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The Rule of Four Discussion

The Rule of Four Discussion.

The U.S. Supreme Court receives around 7,000+ appeals each year, the majority of which are disposed of when the Court decides not to hear the case because of the subject matter, or if the issues presented are not significant enough to merit court review. The decision to hear a case is made when the justices meet to review all of the 7,000+ appeals. In order for all the justices to hear an appeal, the case must pass a screening known as the “Rule of Four.” This means that at least four of the nine justices must agree that the case has constitution merit or presents issues of national importance. If a case receives four or more votes from the justices, it is placed on the docket and scheduled to be heard. Annually, only about 100 or so cases pass the “Rule of Four” and are placed on the docket for an opinion.Discuss the following (2 or more paragraphs):(a) Should the rule be changed?(b) Should the U.S. Supreme Court hear more cases considering the 7,000+ appeals they receive and why?…. perhaps a Rule of Two or even a Rule of One?Discuss the possible implications of keeping the Rule of Four as it is or extending the rule to include more cases.
The Rule of Four Discussion

According to the Findings the most pure, beneficial and the most powerful biggest industry in the world is Textile industry. In today world of business it is working as a back bone of the countries. An estimated figure of the industry market is $400 billion and there are more chances of growth in the coming years, according to the saying in 2001of the research analyst that textile industry will grow 25% in 2002 to 2010 and there figure was true and in 2010 the figure accumulates to $480 billion and in the coming few years it will further grow. Toady, every country is putting his hands in this business and trying to give his best. Britain was the first country who just gave a new life to the textile industry by making machinery for the textile industry and the slowly it spread over the whole market of the world. Global Economy By Global economy means economy of all the countries. Because, international economy is the name when the economy of all countries comes together. There are factors which makes international economy which are, trade, investment, economical alliance of the countries and migration. The economy of a country can be measured by his GDP. According to the economists monetary values f any country whether it is USA by itself all the economies could only be measured by preferably through dollar. “Global economy could be affected by different factors which includes Currency Value, Trade Restriction, Political Situations, and labor cost, etc. “J.P. Morgan (Global Data watch) There are countries who contributes in a huge /wide range to the global economy Countries contribution to the global economy: First thing through which all the countries of the world contribute to the global economy is Politics because though politics here are many things which came into existence in the form of contribution to the global economy. Secondly, trade is most appropriate and unique way of contribution in the global economy. There are so many other factors which contribute in a large amount to the global economy. According to the facts and figure including china and Japan, USA, France and Germany are the largest economies of the world because they gives an output which is not in comparison of others. Because they give best output in the very field, like food, labor, imports and exports which gave them a top level. There are other countries too which comes in the list of top ten countries of the world who contribute a large amount in global economy. This list includes brazil, Italy Canada and some other countries. However, beside this great contribution by all the countries global economy is still providing a figure of challenges in the form of unemployment whose rate is 30% around the world, enforcement to the labor footwork 41%, investment by public to the government plan less then 40%, and etc., All the countries are trying to just remove these factors affecting the global economy but they can’t, china is heavily providing cheap labor but this does not remove the unemployment. (WTO by Dr.Supachai) Another important factor which is heavily affecting the economy is terrorism. Terrorism is another part of the economies of the countries which is badly affecting it. Countries and there economies are also being affected with the increase in oil prices. There is factor of global health crisis, it is true that globally health is maintained by all the countries but to some extent thy lack and they have just left some loop holes which causes bad effect on the human’s life i. e., spreading diseases in the form of HIV Aids, bird flu, swine flu. There are measures to deal with these things but those are not adopted. (business-and-economy/textile-industry) As the factor terrorism is creating so much problems for the global economy so to deal with it is very important for all the countries and to deal with this factor all the countries have to come together to find out some better results. Infect, not just for the terrorism all the countries have to come together to deal with all the problem because the problems like, terrorism, Health diseases, inflation, poverty, unemployment are not small problems they are worst threats for the economies of all the countries around the world. History of textile History of textile is roughly based on these things or countries which have given a boost to the textile sector in the whole world and these countries are: Islamic Persian Excerpt from “Woven from the soul, spun from the heart” Excerpt from ” master pieces of Persian art safavid” Turkish Chinese Indian Italian Japanese Kashmiri Lets talk abut these simple but beautiful art of textiles styles which gave a wave to the textile industry both in design and culture. (Mary Belles) Islamic