Toni Morrison s Beloved, Traumatic Memories From The Past...

Within America’s history there are sixty million and more African Americans with untold stories lost forever. To those voiceless, the cruelties of slavery brought suffering and loss. Cruelty involves causing pain to another, but at its core it has a much more deeper meaning; it is when an advantage over another being is unnecessarily used to inflict lasting damage and humiliation out of pleasure and self-fulfillment from the perpetrator. As seen in author Toni Morrison’s novel, Beloved, traumatic memories from the past linger among the characters as they try to deal with slavery’s scars and move forward in life. Cruelty appears in the novel through the people who profited from dehumanizing slaves and the victims who lived under oppression, which shows how a white supremacist society can have harmful long-term effects on a person’s psyche in relation to behavior and self-image. A main issue that occurred among former slaves was the difficult rebuilding of identity since they were made to feel like nothing more than cattle under the slavery system. African Americans laid in the mercy of their owners who methodically broke down the spirits of the enslaved until they lost all hope of obtaining individuality. Former slave and Sweet Home inhabitant, Paul D, expressed anguish over feeling dehumanized in the lines, â€Å"Schoolteacher changed me. I was something else and that something was less than a chicken sitting in the sun on a tub† (72). To feel worth less than a chickenShow MoreRelatedBeloved Essay3346 Words   |  14 PagesBeloved Essay In today’s modernized world, it is crucial to be able to comprehend and recognize conflicts dealing with racial tensions due to the increased growth of diversity in nations all over the world. Countries like North America are inhabited by people of different backgrounds, cultures, and colors. Since there is intermingling among everyone, the differences between the diverse ethnic backgrounds could stir up trouble which can lead to serious skirmishes like Watts Rebellion in 1965. To

Participatory sensing services for smart phones Free Essays

1. Motivation In modern society, environmental pollution is usually a headache for citizens, especially those who live in the urban areas. Many researches have shown that there is a direct link between environmental pollution and health effects. We will write a custom essay sample on Participatory sensing services for smart phones or any similar topic only for you Order Now In the last two decades, the overall environment quality has improved. However, there is still a concern about environmental pollution in the urban areas. Citizens, especially the elderly and children, are vulnerable to the effects of environmental pollution. Nowadays, the latest technologies in the wireless field provide an innovative approach for the citizens to access the information about environmental pollution. With over 3 billion subscriber lines active today, nearly half the world’s population uses mobile phones [1]. Given the right structure, the ubiquitous mobile devices could act as sensor nodes, capable of capturing, classifying, and transmitting environmental data, such as image, acoustic, and temperature. In the foreseeable future, other sensors may be embedded in or connect wirelessly to the mobile phones to gather information about air pollutants, like CO2, NO2 and SO2. Participatory sending can employ a variety of devices to collect data; however, some special characteristics of mobile phones enable them to be an unprecedented tool for engaging participants in sensing their local environment. The sheer ubiquity across the geographic and demographic spectrum and the broad proliferation of cellular infrastructure and mobile phone usage make it possible to collect data over large areas for little incremental cost. Participatory sensing will utilize current wireless network, which consists numerous mobile phones, to form a vast interactive participatory sensor network that enables professional users and lay public to gather, analyze and share environment information [2]. Citizens, especially the elderly, children, urban commuters, urban office workers and students, will benefit from such a revolutionary technology. 2. Background In virtue of the rosy prospect and importance of participatory sensing, there are more and more research institutes engaging in this field. The concept of PES has been proposed in recent years (Karatzas, 2005; Burke et al., 2006; Goldman et al., 2009), and related projects have been in development around the world, especially in the USA and Europe [3]. PEIR, one of the most successful participatory sensing projects, is research collaboration between CENS, UCLA and Nokia. It makes use of Internet to allow citizens to use their mobile phones to interact with PEIR, and explore and share the impact between environment and the citizens. PEIR senses pollution by using existing infrastructure without user intervention and emphasizes how individual transportation choices simultaneously influence both environmental impact and exposure, which makes it different from other existing carbon footprint calculators [4]. Eye on Earth project of the European Environment Agency is a two-way communication platform on the environment. It