Ideas For Writing a Good Eugenics Essay Topic

Ideas For Writing a Good Eugenics Essay TopicWriting a eugenics essay topic can be fun. After all, it's not easy to write an essay, and we all know how difficult it is to write a good one. However, if you put your mind to it, you can learn how to write a good eugenics essay topic. It takes time, but with the right preparation, the process can be easy.The first thing you want to do is write the topic and then write it in a way that focuses on the thesis. This is where you explain your thesis statement. Don't get into the details and don't tell someone how many children you want. That's not the point of eugenics; you're trying to get across a common point. Focus on what the thesis statement is going to be, and then think about how you are going to use that to your benefit.Sometimes common eugenics essay topics comes from general knowledge or a passion for animals. Be sure to make this clear, because sometimes it's easier to give a generic statement about animals than to mention specifi c details about specific animals. Don't forget to include information about some of the more controversial practices, such as the eugenics of cats. Doing so could be taken as controversial, which may cause problems at your school.One of the main focuses of the eugenics movement is that there are benefits to breeding and selective breeding. So the topic you should consider using for your eugenics essay topics is what you will gain from those practices. Obviously, that's the purpose. You should also consider whether you believe that all humans are worth saving, and that not all humans are valuable. If you are one of the few people who believe that the whole world is worth saving, you'll probably make a good topic. The rest of us are more likely to be labeled unoriginal, untidy, or out of step with the culture.Other common eugenics essay topics include the rise in birth defects, the increase in crime, and social problems like depression. Again, you don't want to get too specific, but y ou do want to discuss the point in a way that makes it easier to remember the topic. Once again, try to make it easier for yourself.After you've decided on the topic, you need to think about how you will go about describing your thesis. There are a few ways you can go about this. The first is to include all of the details you can think of. Alternatively, you can write in your own words.Good eugenics essay topics are not hard to come by. Remember that you must write them with the purpose of teaching, and with the purpose of helping people, not creating controversy.

Music and Film Essays - 991 Words

Exam 1 Essay Portion 1) Describe the three basic types of music heard in original scores during the silent film era and cites specific examples from The Birth of a Nation. (10 points) Music is an important form of art; it has always been utilized by each and every culture for entertainment purpose. Earlier in the silent film era, music was generally not included in the films but played in the beginning or at the end to entertain the audience. Later music was used in the form of background score to provide strength to the scenes of the film. There were three types of original scores of music during the silent film era, improvised score, compiled scores and composed scores. Improvise score refer to the created-off-the cuff by the†¦show more content†¦The music was given by Max Steiner who was very famous for his music scores in the silent films. In the film the songs are actually telling the story. Like the first song, â€Å"La Marseillaise† which is a French national anthem has been transformed a cording to the demand of the story. It was actually written during the French Revolution era in which the people were fighting for freedom from political repression. The song represents France which free and liberal, in the film it was played several times to represent patriotism. The song was successful in reflecting the patriotism of the French countrymen. The second song â€Å"As the time goes† represents the love story between the lead characters. It was successful in overcoming the effect of wars in the film. The music is soothing and very emotional. This song was very much praised in Paris and it is considered as a symbol of love. It represents the romantic feeling of Rick and IIsa for each other. Both the songs were beautiful and fulfil the demand of the story of the film. Since during the war it was necessary to reflect the patriotism of the people for their country, so according the music score of the national anthem was followed. So here we can suggest that it was a compiled music score. And since the film was a romantic drama so to reflect the feeling of the characters in the film a romantic track was needed which was composed so beautifully that it became a symbol of love for theShow MoreRelatedMusic Of Film And Film1120 Words   |  5 PagesAddition of Music in to Film When is the last time that we as an audience watched a film without sound? What if the silent film was to make a resurgence, how would we, as a nation, respond? How important has music within film become? Why does music affect us the way that it does? From the beginning of film to today’s digital formatting, music had been a stable part of entertainment and used to suggest certain emotional responses on the audience and we haven’t questioned it. Music is an importantRead MoreMusic and Film665 Words   |  3 PagesSince Ive been studying hard all day, I didnt really have time to post something. Well I would if I wasnt watching  Schindlers List  again, but when the mood strikes, one should watch that film. So here is an essay that I wrote a couple of months ago for school, which is all about film piracy and why Im against it. The essay managed to get an extremely high excellence. See how different my writing is when Im at school compared to when Im blogging (if I se em to be over-exaggerating a lot thisRead MoreMr. Williams And The Music Of Music And Film1427 Words   |  6 Pagesdid. Mr. Williams has made significant contributions to the arts of music and film. To fully understand the gravity of his achievements and their affect on humanity, we must first look at the progression of sound in film; the effect music has in film and its audience; and lastly his accomplishments of music and film. 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We underestimate the effectiveness and power that music, in any form , can have over even the most insensitive of people. In almost everything we do and see music is involved in some form or another. Be it a piece played at a wedding, a song played on the radio or even the music played in the background in a television commercialRead MoreGender And Bollywood Music And Film1520 Words   |  7 PagesGender and Bollywood Music and Film Bollywood is the Hindi language music and film industry based out of Mumbai, India. It began with the first silent film in 1913 and then escalated from there. Throughout the 1900s, Bollywood was significantly changing and growing. During the 1960s, Bollywood portrayed themes of Indian mafia and the gangster scene, and then in the 1980s and 1990s, it started to revert back to romantic themes. 