Finance Now, New Zealand Analysis

Finance Now, New Zealand Analysis Company Name: Finance Now, New Zealand Companies find it hard to survive in todays world of cut throat competition. All functions, including but not limited to, IT, Marketing, Service, Operations, Human Resource Management etc. are vital in making an organization a commercial success (Scott, 2015). Marketing, being one of the most significant domains, has a crucial role to play. Right from zeroing on a target market to communicating the end product to users, marketing has it all covered under its wing (Slater, 2015). This report highlights the facets of marketing, such as market segmentation, impact the overall performance of a firm named Finance Now. It also gives an overview of the impact of external as well as internal business environment on the functioning of the firm. A detailed analysis highlighting the strengths, weaknesses, opportunities and threats of organization has also been done. Finance Now Ltd, established in 2000, is a company that is 100% owned and managed by a loan-lending, local company of New Zealand. SBS (Southland Banking Society) is the parent company of Finance Now and was established in 1869. The company is known to grant loans to only kiwis and work visa holders. A wide array of loans comprising of retail loans, business loans, personal loans etc. are offered to kiwis by the largest building society of New Zealand, SBS. Finance Now has a diverse range of products to offer to its customers. Its association with over 1500 retail locations helps boost its credit sales for motor vehicle dealers as well as good finance/consumer loans all through New Zealand. Interest rates charged by the organization vary from person to person depending on the type of application (Now, financenow.co.nz, 2017). The business world, today, is facing with numerous challenges when it comes to running a commercially successful organization,courtesy the ever-changing external and internal environment. The growth and profitability of a firm are largely dependent on factors within and beyond the scope of the organization (Dibrell, 2015). Thus, it is in the best interest of a firm to adopt strategies that promote sustainable development taking into consideration the impact of external as well as internal factors affecting growth (Boons, 2013). External Environment: Some of the factors, beyond the control of the organization, that may have an impact on its growth are: 1. Social Factors: The lifestyle of the local population of the country in which the firm is operational is a major determinant of the success of firm. This is because a grand lifestyle with little disposable income would result in an enhanced customer base taking loans (Medina Munro, 2017). Growth in population is another factor that could enhance the penetration of Finance Now as more people would mean more requirements of houses and other facilities (Rothaermel, 2015). Also, the rapidly increasing working population of New Zealand has the potential to impact the growth of Finance Now. 2. Legal/Regulatory Factors: Affirming to the rules and regulations set by the government of New Zealand is a prerequisite to establishing and running any business in the nation. Fluctuating interest rates have a direct impact on the growth of financial firms with more customers taking loans when the interest rates are low (Chang, 2013). The documentation process is often standard and a simpler process helps getting more customers on board. 3. Economic Factors: The economic situation of New Zealand is expected to impact the growth of Finance Now the most. This is because, a fluctuating economy would directly contribute to a fluctuating customer base with more people opting for personal and business loans when the economy is low. An evidence is that SBS recorded an annual growth of 24% in Financial Year 2014-15 even though the GDP staggered at 3.5% (McBeth, 2015). A rise in inflation rates leads to a rise in interest rates. On the other hand, a drop in inflation may lead to more locals taking to financial help due to lesser rate of interests. This helps in increasing profitability of financial firm. For example the profit made by SBS rose to $14.7 mn in the first two quarters of Financial Year 2016 despite the drop of interest rates as more people opted for loans (Morgan, 2016). 4. Technological Factors: Technology helps make the otherwise complex procedures of documentation easy, hence contributing to the growth of an organization (Rouse, 2016). E-Money feature E Finance cash card for consumer loans Online Portal Mobile Apps-AMP Digital Marketing PPC Digital Advertising, Remarketing or Retargeting Internal Environment The internal environment of an organization comprises to elements that can be controlled by the organization to an extent (Kuratko, 2014). For example infrastructure, employees, values, vision and mission and products and services offered (Hair, 2015). Finance Now competes against others of its kind in the market, including Kiwi Bank, ASB Bank, Moneyshop, Loansmart, Harmoney, Ferratum, Moola, Rapid Loans etc. The more the presence of competitors, the more beneficial a companys products and offerings must be in order to sustain competition. A competitive advantage can be gained by organizing marketing campaigns to increase awareness about products, offering products with enhanced customer value and also guaranteeing superior service (Wagner III, 2014). For example, SBS banks on competitive pricing for gaining an edge over other players in the market. It launched a 3.99% fixed mortgage rate in 2016, which was the lowest observed interest rate in decades. SBS also offered a 0.20% bonus on Term Investments which provided an added benefit to existing investors, thus contributing to customer retention (Bank, 2016). The diverse range of products offered by Finance Now, ranging from personal and home loans to retail loans, helps attract cu stomers from all walks of life. The coming together of Finance Now and dentists of New Zealand to offer an interest free credit deal for 12 months is a great example of how the company intends to diversify its offerings (Times, 2014). A SWOT analysis helps us determine the Strengths, Weaknesses, Opportunities and Threats of a firm. Strengths 1. Advertisements: The light hearted advertisements of SBS bank help in attracting new customers and also retaining those existing For example the warm advertisement depicting a couples excitement to embark on a journey of owning their own home (Commercial, 2016). Finance Now also organizes competitions to help keep its customers engaged (Now, Finance Now) 2. Team, members and partners: The team of Finance Now is its biggest strength. The customers are referred to as members. The company also has over 1500 retail partners to help boost its business (Now, financenow.co.nz). 