The Character of Cholly in The Bluest Eye Essay -- Bluest Eye Essays

The Character of Cholly in The Bluest Eye Morrison has divided her portrayal of a fictional town of blacks, which suffers from alienation and subjugation, into four seasons. I believe that her underlying message is to illustrate the reality of life's travails: the certain rhythms of blessings and tragedies. Some blacks understand and acccept this philosophy and Morrison's use of the seasons portrays and echoes the bible verse, "To every thing there is a season, and a time to every purpose under the heaven"(Ec. 3.1). Perhaps this is a fatalistic approach or as Darrow says, Man is the product of heredity and environment and that he acts as his machine responds to outside stimuli and nothing else, seem amply proven by the evolution and history of man. Every process of nature and life is a continuous sequence of cause and effect (156). This theory is particularly evident in Morrison's development of Cholly, the man who raped his daughter. She could have portrayed him as a degenerate akin to Soaphead, a slimy character, who leaves us with a feeling of revulsion. Instead, step-by-step, she leads us through Cholly's life and experiences; so in the end, instead of hating him, we feel his pain. Cholly is introduced in the first chapter. He is the father of Pecola. Because of his actions, the whole family has been put out of their home. It was a miserable apartment, as ugly in appearance as the family. Except for Cholly. In his youth he had been big strong long limbed and full of his own fire. Now his behavior was his ugliness. Years of despair, dissipation and... ...ft pregnant with his child, and pushed to madness by these terrible circumstances: she finds her beauty in the bluest eye. I said in mine heart, God shall judge the righteous and the wicked; for there is a time for every purpose and for every work (Ec. 17). Morrison draws a sympathetic picture of Cholly. She blurs the reality and covers him with emotional longing for the love he knew in the past. Cholly has nothing more to lose. His life is a tragedy. Works Cited Darrow, Clarence."Crime and Free Will". Introductory Readings in Philosophy. Ed. Marcus G. Singer and Robert R. Ammerman. New York: Scribner, 1962. 156-57. Morrison, Toni. The Bluest Eye. New York: Plume: 1994. The New Chain Reference Bible. Ed. Frank Charles Thompson. Mt. Morris, N.Y: Chain Reference Bible Publishing. 1929.

Value at Risk (VaR)

Financial markets started to use the â€Å"Value at Risk† extensively since 1990’s. But the measures of Value at Risk (VaR) were active in different names since as early as 1920’s (Holton 2003). It is the measurement of the worst expected loss at a given confidence level under normal market conditions over a specific time interval. It can also be expressed as the lowest confidence level of the potential losses that can occur within a given portfolio during a specified time period. Value at Risk only presents the worst-case scenario (Harper n. d. ).The two major parameters to be chosen for risk measurement are the time period and the confidence level. The time period can vary from a few hours to a few years. For example it can be stated that when a portfolio manager has a daily VaR at $1 million at 1%, it means that there is only 1 chance in 100 to incur a daily loss of more than $1 million under normal market conditions. The commonly used methods to estimate Valu e at Risk are: Variance – Covariance Method, Historical Performance and Monte Carlo Simulation (Benninga & Wiener 1998). Variance – Covariance Method:This model was made popular by J. P. Morgan in early 1990’s. This approach is based on the assumption that the underlying market factors have a multivariate normal distribution. This assumption helps in determining the distribution of mark-to-market portfolio profits and losses. After finding the distribution of possible portfolio profits and losses, the standard mathematical properties of Normal distribution can be used to determine the loss that will be equaled or exceeded x percent of the time which is called Value at Risk (Linsmeier & Pearson 1996).The following example can be taken to discuss the theory. A U. S. company entered a FX forward contract in the past. The difference between current date and date of delivery is 91 days. The contract requires the company to deliver $15 million in 91 days and in exchan ge it will receive  £10 million. The facts taken into consideration are the spot exchange rate expressed in dollars per pound (S), 3 month pound interest rate (rGBP) and 3 month dollar interest rate (rUSD). The current mark to market values in dollars is calculated based on the following formula:USD mark to market value= S x GBP 10million – USD 15 million 1+ rGBP (91/360) 1+ rUSD (91/360) Here the holding period is one day and the probability is 5%. The distribution of possible profit and loss on this portfolio has the mean of zero as the expected change in portfolio value over a short holding period is almost always close to zero. A standard property of the Normal distribution is that if a probability of 5% is used in determination of the Value at Risk then it will be equal to 1. 