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In most cases, adaptation of classics involves action and dramatic scenes. It is borrowing a large amount of an already existing composition for use in film score. In The Birth of a Nation, Mozart’s music wasRead MorePopular Culture Film And Music1385 Words   |  6 PagesPopular culture film and music has long since been awash with drug references and imagery. The context of these references has majorly affected the way in which they are received and perceived by the wider public, expressly in times of social or political change and unrest. The context in which these images and sounds are being interpreted affect the response to racial vilification, representation, along with gender roles and stereotypes. Conventional practice in the entertainment industries hasRead MoreFilm Music Critique Essay606 Words   |  3 P ages355 Music Critique of film Score Action, suspense, love, and drama are all the makings for a great film. None of these key features to a film could have any substance or feeling without the help of music. Composers play a big role for setting the tone of the movie, developing characters, moving along or supporting action, and depicting the time and place the movie is taking place. In the movie Heat, Elliot Goldenthal does just that. Goldenthal was born in NY in 1954 and studied music under

Importance of Transportation Cost-Free-Samples-Myassignmenthelp.com

Question: Discuss about the Importance of transportation cost for different manufacturing option. Answer: Transportation operation in a region reflects the efficiency of transporting goods. In the location decision for any manufacturing firms, cost of transportation plays an important role (Knaap Oosterhaven, 2017). For homeowner club, to decide over whether to establish manufacturing plant in Canada or export from China it should consider demand and supply of different mode of transportation and corresponding pricing for each mode. Importance of transportation cost for different manufacturing option If the company decide to build its own plant in Canada then it might enjoy the benefits of economies of scale from operating in the home country. Following establishment of new plant, new employment opportunities are created and this would inspire other related industries to develop in the region. This will in turn reduce transportation cost of other raw materials as well (Hu et al. 2015). For other alternative, that is export from China involves additional transportation cost. The additional transportation cost depend on the availability of different transportation mode in China. Supply and demand of different mode of transportation Supply of different transportation mode The specific transportation mode for importing the required product from China to Canada include air transport and transportation via oceans. Air China has a rapidly growing aviation industry. In 2007, China had nearly 500 airports of various size. Among these 500 airports, 400 had paved runways while 100 had runways of size 3,047 m or shorter. China also has 35 heliports providing additional assistance in air transportation (Ding et al., 2015). The operation of several airline companies such as Air China, Beijing capital Airlines, China Eastern Airlines, China Express Airline and other increases the availability of flight for carrying goods and passengers at different times of the day. Table 1: Air transport statistics in China (Source: hong-kong-economy-research.hktdc.com, 2018). Shipping and Ports There are nearly more than 2000 ports in China. Of which 130 are open foreign ships. Beihai, Fuzhou, Haikou, Nantong, Tianjin, Weihai and Zhanjiang are some of the major ports of China and are open to access for ocean going ships (Hu et al. 2015). The merchant fleet of China has 3497 ship. Table 2: Statistics for different mode of water transportation Year Barge carrier Bulk carrier Cargo ship Carrier Container ship 2004 2 325 840 11 125 2007 3 415 689 3 157 (Source: Ding et al., 2015) Demand of different mode of transportation The firm prefers to use cargo air carriers for importing their goods. The demand for mode of transportation however depend on the demand for companys product. If there is sufficient time, then the required tools of the company can be carried by cargo ships because of a lower cost Cargo flights though cost higher but are more time efficient (cargofromchina.com, 2018). The transportation pricing however often depends on specific period of the year. During peak season, the fair is higher as compared to the average cost. It is therefore beneficial for the company to exchange goods during off-season and maintaining an inventory stock to maintain smooth supply (Knaap Oosterhaven, 2017). In order to construct own plant in Canada, the transportation facilities within the country and corresponding cost needs to be considered. If transportation cost from China outweighs the benefits from operating within the country, then the country should chose to export from China rather than building its own plant References Air Freight Shipping from China: A Compelete Guide. (2018).Cargofromchina.com. Retrieved 3 April 2018, from https://cargofromchina.com/air-freight/ Air Transport and Express Cargo Industry in Hong Kong | HKTDC. (2018).Hong-kong-economy-research.hktdc.com. Retrieved 3 April 2018, from https://hong-kong-economy-research.hktdc.com/business-news/article/Hong-Kong-Industry-Profiles/Air-Transport-and-Express-Cargo-Industry-in-Hong-Kong/hkip/en/1/1X000000/1X0018JT.htm Ding, Z. Y., Jo, G. S., Wang, Y., Yeo, G. T. (2015). The relative efficiency of container terminals in small and medium-sized ports in China.The Asian Journal of Shipping and Logistics,31(2), 231-251. Hu, Y., Xiao, J., Deng, Y., Xiao, Y., Wang, S. (2015). Domestic air passenger traffic and economic growth in China: Evidence from heterogeneous panel models.Journal of Air Transport Management,42, 95-100. Knaap, T., Oosterhaven, J. (2017). Spatial economic impacts of transport infrastructure investments. InTransport Projects, Programmes and Policies(pp. 87-105). Routledge

Strategic Asset Allocation Determining the Optimal Portfolio with Ten Asset Classes Essay Example

Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes Essay Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes Niels Bekkers Mars The Netherlands Ronald Q. Doeswijk* Robeco The Netherlands Trevin W. Lam Rabobank The Netherlands October 2009 Abstract This study explores which asset classes add value to a traditional portfolio of stocks, bonds and cash. Next, we determine the optimal weights of all asset classes in the optimal portfolio. This study adds to the literature by distinguishing ten different investment categories simultaneously in a mean-variance analysis as well as a market portfolio approach. We also demonstrate how to combine these two methods. Our results suggest that real estate, commodities and high yield add most value to the traditional asset mix. A study with such a broad coverage of asset classes has not been conducted before, not in the context of determining capital market expectations and performing a mean-variance analysis, neither in assessing the global market portfolio. JEL classification: G11, G12 Key words: strategic asset allocation, capital market expectations, mean-variance analysis, optimal portfolio, global market portfolio. This study has benefited from the support and practical comments provided by Jeroen Beimer, Leon Cornelissen, Lex Hoogduin, Menno Meekel, Leon Muller, Laurens Swinkels and Pim van Vliet. Special thanks go to Jeroen Blokland and Rolf Hermans for many extensive and valuable discussions. We thank Peter Hobbs for providing the detailed segmentation of the global real estate market that supplemented his research paper. Last, but not least, we thank Frank de Jong for his constructive comments and useful suggestions during this study. * Corresponding author, email: r. [emailprotected] com, telephone: +31 10 2242855. Electronic copy available at: http://ssrn. com/abstract=1368689 1 Introduction Most previous academic studies agree on the importance of strategic asset allocation as a determinant for investment returns. In their frequently cited paper, Brinson, Hood and Beebower (1986) claim that 93. 6% of performance variation can be explained by strategic asset allocation decisions. This res ult implies that strategic asset allocation is far more important than market timing and security selection. We will write a custom essay sample on Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes specifically for you FOR ONLY $16.38 $13.9/page Hire Writer Most asset allocation studies focus on the implications of adding one or two asset classes to a traditional asset mix of stocks, bonds and cash to conclude whether and to what extent an asset class should be included to the strategic portfolio, see for example Erb and Harvey (2006) and Lamm (1998). However, because of omitting asset classes this partial analysis can lead to sub-optimal portfolios. This is surprising, as pension funds and other institutions have been strategically shifting substantial parts of their investment portfolio towards non-traditional assets such as real estate, commodities, hedge funds and private equity. The goal of this study is to explore which asset classes add value to a traditional asset mix and to determine the optimal weights of all asset classes in the optimal portfolio. This study adds to the literature by distinguishing ten different investment categories simultaneously in a mean-variance analysis as well as a market portfolio approach. We also demonstrate how to combine these two methods. Next to the traditional three asset classes stocks, government bonds and cash we include private equity, real estate, hedge funds, commodities, high yield, credits and inflation linked bonds. A study with such a broad coverage of asset classes has not been conducted before, not in the context of determining capital market expectations and performing a mean-variance analysis, neither in assessing the global market portfolio. The second step in portfolio management, i. e. market timing and security selection are tactical decisions. These are beyond the scope of this study. In short, this study suggests that adding real estate, commodities and high yield to the traditional asset mix delivers the most efficiency improving value for investors. Next, we show that the proportion of non-traditional asset classes appearing in the market portfolio is relatively small. In the remainder of this study we conduct an empirical and literature analysis to establish long-run capital market expectations for each asset class, which we subsequently use in a mean-variance analysis. Then, we provide an assessment of the global market portfolio. Finally, we show how the mean-variance and market portfolio approaches can be combined to determine optimal portfolios. 1 Electronic copy available at: http://ssrn. om/abstract=1368689 2 Methodology and data Methodology Markowitz (1952, 1956) pioneered the development of a quantitative method that takes the diversification benefits of portfolio allocation into account. Modern portfolio theory is the result of his work on portfolio optimization. Ideally, in a mean-variance optimization model, the complete investment opportunity set, i. e. all assets, should be considered simultaneously. However, in pr actice, most investors distinguish between different asset classes within their portfolio-allocation frameworks. This two-stage model is generally applied by institutional investors, resulting in a top-down allocation strategy. In the first part of our analysis, we view the process of asset allocation as a four-step exercise like Bodie, Kane and Marcus (2005). It consists of choosing the asset classes under consideration, moving forward to establishing capital market expectations, followed by deriving the efficient frontier until finding the optimal asset mix. In the second part of our analysis, we assess the global market portfolio. Finally, we show how the mean-variance and market-neutral portfolio approaches can be combined to determine optimal portfolios. We take the perspective of an asset-only investor in search of the optimal portfolio. An asset-only investor does not take liabilities into account. The investment horizon is one year and the opportunity set consists of ten asset classes. The investor pursues wealth maximization and no other particular investment goals are considered. We solve the asset-allocation problem using a mean-variance optimization based on excess returns. The goal is to maximise the Sharpe ratio (risk-adjusted return) of the portfolio, bounded by the restriction that the exposure to any risky asset class is greater than or equal to zero and that the sum of the weights adds up to one. The focus is on the relative allocation to risky assets in the optimal portfolio, in stead of the allocation to cash. The weight of cash is a function of the investor’s level of risk aversion. For the expected risk premia we use geometric returns with intervals of 0. 25%. The interval for the standard deviations is 1% and for correlations 0. 1. In our opinion, more precise estimates might have an appearance of exactness which we want to prevent. We do not take management fees into consideration, except for private equity and hedge funds as for these asset classes the management fees are rather high relative to the expected risk premia of the asset class. Other asset classes have significantly lower fees compared to their risk premia. They are therefore of minor importance, especially after taking the uncertainty of our estimates into account. We estimate risk premiums by 2 subtracting geometric returns from each other. Hereby, our estimated geometric returns as well as the risk premiums both are round numbers. In the mean-variance analysis, we use arithmetic excess returns. Geometric returns are not suitable in a mean-variance framework. The weighted average of geometric returns does not equal the geometric return of a simulated portfolio with the same composition. The observed difference can be explained by the diversification benefits of the portfolio allocation. We derive the arithmetic returns from the geometric returns and the volatility. Data We primarily focus on US data in the empirical analysis. The choice for this market is backed by two arguments. First, the US market offers the longest data series for