Assignment Essay Example | Topics and Well Written Essays - 500 words - 92

Assignment - Essay Example Experience is the best teacher, they say. Experience is something that people go through in the course of their lifetime that instills new knowledge to them. A teacher, therefore, may not only be in human form. A successful teaching process is one in which both the teacher and the student end up satisfied with the action. The knowledge has to be passed in a particular way so that the teacher ends up fulfilled, and the student understands. For a teaching method to be successful, there should be a definite goal (Ingvarson, 2013). A goal is a definition of what people desire to achieve. The lesson objective should, therefore, be clear, and the student should know what they should make by studying that particular subject. The goal is the main reason for a study subject, and it acts to the level of knowledge attained. The goal should, therefore, be clear, precise and to the point. A successful teaching method should deal with specific educational content. Research findings have continuously confirmed that it is more difficult to concentrate on a full field of view than on a particular scope or subject (Rodgers, 2014). Educational material is therefore divided into subjects, topics and subtopics. There should also be a large scope of educational activities, apart from the basic classroom part. Activities like physical education and subject experiments should be part of the learning activity. Time is an essential factor for the success of every activity in life. Teaching should, therefore, include a drafted calendar for the activities that the students expect to take place at different intervals of the day. The schedule should contain no unnecessary information and should be very precise and understandable. The teacher should also provide the feedback to the learner. There should be regular updates on how the student is progressing and the areas that need improvement. The whole objective of the teaching process is to ensure that the

Unprofessional Athletes Essay Example for Free

Unprofessional Athletes Essay Back in the year 1860, the Pony Express was known to be the fastest and most efficient method of sending mail. It had taken approximately ten days for a horse to travel across the country and deliver the parcels to their recipients, an astonishingly short amount of time for the people of that particular era. A little over 150 years after the inception of the Pony Express, technological advances have been made and it is safe to say that a simple message to a friend no longer takes ten days to send, nor does it travel by horse. Now, in the year 2012, a message can be sent simply with a few clicks on a keyboard or a couple clicks of a cell phone. Along with the gratification that comes along with knowing that your message was sent and received instantly, there comes a few dangers. These hazards become a greater risk for those individuals who are in the spotlight, especially professional athletes. If an athlete makes a controversial remark about any issue, he makes himself subject to mass public scrutiny; from there, the athlete may lose the respect of his fans, supporters, and even teammates based on his stance on the particular topic. An athlete may be so preoccupied by social media and how the world perceives them that he may lose focus on his main goal, which is performing well in his sport. Many professional sports leagues have rules set in place against athletes expressing their opinions of certain sports-related topics on social media, so if a player steps out of line and disobeys one of these rules he is subject to a heavy fine enforced by the league’s officials. Social media shouldn’t be used by professional athletes because of the intense microscope they are under on an everyday basis. Professional athletes have a huge following while participating in their craft, but once they enter the world of social media, especially Twitter, some athletes see this crowd start to dwindle down. Many believe that although fans may root for a player during a game, it does not necessarily translate into support off the field in their social life., In Mark Emmons’ Mercury News article entitled â€Å"Amid Giants World Series, Twitter gives fans a glimpse into athletes lives,† Harry Edwards, a UC Berkeley professor emeritus of sociology, states that: The [San Francisco] 49ers want guys to interact with fans, but they want them to be smart because when you put something out there, its out there forever. It could end up in your obituary. But its important that fans can feel like they can talk to an athlete and say, Maybe it was a tough day at the office for you guys Sunday, but youll get em next week. Figure.1 Stoudemires actions on Twitter epitomize that anything that is done over social media can be publicized and scrutinized in an instant. Figure.1 Stoudemires actions on Twitter epitomize that anything that is done over social media can be publicized and scrutinized in an instant. Although he has always been on rival opposing teams, Amar’e Stoudemire had been one of my favorite NBA players to watch due to his toughness and high-flying ability. When I first joined Twitter in 2011 he was one of the first people that I knew I had to follow. Unlike some athletes before him, he was—by most people’s standards—a respected professional basketball player who did most of his trash talking between the basketball court’s lines rather than blowing up on Twitter after a game. However, during late June of this year, Stoudemire’s reputation and fan following took a major hit after he angrily messaged a fan in response to the fan’s tweet questioning Stoudemire’s performance on the court. In the direct message as shown in Figure 1.1, Stoudemire uses slanderous and even anti-gay slurs which are blocked out with black boxes. Although he apoligized after the picture went viral, the damage had already been done and his reputation had taken a permanent hit. Stoudemire had begun to lose long-time supporters, including myself, because of the reaction he had to a simple criticism he received over Twitter. Everything an athlete does, especially over social media websites, is heavily scrutinized and can land him in an uncomfortable and unwanted position in the public. All professional athletes must be aware of the fact that with all of the intense training that they put forth in hopes of perfecting their particular craft, social media outlets, especially Twitter and Facebook, can provide unnecessary distractions that may interfere with their performance. It has become such an addiction to some players that they cannot bear to go a whole game without tweeting or writing a status update about their team’s performance. A few years ago during halftime of a game against the Boston Celtics, Charlie Villanueva of the Milwaukee Bucks tweeted this, leading to then-head coach Scott Skiles banning Twitter use during games: â€Å"In da locker room, snuck to post my twitt. Were playing the Celtics, tie ball game at da half. Coach wants more toughness. I gotta step up. (si.com â€Å"Twitter Trouble†) The pressures put on athletes by fans is not only felt here in the United States, but also on a global level. Before the 2012 Summer Olympic Games, Australian swimmer Emily Seebohm was by far the favorite to win in the 100-meter backstroke, but was just edged out by American teenager Missy Franklin. When asked about her performance, Seebohm claimed to have been distracted by all of the posts from friends and fans back in her home country, causing a lack of sleep and mental preparation that goes into earning a gold medal at the Olympics. (The Telegraph) Professional athletes around the world should not be using any social media or social networking devices because of the negative impact it can have on their on-field performance and thus blocking them from reaching their maximum potential and skill level. It is a necessity for athletes to be cautious with their word choice because of the fines they may receive as a result of their comments. In an April 2012 Time magazine, then Miami Marlins manager Ozzie Guillen blurted out that he loved and respected oppressive Cuban leader Fidel Castro for his unwillingness to be caught and brought down by those looking to end his reign as tyrant. (Time Magazine) These comments were not well received by the Miami community—made up of mostly Cuban immigrants who fled the country to escape from its unruly dictator. Guillen received a five game suspension, but the stain on his reputation was never completely removed. Since the preseason comments made regarding Castro, Guillen continued to make negative comments about his team’s performance, leading to multiple fines from the team’s owner and a loss of respect from a city as a whole. On October 23,2012, just over a year from initially being hired as the Marlins’ manager, Guillen was fired because of a combination of lack of wins on the field and an excess of controversial remarks made off the field of play. Athletes and coaches both need to watch whatever they say to the media or on a social networking site because of the ramifications that the comments may have with the team or sponsors they are currently working for. Many sports fans, myself included, agree that they enjoy witnessing and reading about how the everyday lifestyle of a professional athlete plays out through social media outlets. Despite the enjoyment that I experience from getting an inside glimpse of a professional athlete’s life, I do realize the issue that they may not be setting a prime model for the younger generation that look up to them. No, not all athletes are monsters made out to destroy a child’s innocence through their Twitter, but there are enough poor examples in the world to raise the question of whether or not these athletes should have their own social media outlets due to the issue of molding a younger generation into respectable adults that didn’t have their â€Å"hero’s† identity ripped away by one careless tweet or status update sent