Textile History: Islamic textiles are as old as the Islam itself, Islamic textiles are the master piece of the textiles industry they gave a shape and a beautiful view of the clothing system. Islamic textiles were as demanded by the all countries as now e demand for the latest verities of the design. Islam is the symbol of peace and Islamic people were having a great quality of showing there culture I n the way of coloring their cloths. The essence of Islam in Europe is also the size of their language, their impact highlighted by the West was exported widely. For example, “Geffen” English word “mohair” and “Taft» and «Highlights», any manufacturer, Arabic, Farsi. Despite its nature, a relatively small fibers of the early Islamic era is alive. At any time, value Islamic fabrics were on stretchers, cut because they are inherently weak again, over fiber. Most of the early Islamic textiles, notably the maintenance of the store is dry and dark, including the grave, could be used in Egypt. Living piece of silk, cotton, linen and wool, often dyed in bright colors. These intricate designs and rich colors for use in a structured screens show textile technology. Silk Industry History: It is a great source of inspiration, often expect to find more songs from the miniature glossy silk fibers woven Peres today, inspired by the Merchant of Venice with a touch of world imports, often, sometimes bright, Culture in the vehicle owner with life. The project is based on animal and plant origin of the naturalist and created images based on royal Persian carpets of the Safari Empire and luxurious fabrics with sophisticated design language is polite and civilized. Persian rugs and remote villages, the lack of cooperation tissue and a variety of colorful geometric abstractions in the design is unlike kkwaewaneun. The experience begins long before the dynasty in the history of silk embroidered fabrics. At the time this work was exported to Europe and Rome. Prohibited the use of gold in the men because they stopped after the Sassanid period and type of tissue, almost. Mughal period, almost hiding fearing for his life he lived in Iran, the forgotten master of the textile sector. During the Safavid Shah was revived, the textile industry during the reign of apbaseuui was to textile artists from Isfahan switch the monarchy and the workshop are invited to start work. Turkish Textile History: Making fiber arts, especially in Anatolia, Konya Turkey, Bergama size barn and Seljuk, Feudal, during the Ottoman and the best fiber in the middle of a flourished jjanhaetdeon. Choose rugs and textiles, and fine examples of Turkish Islamic Art Museum (both in Istanbul) Kilim rugs Vakiflar museums and other museums in Turkey are different. Turkey has been developing more practice in the textile arts, weaving for centuries. The National Museum eloquent testimony to the example of the private collection of textiles and embroidery, painting, block printing, and provides an artistic medium. Ottoman era is to Bursa, Bilecik and Üsküdar, and the major cities of the world, such as silk, velvet, cotton and wool are now living, Sarayi clothes jjandoeeotda the Topkapi Museum, a collection of the Sultan is to focus on the case. Shares a wealth of material in court and the artist’s studio as a judicial decision based on running the design. (Mary Craft) Greater part of life and death, but all shares sold in Europe and some are intended for private use. Silk production in the late 16 Century stock market opened, but the performance, and that was not enough to satisfy the demand of the Ottoman repeated domestic world must rely on imported raw materials continued. Velvet Italian history: Weaver over most fanciful images of art: the kingdom, the altar, the royal bed chambers, bourgeois salons and ateliers of great couturiers, seems full of velvet. Giuseppe Verdi’s opera with only the most provocative characters such as velvet dress that Rossini and Donizetti. Giuditta Pasta, one of opera velvet play all the crazy waste of attention in costumes from Caruso to Galeffi So first, Courreges, Cardin, Rabanne, Marucelli and a long list of de Barentzen what was said about the designer? Italy, the entire 18th century until the twelfth century, the largest manufacturer in the Western world of velvet has been signed. These wall decor fabrics for clothes, and is expected to be for centuries, Lucca, Siena, Venice, Florence and Genoa in the offspring of a car interior, and all kinds of horse furniture collection, providing rest of Europe. Textile Industry and Revolution in Britain By having a look at the market and at global economy I found Textile industry at his best. According to the facts and figures textile industry has grown itself at a very high rate and today textile industry is contributing at a very high level to the global economy. With the invention of spinning mills and weaving machines in Britain the whole world witnessed remarkable growth because it has reduced labor cost as well as time consumption. Let’s talk about the history of textile industry, there were some major steps to be taken which were, Harvesting and clean of wool by hands Card it and spin it to thread To wave the thread into cloth Finally fashion and sew the cloth And it was all done with the human labor which consumes cost and time so it was a lassie process. According to the history America in 1786 tried first to make yarn weaving machine to reduce time and cost effecting thing s they encouraged the engineers but because of some loop holes those machineries didn’t worked correctly and they sold the machinery to Moses brown Britain engineer. It was the time of revolution for the Britain. During the eighteenth century Britain got the control over the textile industry figure shows that its exports were increase 25 % due to this revolution and then as the time passed they spread it all over the world with the latest technology of machinery for the textile industry. Decline of British Industry Even though Britain was the leader