Video game literature review Essay Example for Free

Video game literature review Essay Violent video games are said to have a negative effect on those who play them, but there is also the debate that violent video games help those who play them rather than hurt them. There is a rating system that separates games into groups from games for everyone all the way to games that can only be bought if youre eighteen and older. The main questions with this rating system seem to be, Where do we draw the line, and Who draws the line? All to often younger teens get their hands on the video games that are made for the eighteen and older crowd, but will the game actually have a negative effect on the teen, or will it help the teen by allowing them to vent some anger or make them feel good about themselves because they solved a difficult puzzle within the game. As you may have seen there are many contrasting viewpoints, but before we explore the contrasting views on violent video games, we should try to understand our own views, and those of others who take positions that are different from ours, by reviewing some key insights. First we can start with the insights of a few different people who dont think violent video games are bad for teens. From there we can move to a couple of pieces that think violent video games are bad. To finish we will look at an article doesnt take a stance either way, but does provide some very good facts. Greg Costikyan, also known as Designer X, is an American game designer and science fiction writer. Costikyans career spans nearly all genres of gaming, including hex-based war games, role-playing games, board games, card games, computer games, online games and mobile games. Several of his games have won Awards. In Costikyans argument, The Problem of Video Game Violence is Exaggerated, he tackles violence in video games from many different angles such as video game advertising, the successful way to incorporate violence into video games, how violence is part of human nature, and the ignorance of the opposing viewpoint. When reading the argument it is easy to see that Costikyans viewpoint is biased, but he does a good job of stating the opposition and then shooting it down with his own research, and he does not avoid certain questions just to prove his point. I think that Costikyan makes his best argument when he talks about the artistic use of violence in video games. He says that when people play video games they develop a rhythm, but when violence is thrown in it creates a dissonance which breaks the players rhythm, which in turn makes the game that much more of a challenge. Costikyan sums it up best when he says, Violence used artistically is effective; violence used crudely is vile. Tom Kalinske is the former president and CEO of Sega America, Inc. , and now works for Educational Technology, LLC. In Kalinkses speech, Video Games do not Cause Aggressive Behavior in Children, he makes some very good points on why people might think that video games are bad. Kalinske poses a very good point in his speech where he says, Parents and educators who look casually at boys playing out fighting games are quick to condemn because the content of the games mirrors real societal problems. But to jump to the conclusion that game content leads to really inappropriate behavior is like speculating that students studying the Napoleonic Wars may lay siege to their neighborhood. Kalinske argues that parents fear technology because they have less of an understanding of it than their children, and those who think that kids will emulate the violence seen within the video games that they play have a very pessimistic view of kids. Kalinske also makes a very good argument about how video games can improve academic performance. He says that beating a video game takes more than good hand-eye coordination. It takes good puzzle solving, critical thinking, deductive reasoning, and problem solving skills, which all happen to be key skills for academic success. I think that Kalinske has many good points in his speech that will help me in writing my paper. David Deutsch is a physicist at the University of Oxford. He is a Visiting Professor in the Department of Atomic and Laser Physics at the Centre for Quantum Computation, Clarendon Laboratory. He pioneered the field of quantum computers, and is a proponent of the many-worlds interpretation of quantum mechanics. In Deutschs interview he talks about how video games are beneficial to children, because it gives children a different and unique learning environment. Deutsch says that all the evidence that video games are bad boils down to the fact that children like them, and prima facie video games are bad. He suggests that if children like doing something so much, such as playing video games, then we should find ways to make it better and allow them to do more of it. Deutsch make a very good argument when he compares playing video games to playing the piano or playing chess. He says that all three take a lot of time to master, some more that others, and if a child is seen playing chess for long periods of time he is considered a genius, but if a child is seen playing video games for long periods of times he is stigmatized. This doesnt make sense, because all three are done for the same reason which is the impulse to understand things. Deutsch also argues the addiction to video games very well by saying that the reason why people choose to play video games so much is because the games make you engage you emotions as well as your intellect. He also gave this as a very good example, I remember once, I came back to playing the Piano after a long time, and I ended up with blood all over the keys. I saw that I had a cut, but I did not want to stop, so I carried on playing. If that had been a video game and I had