65 times the standard deviation of changes in the portfolio value.Standard deviation is the measure of the spread or dispersion of the distribution and computing the value of the standard deviatio n of changes in the portfolio value is the main factor in this method (Linsmeier & Pearson 1996). Value at Risk = 1. 65 x standard deviation of change in portfolio value The first step in measurement of VaR through this method is to determine the basic market factors and standardized market positions through â€Å"Risk Mapping†. In this case the basic market factors are spot exchange rate and 3-month dollar and pound interest rates.The associated standardized positions are spot pounds, dollar dominated 3 month zero coupon bond and a 3 month zero-coupon bond exposed only to changes in the pound interest rate. The next step is to estimate the parameters of distribution assuming that the percentage changes in the basic market factors have a multivariate Normal distribution with means of zero and thus capturing the variability of market factors by standard deviation and co-movement by the correlation coefficients.The third step is to compute standard deviations and correlations o f the changes in the values of standardized positions using the covariance matrix of changes in the basic market factors. The final step is to calculate the value of variance and standard deviation of the portfolio using standard mathematical results about the distributions of sums of Normal random variables. Standard deviation is the square root of variance. In our case its value is $ 52500 approximately. Now as the probability was taken as 5%, the formula comes to Value at Risk = 1. 65 x standard deviation of change in portfolio value = 1. 65 x $ 52,500 = $ 86,625The benefit of this model is that it uses compact and maintainable data set often available from market and third parties and calculation is quite speedy using algebraic formulae. The drawback of this method is that it assumes the change of the portfolio value to be linearly dependent on all the changes in the values of assets and also that the asset returns normal distributed (Jorion 2006). Historical Performance: Histor ical Performance method is the simplest and most transparent method that takes into account relatively lesser number of assumptions about the statistical distribution of underlying market factors (Linsmeier & Pearson 1996).The method works by using historical changes in market rates and prices to estimate potential future loss or profit with the portfolio and thereby calculating the Value at Risk. This can be illustrated based on the above example. Here we assume the holding period as 1 day, probability of 5% and computation to be based on 100 preceding business days from the current date. The current day will be the 100th day. The method involves five steps. The first step is to identify the basic market factors and to determine the formula to express mark to market value.In our case the basic market factors are 3 month dollar interest rate, 3 month pound interest rate and spot exchange rate. The formula for mark to market value is derived as USD mark to market value= S x GBP 10mil lion – USD 15 million 1+ rGBP (91/360) 1+ rUSD (91/360) Next the values of the identified basic market factors for previous 100 days are to be obtained. Daily change in these rates will be able to set the base for constructions of hypothetical values of market factors useful in the calculation of hypothetical profit and loss.The daily Value at Risk number is a measure of the portfolio loss caused by such changes over a one day holding period. The next and most important step is to subject the current portfolio to the changes experienced in the previous 100 days to calculate daily hypothetical profits and losses. In this step 100 sets of hypothetical values for market factors are calculated based on daily historical percentage changes in the market factors combined with current market factors. These hypothetical values are then used to compute 100 hypothetical mark to market portfolio values.Subtraction of current day mark to market portfolio value from each of the 100 hypothe tical values gives 100 hypothetical daily profits and losses. Ordering mark to market profits and losses from the largest profit to the largest lost is the next step. Finally the loss, which equals or exceeds 5% of the time is selected. In the present example of 100 days calculation the fifth worst loss will be the value at risk. This method relies completely on the historical data. Thus it may not be able to predict most accurately if the period chosen is not a typical one and is posing any special market condition (Jorion 2006).Monte Carlo Simulation: This method is quite similar to the Historical Performance Method. The major difference is that this method uses statistical distribution to capture the possible changes in the market factors instead of observing historical changes in market factors to calculate hypothetical profit and loss. The method involves five steps to estimate Value at Risk. The same example of single forward contract can be considered