VACUUM ASSIGNMENT Example | Topics and Well Written Essays - 2500 words - 1

VACUUM - Assignment Example were developed and used to meet the stringent demands on these semiconductor devices. However, the semiconductor films produced by these processes were not structurally equivalent t the bulk material and hence were not of device grade. The problem associated with vapor phase deposition processes was differential vapor pressure of different constituents. For example vapor pressure of Ga and As differs by as much as two orders of magnitude at temperatures useful for thin film deposition. Therefore, to achieve equal vapor pressure and hence equal flux of arrival of Ga and As on the substrate by thermal evaporation of separate As and Ga sources will require too stringent control on the temperature to be achieved [1]. Many research groups tried to overcome this limitation by innovative approaches. One remarkable approach by Collins et al [2] involved using two separate crucibles containing Ga and Sb to deposit films of GaSb onto a glass substrate by evaporating these substances. His basic idea was to exploit decrease in angular decrease in the flux and hence to place the substrate at an angular location with respect to the individual crucibles where the two atomic fluxes will be equal and hence a stoichiometric film will be produced. However, the films he could produce were polycrystalline. GÏ‹nter K. G. [3] tried to arrive at appropriate vapor ratio by control of the temperatures of the evaporating species and the substrate separately. However, he could also not produce quality ordered films. During those days (1960 s) it was not easy to characterize the condition of the substrate, the quality of the vacuum and the composition and crystallinity of the films. The researchers had to do electron-diffraction after growing the films and this was taking much longer. It was development of small mass spectrometers, auger electron spectroscopy and compact electron diffraction instruments which made it

How I will lead groups to become great teams Essay

How I will lead groups to become great teams - Essay Example As a member of the Large Learning Group, I noticed various issues that emerged in the process of our interaction and learning. To begin with there were various psychodynamic characteristics that emerged among the group members which are pertinent to any person with the ambition to lead and make decisions on large groups or team. The first lesson I learnt from the Large Learning Group is that it is pertinent for any group to define roles among the members. I will apply this strategy in my leadership program. I will begin by allocating roles to each member of the group; a process which will begin by identifying my roles and ultimately the roles of others. Allocation of roles is pertinent due to the fact that it allows the group members to focus on their specific duties and have a sense of direction. This process will be guided through proper communication and motivations as well as supervision in order to ensure that members follow direction and are enthusiastic in performing their duties. Proper communication also encompasses taking feedbacks from the group members in order to determine the challenges faced as they perform their duties and the development of solutions. Secondly, I also learned a common feature that existed between the Large Learning Group and the Peer Learning Group; the confirmation of authority. It is very crucial for any person aspiring to be a successful leader to be in a position to confirm his/her authority that is, it is imperative to determine and confirm your duties and responsibilities as well as the duties and the responsibilities of others. This step is arrived at by making agreements among the group members on each person’s responsibility as it will ensure that there are proper intra-group relationships and a harmonious flow of actions. As a leader, I am going to apply this strategy to ensure that the possibility of occurrence of conflicts is reduced and that

Stock Market Performance and Economic Activity Relationship

Stock Market Performance and Economic Activity Relationship Introduction The debate of whether stock market is associated with economic growth or the stock market can be served as the economic indicator to predict future. According to many economists stock market can be a reason for the future recession if there is a huge decrease in the stock price or vice versa. However, there are evidence of controversial issue about the ability of prediction from the stock market is not reliable if there is a situation like 1987 stock market crashed followed by the economic recession and 1997 financial crises. (Stock market and economic growth in Malaysia: causality test). The aim of the study is to find the relation between the stock market performance and the real economic activity in case of four countries The UK, The USA, Malaysia and Japan. With my limited knowledge I have tried to find out the role of financial development in stimulating economic growth. A lot of economists have different view about stock market development and the economic growth. If we focus on some related literature published on this topic one question arises: Is economic development is affected by stock market development? Even though there are lots of debate on some are saying that stock market can help the economy but the effect of stock market in the economy especially in the economy is very little. Ross Levine suggested in his paper published in 1998 that recent evidence suggested stock market can really give a boom to economic growth. (REFERENCE) It is not really possible to measure the growth by simply looking at the ups and down in the stock market indicator and by looking at the rates of growth in GDP. A lot of things can cause in the growth of stock market like changes in the banking system, foreign participation in the in the financial market may participate strongly. Apparently it seems that these developments can cause development of stock market followed by the good economic growth. But to check the accuracy one required to follow an appropriate method which would meaningfully measure whether stock price is really effecting the economic growth or not? In my work I have tried to find out the co integrating relationship between Stock price and GDP and tried to check if there is a long run and short run relationship between the stock price and GDP. The method used for the studies is Engle Granger co integration method. To do this I have used ADF (Augmented Dickey Fuller Test) to check for the stationary behaviour of the variables and then I have performed the Engle Granger Engle Granger co integration method followed by residual based error correction model. To check for the short run relationship I have used 2nd stage Engle Granger co integration method. To check the causal effect of the four countries stock market and economic growth I used Granger Causality Method. In this paper I have reviewed some studies of scholars which I have discussed on the literature review part. This paper contains five parts Part two is about the literature based on the past wok of scholars. Part Three discussed about the Data. Part four is about the methodology, Results are discussed on part five and part six is all about the summary and conclusion of the whole study. In my work I have founded there is no long run relationship between stock market and economic growth in all four countries. In addition there is no causal relation between stock index yield and the national economy growth rate. The empirical results of the thesis concludes that the possibility of seemingly abnormal relationship between the stock index and national economy of these for countries. Literature Review: Stock market contributes to economic growth in different ways either directly or indirectly. The functions of stock market are savings mobilization, Liquidity creation, and Risk diversification, keep control on disintermediation, information gaining and enhanced incentive for corporate control. The relationship between stock market and economic growth has become an issue of extensive analysis. There is always a question whether the stock market directly influence economic growth. A lot of research and results shows that there is a strong relationship between stock market and economic growth. Evidence on whether financial development causes growth help to reconcile these views. If we go back to the study of Schumpeter (1912) his studies emphasizes the positive influence on the development of a countrys financial sector on the level and the potential risk of losses caused by the adverse selection and moral hazard or transaction costs are argued by him how necessary the rate of growth argues that financial sectors provides of reallocating capital to minimize the potential losses. Empirical evidence from king and Levine (1983) show that the level of financial intermediation is good predictor of long run rates of growth, capital accumulation and productivity. Enhanced liquidity of financial market leads to financial development and investors can easily diversify their risk by creating their portfolio in different investments with higher investment. Demiurgic