been younger, people would have used that as evidence of addiction. Kevin Saunders is currently a professor at Michigan State University and is the author of two books, Violence as Obscenity: Limiting the Medias First Amendment Protection and Saving Our Children from the First Amendment. He has authored dozens of book chapters, law review articles, and commentaries in legal and popular periodicals. He also teaches a variety of courses and seminars on topics in Constitutional Law. In this article Saunders establishes a good topic for debate when he says that fps (first-person shooter) games create a realistic adaptation of an actual gun fight to whereas the armed forces and law enforcement agencies use fps games to train their soldiers. He then gives us a couple of examples of what these violent games can make teens do in real life. The first example is about Michael Carneal, a fourteen-year-old freshman who enjoyed playing the popular fps Doom. One morning Michael showed up at school with a stolen pistol and open fired on a group of kids. He killed three and injured eight. The second example is about Eric Harris and Dylan Klebold the two students who showed up at Columbine High School heavily armed and killed one teacher, twelve students, and injured twenty-three others. They too were avid players of the game Doom. These are both prime examples of what violent video games can do to teens. Eugene F. Provenzo, Jr. is a professor in the Department of Teaching and Learning at the University of Miami. Provenzos academic interests include the role of the teacher in American society, and the influence of computers and video games on children. His work has been reviewed in American and British media, including ABC World News Tonight, The Economist, and The New York Times. In this article Provenzo says he believes that real life simulators, such as video games, are taking kids out of the real world and teaching them about violence, and how to be violent. He argues that when teens play an fps (first-person shooter) game they virtually put themselves into an emotionless killing machine and by doing this they are behaviorally reinforced as they play the game thus being taught that its ok to shoot people. Provenzo makes a great comparison when he compares playing an fps and playing a game of paintball. He says that they are two different things because while playing paintball you can get tired and wounded, and there are serious consequences for getting out of control. When playing an fps there are no limits, players are not responsible for what they do, and there are no consequences for anybody. I think that Provenzo makes a great point when he says, Video and computer games are, in fact, highly effective teaching machines. You learn the rules, play the game, get better at it, accumulate a higher score, and eventually win. This next article is titled Video Games and Violence and it was taken from Issues and Controversies at facts. com database. The article covers both sides of the argument. It says that supporters of the legislation against violent video games say that violent video games make kids more acclimated to violence, and that violent video games cause an increase in violence within the kids. Critics of the legislation against violent video games say that our current rating system for video games is working and that video games should be protected as free speech. Within this article are some very good statistics one of which being in the year 2000 85% of minors sent to buy a video game rated M (M for Mature) were successful. Sometime after that study stores started to enforce an ID rule for M rated video games, and in the year 2003 the percentage of minors able to purchase M rated video games fell to 69%. Another good statistic within the article is that in the year 2003 out of all the video games purchased only 11. 9% were M rated games. The biggest percentage of games being bought were rated E (E for Everyone) with 54%, and in second were T (T for Teen) rated games with 30. 5%. This article brings up a very good point when it says that parenting is a big part of regulation in what youth under the age of eighteen watch and do. The video game rating system was originally put in place for parents to be able to judge what their children should be playing and to have an idea of what would be in the game that their children were playing. As you can see, with the information provided, there are many valid points around this debate. While reading Saunders and Provenzo I noticed that both of them brought up the Columbine school shooting which is a very emotional subject for some people. Kalinske and Deutsch both portray the general argument that video games can help educate teens, and video games could be a very powerful educational tool, if used correctly. All of these sources have helped me a lot in understanding more about the effects of violent video games on teens. Before my research I was not sure if I was for or against changing the rating system for video games, but now, with all this information, I will be arguing against creating a more strict rating system for video games. Works Cited Costikyan, Greg. The Problem of Video Game Violence Is Exaggerated. Video Games (2003) 25 Jan. 2007 . Deutsch, David. Playing Video Games Benefits Children. Video Games: Harmfully Addictive or a Unique Educational Environment? (1992) 02 Feb. 2007 . Kalinske, Tom. Video Games Do Not Cause Aggressive Behavior in Children. Violent children (2000) 02 Feb. 2007 . Provenzo, Eugene. Violence in Video Games Is a Serious Problem. Is Media Violence a Problem? (2002) 02 Feb. 2007 . Saunders, Kevin. Censorship Should Be Used for the Protection of Children. Censorship (2005) 05 Feb. 2007 . Video games and violence. Facts. com. (2007). Issues and Controversies. 25 Jan. 2007.