3. Innovation: Finance Now follows innovative techniques to cope with the ever advancing technology. For example the e-money card and mobile app launched by the company have been immensely popular among masses (Fung, 2014). 4. Customer Service The finance companies or banks are always known to be in the good books of its existing customer base by virtue of its superior customer service. The testimonials put up on the website are evidence of the same (Now, financenow.co.nz, 2016). Weaknesses 1. High interest rates Finance Now offers Business loan interests ranging from 0% to 22.5% (Now, financenow.co.nz). Other competitors offer loans at a borrowing rate of 14-18% on an average (Tarrant, 2017) 2. Nomenclature Since Finance Now is an extremely common name, particularly in the world of finance, its becomes difficult for the company to mark its online presence Opportunities With more and more people taking to loans as an easy way of starting a business or buying a house, the loan market is on a rapid growth (Riasi, 2015). The ease of applying for loans makes it an even better deal. With Finance Now positioned as a Kiwi Bank, it has an edge among the locals of New Zealand. Threats Presence of several competitors with substitute products at cheaper interest rates poses the biggest threat to Finance Now. Government policies may also not always turn out to be in favor of the financial institution. Advertising Policies- Google facebook- Ban on Payday personal Loans with high interest rates. Govt Financial Organization Polices Example of Competitor- recent New Rapid Loans The theory of stakeholder identification is majorly concerned with the principle that who all and what really counts in an organization. The normative theory of stakeholder identification helps us understand why employees and managers are important stakeholders in an organization (Agnà ©, 2015). Some of the other important stakeholders of Finance Now are: 1. Parent Company SBS The board of members of the parent company of SBS comprises of the most prominent stakeholders of Finance Now. The ultimate decision pertaining to any activity carried out by Finance Now is monitored by the parent company. 2. Associated Company -Marble Finance 3. Team Finance Now has its own employees working to attain the vision and mission of the company. The employees belonging to different levels of management and varied domains are significant stakeholders as they impact the profitability of the organization and vice versa. 4. Members The company treats its customers as its members, offering privileges from time to time. The members of Finance Now invest money and show faith in the organization which makes them important stakeholders in the firm. 5. Retailers Finance Now has a tie up with over 1500 retailers(list enclosed appendix no ) in order to boost sales across the country. 6. Associates In addition to having an association with retailers, Finance Now also makes associations with third party Sales and Marketing Teams in order to ensure deeper penetration of its products into the market. 7. Customers/Loan Applicants The loan applicants are also put their faith on company before applying for a loan. 8. Other Investors Target market identification is essential for an organization. This is because it becomes difficult, almost impossible, to cater to the needs of the masses without having a target population in mind. The same product may not suit everyone. Hence, market segmentation is done in order to ensure greater profitability. The products are designed to fit the needs of the target market, thus ensuring a deeper penetration and bigger market share. Market segmentation at Finance Now was done based on the industry it was to operate in. Money lending financial institutions often target a market that they can rely on to repay the loan within a stipulated time. The needs of the target market were then reviewed to create a portfolio of product that could fit the needs of the target population. The process of target market identification proved to be robust with the company making profits soon after its inception. Finance Now aims at catering to the needs of the working population (Li, 2016). This is because the working population has the ability to repay the loans along with the interests associated with it in the future (Bilton, 2016). Finance Now offers a wide range of products ranging from car loans to vacation loans, thus ensuring that all sub groups of the target market are catered to. Secured loans with lesser interest rates are available for those who wish to provide a backup or security, such as a car or property, against the loan that they take. Unsecured loans at the other hand, have the benefit of not having to keep anything as security. The interest rates, however, in case of unsecured loans are higher than those for secured loans. The market segmentation strategy has been working in favor of Finance now with the firm expanding its customer base and making enha nced profits. Finance Now has been a profitable financial institution because of effective market segmentation and positioning. The firm has also efficiently used marketing campaigns to its favor. The wide array of product portfolio offered by the company is instrumental in helping it cater to its target market. The use of technology further enhances its growth prospects. The organization aims at outweighing the presence of competitors in the financial arena by virtue of providing a superior experience to its customers. Appendices Types of loans and products List of Retailers and partners List of competitors Organic Rank Report Glimpse of Google Adwords TV and Radio Advertisements links

Risk and Return Analyis and Portfolio Management of Indian Automobile Companies