and Maksimovic (1996) have found positive causal effects of financial development on economic growth in line with the ‘supply leading hypothesis. According to his studies countries with better financial system has a smooth functioning stock market tend to grow much faster as they have access to much needed funds for financially constrained economic enterprises by the large efficient banks. Related research was done for the past three decades focusing on the role of financial development in stimulating economic growth they never considered about the stock market. An empirical study by Ming Men and Rui on Stock market index and economic growth in China suggest that possible reason of apparent abnormal relationship between the stock Index and national economy in china. Apparent abnormal relationship may be because of the following reason inconsistency of Chinese GDP with the structure of its stock market, role played by private sector in growth of GDP and disequilibrium of finance structure etc. The study was done using the cointegration method and Granger causality test, the overall finding of the study is Chinese finance market is not playing an important role in economic development. (Men M 2006 China paper). An article by Indrani Chakraborti based on the case of India presented in a seminar in kolkata in October, 2006 provides some information about the existence of long run stable relationship between stosk market capitalization, bank credit and growth rate of real GDP. She used the concept of the granger causality after using both the Engle-Granger and Johansen technique. In her study she found GDP is co-integrated with financial depth, Volatility in the stock market and GDP growth is co integrated with all the findings the paper explain that the in an overall sense, economic growth is the reson for financial development in India.(Chakraboty Indrani). Few writers from Malaysia found that stock market does help to predict future economy. Stock market is associated with economic growth play as a source for new private capital. Causal relationship between the stock market and economic growth which was done by using the formal test for causality by C.J. Granger and yearly Malaysia data for the period 1977-2006. The result from the study explain that future prediction is possible by stock market. A study focused on the relationship between stock market performance and real economic activity in Turkey. The study shows existence of a long run relationship between real economic activity and stock prices†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Result from the study pointed out that economic activity increases after a shock in stock prices and then declines in Turkish market from the second quarter and a unitary (Turkish paper) An international time series analysis from 1980-1990 by By RAGHURAM G. RAJAN AND LUIGI ZINGALES shows some evidence of the relation between stock market and economic growth. This paper describes whether economic growth is facilitated by financial development. He found that financial development has strong effect on economic growth. (Rajan and Zingales, 1998) The study of Ross LEVINE AND SARA ZERVOS on finding out the long run relationship between stock market and bank suggest a positive effect both the variables has positive effect on economic growth. International integration and volatility is not properly effected by capital stock market. And private save saving rates are not at all affected by these financial indicators. (Levine and Zervos 1998) Belgium Stock market study with economic development shows the positive long run relationship between both the variables. In case of Belgium the evidences are quiet strong that Economic growth is caused by the development of the stock market. It is more focused between the period 1873 and 1935, basically this period is considered as the period of rapid industrialization in Belgium. The importance of the stock market in Belgium is more pronounced after liberalization of the stock market in 1867-1873. The time varying nature of the link between stock market development and economic growth is explained by the institutional change in the stock exchange. They also tried to find out the relationship to the universal banking system. Before 1873 the economic growth was based on the banking system and after 1873 stock market took the place. (Stock Market Development and economic growth in Belgium, Stijin Van Nieuwerburg, Ludo Cuyvers, Frans Buelens July 5, 2005) Senior economist of the World Banks Policy research department Ross Levine has discussed about Stock market in his paper Stock Markets: A Spur to economic growth on the impact of development. Less risky investments are possible in liquid equity market and it attracts the savers to acquire an asset, equity. As they can sell it quickly when they need access to their savings, and if they want to alter their portfolio. Though many long term investment is required for the profitable investment. But reluctance of the investors towards long term investment as they dont have the access to their savings easily. Permanent access to capital is raised by the companies through equity issues as they are facilitating longer term, more profitable investments and prospect of long term economic growth is enhanced as liquid market improves the allocation of capital. The empirical evidence from the study strongly suggests that greater stock markets create more liquidity or at least continue economic gro wth. (Levine. R A spur to economic Growth) Another paper was focused on the linkages between financial development and economic growth using TYDL model for the empirical exercises by Purna Chandra Padhan suggests that both stock price and economic activity are integrated of order one and Johansen-Juselias Coin-integration tests for this study found one co integrating vector exists. It is proved by the spurious relation rule in this study the existence of at least one direction of causality. He described that bi-directional causality between stock price and economic growth meaning that economic activity can be enhanced by well developed stock exchange and vice-versa. ( Title:  The nexus between stock market and economic activity: an empirical analysis for India Author(s): Purna Chandra Padhan Journal: International Journal of Social Economics Year: 2007 Volume: 34 Issue: 10  Page: 741 – 753 DOI: 10.1108/03068290710816874 Publisher: Emerald Group Publishing Limited) Chee Keong Choong (Universiti Tunku Abdul Rahman Malaysia) Zulkornain Yusop (Universiti Putra Malaysia) Siong Hook Law (Universiti Putra Malaysia) Venus Liew Khim Sen (Universiti Putra Malaysia) Date of creation: 23 Jul 2003 tried to find out the importance of the causal relationship of Financial development and economic growth. The findings of their study usin autoregressive Distributed lag (ARDL) describes about the positive long run impact on economic growth Granger causality also suggest same results. However, another study on Iran by N. Shahnoushi, A.G Daneshvar, E Shori and M. Motalebi 2008 Financial development is not considered as an effective factor to the economic growth. The study was focused on the causal relationship between the financial development and economic growth. Time series data used for the study from the period 1961-2004. Granger causality shows there is no co integrating relationship between financial development and economic growth in Iran only the economical growth leads to financial development. Establishing link between savings and investment is very much important and financial market provides that. Transient or lasting growth is the ultimate affect of the financial market. Economic growth can be influenced by financial market by improving the productivity of the capital, Investment to firms can be channelled and greater capital accumulation by increasing savings. To ensure the stability of the financial market potential regulation is important due to asymmetric information, especially at the time of financial liberalization. (Economic Development and Financial Market Tosson Nabil Deabes Moderm Academy for technology aand computer sciences; MAM November 2004 Economic Development Financial Market Working Paper No. 2 ) Data: The empirical analysis was carried out using the quarterly data for The UK, The USA, Japan and Malaysia. The data were collected from the DataStream for the period 1993I to 2008III. Economic growth is measured as the growth rate of gross domestic product (GDP) of each country with the help of stock prices SP. For the software processing I used Eviews 6.0 for the planned regression in order to get the results. The empirical analysis is done from the quarterly data from the stock market indices and the and the GDP between the first quarter of 1993 and the fourth quarter of 2008. All the data has been extracted from the data stream and expressed in US$. The data for Japan share price is from Tokyo Stock Exchange. Malaysias Share price is form Kuala Lumpur Composite Index, UKs is from UK FT all share price index and USA share price is taken from the DOW Jones industrial share price index. The nature of the Data is series used for the time series regression. List of Variables: UGDP UK GDP USP UK Share price LUGDP Log