (1982) and shanken (1985) could not offer any significant evidence in support of the CAPM. In their paper, Fama and French (2004) noted that in regressing a cross section of average portfolio returns on portfolio beta estimates, the CAPM would predict an intercept which is equal to the risk free rate (Rf) and a beta coefficient equal to the market risk premium (E(Rm) Rf). However, Black, Jensen and Scholes (1972), Blume and Friend (1973), Fama and MacBeth (1973) and Fama and French (1992) after running series of cross-sectional regressions found that the average risk-free rate, which is proxied by the one month T-bill, was always less that the realised intercept. Theory stipulates that, the three main components of the model (the risk free, beta and the market risk premium) must be forward-looking estimates. That is they must be estimates of their true future values. Empirical studies and survey results however show substantial disagreements as to how these components can be estimated. While most empirical researches use the one month T-bill rate as a proxy to the risk-fr ee rate, interviews depicts that practitioners prefer to use either the 90-day T-bill or a 10-year T-bond (normally characterised by a flat yield curve). Survey results have revealed that practitioners have a strong preference for long-term bond yields with over 70% of financial advisors and corporations using Treasury-bond yields with maturities of ten 10 or more years. However, many corporations reveal that they match the tenor of the investment to the term of the risk free rate. Finance theory postulates that the estimated beta should be forward looking, so as to reflect investors uncertainty about future cash flows to equity. Practitioners are forced to use various kinds of proxies since forward-looking betas are unobservable. It is therefore a common practice to use beta estimates derived from historical data which are normally retrieved from Bloomberg, Standard Poors and Value Line. However, the lack of consensus as to which of these three to use results in different betas for the same company. These differences in beta estimates could result in significantly different expected future returns or cost of equity for the company in question thereby yielding conflicting financial decisions especially in capital budgeting. In the work of Bruner et al. (1998), they found significant differences in beta estimates for a small sample of stocks, with Bloomberg providing a figure of 1.03 while Value Line beta was 1.24. The use of historical data however requires th at one makes some practical compromises, each of which can adversely affect the quality of the results. Forinstance, the statistically reliability of the estimate may improve greatly by employing longer time series periods but this may include information that are stale or irrelevant. Empirical research over the years has shown that the precision of the beta estimates using the CAPM is greatly improved when working with well diversified portfolios compared to individual securities. In relation to the equity risk premium, finance theory postulates that, the market premium should be equal to the difference between investors expected returns on the market portfolio and the risk-free rate. Most practitioners have to grapple with the problem of how to measure the market risk premium. Survey results have revealed that the equity market premium prompted the greatest diversity of responses among survey respondents. Since future expected returns are unobservable, most of the survey participants extrapolated historical returns in the future on the assumption that future expectations are heavily influenced by past experience. The survey participants however differed in their estimation of the average historical equity returns as well as their choice of proxy for the riskless asset. Some respondents preferred the geometric average historical equity returns to the arithmetic one while some also prefer the T-bonds to the T-bill as a proxy for the riskless asset. Despite the numerous academic literatures which discuss how the CAPM should be implemented, there is no consensus in relation to the time frame and the data frequency that should be used for estimation. Bartholdy Peare (2005) in their paper concluded that, for estimation of beta, five years of monthly data is the appropriate time period and data frequency. They also found that an equal weighted index, as opposed to the commonly recommended value-weighted index provides a better estimate. Their findings also revealed that it does not really matter whether dividends are included in the index or not or whether raw returns or excess returns are used in the regression equation. The CAPM has over the years been said to have failed greatly in explaining accurate expected returns and this some researchers have attributed to its many unrealistic assumptions. One other major assumption of the CAPM is that there exists complete knowledge of the true market portfolios composition or index to be used. This assumed index is to consist of all the assets in the world. However since only a small fraction of all assets in the world are traded on stock exchanges, it is impossible to construct such an index leading to the use of proxies such as the SP500, resulting in ambiguities in tests. The greatest challenge to the CAPM aside that of Banz (1981) came from Fama and French (1992). Using similar procedures as Fama and MacBeth (1973) and ten size classes and ten beta classes, Fama and French (1992) found that the cross section of average returns on stocks for the periods spanning 1960s to 1990 for US stocks is not fully explained by the CAPM beta and that stock risks are multidimensional. Their regression analysis suggest that company size and book-to-market equity ratio do perform better than beta in capturing cross-sectional variation in the cost of equity capital across firms. Their work was however preceded by Stattman (1980) who was the first to document a positive relation between book-to-market ratios and US stock returns. The findings of Fama and French could however not be dismissed as being economically insignificant as in the case of Banz. Fama and French therefore in 1993 identified a model with three common risk factors in the stock return- an overall market factor, factors related to firm size (SMB) and those related to book-to-market equity (HML), as an alternative to the CAPM. The SMB factor is computed as the average return on three small portfolios (small cap portfolios) less the average return on three big portfolios (large cap portfolios). The HML factor on the other hand is computed as the average return on two value portfolios less the average return on two growth portfolios. The growth portfolio represents stocks with low Book Equity to Market Equity ratio (BE/ME) while the value portfolios represent stocks with high BE/ME ratio. Their three-factor model equation is described as follows: E(Ri) Rf = ÃŽ ±i + [ E(RM) Rf ]bi + si E(SMB) + hi E(HML) + ÃŽ µi (7) Where E(RM) Rf, , E(SMB) and E(HML) are the factor risk premiums and bi , si and hi are the factor sensitivities. It is however believed that the introduction of these two additional factors was motivated by the works of Stattman (1980) and Banz (1981). The effectiveness of these two models in capturing variations in stock returns may be judged by the intercept (alpha) in equations (6) and (7) above. Theory postulates that if these models hold, then the value of the intercept or alpha must equal zero for all assets or portfolio of assets. Fama and French (1997) tested the ability of both the CAPM and their own three-factor model in estimating industry costs of equity. Their test considered 48 industries in which they found that their model outperformed the CAPM across all the industries considered. They however could not conclude that their model was better since their estimates of industry cost of equities were observed to be imprecise. Another disturbing outcome of their study is that both models displayed very large standard errors in the order of 3.0% per annum across all industries. Connor and Senghal (2001) tested the effectiveness of these two models in predicting portfolio returns in indias stock market. They tested the models using 6 portfolio groupings formed from the intersection of two size and three book-to-market equity by examining and testing their intercepts. Connor and Senghal in this paper examined the values of the intercepts and their corresponding t-statistics and then tested the intercepts simultaneously by using the GRS statistic first introduced by Gibbons, Ross and Shanken (1989). Based on the evidence provided by the intercepts and the GRS tests, Connor and Senghal concluded generally that the three-factor model of Fama and French was superior to the CAPM. There have been other several empirical papers ever since, to ascertain which of these models is better in the estimation of expected return or cost of equity, most producing contrasting results. Howard Qi (2004) concluded in his work that on the aggregate level, the two models behave fairly well in their predictive power but the CAPM appeared to be slightly better. Bartholdy and Peare (2002) in their work came to the conclusion that both models performed poorly with the CAPM being the poorest. 3.0 DATA SOURCES T