PSG INSTITUTE OF MANAGEMENT FINANCIAL SYSTEMS A PROJECT REPORT On RISK AND RETURN ANALYSIS & PORTFOLIO MANAGEMENT Of INDIAN AUTOMOBILE COMPANIES Submitted by, G. Abirami(9UTB02) M. Kamalam(9UTB13) N. Nirupa(9UTB18) P. Srilakshmi(9UTB32) INDEX CONTENTS PAGE NO. Acknowledgement Statement of Problem Introduction: Industry overview Company profiles Objectives Scope & Limitations Literature Review Research Methodology Analysis & Interpretation Findings Suggestions Conclusion Bibliography (i) (ii) 1 1 3 13 13 14 18 20 33 36 37 38 ACKNOWLEDGEMENT First of all we thank the Almighty for having bestowed upon us the sufficient potential with which we are able to complete whatever work we undertake successfully. We feel a heart full of gratitude to our Director Mr. R. Nandagopal for encouraging us regarding all our curricular activities which take place at PSGIM. We also extend our thanks to our co-ordinator Mrs. V. Srividhya for being a constant support throughout and keeping us guided along the right path always. We also wish to thank our teacher for Financial and Management Accounting Mr. P. Varadharajan for having given us this opportunity in taking up this project and for his constant support and guidance throughout the course of the project. We also like to thank our parents who have carved a bright future for us by placing us in such a spectacular and prestigious institution where we could see ourselves as what and as whom we dream to become. May be the last but not the least people to thank are our friends. Thanks is a word not to be shared among friendship but it should be felt for the presence of their soulful support throughout our life. (i) STATEMENT OF PROBLEM Automotive Industry has significantly increased its contribution to overall industrial growth in the country. By 2030 India will be the third largest car market in the world after China and Japan. This coupled by the purchasing power of the ultra rich makes India a top destination for manufacturers of luxury cars Investment by foreign companies in automobiles implies a bright future for the auto industry India. This will lead to the creation of jobs, and a wider range for consumers to choose from. It will also give Indian companies a chance to compete globally for clients. This will greatly benefit the auto component and ancillary industry that will get access to the latest technology and manufacturing practices. According to Commerce Minister Kamal Nath, India is an attractive destination for global auto giants like BMW, General Motors, Ford and Hyundai who were setting base in India, despite the absence of specific trade agreements. Current Scenario On the cost front of Indian automobile industry, OEMs are eyeing India in a big way, investing to source products and components at significant discounts to home market. Overview By 2010, India is expected to witness over Rs 30,000 crore of investment. Maruti Udyog has set up the second car with an investment of Rs 6,500 crore. Hyundai will bring in more than Rs 3,800 crore to India. Tata Motors will be investing Rs 2,000 crore in its small car project. General Motors will be investing Rs 100 crore and Ford about Rs 350 crore. Ashok Leyland and Tata Motors have each announced over Rs 1,000 crore of investment. (ii) ________________________________________ ________________________________________ INTRODUCTION In India there are 100 people per vehicle, while this figure is 82 in China. It is expected that Indian automobile industry will achieve mass motorization status by 2014. Industry Overview: Since the first car rolled out on the streets of Mumbai (then Bombay) in 1898, the Automobile Industry of India has come a long way. During its early stages the auto industry was overlooked by the then Government and the policies were also not favourable. The liberalization policy and various tax reliefs by the Govt. of India in recent years have made remarkable impacts on Indian Automobile Industry. Indian auto industry, which is currently growing at the pace of around 18 % per annum, has become a hot destination for global auto players like Volvo, General Motors and Ford. A well developed transportation system plays a key role in the development of an economy, and India is no exception to it. With the growth of transportation system the Automotive Industry of India is also growing at rapid speed, occupying an important place on the ‘canvas' of Indian economy. Today Indian automotive industry is fully capable of producing various kinds of vehicles and can be divided into 03 broad categories : Cars, two-wheelers and heavy vehicles. Snippets: The first automobile in India rolled in 1897 in Bombay. India is being recognized as potential emerging auto market. Foreign players are adding to their investments in Indian auto industry. Within two-wheelers, motorcycles contribute 80% of the segment size. Unlike the USA, the Indian passenger vehicle market is dominated by cars (79%). Tata Motors dominates over 60% of the Indian commercial vehicle market. 2/3rd of auto component production is consumed directly by OEMs. India is the largest three-wheeler market in the world. India is the largest two-wheeler manufacturer in the world. India is the second largest tractor manufacturer in the world. India is the fifth largest commercial vehicle manufacturer in the world. The number one global motorcycle manufacturer is in India. India is the fourth largest car market in Asia – recently crossed the 1 million mark. 1 Segment Knowhow: Among the two-wheeler segment, motorcycles have major share in the market. Hero Honda contributes 50% motorcycles to the market. In it Honda holds 46% share in scooter and TVS makes 82% of the mopeds in the country. 40% of the three-wheelers are used as goods transport purpose. Piaggio holds 40% of the market share. Among the passenger transport, Bajaj is the leader by making 68% of the three-wheelers. Cars dominate the passenger vehicle market by 79%. Maruti Suzuki has 52% share in passenger cars and is a complete monopoly in multipurpose vehicles. In utility vehicles Mahindra holds 42% share. In commercial vehicle, Tata Motors dominates the market with more than 60% share. Tata Motors is also the world's fifth largest medium & heavy commercial vehicle manufacturer. 