of UK GDP LUSP Log of UK Share price USGDP USA GDP USSP USA (DOW Jones) Share price LUSGDP Log of USA GDP LUSSP Log of USA Share price MGDP Malaysia GDP MSP Malaysia Share price LMGDP Log of Malaysia GDP LMSP Log of Malaysia Share price JGDP Japan GDP JSP Japan Share Price LJGDP Log of Japan GDP LJSP Log of Japan Share price Methodology: Engle and Granger (1987) first established the cointegration method. It is a method of measuring long term diversification based on data. Linear combination of two non stationary series shows that they are integrated in order one I(1) that is stationary. And this is a co integrated series. Cointegration Long term common random trend between non stationary time series. The linear combination of both the nonstationary series can be stationary if both the variables are integrated in same order. Cointegration is a very powerful approach in the long term analysis because a common stochastic trend is shared in cointegration that mean two series will not drift separately too much. They might deviate from each other but in the long run but eventually the will revert back in the long run. If there is very low correlation between the series still the series can be co-integrated as high correlation is not implied in cointegration. The reason for choosing the method as it will allow us to check the move between the variable in the long run even there might be a divergence in the short run. The first step in the analysis is check each index series whether the series for the presence of unit root which shows whether the series is non stationary. The method that I followed to do this is Augmented Dickey Fuller Test (ADF). I proceed the Granger cointegration technique 1987 when the stationary requirements are met. Cointegration long term common stochastic trend between nonstationary time series. If non-stationary series x and yare both integrated of same order and there is a linear combination of them that is stationary, they are called cointegrated series. A common stochastic trend is shared in Cointegration. It follows that these two series will not drift apart too much, meaning that even they may deviate from each other in the short-term, they will revert to the long-run equilibrium. This fact makes cointegration a very powerful approach for the long-term analyses. Meanwhile, cointegration does not imply high correlation; two series can be co integrated and yet have very low correlations. Cointegration tests allow us to determine whether financial variables of different national markets move together over the long run, while providing for the possibility of short-run divergence. The first step in the analysis is to test each index series for the presence of unit roots, which shows whether the series are nonstationary. All the series must be nonstationarity and integrated of the same order. To do this, we apply both the Augmented Dickey-Fuller (ADF) test. Once the stationarity requirements are met, we proceed Granger bivariate cointegration (1987) procedure. 30 International Research Journal of Finance and Economics Issue 24 (2009) Series Stationary Test: In this study I have used Augmented Dickey Fuller Test (ADF) to test the stationarity of variables. ADF is test for unit root where I have checked the Unit root and strong negative numbers of unit root is being rejected by the null hypothesis (level of significance). The following regression for the unit root test in Eviews: Is the white noise error tem. Is the difference operator. , () () Here with the test we can find the estimates of are equal to zero or not. Y is said to be stationary if the cumulative distribution of the ADF statistics by showing that if the calculated ratio of the coefficient is less than the critical value according to Fuller (1976). If we accept the Ho the sequence is predicted to be having unit root and if Ho is rejected then we can say that the series doesnt have unit root. This proves that the series is stationary. The co –integration test can only be performed if both the sequences are all integrated of order I (1). Cointegration Test: According to Engle and Granger (1987) to check for cointegration if both the variables and are integrated with order one the proposed method for cointegration residual-based test for cointegration (Engle-Granger method). So from the above method we can find the equation By regressing with And after that and is denoted as the estimated regression coefficient vectors. Then, = – is representing the estimated residual vector. If the residual is itegrated with zero that means the series for the residual is stationary, and and are then co integrated. An in this situation (1, -) is called co-integrating vector. Therefore is a co integrating equation, so, from it we can say that there is long run relationship between and. Granger causality test: Granger causality test is applied if the relationship is lagged between the two variables to determine the direction of relation in statistical term. It gives information about the short term relationship between the variables. In terms of conceptual definition causality is consist of different ideas, this concept produce a relation between caused and results were agreed upon. Aristo defines that there exist a link between causes and results and without causes these results are impossible. And this strong relationship. Some economists believe that the idea of causality is the mix of both theoretical and explanation and statistical concept. The frontline operational definition of causality is given by some economist, but Granger is the one who provided the information to understand it correctly and completely. Granger s operational causality definition depends of below hypotheses, Next cannot be the reason of past. 1. Next cannot be reason of past. Certain causality is possible only with past causes present time or future time. Cause is always to be come true before the result. In addition, this makes time lagged between causes and results. 2. Causality can be determined only stochastic process. It is not possible to determine the causality between two deterministic processes. After 1990s, Granger and Engle contributed to time series literature importantly. On these developments about time series analysis, some variations were done with Granger Causality test. According to this, possible long-term relationship would be tested and if 20 variables were co-integrated, long-term regression error equation s lagged value would be included in Granger Error Correction model as error correction term. Thus, Granger Causality test should be applied. If there is no co-integration between the variables, it can be continued with Granger Causality Test without including error correction terms. If there is a co-integration between the variables, Granger Causality Test will be failed and it will be certainly necessary to be included error correction term into the models. Granger Causality Test, which depends on time series data, is made by the estimation of the equations below with Least Squares Method (LSM). Xt = + j t j X + i t i Y + Ut Yt = + j t j Y + j t j X + Ut In Granger Causality test, there are three possible situations that one directional causality from x to y or y to x, opposite direction between x and y or one affect to other and independency of x and y each other. This situation changes according to chosen of null hypothesis and lagged values randomly in equations above whose parameters are whether equal to zero or not. According to researches, randomly choice makes causality incline to deviations importantly. To understand this test clearly it can be talked about below equation; t (LNGDP) = 0 + t inii (LNGDP)1+ t I nii (LND1)1+ Ut To apply Granger Causality test under null hypothesis, which illustrates coefficients of financial deepening variables (LND1) are meaningful (equal to zero) and then F-statistics can be calculated. If null hypothesis is not rejected then it is possible to say that Granger causality test accepts that financial deepening causes economic growth. The direction can be either negative or positive (Granger and Engle, 1987). Indicators of the economic growth and the financial deepening are variables, which are used for Granger Causality test. Moreover, this test can determine the effects of one variable on the other. Test result for Unit Root: Augmented Dickey Fuller Model (ADF) is used to test the stationary of each variable. Null and alternative hypothesis describes about the investigation of unit root. If the null is accepted and alternative is rejected then the variable non stationary behaviour and vice versa is stationary. Form the result of Augmented Dickey Fuller test of the four countries variables (Log GDP and Log Share price) shows that the entire variable has unit root at level which proves that the series is not stationary. However, the result from the first difference shows the significance at 1%, 5% and 10% critical value and found to be stationary behaviour. Therefore, it suggests that all the variables are integrated of order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Japan Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -2.653258 -3.522887     -2.901779 -2.588280   -2.693600   -4.088713   -3.472558 -3.163450 1st