out. In the social media world we live in the question is not whether or not we enjoy seeing an athlete’s life play out over Twitter or any other social media outlet, but whether or not the material they post is ethical enough to keep their â€Å"professional† status. We are constantly told that our generation is going through a technological revolution. In fact, new, simpler ways of communicating with each other are being invented every day. However, there is one group that has to be more cautious of what they send out over these social outlets than the rest of us do, celebrities, and in particular athletes. Athletes are constantly being thrown under the spotlight for controversial Figure 2 Although Rashard Mendenhall is exercising his right to free speech, his remarks garnered much animosity toward him and his team. Figure 2 Although Rashard Mendenhall is exercising his right to free speech, his remarks garnered much animosity toward him and his team. remarks made on social media websites, from Rashard Mendenhall of the Pittsburgh Steelers criticizing people for celebrating the death of Osama bin Laden (Figure 2) to TJ Lang of the Green Bay Packers bashing replacement referees for a blown last second call that cost his team the game. These statements made by athletes can cause them to lose fans across the country and possibly the globe. Social media also provides unwanted distractions to athletes everywhere that may take their mind off of performing to their utmost capability. Also, it can become such a problem that a team may eventually cut or fire a player based off of previous controversial comments made by the athlete. Professional athletes shouldn’t have access to social media outlets, despite the amusement fans see from their day-to-day access. Works Cited Babel, Ryan. â€Å"Twitter Trouble. N.p., n.d. Web. 25 Oct. 2012. http://sportsillustrated.cnn.com/multimedia/photo_gallery/0911/twitter.trouble/content.5.ht ml. Berman, Len. Trending Stories. Mashable. N.p., 4 Jan. 2010. Web. 25 Oct. 2012. http://mashable.com/2010/01/04/social-media-athletes/. Ottesen, Didrik. London 2012 Olympics: Australian Swimmer Emily Seebohm Blames Twitter and Facebook for Failure. Editorial. The Telegraph [London] 31 July 2012: n. pag. The Telegraph. 31 July 2012. Web. 21 Oct. 2012. http://www.telegraph.co.uk/sport/olympics/news/9440774/London-2012-Olympics- Australian-swimmer-Emily-Seebohm-blames-Twitter-and-Facebook-for-failure.html. Ortiz, Maria B. Twitter Gaffes Begat Punishment for Athletes. ESPN. Entertainment and Sports Programming Network, 27 July 2012. Web. 21 Oct. 2012. http://espn.go.com/blog/playbook/fandom/post/_/id/7495/voula-papachristou-inspires- twitter-fail-list.

Study on the Prediction of Corporate Bankruptcy

Study on the Prediction of Corporate Bankruptcy CHAPTER 1: A number of researches have been carried on the prediction of bankruptcy; formal studies linked with failure of business were conducted in 1930s. A study conducted by Simth and Winakor (1935) said that ratios of the failing firms were significantly changed from the continuing firms. In addition to that another study was related to the financial ratio of large size corporation that suffered in meeting fixed liability (Hickman 1958). Recent studies took potential ratios given in annual financial statements like profitability, solvency, and liquidity ratios considered as the most predictive indicator and these ratios were matched with failed and well worth firms for analysis. A group of financial and economic ratios were examined in the prediction of bankruptcy through multiple discriminant statistical technique, highest contributor ratios were profitability, operational profit/ total assets and very low contributor ratio was working capital/Assets (Altman, 1968). According to Pastena and Ruland (1968), the bankruptcy was defined in the literature review in various ways. Among those one was in a condition of negative worth where the market value of assets was less than the total value of liabilities. And the other was that the firm was not in a condition to pay back its liabilities as it became due. This term could also be used in a legal condition under which the firms continued to operate under court protection. 1.2 Problem Statement In the corporate finance, the prediction of corporate bankruptcy was considered to be one of the most important issues. The main objective behind the study of the prediction of corporate bankruptcy was that this was the most important issue for the present firms to either file for the bankruptcy or not. The rationale of the study was to examine whether the financial ratios given in detail by Altman (1968) presented the detail regarding the factors of the firm which were helpful in the prediction of corporate bankruptcy in Pakistan. The capacity of study was to investigate the distinctive financial ratios which impacted the firms decisions to file for the bankruptcy or not and on the basis of firms financial ratios, the research study found the different significant ratios which were useful in determining the prediction of any of the organization. 1.3 Hypotheses The main problem of the different firms was to identify those financial factors or the most important ratios which could lead to the filing of bankruptcy or those factors which were useful in determining the prediction of the corporate firms. A central query in front of firms which wanted to file for bankruptcy was why the firms filed for bankruptcy or what financial factors helped out in taking decision to file for bankruptcy. Various financial factors or ratios impacted the decision regarding the filing for bankruptcy. These financial characteristics or the most important ratios were current ratio, debt ratio, net profit margin, assets to long term debt ratio, and growth rate. Many authors as Altman (1968) discussed these characteristics in research. The hypothesized relationship of these listed financial factors with bankruptcy was provided below: H1: There is a difference between the Current ratio of bankrupted companies and non bankrupted companies. H2: There is a difference between the Debt ratio of bankrupted companies and non bankrupted companies. H3: There is a difference between the Net Profit Margin ratio of bankrupted companies and non bankrupted companies. H4: There is a difference between the Assets to long term debt ratio of bankrupted companies and non bankrupted companies. H5: There is a difference between the Growth rate of bankrupted companies and non bankrupted companies. 1.4 Outline of the Study The research structured as follows. Chapter one based on the introduction of the thesis, which consists of the some introduction of the prediction of bankruptcy by different authors, the statement of problem, scope and objectives, hypothesis etc. Chapter two consists of literature review given by different authors, theories on prediction of bankruptcy and financial factors affecting the choice of decision to file for bankruptcy or not. Chapter three described methodology which is composed of justification of the selection of the variables utilized in analysis sample, the data, technique and hypothesis, also estimate model utilized in analysis. In chapter four, analyses of the results were there which were taken after the data processing. Chapter five contained the final results, conclusions and recommendations. References are included in chapter number six. CHAPTER 2: LITERATURE REVIEW A number of researches have been carried on the prediction of bankruptcy; formal studies linked with failure of business were conducted in 1930s. A study conducted by Simth and winakor (1935) said that ratios of the failing firms were significantly change from the continuing firms. In addition to that an other study was related to the financial ratio of large size corporation that suffered in meeting fixed liability (Hickman 1958). Recent studies took potential ratios given in annual financial statements like profitability, solvency, and liquidity ratios considered as the most predictive indicator and these ratios were matched with failed and well worth firms for analysis. A group of financial and economic ratios were examined in the prediction of bankruptcy through multiple discriminant statistical technique, highest contributor ratios were profitability, operational profit/ total assets and very low contributor ratio was working capital/Assets (Altman, 1968). A study conducted by Sandin and Porporato (2007) on corporate bankruptcy prediction model applied to emerging economies. The aim of this study was to find the predictability of bankruptcy by using the financial ratios given in the financial statements and these financial statements were taken from the Buenos Aires Stock Exchange. To test the hypothesis twenty two bankrupt and non bankrupt companies were examined by using the multiple discriminant analysis technique, resulted that financial ratios were very useful in predicting the bankruptcy. Actually this study was about the prediction model and classification of the distressed and failed companies in the Argentina. William Beaver (1996) conducted a study that Financial Ratios As Predictor of Failure, wherein ratios were tested for a specific purpose. The purpose was to forecast the failure. Since ratios were mostly examined for the prediction of failure. The aim of the study was to analyze the status quo that was depended on the financial statements made under the reporting standard and this study was conducted as a bench mark for further studies in bankruptcy area. Sample of data was selected on the basis of industry, firm size and period, Walworth companies should have taken from the same industry where from failed companies taken along with same firm size based on firm value and equal time duration then reliable result can be obtained said by Beaver (1996). This study pointed out and directed to the asset size and relationship among ratios, assets size and failure, study implicated that larger firms were more solvent than smaller firms, even if ratios were same. To examine the