has introduced the participation of millions of ordinary people to create the first environmental portal that includes citizens’ observations on air and bathing water quality at present. Eye on Earth aims to gradually include information on many other environmental topics and grow to a global observatory for environmental change [5]. MESSAGE is to provide data collecting through three sensor platforms for the planning, management and control of the environmental impacts of transport activity at urban, regional and national level. Mobile phones are investigated to support a sensing system, in which people play an important role [6]. In addition to the projects introduced above, other participatory sensing projects have also appeared, such as Living Environments, Citysense, Common Sense, Envitori and MIMAQ [3]. A lot of evidences have shown that new intuitive ways of interactions and user friendly context aware service can be introduced by various sensors in mobile phones. Therefore, mostly specialized sensors were applied in participatory sensing. Some projects also suggest that standard sensors already embedded in the mobile phones can be used for this. Overall, there are a variety of participatory sensing projects, and they can be divided into three categories according to the participation patterns [1]: Collective Design and Investigation. A group of individuals work together to decide where, what and why to sense. Then a data collection system is collectively designed, and an investigation is conducted. The group interprets the data and acts on the results. An evident feature of this participatory pattern is that the community of participants owns the entire process. Instead of serving merely research subjects, individuals play an active role in the investigative process. Public contribution. Individuals or organizations define inquiries and then other individuals collect data in respond to such inquiries. In this case, participants actively engage in the data collection and make contributions to an effort they find meaningful. For organizers, they can gather as many data as possible at a scale unachievable by professionals acting alone. Personal Use and Reflection. Individuals log information about themselves, like images, sounds and so on. Such recorded information may reveal hidden habits and patterns in one’s life after analyzed and visualized. Participants use the results for personal discovery to reflect on, evaluate, and perhaps change patterns that were previously overlooked. 3. Methods Data collection and interpretation are the heart of participatory sensing which places the emphasis on the involvement of citizens and community groups. In spite of participation patterns, the basic process for every participatory sensing project is similar, and it can be broken down into the following eight steps: coordination, capture, transfer, storage, access, analysis, feedback and visualization [1]. Coordination explains the sensing effort to the participants and provides necessary guidance to them. Capture is the collection of data on a mobile phone, which is the core step of participatory sensing. Data can be captured by the existing sensors already embedded in the mobile phones or by those specialized sensors connecting wirelessly to the mobile phones. In the course of data collection, the credibility of data must be guaranteed. More significantly, data about geographical position and time must be captured every time. Transfer is processed automatically by mobile phones via wireless network. Mobile phone software takes the responsibility of uploading data and makes it transparent to the participants. Furthermore, mobile phone software should be tolerant of inevitable network interruptions. Storage takes place on servers which are distributed remotely in the Internet. Access is under the control of project organizers and participants according to the privacy policy. Due to the possible disclosure of private information about the participants, it is of vital importance for the participants to determine what information to share and with whom. Analysis includes various data-processing methods, the calculation of group statistics and the integration of contributed data into statistical and spatial models that can be used to determine patterns in space and time. Feedback may be required in the event of a project triggering manual or automatic events. Visualization is closely related to the analysis. It is the step to present the contributed data after analysis. In some sense, well-designed visualization increases the applicability of a participatory sensing project. The project of Participatory sensing services for smart phones can be divided into two collaborative subprojects based on the Android platform, one focusing on data gathering and the other one dealing with the data processing and visualization. We take the responsibility for presenting data in some friendly and easy-understandable way. Thus the data analysis and visualization are the center of our work. For the subproject of data processing and visualization, we have to deal with data and services. In the assumption that the contributed data are already available and their credibility has been verified, we get data via a server-based application which acts as a data storage. This