Difference -9.053185 -3.524233   -2.902358 -2.588587 -9.003482   -4.090602   -3.473447 -3.163967 Share Price Level   -2.116137 -3.522887     -2.901779 -2.588280   -2.203273   -4.088713   -3.472558 -3.163450 1st Difference   -6.899295 -3.524233   -2.902358 -2.588587   -6.844396   -4.090602   -3.473447 -3.163967 Table 01: Unit root test for stationary Japan If we have a look on the unit root test for the variables GDP and Share price to find out the stationary behaviour the Augmented Dickey Fuller Test with intercept and with intercept and trend in level and first difference. The t statistic value with trend is -2.653258 which is higher than the critical values in 1%, 5% and 10% critical value. The same applies with intercept and trend as the t statistic value -2.693600 is higher than the critical value in all the level of critical value. So from the nature of stationary behaviour we can say in level GDP shows nonstationary behaviour. And the first difference LnGDP is integrated with order one. In case of LnSP the results with intercept and with intercept trend in level are -2.116137 and -2.203273 which is higher than the critical values shows non stationary behaviour as they are higher than the critical value. The unit root test for the variables at first difference shows stationary as the t statistic value is than the critical value i n all level and they are integrated in order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Malaysia Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -1.195020 -3.522887     -2.901779 -2.588280 -1.933335   -4.088713   -3.472558 -3.163450 1st Difference -5.951843 -3.524233   -2.902358 -2.588587 -5.923595   -4.090602   -3.473447 -3.163967 Share Price Level   -1.900406 -3.522887     -2.901779 -2.588280   -1.891183   -4.088713   -3.472558 -3.163450 1st Difference   -7.842122 -3.524233   -2.902358 -2.588587   -7.779757   -4.090602   -3.473447 -3.163967 The unit root test result for LMGDP and LMSP values presented in natural logarithm. And the level values with intercept and with intercept and trend for LMGDP is -1.195020 and -1.93335 respectively. The values are higher than the critical value means the series has non stationary behaviour. On the other hand the 1st difference values with intercept and with intercept and trend are -5.951843 and -5.923595 respectively. The 1st difference values are integrated with order one. And in the same way I did the ADF test to check for Stationary behaviour of LMSP in level and first difference with intercept and trend. The values in level are -1.900406 and -1.891183 with intercept and trend us higher than the critical value and the series is not integrated with order one. The first difference t statistic values are -7.842122 and -7.779757 with intercept and with intercept and trend respectively are less than the critical value in both the case implies that the series is integrated with order on e. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test UK Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -0.690866 -3.522887     -2.901779 -2.588280 -2.377333   -4.088713   -3.472558 -3.163450 1st Difference -7.474388 -3.524233   -2.902358 -2.588587 -7.439027   -4.090602   -3.473447 -3.163967 Share Price Level -1.711599 -3.522887     -2.901779 -2.588280 -1.261546   -4.088713   -3.472558 -3.163450 1st Difference -7.254574 -3.524233   -2.902358 -2.588587 -7.391821   -4.090602   -3.473447 -3.163967 The results from Augmented Dickey Fuller test (ADF) for UK GDP in level with intercept and with intercept and trend is –0.690866 and -2.377333 respectively. Both the values in level are higher than the critical value and are integrated in order 0 shows non stationary behaviour. The t statistic values in 1st difference with intercept and with intercept and trend are -7.474388 and -7.439207 respectively. Which suggest that the critical values are less than the critical values in 1%, 5% and 10% level. So from the above hypothesis it can be said that it series is integrated with order one. When I performed the unit root test using the same method the series in level with intercept and with intercept and trend the values in are -1.711599 and -1.261546 respectively. The values are higher than the critical values implies that they are not integrated in order one shows non stationary behaviour. However, the 1st difference value of log natural share price is -7.254573 and -7.391821 wit h intercept and with intercept and trend respectively. So from the result we can say that the series is integrated in order one in both the cases with intercept and with intercept and trend. So the series in first difference is stationary. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test USA Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -3.244801 -3.522887     -2.901779 -2.588280   2.866507   -4.088713   -3.472558 -3.163450 1st Difference -5.010864 -3.524233   -2.902358 -2.588587 -5.010864   -4.090602   -3.473447 -3.163967 Share Price Level -2.074732 -3.522887     -2.901779 -2.588280 -0.359637   -4.088713   -3.472558 -3.163450 1st Difference -8.181234 -3.524233   -2.902358 -2.588587 -8.735399   -4.090602   -3.473447 -3.163967 Augmented Dickey Fuller Statistic in case of the variable of USA LUSSP and LUGDP I have used the same method using intercept and intercept and trend in level and first difference. Th Stock Market Performance and Economic Activity Relationship Stock Market Performance and Economic Activity Relationship Introduction The debate of whether stock market is associated with economic growth or the stock market can be served as the economic indicator to predict future. According to many economists stock market can be a reason for the future recession if there is a huge decrease in the stock price or vice versa. However, there are evidence of controversial issue about the ability of prediction from the stock market is not reliable if there is a situation like 1987 stock market crashed followed by the economic recession and 1997 financial crises. (Stock market and economic growth in Malaysia: causality test). The aim of the study is to find the relation between the stock market performance and the real economic activity in case of four countries The UK, The USA, Malaysia and Japan. With my limited knowledge I have tried to find out the role of financial development in stimulating economic growth. A lot of economists have different view about stock market development and the economic growth. If we focus on some related literature published on this topic one question arises: Is economic development is affected by stock market development? Even though there are lots of debate on some are saying that stock market can help the economy but the effect of stock market in the economy especially in the economy is very little. Ross Levine suggested in his paper published in 1998 that recent evidence suggested stock market can really give a boom to economic growth. (REFERENCE) It is not really possible to measure the growth by simply looking at the ups and down in the stock market indicator and by looking at the rates of growth in GDP. A lot of things can cause in the growth of stock market like changes in the banking system, foreign participation in the in the financial market may participate strongly. Apparently it seems that these developments can cause development of stock market followed by the good economic growth. But to check the accuracy one required to follow an appropriate method which would meaningfully measure whether stock price is really effecting the economic growth or not? In my work I have tried to find out the co integrating relationship between Stock price and GDP and tried to check if there is a long run and short run relationship between the stock price and GDP. The method used for the studies is Engle Granger co integration method. To do this I have used ADF (Augmented Dickey Fuller Test) to check for the stationary behaviour of the variables and then I have performed the Engle Granger Engle Granger co integration method followed by residual based error correction model. To check for the short run relationship I have used 2nd stage Engle Granger co integration method. To check the causal effect of the four countries stock market and economic growth I used Granger Causality Method. In this paper I have reviewed some studies of scholars which I have discussed on the literature review part. This paper contains five parts Part two is about the literature based on the past wok of scholars. Part Three discussed about the Data. Part four is about the methodology, Results are discussed on part five and part six is all about the summary and conclusion of the whole study. In my work I have founded there is no long run relationship between stock market and economic growth in all four countries. In addition there is no causal relation between stock index yield and the national economy growth rate. The empirical results of the thesis concludes that the possibility of seemingly abnormal relationship between the stock index and national economy of these for countries. Literature Review: Stock market contributes to economic growth in different ways either directly or indirectly. The functions of stock market are savings mobilization, Liquidity creation, and Risk