Beveridges Social Security Essay Example | Topics and Well Written Essays - 500 words

Beveridges Social Security - Essay Example "There is world economy, but there is no world polity". (Altiero Spinelli and Brit Federa: Writings by Bevirdige, Robbins and Spinelli) The Beveridge Report is based on certain principles that put forth the cause of the lower strata of the society and social security. Firstly, the main principle underlines in the Report is that all the proposals for the establishment of a Welfare State and to promote the interests of the society, need to be unbiased and non-partisan. The proposals need to be commonly targeted and certainly not in the interest of a section of the society. Besides using past experience and knowledge in governance, proposals need to highlight the positive impact they would bring about, on the entire society, and not only the affluent strata. Secondly, the Report highlighted that social insurance must be incorporated into the process of bringing about social welfare.

Youth Consumption and Fragrances Essay Example | Topics and Well Written Essays - 2500 words - 1

Youth Consumption and Fragrances - Essay Example But the new and cheaper mass brands have registered the highest growth in percentage and absolute levels. The perfumes and fragrances segment have targeted the younger age groups particularly the teen segment. The teens whose ages range from 13 years old to 19-years-old have a total population of 860 million all over the world. These teens have a bigger purchasing power than most of the generations before them. The teens' market is valued at US$250 billionannually worldwide, based on studies done by Euromonitor International. This market segment is a wealthy and sophisticated segment which bodes positive prospects for premium fragrances and celebrity scents. Indeed, celebrity scents have increased the profitability and the resilience of the perfume and fragrances industry on a global sale. Celebrity scents base itself on the established image of an actress or performer and it guarantees a deep consumer base. Hence, this helps fragrance makers to reduce marketing and promotions expens es. Young people look for celebrity scents since they want to imitate their favorite R & B performers, Hollywood actors and actresses and musical artists. Having a good and pleasant smell is a status symbol and an example of making a good impression on one's friends and on one's sweetheart. The basic barometer is this: that what smells good is good, and that what smells bad is bad. The fragrance industry exemplifies that fact that smell is a reflection of material culture and it enhances the olfactory senses of persons. The fragrance market as a whole is composed of these sets: (1) soaps and detergents (in which scents are added in a particular way) (34%); (2) cosmetics and toiletries; and (3) others (air fresheners, polishes, foods, and others) which are designed to convey an unconscious scent experience. (41%). The market is equally shared between flavors (51%) and fragrances (49%). Perfumes, fragrances and deodorants are part of a global beauty business that has been pegged at US $160 billion dollars a year with a very high annual growth rate of 7%. The seven percent growth rate is higher than the growth rate of the Gross Domestic Product (GDP) of the world's developed countries. The estimated global market in 2008 for the perfumes and fragrances segment is pegged at US $15 billion dollars. The Japanese market accounts for US $4.5 billion (Fuji Keizai, 2002, "Fragrance," p. 145).

Improving The Risk Return Performance Of Portfolios

Improving The Risk Return Performance Of Portfolios With the development of the Chinese capital market, more and more investors start to look for a more rational way to invest. To increase the investment return and decrease the risk, investors must learn to allocate their funds in order to diversify risk. However, due to the limited assets that can be invested in, the convenience and effectiveness of portfolio diversification must be studied. This paper mainly explores the function of futures in the ordinary stock portfolio through the study of risk-return performance. By comparing the efficient frontiers of different portfolios, the risk-return performance of the futures portfolio and mixed stock-futures portfolio is better than the stock only portfolio. Futures play an important role in upgrading the integrated portfolio of stock and futures. The results of this study provide investors with a feasible way to diversify their funds in multi-type investment portfolios, which is of great theoretical and practical significance. I. An introduction to Chinese capital market Ever since December 19, 1990, when Shanghai stock exchange opened, people become more and more interested in investing in the security market to make money. After twenty years, investing in stocks is a quite popular and important way for ordinary Chinese people to manage their money. However, stock market itself can not meet investors needs of diversifying risk and increase capital return, and investment diversification becomes a natural solution and guiding concept. Although twenty years have passed since Shanghai stock exchange came in existence, development of Chinese capital market is quite slow, with limited kinds of investment products. Lack of varieties of trading tools and incomplete structure of capital market products make it difficult to diversify in Chinese capital market. In developed capital markets such as Hong Kong, over 80% of financial derivative instruments in international financial market have been introduced. In stock market, the trading of index futures, options and warrants is quite active with a trending of exceeding the trading of spot market. Hong Kong bond market is even more diversified. Based on three basic kinds which are bond, note and certificate of deposits of fund-raising tools, many more complicated derivatives such as floating rate bonds, variable rate bonds, convertible bonds, credit card receivables, and the current debt instruments traded on the Hong Kong Stock Exchange listing has been increased to 129.(20 09) On the contrary, despite of stocks, there are few more than five years investment instruments in mainland China capital markets. The trading of 1-5 year instruments is also confined so that the available trading instruments are quite limited. As an emerging market the risk of stock market is higher than normal, both systematic risk and market risk. The systematic flaws in Chinese stock market such as no trades of state owned and corporation owned stocks and lack of index futures  [1]  or other kinds of hedging instruments make the whole stock exchange system more uncertain. The strong influence of state policy changing is also a reason for high uncertainty. As for the market risk, stock market is in sharp adjustment since the end of 2007. On the one hand, the overall risk has lowered a little; it is still too high compared with the mature capital markets. On the other hand, the low self-control ability of the participants involved in stock market makes the unsystematic risk highe r than average. Investing only in stock market can not successfully diversify risk. Considering the incompleteness of Chinese warrant market, futures have been chosen to diversify risk. Chinese future market also started in 1990. After six years of cleaning up and reconstruction (1995-2000), future market is in good development. In 2002, stock market turned down, which made part of the stock market capital switch to future market and made it a hot deal. This situation is quite similar to what happened in 2007-2008. Chinese future market developed from first pilot reform to rectification and now has entered a new stage of stable development. The legal operation and market discipline have been significantly improved. These features make futures possible as a component of portfolio. At present, research of the role of futures in the portfolio is focused on index futures and its hedging properties, while the research of commodity futures is focused on its function of price discovering. Adding futures into ordinary