in this respect. The fir st step here is to identify the basic market factors and to determine the formula to express mark to market value similar to the Historical Performance Method.The next step is to assume a specific distribution for changes in the basic market factors and to estimate the parameters of that distribution. For the present example the percentage change in the basic market factors having multivariate Normal distribution is assumed and estimates of standard deviation and correlates are used as in this case the parameters like means, standard deviations and correlations can be interpreted naturally and their estimation is easier. However, it can be said that Monte Carlo Simulation allows risk managers to choose the distribution according to their requirements.But this flexibility also runs a risk of a bad choice that may not be suitable for the particular case (Jorion, 2006). Pseudo-random generator is used in the following step to generate more than 1000 or sometimes 10000 hypothetical valu es of changes in market factors. These are then used to calculate hypothetical mark to market portfolio values. Actual mark to market portfolio value on the current date is subtracted from each of the hypothetical values to get the hypothetical daily profits and losses.The following step is to order the mark to market profits and losses from the largest profit to the largest loss and the Value at Risk is selected as the loss which equals or exceeds 5% of time. While comparing the different aspects of these three methods it can be said that Historical Performance is the simplest method for estimating Value at Risk. It is suitable for estimation for any kind of options of the portfolio. It is easy to compute and implement and can be explained without much effort.The drawbacks of the method are that it can be misleading if the data used is not typical and represents a specific condition quite similar to Monte Carlo Simulation and Variance-Covariance methods. It is too much dependent on historical data. It is not possible to analyze alternative assumptions through this method. Monte Carlo Simulation and Variance-Covariance methods on the other hand can easily analyze alternative assumptions. Variance-Covariance method though can not examine distribution of market factors other than normal. Both of these methods are easy to implement but tougher to explain.Variance-Covariance method is easy in computation but can not capture the risks of portfolio with options when the holding period is long. Monte Carlo Simulation on the other hand is not easy to compute but it can surely capture the risks regardless of any options (Linsmeier & Pearson 1996). Thus it can be said that all of the three methods have their own benefits and drawbacks and it is completely at the discretion of the risk manager to choose a method appropriate to the portfolio based on the factors to be considered and the holding time.

Microfinance And Financial Inclusion Microfinance

4. Microfinance and Financial Inclusion: Microfinance programmes are intended to reach poor segments of society as they lack access to formal financial services. It, therefore, holds greater promise to further the agenda of FI as it seeks to reach out to this excluded category of population. India has adopted the Bangladesh’s model in a modified form. The Apex-Bank NABARD started ‘SHG bank linkage programme’ during the last decade of by-gone century, is by far the major programme initiative without parallel in any parts of the world for achieving the FI. The programme has demonstrated across the country its effectiveness in linking banks with excluded category of poor segments of population. In this process role of NGOs in development is quite pronounced in providing the last mile connectivity as enablers and catalyst between the SHGs and Village level co-operatives/banks. This is also supplemented by the MFIs delivering credit. To alleviate poverty and to empower particularly women, the micro-finance ha s emerged as a powerful instrument to serve the objective of FI in India. With availability of micro-finance, self-help groups and credit management groups have also started in India. More importance is being given to SHGs, since the micro lending to the group rather than individual borrowers is more successful and in the process also making it to reach the goal of FI. All the members of the group are equally benefitted and also the repayment by each member is guaranteed byShow MoreRelatedEssay On Microfinance Sector836 Words   |  4 Pagesnumbers highlight the extent of financial exclusion.2 Banks seem to have taken note of these realities and are adopting new technologies and leveraging partners to tap the underserved. This has resulted in increased financial inclusion in rural areas, especially among those who are opening bank accounts for the first time. Still, despite the best efforts of banks, many are yet to be included in the formal financial system through access to forma l credit. Microfinance institutions (MFIs) have takenRead MoreIslamic Microfinance And Islamic Institutions1310 Words   |  6 Pagesto Sharia (Islamic law) compliant