diversification, keep control on disintermediation, information gaining and enhanced incentive for corporate control. The relationship between stock market and economic growth has become an issue of extensive analysis. There is always a question whether the stock market directly influence economic growth. A lot of research and results shows that there is a strong relationship between stock market and economic growth. Evidence on whether financial development causes growth help to reconcile these views. If we go back to the study of Schumpeter (1912) his studies emphasizes the positive influence on the development of a countrys financial sector on the level and the potential risk of losses caused by the adverse selection and moral hazard or transaction costs are argued by him how necessary the rate of growth argues that financial sectors provides of reallocating capital to minimize the potential losses. Empirical evidence from king and Levine (1983) show that the level of financial intermediation is good predictor of long run rates of growth, capital accumulation and productivity. Enhanced liquidity of financial market leads to financial development and investors can easily diversify their risk by creating their portfolio in different investments with higher investment. Demiurgic and Maksimovic (1996) have found positive causal effects of financial development on economic growth in line with the ‘supply leading hypothesis. According to his studies countries with better financial system has a smooth functioning stock market tend to grow much faster as they have access to much needed funds for financially constrained economic enterprises by the large efficient banks. Related research was done for the past three decades focusing on the role of financial development in stimulating economic growth they never considered about the stock market. An empirical study by Ming Men and Rui on Stock market index and economic growth in China suggest that possible reason of apparent abnormal relationship between the stock Index and national economy in china. Apparent abnormal relationship may be because of the following reason inconsistency of Chinese GDP with the structure of its stock market, role played by private sector in growth of GDP and disequilibrium of finance structure etc. The study was done using the cointegration method and Granger causality test, the overall finding of the study is Chinese finance market is not playing an important role in economic development. (Men M 2006 China paper). An article by Indrani Chakraborti based on the case of India presented in a seminar in kolkata in October, 2006 provides some information about the existence of long run stable relationship between stosk market capitalization, bank credit and growth rate of real GDP. She used the concept of the granger causality after using both the Engle-Granger and Johansen technique. In her study she found GDP is co-integrated with financial depth, Volatility in the stock market and GDP growth is co integrated with all the findings the paper explain that the in an overall sense, economic growth is the reson for financial development in India.(Chakraboty Indrani). Few writers from Malaysia found that stock market does help to predict future economy. Stock market is associated with economic growth play as a source for new private capital. Causal relationship between the stock market and economic growth which was done by using the formal test for causality by C.J. Granger and yearly Malaysia data for the period 1977-2006. The result from the study explain that future prediction is possible by stock market. A study focused on the relationship between stock market performance and real economic activity in Turkey. The study shows existence of a long run relationship between real economic activity and stock prices†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Result from the study pointed out that economic activity increases after a shock in stock prices and then declines in Turkish market from the second quarter and a unitary (Turkish paper) An international time series analysis from 1980-1990 by By RAGHURAM G. RAJAN AND LUIGI ZINGALES shows some evidence of the relation between stock market and economic growth. This paper describes whether economic growth is facilitated by financial development. He found that financial development has strong effect on economic growth. (Rajan and Zingales, 1998) The study of Ross LEVINE AND SARA ZERVOS on finding out the long run relationship between stock market and bank suggest a positive effect both the variables has positive effect on economic growth. International integration and volatility is not properly effected by capital stock market. And private save saving rates are not at all affected by these financial indicators. (Levine and Zervos 1998) Belgium Stock market study with economic development shows the positive long run relationship between both the variables. In case of Belgium the evidences are quiet strong that Economic growth is caused by the development of the stock market. It is more focused between the period 1873 and 1935, basically this period is considered as the period of rapid industrialization in Belgium. The importance of the stock market in Belgium is more pronounced after liberalization of the stock market in 1867-1873. The time varying nature of the link between stock market development and economic growth is explained by the institutional change in the stock exchange. They also tried to find out the relationship to the universal banking system. Before 1873 the economic growth was based on the banking system and after 1873 stock market took the place. (Stock Market Development and economic growth in Belgium, Stijin Van Nieuwerburg, Ludo Cuyvers, Frans Buelens July 5, 2005) Senior economist of the World Banks Policy research department Ross Levine has discussed about Stock market in his paper Stock Markets: A Spur to economic growth on the impact of development. Less risky investments are possible in liquid equity market and it attracts the savers to acquire an asset, equity. As they can sell it quickly when they need access to their savings, and if they want to alter their portfolio. Though many long term investment is required for the profitable investment. But reluctance of the investors towards long term investment as they dont have the access to their savings easily. Permanent access to capital is raised by the companies through equity issues as they are facilitating longer term, more profitable investments and prospect of long term economic growth is enhanced as liquid market improves the allocation of capital. The empirical evidence from the study strongly suggests that greater stock markets create more liquidity or at least continue economic gro wth. (Levine. R A spur to economic Growth) Another paper was focused on the linkages between financial development and economic growth using TYDL model for the empirical exercises by Purna Chandra Padhan suggests that both stock price and economic activity are integrated of order one and Johansen-Juselias Coin-integration tests for this study found one co integrating vector exists. It is proved by the spurious relation rule in this study the existence of at least one direction of causality. He described that bi-directional causality between stock price and economic growth meaning that economic activity can be enhanced by well developed stock exchange and vice-versa. ( Title:  The nexus between stock market and economic activity: an empirical analysis for India Author(s): Purna Chandra Padhan Journal: International Journal of Social Economics Year: 2007 Volume: 34 Issue: 10  Page: 741 – 753 DOI: 10.1108/03068290710816874 Publisher: Emerald Group Publishing Limited) Chee Keong Choong (Universiti Tunku Abdul Rahman Malaysia) Zulkornain Yusop (Universiti Putra Malaysia) Siong Hook Law (Universiti Putra Malaysia) Venus Liew Khim Sen (Universiti Putra Malaysia) Date of creation: 23 Jul 2003 tried to find out the importance of the causal relationship of Financial development and economic growth. The findings of their study usin autoregressive Distributed lag (ARDL) describes about the positive long run impact on economic growth Granger causality also suggest same results. However, another study on Iran by N. Shahnoushi, A.G Daneshvar, E Shori and M. Motalebi 2008 Financial development is not considered as an effective factor to the economic growth. The study was focused on the causal relationship between the financial development and economic growth. Time series data used for the study from the period 1961-2004. Granger causality shows there is no co integrating relationship between financial development and economic growth in Iran only the economical growth leads to financial development. Establishing link between savings and investment is very much important and financial market provides that. Transient or lasting growth is the ultimate affect of the financial market. Economic growth can be influenced by financial market by improving the productivity of the capital, Investment to firms can be channelled and greater capital accumulation by increasing savings. To ensure the stability of the financial market potential regulation is important due to asymmetric