Themes In A Farewell To Arms :: essays research papers

A Farewell To Arms: Themes   Ã‚  Ã‚  Ã‚  Ã‚  There are three major themes in Hemingway’s A Farewell to Arms. The first themeis enduring love ended only by mortality. The second, the effects of war on a man’s ideals and morals, things which people can and do believe during war. The last and most important theme is Frederic Henry’s disillusionment.   Ã‚  Ã‚  Ã‚  Ã‚  Hemingway shows that love can persevere in a world ruined with war. Frederic is not looking for love, and when Rinaldi introduces him to Catherine Barkley, he thinks of her as merely a sexual conquest. Henry considers his flirting with Catherine â€Å"like moves in a chess game.†. Henry thinks Catherine is a little bit crazy, and both admit they are acting. At the front, Henry realizes he is lonely without her and misses her. But it is not until he meets her, after he is wounded and sent to an American hospital, that he realizes he loves her. Henry admits he didn’t want to fall in love with her, but even so he has. Their love continues to grow during his stay at the hospital. Their relationship is unusual since they rarely argue. Their ideal relationship provides them with refuge from the war. However, love, has it’s limit, mortality. Henry leaves for the front again he suggests that their romance is only ended by death. He notices because of his love he has become gentle. When he deserts and returns to Catherine he finds comfort, order, and courage. He says, foreshadowing the end of their love, â€Å"If people bring so much courage to this world the world has to kill them to break them, so of course it kills them.†. Henry has become dependent on Catherine. His love for her is strong enough to ease his disillusionment In Chapter 41 their baby is born dead. Henry hopelessly watches as Catherine dies and he is left without comfort or hope.   Ã‚  Ã‚  Ã‚  Ã‚  Henry’s ideals and morals change during the novel. He begins to question the legal and immoral theories of the war and replace them with illegal but moral ideas. For instance, in Chapter 7 Henry meets a soldier who wants to be taken to a hospital which is against the rules. At first Henry objects, but when the soldier asks him â€Å"You wouldn’t want to go in the line all the time, would you?†, he answers no and decides to return later and pick him up. Henry has been unable to find new morals, since he has lost faith in what the leaders proclaim. Another example is the Romantic ideology of the time, the belief

How Have Our Ideas of Heroes Changed over Time Essay

In the beginning of cinema heroes and heroines tended to stay within the mythic structure of heroes using binary pairs of opposite terms to simplify the complexity of events and reducing the players down to good guys and bad guys or more cinematic, white hats and black hats. That changed radically in the late 1960’s and early ’70’s when a series of films such as Butch Cassidy and the Sundance Kid, Bonnie and Clyde, The Godfather, Midnight Cowboy and One flew Over the Cuckoo’s Nest, literally turned mythic structure on its head and presented the cinematic anti-hero. Before this golden age of film an audience could rely on the belief that no matter how complicated events got for the hero in the end the hero would prevail and the villain would be brought to justice. Butch Cassidy and the Sundance Kid asks its audience to redefine justice in order to root for our heroes who are in fact the villains and hiss the villains who are in fact the good guys. Bonnie and Clyde does the same, the Godfather does it so well that films influence is noticeable in prevailing attitudes about justice today. Midnight Cowboy and One flew Over the Cuckoo’s Nest don’t necessarily offer up villains as heroes, but our heroes are so flawed, so aimless in their pursuit that even if in the end they are brought down by their own hubris they are still weaker, less competent versions of the mythic hero who rather than ask there audience to be inspired by greatness they ask their audience to celebrate rebelliousness for the sake of rebellion and immorality as an acceptable form of happiness. The radical changes that took place in the films of the seventies still has heavy influence in film making and particularly in film criticism today. There are still and will always be plenty of films made that remain true to classical mythic structure where white hats prevail and black hats do not. Current examples of such mythic structure can be found in films such as Live Free Die Hard, Casino Royale, Mission Impossible, and almost any Harrison Ford film. In these films, no matter how complicated things get the white hats always prevail the black hats lose. These films do not do well with the film critics that find employment in the media. It’s not that critics don’t