almost all asset classes. This makes a historical comparison more meaningful. For instance, the high yield bond market has long been solely a US capital market phenomenon. Secondly, using US data avoids the geographical mismatch in global data. A global index for the relatively new asset class of inflation linked bonds is biased towards the US, French and UK markets, while a global stock index is decently spread over numerous countries. We use total return indices in US dollars. Asset classes like real estate and private equity are represented in both listed and non-listed indices, while hedge funds are only covered by non-listed indices. Non-listed real estate and private equity indices are appraisal based, which may cause a smoothing effect in assumed risk of the asset class. This bias arises because the appraisals will not take place frequently. However, interpolating returns causes an underestimation of risk. Also, changes in prices will not be immediately reflected in appraisal values until there is sufficient evidence for an adjustment. Statistical procedures to mitigate these data problems exist, but there is no guarantee that these methods produce accurate measures of true holding-period returns, see Froot (1995). As these smoothing effects can lead to an underestimation of risk, this study avoids non-listed datasets and instead adopts listed indices for real estate and private equity. The quality of return data of listed indices is assumed to be higher as they are based on transaction prices. Ibbotson (2006) supports this approach and states â€Å"Although all investors may not yet agree that direct commercial real estate investments and indirect commercial real investments (REITs) provide the same risk-reward exposure to commercial real estate, a growing body of research indicates that investment returns from the two markets are either the same or nearly so. †. For hedge funds we will use a fund of fund index that we unsmooth with Geltner (1991, 1993) techniques. Fung and Hsieh (2000) describe the important role of funds of hedge funds as a proxy for the market portfolio of hedge funds. Appendix A and B contain our data sources. In appendix A we discuss our capital market expectations and in appendix B we derive the market portfolio from a variety of data sources. 3 3 Empirical results Capital market expectations We estimate risk premia for all asset classes based on previous reported studies, our own empirical analyses of data series and on the basic idea that risk should be rewarded. Obviously, estimates like these inevitably are subjective as the academic literature only provides limited studies into the statistical characteristics of asset classes. Moreover, there is generally no consensus among academics and we lack long term data for most asset classes. Our results should therefore be treated with care, especially since mean-variance analysis is known for its corner solutions, being highly sensitive in terms of its input parameters. In this study we proceed with the risk premia and standard deviations as shown in Table 1. Appendix A contains the reasoning for these estimates and for the correlation matrix. [INSERT TABLE 1] Mean-variance analysis Table 2 shows the optimal portfolio based on the mean-variance analysis and its descriptive statistics for a traditional portfolio with stocks and bonds as well as a portfolio with all assets. On top of the traditional asset classes of stocks and bonds, this analysis suggests that it is attractive for an investor to add real estate, commodities and high yield. The Sharpe ratio increases from 0. 346 to 0. 396. The allocation to real estate is quite high. To bring this into perspective, we would suggest that the proposed portfolio weight is overdone. When one, for example, would be willing to perceive utilities as a separate asset class, it is likely that it also would get a significant allocation as this sector also has a low correlation to the general stock market. Table 2 also illustrates that mean-variance analysis tends towards corner solutions as it neglects credits which has characteristics comparable with bonds. However, with these parameters it prefers bonds in the optimal portfolio. [INSERT TABLE 2] Figure 1 shows the benefits of diversification into non-traditional asset classes. In the volatility range of 7% to 20% the diversification benefits vary between 0. 40% and 0. 93%. This additional return is economically significant. For example, at a volatility of 10% the additional return is 0. 56%. The efficient 4 frontier of a portfolio with stocks, bonds and the three asset classes real estate, commodities and high yield comes close to the efficient frontier of an all asset portfolio. By adding these three asset classes, an investor almost captures the complete diversification benefit. [INSERT FIGURE 1] For various reasons not all investors use cash to (un)leverage their investment portfolio. Therefore, it is interesting to observe the composition of efficient portfolios in a world without the risk free rate. Figure 2 shows the asset allocation on the efficient frontier in an all asset portfolio starting from a minimum variance allocation towards a risky portfolio. It maximizes the expected excess return constrained by a given volatility. [INSERT FIGURE 2] In the least risky asset allocation, an investor allocates 77. 7% of the portfolio towards fixed-income assets. Next to bonds and stocks, real estate and commodities receive a significant allocation in portfolios with a volatility in the range of 7. %-12. 5%. High yield is also present in most of the portfolios in this range. For riskier portfolios, private equity shows up and, in the end, it ousts bonds, real estate, commodities and stocks (in this order). For defensive investors, inflation linked bonds and hedge funds enter the portfolio. We have tested the sensitivity of the mean-variance analysis to the input parame ters. Table 3 shows the impact on the optimal portfolio of an increase and a decrease in the expected volatility of an asset by a fifth, all other things being equal. Note that a change in volatility affects both the arithmetic return and the covariance matrix. Again, this table demonstrates the sensitivity of a mean-variance analysis to the input parameters. An increase in expected volatility leads to a lower allocation to that asset class. High yield even vanishes completely from the optimal portfolio. It is noteworthy that commodities are hardly affected by a higher standard deviation. A decrease in volatility mostly leads to a higher allocation, with the exception of hedge funds and commodities. Commodities, despite their expected zero risk premium, add value due to the strong diversification benefit. In this analysis, they appear to be insensitive to a change in their expected volatility. Credits and bonds are quite similar asset classes and, in a mean-variance context, the optimal portfolio tends to incline towards one or the other. [INSERT TABLE 3] In short, the mean-variance analysis suggests that adding real estate, commodities and high yield to the traditional asset mix of stocks and bonds creates most value for investors. Basically, adding these 5 three asset classes comes close to an all asset