information, especially at the time of financial liberalization. (Economic Development and Financial Market Tosson Nabil Deabes Moderm Academy for technology aand computer sciences; MAM November 2004 Economic Development Financial Market Working Paper No. 2 ) Data: The empirical analysis was carried out using the quarterly data for The UK, The USA, Japan and Malaysia. The data were collected from the DataStream for the period 1993I to 2008III. Economic growth is measured as the growth rate of gross domestic product (GDP) of each country with the help of stock prices SP. For the software processing I used Eviews 6.0 for the planned regression in order to get the results. The empirical analysis is done from the quarterly data from the stock market indices and the and the GDP between the first quarter of 1993 and the fourth quarter of 2008. All the data has been extracted from the data stream and expressed in US$. The data for Japan share price is from Tokyo Stock Exchange. Malaysias Share price is form Kuala Lumpur Composite Index, UKs is from UK FT all share price index and USA share price is taken from the DOW Jones industrial share price index. The nature of the Data is series used for the time series regression. List of Variables: UGDP UK GDP USP UK Share price LUGDP Log of UK GDP LUSP Log of UK Share price USGDP USA GDP USSP USA (DOW Jones) Share price LUSGDP Log of USA GDP LUSSP Log of USA Share price MGDP Malaysia GDP MSP Malaysia Share price LMGDP Log of Malaysia GDP LMSP Log of Malaysia Share price JGDP Japan GDP JSP Japan Share Price LJGDP Log of Japan GDP LJSP Log of Japan Share price Methodology: Engle and Granger (1987) first established the cointegration method. It is a method of measuring long term diversification based on data. Linear combination of two non stationary series shows that they are integrated in order one I(1) that is stationary. And this is a co integrated series. Cointegration Long term common random trend between non stationary time series. The linear combination of both the nonstationary series can be stationary if both the variables are integrated in same order. Cointegration is a very powerful approach in the long term analysis because a common stochastic trend is shared in cointegration that mean two series will not drift separately too much. They might deviate from each other but in the long run but eventually the will revert back in the long run. If there is very low correlation between the series still the series can be co-integrated as high correlation is not implied in cointegration. The reason for choosing the method as it will allow us to check the move between the variable in the long run even there might be a divergence in the short run. The first step in the analysis is check each index series whether the series for the presence of unit root which shows whether the series is non stationary. The method that I followed to do this is Augmented Dickey Fuller Test (ADF). I proceed the Granger cointegration technique 1987 when the stationary requirements are met. Cointegration long term common stochastic trend between nonstationary time series. If non-stationary series x and yare both integrated of same order and there is a linear combination of them that is stationary, they are called cointegrated series. A common stochastic trend is shared in Cointegration. It follows that these two series will not drift apart too much, meaning that even they may deviate from each other in the short-term, they will revert to the long-run equilibrium. This fact makes cointegration a very powerful approach for the long-term analyses. Meanwhile, cointegration does not imply high correlation; two series can be co integrated and yet have very low correlations. Cointegration tests allow us to determine whether financial variables of different national markets move together over the long run, while providing for the possibility of short-run divergence. The first step in the analysis is to test each index series for the presence of unit roots, which shows whether the series are nonstationary. All the series must be nonstationarity and integrated of the same order. To do this, we apply both the Augmented Dickey-Fuller (ADF) test. Once the stationarity requirements are met, we proceed Granger bivariate cointegration (1987) procedure. 30 International Research Journal of Finance and Economics Issue 24 (2009) Series Stationary Test: In this study I have used Augmented Dickey Fuller Test (ADF) to test the stationarity of variables. ADF is test for unit root where I have checked the Unit root and strong negative numbers of unit root is being rejected by the null hypothesis (level of significance). The following regression for the unit root test in Eviews: Is the white noise error tem. Is the difference operator. , () () Here with the test we can find the estimates of are equal to zero or not. Y is said to be stationary if the cumulative distribution of the ADF statistics by showing that if the calculated ratio of the coefficient is less than the critical value according to Fuller (1976). If we accept the Ho the sequence is predicted to be having unit root and if Ho is rejected then we can say that the series doesnt have unit root. This proves that the series is stationary. The co –integration test can only be performed if both the sequences are all integrated of order I (1). Cointegration Test: According to Engle and Granger (1987) to check for cointegration if both the variables and are integrated with order one the proposed method for cointegration residual-based test for cointegration (Engle-Granger method). So from the above method we can find the equation By regressing with And after that and is denoted as the estimated regression coefficient vectors. Then, = – is representing the estimated residual vector. If the residual is itegrated with zero that means the series for the residual is stationary, and and are then co integrated. An in this situation (1, -) is called co-integrating vector. Therefore is a co integrating equation, so, from it we can say that there is long run relationship between and. Granger causality test: Granger causality test is applied if the relationship is lagged between the two variables to determine the direction of relation in statistical term. It gives information about the short term relationship between the variables. In terms of conceptual definition causality is consist of different ideas, this concept produce a relation between caused and results were agreed upon. Aristo defines that there exist a link between causes and results and without causes these results are impossible. And this strong relationship. Some economists believe that the idea of causality is the mix of both theoretical and explanation and statistical concept. The frontline operational definition of causality is given by some economist, but Granger is the one who provided the information to understand it correctly and completely. Granger s operational causality definition depends of below hypotheses, Next cannot be the reason of past. 1. Next cannot be reason of past. Certain causality is possible only with past causes present time or future time. Cause is always to be come true before the result. In addition, this makes time lagged between causes and results. 2. Causality can be determined only stochastic process. It is not possible to determine the causality between two deterministic processes. After 1990s, Granger and Engle contributed to time series literature importantly. On these developments about time series analysis, some variations were done with Granger Causality test. According to this, possible long-term relationship would be tested and if 20 variables were co-integrated, long-term regression error equation s lagged value would be included in Granger Error Correction model as error correction term. Thus, Granger Causality test should be applied. If there is no co-integration between the variables, it can be continued with Granger Causality Test without including error correction terms. If there is a co-integration between the variables, Granger Causality Test will be failed and it will be certainly necessary to be included error correction term into the models. Granger Causality Test, which depends on time series data, is made by the estimation of the equations below with Least Squares Method (LSM). Xt = + j t j X + i t i Y + Ut Yt = + j t j Y + j t j X + Ut In Granger Causality test, there are three possible situations that one directional causality from x to y or y to x, opposite direction between x and y or one affect to other and independency of x and y each other. This situation changes according to chosen of null hypothesis and lagged values randomly in equations above whose parameters are whether equal to zero or not. According to researches, randomly choice makes causality incline to deviations importantly. To understand this test clearly it can be talked about below equation; t (LNGDP) = 0 + t inii (LNGDP)1+ t I nii (LND1)1+ Ut To apply Granger Causality test under null hypothesis, which illustrates coefficients of financial deepening variables (LND1) are meaningful (equal to zero) and then F-statistics can be calculated. If null hypothesis is not rejected then it is possible to say that Granger