2 COMPANY PROFILES ASHOK LEYLAND In 1948, The Company was incorporated on 7th September, at Chennai. The Company Manufacture Comet chassis and Leyland `Tiger' and `Titan' Chassis and Leyland diesel engines. In 1955, the name of the Company was changed from Ashok Motors Ltd. , to AshokLeyland Ltd. in July. Ashok Leyland Motors Ltd. , are the associates Of the company In 2006, Ashok Leyland gets ISO/TS 16949 corporate certification In 2010, Ashok Leyland, the flagship company of Hinduja group, unveiled the Country’s first electric plug-in CNG hybrid bus, HYBUS, at the Delhi Auto show. Company Background Name Auto LCVs/HCVs House Name Hindujas Group Year of Incorporation 1948 Board of Directors: R J Shahaney Chairman / Chair Person D J Balaji Rao Director Ramachandran R Nai Director Shardul S Shroff Director V Sumantran Director Vinod K Dasari Whole Time Director J N Amrolia Executive Director S Balasubramanian Executive Director R R G Menon Executive Director M Nataraj Executive Director Rajive Saharia Executive Director 3 EICHER MOTORS In 1982, The company was incorporated on 14th October, and the Certificate of commencement of business was obtained on 28th March, 1983. It was promoted in the joint sector by Eicher Goodearth Ltd. Mitsubishi Corporation, Japan, Mitsubishi Motors Corporation Japan and Madhya Pradesh Audyogik Vikas Nigam Ltd. In 2005, Eicher Motors entered into definitive agreements with TMTL on May 27, In 2006, Eicher Motors Ltd (EML) on Feb 20, announced Mr. Siddhartha Lal as its new Managing Director designate. Eicher joins hands with Wipro to source hydraulic kits In 2007, Eicher Motors Ltd has informed that the Board of Directors of the Company in its meeting held on October 22, 2007 approved appointment of Mr. Rajesh Arora as Company Secretary as well as Compliance Officer of the Company. Company Background: Industry Name Auto LCVs/HCVs House Name Eicher Group Year of Incorporation 1982 Board of Directors: S Sandilya Chairman / Chair Person Priya Brat Director Prateek Jalan Director Siddhartha Lal Managing Director & CEO 4 ESCORTS In 1947, After partition the registered office of the Company was shifted from Lahore to New Delhi. The name of the Company was changed from Escorts (Agents) Pvt. Ltd. , to Escorts Ltd. upon its conversion into a Public company. In 2005, Escorts win . 5-m tractor order from Ghana Escorts Ltd has acquired its Polish joint venture partner, Farmtrac Tractors Europe Escorts' US subsidiary teams up with SAME Deutz-Fahr Italia In 2006, Escort India is set to manufacture tractors in Bangladesh through a Joint venture with the Nitol-Niloy group. Company Background Name Auto Tractors House Name Nand Year of Incorporation 1944 Board of Directors: Rajan NandaChairman and Managing director M G K MenonDirector P S PritamDirector Nikhil NandaJoint Managing Director 5 HERO HONDA In 1984, The Company was incorporated on 19th January, at New Delhi. The Company Manufacture motor cycles up to 100 cc capacity. The Company Was promoted by Hero Cycles (P) Ltd. (HCPL). In 2005, New product launches widen HHML's product portfolio Two-wheeler major Hero Honda on October 5 announced launch of its First scooter ‘Pleasure' Hero Honda rolls out 150-cc motorcycle Achiever. In 2006, Hero Honda announced the launch of two new variants the new ‘Glamour' and ‘Passion Plus' limited edition. In 2007, Hero Honda Motors Ltd. has appointed Mr. Yutaka Kudo as Director and Whole-time Director of the Company in the category of Executive Director w. e. f. April 1, 2007. Company Background: Industry Name Auto 2 & 3 Wheelers House Name Hero Year of Incorporation 1984 Board of Directors: Toshiaki Nakagawa Joint Managing Director Masahiro Takedagawa Non Executive Director Pawan Munjal Managing Director and CEO Takashi Nagai Non Executive Director Pradeep Dinodia Non. Exe. Independent Director 6 HMT In 1953, The Company was incorporated in Bangalore. The Company was converted into a Public Limited Company on May 13, 1977. The main objects of the Company is Manufacturing of the Machine tools, metal forming presses and press brakes, pressure die, casting machines and automatic plastic injection molding machines, automatic plastic injection molding machines. In 1998, HMT International Ltd, a wholly-owned subsidiary of HMT, has bagged a Rs. 3-crore order for setting up an Entrepreneur Technical Development Centre (ETDC) at Dakar in Senegal. In 2010, HMT Ltd has informed that Shri Harbhajan Singh has been appointed as Part-time Official Director on the Board of the Company with Effect from January 11, 2010 Company Background: Industry Name Auto Tractors House Name Public Sector Year of Incorporation 1953. Board of Directors: Rajiv BansalDirector S G SridharDirector (Operations) S BehuriaDirector Sourabh ChandraDirector K KipgenDirector Prakash SharanExecutive Director Harbhajan SinghPart Time Official Director 7 MARUTI SUZUKI In 2000, The Company was awarded the Highest Exporter Award in New Delhi. ICRA has assigned `LAAA' rating to the Rs. 200-crore Long-term non-convertible debenture program and `A1+' rating to the Rs. 100-crore commercial paper program of the company. In 2002, The government on May 14, 2002 set into motion big-ticket disinvestment in 2002-03 by announcing a two-stage process to exit from Maruti Udyog Ltd, a joint venture with Suzuki Motor Company. In 2007, Maruti Udyog Limited has informed that Mr. Tsuneo Kobayashi, a Non-executive director, has been appointed as Whole-time Director designated as Senior Joint Managing Director. The Board of Directors in their meeting held on 22nd January, 2007 has approved the above. UTI Bank and Maruti have joined hands for giving car finance. Company Background: Industry Name Auto Cars & Jeeps House Name MNC Associate Year of Incorporation 1981 Board of Directors: R C BhargavaChairman / Chair Person Amal GanguliDirector Keiichi AsaiDirector Osamu SuzukiDirector Davinder Singh BrarDirector 8 TATA MOTORS Tata Motors Limited is India's largest automobile company, with consolidated revenues of Rs. 70,938. 85 crores (USD 14 billion) in 2008-09. It is the leader in commercial vehicles in each segment, and among the top three in passenger vehicles with winning products in the compact, midsize car and utility vehicle segments. The company is the world's fourth largest truck manufacturer, and the world's second largest bus manufacturer. The company's 24,000 employees are guided by the vision to be â€Å"best in the manner in which we operate, best in the products we deliver, and best in our value system and ethics. Established in 1945, Tata Motors' presence indeed cuts across the length and breadth of India. Over 4 million Tata vehicles ply on Indian roads, since the first rolled out in 1954. Company Background Industry Name Auto LCVs/HCVs House Name Tata Group Collaborative Year Of Incorporation 1945 Board of Directors: Ratan N TataChairman / Chair Person N A SoonawalaDirector R Gopalakri shnanDirector S M PaliaDirector S BhargavaDirector V K JairathDirector 9 TVS MOTORS TVS has been at the forefront in bringing a revolution in the way personal commutation was happening, way back in the 1980s. Beginning with launching a simple, easy-to-use moped for the middle class in India in the 1980s to launching 7 new bikes in a single day (first time in the history of the automotive industry in the world), TVS has often taken the unbeaten path to innovation. The Group's principal activity is to manufacture and sell motor cycles and components. The Group operates in two segments: Automotive Vehicles and Automotive Components. Automotive Vehicles include motorcycles, mopeds, ungeared scooters and three wheelers. The products of the Group include TVS Apache, TVS Scooty, TVS Fiero, TVS Super XL, TVS Victor, TVS Centra, TVS Star etc. It's plants are located at Hosur, Tamil Nadu , Mysore, Karnataka and Solan, Himachal Pradesh. Company Background Industry Name Auto 2 & 3 Wheelers House Name TVS Group Year of Incorporation 1982 Board of Directors: Venu Srinivasan Chairman and Managing director T Kannan Director K S Bajpai Director Prince Asirvatham Director 10 MAHINDRA AND MAHINDRA: Mahindra embarked on its journey in 1945 by assembling the Willys Jeep in India and is now a US $6. 