like action films as most heaped plenty of praise on such films as Children of Men, Pans Labyrinth, 3:10 to Yuma and I am Legend. The difference between these movies and the action films such as Live Free Die Hard or any Harrison Ford Film is that Harrison Fords heroes always live and in the films praised by critics the heroes always died. I am skeptical that Braveheart would have actually won the Oscar for best picture if William Wallace lived. This is the primary and perhaps the most important change in the depiction of heroes and heroines over the years in film. The abandonment of classical mythic structure in exchange for â€Å"realism† where â€Å"rational ideas† become notions that heroes aren’t heroes unless they die fighting the good fight and villains aren’t so bad once you really get to know them.

A Look At Capital Asset Pricing Model Finance Essay - Free Essay Example

Sample details Pages: 10 Words: 2905 Downloads: 4 Date added: 2017/06/26 Category Finance Essay Type Compare and contrast essay Did you like this example? The Capital Asset Pricing Model (CAPM) has been invented by Sharpe (1964), and Lintner (1965) after the work of Markowitzs in 1959. Since then the model has known tremendous success, its simplicity has lured many professionals and academics as well. Despite many criticisms, the CAPM is still used in modern finance and is widely present in finance textbooks. Don’t waste time! Our writers will create an original "A Look At Capital Asset Pricing Model Finance Essay" essay for you Create order On the other hand we have the Arbitrage Pricing Theory (APT), a less restricted model when compared to the CAPM, but with its own limitations as well. The APT, invented by Ross in 1976, tries to capture the non-market influences that are responsible in making assets to move in tandem. Both models are definitely different in some aspects, and therefore their effectiveness differs. In the literature we find many studies around the two models where some even tried to compare between the two, this chapter aims at reviewing those studies that have described and tested the models as well as introducing the Stock Exchange of Mauritius. The motivation behind this study is to find out which of the models is the most appropriate to predict return in relation to the risks. Moreover little study has been done about them and no research has been carried out yet to find out which of the two is more effective. The financial environment prevailing in Mauritius is juvenile, despite rapid growth in th e industry it is still small yet well regulated when compared to other countries financial markets. There is a gap in the literature as no comparison between the two models has been made for Mauritius! introduction to the Stock Exchange of Mauritius: The Stock Exchange of Mauritius (SEM) was established in the year 1989 under the Stock Exchange Act 1988. There are two markets under the SEM namely Official List (for listed companies) and Over-the-Counter market (for unlisted companies). There are three market indices namely SEMDEX, SEMTRI, and SEM-7. The size of the SEM is rather small compared to others worldwide and the market capitalization to date is USD 1.4 billion  [1] Review of the theoretical literature: The CAPM, underpinning theory in finance among academics and practitioners in the industry, has had a history full of supportive research and contradictive findings. The theory itself was developed by, Sharpe (1964), and Lintner (1965), following the work of Markowitz on portfolio theory in 1959. Basically CAPM states an investor has the choice of exposing himself to a considerable amount of risk through a combination of lending-borrowing and a correctly composed portfolio of risky securities (Petros, 2012, p2). Moreover it is said that higher risk, which is known as the beta (ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²), is associated with higher level of returns. In more technical terms we can say that the expected return on an asset above the risk-free rate is linearly related to the non-diversifiable risk (market risk) as measured by the assets beta. Despite many criticisms surrounding this theory, the CAPM is still a widely used theory because of its simplicity and is one of the most important chapter s in portfolio theory. Moreover, it is still the centrepiece of many investment and financial market courses (Choudhary and Choudhary, 2006, p2). The CAPM is an intuitive model and that is why managers still use it in justifying investments despite 30 years of critics over its assumptions and usefulness. Equation of the CAPM: a = rf + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²a (m rf ) Where: rf is the risk free rate, ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²a is the beta of the security, m is the expected