server-based application will provide web service interfaces for data access. Thus WSDL language for web services will be utilized to develop an Android-based application with the aid of development environments like Eclipse. There are a wide variety of available solutions to make use of web services via Android, and the solution to use ksoap2 will be suitable for our project. The data accessed via web services can be classified into two kinds: subjective data and objective data. Subjective data: a categorization of the quality of the environment. They are feedback commented and reported by the citizens on the air quality. We intend to make use of the EEA categorization for air pollution, which is applicable on http://www.eyeonearth.eu/. Objective data: in the form of numeric values. They are automatically captured by the sensors or reported manually by the users. Images, sound, location and time are objective data. All data processed in the frame of participatory sensing project will include the following three categories of information: Georeference. Geographical position and time is extremely important for participatory sensing, and forms the cornerstone of the follow-up work. User categories. At the initial stage, our project will serve the urban commuters, office workers, students and the elderly. Other categories of users are possibly added if necessary at the later stage. We allocate every user group a unique ID, which will be used to identify the category which the users belong to. Furthermore, category ID will be used to send a request to the server which involves user category. Thematic profiling. Our project is to process information about environment and we aim to deal with air pollution, odors, noise, traffic congestion and waste. In order to present the result of the contributed data to the participants in a user-friendly and easy-understandable way, GMap API may be utilized to map the georeference and thematic profiling, which will provide an interactive feature between our project and participants. Due to the distinct flexibility, Modest Maps API is an alternative to achieve the same goal. 4. Metrics for evaluation To encourage the handset owners to participate in our project, privacy protection policy has to be taken into account to prevent privacy disclosure. One of the basic rules is that participants cannot access other people’s private information, and such an attempt should be denied. Furthermore, the data visualization should be easily and readily comprehended or understood not only by the professional users but also by the general public. In some sense, the degree of understandability of data presentation determines the scope of applicability of participatory sensing. Another metric related to the visualization is that the users are able to customize the configuration to present what they want. With regard to air quality, if the concentration of air pollutants detected does not fall into the scope which is safe and suitable for humankind, the participants should receive a warning, so that they can take actions to avoid being harmed. Due to regional differences, different air pollution standards are applied in different areas. 5. Outputs The output of our project is an application running on the Android platform. Interested people can download it from the Internet and install it in their Android phones to access the information about environment surrounding them. 6. Workplan The rough time schedule of our project is listed below, including the milestones and corresponding estimated completion dates. In table 1, some stages may overlap with others. In the course of project development, the time schedule may be changed according to specific situation. Milestone Anticipated completion date Analyze the project and do literary reviewFebruary 28, 2011 Define the project scopeFebruary 28, 2011 Write the research proposalMarch 23, 2011 Study mobile phone programming techniquesMay 27, 2011 Make a plan for the projectMay 28, 2011 Implement the projectJuly 28, 2011 Test the projectAugust 3, 2011 Take field trialsAugust 5, 2011 Deliver the projectAugust 8, 2011 Complete the dissertationAugust 19, 2011 7. References [1] J. Goldman, K. Shilton, J. Burke, D. Estrin, M. Hansen, N. Ramanathan, S. Reddy, V. Samanta, M. Srivastava, R. West, â€Å"Participatory Sensing: A citizen-powered approach to illuminating the patterns that shape our world† [2] J. Burke, D. Estrin, M. Hansen, A. Parker, N. Ramanathan, S. Reddy, M. B. Srivastava, â€Å"Participatory Sensing† [3] https://projects.inf.ed.ac.uk/msc/project?number=P165 [4] http://urban.cens.ucla.edu/projects/peir [5] http://www.eyeonearth.eu/About.aspx?culture=en-GB [6] http://bioinf.ncl.ac.uk/message/?q=node/5 How to cite Participatory sensing services for smart phones, Essay examples Participatory sensing services for smart phones Free Essays 1. Motivation In modern society, environmental pollution is usually a headache for citizens, especially those who live in the urban areas. Many researches have shown that there is a direct link between environmental pollution and health effects. We will write a custom essay sample on Participatory sensing services for smart phones or any similar topic only for you Order Now In the last two decades, the overall environment quality has improved. However, there