causality test accepts that financial deepening causes economic growth. The direction can be either negative or positive (Granger and Engle, 1987). Indicators of the economic growth and the financial deepening are variables, which are used for Granger Causality test. Moreover, this test can determine the effects of one variable on the other. Test result for Unit Root: Augmented Dickey Fuller Model (ADF) is used to test the stationary of each variable. Null and alternative hypothesis describes about the investigation of unit root. If the null is accepted and alternative is rejected then the variable non stationary behaviour and vice versa is stationary. Form the result of Augmented Dickey Fuller test of the four countries variables (Log GDP and Log Share price) shows that the entire variable has unit root at level which proves that the series is not stationary. However, the result from the first difference shows the significance at 1%, 5% and 10% critical value and found to be stationary behaviour. Therefore, it suggests that all the variables are integrated of order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Japan Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -2.653258 -3.522887     -2.901779 -2.588280   -2.693600   -4.088713   -3.472558 -3.163450 1st Difference -9.053185 -3.524233   -2.902358 -2.588587 -9.003482   -4.090602   -3.473447 -3.163967 Share Price Level   -2.116137 -3.522887     -2.901779 -2.588280   -2.203273   -4.088713   -3.472558 -3.163450 1st Difference   -6.899295 -3.524233   -2.902358 -2.588587   -6.844396   -4.090602   -3.473447 -3.163967 Table 01: Unit root test for stationary Japan If we have a look on the unit root test for the variables GDP and Share price to find out the stationary behaviour the Augmented Dickey Fuller Test with intercept and with intercept and trend in level and first difference. The t statistic value with trend is -2.653258 which is higher than the critical values in 1%, 5% and 10% critical value. The same applies with intercept and trend as the t statistic value -2.693600 is higher than the critical value in all the level of critical value. So from the nature of stationary behaviour we can say in level GDP shows nonstationary behaviour. And the first difference LnGDP is integrated with order one. In case of LnSP the results with intercept and with intercept trend in level are -2.116137 and -2.203273 which is higher than the critical values shows non stationary behaviour as they are higher than the critical value. The unit root test for the variables at first difference shows stationary as the t statistic value is than the critical value i n all level and they are integrated in order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Malaysia Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -1.195020 -3.522887     -2.901779 -2.588280 -1.933335   -4.088713   -3.472558 -3.163450 1st Difference -5.951843 -3.524233   -2.902358 -2.588587 -5.923595   -4.090602   -3.473447 -3.163967 Share Price Level   -1.900406 -3.522887     -2.901779 -2.588280   -1.891183   -4.088713   -3.472558 -3.163450 1st Difference   -7.842122 -3.524233   -2.902358 -2.588587   -7.779757   -4.090602   -3.473447 -3.163967 The unit root test result for LMGDP and LMSP values presented in natural logarithm. And the level values with intercept and with intercept and trend for LMGDP is -1.195020 and -1.93335 respectively. The values are higher than the critical value means the series has non stationary behaviour. On the other hand the 1st difference values with intercept and with intercept and trend are -5.951843 and -5.923595 respectively. The 1st difference values are integrated with order one. And in the same way I did the ADF test to check for Stationary behaviour of LMSP in level and first difference with intercept and trend. The values in level are -1.900406 and -1.891183 with intercept and trend us higher than the critical value and the series is not integrated with order one. The first difference t statistic values are -7.842122 and -7.779757 with intercept and with intercept and trend respectively are less than the critical value in both the case implies that the series is integrated with order on e. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test UK Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -0.690866 -3.522887     -2.901779 -2.588280 -2.377333   -4.088713   -3.472558 -3.163450 1st Difference -7.474388 -3.524233   -2.902358 -2.588587 -7.439027   -4.090602   -3.473447 -3.163967 Share Price Level -1.711599 -3.522887     -2.901779 -2.588280 -1.261546   -4.088713   -3.472558 -3.163450 1st Difference -7.254574 -3.524233   -2.902358 -2.588587 -7.391821   -4.090602   -3.473447 -3.163967 The results from Augmented Dickey Fuller test (ADF) for UK GDP in level with intercept and with intercept and trend is –0.690866 and -2.377333 respectively. Both the values in level are higher than the critical value and are integrated in order 0 shows non stationary behaviour. The t statistic values in 1st difference with intercept and with intercept and trend are -7.474388 and -7.439207 respectively. Which suggest that the critical values are less than the critical values in 1%, 5% and 10% level. So from the above hypothesis it can be said that it series is integrated with order one. When I performed the unit root test using the same method the series in level with intercept and with intercept and trend the values in are -1.711599 and -1.261546 respectively. The values are higher than the critical values implies that they are not integrated in order one shows non stationary behaviour. However, the 1st difference value of log natural share price is -7.254573 and -7.391821 wit h intercept and with intercept and trend respectively. So from the result we can say that the series is integrated in order one in both the cases with intercept and with intercept and trend. So the series in first difference is stationary. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test USA Conclusion t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -3.244801 -3.522887     -2.901779 -2.588280   2.866507   -4.088713   -3.472558 -3.163450 1st Difference -5.010864 -3.524233   -2.902358 -2.588587 -5.010864   -4.090602   -3.473447 -3.163967 Share Price Level -2.074732 -3.522887     -2.901779 -2.588280 -0.359637   -4.088713   -3.472558 -3.163450 1st Difference -8.181234 -3.524233   -2.902358 -2.588587 -8.735399   -4.090602   -3.473447 -3.163967 Augmented Dickey Fuller Statistic in case of the variable of USA LUSSP and LUGDP I have used the same method using intercept and intercept and trend in level and first difference. Th

Non-Chronological Narration Technique Used in Faulkner’s The Unvanquished :: Unvanquished Essays

Non-Chronological Narration Technique Used in Faulkner’s The Unvanquished The novel The Unvanquished is a about a young boy’s coming of age story, as seen through the eyes of the grown man that he is to become. The great advantage of this form of narration is the ability it grants Faulkner to be able to reach forward and backward through time unrestrained in order to pull the type of significance and lesson from this boy’s story that can only be seen upon reflection. Despite surely being a technique borrowed from the author James Joyce, William Faulkner was arguably the first to realize what this disregard for chronology could offer to a story of values of masculinity. By looking back on what it means to be a man, as opposed to forward, William keeps the lessons of manhood clear and concise, as opposed to the vague and confused path a boy must in actuality take. From the very first lines we see the stark contrast between protagonist and narrator, and the important role it plays. The story opens with the two youthful friends, Ringo and Bayard, fantasizing about the battle in Vicksburg they believed their hero and Bayard’s father, Colonel Sartoris, was fighting. As they stage their own imitation though, the narrator’s tone is completely opposite of the idolatry of the children. He says of their mock Vicksburg landscape, that it was â€Å"possessing even in miniature that ponderable though passive recalcitrance of topography which outweighs artillery, against which the most brilliant of victories and the most tragic of defeats are but the loud noises of a moment.† In this way the narrator has completely laid bare the naivety of the children in getting caught up in the passions of their limited and ultimately insignificant struggles, and even more importantly, the ignorance of the man whom they attempt to emulate. While the story is one of confederate pride, embodied in spirit by the character of Bayard’s father, the narrator is the voice of tempered reflection. He describes the futility of the south’s plight through the metaphor of the children playing. He says of their miniature battle of Vicksburg, â€Å"[It was] the very setting of the stage for conflict a prolonged and wellnigh hopeless ordeal in which we ran, panting and interminable, with the leaking bucket between wellhouse and battlefield,†¦ to join forces†¦against†¦time, before we could engender between us and hold intact the pattern of recapitulant mimic furious victory like a cloth, a shield between ourselves and reality, between us and fact and doom.