because revolution was came in the Britain for first time in Textile industry but Britain lost its status in the ERA of 2000, Britain’s started declining itself from 1950 because the mill owner and the workers union were not combined and doing work with effort. Secondly the competitors from Japan textiles industry gave them a big defeat. With the entry of Far East and India in cotton weaving they were in a big competitive situation. With the increase in the growth of these countries Britain started to blame the political situation of the country. (Susan Wolcott) America’s wrong way to defeat the Britain The USA personnel followed the British lead by using blue prints of the Britain’s which were stolen by their respective personnel’s and by the immigration of the engineer’s of the British to USA, by doing this thing slowly but steadily USA made a big giant of sewing , weaving and cotton spinning mills. They used all the measures to defeat the Britain and sooner they became the leader of the market. Asian Textile Industry America has enjoyed an ERA of being at the top of textile industry but then they got a situation of great rivals in the form Asian competetors. America tried hard to improve the material quality; although America was having an edge over the quality of machinery but due to cheap labor and low material cost Asian countries take the control from USA this thing gave him a big defeat, and because of the cancellation of MFA the developing countries got an edge over the success rate then USA. Although it was not a god idea but Asian countries were still getting the best out of it. Being the holder of market Asian countries got the best share rating, India was at 20 %,and china was representing a share of 45% according to the proceeding of 2010.other the these two countries Pakistan, Bangladesh and some other countries are also trying there best to gave quality production. Because, these countries are awarded of this fact that if they will produced quality production then they will get foreign investment and their economy will boost and there are so many chances to come at the top. There is round figure investment in china according to the stock market and global market analysis in 2010 there was a 100 bln investment in china in textile sector of foreign countries. There are some other factor which gives ways to become at the top, these includes, Growth Drivers’ Season’s cheer If we look at the customer his taste changes and this is the most important factor which china and other Asian countries have adopted, they are changing their designs and fashion with the change in time to remain at the top. There are mild signs are seen for the success of textile industry in Asian countries. (Mary Bellies) With some rough facts and figures this thing came into being that round about 45 % of the dyes were purchased by the Asian countries from the global market which accumulates to an amount of 16 million USD and this is just the figure off Asian country means Asian countries textile contribution in international market as well as in their local market is a t a very high level. Methodology This research has been conducted qualitatively. We have looked and gathered data from many different resources which include, Books, Websites, Articles Published In journals. First of all we have just looked at the global economy about the contribution of the different countries I to the international/global economy, then we looked into the local economies of the countries and gathered data to analyze the differences of the countries contribution to the global economy. We have also looked for the challenges difficulties that countries are facing during their success. Through this research we have been clarified that at the start Britain were the leader but then Asian countries got a boost and captured the textile industry. Results and Findings China’s Textile Industry: IF we talk about china it is having a long history, the textile industry of china is a conventional cutthroat industry, industry of china at this time is playing a main role in development of national economy. More on textiles are also the main exports of china. According to the figures of 2009 with the provocation of the economic situation, Chinese government issued an array of industrial supporting policies including increase in the export rate. The figures also show that china was having a sustained growth in 2005. But, there growth started to boost up in 2007. And in 2009 Chinese realized that there sales revenue has grown from 2.01 to 10.32%. This was a great rise for the Chinese although according to them their rat has gone down but still they are having better results. Although china was at a success but he was having a threat. His biggest threat was his rival countries which include Bangladesh, India, Pakistan and Indonesia; All these countries were also enjoying the same level position as china. And juts like china Pakistan, India and Bangladesh also having cheap labor and raw material of best quality.. Indian Textile Industry India is at the second spot in the field of textile and he is also enjoying the benefits just like china and other countries. India’s textile industry plays a role in the stabilization of his economy. The contribution of India in his economy from just textile sector is 35 %, It accumulates to the at least one third of the total contribution from all other sector which means India’s textile sector splaying a role of backbone of his country. History shows that by the end of 19th century, domestic wool production of India was having a transformation that was largely attributable to imposing rule. India’s textile industry is mostly based on small scale , spinning, weaving, finishing and apparel making enterprises. Research shows that India accounts to 22% of world spiritless capacity. Its spinning sector consists of 1,161 small scale independent firms and 1,566 larger scale. (Susan Wolcott) India has grown it sector on textile by giving it more preference rather