is still a concern about environmental pollution in the urban areas. Citizens, especially the elderly and children, are vulnerable to the effects of environmental pollution. Nowadays, the latest technologies in the wireless field provide an innovative approach for the citizens to access the information about environmental pollution. With over 3 billion subscriber lines active today, nearly half the world’s population uses mobile phones [1]. Given the right structure, the ubiquitous mobile devices could act as sensor nodes, capable of capturing, classifying, and transmitting environmental data, such as image, acoustic, and temperature. In the foreseeable future, other sensors may be embedded in or connect wirelessly to the mobile phones to gather information about air pollutants, like CO2, NO2 and SO2. Participatory sending can employ a variety of devices to collect data; however, some special characteristics of mobile phones enable them to be an unprecedented tool for engaging participants in sensing their local environment. The sheer ubiquity across the geographic and demographic spectrum and the broad proliferation of cellular infrastructure and mobile phone usage make it possible to collect data over large areas for little incremental cost. Participatory sensing will utilize current wireless network, which consists numerous mobile phones, to form a vast interactive participatory sensor network that enables professional users and lay public to gather, analyze and share environment information [2]. Citizens, especially the elderly, children, urban commuters, urban office workers and students, will benefit from such a revolutionary technology. 2. Background In virtue of the rosy prospect and importance of participatory sensing, there are more and more research institutes engaging in this field. The concept of PES has been proposed in recent years (Karatzas, 2005; Burke et al., 2006; Goldman et al., 2009), and related projects have been in development around the world, especially in the USA and Europe [3]. PEIR, one of the most successful participatory sensing projects, is research collaboration between CENS, UCLA and Nokia. It makes use of Internet to allow citizens to use their mobile phones to interact with PEIR, and explore and share the impact between environment and the citizens. PEIR senses pollution by using existing infrastructure without user intervention and emphasizes how individual transportation choices simultaneously influence both environmental impact and exposure, which makes it different from other existing carbon footprint calculators [4]. Eye on Earth project of the European Environment Agency is a two-way communication platform on the environment. It has introduced the participation of millions of ordinary people to create the first environmental portal that includes citizens’ observations on air and bathing water quality at present. Eye on Earth aims to gradually include information on many other environmental topics and grow to a global observatory for environmental change [5]. MESSAGE is to provide data collecting through three sensor platforms for the planning, management and control of the environmental impacts of transport activity at urban, regional and national level. Mobile phones are investigated to support a sensing system, in which people play an important role [6]. In addition to the projects introduced above, other participatory sensing projects have also appeared, such as Living Environments, Citysense, Common Sense, Envitori and MIMAQ [3]. A lot of evidences have shown that new intuitive ways of interactions and user friendly context aware service can be introduced by various sensors in mobile phones. Therefore, mostly specialized sensors were applied in participatory sensing. Some projects also suggest that standard sensors already embedded in the mobile phones can be used for this. Overall, there are a variety of participatory sensing projects, and they can be divided into three categories according to the participation patterns [1]: Collective Design and Investigation. A group of individuals work together to decide where, what and why to sense. Then a data collection system is collectively designed, and an investigation is conducted. The group interprets the data and acts on the results. An evident feature of this participatory pattern is that the community of participants owns the entire process. Instead of serving merely research subjects, individuals play an active role in the investigative process. Public contribution. Individuals or organizations define inquiries and then other individuals collect data in respond to such inquiries. In this case, participants actively engage in the data collection and make contributions to an effort they find meaningful. For organizers, they can gather as many data as possible at a scale unachievable by professionals acting alone. Personal Use and Reflection. Individuals log information about themselves, like images, sounds and so on. Such recorded information may reveal hidden habits and patterns in one’s life after analyzed and visualized. Participants use the results for personal discovery to reflect on, evaluate, and perhaps change patterns that were previously overlooked. 