stock portfolio has not been well discussed so that this article will research on the performance of portfolio with commodity futures to see whether futures can effectively diversify risk and raise the return. How to optimize investment portfolio becomes the first and most important question that investors need to consider. Thus, modern portfolio theory becomes quite widely applied in practice. Portfolio means investors allocate certain amount of money to different kinds of assets in order to gain as much as possible return or to get the lowest possible risk. II. Past literature review in portfolio selection theories In 1959, Markowitz published his paper named Portfolio Selection: Eficient Diversification of Investments, which conducted a pioneering study of optimizing portfolio in the security market. Ever since then, modern finance and investment decision making comes into a quantitative stage. Portfolio theory is a set of theories and methods to help investors choose certain types and allocate their money from varieties of instruments to form efficient portfolio. In Markowitz theory, mean-variance model can be applied to any class of financial assets, as long as its expected return and the correlation of each asset can be accurately estimated (Markowitz, 1959). In his model, mean represents the expected return of an asset and its risk is represented by the variance. In order to use the Markowitz mean-variance method, we need to find the expected rate of return and risk. However, considering the ineffectiveness of Chinese stock market, the simple mean-variance is not applicable. Thus, more app ropriate method of evaluating return and risk needs to be found. Among these different evaluating methods, people tend to agree using expected return as a representative of future earnings. The return of a financial asset is consisted of two parts: intertemporal cash flows and capital premium (asset price changes during the holding period). The return that this article is going to use is the daily logarithmic rate of return, so the intertemporal cash flows can be ignored. The yield can be expressed as: Because logarithmic rate of return can be simply added which facilitate the data processing by software and its value can be any real numbers, this article will use logarithmic rate of return as the evaluation of asset yields. The simplest way to get the expected rate of return is calculating its average. Its flaws are also quite obvious: the result is far from accurate. In order to find more accurate estimation, we need to fit time series data to appropriate model and find the unconditional expectation of asset return. In 1980s and 1990s, lots of literatures have discussed the predictability of stock market and suitable model of predicting asset returns. M.Hashem Pesaran and Allan Timmermann (1995) found that the predictable components of stock returns are highly correlated with business cycle and the magnitude of shocks influences the model more than expected. But because what they studied is a long term relationship in the stock market, the results can only be a consultation. As for the daily stock return, many researches suggest that it shows significant dependence on former returns. Vedat Akgiray found in his paper about the conditional heteroscedasticity in stock returns that the probability distribu tion of return lag of s days is dependent on return today for several values of s (1989). He used daily returns on the CRSP (Center for Research in Security Prices) value-weighted and equal-weighted index from January 1963 to December 1986 to find that GARCH (1,1) shows the best fit and forecast ability among the econometric models. Noticing that the return he used is also logarithmic rate, the features of logarithmic rate in this article can be expected to be just like that in his study. Similar results can be obtained from other literatures. There is a positive relation between the expected risk premium and the predictable level of volatility and a negative relation between unpredictable component of stock market risk and excess holding period return (K. R. French et al, 1987). Although they can not determine a certain model to describe the exact relation (difficult to choose between ARIMA and GARCH-M), the relation between return and risk is quite significant. Studies about Chinese stock market also show evidence of fitting stock return data in ARMA or GARCH models. The daily returns of Shanghai and Shenzhen index indicates significant ARCH effect and the data fit in GARCH-M model well (Hua Tian and Jiahe Cao, 2003). It is reasonable to choose ARMA or GARCH model to simulate the actual stock movement. But as for the measurement of risk there are comparably various methods. Markowitz explained the mean-variance theory in his 1959 portfolio selection paper which introduced the statistical concept of expectation and variance into the study of investment portfolio. Under a certain probability distribution of returns, he used the average deviation from the average return of all the random returns. Thus, risk can be quantified with the expectation of return as return expected and standard deviation as the measurement of risk. Although variance has some easy to use features such as simple calculating and easy understanding, it is only an approximate measurement of risk. Using variance needs the distribution to be systematic and does not take the investors different feeling about capital gain and loss into consideration. Given the same amount of gain and loss, the pain of loss is usually larger than the happiness of the capital earnings. Variance ignores this asymmetry while LPM (lower partial moments) would be a better measurement. Harlow proposed this new indicator as a more accurate way to describe risk (1991). LPM is an abbreviation of lower partial moment, which P (partial) stands for its measuring only one side of the returns compared with the fundamental rate and L (lower) stands for less than fundamental rate (downside risk). LPM is a risk measurement which meets the requirements of Von Neumann Morgenstern utility function and can cover almost all peoples risk preference. It shows a new way to describe risk apart from the traditional utility measurement which is the function of variance or the standard deviation. The expression of LPM is: , where n is called the order of LPM indicators, representing the risk aversion of investors, and z is called fundamental rate of return which is the minimum return that investors would accept. Different values of n would change LPM into different measurements of risk and therefore meet different investors risk preference, from risk preference to risk neutral, then risk aversion. One advantage of LPM is that it can show only the pain or loss possibility when the return is lower than the expected. The other is it can show what investors different risk preference can affect the feelings to the same asset by simply changing the order n. LPM is less popular in evaluating volatility than variance as the calculation of LPM is more complicated. Another reason is that LPM must be calculated separately for each variable while variance can be added or processed under certain assumptions. This means people need to program it in order to use LPM with computer data processing programs. On the contrary, all the data processing programs have a default function of calculating variance. The way to evaluating the performance of asset portfolios is its efficient frontier. Every combination of risky assets can be plotted in a risk-return space, and those combinations with the highest return under the same risk or with the lowest risk under same return are called efficient portfolios. Usually, the upper part of the curve which describes risk-return features of efficient portfolios is called efficient frontier. Ordinary efficient frontier of investment portfolio is calculated by Markowitzs mean-variance method. This article will use LPM to substitute variance to calculate efficient frontier which makes it more like investors thoughts of risk. Merriken suggested that variance and LPM are suitable for the study of short-term investment (1994), which