hypothesis, a paired analysis was used. According to Pastena and Ruland (1968), the bankruptcy was defined in the literature review in various ways. Among those one was in a condition of negative worth where the market value of assets was less than the total value of liabilities. And the other was that the firm was not in a condition to pay back its liabilities as it became due. This term could also be used in a legal condition under which the firms continued to operate under court protection. Merger and Bankruptcy Based on the literature review in the different research studies, it was found that the shareholders of the distressed firms were getting more benefit from mergers than from the bankruptcy. Thus, the investors kept the positive number of the firms stocks up as a consequence of the merger. Contrastingly, the stakeholders received nothing in case of the bankruptcy. Shrieves and Stevens (1979) managed to explain all of the possible reasons for preferring merger over bankruptcy and those principles included: (1) to avoid the bankruptcy legal and administrative costs, (2) possible loss of tax carry forwards of the loss firm incurred on liquidation, (3) the value of the going-concern in the merger was more than liquidation value if the firm bankruptcy progressed towards the liquidation, and (4) the bankruptcy created the bad effects on the revenues including sales and income due to the customer fears of inability contracts, give replacement parts, etc. Bulow and Shoven (1978) noticed based on the research that the investors have always been avoiding the bankruptcy and this tendency always benefitted the creditors as a whole and that theoretically, the bankruptcy occurred because of the disagreement between the concerned parties. This was treated in a literature that the merger was the best possible alternate of the bankruptcy with the assumption in the mind that it was more easy for the distressed firms to find a merger partner at some price as long as the net asset value was positive and this was also under the assumption of a well-functioning market for information. When the situation was aggravated toward a condition of less or negative net asset value, the possibility of merger was reduced. Hong (1983) made an empirical as well as theoretical model which distinguished among three different categories of financially upset firms and it was organized in three ways such as: firms which filed bankruptcy but reorganized successfully, firms which filed for bankruptcy but were liquidated ultimately, and also the firms which continued operations with out even filing for bankruptcy. Author further made a hypothesis that the intangible assets, the value of the firm as in a going concern and the value of the same firm in liquidation was different, were the main describing factor which affected the eventual outcome. The firms which had greater intangible assets were possibly having a sustainable economic growth and that growth allowed a firm to survive rather than be liquidated. LoPucki (1983) made an explanatory study of about 41 firms which filed the bankruptcy court of the Western District of Missouri. In this study, the à ¢Ã¢â€š ¬Ã…“successesà ¢Ã¢â€š ¬? were defined as the firms which have verified its various reorganization strategies that kept it on to survive for about three years after the date of petitioning the bankruptcy. Failures according to the author were those firms which had stopped operating functions before February 1983. LoPucki (1983) further could not try to make a method with discriminatory power, but in fact simply scrutinized the associations between the results of reorganization process and numerous individual variables. These individual variables included size, age, and type of the businesses, the survival of creditors opposition to the reorganization strategy, and physical geographic location. The relationships which were found during the research were: significantly higher success rate was associated with the manufacturing fi rms; more successful firms were only the larger firms; success was not significantly associated with the age of the firms; the target opposition of the creditors was mainly at the more successful firms; and lastly, the physical geographical location was not a significant describing variable. In short, only a finite amount of research was conducted on the topic of differentiating between failures and successes in bankruptcy, and outcomes have been open to doubts or inconclusive. The one published study conducted by the LoPucki (1983), scrutinized the first order correlations and could not struggle to build the model of classification. The other published research study conducted by Hong (1983), scrutinized the comparative importance of numerous individual variables and had not analyzed the classification authentication of the multivariate model. As it was already discussed in detail, this present study scrutinized the classification authentication of the multivariate model by using data from both analysis sample and a holdout sample 113 firms. Bordman, Bartley, and Ratliff (1981) noticed that firms went bankrupt only when its capital resources were not enough to pay back the obligations of the business. Thus it became the more important challenge for the new comers in the industry to maintain and establish such valuable resources and capabilities which could ultimately leaded to the production of positive cash flows before starting asset resources were exhausted (Levinthal, 1991). According to DAveni (1989), and Hambrick and DAveni (1988), both researches have noticed that most of the attention has been paid to the early failures and dramatic research has also been conducted in the literature. A macro view of the bankruptcy was given as a known strategy and an empirical examination of factors associated to successful reorganization (Moultan, and Thomas, 1993) and however, the structures of corporate governance were not incorporated in the analysis. An extensive data was available relating the intensity to which the officers and directors of the firm which was bankrupt were more possibly resigning or were being replaced (DAveni, 1990; Fizel Louie, 1990; Gilson, 1989). Several researchers used the multiple discriminant analysis MDA technique to develop a linear model to predict those firms which failed could be differentiated from the non-failed firms in UK (Taffler, 1977). This model resulted in an overall classification authentication for the year before the failure as comparative to three or two prior years of failure. The major contribution made by Taffler was the establishment of a Z-score model which was used for the prediction of company failures in the UK and furthermore, the author claimed of 100 percent predictive authentication in the model. In addition, in the consequent studies, Taffler (1982, 1983) discussed the pairing technique which was used in the prediction of corporate failure studies proved no more successful technique than any selection by the other tool or technique. Multiple Discriminant Analysis MDA models were dependable to certain intensity in the prediction of corporate failure. CHAPTER 3: RESEARCH METHODS 3.1 Method of Data Collection Data was selected from Karachi Stock Exchange KSE 100 Index as given by State Bank of Pakistan in publication Balance Sheet Analysis of Joint Stock Companies Listed on the KSE (2004-2009). The period of study covers six years, 2004-09. The opted sample size of 44 firms was taken from KSE 100 Index and all of the firms listed on KSE 100 Index were selected for the samples which were going to bankruptcy in the past and some were also the present functioning firms which were currently working; so, only 44 firms included in the sample period of 2004-09. The objective behind the inclusion of these selected firms in the sample was that the inclusion of bankrupt and non-bankrupt firms in the analysis made it easier to distinguish the critical financial ratios of these both firms in order to predict for corporate bankruptcy. The data availability was the major issue faced in this research study. The secondary data sources were adopted for the collection of the data during this research study. Both of the empirical and theoretical aspects regarding the prediction of corporate bankruptcy were analyzed in this research study. For the purpose of the collection of the secondary data, external data sources were used, such as the data was collected from State Bank of Pakistan, general business publications, newspapers and journal articles, annual reports, internet and books. The data required for this study was completely dependent on the published data sources, such as the published sources listed above. 3.2 Sample Size A sample of 44 firms from KSE 100 Index was selected and in addition, out of these firms 22 firms were bankrupt and the remaining 22 were not bankrupt which was taken as the holdout sample for the prediction of the corporate bankruptcy. Only firms were used in the samples which were either became bankrupt due to the impact of the some of the financial factors or the ratios or the firms which were in operations during the research study was conducted and these firms were listed on the KSE 100 Index form 2004-2009. The impact of the different financial factors or ratios, which were listed in the previous chapters, on the prediction of corporate bankruptcy was analyzed on all of the firms selected as the sample. 