market return. According to the CAPM, if the market is efficient, the risk premium and the expected return on an asset will vary in direct proportion to the beta value. The beta factor or beta value designates the marginal contribution of the share to the risk of the whole market portfolio or risky securities. The assumptions underlying the CAPM:  There are many investors who are all price takers. All investors plan to invest over the same horizon. There are no taxes or transaction costs. Investors can borrow and lend at the same risk-free rate over the planned investment horizon. Investors only care about expected return and variance. All investors have the same information and beliefs about the distribution of returns. 7. The market portfolio consists of all publicly traded assets. Though the CAPM is popular, it has had many critics in the literature, indeed the very attractive feature of the model, namely its simplicity, sometimes poses problem. As such CAPM has proved to be unreliable in some cases, indeed in Greece CAPM proved to be a weak model to predict return as the findings show that higher beta is not necessarily associated with higher level of return. Nevertheless it does explain excess return and therefore it has its usefulness. (Michailidis et al, 2006). It is stated that there is a need fo r a more complicated model and the assumptions on which the theory is based are often unrealistic (Fama and French, 2004). This is because it is not conceivable to think that investors care only about the mean-variance of one-period portfolio returns, other dimensions of risks need to be considered, for example labour income and future investment opportunities that the variance miss out. Adding to this Roll (1977) mentioned that having the market portfolio at the heart of the model is theoretically and empirically elusive and the data required are sometimes difficult to obtain, thus encouraging the use of proxies and not the true market portfolios and therefore weakens the theory in a sense. Yu (2003) mentioned that from the research he has carried out, he found that the relationship between risk and return is non linear, also he found that asset return can be predicted using other factors as well. Moreover, research in the late 1970s has revealed that there are other factors which are also important. Indeed we have variables like size, various price ratios and momentum that add to the explanation of average returns provided by beta. Such problems are enough to invalidate the CAPM. (Fama and French, 2004). Therefore on this note we can already conclude that there are factors which have better prediction power, this was mentioned by Fama and French (1996) whereby it is said that accounting ratios and size of the firm can even do better than the CAPM (Petros, 2012, p2). Critics do not stop here, indeed Roll (1977) said that the market in the theory of CAPM is not about a single equity market, but rather an index of all wealth. Thus bonds, property, foreign assets, human capital and any tangibles or intangibles that increase the wealth of people should be inclusive of the market. (Petros, 2012, p7) Therefore it is found that CAPM might be very popular and surprisingly still in use, a need for a different and less restrictive model was needed in order to provide a more realistic prediction. This fact has created a need for a better model, or at least a model that can get over the limitations of CAPM, and there was invented the Arbitrage Pricing Theory (APT), a model that has more factor loadings and which has no restriction on the variables to be taken into account. The APT was developed by Ross in the year 1976 and as a multi factor model it has had quite some success. It is known to be a one-period model for which there is prevention of arbitrage over static portfolios of the assets being taken into consideration thus leading to a linear relationship between the expected return and its covariance with the factors. It can be said that the theory provides arbitrage-free pricing to existing assets. (Huberman and Wang, 2005) The APT has the feature of capturing the non-market influences which are responsible for making assets to move in tandem. Thus idiosyncratic factors that affect returns can be diversified away. Therefore under APT the i nvestors are supposed to be rewarded only for the systematic risks they are undertaking, that is risks that cannot be diversified away. Being a multifactor model, the APT has the power to include several factors that influence return, and hence it is considered to be a more precise model for evaluating expected return over given risks. The factors used under the APT are diverse, though no guidance is given in the literature to which factors to be used, statistical techniques are available to pick the right factor