3. Methods Data collection and interpretation are the heart of participatory sensing which places the emphasis on the involvement of citizens and community groups. In spite of participation patterns, the basic process for every participatory sensing project is similar, and it can be broken down into the following eight steps: coordination, capture, transfer, storage, access, analysis, feedback and visualization [1]. Coordination explains the sensing effort to the participants and provides necessary guidance to them. Capture is the collection of data on a mobile phone, which is the core step of participatory sensing. Data can be captured by the existing sensors already embedded in the mobile phones or by those specialized sensors connecting wirelessly to the mobile phones. In the course of data collection, the credibility of data must be guaranteed. More significantly, data about geographical position and time must be captured every time. Transfer is processed automatically by mobile phones via wireless network. Mobile phone software takes the responsibility of uploading data and makes it transparent to the participants. Furthermore, mobile phone software should be tolerant of inevitable network interruptions. Storage takes place on servers which are distributed remotely in the Internet. Access is under the control of project organizers and participants according to the privacy policy. Due to the possible disclosure of private information about the participants, it is of vital importance for the participants to determine what information to share and with whom. Analysis includes various data-processing methods, the calculation of group statistics and the integration of contributed data into statistical and spatial models that can be used to determine patterns in space and time. Feedback may be required in the event of a project triggering manual or automatic events. Visualization is closely related to the analysis. It is the step to present the contributed data after analysis. In some sense, well-designed visualization increases the applicability of a participatory sensing project. The project of Participatory sensing services for smart phones can be divided into two collaborative subprojects based on the Android platform, one focusing on data gathering and the other one dealing with the data processing and visualization. We take the responsibility for presenting data in some friendly and easy-understandable way. Thus the data analysis and visualization are the center of our work. For the subproject of data processing and visualization, we have to deal with data and services. In the assumption that the contributed data are already available and their credibility has been verified, we get data via a server-based application which acts as a data storage. This server-based application will provide web service interfaces for data access. Thus WSDL language for web services will be utilized to develop an Android-based application with the aid of development environments like Eclipse. There are a wide variety of available solutions to make use of web services via Android, and the solution to use ksoap2 will be suitable for our project. The data accessed via web services can be classified into two kinds: subjective data and objective data. Subjective data: a categorization of the quality of the environment. They are feedback commented and reported by the citizens on the air quality. We intend to make use of the EEA categorization for air pollution, which is applicable on http://www.eyeonearth.eu/. Objective data: in the form of numeric values. They are automatically captured by the sensors or reported manually by the users. Images, sound, location and time are objective data. All data processed in the frame of participatory sensing project will include the following three categories of information: Georeference. Geographical position and time is extremely important for participatory sensing, and forms the cornerstone of the follow-up work. User categories. At the initial stage, our project will serve the urban commuters, office workers, students and the elderly. Other categories of users are possibly added if necessary at the later stage. We allocate every user group a unique ID, which will be used to identify the category which the users belong to. Furthermore, category ID will be used to send a request to the server which involves user category. Thematic profiling. Our project is to process information about environment and we aim to deal with air pollution, odors, noise, traffic congestion and waste. In order to present the result of the contributed data to the participants in a user-friendly and easy-understandable way, GMap API may be utilized to map the georeference and thematic profiling, which will provide an interactive feature between our project and participants. Due to the distinct flexibility, Modest Maps API is an alternative to achieve the same goal. 4.Metrics for evaluation To encourage the handset owners to participate in our project, privacy protection policy has to be taken into account to prevent privacy disclosure. One of the basic rules is that participants cannot access other people’s private information, and such an attempt should be denied. Furthermore, the data visualization should be easily and readily comprehended or understood not only by the professional users but also by the general public. In some sense, the degree of understandability of data presentation determines the scope of applicability of participatory sensing. Another metric related to the visualization is that the users are able to customize the configuration to present what they want. With regard to air quality, if the concentration of air pollutants detected does not fall into the scope which is safe and suitable for humankind, the participants should receive a warning, so that they can take actions to avoid being harmed. Due to regional differences, different air pollution standards are applied in different areas. 