3.3 Research Model Developed There are various financial factors or the ratios of the firms which affected the prediction of the corporate bankruptcy of the firms. This research study analyzed the impact of different factors or ratios already listed in the previous chapters on the prediction of corporate bankruptcy. The model developed was a binary logistic model and its specifications are provided below: Liquidity = a0 + a1Firm Size + a2DEBT + a3LTD + a4LSALES + a5OI/S + a6OI/TA+ a7IGP/TA+ a8Market to Book Ratio + ц where: Liquidity = the sum of cash and marketable securities divided by total assets Firm Size = natural log of the book value of total assets DEBT = the ratio of shorter period plus longer period debt to total assets LTD = the ratio of longer period debt to total assets LSALES = natural log of the annual sales OI/S = the ratio of operating income to sales OI/TA = the ratio of operating income to total sales IGP/TA = the inventory plus gross fixed assets to total assets ratio à Ã¢â‚¬Å¾ = the error term 3.4 Statistical Technique Binary Logistic Regression Analysis technique was used for this research study to examine the impact of the distinctive financial characteristics or the financial ratios of the firms on the prediction of corporate bankruptcy of the selected firms; Statistical Package for the Social Sciences (SPSS) was used for the examination of the secondary data. Binary Logistic Regression Analysis technique was used for the purpose of prediction of of corporate bankruptcy or the prediction of the firms decisions to file for bankruptcy. The selected technique was used to study the impact of the different independent variables (financial factors as listed in the previous chapters) on the dependent variable i.e., prediction of corporate bankruptcy. The binary logistic regression analysis was selected for this study. It showed the intensity of the impact on the prediction of corporate bankruptcy during year 2004-2009 on the basis of several independent variables. CHAPTER 4: RESULTS The sample of 44 firms from the Karachi Stock Exchange KSE 100 Index was taken; Binary Logistic Regression Analysis technique was used for this research study. Research examined the distinctive financial characteristics or financial ratios of firms which filed for the bankruptcy. The selected technique was used to study the impact of the different independent variables (financial factors as listed in the previous chapters) on the dependent variable i.e., the prediction of corporate bankruptcy. Statistical Package for the Social Sciences (SPSS) was used for the analysis and examination of data. 4.1 Findings and Interpretation of the results Initially, the binary logistic regression technique was applied on the data collected using SPSS. Now, it was a nice time to proceed with the analysis of the results because the data was collected and ready to be examined. The interpretation and analysis is presented in the next sections of this research study. Case Processing Summary Unweighted Casesa N Percent Selected Cases Included in Analysis 192 91.4 Missing Cases 18 8.6 Total 210 100.0 Unselected Cases 0 .0 Total 210 100.0 This table explains the total population in the data file that is the 210 observations or the cases for the analysis of the bankruptcy prediction. This table further elaborates that the there were also some of the cases missing in the data because of the issue of data availability and some of the cases were the figures of zero. Dependent Variable Encoding Original Value Internal Value Bankrupt 0 Non-Bankrupt 1 The above table shows that there are only two variables in the dependent variable of bankruptcy that are the being bankrupt or non-bankrupt. Model Summary Step -2 Log likelihood Cox Snell R Square Nagelkerke R Square 1 234.707a .144 .192 This table elaborates the predictability of the complete model of the logistic regression which meant that to what extent the model predict the variation in the predicted group of bankruptcy. According to Cox Snell, the total predictors jointly explained variation in the groups of bankruptcy was 14.4%. While according to Nagelkirki, the all independent variable explained the group prediction of about 19.2%. Hosmer and Lemeshow Test Step Chi-square df Sig. 1 32.715 8 .000 This table checks the overall model fit which means that the model is at its best in predicting the group variation from non-bankrupt to bankrupt. The hypothesis of the above table is that the test model is fit. The hypothesis is rejected because the sig value is less than .05 which concluded that the test model was not fit in this case of predicting the group variation. Classification Tablea Observed Predicted Banckruptcy Percentage Correct Bankrupt Non-Bankrupt Step 1 Banckruptcy Bankrupt 76 29 72.4 Non-Bankrupt 43 44 50.6 Overall Percentage 62.5 The classification table is the most important table in case of the logistic regression because this table explained the correct identification of the cases correctly identified. The percentage of correctly identified cases is 62.5% which is also commonly known as the hit ratio which means that to what extent the numbers of cases were correctly identified. Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a DA -1.219 .510 5.725 1 .017 .295 .109 .802 AtoLTD -.002 .001 1.583 1 .208 .998 .996 1.001 CR .938 .348 7.242 1 .007 2.554 1.290 5.056 NPM .037 .073 .262 1 .609 1.038 .899 1.198 SG .161 .232 .482 1 .488 1.175 .745 1.852 Constant .066 .579 .013 1 .910 1.068 This is the final most important table in the logistic regression because this is the only table which shows the role of different predictors in significantly explaining the role in the prediction of group variations. Those important significant variables were only two that were DA, and CR because the sig value of only these variables were less than .05. 4.2 Hypotheses Assessment Summary The hypothesis of the study was distinctive financial ratios have significant impact on the non firms decision to file for bankruptcy. These financial characteristics were current ratio (CR), debt ratio (DA), net profit margin (NPM), assets to long term debt ratio, and growth rate. In this study each of the financial characteristics or financial ratios of firms was tested and concluded the results. TABLE 4.4 : Hypotheses Assessment Summary S.NO. Hypotheses ÃŽÂ ²       SIG. RESULT H1 There is a difference between the Current ratio of bankrupted companies and non bankrupted companies. 0.938 0.007 Accepted H2 There is a difference between the Debt Ratio of bankrupted companies and non bankrupted companies. -1.219 0.017 Accepted H3 There is a difference between the Net Profit Margin Ratio of bankrupted companies and non bankrupted companies. 0.037 0.609 Rejected H4 There is a difference between the Assets to long term debt ratio of bankrupted companies and non bankrupted companies. -0.002 0.208 Rejected H5 There is a difference between the Growth rate of bankrupted companies and non bankrupted companies. 0.161 0.488 Rejected CHAPTER 5: DISCUSSIONS, CONCLUSION, IMPLICATIONS AND FUTURE RESEARCH 5.1 Conclusion It was concluded based on the results of this research study that current ratio and debt ratio were only the independent variables which were showing significance in Pakistani market and these variables were highly significant in playing the vital role explaining the variation in the dependent variable of the prediction of corporate bankruptcy and the remaining independent variables could not explain the variation in the prediction of corporate bankruptcy. These results were not matching with the study conducted by Altman (1968). These results were varying because in various countries, there was difference in environments and circumstances and firms usually made decision accordingly. 5.2 Discussions Current ratio played a significant role in defining the variation in the prediction of corporate bankruptcy and this was also the case with the research study conducted by Altman (1968) because in his study the firm size was also playing a significant role. The variation in the prediction of corporate bankruptcy was not explained by the net profit margin ratio while it was significant in the study done by Altman (1968). The assets to long term debt ratio, and growth rate were not significantly explaining the variation in the prediction of corporate bankruptcy and study analyzed by Altman (1968), concluded the different results with some addition. 5.3 Implications and Recommendations This research was limited to the various firms listed on Karachi Stock Exchange of Pakistan only. The data taken from 44 firms which were took through various sectors of the KSE 100 Index for the year 2004-09 which were previously bankrupt and which were currently operating. It suggested that such type of study should be carried out in other countries of Asia as well, as to have comprehensive idea about the choices of the firms decision to file for bankruptcy. Moreover, it also suggested that other factors except ones examined in this study should be researched as to have perfect idea about the selection of the prediction of corporate bankruptcy. Besides that, this study can also be replicated in other developing countries. 5.4 Future Research This study helped various investors, management and other research conductors in analyzing and observing the behavior of firms regarding their decisions to file for the bankruptcy. Research students who want to work further on the prediction of bankruptcy can be benefited by this research study. Further more, the firms will become advantageous from this study because the study clarifies the distinctive financial characteristics or the financial ratios of different firms which significantly explain the variations in the prediction of corporate bankruptcy. Study on the Prediction of Corporate Bankruptcy Study on the Prediction of Corporate Bankruptcy CHAPTER 1: A number of researches have been carried on the prediction of bankruptcy; formal studies linked with failure of business were conducted in 1930s. A study conducted by Simth and Winakor (1935) said that ratios of the failing firms were significantly changed from the continuing firms. In addition to that another study was related to the financial ratio of large size corporation that suffered in meeting fixed liability (Hickman 1958). Recent studies took potential ratios given in annual financial statements like profitability, solvency, and liquidity ratios considered as the most predictive indicator and these ratios were matched with failed and well worth firms for analysis. A group of financial and economic ratios were examined in the prediction of bankruptcy through multiple discriminant statistical technique, highest contributor ratios were profitability, operational profit/ total assets and very low contributor ratio was working capital/Assets (Altman, 1968). According to Pastena and Ruland (1968), the bankruptcy was defined in the literature review in various ways. Among those one was in a condition of negative worth where the market value of assets was less than the total value of liabilities. And the other was that the firm was not in a condition to pay back its liabilities as it became due. This term could also be used in a legal condition under which the firms continued to operate under court protection. 