is quite popular in Chinese capital market. Based on the review of the related literatures, this article will use econometric models to get expectation daily return of stock and futures and both variance and LPM to calculate efficient frontiers to see whether adding futures into stocks would improve the performance of portfolios. III. Theoretical study and empirical data results i. Theories of econometric models and multi-type asset portfolio The econometric models used to estimating the expected return and risk are ARMA and GARCH models depending on the features of different stock and futures time series. ARMA is an abbreviation of autoregressive and moving average model, which is typically used in estimating autocorrelated time series. As what is mentioned in the literature, auto-correlation in daily logarithmic return is shown by theoretical study, and the empirical study of the realistic data also suggests this result. Typical ARMA model is consisted of two parts: AR (auto-regressive) part and MA (moving average) part. It is normally notified as ARMA (p, q) where p is the order of autoregressive part and q is the order of moving average part. AR part is written as: , where are the parameters and is the error term (usually white noise). The value of p suggests how many lags of are regressed on and therefore is a measurement of autocorrelation. For the need of stays stationary, usually we need the absolute value of is less than unit. MA part is written as: , where are the parameters, is the expectation of , and is still the error term (usually white noise). The value of q suggests how many error terms are included in the smoothing process of average and MA process is always a stationary time series. Thus, ARMA model is written as: , which is a combination of autoregressive part and moving average part. The value of parameters is generally determined by the least square method which minimized the residual error term. The value of p and q is chosen to better fit the model without too much lags or smoothing terms. The method used in this article is through the value of ACF (autocorrelation function, which is used to determine the order of moving average) and PACF (partial autocorrelation function, which is used to determine the order of autoregressive part). In spite of autocorrelation, there are other special features of financial time series data such as fat tails, extreme values and volatility clustering. Simple ARMA models assume that the error term is independently and identically distributed which does not meet the fact. Thus, Engle (1982) posed ARCH (Autoregressive Conditional Heteroscedasticity) model to analyze this volatility feature of financial data. Four years later, T.Bollerslev improved this model and made it GARCH which is a generalized ARCH model. GARCH model is developed specially for financial data and is widely used in the study of volatility. In addition to the normal econometric model, people use GARCH to better analyze and forecast volatility. GARCH model can be written as: where the first equation is a simple ARMA model, but this time is not an independently and identically distributed normal error term. is an independently and identically distributed error term and is called conditional variance which is estimated by the third equation (also an ARMA model). and are independent of each other and the distribution of is not restricted as normal but can be changed to satisfy actual situation. This makes GARCH a more accurate model in estimating the expected rate of return and risk. Hiroshi Konno and Katsunari Kobayashi (1997) made an attempt to add bonds into ordinary stock portfolio to find a new way of allocating investment. Their purpose is to extend the mean-variance model normally used in optimizing stock portfolios to integrated bond-stock portfolios. At that time, big scale mean-variance models were restricted in stock portfolios although the computer technology and mathematical methods in financial engineering developed fast. Although bonds seem always to be considered separately when people intend to invest in financial market, Hiroshi and Katsunari still want to add bonds into portfolios. The reason is that before 1980s, the return of bond was far less risky than that of stock due to the stable interest rate. However, after 1980s, interest rate became much more volatile and investors bore heavily loss and huge risks. Actually, the volatility of bonds at that time was even higher than that of stocks. Considering this, combining bonds and stocks into the same portfolio is of great realistic meanings. The method they used is mean-variance and mean-absolute deviation models where variance and absolute deviation are as the different measurement of risk. The results are also quite satisfied as adding bonds into stock portfolios can increase the expected return under the same risk level. Never the less, Raimond Maurer and Frank Reiner in 2001 also used this idea of multi-type asset portfolio to discuss the possible outcomes of adding real estate securities into international asset portfolios under a shortfall risk frame. They noticed the fact that financial time series data had its own features and the tradition way of evaluating risk using variance can not reflect what investors think in the reality. Therefore, LPM was introduced as the way of measuring risk to reflect the asymmetry in the rate of return of asset. They compared the situation in Germany and in US by calculating the efficient frontiers of common portfolios, then calculating the efficient frontiers of adding real estate securities into portfolios. Because they studied between different countries, Raimond Maurer and Frank Reiner also calculated the effects of hedging. The results are also quite satisfied as the efficient frontiers move to the left, especially for those high risk-averse investors in Germany. Also, hedging could improve the performance of portfolios, especially for the US investors. With hedging they can build investment portfolios with higher rate of return under a relatively low risk level. But as mentioned above in the introduction part, there are few commercial bonds besides the government bonds; the only possible type of asset besides stocks that can be added into investment portfolios is futures. This article will also calculate the efficient frontiers of stocks, futures and combined portfolios separately, using both variance and LPM as the measurement of risk. As to the number of assets that should be held in one portfolio, investors have different opinions. Most mutual funds in the US market hold more than 100 stocks. Although these over-sized investment portfolios may well diversified risks, the expected return can be just acceptable as higher operational fee are needed to maintain such a huge portfolio and these stocks usually contains some low return ones. Xianyi Lu (2006) discussed this question that how many stocks are suitable for Chinese investors to hold in a single portfolio. He constructed portfolios with different number of stocks to compare their risk-return performance. The measurement of risk he used is variance. He came to the conclusion that 20 stocks would be enough to diversify most of the risk. The close-up price of stock is quite easily obtained while to find suitable closing price of futures is somewhat tricky. Futures are contracts which specify certain quantity and quality of fundamental assets between two parties to trade at a specified date in the future with a price agreed today. Thus there can be various contracts with the same kind of fundamental asset in different delivery date. Considering the trading characteristics of Chinese future market, Chengjie Ge and Yong Liang from a Chinese fund called Guotai Junan tried to construct a continuous future contract to get the daily closing price in 2008. When a contract first comes into market, the transactions are quite few. One contract is traded most actively just three or four months before delivery date, as the coming of specified date the trading volume begins to fall quickly. Those investors, especially the speculators would only trade those contracts that so-called à ¢Ã¢â€š ¬Ã…“dominant contractà ¢Ã¢â€š ¬?. Thu s, each future contract is in good liquidity only for a short time period. A continuous future contract is selecting the most actively traded contract of same fundamental asset at the same time to form a new, artificial contract to get the continuous price time series of one asset. ii. Data collection and analysis This article uses daily closing price of stock and futures from the time period 04/01/2007 to 31/12/2008. The data is obtained from RESSET database  [4]   Futures chosen are copper, aluminum, rubber and fuel oil from Shanghai Future Exchange, corn and soybean meal from Dalian Future Exchange and cotton and wheat gluten from Zhengzhou Future Exchange. In order to get daily return we need to construct continuous future contracts by selecting the most active contracts. As to the 8 futures used in this article, the most active contracts of wheat gluten, soybean meal, cotton, fuel oil and corn are those contracts with delivery date four months before the current month (not accounting current month); the most transacted contracts of rubber, aluminum and copper are those with delivery date two months before the current month (still not accounting current month). For example, current time is 19970201, so the contract which should be selected for cotton is the 199705 contract whose delivery month is May 1997. When it comes to 19970301, the contract selected for cotton should be 199703, and so on, so forth. After constructing eight continuous future contracts, we can get the time series of close-up price. The calculation of logarithmic rate of return, variance and LPM is just like the stock data. Table 1 shows the descriptive statistics of futures like the mean, the standard deviation, and some others. As the bond market is not mature in China, the risk free rate that used in this article is the three-month central bank bill rate which is also from the RESSET database, same database as the closing price of stocks and futures. From the statistics in the table we can find that the logarithmic daily return of futures shows asymmetry and fat tails, far from the assumption of mean-variance model that the distribution of returns should be normal distribution, or at least a symmetric bell-shaped distribution. Thus, using variance or standard deviation or any other kind of symmetric statistics would be less accurate. Fitting data into econometric models should provide a better estimation of expected rate of return and risk. Table 2.1-2.4 and Table 3.1-3.3 show the estimation of coefficients using ARMA and GARCH models. The models of stock returns are mostly ARMA models, but of futures are half GARCH models and half ARMA models. Table 2 is the results of future data and table 3 is the results of stock data. From the table we can see that there are four futures which are better fit in GARCH models and for the other four, ARMA is enough as the residual series after ARMA does not show significant heteroscedasticity in error terms. As for stocks, none of the 19 stock time series show significant heteroscedasticity which means ARMA could describe the features of stock price series. One interesting finding is that only 11 stock price time series show the correlation effect while the other 8 stock price series seem to be random walk. Table 2.1 and Table 2.2 are the GARCH results of future returns. Cotton, soybean meal, aluminum and copper show significant auto correlated heteroscedasticity. The basic model that used to estimate the return is ARMA model, and the first two lags show the most correlation with current logarithmic rate of return. The null hypothesis for all the coefficient in the model is the coefficient equals zero. The constant terms in the models are not significant despite that of soybean meal whose p-value is 0.0202, which means we can reject the null hypothesis under a 5% confidence level. The reason for not able to reject the null hypothesis of constant terms equaling zero may be the absolute value of daily logarithmic rate of return is too small, usually under 0.01. In such a low level the normal test to calculating p-value may become not suitable. So the value of constant terms is still used in the ultimate model to calculate the estimation of expected return although we can not reject the po ssibility that it actually equals zero. Table 2.3 and Table 2.4 show the ARMA results of future returns. Wheat gluten, corn, fuel oil and rubber daily logarithmic rate of return are estimated by ARMA model. The null hypothesis is also that any coefficient equals zero with p-value stands for the probability of making mistakes when rejecting the null hypothesis. The problem is the same with that of GARCH models as the p-values are too large to reject. But still we accept this result and make forecast using the present model. In spite of the not-so-satisfying results in the constant term, the coefficients of AR term and MA term are quite significantly different from zero which can be tell from the p-values. This is also true in futures GARCH model and stocks ARMA models. The significance of correlations in logarithmic rate of return series matches the features of financial time series and is what we would like to expect when estimating these coefficients. There are 19 stock return series to be modeled, but only 11 of them shows autocorrelation with their lags. None of these shows significant heteroscedasticity in the error terms so the model chosen is ARMA model. The constant terms of each stock return model is smaller than that of future return model, and the p-value is bigger than 0.05 as expected. The current return of four stocks out of this eleven shows significant correlation with the six and seven lags, showing the existence of cycle effects in the stock market. For these four stocks, what happened in the week before affects the price of this week more compared with other time. Other seven stocks show the ordinary one or two lags correlation. The coefficients of AR and MA part are also of great significance and the null hypothesis can be rejected. For those 8 stocks which do not show the existence of autocorrelation, the processing method is to calculate the basic descriptive statistics such as mean and variance. This method may ignore the asymmetry and fat tails of the data, but as there is no good econometric model to estimate random walk series, this simple way has its own advantage and also of quite high accuracy in estimating the expected rate of return and risk. This article use the forecast value of each model as the expected rate of return, and the variance of the sample as the expected risk for the mean-variance model of investment portfolios. For those 4 GARCH future models, the expected risk is the forecast value of the error part model. As for those eight stocks whose logarithmic daily return series are random walk, simply use the mean as the expected rate of return and the variance as the expected rate of risk. LPM1 is using the three-month central bank bill rate as fundamental rate of return because of its risk-free characteristic. The mean-LPM model also uses the results of expected rate of return from the forecast of GARCH and ARMA models as the only change in this new model is the risk measurement from variance to LPM. Someone may argue that different econometric models could cause different estimation of expected rate of return, thus the results of efficient frontiers become not so convincing. The purpose of this article is to compare the efficient frontiers of different asset portfolios, trying to find the possible improvement of adding futures into the ordinary stock portfolios. The econometric estimation is used to construct Markowitzs mean-variance model. What can be seen from Table 2 and Table 3 is that most of the assets can be fitted into ARMA model. As a matter of fact, because the absolute value of daily logarithmic rate of return is too small, the difference of constant terms between GARCH and ARMA model for the same asset is very small that can be ignored. The calculation of efficient frontiers is using MATLAB financial tool box, and the original data is what has been done above. After calculating the correlation coefficient matrix of 19 stocks and 8 futures, there is not much correlation of each asset. In fact, most of the correlations coefficients are between 0.1 to 0.3, with some of them even to be negative correlated. It suggests that the risk diversify of investment portfolios should successful using these 27 assets according to the statement of Markowitz. 