5. Outputs The output of our project is an application running on the Android platform. Interested people can download it from the Internet and install it in their Android phones to access the information about environment surrounding them. 6. Workplan The rough time schedule of our project is listed below, including the milestones and corresponding estimated completion dates. In table 1, some stages may overlap with others. In the course of project development, the time schedule may be changed according to specific situation. Milestone Anticipated completion date Analyze the project and do literary reviewFebruary 28, 2011 Define the project scopeFebruary 28, 2011 Write the research proposalMarch 23, 2011 Study mobile phone programming techniquesMay 27, 2011 Make a plan for the projectMay 28, 2011 Implement the projectJuly 28, 2011 Test the projectAugust 3, 2011 Take field trialsAugust 5, 2011 Deliver the projectAugust 8, 2011 Complete the dissertationAugust 19, 2011 References J. Goldman, K. Shilton, J. Burke, D. Estrin, M. Hansen, N. Ramanathan, S. Reddy, V. Samanta, M. Srivastava, R. West, â€Å"Participatory Sensing: A citizen-powered approach to illuminating the patterns that shape our world† J. Burke, D. Estrin, M. Hansen, A. Parker, N. Ramanathan, S. Reddy, M. B. Srivastava, â€Å"Participatory Sensing† https://projects.inf.ed.ac.uk/msc/project?number=P165 http://urban.cens.ucla.edu/projects/peir http://www.eyeonearth.eu/About.aspx?culture=en-GB http://bioinf.ncl.ac.uk/message/?q=node/5 How to cite Participatory sensing services for smart phones, Essay examples

Accounting Calculation of Dividend Valuation Model

Question: Discuss about the calculation of dividend valuation model, it can be concluded that current share price (116.55) of the companys is lower than the calculated share price (196.22) through use the dividend valuation method? Answer: Introduction British American Tobacco plc (BAT) is a British multinational tobacco company that is a leading company that successful worldwide. BAT is operating in more than 180 countries and has taken leading position in around 50 countries. BAT is one of the worlds five largest tobacco companies and it products are enjoyed by millions of consumers in the worldwide. BAT largest and most popular brands are Benson Hedges, Dunhill, Kent, Kool, Lucky Pall Mall, Strike, and Rothmans. The company act responsibly and with integrity. In the year 2012, BAT market capitalization of 65.6 billion that is the sixth-largest of any company those are listed in LSE (London Stock Exchange). It indicates the leading position of the company in the tobacco sector and in the international market. This paper evaluates the shape of the UK yield curve and explains the concept of the UK market risk premium under existing market conditions. In addition, this paper evaluates the price of the BATs share through using the D ividend Valuation Model and recommends the BATs share should be held, bought or sold at present time. Shape of the UK Yield Curve The Bank of England division of the Macro Financial Analysis estimates yield curves for the UK. The below chart indicates the government liability nominal yield curves are derived from UK gilt prices and General Collateral (GC) repo rates. The real yield curves are derived from UK index-linked bond prices. The instruments used in the construction of the commercial bank liability curve are first converted into synthetic bonds, and the same method is then used to produce the commercial bank liability curve as is used for the nominal UK government curve. The nominal OIS (overnight index swap rates) yield curves are derived from the fixed interest rate component of spot OIS contracts (Bank of England, 2015). In addition, the spreadsheets on the Bank of Englands website provide spot rates and instantaneous forward rates for each type of curve. In the below graph, for horizons out to five years, points on the curves are available at monthly intervals. Moreover, the below graph also show available points on the government and bank liability curves out to a horizon of 5 years at half-yearly intervals. Moreover, the yields on UK government based on bonds (gilts) and include nominal and real yield curves and the inflation term structure for the UK (Bank of England, 2015). The estimates of the UK government curve from the period of 2007 to December 2014 that is derived from the estimates of the nominal government liability curves. (Source: Bank of England, 2015) The above graph shown the normal yield curve and indicates that longer maturity bonds have higher yield compared to short-term bonds because long-time risk is higher than short-time. Many economics conceive that a vertical positive curve (normal yield