3 billion Indian multinational. It employs over 1,00,000 people across the globe and enjoys a leadership position in utility vehicles, tractors and information technology, with a significant and growing presence in financial services, tourism, infrastructure development, trade and logistics. The Mahindra Group today is an embodiment of global excellence and enjoys a strong corporate brand image. Mahindra is the only Indian company among the top tractor brands in the world and has made an entry in the two-wheeler segment, which will see the company emerge as a full-range player with a presence in almost every segment of the automobile industry. The Mahindra Group expanded its IT portfolio when Tech Mahindra acquired the leading global business and information technology services company, Satyam Computer Services. The company is now known as Mahindra Satyam. Mahindra's Farm Equipment Sector is the proud recipient of the Japan Quality Medal, the only tractor company worldwide to be bestowed this honour. It also holds the distinction of being the only tractor company worldwide to win the Deming Prize. The US based Reputation Institute recently ranked Mahindra among the top 10 Indian companies in its Global 200: The World's Best Corporate Reputations list. Mahindra is also one of the few Indian companies to receive an A+ GRI checked rating for its first Sustainability Report for the year 2007-08. Company Background: Industry Name Auto -Cars & Jeeps House Name M & M Year of Incorporation 1945 Board of Directors: Keshub Mahindra Chairman / Chair Person Deepak S Parekh Director M M Murugappan Director A S Ganguly Director Anupam Puri Director 11 BAJAJ AUTO Bajaj Auto Ltd. is the largest exporter of two and three wheelers. With Kawasaki Heavy Industries of Japan, Bajaj manufactures state-of-the-art range of two-wheelers. The brand, Pulsar is continually dominating the Indian motorcycle market in the premium segment. Its Discover DTSi is also a successful bike on Indian roads. 2010 – Bajaj Auto launched a 135 cc Pulsar, priced at Rs 51,000, pushing the Pulsar brand into the mass segment. Company Background: Founder Jamnalal Bajaj Year of Establishment 1926 Industry Automotive 2 & 3 Wheelers Business Group The Bajaj Dominant presence in Sri Lanka, Bangladesh, Columbia, Guatemala, Peru, Egypt, Iran and Indonesia. Joint Venture Kawasaki Heavy Industries of Japan Board of Directors: Rahul Bajaj Chairman / Chair Person Rajiv Bajaj Managing Director D S Mehta Director Shekhar Bajaj Director J N Godrej Director Suman Kirloskar Director 12 ________________________________________ ________________________________________ OBJECTIVES Primary Objective: Construction of optimal portfolio using Sharpe Index Model To analyze the risk and return of Indian automobile companies. Secondary Objectives: To understand the Sharpe's Portfolio Selection Model over the Standardized Index Portfolio called Market portfolio in respect of stock market perations in India. It also involves the estimation of Beta for each potential asset; these estimations are obtained based on past data and using statistical methods in order to obtain future Beta. To understand the current scenario of Indian automobile industry. SCOPE & LIMITATIONS Scope: To get overview outline about the selected Indian automobile company, their performance comparison, market share, potential and their volatility. Serves as a source of information for investors in identifying the risk averse and risk seeking shares (more return and less risk)of selected automobile industry. To get insight about the application of Sharpe index model in risk and return analysis of portfolio management. Limitations 1. Only selected industries in Indian automobile sector. 2. The data obtained and collected are only approximate and not more accurate. 3. Market fluctuations in share price of the selected industries. 4. Application of Sharpie index model alone. 13 ________________________________________ ________________________________________ LITERATURE REVIEW â€Å"The Accounting Review†: Elgers, Pieter T. Murray, Dennis ( Apr 1982) published that a measure of investment risk-the systematic risk of the Sharpe-Linter capital asset pricing model (CAPM)-is now widely employed. The relationship between beta estimates and various accounting risk measures (ARMs) have been extensively studied by accounting researchers, but results have led to different inferences about the usefulness of ARMs. The impact of the choice of market index on inferences concerning the usefulness o f ARMs in explaining and predicting beta is investigated. The association of ARMs and beta tests are always joint tests. Beta reflects the expected co variation between the returns of a given security and those of the market portfolio of all risky capital assets. The market portfolio, however, is not observable. Empirical evidence showed: 1. that the stability of beta estimates over time are quite sensitive to the market index employed, 2. that the ability of ARMs to explain differences among betas for a cross-section of firms is highest when the betas are estimated using the CRSP equal-weighted index, and 3. that the ability of ARMs to improve upon market-based forecasts of beta depends upon the choice of market index and the error metric employed. The Journal of Finance†: Kwan, Clarence C. Y (Dec 1984) published that a simple common algorithm that is applicable to 7 models is suggested for optimal portfolio selection disallowing short sales of risky securities. The 7 models considered are: 1. Sharpe's (1963) single index model, 2. Cohen and Pogue's (1967) multi-index models in diagonal and cova riance forms, 3. Two multi-index models with orthogonal