8 futures portfolio Stock and future portfolio (The green line is the efficient frontiers of 19 stocks portfolio, the purple line (in the middle) is of 8 futures portfolio and the blue line is of the mixed stock and future portfolio.) Compared these three efficient frontiers, we can find that adding futures into the ordinary stock portfolio can greatly improve the performance of portfolios, which is even greater under lower risk level. Single future portfolio also performs well compared with single stock portfolio as it can offer higher rate of return under the same risk level. From Figure 1 we can find with the same expected return of 0.4ÃÆ'—10-3, the mixed stock and future portfolio can reduce the risk from 0.012 of single stock portfolio to less than 0.006. This more than fifty percent of risk reduction shows great practical meaning of multi-type asset investment portfolios. Figure 2: the efficient frontiers of stock, future and mixed portfolios using mean-LPM model Figure 2 shows the same results as the Figure 1. The mixed stock and future investment portfolio can improve the risk-return performance of portfolios. Similarly, future portfolio performs much better than stock portfolio, and it can greatly raise the expected return under higher risk level. The mixed portfolios improvement is mainly under low risk level, as the risk becomes bigger, the performing difference between future portfolio and mixed portfolio are not so significant, for the efficient frontiers overlap each other. The efficient frontiers are straight lines in Figure 2 while they are curves in Figure 1. The different risk measurement may result in this. Because LPM only calculates the downside risk, the risks of the portfolios which provide same return are not the same. Every single LPM must be calculated separately. So the shape of the new efficient frontiers may look different from the traditional hyperbola-shaped curves in mean-variance models. Both the mean-variance model and the mean-LPM model show that only investing in stock market can not get as much return as investing only in future market under the same risk level because the efficient frontier of stock portfolio is to the right of that of future portfolio and the distance between the two efficient frontiers is quite large. It reveals a fact that investing only in stock market can not guarantee ideal revenue. Although twenty years has passed since the establishment of

Elements that make up Winning Teams Essay -- essays research papers

Every person within any team wants to feel they are part of a winning team, and that they are contributing to its success and the success of the company. For teams to able to do this, personnel must be able to work together, be committed to the team's goal, to encourage formal and informal interactions and instill that winning attitude. For teams to be able to achieve this, certain attributes must be instilled within any team. As defined in the Oxford Dictionary loyalty is, ?steadfast in ones allegiance to a person.? This can come in many forms, whether it?s loyalty to your partner, your favourite sporting team or as in this case the Company. Managers must be able to trust their employees. Giving responsibilities and passing on relevant information pertinent to any goal can instil trust and confidence and commitment from your employees. Without the fundamental tools, they will possibly feel that they are not contributing to the success of the team or company. If this happens then they may feel the Manager is not dependable and therefore loyalty will be eroded. The manager should never feel challenged about his authority, but should openly answer relevant questions regarding the Teams goal. Discussion should be encouraged, as by working through or discussing the situation in hand as it leads to the development of the person and an increase in their loyalty, as opposed to a person who keeps quiet an d does not question anything. Being honest and upfront to your workforce will help build up any trust. Being forthright with any news pertinent to the workforce can only bolster your loyalty from them. They would rather have the bad news from you, than hear it from an unknown senior manager who just sees them as a number... ...ed, the two Complete Finisher are on hand to ensure deadlines are met. The weakness of this team is:  · Lack of a team worker.  · Insufficient specialists (Minimum of two required)  · Insufficient Implementers  · If the Resource Investigator or Plant are away who will bring in ideas and make contacts from outside the team. The strength of this team is:  · Strong personalities  · Discipline  · Respect  · Commitment  · Loyalty to fellow team members In conclusion every person within the team has an additional role as indicated within the table. With these additional roles and the combination of experience developed with long careers, combined with a wealth of knowledge and completion of successful management courses, this team has a successful and winning formula, which can only lead to a better performance thus giving better customer satisfaction.

Ocean Carrier’s Case Essay

1) Do you expect daily spot hire rates to increase or decrease next year? According to the Case description, Exhibit 3 showed order booking and delivery schedule for bulk capsizes for coming years from 2001 to 2004. It was larger than the number of current fleet size in Exhibit 2. Thus, the spot hire rates would likely to decrease since capsizes are available. 2) What factors drive average daily hire rates? Daily hire rate were determined by the supply and the demand. From Exhibit 2, the existing capsizes carriers in terms of the sum of the loading ability. Factors of supply such as age and size of vessel, cost of repair and maintenance as well as demand factor such as market condition would affect daily rates. 3) How would you characterize the long-term prospects of the capsize dry bulk industry? According to Case description, availability of fleet in the market and availability of transports good drives average daily hire rates. The daily hire rates would increase if ore exports from Australia and India starts in coming years. This would bring huge business trade. In absence of a new business, the average daily rates will decrease because of increasing number of fleet (demand is decreasing). There are about 2 million tons of capsize with age over 24 years. We will hope that these old vessels would be soon scrapped and this would reduce the supply of the capsize vessels. However, those old vessels were not a significant part of the total existing vessels. So we probably will not see a result that an obviously decreasing in supply because of the scraping of old vessels. In Exhibit3, the current order of new capsize vessels delivered in the coming 4 years. There will be a large supply of new capsize vessels from 2001 to 2003. This will increase the supply of capsize vessel in the future. 4) Evaluate the cost of the new capsize and forecast the expected cash flows. See OceanCariers4.xls 5) Should Ms Linn purchase the $39m capsize? Make 2 different assumptions. First, assume that Ocean Carriers is a US firm subject to 35% taxation. Second, assume that Ocean Carriers is located in Hong Kong, where owners of Hong Kong ships are notrequired to pay any tax on profits made overseas and are also exempted from paying any tax on profit made on cargo uplifted from Hong Kong. See OceanCarrier5.xls 6) What do you think of the company’s policy of not operating ships over 15 years old? This is a low-risk policy of company; this policy will save the company from uncertainty. At the same time, it will be not able to take advantage of returns on investment of vessels in the next years. This policy will not give a favorable outlook for investment.