portfolio. Private equity is somewhat similar to stocks, but shows up in riskier portfolios, moving along the efficient frontier. This part of the efficient frontier is interesting for investors in search of high returns without leveraging the market portfolio. Hedge funds as a group do not add value. Obviously, when investors attribute alpha to a particular hedge fund, it changes the case for that fund. This also applies to private equity. Credits and bonds are quite similar asset classes and in a mean-variance context the optimal portfolio tends to tilt to one or another. Inflation linked bonds do not show up in our mean-variance analysis. The inflation risk premium and the high correlation with bonds prevent an allocation towards this asset class in that setting. However, for defensive investors who primarily seek protection against inflation this asset class can be very interesting. Market portfolio Both academics and practitioners agree that the mean-variance analysis is extremely sensitive to small changes and errors in the assumptions. We therefore take another approach to the asset allocation problem, in which we estimate the weights of the asset classes in the market portfolio. The composition of the observed market portfolio embodies the aggregate return, risk and correlation expectations of all market participants and is by definition the optimal portfolio. In practice however, borrowing is restricted for most investors and at the same time borrowing rates usually exceed lending rates. The result is that the market portfolio is possibly no longer the common optimal portfolio for all investors, because some might choose risky portfolios on the efficient frontier beyond the point where no money is allocated to the risk free rate. In addition, an investor’s specific situation could also lead to a different portfolio. Despite this limitation, the relative market capitalization of asset classes provides valuable guidance for the asset allocation problem. In this setting, the market-neutral weight for a particular asset class is its market value relative to the world’s total market value of all asset classes. Figure 3 shows the global market portfolio based on a variety of data sources. Appendix B provides details about the market portfolio and its dynamics for the period 2006-2008. The asset classes stocks and investment grade bonds (government bonds and credits) represent more than 85% of the market for these years. At the end of 2008 we estimate this number at 88. 8%. This means that the size of the average remaining asset class is less than 2. 0%. Based on this analysis, we conclude that the proportion of non-traditional asset classes appearing in the market portfolio is relatively small. [INSERT FIGURE 3] 6 Combination of market portfolio and mean-variance analysis The mean-variance analysis can be combined with the market portfolio. Here, we choose to take the market portfolio as a starting point which we subsequently optimize with turnover and tracking error constraints. We choose to take the market portfolio as a starting point, as it embodies the aggregate return, risk and correlation expectations of all market participants without the disadvantage of delivering the corner solutions of the mean-variance analysis. Table 4 shows the optimal portfolios with different tracking error constraints and a maximum turnover of 25% (single count) relative to the market portfolio. In other words, in this example we limit ourselves to finding optimized portfolios with portfolio weights that do not differ more than 25% from the market portfolio, calculated as the sum of the absolute difference between the market portfolio and the optimized portfolio for each asset class. Focusing on the 0. 25% tracking error constraint, it appears that the analysis recommends especially adding real estate, commodities and high yield, and removing hedge funds and inflation-linked bonds. This is logical, as the results from the meanvariance analysis are applied in this market-portfolio-adjustment process. There is a 12. 5% shift in portfolio weights. Obviously, less constraints result in a higher risk premium and a higher Sharpe ratio, until we end up with the theoretically optimal portfolio from the mean-variance analysis. Within this methodology, investors must determine their own individual constraints, while the market portfolio and the portfolio optimized by mean-variance are considered as the boundaries for the asset classes. [INSERT TABLE 4] 4 Summary and conclusions Our mean-variance analysis suggests that real estate, commodities and high yield add most value to the traditional asset mix of stocks, bonds and cash. Basically, adding these three asset classes comes close to an all asset portfolio. The portfolio with all assets shows a diversification benefit along the efficient frontier that varies between 0. 40% and 0. 93% in the volatility range of 7% to 20%. That is an economically significant extra return for free. Another approach to the asset allocation problem is assessing the weights of the asset classes in the market portfolio. Based on this analysis we conclude that the proportion of non-traditional asset classes appearing in the market portfolio is relatively small. 7 One can combine the mean-variance analysis with the market portfolio. Within this methodology, investors must determine their own individual constraints, while the market portfolio and the portfolio optimized by mean-variance are considered as the boundaries for the asset classes. 8 References Altman, E. I. , 1998, â€Å"The Anatomy of the High Yield Bond Market: After Two Decades of ActivityImplications for Europe†, research paper. Amin, G. , and H. Kat, 2005, â€Å"Welcome to the Dark Side: Hedge Fund Attrition and Survivorship Bias 1994-2001†, Journal of Alternative Investments, vol. 6, no. 2, 57-73. Bodie, Z. , A. Kane and A. Marcus, 2005, â€Å"Investments†, McGraw-Hill, sixth dition. Brinson, G. P. , L. R. Hood and G. L. Beebower, 1986, â€Å"Determinants of Portfolio Performance†, Financial Analysts Journal, vol. 42, no. 4, p. 39-44. Dimson, E. , P. Marsh and M. Staunton, 2003, â€Å"Global Evidence on the Equity Risk Premium†, Journal of Applied Corporate Finance, vol. 15, no. 4, p. 27-38. Dimson, E. , P. Mars h and M. Staunton, 2009, â€Å"Global Investment Returns Sourcebook 2009†, Credit Suisse. Doyle, E. , J. Hill and I. Jack, 2007, â€Å"Growth in Commodity Investment: Risks and Challenges for Commodity Market Participants†, study from the FSA Markets Infrastructure Department. Elton, E. J. , M. J. , Gruber and D. M. C. Agrawal, 2001, â€Å"Explaining the Rate Spread on Corporate Bonds†, Journal of Finance, vol. 56, no. 1, 247-277. Erb, C. B. , and C. R. Harvey, 2006, â€Å"The Tactical and Strategic Value of Commodity Futures†, Financial Analysts Journal, vol. 62, no. 2, p. 69-97. Fama, E. F. , and K. R. French, 2002, â€Å"The Equity Premium†, Journal of Finance, vol. 57, no. 2, p. 637660. Froot, K. A. , 1995, â€Å"Hedging Portfolios with Real Assets†, Journal of Portfolio Management, vol. 21, no. 4, p. 60-77. Fugazza, C. , M. Guidolin and G. Nicodano, 2007, â€Å"Investing for the Long-Run in European Real Estate†, Journal of Real Estate Finance and Economics, vol. 34, no. 1, p. 35-80. 