indexes, and 4. Two constant correlation models. The proposed algorithm successfully bypasses the requirement of explicitly ranking securities that is essential in previous research on the topic. Because of this feature, the algorithm is especially useful for the 2 multi-index models with orthogonal indexes where there are problems in establishing a ranking criterion. An illustrative example is provided showing the results of all the iterative steps. It is demonstrated in a simulation study performed on the 5 models with multiple groups that the procedure involved in the search for optimality requires only small numbers of simple iterative steps. Thus, the method can enhance the usefulness of these index models and constant correlation models in portfolio analysis. The Journal of Portfolio Management†: Gressis, N. , Vlahos, G. , Phillipatos, G. C. (Spring 1984) published that the recent establishment of stock index futures markets has opened up a variety of new investment opportunities that should improve the performance of both secondary markets and individual investor portfolios. Trading in stock index futures has been proposed as an effective hedge against investment risk. A technique based on the capital asset pricing model (CAPM) framework is here developed to identify the profit opportunities of stock index futures trading. With this technique, the systematic risk of a stock index futures contract can be identified for the investor buying on margin, along with the abnormal returns that can be expected from the contract and its equilibrium price. The technique is demonstrated in application to the Standard & Poor's 500 Index futures. It is shown that the risk of a stock index futures contract declines with the length of the investment horizon. However, the degree of abnormal performance and the deviation of the equilibrium price of the contract from the market price increases with time to maturity. The Journal of Portfolio Management†: French, Dan W. , Henderson, Glenn V (Winter 1985) published that the investment portfolio performance measures based on the capital asset pricing model are examined under ideal conditions that work around the problems that their critics have discovered. These problems include Miss specified independent variables, omitted variables, errors in variables, and unstable p arameters, all of which are basically beta problems. A database is constructed by simulating 60 portfolios or security return series, each containing 3 random variants having their own distribution. Regression analysis results show that winners cannot be distinguished from random performers, and that winners cannot even be labelled as such unless they are remarkably successful. If random noise is the only contaminating factor in performance evaluation, then the 4 currently popular performance measures rank in an internally consistent fashion and rank portfolio performance correctly â€Å"The Journal of Portfolio Management†: Peters (Summer 1985) published that Evidence is presented suggesting that early mispricing of stock index futures was due to market inefficiencies, but that the markets have become more efficient over time. This growing efficiency is the result of more experienced traders and the increasing availability of accurate valuation models. This evidence is derived from a test of market efficiency done using a cost-of-carry valuation model. The test is limited to the Standard & Poor's 500 and the New York Stock Exchange Composite indexes. The theoretical value for each future contract over the period June 1982-December 1983 is computed using data from CE/ICD's ANALYSTICS database. Results indicate that both index futures markets have become more efficient with time. If it is assumed that investors are rational and that expectations of the index value are not considered in valuation, it can further be assumed that dividend stream estimation is the major source of market inefficiency. Portfolio managers can now use index futures for hedging with greater confidence. 15 â€Å"The Journal of multinational financial management†: Javier Estrada and Ana Paula Serra (July 2005) published that the proper identification of the risk variables that explain the cross-section of returns in emerging markets has many and far-reaching implications for both companies and investors. We examine this risk–return relationship by focusing on three families of models, over 25 years of data, and over 1600 companies in 30 countries. We perform a statistical analysis that seeks to identify the variables that should be incorporated into the calculation of required returns on equity, and an economic analysis that seeks to determine the variables that produce the most profitable portfolio strategies. We find rather weak statistical results that prevent us from strongly recommending a given family to estimate required returns on equity. And we find somewhat stronger economic results that show that a variable belonging to our downside risk family, the global downside beta, is the one that has the largest impact on returns when portfolios are rebalanced every 5 years. â€Å"University of Mannheim – Department of Business Administration and Finance† : Alen Nosic (March 6, 2007), published that the determinants of investors' risk taking behavior. We find that investors' risk taking behaviour is affected by their subjective risk attitude and by the risk and return of an investment alternative. Our results also suggest hat consistent with previous findings in the literature objective or historical return and volatility of a stock are not as good predictors of risk taking behavior as subjective risk and return measures. Moreover, we illustrate that overconfidence or more precisely miscalibration has an impact on risk behavior as predicted by theoretical models. However, our results regarding the effect of var ious determinants on risk taking behavior heavily depends on the domain the respective determinant is elicited. We interpret this as an indication for extended domain specificity. In particular with the Markets of Financial Instruments Directive (MiFID) coming into effect we believe practitioners could improve on their investment advising process by incorporating some of the determinants we argue to influence investment behavior. † European Journal of Operational Research†: Xiang Li, Zhongfeng Qin, Samarjit Kar (April 1, 2010) published Numerous empirical studies show that portfolio returns are asymmetric, and investors would prefer a portfolio return with larger degree of asymmetry when