Emily: A Case Study in Adolescent Development Essay

Abstract This case study details the developmental milestones of an adolescent girl named Emily. Emily is 12 years old and lives with her mother who is a single parent. According to many theorists and researches, because she is being raised by a single mother, Emily is an at-risk adolescent who may have trouble properly hitting developmental milestones along with her peers. After observing Emily in her natural environment, then spending time interacting with Emily and interviewing her mother Elizabeth, I found that Emily is a typically developing adolescent. Emily has developed before or along with her peers physically, cognitively, and psychosocially. Emily appears to be developing a healthy sense of independence and self concept. Finally, Emily is healthy and appears to be progressing through puberty at a normal rate. Emily: A Case Study In Adolescent Development Emily is a 12-year-old girl. Since birth she has lived with her mother Elizabeth in a small South Carolina town – population 60,000. She was an only child until three years ago when her brother Wade was born. Emily’s mother Elizabeth is a single mother. Emily has never met her own father but had grown close to Wade’s father, her step dad, when he died nine months ago from Hodgkin’s Lymphoma. Emily’s mother According to Milstead and Perkins (2010), a child’s family is central to their successful development. Their research suggests that children who are raised in non-traditional families are at a disadvantage is all areas of development as well as socioeconomically. This case study will examine typical physical, cognitive, and psychosocial milestone of adolescent children and if 12-year-old Emily has been negatively affected in these areas as a result of her living in a single parent home. LITERATURE REVIEW At 12 years old Emily is entering adolescence. It is during adolescence that puberty begins. The time of adolescence is a time of rapid changes and physical growth in children. Rapid growth occurs in the bones and muscles, changes in body shape and size occur, and sexual maturation begins, essentially ending childhood. Beginning with hormonal changes, including an increase in estrogen and progesterone, girls typically begin experiencing pubescent changes at the approximate age of eight. Soon after, the uterus and vagina begin to grow larger and girls begin to develop breast buds. Around the age of eleven, girls begin to develop pubic hair. Girls can expect their weight and height to increase during this time as well. As girls a girl’s body begins to prepare for menarche, their hips will become wider. The first menstrual period typically occurs around the age of twelve; however, this can happen earlier for some girls and much later for others. Puberty continues through the age of 18 as girls breasts fully develop and their first ovulation occurs (Berger, 2011). In addition to sexual development during puberty, adolescents develop physically as well. A growth spurt occurs during adolescence where nearly every body part grows, most notably at different and uneven rates. According to Berger (2011), the fingers and toes of an adolescent grow longer before the hands and feet. The hands and feet grow longer before the arms and legs, and the arms and legs grow longer before the torso. It is not uncommon for an adolescent’s body to appear unsymmetrical. â€Å"One foot, one breast, or even one ear may grow later than the other,† (Berger, 2011, p. 393). The hormones responsible for puberty and growth spurts in adolescent girls are also responsible for emotional changes. It is not uncommon for girls experiencing these hormone changes to have sudden outbursts of anger, sadness, or even lust. Neurological changes occur as the â€Å"limbic system, responsible for intense fear and excitement from the amygdale, matures before the prefrontal cortex, where planning ahead, emotional regulation, and impulse control occur,† (Berger, 2011, p 400). These neurological changes often lead adolescents to throw caution to the wind, especially in social situations. Adolescents are more likely to act impulsively. Their impulsive behaviors coupled with their increase in hormones and interest in  sexual activities puts adolescents at risk for sexual abuse and early pregnancy (Berger, 2011). During adolescence, physical and hormonal changes aren’t the only changes occurring. Brain maturation also occurs and cognitive growth increases. Adolescent children will experience increased independence, a heightened sense of self-consciousness, the ability to think more abstractly. According to Swiss developmental psychologist and philosopher, Jean Piaget, adolescents develop the ability to use abstract logic, in contrast to children in early and middle childhood who primarily only have the ability to think in concrete terms (Goncu, & Abel, 2011). In addition, during adolescence, identity struggles often begin. Developmental psychologist and psychoanalyst, Erik Erickson, described this stage of development as identity versus role confusion. According to Erickson, an adolescent’s mission during this state is to unearth who they are as individuals, apart from their families and as members of society at large. Futile navigation of this stage, according to Erickson, results in role confusion and upheaval. Adolescents develop a sense of personal identity through many avenues including religion, politics, natural abilities, and gender. Merging childhood events, social ideals, and their distinctive ambitions, identity is developed. However, according to Erickson, adolescents seldom reach identity and role confusion is more probable (Boddington, 2009). OBSERVATION AND INTERACTION Emily is attending a birthday party for one of her peers at school. The party is being held at a local church, in the church’s social hall. According to Emily’s mother this is not the first birthday party that Emily had attended where both boys and girls are present; however, it is the first co-ed party that she has attended since she began showing an interest in boys. Most of the girls are wearing dresses and shoes with modest heels; their hair perfectly tended to with hints of gloss on their lips and blush on their cheeks. Emily wears blue jeans, a blue and white stripped long sleeved shirt and boat shoes. Her normal blond curls have been flattened with a straightening iron, according to her mother. Emily likes her hair better  straight and she hates dresses. Emily is tall, standing at 5 feet 6 inches tall. She weighs 150 pounds. Her body is well proportioned and she does not appear to be overweight. Emily has developed breasts and she has the appearance of some acne on her chin and forehead. The overhead fluorescent lights are dimmed in the social hall but the area is lit well with blue, red, and green lights which flash in sync with the music playing over a pair of large speakers. A DJ encourages the 28 eleven and twelve year olds to join the only two boys on the dance floor. The room is divided. Girls stand near a row of metal folding chairs lining a wall. The boys gather near a stage on the far end of the room. Emily’s mother Elizabeth is also attending the party as a chaperone. Elizabeth motions for Emily to come to her three times during a thirty minute period in an effort to encourage Emily to join the others on the dance floor. Each time Emily ignores her mother’s encouragements. The third time Emily’s eyes grow wide and from across the room she mouths the word â€Å"stop† to Elizabeth. Nearly an hour into the party, the girls scream with delight when a popular song begins to play and several