curve) shows higher interest rates, so investors expect high upcoming inflation and strong upcoming growth of the economy (Baker Pow, 2009). The UK yield curve (Shown in below diagram), the short-term yield (blue line) is higher than long-term yield (pink line) that is the sign of coming recession in the future. Many economics consider that an aggressively inverted yield curve indicates low interest rates, so investors assume low inflation and slow economy in the future. In the UK yield curve (in below diagram), short-term and long-term yield are similar or close (not major differences in blue and pink lines) to each other and shown an economic transition situation. The treasury securities are plots the flat yield curve because it is generally considered risk-free. The shape of the yield curve changes over time as it is lower and increased according to time period. Moreover, less changes in the yield curve indicates less uncertainty and changes in inflation and economic growth (Shenkman, Weiner Taback, 2003). In addition, the yield curve shows the less risky position of the UK market or economy due to the improvement in the chat or upward trend of the curve. At the same time, the UK yield curve shape is upward that indicates the good or positive sigh of the economy and the good inflation term structure for the UK. It represents the positive sign for the future of the UK government and indicates the Bank of England will focus on monetary policy through decrease short-term and long-term interest rate to increase growth of economic and face inflation pressure. So, future inflation impacts on yield curve as it change in a vertical positive curve (normal yield curve in the above chart). It indicates the UK government and the Bank of England focused or contributed to maintain the growth of the country through monetary policy (Bank of England, 2015). Moreover, it indicates the good situation of the investors point of view due to upward trend of yield curve and improving trend of the UK economy. UK Market Risk Premium Market risk premium is a central component of every risk and return model in finance. The standard approach to assume market risk premium remains through the use of historical returns data with the difference in annual returns on stocks and bonds over a long time period containing the expected risk premium. The main limitation related to this approach in the UK is the required long periods of historical data and its complete failure in emerging markets as well as the limited and noisy trend of the historical data (Albrecht, Stice, Stice Swain, 2007). In this situation, the UK market risk premium can be estimated through using a base of equity premium and a country risk premium. The alternative approach to estimate market risk premium is based on the updated estimates for most markets without historical data. In addition, risk and return model estimate risk in terms of variance in actual return around an expected return as the investment is riskless if actual return is equal to the expected market return (Batten Szilagyi, 2011). The below graph indicates the equity risk premium historical data points of the UK that have been calculated after taking inflation into account and are based on annual returns. The below graph indicates the past ten year equity risk premium is trending downwards that means risky situation of the market. (Source: See It Market, 2015) In addition, the recent times, the mostly preferred model of estimate market risk through the use of the local currency sovereign rating from Moody's. The Moody's equivalent of the SP rating that estimate the default spread for that rating (based upon traded countries bonds) over a default free UK government bond rate. United Kingdom Moodys rating is Aa1 that indicates the medium risk situation of the market (Damodaran, 2015). Moody rating and the above graph indicates the risky situation (more than average risk premium) of the UK market. Using Dividend Valuation Model to Evaluate the Price of the BATs Share In this section, using the dividend pricing model to evaluate the price of the BATs share and use it to make a recommendation on whether the share as at 1 June 2015, should be held, bought or sold. The below table indicates the share price of British American Tobacco plc (BAT) in the last 25 years at the year ended 31 December: Year Share price 1990 3.5 1991 3.54 1992 4.52 1993 5.25 1994 4.92 1995 6.64 1996 6.25 1997 7.72 1998 8.85 1999 4.25 2000 7.57 2001 9.39 2002 10.9 2003 17.12 2004 22.16 2005 30.41 2006 42.05 2007 50.44 2008 40.79 2009 51.93 2010 60.62 2011 78.97 2012 92.76 2013 89.27 2014 109.46 (Source: Yahoo Finance, 2015) The chart of the changes in the BATs share price in the last 25 years shown in the below that shown the continuous upward trend and high growth of the prices of the share in the market. The below graph and the above table indicates the BATs share price declines highly in 2008 due to the global financial condition but it increased in 2009 and also achieved high growth after crisis. The below table and graph indicates the dividends given by the British American Tobacco plc (BAT) in the last 25 years: Year Dividend Paid 1990 1.040 1991 0.514 1992 0.600 1993 0.589 1994 0.798 1995 0.891 1996 0.995 1997 1.072 1998 0.796 1999 1.000 2000 0.917 2001 0.949 2002 1.071 