then other sectors because he knows the situation of the market , Indian government also support the textiles industry that it should grow as much as it can. India is not just having a share in just local markets market but India is having a name in the international market. India has gain more then any other country it also some value when its currency gain some appreciation in international market. Indian government took many steps to boost the textiles economy, government started many different projects at small level and at big level. There is no doubt that Indian textile industries future is bright and there are many chances of India to becoming at that number one spot. India is having a vast number of players, named: Arvind mills limited Raymond lTd Alok Industries Aditya Birla nuvo LTD. Century Textiles. Welspun India Himatsighka seide lTd Bombay Dieng. Opportunities and challenges for Indian textile Factor Conditions • Abundant Availability of raw materials • Low Cost • Flexibility • Skilled Labor • Ability to produce customized Apparel • Lower Lead Tim Firm Strategy, Structure and Rivalry Dominated by unorganized sector • Highly competitive and fragmented • Entry of foreign players Govt. Regulations/ Policy Support for Technology up gradation • Government reimburses 5% of the interest rates • A credit linked capital subsidy of 10%, In addition to the existing 5% interest Reimbursement for modernizing the processing sector • Quality Improvement Related
The capital Asset pricing Model In 1959 Markowitz did the groundwork for the capital asset pricing theory (CAPM). He introduced the notion of mean-variance efficient portfolio. According to him it is optimal for an investor to hold a mean-variance efficient portfolio. The mean-variance efficient portfolio is a portfolio for an investor where he minimizes the portfolio return, given the expected return and maximizes expected return, given the variance. Later Sharpe (1964) and Lintner (1965b) further developed the work of Markowitz. In their work it has been showed that if the investors’ expectations are homogeneous and when the hold the mean-variance efficient portfolio then in the nonexistence of market friction the market portfolio will be a mean-variance efficient portfolio. There are two basic building blocks to derive the CAPM: one is the capital market line (CML) and the other one is the security market line (SML). In CAPM the securities are priced in a way where the expected risks are compensated by the expected returns. As we will be investigating different form of CAPM in this work it is worthy to review the basic notions of CML and SML. Capital Market Line The capital market line (CML) conveys the return of an investor for his portfolio. As we have already mentioned, there is a linear relationship exists between the risk and return on the efficient portfolio that can be written as follows: Here we can consider the expected return on a portfolio as a sum of the returns for deferring consumption and a premium for bearing the risk underlying the portfolio. It is noteworthy here that the CML is compelling only for the efficient portfolio. On the Other hand the SML specifies the return what an individual expects in terms of a risk-free rate and the relative risk of a portfolio. The Beta is interpreted as the amount of non-diversifiable risk intrinsic in the security relative to the risk of the efficient market portfolio. The utility function of the market agent is either quadratic or normal All the diversifiable risks are eliminated The efficient market portfolio and the risk-free assets dominate the opportunity set of the risky asset. We can use the security market line can be used to test whether the securities are fairly priced. Single-factor CAPM In practice, to check the validity of the CAPM we test the SML. Although CAPM is a single period ex-ante model, we rely on the realised returns. The reason being the ex ante returns are unobservable. So, the question which becomes so obvious to ask is: does the past security return conform to the theoretical CAPM? We need to estimate the security characteristic line (SCL) in order to investigate the beta. Here the SCL considers the excess return on a specific security j to the excess return on some efficient market index at time t. The SCL can be written as follows: Many early studies (e.g. Lintner, 1965; Douglas, 1969) on CAPM focused on individual security returns. The empirical results are off-putting. Miler and Scholes (1972) found some statistical setback faced when using individual securities in analyzing the validity of the CAPM. Although, some of the studies have overcome the problems by using portfolio returns. In the study by Black,Jensen and Scholes (1972) on New York stock exchange data, portfolios had been formed and reported a linear relationship between the beta and average excess portfolio return. The intercept approaches to be negative (Positive) for the beta greater than one (less than one). Thus a zero beta version was developed of the CAPM model. The model was developed in a model where the intercept term is allowed to take different values in different period. Fama and Mcbeth (1973) extended the work of Black et al (1972). They showed the evidence of a larger intercept than the risk neutral rate. They also found that a linear relationship exists between the average returns and the beta. It has also been observed that this linear relation becomes stronger when we work with a dataset for a long period. However, other subsequent studies provide weak empirical evidence of this zero beta version. Multifactor Models So far we have not talked anything about the cross sectional variation. In many studies we have found that market data alone cannot explain the cross sectional variation in average security returns. In the analysis of CAPM some variables like, ratio of book-to-market value, price-earning ratio, macroeconomic variables, etc are treated as the fundamental variables. The presence of these variables