9 Fung, W. , and D. A. Hsieh, 2000, â€Å"Performance Characteristics of Hedge Funds and Commodity Funds: Natural vs. Spurious Biases†, Journal of Financial and Quantitative Analysis, vol. 35, no. 3, p. 291-308. Geltner, D. M. , 1991, â€Å"Smoothing in Appraisal-Based Returns†, Journal of Real Estate Finance and Economics, vol. 4, no. 3, 327-345. Geltner, D. M. , 1993, â€Å"Estimating Market Values from Appraised Values without Assuming an Efficient Market†, Journal of Real Estate Research, vol. 8, no. , 325-345. Gorton, G. , and K. G. Rouwenhorst, 2006, â€Å"Facts and Fantasies about Commodity Futures†, Financial Analysts Journal, vol. 62, no. 2, p. 47-68. Graham, J. R. , and C. R. Harvey, 2008, â€Å"The Equity Risk Premium in 2008: Evidence from the Global CFO Outlook Survey†, working paper. Graybill, F. A. , 1983, â€Å"Matrices with Applications in Statistics†, Wadsworth International Group, California. Grishchenko, O. V. , and J. Huang, 2008, â€Å"Inflation Risk Premium: Evidence from the TIPS Market†, working paper. Hammond, P. B. , 1999, â€Å"Using Inflation-Indexed Securities for Retirement Savings and Income: The TIAA-CREF Experience†, in J. Brynjolfsson and F. J. Fabozzi, Handbook of Inflation Indexed Bonds, New Hope. Hordijk, A. C. , and C. Ahlqvist, 2004, â€Å"European Market Dimensions: An Inventory of the Investable Market in 11 European Countries†, The Compendium of Real Estate Papers 2. Ibbotson, 2007, â€Å"Private Equity and Strategic Asset Allocation†, research paper. Ibbotson, 2006, â€Å"Commercial Real Estate: The Role of Global Listed Real Estate Equities in a Strategic Asset Allocation†, research paper. Jong, F. de, and J. Driessen, 2005, â€Å"Liquidity Risk Premia in Corporate Bond Markets†, working paper. 10 Kaplan, P. D. , and S. L. Lummer, 1998, â€Å"GSCI Collateralized Futures as a Hedging and Diversification Tool for Institutional Portfolios: An Update†, Journal of Investing, vol. 7, no. 4, p. 11-17. Kaplan, S. N. , and A. Schoar, 2005, â€Å"Private Equity Performance: Returns, Persistence, and Capital Flows†, Journal of Finance, vol. 60, no. 4, p. 1791-1823. Lamm, R. M. , 1998, â€Å"Asset Allocation Implications of Inflation Protection Securities†, Journal of Portfolio Management, vol. 24, no. 4, p. 8-13. Li, L. , 2002, â€Å"Macroeconomic Factors and the Correlation of Stock and Bond Returns†, working paper. Liang, Y. , and N. M. Gordon, 2003, â€Å"A Bird’s Eye View of Global Real Estate Markets†, Prudential Real Estate Investors, research paper. Lummer, S. L. , and L. B. Siegel, 1993, â€Å"GSCI Collateralized Futures: A Hedging and Diversification Tool for Institutional Portfolios†, Journal of Investing, vol. 2, no. 2, 75-82. Markowitz, H. M. , 1952, â€Å"Portfolio Selection†, Journal of Finance, vol. 7, no. 1, p. 77-91. Markowitz, H. M. , 1956, â€Å"The Optimization of a Quadratic Function Subject to Linear Constraints†, Naval Research Logistics Quarterly, vol. 3, no. 1-2, 111-133. Masters, M. W. , 2008, Testimony Before the US Senate. McKinsey Global Institute, 2007, â€Å"The New Power Brokers: How Oil, Asia, Hedge Funds, and Private Equity are Shaping Global Capital Markets†, research paper. McKinsey Global Institute, 2008, â€Å"Mapping the Global Capital Markets Fourth Annual Report†, research paper. Norman, E. J. , G. S. Sirmans and J. D. Benjamin, 1995, â€Å"The Historical Environment of Real Estate Returns†, The Journal of Real Estate Portfolio Management, vol. 1, no. 1, p. 1-25. Ong, S. E. , and M. Ranasinghe, 2000, â€Å"Portfolio Variance and Correlation Matrices†, Journal of Real Estate Portfolio, vol. 6, no. 1, p. 1-6. Phalippou L. 2007, â€Å"Investing in Private Equity Funds: A Survey†, working paper. 11 Phalippou, L. , and O. Gottschalg, 2007, â€Å"The Performance of Private Equity Funds†, Review of Financial Studies, forthcoming. Posthuma, N. , and P. J. van der Sluis, 2003, â€Å"A Reality Check on Hedge Fund Returns†, working paper. Hobbs, P. , and H. Chin, 2007, â€Å"The Future Size of the Global Real Estate Market†, RREEF research paper. Swensen, D. F. , 2000, â€Å"Pioneering Portfolio Management†, Free Press, New York. Welch, I. , 2008, â€Å"The Consensus Estimate for the Equity Premium by Academic Financial Economists in December 2007†, working paper. Wilshire, 2008, â€Å"Report on State Retirement Systems: Funding Levels and Asset Allocation†, research paper. 12 Appendix A: Capital market expectations Risk premia for stocks and bonds are well documented and long term data series extending over 100 years are available. We will therefore start with the risk premia for stocks and bonds. Then, we derive the risk premia of other asset classes by comparing historical performance data and consulting the literature. In order to estimate volatilities and correlations, we rely more on our own historical data, due to a lack of broad coverage in the literature. Below, we discuss returns and standard deviations for each asset class. Afterwards, we estimate correlations among all asset classes. Stocks Extensive research on the equity-risk premium has been conducted in recent years. Fama and French (2002) use a dividend discount model to estimate an arithmetic risk premium of 3. 54% over the period 1872-2000 for US stocks, while the realized risk premium for this period is 5. 57%. In the period 19512000, the observed difference is even larger. They conclude that the high 1951-2000 returns are the result of low expected future performance. However, the US was one of the most successful stock markets in the twentieth century, so a global perspective is important to correct this bias. Dimson, Marsh and Staunton (2009) use historical equity risk premia for seventeen countries over the period 1900-2008. They conclude that their equity risk premia are lower than frequently cited in the literature, due to a longer timeframe and a global perspective. Table A. 1 provides an overview of historical risk premia and volatilities. TABLE A. 1 OVERVIEW OF HISTORICAL RISK AND RETURN CHARACTERISTICS FOR STOCKS SOURCE COUNTRY RISK ST. DEV. ANN. ST. DEV. PREMIUM OF MONTHLY ON CASH RETURNS MSCI US US 3. 1% 18. 4% 15. 4% MSCI WORLD WORLD 3. 0% 18. 8% 14. 8% FAMA AND FRENCH (2002)* US US US US UK WORLD 3. 9% 2. 5% 6. 0% 5. 2% 4. 2% 4. 4% 18. 5% 19. 6% 16. 7% 20. 2% 21. 8% 17. 3% 22. 0% N. A. N. A. N. A. N. A. N. A. N. A. 16. 0% DATA 1970-2008 1970-2008 1872-2000 1872-1950 1951-2000 1900-2008 1900-2008 1900-2008 1970-2008 DIMSON, MARSH AND STAUNTON (2009) ST. DEV. OF MSCI WORLD IN EUROS * STANDARD DEVIATION OF THE RISK PREMIUM INSTEAD OF THE STANDARD DEVIATION OF THE NOMINAL RETURN. WE DERIVE GEOMETRIC DATA BY USING THE EQUATION RG = RA 0. 5*VARIANCE Both Fama and French (2002) and Dimson, Marsh and Staunton (2003, 2009) find that the historical equity premium was significantly higher in the second half of the twentieth century than it was in the first half. Dimson, Marsh and Staunton (2009) expect a lower equity premium in the range of 3. 0%- 13 3. 5% going forward. In this study we use an equity risk premium of 4. 75%. This is slightly above the average of countries in a long timeframe and corresponds well with consensus estimates among finance professors as documented by Welch (2008) and among CFOs as reported by Graham Harvey (2008). The other estimate we need is stock market volatility. Dimson, Marsh and Staunton (2009) find a standard deviation of 17. 