1.2 Problem Statement In the corporate finance, the prediction of corporate bankruptcy was considered to be one of the most important issues. The main objective behind the study of the prediction of corporate bankruptcy was that this was the most important issue for the present firms to either file for the bankruptcy or not. The rationale of the study was to examine whether the financial ratios given in detail by Altman (1968) presented the detail regarding the factors of the firm which were helpful in the prediction of corporate bankruptcy in Pakistan. The capacity of study was to investigate the distinctive financial ratios which impacted the firms decisions to file for the bankruptcy or not and on the basis of firms financial ratios, the research study found the different significant ratios which were useful in determining the prediction of any of the organization. 1.3 Hypotheses The main problem of the different firms was to identify those financial factors or the most important ratios which could lead to the filing of bankruptcy or those factors which were useful in determining the prediction of the corporate firms. A central query in front of firms which wanted to file for bankruptcy was why the firms filed for bankruptcy or what financial factors helped out in taking decision to file for bankruptcy. Various financial factors or ratios impacted the decision regarding the filing for bankruptcy. These financial characteristics or the most important ratios were current ratio, debt ratio, net profit margin, assets to long term debt ratio, and growth rate. Many authors as Altman (1968) discussed these characteristics in research. The hypothesized relationship of these listed financial factors with bankruptcy was provided below: H1: There is a difference between the Current ratio of bankrupted companies and non bankrupted companies. H2: There is a difference between the Debt ratio of bankrupted companies and non bankrupted companies. H3: There is a difference between the Net Profit Margin ratio of bankrupted companies and non bankrupted companies. H4: There is a difference between the Assets to long term debt ratio of bankrupted companies and non bankrupted companies. H5: There is a difference between the Growth rate of bankrupted companies and non bankrupted companies. 1.4 Outline of the Study The research structured as follows. Chapter one based on the introduction of the thesis, which consists of the some introduction of the prediction of bankruptcy by different authors, the statement of problem, scope and objectives, hypothesis etc. Chapter two consists of literature review given by different authors, theories on prediction of bankruptcy and financial factors affecting the choice of decision to file for bankruptcy or not. Chapter three described methodology which is composed of justification of the selection of the variables utilized in analysis sample, the data, technique and hypothesis, also estimate model utilized in analysis. In chapter four, analyses of the results were there which were taken after the data processing. Chapter five contained the final results, conclusions and recommendations. References are included in chapter number six. CHAPTER 2: LITERATURE REVIEW A number of researches have been carried on the prediction of bankruptcy; formal studies linked with failure of business were conducted in 1930s. A study conducted by Simth and winakor (1935) said that ratios of the failing firms were significantly change from the continuing firms. In addition to that an other study was related to the financial ratio of large size corporation that suffered in meeting fixed liability (Hickman 1958). Recent studies took potential ratios given in annual financial statements like profitability, solvency, and liquidity ratios considered as the most predictive indicator and these ratios were matched with failed and well worth firms for analysis. A group of financial and economic ratios were examined in the prediction of bankruptcy through multiple discriminant statistical technique, highest contributor ratios were profitability, operational profit/ total assets and very low contributor ratio was working capital/Assets (Altman, 1968). A study conducted by Sandin and Porporato (2007) on corporate bankruptcy prediction model applied to emerging economies. The aim of this study was to find the predictability of bankruptcy by using the financial ratios given in the financial statements and these financial statements were taken from the Buenos Aires Stock Exchange. To test the hypothesis twenty two bankrupt and non bankrupt companies were examined by using the multiple discriminant analysis technique, resulted that financial ratios were very useful in predicting the bankruptcy. Actually this study was about the prediction model and classification of the distressed and failed companies in the Argentina. William Beaver (1996) conducted a study that Financial Ratios As Predictor of Failure, wherein ratios were tested for a specific purpose. The purpose was to forecast the failure. Since ratios were mostly examined for the prediction of failure. The aim of the study was to analyze the status quo that was depended on the financial statements made under the reporting standard and this study was conducted as a bench mark for further studies in bankruptcy area. Sample of data was selected on the basis of industry, firm size and period, Walworth companies should have taken from the same industry where from failed companies taken along with same firm size based on firm value and equal time duration then reliable result can be obtained said by Beaver (1996). This study pointed out and directed to the asset size and relationship among ratios, assets size and failure, study implicated that larger firms were more solvent than smaller firms, even if ratios were same. To examine the hypothesis, a paired analysis was used. According to Pastena and Ruland (1968), the bankruptcy was defined in the literature review in various ways. Among those one was in a condition of negative worth where the market value of assets was less than the total value of liabilities. And the other was that the firm was not in a condition to pay back its liabilities as it became due. This term could also be used in a legal condition under which the firms continued to operate under court protection. Merger and Bankruptcy Based on the literature review in the different research studies, it was found that the shareholders of the distressed firms were getting more benefit from mergers than from the bankruptcy. Thus, the investors kept the positive number of the firms stocks up as a consequence of the merger. Contrastingly, the stakeholders received nothing in case of the bankruptcy. Shrieves and Stevens (1979) managed to explain all of the possible reasons for preferring merger over bankruptcy and those principles included: (1) to avoid the bankruptcy legal and administrative costs, (2) possible loss of tax carry forwards of the loss firm incurred on liquidation, (3) the value of the going-concern in the merger was more than liquidation value if the firm bankruptcy progressed towards the liquidation, and (4) the bankruptcy created the bad effects on the revenues including sales and income due to the customer fears of inability contracts, give replacement parts, etc. Bulow and Shoven (1978) noticed based on the research that the investors have always been avoiding the bankruptcy and this tendency always benefitted the creditors as a whole and that theoretically, the bankruptcy occurred because of the disagreement between the concerned parties. This was treated in a literature that the merger was the best possible alternate of the bankruptcy with the assumption in the mind that it was more easy for the distressed firms to find a merger partner at some price as long as the net asset value was positive and this was also under the assumption of a well-functioning market for information. When the situation was aggravated toward a condition of less or negative net asset value, the possibility of merger was reduced. Hong (1983) made an empirical as well as theoretical model which distinguished among three different categories of financially upset firms and it was organized in three ways such as: firms which filed bankruptcy but reorganized successfully, firms which filed for bankruptcy but were liquidated ultimately, and also the firms which continued operations with out even filing for bankruptcy. Author further made a hypothesis that the intangible assets, the value of the firm as in a going concern and the value of the same firm in liquidation was different, were the main describing factor which affected the eventual outcome. The firms which had greater intangible assets were possibly having a sustainable economic growth and that growth allowed a firm to survive rather than be liquidated. LoPucki (1983) made an explanatory study of about 41 firms which filed the bankruptcy court of the Western District of Missouri. In this study, the à ¢Ã¢â€š ¬Ã…“successesà ¢Ã¢â€š ¬? were defined as the firms which have verified its various reorganization strategies that kept it on to survive for about three years after the date of petitioning the bankruptcy. Failures according to the author were those firms which had stopped operating functions before February 1983. LoPucki (1983) further could not try to make a method with discriminatory power, but in fact simply scrutinized the associations