account for the cross-sectional variation in expected returns. Fana and French (1995), in their study showed that the difference between the return of small stock and big stock portfolio (SMB) and the difference between high and low book-to-market stock portfolio (HML) become useful factor in cross sectional analysis of the equity returns. Chung, Johnson and Schill (2001) found that the SMB and HML become statistically insignificant if higher order co-moments are included in the cross sectional portfolio return analysis. We can infer from here that the SMB and HML can be considered as good proxies for the higher order co-moments. Ferson and Harvey (1999) made a point that many econometric model specifications are rejected because they have the tendency of ignoring conditioning information. On the other hand arbitrage pricing theory (APT) by Ross (1976) shows that we do not need the condition of man-variance optimization for all the vendors. APT outperforms CAPM CAPM with higher-order co-moments We know that the unconditional security return distribution is not normal. Moreover, the mean and variance of security returns are not sufficient enough to characterise the distribution completely. Thus it encourages the researchers to look for the higher order co-moments. In practice we estimate the skewness (third moment) and kurtosis (fourth moment). In many studies researchers paid attention to the validity of CAPM in the presence of the higher order co-moments and their effects on the asset pricing. In many studies skewness has been incorporated in the asset pricing models and it provided mixed results. Some studies incorporated conditional skewness in their models. For example Harvey and Siddique (2000) investigated an extended version of CAPM. Since the conditional skewness confines the asymmetry in risk, this version of CAPM is usually preferred over the fundamental one. In recent times, this concept of conditional skewness has become very useful in measuring the value at risk. From the study of Harvey and Siddique (2000) we notice that the conditional skewness captures the variation in cross-sectional regression analysis of expected returns significantly. This also holds true when factors based on size and book-to-market are also considered. In some studies we see that in determining the security valuations, the non-diversified skewness and kurtosis play an important role. Fang and Lai (1997) reported a four-moment CAPM and in their study they showed that systematic variance, systematic skewness and kurtosis contribute to the risk premium of the underlying asset. Conditional asset pricing models Levy (1974) suggested to estimate different betas for bull and bear markets. Following that suggestion, Fabozzi and Francis (1977) estimated the betas for bull and bear markets. However, they didn’t find any evidence for beta instability. However, in another work Fabozzi and Francis (1978) reported that investors need a positive premium in order to accept the downside risk. On the other hand a negative premium corresponds with the up market beta. This up market beta is considered as a more appropriate measure of portfolio risk. There are few other studies examined the randomness for beta. Kim and Zumwalt (1979) examined the variation in returns on portfolios in both up and down markets. They concluded that the up market comprises the months for which the market returns exceed the average market return, the average risk neutral rate and zero. They specified three measures to identify what make up an up and down market. Those months for which the market return exceeds that the average market return and when it is above the risk free rate or greater than zero constitute the up market. They observed that the respective betas of the down market is more accurate measure for the portfolio risk than the single beta we see in the conventional CAPM. In an investigation on risk-return relationship Chen (1982) allowed the beta to be non-stationary and observed that investor need compensation when they assume downside risk no matter whether the betas are constant or changing. The concluded the same about the down market risk that Kim (1979) did. Bhardwaj and Brooks (1993) concluded that the systematic risks are different in bull and bear time periods. The also classified the market as Kim and Zumwalt (1979) did but instead of comparing the market return with mean return they compared it with the median return. Pettengill, Sundaram and Mathur (1995) observe that if we use the realized return then the beta-expected return relationship becomes conditional on the excess market return. From that study we that there exists a positive relationship between beta and ecpected return during a up market. In line with their study, Crombez and Vennet (2000) studied the conditional relationship between asset return and beta. They concluded that beta is a dependable meter in both bull (upward market) and bear market (downside risk). For different kind of specifications of the up and the down market this beta factor becomes robust and the investors can increase the expected asset return by considering the up and down market separately. Therefore different moments vary and correspond to the up and the down market. Galagedera and Silvapulle (2002) analyzed the asset return and the higher order co-moments in both bull and bear market and suggested that in the skewed market return distribution, the excess return is related to the systematic co-skewness. Early Empirical Test There are three relationships between expected return and market beta which is implied by the model. First, the expected returns on all the underlying assets are linearly related to their respective betas. Second, the premium for beta is positive which implies that the expected return on the market portfolio exceeds the expected return on assets. Moreover, the returns of these assets are uncorrelated with the expected return of market portfolio. Third, in the Sharpe-Lintner model we see that the underlying