financial tools. According to CGAP 2013, there are around 255 Islamic microfinance providers in the world (Figure 1 and 2). Studies conducted in Bangladesh, Sudan and Indonesia show that Islamic microfinance is growing at much faster rate than conventional microfinance. TechNavio forecasts the market to grow at a CAGR of 19.7 percent over the period 2013-2018. There is a huge opportunity for the growth of Islamic Microfinance in Pakistan as well. This sector isRead MoreRole of Microfinance:- The micro credit of microfinance program was first initiated in the year600 Words   |  3 Pages Role of Microfinance:- The micro credit of microfinance program was first initiated in the year 1976 in Bangladesh with promise of providing credit to the poor without collateral , alleviating poverty and unleashing human creativity and endeavor of the poor people. Microfinance impact studies have demonstrated that : †¢ Microfinance helps poor households meet basic needs and protects them against risks. †¢ The use of financial services by low-income households leads to improvements in household economicRead MoreThe Structure Of The Banking Industry1608 Words   |  7 Pagesthe State Bank of Vietnam (SBV) it has now expanded to several players and has recently enabled MFIs to be part of the formal financial system. However, despite these achievements, there are still challenges that linger and financial inclusion remains an issue. This part explores the current structure of the banking industry and touches on the status of financial inclusion in Vietnam. 4.3.1. Banking Industry Vietnam’s banking sector is fairly recent being founded a little over 2 decades ago. PriorRead MoreFactors Affecting Organizational Transparency Of Microfinance Institutions1660 Words   |  7 Pagesorganizational transparency of Microfinance institutions Empirical evidence from microfinance institutions in sub-Saharan Africa. 1. INTRODUCTION Microfinance institutions (MFIs) are established to serve the poor through providing financial services such as loans, savings, remittance services, insurance, trainings and technical assistances etc(Callaghan et al. 2007; Mersland, 2009). Unlike other firms, microfinance institutions are expected to meet two objectives, namely financial and social which are calledRead MoreMoney Flow Indexes864 Words   |  3 PagesResearch Design: Descriptive research is undertaken for study. Data collection was done from the Credit rating reports Microfinance sector reports. Sources of Data: Secondary data for the study Sources: †¢ M-CRIL (Micro Credit Rating International Ltd.) †¢ CRISIL Ratings †¢ Microfinance India, State of the sector reports Research Tool: MS-Excel Statistical tools CHAPTER 4 DATA ANALYSIS Analysis of the funds used by the MFIs for different purposes Figure 1: Use of funds byRead MoreThe Communist Party Of Vietnam Essay983 Words   |  4 Pagesaccountable (DFAT 2016). Recent political developments in Vietnam has seen the end of 12th National Congress elections held every 5 years and resulted in the continuation of Nguyen Phu Trong as the general secretary (EIU 2016). In terms of the microfinance industry, there are two government bodies that are mainly responsible for the legal, regulatory and supervisory environment of the sector. The State Bank of Vietnam (SBV), founded in October 26, 1961,is a ministry within the government responsibleRead MoreDeveloping A Small Enterprises And Micro Leasing1804 Words   |  8 PagesMicrofinance provides the basic financial services to low income people, who have lack to access to bank related services. This includes credit for instance, micro saving’s, micro insurance and micro leasing. The main focus of European Union is on microcredit because there is only limited experience with micro savings and micro leasing exists, it is due to the strict regulation, for instance with regard to deposit taking. The microcredit is the extension of very small loans to those who are in povertyRead MoreA Market Based Approach For Community Development Essay1400 Words   |  6 Pagessocio-economic, and political context that our country is in. A market-based approach provides a mechanism to define relationships and allocate economic resources to create systemic change within communities. increasing opportunities for social inclusion and economic sustainability Social Sustainability 1. True community development exemplifies the relationship between the local actor and the interconnectedness that needs to exist to accomplish change. Market based approaches to community developmentRead MoreFactors Hindering Financial Inclusion in Uganda: A Case Study of Kamuli District1618 Words   |  7 PagesFACTORS HINDERING FINANCIAL INCLUSION IN UGANDA: A CASE STUDY OF KAMULI DISTRICT. CHAPTER ONE: INTRODUCTION Background to the Study Uganda’s Vision 2040 highlights access to finance as one of the barriers among others that are affecting the competitiveness of the economy. Most individuals and firms access credit from informal sources. One of the reasons for the limited access to credit is the low level of domestic savings which affects the ability by institutions to offer long term finance. As such