2003 1.232 2004 1.414 2005 1.615 2006 1.799 2007 2.352 2008 2.648 2009 2.776 2010 3.233 2011 3.852 2012 4.222 2013 4.336 2014 4.904 Average 1.825 (Source: Yahoo Finance, 2015) On the basis of the above 25 years trends of the dividend paid by the BATs, it can be stated that the continuous improvement in the financial performance of the company. On the basis of the continuous growth and upward trend of the BATs share prices in the market and dividend given by the company indicates the investors would have earned sufficient return with less risk in the past 25years those invest in the company stock price (Baker Pow, 2009). Dividend Valuation Model: P= d0 (1+g)/k-g There, d0= Past year dividend (average of 25 years) = 1.825 g (risk free rate) = US 10-year Treasury Bond Rate = 2.14% (Yahoo Finance, 2015) K = Constant growth rate in perpetuity expected for the dividends= 3.09% (Yahoo Finance, 2015) Then, P= d0 (1+g)/k-g (Albrecht, Stice, Stice Swain, 2007) =1.825 (1+0.0214) / (0.0309-0.0214) =1.825 (1.0214)/0.0095 =196.22 Actual share price on 17 August was 116.55. Recommendation On the basis of the above calculation of dividend valuation model, it can be concluded that current share price (116.55) of the companys is lower than the calculated share price (196.22) through use the dividend valuation method. On the basis of the dividend valuation method calculation and current share price, it can be recommended that BATs share would not be purchase by the investors and they would sell the share of the company. The low value of current share price comparison of the calculated share price indicates the risks and less return situation from the investor point of the views. The dividend valuation method calculation indicates the investor would not earn high return if they invest in the BATs stock for the long-term time period. In addition, the past 25 years trends of the share price and dividend indicates differently from the dividend valuation methods as the future of the company is secured and it able to face any financial condition in the future. The continuous high growth and upward trends of the last 25 years regarding the share price and dividend paid to shareholders indicates the improvement in the companys financial performance and its ability to face any situation in the market. The past trends of the companys related to share price and dividend paid to investors growth indicates the different from the dividend value model that investment in the BATs share would be financial beneficial of the investors. The continuous growth trend and upwards situation indicates the less risky and high return situation or condition from the investors point of views. In addition, on the basis of the both the past trends and the dividend valuation method, it can be concluded or recommended that the investors would be invested or hold the BATs share due to the positive trends and strong financial position of the company. The high growth trends in the past 25 years of share price and dividend of BATs (upwards flow of both graphs in the above) indicates in the future the company would be also achieve growth, maintain financial performance and able to face any financial situation or uncertainty of the market. It represents the buy and hold decision of the BATs stock would be good financial decision of the investors points of views in regarding earn high return at less risks. So, the finally recommended that the investors should be held as well as bought the BATs stock to earn high return at less risks rather than invest in the other company. In the global market, the strong market share and strong financial position in the more than 50 countries also indicates the investment in the stock of the BADs would be better financial or economical decision of the investors. References Albrecht, W., Stice, J., Stice, E. Swain, M. (2007). Accounting: Concepts and Applications (10th ed.). USA: Cengage Learning. Baker, H.K. Pow, G. (2009). Understanding Financial Management: A Practical Guide. USA: John Wiley Sons. Bank of England. (2015). NOTES ON THE BANK OF ENGLAND UK YIELD CURVES. Retrieved from: https://www.bankofengland.co.uk/statistics/Documents/yieldcurve/yields_background_note.pdf Bank of England. (2015). Yield Curves. Retrieved from: https://www.bankofengland.co.uk/statistics/pages/yieldcurve/default.aspx Batten, J. Szilagyi, P.G. (2011). The Impact of the Global Financial Crisis on Emerging Financial Markets. UK: Emerald Group Publishing. Damodaran, A. (2015). Country Default Spreads and Risk Premiums. Retrieved from: https://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/ctryprem.html See It Market. (2015). Equity Risk Premium Historical Data: 1976 to 2012. Retrieved from: https://www.seeitmarket.com/equity-risk-premium-historical-data-1976-to-2012-13300/ Shenkman, M.M., Weiner, S. Taback, I. (2003). Starting a Limited Liability Company. USA: John Wiley Sons. Yahoo Finance. (2015). 10 Year Treasury Rate:2.14% for Aug 12 2015. Retrieved from: https://ycharts.com/indicators/10_year_treasury_rate Yahoo Finance. (2015). British American Tobacco p.l.c. (BTI). Retrieved from: https://finance.yahoo.com/q?s=BTIql=1 Yahoo Finance. (2015). British American Tobacco p.l.c. (BTI): Historical Price. Retrieved from: https://finance.yahoo.com/q/hp?s=BTIa=03b=14c=1990d=07e=17f=2015g=v