and plug into the model. The equation of the APT is not restricted in terms of variables all the factors that have an impact on return can be included in the model. Here is the equation for the APT: Expected Return = rf + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1 (factor 1) + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2 (factor 2) + + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²n (factor n) Where: rf = the risk free interest rate, which is the interest rate the investor would expect to receive from a risk-free investment. ÃÆ'Ã… ½  ² = the sensitivity of the stock or security to each factor. factor = the risk premium associated with each factor. The problem with APT is that it lacks theoretical support for the factor loadings to be used. The freedom of choosing the factors to be included in the model does provide flexibility and improve accuracy. However there is the danger of picking the wrong factors or missing the right ones, therefore proper statistical methods need to be applied in order to include only all those factors that have an impact on returns. Azeez and Yonoezawa (2003) reiterated this fact by pointing out that no theoretical guidance is provided for the right economic influences that need to be plugged into the model. (Paavola, 2006, p9) Usually the statistical methods used are Principle Component Analysis and Factor Analysis, these two seems to provide the most accurate way of picking the right factors. Before comparing the two models in any country, it is important to know the differences first. Indeed there is a growing literature that tends to favour APT over CAPM because of the restrictive nature of the latter. As such, the APT being a multiple factor model allows multiple sources of systematic risks to be taken into account, performs better than the CAPM. (Paavola, 2006) However CAPM has not been retired from the financial world and is still in use, along with its other variants (example: ICAPM). The differences between the CAPM and the APT are as follows: The CAPM is more about how investors construct efficient portfolios and is derived from the mean variance analysis, whereas, as mentioned by Brealey et al. (2008), the APT assumes that equitys return depend on macroeconomic factors and partly on noise (Paavola, 2006, p3). Unlike the CAPM, the APT is less restrictive in its assumption and therefore allows for an explanatory model of asset return. For the CAPM we have only the market index whereas for APT we assume that the investor will be holding a unique portfolio with its own set of betas. With APT it is possible to make predictions using a proxy for the market, whereas with CAPM this is not possible. Nevertheless, despite the differences between the two theories, APT can still be a substitute to CAPM. As a matter of fact, both agree that there is a linear relationship between the expected return of the assets and their covariance, which is a measure of risks that investors cannot avoid, with other variables. Still the two models have a few differences, but it is the potency of the model that is most important and so far the literature has been more lenient to APT than CAPM. There is definitely a conflict between simplicity and accuracy, the use of either model will depend on the context and the availability of information. But the methodology that is typical to the two also matters, some information (such as factor loadings) need to be extracted or estimated, and the methods of estimation might sometime r aise doubts over the precision of the model. Review of the empirical literature: The early empirical tests on the CAPM usually were based upon certain implications, indeed we note that expected returns on all assets are linearly related to their betas, and no other variable has marginal explanatory power. Moreover beta premium is positive implying that the expected return on market portfolio is higher than the expected return on assets whose returns are not correlated with the market return minus the risk free rate. All of these implications are hinting towards the fact that these tests were carried out using regressions. Either it was cross-section or time series regressions (Fama and French,2004). To test CAPM, either individual assets can be used, or these assets can be grouped as portfolios. This was done by Black, Jensen and Scholes (1972), they decided to group the stocks of the New York Stock Exchange (NYSE) into portfolios within a time frame of 34 years (1931 to 1965). From that the results were that high beta intercepts tend to be negative, unlike a l ow beta intercept which tend to be positive (Choudhary and Choudhary, 2006, p2). Other studies have used similar methodology, as such Choudhary and Choudhary (2006) who followed the suggested methodology of Black et al (1972) and