assets which are uncorrelated with the market portfolio have the expected returns which are equal to the risk neutral interest rate. In that model, if we subtract the risk free rate from the expected market return, we get the beta premium. Conventionally the tests of CAPM are based on those three implications mentioned above. Test on Risk Premiums Most of the previous cross-section regression tests primarily focus on the Sharpe-Lintner model’s findings about the concept and the slope term which studies the relationship between expected return and the market beta. In that model they regressed the mean asset returns on the estimated asset betas. The model suggests that the constant term in the cross-section regression stands for the risk free interest rate. Eqn-page8_chicago and the slope term stands for the difference between market interest rate and risk free interest rate. There are some demerits of the study. First of all, the estimated betas for individual assets are imprecise which creates the measurement error when we use them to explain average returns. Secondly, the error term in the regression has some common sources of variation which produces positive correlation among the residuals. Thus the regression has the downward bias in the usual OLS estimate. Blume (1970) and Black, Scholes and Jensen (1972) worked on overcoming the shortcomings of Sharpe-Lintner model. Instead of working on the individual securities they worked on the portfolios. They combined the expected returns and market beta in a same way that if the CAPM can explain the security return, it can also explain portfolio return. As the econometric theory suggests, the estimated beta for diversified portfolios are more accurate than the estimated beta for the individual security. Therefore, if we use the market portfolio in the regression of average return on betas, it lessens the critical problem. However, grouping shrinks the range of estimated betas and shrinks the statistical power as well. To tackle this researchers sort securities to create two portfolios. The first one contains securities with the lowest beta and it moves up to the highest beta. We know that when there exists a correlation among the residuals of the regression model, we cannot draw accurate inference from that. Fama and Macbeth (1973) suggested a method to address this inference problem. They ran the regression of returns on beta based on the monthly data rather than estimating a single cross-section regression of the average returns on beta. In this approach the standard error of the means and the time series means can be used to check whether the average premium for beta is positive and whether the return on the asset is equal to the average risk free interest rate. Jensen (1968) noted that Sharpe-Lintner model also implies a time series regression test. According to Sharpe-Lintner model, the average realized CAPM risk premium see page10 explains the average value of an asset’s excess return. The intercept term in the regression entails that “Jensen’s alpha” In early studies we reject Sharpe-Lintner model for CAPM. Although there exists a positive relation between average return and beta, it’s too flat. In Sharpe-Lintner model the intercept stands for the risk free rate and the slope term indicates the expected market return in access of the risk neutral rate. In that regression model the intercept is greater than the risk neutral rate and the coefficient on beta is less than E(R_M)-R_f In past several studies it has been confirmed that the relationship in between average return and beta is too flat (Blume: 1970 and Stambaugh: 1982). With the low betas the constant term in the time series regression of excess asset return on excess market return are positive and it becomes negative for the high betas of the underlying assets. In the Sharpe-Linter model, it has been predicted that portfolios are plotted along a straight line where the intercept equals the risk free rate, R_f, and the slope equals to the expected excess return on the market rate E(R_M)-R_f. See page 12, write the results and restrictions Testing whether market betas explain market betas Both the Sharpe-Lintner and Black model predict that market portfolio is mean-variance efficient. The mean-variance efficiency implies that the difference in market beta explains the difference in expected return of the securities and portfolios. This prediction plays a very important role in testing the validity of the CAPM. In the study by Fama and Macbeth (1973), we can add pre-determined explanatory variables to the month wise cross section regressions of asset return on the market beta. Provided that all the differences in expected return are explained by the betas, the coefficients of any additional variable should not be dependably different from zero. So, in the cross-section analysis the important thing is to carefully choose the additional variable. In this regard we can take the example of the study by Fama and MacBeth (1973). In that work the additional variables are squared betas. These variables have no impact in explaining the average asset return. By using the time series regression we can also test the hypothesis that market betas completely explain expected asset return. As we have already mentioned that in the time series regression analysis, the constant term is the difference between the asset’s average return and the excess return predicted by the Sharpe-Lintner model. We cannot group assets in portfolios where the constant term is dependably different from zero and this applies only the model holds true. For example, for a portfolio, the constant term for a high earning to price ratio and low earning to price ratio should be zero. Therefore, in order to test the hypothesis that betas suffice to explain expected returns, we can estimate the time-series regression for the portfolios and then test the joint hypothesis for the intercepts against zero. In this kind of approach we have to choose the form of the portfolio