The Pursuit of Happyness

â€Å"The Pursuit of Happyness† The movie it’s about a man called Christopher Gardner that lives with his wife and son in a small apartment. They have a low budget and are going thru a very difficult time economically and it could come to a point where they can lose everything and even get apart. This man invested the family savings in this kind of machines called â€Å"Bone Density scanner’’ thinking he was going to invest and earned a lot of money to maintain his family. They thought it was going to be a great result, but it turned out the opposite way. In life not everything that seems bright as gold.The Gardner family where trying to survive the most that they can. While the days were passing it was getting worst and worst. Chris Gardner has big dreams for him and his family but it doesn’t seem to come together for him. This financial thing that were going on suddenly breaks the family starting with troubles in the relationship with his wife th at leaves him and his son and moves to New York. His wife wanted to take their son with her because she said that every children should be with their mom, but Christopher said that it’s very true, but he said that he could take better care of him than her because his used to it.After that he loses his wife, lost his bank account, and credit cards. He was searching for jobs all over but he couldn’t find anything, until finally he decided to do an stockbroker internship position at Dean Witter, competing for one career for six months with getting any salary at all with twenty other candidates for that position and only one of them was going to get the job. He was doing the best he could to fight for what he wanted. He was being a father and a mother at the same time it was not easy as it seemed to be. Meanwhile, they were homeless and he was going thru all the difficulties with his son Christopher Jr.Even thou they were struggling Chris was determined to make it and not giving up, in another words with the little that they had they were trying to survive. What it seemed impossible turned possible because after all the hard work and the difficult times that they were going thru, all that turned out to be a wonderful result for their lives because he finally got the job, from all twenty candidates he got to be the chosen one. Chris and his son’s lives change from the darkness past to a brightness present. In conclusion, this movie it’s amazing and great.It inspired me a lot because it teach me that no matter what are you going thru or what you face in life there’s nothing impossible and giving up is not an option. It doesn’t matter how many times you fall, what it matters it’s how many times you stand up and keep moving forward. Life could give you so many challenges, but it’s up to you how you decided to face it and deal with it and besides that it’s the result that you are going to obtain. These word s of the movie â€Å"Don’t ever let somebody tell you†¦You can’t do something† â€Å"You got a dream†¦ you got to protect it.People can’t do something themselves, they want to tell you, you can’t do it. If you want something go get it. Period† they inspired me a lot because you can’t let anyone bring you down and tell you that you’re a nobody and that you can’t do anything just because they haven’t gotten what they wanted or their dreams come true. We have to stand up, be strong, and demonstrate that we are better than them and that we could do anything that step in our ways without the help of anybody. I leave with this saying â€Å"What it looks impossible for man, it’s possible for God†. The Pursuit of Happyness â€Å"The Pursuit of Happyness† The movie it’s about a man called Christopher Gardner that lives with his wife and son in a small apartment. They have a low budget and are going thru a very difficult time economically and it could come to a point where they can lose everything and even get apart. This man invested the family savings in this kind of machines called â€Å"Bone Density scanner’’ thinking he was going to invest and earned a lot of money to maintain his family. They thought it was going to be a great result, but it turned out the opposite way. In life not everything that seems bright as gold.The Gardner family where trying to survive the most that they can. While the days were passing it was getting worst and worst. Chris Gardner has big dreams for him and his family but it doesn’t seem to come together for him. This financial thing that were going on suddenly breaks the family starting with troubles in the relationship with his wife th at leaves him and his son and moves to New York. His wife wanted to take their son with her because she said that every children should be with their mom, but Christopher said that it’s very true, but he said that he could take better care of him than her because his used to it.After that he loses his wife, lost his bank account, and credit cards. He was searching for jobs all over but he couldn’t find anything, until finally he decided to do an stockbroker internship position at Dean Witter, competing for one career for six months with getting any salary at all with twenty other candidates for that position and only one of them was going to get the job. He was doing the best he could to fight for what he wanted. He was being a father and a mother at the same time it was not easy as it seemed to be. Meanwhile, they were homeless and he was going thru all the difficulties with his son Christopher Jr.Even thou they were struggling Chris was determined to make it and not giving up, in another words with the little that they had they were trying to survive. What it seemed impossible turned possible because after all the hard work and the difficult times that they were going thru, all that turned out to be a wonderful result for their lives because he finally got the job, from all twenty candidates he got to be the chosen one. Chris and his son’s lives change from the darkness past to a brightness present. In conclusion, this movie it’s amazing and great.It inspired me a lot because it teach me that no matter what are you going thru or what you face in life there’s nothing impossible and giving up is not an option. It doesn’t matter how many times you fall, what it matters it’s how many times you stand up and keep moving forward. Life could give you so many challenges, but it’s up to you how you decided to face it and deal with it and besides that it’s the result that you are going to obtain. These word s of the movie â€Å"Don’t ever let somebody tell you†¦You can’t do something† â€Å"You got a dream†¦ you got to protect it.People can’t do something themselves, they want to tell you, you can’t do it. If you want something go get it. Period† they inspired me a lot because you can’t let anyone bring you down and tell you that you’re a nobody and that you can’t do anything just because they haven’t gotten what they wanted or their dreams come true. We have to stand up, be strong, and demonstrate that we are better than them and that we could do anything that step in our ways without the help of anybody. I leave with this saying â€Å"What it looks impossible for man, it’s possible for God†.

Music Videos

Most songs have a videos produced as a sort of advertisement back up for the song to sell. Videos narrate the song, while actions take place in the background. An example of a video having a narration would be the Oasis song ‘Stand by me'. The movie shows part of what is happening, then repeats the scene, however so you can see what is actually happening in the second clip. The first scene shows a baby getting snatched, a shop being robbed, also a motorist trying to run over a person. This is the gut feeling of what you think is happening. In actual fact what happens is; a motorist loses control of his bike, a man grabs the baby out of the way, the motorist drives past a person, then through a shop window. People help move the objects from the window, helping the injured motorist, where this is thought to be the shop getting robbed. We would expect to find music videos on TV, where certain channels show music videos, being named music channels. An example of a popular music channel being The hits. It is very important for record companies to produce videos for their songs as many people are influenced by songs which have good videos, with decent tunes. Many people mostly watch, or listen to music on their TV's, whether they are getting ready, or just chilling watching the movies. If a record company did not have a video, or their song was not advertised on TV, then you could expect it not to sell well on the net, or by singles in shops. The reason behind this is when songs are advertised on TV, or played on TV; a person would remember it better than a quick listen to it on the radio. I took certain parts of research for designing my music video, one thing surprising me is that not most people like pop music than I thought, tending to have a mixed variety. Depending on the type of genre the song is, would decide which TV channels your music video is to be played or advertised. My planning source for my music turned out to be quite difficult, however I done the difficult parts first, to make it not as sophisticated to do there on. One of the most difficult things was to watch all of Alan Shearers 206 goals, deciding the featured top five, and crediting on another magnificent six. First of all I thought of doing the song Local Hero, produced by Dire Straits. This decision is because I am a Newcastle United fan, knowing it would be good to produce something about the club I support. So the idea developed from there, as Alan Shearer being as what all ‘Toon' fans class as the ‘Local Hero' I thought I could do nothing other. The name of the song is a sort of narration for Alan Shearer's incredible 10 year career at Newcastle. Shearer being the man to demolish Sir Jackie's 200 goal record plus gaining the heart of all the Geordie faithful is a fanatical achievement to establish as a player. I think the planning for my music video was very successful, having completed almost all the work without errors. I think my movie would work as a music video, as it has a purpose, which is to remind Newcastle United fans of the exceptional talent Shearer has. Also the song is a great song, matching a great player. If I had to produce another music video I would produce a video, with a pop genre.