the mean value and variance are same. In order to measure the asymmetry of fuzzy portfolio return, a concept of skewness is defined as the third central moment in this paper, and its mathematical properties are studied. As an extension of the fuzzy mean-variance model, a mean-variance-skewness model is presented and the corresponding variations are also considered. In order to solve the proposed models, a genetic algorithm integrating fuzzy simulation is designed. Finally, several numerical examples are given to illustrate the modeling idea and the effectiveness of the proposed algorithm. Banking and Finance†: Cheol S Eun, Jinso Lee (April 2010) published that the risk-return characteristics of our sample of 17 developed stock markets of the world have converged significantly toward each other during our study period 1974-2007, and (ii) that this international convergence in risk-return characteristics is driven mainly by the declining ‘country effect', rather than the rising ‘industry effect', suggesti ng that the convergence is associated with international market integration. Specifically, we first ompute the risk-return distance among international stock markets based on the Euclidean distance and find that the distance thus computed has been decreasing significantly over time, implying a mean-variance convergence. In particular, the average risk-return distance has decreased by about 50% over our sample period. We also document that the risk-return characteristics of our sample of 14 emerging markets have been converging rapidly toward those of developed markets in recent years. This development notwithstanding, emerging markets still remain as a distinct asset class. Lastly, we show that the convergence in risk-return characteristics has exerted a negative impact on the efficiency of international investment during our sample period. â€Å"Journal of investment management†, Lisa R Goldberg, Michael Y Hayes (first quarter 2010) published that a practical and effective extension of portfolio risk management and construction best practices to account for extreme events. The central element of the extension is (expected) shortfall, which is the expected loss given that a value-at-risk limit is breached. Shortfall is the most basic measure of extreme risk, and unlike volatility and value at risk, it probes the tails of portfolio return and profit/loss distributions. Consequently, shortfall is (in principle) a guide to allocating reserve capital. Since it is a convex measure, shortfall can (again, in principle) be used as an optimization constraint either alone or in combination with volatility. In principle becomes in practice only if shortfall can be forecast accurately. A recent body of research uses factor models to generate robust, empirically accurate shortfall forecasts that can be analyzed with standard risk management tools such as betas, risk budgets and factor correlations. An important insight is that a long history of returns to risk factors can inform short-horizon shortfall forecasts in a meaningful way. 17 ________________________________________ ________________________________________ RESEARCH METHODOLOGY Sources of data: We selected the companies based on the market capitalisation and for this we referred money control. om from where we sorted out the top ten automobile companies in India based on the market capitalisation value given as of March 1, 2010. Then the opening and closing stock price of the top ten automobile companies for the previous five financial years (2005-2006, 2006-2007, 2007-2008, 2008-2009, 2009-2010) was downloaded from NSE website(nseindia. com). The overall index return price was also downloaded from the same website for the same period. Top ten automobile industries selected based on market capitalisation are: Company nameMarket Capitalisation(Rs. Crore) Tata Motors43,388. 97 Maruti Suzuki 42,705. 24 Hero Honda38,218. 19 Tech Mahindra31,398. 74 Bajaj Auto 27,698. 93 Ashok Leyland 7,183. 83 HMT 6,307. 10 TVS Motor 1,800. 58 Eicher Motors 1,685. 52 Escorts 1,387. 46 Market capitalization (often market cap) is a measurement of the size of a business enterprise (corporation) equal to the share price times the number of shares outstanding of a public company. As owning stock represents ownership of the company, including all its equity, capitalization could represent the public opinion of a company's net worth and is a determining factor in stock valuation. Tools used: We used certain formulae to study on the risk and return of the companies and the portfolio management based on the Sharpe – Index model. The calculations were done in a spread sheet to make it easier. The formulae of the elements used in the spread sheet are as follows: Sum of Individual Stock returns – Ri and Market return – Rm. 18 Stock return – Y and Market return – X: = ((Today’s price – Yesterday’s price) / Yesterday’s price)*100. Mean of stock return – Y? , Mean of market return – X?. Y? = (sum of Y)/ total number of days X? = (sum of X)/ total number of days Standard deviation of Stock return – ? , Standard deviation of market return – ? x. Correlation = Covariance/(? y * ? x) Risk factor ? = Covariance *(? y / ? x) Return indicator ? = Y? – ? (X? ). Unsystematic risk – ? ei?. Cut off point Ci: n Ci = ? m? * ? ((Ri-Rf)? )/ ? ei? ) i =1 n 1 + ? m? * ? ( / ? ei? ) i=1 where , ? m = market variance. Z value = Zi/ ? _(i=1)^n-Zi where, Zi = ? /? ei? ( Ri-Rf)/? – Ci X value = Zi / Z. Tables and bar graphs are drawn for average values of important parameters like ? , ? x, ? y, X? , Y? , for each company for all five years. Outcomes are represented diagramaticaly) A table for all companies’ cut-off point, Z value, X value is also drawn. Population & Sample size: There was a total of about 16 automobile companies registered in NSE website out of which we selected top 10 companies based on the market capitalisation as mentioned before. Total population in NSE = 16. Sample size = 10. (Specific yrs. 2005-2010) 19 ________________________________________ ________________________________________ ANALYSIS AND INTERPRETATION Ashok Leyland Interpretation: Average Stock return Y? is largest during the year 2009(approximately 0. 6) and lowest during the year 2008 (approx. -0. 4). Risk factor ? is more during the year 2010 and low during the years 2006, â €™07, ’08. Highest deviation is seen in the year 2008 and least is seen in 2005. 20 Eicher Motors Interpretation: The company experiences the highest average stock return during the year 2009 (approx. 0. 