3% for global equity during the 109 year period 1900-2008. Over the period 1970-2008 the global MSCI index had a volatility of 18. 8% and 22. 0% expressed in dollars and euros respectively. We average these last two figures and estimate the volatility of stocks at 20%. 1 Government bonds Dimson Marsh and Staunton (2009) also evaluate the risk premium of bonds over cash. Their data point to a lower risk premium than the Barclays Government Indices which have been available since 1973, see Table A. . The last decades have been extremely good for government bonds. We use a geometric risk premium of 0. 75% for government bonds over cash, in line with the long term historical average from Dimson, Marsh and Staunton (2009). TABLE A. 2 OVERVIEW OF HISTORICAL RISK AND RETURN CHARACTERISTICS FOR GOVERNMENT BONDS SOURCE COUNTRY RISK ST. DEV. ANN. ST. DEV. PREMIUM OF MONTHLY ON CASH RETURNS BARCLAYS TREASURIES US 2. 2% 6. 5% 5. 4% US 3. 6% 6. 3% 5. 0% US 3. 0% 5. 5% 4. 8% DIMSON, MARSH AND STAUNTON (2009) US UK WORLD 1. 2% 0. 4% 0. 8% 8. 3% 11. 9% 8. 6% N. A. N. A. N. A. DATA 973-2008 1984-2008 1999-2008 1900-2008 1900-2008 1900-2008 The volatility of bonds has been significantly lower in

The Movie About Family Relations Family Systems

The Movie About Family Relations Family Systems The movie explains family relations. It is noted that one family member may influence the behavior of others. From the movie, it is evident that the family plays a critical role in the life of an individual since it restrains behavior (Knapp, Womack, 2003). Agency-structure theory suggests that the individual does not exist freely in society. However, individuals are influenced by the dynamics of society, such as the family.Advertising We will write a custom essay sample on The Movie About Family Relations: Family Systems specifically for you for only $16.05 $11/page Learn More The movie aims at conveying the purposive nature of human activity as opposed to its constrained aspect. In the movie, it can be observed that social life is largely determined by group life. This would mean the existence of an individual could be explained as an outcome of the structure. From the movie, the family is portrayed as an agent that can either restrain or promote individu al behavior. In a family setup, some forms of interactions usually take place. Family members exchange both material and non-material goods through actions and messages. These exchanges result to interactions, which would take various forms, depending on the nature of the family. Social interactions would sometimes be repetitive and habitual. If interactions become habitual, they might form a certain pattern. This is referred to as patterned social interaction. In this regard, each family member would be expected to demonstrate certain forms of behavior. In this article, two forms of interactions would be compared. Two major forms of social changes would also be compared, which are the first-order and the second-order change. In the film, command is used to influence Ana to defer her studies in favor of employment. In the Latino culture, a woman was supposed to help her family immediately she graduates from high school. Ana’s parents issued a command that she had to obey soci etal rules and assist her mother in undertaking domestic chores. Since it is a traditional society, actors in the movie use command quite often to demand for attention. Ana’s mother accused her of becoming irresponsible when she decided to quit employment and go back to school. In the film, women do not enjoy societal freedoms since they are supposed to be providers and caregivers. Regarding interactions, content and process interactions exist among family members in the movie. Content interactions take place when members of the family come together to discuss major problems affecting them. Moreover, family members would come up with suggestions on how to end problems.Advertising Looking for essay on social sciences? Let's see if we can help you! Get your first paper with 15% OFF Learn More In particular, individuals in the family would be required to highlight the causes of problems. In the movie, content interactions are portrayed in many ways. When Ana finishes high school, her parents never hesitate to inform her that the family is facing many problems and she is the only hope (Lee, 1982). The family agrees that problems would be eliminated if Ana starts working instead of joining college. Content interaction is always the main form of interaction in the backward societies, such as the one portrayed in the movie. There are no clear modes of conflict resolution. On the other hand, process interaction refers to the actions whose main aim is to achieve certain objectives. Process interaction entails thorough evaluation of a problem before coming up with a solution. In the movie, this form of interaction takes place when Ana is about to go back to school. It is after a critical review of her life that Ana decides to quit employment. The mother is reluctant to give in to Ana’s demands. Process interaction involves emotions whereby family members express deep concern. Ana’s mother could not see her daughter leave her and she decides to lock herself in a room. Ana is also overwhelmed by emotions when she leaves for Columbia. Wiener’s cybernetics theory and the systems theory talk about how human beings change over time. Wiener noted that a human being would stretch his or her hand until he or she reaches an object. The theory is used in social sciences to explain the process of change. It means that an individual would not relax until he or she obtains what he or she wants. In the movie, Ana never gives up on her studies. She always admires female professionals and things that one day she could make it. The theory differentiates between first-order change and second-order change. First-order change means championing for the same thing over several years (Salkovskis, 1996). This is the kind of change advocated by Ana. She insists that she wants to be a professional woman and believes that this could be achieved through education. First-order change is non-transformational and is reversible. It is reversible because Ana accepts to join the local industry as a casual laborer but decides to quit after some time.Advertising We will write a custom essay sample on The Movie About Family Relations: Family Systems specifically for you for only $16.05 $11/page Learn More She never needed any information to change her mind implying that first-order change does not need new learning techniques. Second-order change involves accepting the reality due to certain forces. Ana’s father realized that he had to allow her daughter to pursue high education because the world was changing at a faster rate. References Knapp, J. V., Womack, K. (2003). Reading the family dance: Family systems therapy and literary study. Newark: University of Delaware Press. Lee, G. R. (1982). Family structure and interaction: A comparative analysis. Philadelphia: Lippincott. Salkovskis, P. M. (1996). Frontiers of cognitive therapy. New York [u.a.: Guilford Press.