in a way which will depict any limitation of the CAPM prediction. In past literatures, researchers tend to follow different kinds of tests to see whether the constant term in the time-series regression is zero. However, it is very debatable to conclude about the best small sample properties of the test. Gibbons, Shanken and Ross (1989) came up with an F-test for the constant term that has the exact-small sample properties and which is asymptotically efficient as well. Tangency portfolio For the tangency portfolio, this F-test builds a entrant by combining the market proxy and the average value of an asset’s excess return. Then we can test if the efficient set and the risk free asset is superior to that one obtained by combining the market proxy and risk free asset alone. From the study of Gibbons, Ross, and Shanken (1989) we can also test whether market betas are sufficient enough to explain the expected returns. The statistical test what is conventionally done is if the explanatory variables can identify the returns which are not explained by the market betas. We can use the market proxy and the left hand side of the regression we can construct a test to see if the market proxy lies on the minimum variance frontier. All these early tests really do not test the CAPM. These tests actually tested if market proxy is efficient which can be constructed from it and the left hand side of the time series regression used in the statistical test. Its noteworthy here that the left hand side of the time series regression does not include all marketable assets and it is really very difficult to get the market portfolio data (Roll, 1977). So, many researchers concluded that the prospect of testing the validity of CAPM is not very encouraging. From the early literatures, we can conclude that the market betas are sufficient enough to explain expected returns which we see from the Black version of CAPM. That model also predicts that the respective risk premium for beta is positive also holds true. But at the same time the prediction made by Sharpe and Lintner that the risk premium beta is derived from subtracting the risk free interest rate from the expected return is rejected. The attractive part of the black model is, it is easily tractable and very appealing for empirical testing. Recent Tests Recent investigations started in the late 1970s have also challenged the success of the Black version of the CAPM. In recent empirical literatures we see that there are other sources are variation in expected returns which do not have any significant impact on the market betas. In this regard Basu’s (1977) work is very significant. He shows that if we sort the stocks according to earning-price ratios, then the future returns on high earning-price ratios are significantly higher than the return in CAPM. Instead of sorting the stocks by E/P, if we sort it by market capitalization then the mean returns on small stocks are higher than the one in CAPM (Banz, 1981) and if we do the same by book-to-market equity ratios then the set of stocks with higher ratio gives higher average return (Statman and Rosenberg, 1980). The ratios have been used in the above mentioned literatures associate the stock prices which involves the information about expected returns which are not captured by the market betas. The price of the stock does not solely depends on the cash flows, rather it depends on the present discounted value of the cash flow. So, the different kind of ratios discussed above play a crucial role in analyzing the CAPM. In line with this Fama and French (1992) empirically analyzed the failure of the CAPM and concluded that the above mentioned ratios have impact on stock return which is provided by the betas. In a time series regression analysis they concluded the same thing. Go back to page 14 Irrational Pricing of risk: There are two groups who conclude that the empirical validity of CAPM is poor. The one of them is the behavioralists and the other group believes that we need more tedious and complicated asset pricing model. The first group argues that sorting the firms according to the different kind of ratios expose them to the investors and provides them the opportunity to overreact. When the investors correct themselves from overreacting, that results high pay off for the value stocks and the pay off is low for the growth stocks. The second group argues that the assumptions of the CAPM theory are not realistic. For instance, the investors care about the distribution of mean and variance is really unrealistic. Investors care about other investment opportunity, their labour income and the dimensions of the risk. Therefore, the market betas cannot completely capture of an asset’s risk. Consequently differences in expected return cannot be completely captured by the difference in beta. Metron (1973) extended the CAPM which is known as the intertemporal capital asset pricing model (ICAPM). This model is based on different assumptions. In the conventional CAPM, the investors only care about the pay off at the end of the period but in ICAPM, investors also care about the consumptions or the amount of asset they will have to invest in the next period. In ICAPM, the investors prefer high expected return and low variance in return as they do in the CAPM. But along with that the investors also care about the covariance of the asset returns and state variables. Therefore, the combination of the portfolio which is optimal are multifactor efficient which implies that which has largest expected return. ICAPM actually generalizes the rationale behind the CAPM. The portfolio becomes multifactor efficient when the short selling of the risky assets are allowed. This implies that there is a relationship holds between expected market return and beta risks. Ross’s (1976) arbitrage pricing theory (APT) specified some of these state variables. Ideally ICAPM also specifies these state variables.
Discussion Board. Need help with my Business question – I’m studying for my class.