between the results of reorganization process and numerous individual variables. These individual variables included size, age, and type of the businesses, the survival of creditors opposition to the reorganization strategy, and physical geographic location. The relationships which were found during the research were: significantly higher success rate was associated with the manufacturing fi rms; more successful firms were only the larger firms; success was not significantly associated with the age of the firms; the target opposition of the creditors was mainly at the more successful firms; and lastly, the physical geographical location was not a significant describing variable. In short, only a finite amount of research was conducted on the topic of differentiating between failures and successes in bankruptcy, and outcomes have been open to doubts or inconclusive. The one published study conducted by the LoPucki (1983), scrutinized the first order correlations and could not struggle to build the model of classification. The other published research study conducted by Hong (1983), scrutinized the comparative importance of numerous individual variables and had not analyzed the classification authentication of the multivariate model. As it was already discussed in detail, this present study scrutinized the classification authentication of the multivariate model by using data from both analysis sample and a holdout sample 113 firms. Bordman, Bartley, and Ratliff (1981) noticed that firms went bankrupt only when its capital resources were not enough to pay back the obligations of the business. Thus it became the more important challenge for the new comers in the industry to maintain and establish such valuable resources and capabilities which could ultimately leaded to the production of positive cash flows before starting asset resources were exhausted (Levinthal, 1991). According to DAveni (1989), and Hambrick and DAveni (1988), both researches have noticed that most of the attention has been paid to the early failures and dramatic research has also been conducted in the literature. A macro view of the bankruptcy was given as a known strategy and an empirical examination of factors associated to successful reorganization (Moultan, and Thomas, 1993) and however, the structures of corporate governance were not incorporated in the analysis. An extensive data was available relating the intensity to which the officers and directors of the firm which was bankrupt were more possibly resigning or were being replaced (DAveni, 1990; Fizel Louie, 1990; Gilson, 1989). Several researchers used the multiple discriminant analysis MDA technique to develop a linear model to predict those firms which failed could be differentiated from the non-failed firms in UK (Taffler, 1977). This model resulted in an overall classification authentication for the year before the failure as comparative to three or two prior years of failure. The major contribution made by Taffler was the establishment of a Z-score model which was used for the prediction of company failures in the UK and furthermore, the author claimed of 100 percent predictive authentication in the model. In addition, in the consequent studies, Taffler (1982, 1983) discussed the pairing technique which was used in the prediction of corporate failure studies proved no more successful technique than any selection by the other tool or technique. Multiple Discriminant Analysis MDA models were dependable to certain intensity in the prediction of corporate failure. CHAPTER 3: RESEARCH METHODS 3.1 Method of Data Collection Data was selected from Karachi Stock Exchange KSE 100 Index as given by State Bank of Pakistan in publication Balance Sheet Analysis of Joint Stock Companies Listed on the KSE (2004-2009). The period of study covers six years, 2004-09. The opted sample size of 44 firms was taken from KSE 100 Index and all of the firms listed on KSE 100 Index were selected for the samples which were going to bankruptcy in the past and some were also the present functioning firms which were currently working; so, only 44 firms included in the sample period of 2004-09. The objective behind the inclusion of these selected firms in the sample was that the inclusion of bankrupt and non-bankrupt firms in the analysis made it easier to distinguish the critical financial ratios of these both firms in order to predict for corporate bankruptcy. The data availability was the major issue faced in this research study. The secondary data sources were adopted for the collection of the data during this research study. Both of the empirical and theoretical aspects regarding the prediction of corporate bankruptcy were analyzed in this research study. For the purpose of the collection of the secondary data, external data sources were used, such as the data was collected from State Bank of Pakistan, general business publications, newspapers and journal articles, annual reports, internet and books. The data required for this study was completely dependent on the published data sources, such as the published sources listed above. 3.2 Sample Size A sample of 44 firms from KSE 100 Index was selected and in addition, out of these firms 22 firms were bankrupt and the remaining 22 were not bankrupt which was taken as the holdout sample for the prediction of the corporate bankruptcy. Only firms were used in the samples which were either became bankrupt due to the impact of the some of the financial factors or the ratios or the firms which were in operations during the research study was conducted and these firms were listed on the KSE 100 Index form 2004-2009. The impact of the different financial factors or ratios, which were listed in the previous chapters, on the prediction of corporate bankruptcy was analyzed on all of the firms selected as the sample. 3.3 Research Model Developed There are various financial factors or the ratios of the firms which affected the prediction of the corporate bankruptcy of the firms. This research study analyzed the impact of different factors or ratios already listed in the previous chapters on the prediction of corporate bankruptcy. The model developed was a binary logistic model and its specifications are provided below: Liquidity = a0 + a1Firm Size + a2DEBT + a3LTD + a4LSALES + a5OI/S + a6OI/TA+ a7IGP/TA+ a8Market to Book Ratio + ц where: Liquidity = the sum of cash and marketable securities divided by total assets Firm Size = natural log of the book value of total assets DEBT = the ratio of shorter period plus longer period debt to total assets LTD = the ratio of longer period debt to total assets LSALES = natural log of the annual sales OI/S = the ratio of operating income to sales OI/TA = the ratio of operating income to total sales IGP/TA = the inventory plus gross fixed assets to total assets ratio à Ã¢â‚¬Å¾ = the error term 3.4 Statistical Technique Binary Logistic Regression Analysis technique was used for this research study to examine the impact of the distinctive financial characteristics or the financial ratios of the firms on the prediction of corporate bankruptcy of the selected firms; Statistical Package for the Social Sciences (SPSS) was used for the examination of the secondary data. Binary Logistic Regression Analysis technique was used for the purpose of prediction of of corporate bankruptcy or the prediction of the firms decisions to file for bankruptcy. The selected technique was used to study the impact of the different independent variables (financial factors as listed in the previous chapters) on the dependent variable i.e., prediction of corporate bankruptcy. The binary logistic regression analysis was selected for this study. It showed the intensity of the impact on the prediction of corporate bankruptcy during year 2004-2009 on the basis of several independent variables. CHAPTER 4: RESULTS The sample of 44 firms from the Karachi Stock Exchange KSE 100 Index was taken; Binary Logistic Regression Analysis technique was used for this research study. Research examined the distinctive financial characteristics or financial ratios of firms which filed for the bankruptcy. The selected technique was used to study the impact of the different independent variables (financial factors as listed in the previous chapters) on the dependent variable i.e., the prediction of corporate bankruptcy. Statistical Package for the Social Sciences (SPSS) was used for the analysis and examination of data. 4.1 Findings and Interpretation of the results Initially, the binary logistic regression technique was applied on the data collected using SPSS. Now, it was a nice time to proceed with the analysis of the results because the data was collected and ready to be examined. The interpretation and analysis is presented in the next sections of this research study. Case Processing Summary Unweighted Casesa N Percent Selected Cases Included in Analysis 192 91.4 Missing Cases 18 8.6 Total 210 100.0 Unselected Cases 0 .0 Total 210 100.0 This table explains the total population in the data file that is the 210 observations or the cases for the analysis of the bankruptcy prediction. This table further elaborates that the there were also some of the cases missing in the data because of the issue of data availability and some of the cases were the figures of zero. Dependent Variable Encoding Original Value Internal Value Bankrupt 0 Non-Bankrupt 1 The above table shows that there are only two variables in the dependent variable of bankruptcy that are the being bankrupt or non-bankrupt. Model Summary Step -2 Log likelihood Cox Snell R Square Nagelkerke R Square 1 234.707a .144 .192 This table elaborates the predictability of the complete model of the logistic regression which meant that to what extent the model predict the variation in the predicted group of bankruptcy. According to Cox Snell, the total predictors jointly explained variation in the groups of bankruptcy was 14.4%. While according to Nagelkirki, the all independent variable explained the group prediction of about 19.2%. Hosmer and Lemeshow Test Step Chi-square df Sig. 1 32.715 8 .000 This table checks the overall model fit which means that the model is at its best in predicting the group variation from non-bankrupt to bankrupt. The hypothesis of the above table is that the test model is fit. The hypothesis is rejected because the sig value is less than .05 which concluded that the test model was not fit in this case of predicting the group variation. Classification Tablea Observed Predicted Banckruptcy Percentage Correct Bankrupt Non-Bankrupt Step 1 Banckruptcy Bankrupt 76 29 72.4 Non-Bankrupt 43 44 50.6 Overall Percentage 62.5 The classification table is the most important table in case of the logistic regression because this table explained the correct identification of the cases correctly identified. The percentage of correctly identified cases is 62.5% which is also commonly known as the hit ratio which means that to what extent the numbers of cases were correctly identified. Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a DA -1.219 .510 5.725 1 .017 .295 .109 .802 AtoLTD -.002 .001 1.583 1 .208 .998 .996 1.001 CR .938 .348 7.242 1 .007 2.554 1.290 5.056 NPM .037 .073 .262 1 .609 1.038 .899 1.198 SG .161 .232 .482 1 .488 1.175 .745 1.852 Constant .066 .579 .013 1 .910 1.068 This is the final most important table in the logistic regression because this is the only table which shows the role of different predictors in significantly explaining the role in the prediction of group variations. Those important significant variables were only two that were DA, and CR because the sig value of only these variables were less than .05. 4.2 Hypotheses Assessment Summary The hypothesis of the study was distinctive financial ratios have significant impact on the non firms decision to file for bankruptcy. These financial characteristics were current ratio (CR), debt ratio (DA), net profit margin (NPM), assets to long term debt ratio, and growth rate. In this study each of the financial characteristics or financial ratios of firms was tested and concluded the results. TABLE 4.4 : Hypotheses Assessment Summary S.NO. Hypotheses ÃŽÂ ²       SIG. RESULT H1 There is a difference between the Current ratio of bankrupted companies and non bankrupted companies. 0.938 0.007 Accepted H2 There is a difference between the Debt Ratio of bankrupted companies and non bankrupted companies. -1.219 0.017 Accepted H3 There is a difference between the Net Profit Margin Ratio of bankrupted companies and non bankrupted companies. 0.037 0.609 Rejected H4 There is a difference between the Assets to long term debt ratio of bankrupted companies and non bankrupted companies. -0.002 0.208 Rejected H5 There is a difference between the Growth rate of bankrupted companies and non bankrupted companies. 0.161 0.488 Rejected CHAPTER 5: DISCUSSIONS, CONCLUSION, IMPLICATIONS AND FUTURE RESEARCH 5.1 Conclusion It was concluded based on the results of this research study that current ratio and debt ratio were only the independent variables which were showing significance in Pakistani market and these variables were highly significant in playing the vital role explaining the variation in the dependent variable of the prediction of corporate bankruptcy and the remaining independent variables could not explain the variation in the prediction of corporate bankruptcy. These results were not matching with the study conducted by Altman (1968). These results were varying because in various countries, there was difference in environments and circumstances and firms usually made decision accordingly. 5.2 Discussions Current ratio played a significant role in defining the variation in the prediction of corporate bankruptcy and this was also the case with the research study conducted by Altman (1968) because in his study the firm size was also playing a significant role. The variation in the prediction of corporate bankruptcy was not explained by the net profit margin ratio while it was significant in the study done by Altman (1968). The assets to long term debt ratio, and growth rate were not significantly explaining the variation in the prediction of corporate bankruptcy and study analyzed by Altman (1968), concluded the different results with some addition. 5.3 Implications and Recommendations This research was limited to the various firms listed on Karachi Stock Exchange of Pakistan only. The data taken from 44 firms which were took through various sectors of the KSE 100 Index for the year 2004-09 which were previously bankrupt and which were currently operating. It suggested that such type of study should be carried out in other countries of Asia as well, as to have comprehensive idea about the choices of the firms decision to file for bankruptcy. Moreover, it also suggested that other factors except ones examined in this study should be researched as to have perfect idea about the selection of the prediction of corporate bankruptcy. Besides that, this study can also be replicated in other developing countries. 5.4 Future Research This study helped various investors, management and other research conductors in analyzing and observing the behavior of firms regarding their decisions to file for the bankruptcy. Research students who want to work further on the prediction of bankruptcy can be benefited by this research study. Further more, the firms will become advantageous from this study because the study clarifies the distinctive financial characteristics or the financial ratios of different firms which significantly explain the variations in the prediction of corporate bankruptcy.

Fields Of Psychology :: essays research papers

Psychology (Ph.D. Code: PSY) Fields of study: Clinical, cognitive, and social psychology; neuroscience and behavior; visual perception. The program offers doctoral study for students who intend to become psychological scientists or scientist-practitioners. Students who plan to terminate their studies with the master's degree are not encouraged to apply. Admission is not limited to students with undergraduate backgrounds in psychology. Theory, method, and research experience in a number of areas of psychological science are emphasized. Course requirements are organized into the three broad areas of cognitive science, neuroscience, and clinical science. Students have intensive research training with individual faculty in the areas of clinical psychology, cognition, functional imaging, perception, psychobiology, sensory neurophysiology, and social psychology. Students in clinical psychology are also provided with extensive training in clinical skills. Major practicum facilities in which students receive supervised clinical and/or applied research training are found in the Vanderbilt Medical Center and other institutions in Nashville. The department is in a building which offers generous laboratory space for individual and group experiments with human subjects, and facilities for animal experimentation. It has a computerized classroom and connections to the campus mainframe computers. Computerized equipment for neuroanatomy, neurophysiology, and psychophysics is also available and is especially suited for work on sensory systems. Human subjects are available through a University research pool, Vanderbilt clinics, and the local school system. In addition, the department has an animal facility providing a wide variety of species, including fish, rodents, and primates. Faculty: 22 Graduate enrollment: In residence 37; average in entering class 5-8 Address: 111 21st Avenue South; 37240 Phone: (615) 322-2874 E-mail: patricia.m.burns@vanderbilt.edu [Psychology] Psychology and Human Development (M.S., Ph.D. Code: GPSY) Fields of study: Clinical, cognitive studies, community, developmental, and quantitative psychology. The Clinical program focuses primarily on issues facing children and families. Faculty members study the development of aggressive behavior and depression in children and adolescents; psychological factors accompanying developmental disability and chronic physical disease; the role of communities in mental health; cognitive intervention for learning and behavioral problems; and the delivery of mental health services to children, youth, and families. The goal of the clinical program is to educate psychologists as scientists and practitioners so that they may pursue a variety of career paths. The Cognitive Studies program focuses on laboratory- and field-based research into cognitive processes as they occur in formal and informal learning situations. Areas of research emphasis include cognition, instruction, and technology; cognitive development;

Bless Me, Ultima Essay -- essays research papers

The loss of innocence in life is an inevitable process. Losing one’s innocence comes merely by growing up. The philosophy of the loss of one’s innocence is a definite theme in the book Bless Me, Ultima. This theme is displayed throughout the entire story and plot of the novel. There is loss of innocence all around the main character, Tony, with his brothers and the people he meets. Tony also loses a great deal of his own innocence to the harsh realities of the world which marks his transition from a boy to a man.   Ã‚  Ã‚  Ã‚  Ã‚  The theme of the loss of innocence covers the entire essence of the book. There are many cases in the story where people had lost their innocence of life and it was lost to them forever. Tony’s brothers are of such a case. They had gone to war to fight for their country and explore the world. But as they yearned and sought the outside and how it was, they lost their innocence in the process. Being in war they saw death and destruction which soiled their once virgin eyes. Although they gained knowledge and experience they were becoming no longer young and gay, but were becoming mature and knowledgeable. Growing at such a fast pace was a regretful process, that even Andrew advised Tony to not grow too fast but that would not happen as we know.   Ã‚  Ã‚  Ã‚  Ã‚  Another example of loss of innocence in the book would be Tony’s friends. The gang seems to be fairly innocent enough but they ...