rush to the dance floor. Emily rushes to the dance floor with a number of other girls and they begin to dance to the music. Song after song, Emily and her group of friends stay on the dance floor. They stop occasionally to chat with one another but never leave the dance floor. Emily dances and laughs with her female friends for nearly an hour before the group is called to have birthday cake and watch as the birthday girl opens presents. While the children are eating Emily socializes with both her female and male friends. She is particularly friendly with a male named Dawson. The two stand beside one another and talk while their friend opens her birthday presents. She playfully hits him on the arm six times during their exchange. She blushes as he playfully hit her back. Soon the group of adolescents is back on the dance floor for another half hour of dancing before the party is over. This time both the boys and girls are on  the dance floor together. Emily dances alongside both her female and male friends for the remainder of the party. As the party comes to close, Emily hugs each one of her female friends’ goodbye as they leave. When Elizabeth summons Emily to leave the party, Emily shouts out to Dawson, telling him goodbye. On Sunday afternoon, Elizabeth welcomes me to spend time with Emily in the family’s home. Emily’s family lives in a modest three bedroom, two bath house in a popular neighborhood on the North side of town. Their large fenced in back yard is filled with bright colored, plastic play-things belonging to Emily’s younger brother Wade. Emily’s purple Next bicycle leans against a wall in the home’s garage. The bicycle is much too small for her growing stature and Emily readily admits that she hasn’t ridden the bike in at least a year. Nothing else in the yard or garage suggests that a young girl live there but inside the home tells a different story. On the kitchen counter lays a knotted green ribbon with long blonde hairs tangled within the knot. Emily explains that she wore the ribbon on St. Patrick’s Day this year because she had no other green in her wardrobe. Lying on the family couch is a blue and purple fleece blanket and a fuzzy heart -shaped fuchsia pillow donning the words â€Å"Drama Queen.† It’s Emily’s favorite pillow. The floor in the living area is scattered with green toy tractors and an incomplete train set. Leaving the living area and entering the long narrow hallway, Emily’s bedroom is the first room on the left. Her doorway stands open but a handmade foam door hanger hangs from the door knob reading â€Å"Do Not Enter.† Emily’s room is pink and while with accents of black and grey. Her hot pink sheets peek out from under the wrinkled black and white polka dot comforter on her bed. Her bedroom walls are adorned with pictures of her favorite singers, Cody Simpson and Selena Gomez. A large bean bag chair takes up much of the floor space in her bedroom. A large bookcase runs nearly the length of one wall while a keyboard and microphone stand sit against the opposite wall. Emily loves to sing and often spends a great deal of her time singing along with her favorite musicians on her karaoke machine. A framed piece of child-drawn art hangs to the right of her bed. Emily says she completed the work in third grade. It depicts a boy who is seemingly stuck inside of a glass bottom room. Emily explains the technique  she used is called foreshadowing. When asked if it has an underlying leans, Emily whips her hair and nonchalantly replies that it does not. Emily is welcoming and excited to show off her space and her things, including her three dance trophies and her second place youth photography ribbon she won at last year’s South Carolina Festival of Flowers. Emily is creative and has an artistic side through her love of music, photography, drawing and painting, and dance. I inquire more about Emily’s art work and she pulls from her closet several pieces of art work sandwiched between two pieces of cardboard. She carefully pulls out several pieces of art and tells me how old she was when she completed it. Before we can finish, Emily’s phone alerts her that she has a text message. For the next 15 minutes Emily sends and receives text messages from her cell phone. She tells me that she is discussing an upcoming school trip to Philadelphia with her friend Jenny. They are discussing room arrangements. After texting with Jenny, Emily shows me information she has printed from the internet pertaining to her trip to Philadelphia. Emily says she is excited about the trip as she has never been away from home for more than two or three days at a time. She will be in Philadelphia for six days. Emily says she cannot wait to go and excitedly explains how she will be staying in a hotel room with three of her female friends, without an adult. Emily explains that the girls will stay on the third floor of the hotel while the boys will stay on the second floor. Emily receives another text message just as I am leaving. She says goodbye without looking up from her cell phone. INTERVIEW Elizabeth is a thirty-two year old mother of two. She gave birth to Emily at the age of nineteen. Emily was born December 10, 1999 by cesarean section after a full term pregnancy. Emily’s mother Elizabeth reports no prenatal problems and no complications during labor. At birth Emily weighed seven pounds and eleven ounces. She was twenty one inches long. According to the Centers for Disease Control (2000) Emily’s weight put her in the thirty sixth percentile for newborns and her height put her in the ninety third percentile for newborns. As an infant, Emily was breast fed for seven months, according to Elizabeth. Elizabeth explains that as an infant, a  toddler, and a young child, Emily hit all of her developmental milestones early, including puberty which began for Emily around age nine. Emily’s father is not active in Elizabeth and Emily’s lives. Emily has never met her father. Elizabeth explains that Emily’s father attended college with her. They were casually dating when Elizabeth became pregnant. Emily’s father did not want anything to do with Elizabeth after she told him she was pregnant. After finding out that she was pregnant, Elizabeth quit school until she gave birth to Emily then quickly returned to finish her degree. Elizabeth obtained a four year degree in marketing from a local college when Emily was three. She now works for a major hotel chain as their director of communications. Elizabeth earns $43,000 annually. She has no other income. Elizabeth grew up in the Catholic Church but left the church as a teen. Today she is a member of a local Presbyterian church. Elizabeth considers herself an authoritative parent. She says that while she has great deal of expectations for her children, she also has a close and warm relationship with each of them. She says her relationship with Emily has become closer since Emily has begun middle school. Elizabeth believes that it is most important that her children trust her. She explains that she wants her children to feel as if they can talk to her about anything. Elizabeth expects Emily to perform well in school and says Emily has not ever been in trouble at school because Elizabeth does not tolerate disobedience, especially in school. Elizabeth believes she holds the three traits that she says make a great parent: she commands respect; she works constantly to ensure good communication with her children so that they trust her, and she has clear expectations of her children. Elizabeth says that if she were to give new parents three pieces of advice she would impress upon them how quickly time passes. â€Å"Enjoy every minute, and don’t take one second for granted,† she says. Elizabeth says she would also tell new parents to make sure they make time for themselves. Finally, Elizabeth says she would tell them to be honest with their children. â€Å"Share your life experiences with them. Tell them the things you did right and the things you did wrong. Tell them about the lessons you’ve learned. Children learn to respect you and trust you in that sense.