Must be a minimum of 300 words (Include the word count in parentheses at the end of your post. Failure to do so will result in a 1-point deduction).
Thoroughly address the writing prompt, and comment on a minimum of two peer posts. Be respectful, and provide insightful feedback. (300 words each)
Expressing an opinion is not enough. Do NOT respond with a simple “I agree or disagree…” You must further the conversation. Quality posts reflect critical thinking and inquiry. Cite a minimum of one primary or secondary source in each response.(3 minimum total) Your textbook does not count as a source. At the conclusion of each posting period, you should have a minimum of three different quality sources, cited in APA format. See the section on “Source Data” for additional information.

Dictionaries, encyclopedias, blogs, and Wikipedia are not acceptable sources. Use the CUI online library to research journal articles for argumentation.

Post throughout the open period to contribute to the on-going conversation
Utilize all conventions of Standard Written English. Proofread before posting!
(1 is discussion question, 2,3 are peer responses)
Discussion Board

UCLA Time Series Decomposition Seasonal Variation & Scatter Plot Worksheet

UCLA Time Series Decomposition Seasonal Variation & Scatter Plot Worksheet.

Time series are particularly useful to track variables such as revenues, costs, and profits over time. Time series models help evaluate performance and make predictions. Consider the following and respond in a minimum of 175 words:Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components?The model can be additive or multiplicative.When we do use an additive model? When do we use a multiplicative model?The following list gives the gross federal debt(in millions of dollars) for the U.S. every 5 years from 1945 to 2000:Year Gross Federal Debt ($millions)1945 260,1231950 256,8531955 274,3661960 290,5251965 322,3181970 380,9211975 541,9251980 909,0501985 1,817,5211990 3,206,5641995 4,921,0052000 5,686,338Construct a scatter plot with this data. Do you observe a trend? If so, what type of trend do you observe?Use Excel to fit a linear trend and an exponential trend to the data. Display the models and their respective r^2.Interpret both models. Which model seems to be more appropriate? Why?
UCLA Time Series Decomposition Seasonal Variation & Scatter Plot Worksheet

GEOG Brock University Vancouver House Prices Fall by Daniel Tencer Article Discussion

online homework help GEOG Brock University Vancouver House Prices Fall by Daniel Tencer Article Discussion.

Find at least five (5) articles from popular media sources (newspapers, magazines, blogs, etc.) related to one of the neighbourhoods we are discussing (choose one of, for example, of elite housing, lingering racism in housing market, the east/west divide, gentrification, etc.). Read the articles and, in a paragraph or two, offer your comments one the issues/themes that emerge, the stakeholders, the consequences, or any thing else that you think is important. Remember these assignments are supposed to help you build an experience of Vancouver. It is, therefore, important that you: a) explore the these issues on your own, and b) reflect on the material you find. Please review the material on reflection and how it might be graded if necessary.
GEOG Brock University Vancouver House Prices Fall by Daniel Tencer Article Discussion

please paraphrase that

please paraphrase that.

please paraphrase this .A) The lecture discussed changes of culture and what’s important in current American society. deChant also discussed how Santa is sacred and how the tension of religion and secularism affects Christmas. His emotional tone was humorous but concerned. The spiritual meaning is that religious practices have been infected by materialism and need to focus on core values.B) The main message of the lecture is that consumerism is the unifying religion of mass America and Santa serves as the God.2. One revelation I had during this lecture was that 75-80% of the American economy is consumer spending. That’s so insane to me.3. Examples of sacred consumption in America are Valentine’s Day, The Fourth of July, Back to School, and the Holidays.
please paraphrase that

I Need Help With My Assignment

I Need Help With My Assignment. I need support with this Art & Design question so I can learn better.

Art Gallery: Principles of Design
For Unit IV of your art gallery presentation, you will be adding descriptions of the principles of design you observe in the artworks you placed in your art gallery. The purpose of this unit assignment is to demonstrate that you can apply what you learned about design principles to your gallery artworks.

Begin by reviewing your Unit III feedback and making any necessary revisions to the descriptions of the visual elements.
Next, research the design elements in Chapter 4 of your textbook.
Place the Design Principles slide directly after the Visual Elements slide describing each artwork.
Provide a detailed description of the design principles in each artwork, using full and complete sentences. For design principles, make sure you describe how the artist used most or all of the ones in Chapter 4: unity and variety, balance, emphasis, directional forces, contrast, repetition and rhythm, and scale and proportion. Questions to consider are included below:

Unity: what elements work together to make a harmonious whole?
Variety: What creates diversity?
Balance: Is it symmetrical or asymmetrical?
Emphasis: What is the focal point?
Directional forces: What are the paths for the eye to follow?
Contrast: Where do you see contrasting elements in the artwork?
Repetition and rhythm: Is an element repeated?
Scale and proportion: Are the objects in proportion to each other?

You do not need to cite a source if it is your observation. Only cite a source if you are using information that someone published. Be sure to use APA formatting for all outside sources.
Please submit your full presentation thus far, which should include the previous updated segments and the segment for this unit.
This segment must include a minimum of five PowerPoint slides.

To access the art gallery template, an example presentation, and other PowerPoint resources, click on the “Course Resources” link in the course menu bar of Blackboard.
Click here to access an example of this presentation segment. Click here to view this example in PDF format.
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