went to fetch the closing prices of some 278 companies from the BSR 500 index and as market portfolio, the monthly closing values of the BSE Sensex Index were used to measure risk free return, the yield on 91-days treasury bills of the Government of India was taken. The study covered the period from January 1996 to December 2009, here again we have a portfolio formation process starting with the period 1996-98 that was used to estimate the beta of the individual securities and ranked them by beta and construct 1 to 20 portfolios. The beta was estimated using the monthly return, the stock monthly return was regressed against the chosen market index, and as mentioned above the 278 were grouped into portfolios of 20. This was done in order to eliminate firm -specific part of returns, thus improving the precision of the estimates of the beta and the expected rate of return of the portfolios. The conclusion was such that it voided the basic hypothesis of the theory (higher beta yield to higher returns), and the prediction that the intercept to be equal to zero and that the slope should be equal to the excess returns on the market portfolio was contradicted. However the linear structure of the CAPM as a good explanation of security returns was confirmed. Similar methodology was used by Petros (2006) and again the basic hypothesis of CAPM was inconsistent with the findings. Moreover the linear relationship between expected return and beta was again confirmed. Thus it can be found that using the CAPM to make predictions about return is not the best choice. According to Roll (1997) such time-series and cross-section regressions do not really test the CAPM, what is rather tested is whether or not a specific proxy for the market portfolio i s efficient in the set of portfolios that can be constructed from it. Adding to this, there might be problem fetching data, because the data for true market portfolio of all assets are likely beyond reach (Fama and French, 2004). Critics about CAPM do not stop here, in the literature we have Basu (1977), Banz (1981), Bhandari (1988) , Statman (1980), and Rosenberg et al (1985), who used ratios, to be more precise, they used Earnings per Share, Market Capitalization, Debt-equity ratios and Book-to-Market ratios respectively. All of these different ratios proved to perform better than the CAPM, and further reiterated by Fama and French (1992) and Fama and French (1993) that ratios perform better where regression has failed to provide reliable answers (Fama and French, 2004, p12,13). The APT on the other hand, has a particular problem, and that is the choice of factor loadings in the model. This theory was tested in several economies around the world however the method of estimat ion of the factors to be used is rather common, that is PCA and Factor Analysis. The factors that are used in the APT should have particular characteristics, as mentioned by Berry et al (1988), three properties are required namely, at the beginning of every period the factor should not be predictable to the market. Secondly it is important that each factor has its importance in the stock market, and finally, each factor should influence expected return, therefore they must have non-zero prices. Roll and Ross (1980) and Lehmann and Modest (1988) both have put more emphasis on the first property (Gagnetti, 2006) Factor analysis was first proposed by Gehr (1978) and Roll and Ross (1980) as a technique to estimate the common factors and factor loadings of security returns at the same time. Nevertheless, Chen et al (1986) instead tried macroeconomic variables to explain asset returns (Gagnetti, 2006). Groesnewold and Fraser (1997) also worked with macroeconomic variables that affec t share returns based on a general hypothesis. But Cheng (1995) did an even more interesting work by performing a factor analysis of both a sample of securities and of the most important categories of macroeconomic variable and later used canonical correlation techniques to compare the two. Testing the APT usually involves time series data to estimate factor loadings for each asset, and the regress the sample mean returns on the factor loadings using a cross-section regression. This method of finding for the required factors substitute the arbitrary and controversial method of trial and error and provides a more scientific way of picking the right factors that is required for the model according to the context it is being used. Gagnetti (2006) has used the same common methodology, as such PCA was used to find the factors required and the software SPSS 8.0 was used to determine the number of factors needed. The result was that 8 factors were selected and the testing concluded that APT is a more robust model than the CAPM, as it was a comparison between the two models.