Mercedes :: essays research papers

The 1996 Mercedes E320 sustained crash damage to the passenger side front. After we set up and measured the vehicle on the caro-liner frame rack, we found there to be extensive panel, sub frame, and suspension damage. Including consequential interior damage, IE; Driver/passenger airbags deployed, dash panel assembly, and passenger airbags deployed, dash panel assembly, and passenger side mirror. After a complete damage assessment report, we then began disassembly of all damaged panels and assemblies. After the disassembly we decided which parts would be salvaged off of our 1997 Mercedes E320, which parts would be purchased new or those which would need to be straightened and refinished. Once the damaged panels were removed we were able to attach the 10-ton hydraulic ram assembly to the frame rack and began the frame straightening repairs. Our initial pulls were to fix the sway problem of the passenger side front sub frame. This was accomplished by wrapping a chain around the misaligned sub frame, pulling in a straight, level manner opposite the direction of the misalignment. We did several pulls in this manner, stress relieving, before and during, with a ball peen hammer before repositioning for the next pull until brought back into specification. We then positioned our 10-ton ram to the passenger front for repair of the frame rail mash and sag situation sustained on impact. We wrapped the chain around crash impact bar and used it as the hook up point for our pulls. Pulling and stress receiving until it also was within specifications. Our final pull was to the suspension passenger side A-arm. We simply attached our chains to the A-arm and pulled it back into positio n. At this point, we could now begin sectioning and panel removal. This was first done by deciding which panels were to be removed and which were to be repaired. Then all of the spot welds that needed to be removed were marked with a paint marker, so as to only to remove the necessary welds. Some spot welds were located underneath seam sealer and or insulation. We then removed the material with a hand torch to burn the seam sealer, then a steel bristled brush to scratch off the burnt material. We then center drilled all of the marked spot welds with an 1/8† drill bit, followed up by a 5/16† spot weld removal bit to drill out the spot welds along all of the panels to be removed.

Bordean Hill Cottages Essay

WHAT IS THIS LETTER ABOUT? I am writing this letter to apply for the position of a Senior Prefect at Eggar’s School as I believe I would be an ideal representative for the school and a good role model to those younger than me. INTRO – APPLYING APPLICATION I am genuinely very happy at Eggar’s School and it would be a privilege to be part of the Senior Prefect team underpinning the good work that is done by the staff. I see this position as a central part of the school’s foundations, traditions, and effective communication between students, teachers and the local community. Being a senior prefect is one of the top roles a student can have at a school. They work with the teachers to create a better learning environment and provide opportunities for others to succeed. THE ROLE – WHY IS THE ROLE IMPORTANT? HOW WE VALUE PREFECTS? – GENERAL Personally, I believe that having Senior prefects are important as they act as a leading demonstration of the school’s ethos to the ‘outside world’, not only to the parents of current and prospective pupils but the people in the community surrounding our school. Senior prefects act as leaders; they do this with energy and enthusiasm and with a willingness to put others before themselves. Given their status as leaders and role models, Senior Prefects are a visible and active presence around the school. WHY I WANT TO BE A SENIOR PREFECT What school will get out of it – I believe that if I was to become Senior Prefect, I would be able to share my knowledge and advice about the school to suggest improvements from an experienced pupil’s perspective. I would also be able to provide on-going practical support such as parents evenings, sports days, helping out Eggar’s newspapers etc. My knowledge about the school and how it runs from a pupils perspective (experience gained over the last four years) On-going practical supports (eg. Events, parents evenings, sports days, newsletters, teacher etc†¦) Representing the school Being part of the student voice – giving ideas I have gained from being a senior prefect and applying them towards What I want to get out with it   I think as a person I would also widely benefit from becoming Senior Prefect. I would develop my personal skills and qualities including leadership, responsibility and a sense of service which would help me later in life when I have future careers. Being able to demonstrate high expectations of myself and others is very important to me and something I have always tried to maintain over my many years at Eggar’s School. Managing the extra responsibility with professionalism, integrity, sensitivity and good humour is something I wish to gain if I was to become senior prefect. Nevertheless, I believe that becoming a Senior prefect will push me further to continue my commitment to academic success as this has always been very important to me. Furthermore, to receive recognition from Senior staff and being identified to the student body as someone who has, through my actions and efforts, aspired to exemplify the expectations of Eggar’s school would make me very proud. Looking ahead, I know that the experience of being a prefect will bring added value to my further education and career prospects as it will provide positive evidence for collage and job references. Training from the school/staff particularly in relationship to the leadership role To extend CV Provide positive evidence for collage and job references Develop my ability to use my initiative Benefit from the many opportunities to develop personal skills and qualities, including leadership, responsibility, sense of service and trust Being able to demonstrate high expectations of myself and others Make significant contributions to the wider life of the school To have continued commitment to academic success To be able to manage the extra responsibility with professionalism, integrity, sensitivity and good humour. Be self-motivated, proactive and a reliable team member Receive recognition from Senior staff and being identified to the student body as someone who has, through my actions and efforts, aspired to exemplify the expectations of Eggar’s school. STRENGTHS/WEEKNESSES WHY I AM THE RIGHT PERSON FOR THE JOB (GIVE EXAMLES) PERSONALITY AND SKILLS I think I am the right person to take on a role of senior prefect as I am a trustworthy, reliable and responsible person. On numerous occasions I have devoted time to come into school and participate in school fetes, parent’s evenings and showing parents round the school. This is not something that I feel I have to do, but something that I put myself forward for as I enjoy being part of the Eggar’s community. Furthermore, I have proved to be a good ambassador and role model for the school as in year 8 I put myself forward for the role of helping out at the OAP Party which takes place once a year. During this experience I am also very willing to take on extra responsibility. An example of this is when I volunteered to participate in Eggar’s E-learning group. This is where I had the opportunity to help primary school children develop their ICT skills. In the process, my team were successful in winning the competition for the task that was set. I have had a number of opportunities to develop my communication skills. An example of this when I was asked to participate in the BBC School Report in year 8 with around 20 other students. I found this very useful to help develop my team building skills and I will be able to use this skill if I got the role of senior prefect to help motivate and encourage the prefect team. In terms of academic success, I have always given my full commitment and been very self-disciplined. Which has given me very credible results. I was included in the Eggar’s 21 Club which gave me a real sense of pride. I felt that all my hard work had paid off and I would like to, as a Senior Prefect, be able  to encourage other students to work towards this accolade. I have always realised that maintaining a consistently high attendance record (98.3%) will result in a higher level of academic achievement. My participation in many sports days has given me invaluable teamwork and leadership skills, as I have represented my house in a variety of events. This is valuable experience for the position of Senior prefect, as I feel I will be able to carry out a wide variety of tasks required in this demanding position. UNIFORM Not only is it essential that I represent the school by acting very responsibly, both in my manner and academically, it is equally important that I take a pride in my appearance and dress appropriately. WHAT IS MY VISON/ WHAT I CAN BRING TO THE JOB I feel that I can bring a lot to the role of senior prefect as I am very self-disciplined and this quality would help manage my prefect duties with my study commitments and outside school activities. SUMMARY Thank you for considering my application and taking the time out to read it. Yours sincerely, Eleanor Howard