(SOCIAL WORK) Social Circumstances Report - Case Study Essay

(SOCIAL WORK) Social Circumstances Report - Case Study - Essay Example She likes to spend time with her grandmother and learn Gujarati from her. Till this age she has not dated or selected her lover. She comes from a conservative family background. In their family culture they respect Muslim traditions and follow their customs. Ruksana suffers from certain disabilities like learning disability and physical weakness. Many people in the world faced this problem in their childhood. â€Å"Learning disabilities are problems that affect the brains ability to receive process, analyze, or store information.† (Learning disabilities 2009). Her speech is impaired and she struggles due to phonological disorder. These two problem forces her to take help from others in her personal chores. She travels short distance by electric wheelchair. She completed her schooling from a residential specialist school. Students of such schools are different from normal students. They cannot learn like normal students. They are physically weak and have learning disability. According to a report about safeguarding disabled children in residential special schools â€Å"protection from abuse of disabled children living in residential settings has received much less attention than the protection of children looked after by local authorities.† (Paul, Cawson & Paton 2006). People need patience to communicate with her. It indicates that one reason for her impaired speech may be lack of attention from her parents or other close relatives. Had they given more attention to her in her childhood, this problem could have been solved to an extent. Her speech and language therapist Mr. Jean helps her for this. He adopts computerized assistive voice technology and she is interested in this computer based study. Usually such people seek help from learning and speech therapists when they face problem in learning and reading (About academic language therapy 2004). Here Ruksana did not get help at the initial stage. When she got such a

Enviromental Change Essay Example | Topics and Well Written Essays - 1250 words

Enviromental Change - Essay Example Global warming has many greater effects other than melting ice caps and warmer winters. Its effects are escalating over the years and the climate is changing at a very rapid rate. If things are not changed around the earth is going to be a tough place to subsist in. Not just for us but for most animals and creatures. Global warming may be simply defined as the average increase in the earth's atmospheric temperature. Global temperatures have increased by 0.74 0.18C. This rise in temperature has many effects on the environment.The polar ice caps are melting at a rapid rate and this will lead to a rise in sea level by about 1.3 meters within the next century (Carlson, 2008). For most glaciers worldwide, it is predicted that there will be an average volume loss of 60% by the year 2050 (Schneeberger, 2003). This melting can cause flash floods and overflowing of lakes. The changes in climate is leading to a change in the ecosystem.There will be an increase in the frequency of extreme weather events. Places at lower altitudes are at a higher risk from climate change. It is said that there will be lesser rainfall and an increase in the risk of drought in some places, while at some places the rainfall will increase. Global warming has many causes, which are split into two groups, natural causes and man-made or anthropogenic causes. Methane gas is a greenhouse gas and is naturally released from the tundra and wetland regions. A greenhouse gas is one which traps heat in the earths atmosphere. The man-made cause of global warming is basically pollution. Burning and mining of fossil fuels such as petroleum and coal. Minning for fossil fuels releases methane which is found naturally in the earth. Burning of fossil fuels is the major cause of global warming. Burning fossil fuels releases greenhouse gasses such as CO2. Today cars are the main culprits and are responible for releasing 36% of the total amount of greenhouse gasses into the atmosphere. Everyday cars emmit many tonnes of greenhouse gasses into the atmosphere which leads to an increase in global warming. If swift action is not taken soon sceintists fear that there will be catastrophic consequences. Cars are not going to go away. If anything the number of cars are going to increase. "Department of the Environment, Transport and the Regions (DETR) projections envisions that by 2025, there will have been between 82 and 142 per cent growth in national traffic over 1989 levels. In the UK bus, cycle and rail growth has been essentially stagnant since 1952, according to the DETR figures, but car traffic has increased enormously, from less than 100 billion kilometres a year to 600 billion in 1990(when it began to level off) " (Motavalli, 2001). This increase in cars is leading to an increase in emmisions and so increase in greenhouse gasses which leads to thus car companys are taking an initiative and are developing hybrid cars. A hybrid vehicle is a vehicle that uses two or more distinctive power sources. Usually hybrid vehicles use an internal combustion engine along with some another eco-friendly source of power such as electric power. Now