† FINDINGS Emily is nine months shy of her thirteenth birthday. Emily is five feet, six inches tall. She weighs one hundred and fifty pounds. According to the Centers for Disease Control (2000), Emily’s height is greater than the ninety seventh percentile for height. Emily is at the ninety seventh percentile for weight. Although Emily is taller and heavier than more than ninety five percent of her peers, according to her mother, Emily has hit developmental milestones earlier than her peers since she was an infant. Furthermore, Emily is currently experiencing puberty, an expected occurrence at her age. She has developed breasts and she has had her first menstrual period. Emily is not sexually active, according to her mother and therefore she is currently not at risk for early pregnancy. Cognitively, Emily is progressing as a typical 12 year old girl. She displays eagerness to establish a sense of independence from her mother with her upcoming school trip to Philadelphia. She looks forward to being away from her mother, and proving to both her mother and herself that she is maturing in the ability to make her own choices. Emily’s cognitive development is also apparent in the choices she made when dressing and styling her hair for the birthday party she attended. Emily’s mother explained that Emily used a straightening iron on her hair because she was not fond of her naturally curly hair. This demonstrates that Emily has developed a sense of self-consciousness. Lastly, Emily’s psychosocial development is apparent in that Emily is working to develop her own identity. Although Emily’s friends wore dresses to the birthday party, Emily opted for blue jeans and boat shoes. Emily chose to wear what she was comfortable wearing instead of what social norms would have her wear. In addition, Emily knows what she loves. She immerses herself in her art, her music, and her photography. While her friends are participating in sports and trying out for cheerleading, Emily is comfortable in her own vocation and does not seem eager to change. SUMMARY Emily is a typically developing 12 year old girl. It does not appear that her physical, cognitive, and psychosocial development has been negatively affected by her growing up in a single parent home. While Emily’s development is far from over, for now she appears to be progressing well, and developing into a healthy, secure and socially responsible young woman. REFERENCES Berger, K. (2011). The Developing Person Through the Life Span, eighth ed. New York, NY: Worth Publishers. Boddington, E. N. (2009). _Cognitive Process of Development in Children_. Online Submission. Goncu, A., & Abel, B. (2011). The child’s conception of the world: A 20th-century classic of child psychology, Second Edition. Edited by Jean Piaget, Forward by Jacques Voneche. Rowman & Littlefield Publishers, Inc, Lanham, MD, 2007. pp. 432. Price:  £19.99, â‚ ¬31.48†¦ Infant & Child Development, 20(2), 246-248. doi:10.1002/icd.719 Milstead, K., & Perkins, G. (2010). Family Structure Characteristics and Academic Success: Supporting the Work of School Counselors. Academic Leadership (15337812), 8(4), 19. National Center for Desease Control and Prevention (May 30, 2000). CDC growth charts. Retrieved from http://www.cdc.gov/growthcharts/data/set1clinical/cj41c022.pdf.

Free Essays on Fiji

Geography Fiji is located in the South Pacific Ocean about two-thirds of the way from Hawaii to New Zealand, in the area of the world they call Oceania. Fiji consists of 332 islands, which 110 are inhabited. If you were to compare it to something in the U.S. It would be slightly smaller than the state of New Jersey. Officially known as the Sovereign Democratic Republic of the Fiji Islands. The Fiji Islands are an independent nation consisting of an archipelago surrounding the Koro Sea. The Fiji Islands are largely the product of volcanoes, sedimentary deposits and formations of coral. Viti Lever, the largest island, has an area of about 10,429 square kilometers and accounts for more than half of the Fiji’s land. There is a Mountain range by the name of Nakauvadia, that runs North and South. The highest peak being that of Mount Tomanivi which is 4,341 feet and was formerly called Mount Victoria. The main river systems the Rewa, Nauva, Sigatoka, and Ba all have their source in the central Mountain area. Fiji enjoys a tropical South sea maritime climate without great extremes of temperatures. At the capital Suva, the average summer high is 29 degrees C, and the winter low is 20 degrees C. The islands receive the most rainfall (120 inches in a year) during the months of November through march. Which is also the time for hurricanes, which are experienced about once every two years. Population As of July 2002 the total population of Fiji was 856,346 with 46.4% residing in urban areas with the remaining 53.6% in rural areas. Fiji has a relatively young population with about 55% below the age of 25 years of age. When you look at Fiji compared to one of its neighbors Australia, with a population of 19,546,792 you can see that Fiji is not very big at all. Australia is the biggest land mass and populated area in Oceania, when compared to Fiji, Australia is big, but compared to the other world continent... Free Essays on Fiji Free Essays on Fiji Geography Fiji is located in the South Pacific Ocean about two-thirds of the way from Hawaii to New Zealand, in the area of the world they call Oceania. Fiji consists of 332 islands, which 110 are inhabited. If you were to compare it to something in the U.S. It would be slightly smaller than the state of New Jersey. Officially known as the Sovereign Democratic Republic of the Fiji Islands. The Fiji Islands are an independent nation consisting of an archipelago surrounding the Koro Sea. The Fiji Islands are largely the product of volcanoes, sedimentary deposits and formations of coral. Viti Lever, the largest island, has an area of about 10,429 square kilometers and accounts for more than half of the Fiji’s land. There is a Mountain range by the name of Nakauvadia, that runs North and South. The highest peak being that of Mount Tomanivi which is 4,341 feet and was formerly called Mount Victoria. The main river systems the Rewa, Nauva, Sigatoka, and Ba all have their source in the central Mountain area. Fiji enjoys a tropical South sea maritime climate without great extremes of temperatures. At the capital Suva, the average summer high is 29 degrees C, and the winter low is 20 degrees C. The islands receive the most rainfall (120 inches in a year) during the months of November through march. Which is also the time for hurricanes, which are experienced about once every two years. Population As of July 2002 the total population of Fiji was 856,346 with 46.4% residing in urban areas with the remaining 53.6% in rural areas. Fiji has a relatively young population with about 55% below the age of 25 years of age. When you look at Fiji compared to one of its neighbors Australia, with a population of 19,546,792 you can see that Fiji is not very big at all. Australia is the biggest land mass and populated area in Oceania, when compared to Fiji, Australia is big, but compared to the other world continent...