5) and the lowest during the year 2010(approx. -0. 25). Risk factor ? is below 1 for all the years except 2010. But the average value for the five years stays below 1. Highest deviation is seen in the year 2008 and least deviation one is seen in 2005. 21 Escorts Interpretation: The company has a highest stock return in 2009 and less stock return in 2008. Average stock return is very low which is near to 0. 053. ?eta value is high in the year 2005 and low in the year 2009 and all the beta values are above 1. Deviation is seen high in 2008 and less in 2010. 22 Hero Honda Interpretation: Beta value is seen to be above 1 during the years 2007 & 2010. Average beta value of the company is seen to be below 1. Stock return is high during the year 2009 and negative during the years 2006 & 2007. Deviation is high in the year 2008. 23 HMT Interpretation: The company has a good stock return during the years 2005 and 2010 and negative during the year 2008. The deviation is very much high for the company here. Average deviation of 4. 5 is seen here. Average beta value is more than 1. 24 Maruti Suzuki Interpretation: Stock return is highest during the year 2009 and less during 2008. Beta value is less than 1 after 2007 and more than 1 before 2007. Deviation is large during 2008. 25 Tata motors Interpretation: Stock return is high in the year 2009 and has gone negative in the previous year. Beta value is less 1 from 2007 and >1 in 2005 & 2006. The deviation is more in 2009 and 2008. 26 TVS Motors Interpretation: Stock return high in 2009and very low in 2008. Beta value is less than 1 in all cases than in 2006. Deviation is supposed to be high in 2009. 27 Tech Mahindra Interpretation: The stock return is very high during the year 2006 and very less(negative) during the year 2008. Deviation is almost high for all the years. Average beta value is < 1. 28 Bajaj Auto Interpretation: The company has shown a good stock return of positive value during the years 2009 & 2010. Beta value is less than 1 for all the years. Deviation is high during the year 2008. 9 Table- Summary of Calculations Market return vs. Individual stock return Figure – 1 30 Comparison of Unsystematic risk and cut off points Figure – 2 Systematic Risk Figure – 3 31 Interpretation from Summary of Calculations: Table Figure – 1: HMT has the highest stock return and is greater the market return(about 170) Second comes the Maruti Suzuki followed by Hero honda. (about 150) TVS Motors has the lowest stock return of all the 10 companies and is less than the market return. (about 70) Figure – 2: Unsystematic risk is high for HMT (approx 19) and second Escorts. (approx 18) Hero Honda has the lowest unsystematic risk. (approx 5) Bajaj Auto has the highest cut off point whereas Ashok Leyland has the lowest cut off point. Figure – 3: Escorts has highest systematic risk (approx. 1. 36) HMT has the second higher risk value(approx. 1. 09) Bajaj Auto has the lowest risk value (approx. 0. 65) 32 ________________________________________ ________________________________________ FINDINGS Ashok Leyland: The ? value gives us a stock’s risk profile. Here we can take the average beta value and interpret and comment on the overall risk for the five years taken by the concern. Average beta value = 1 which means it is neither stable nor unstable. It is a neutral share and is expected to follow the market. From the table when we look at the ? value its average value is . 01233 which means that the minimum riskless return is 1. 23%. The company’s earnings from stock investment has reduced in the year 2010. We get a positive correlation value which implies that a 0. 5% in the market return will affect a company’s stock return by 0. 5% in the same direction. Eicher Motors: The company’s earnings from stock investment has reduced in the year 2010 from 2009. Here ? he company expects less volatility and less risk and therefore less returns. These are called defensive shares and will generally experience smaller than average gains in a rising market, will generally experience smaller than average falls in a declining market. From the table the average ? value 0. i6691. The minimum risk free return is 16. 69%. Mahindra is having high risk free rate so it is safe to hold this stock. Correlation value = 0. 44% 0. 44% of change in market return affects the stock return by 0. 44% in the same direction. Bajaj Auto: The return on stock investments is good during 2009 & 2010 when compared to the year 2008. Since beta value < 1. The company expects a stability, less risk and less returns. These are called defensive shares and will generally experience smaller than average gains in a rising market, will generally experience smaller than average falls in a declining market. Alpha From the table the average ? value 0. 24715. The minimum risk free return is 24. 715%. Bajaj is having the highest risk free retun in all the ten companies so it is very safe to invest. Correlation value = 0. 46% 0. 46% change in Rm = 0. 46% change in Ri in the same direction. 35 Summary of calculation: HMT is having high stock return because they are using stock investments efficiently in the business The low cut-off point is good which implies less payback. Ashok Leyland has minimum payback whereas Bajaj has maximum payback. Escorts involves in high risky projects expecting more returns rather Bajaj is not involving in risky projects. SUGGESTIONS Hero Honda is having low risk and high return. So it is good for the investors to invest in this company. (for investors) HMT is taking high risk and provides decent returns. So next to Herohonda, HMT is a good company to invest. (for investors) Bajaj is having a low return at a medium risk so the company have to indulge in risky projects to get good returns in the future. (for company) HMT and Escorts have high unsystematic risk, so they can go for product diversification to reduce the unsystematic risk. (for company) (Product diversification helps the companies to reduce the unsystematic risk because even if they lose in one of the products they can make up their revenues by some other product) Cut off point is the point at which the required rate of return is worth the expense. If it is high then that company is going to take a long time to repay its initial investment. In our case Ashok Leyland will be able to recover the money invested in the project as soon as possible than others. Ashok Leyland might serve as the best company to invest to get their investment back whatever the return may be. Based on the stock return, risk and the cut off point, Herohonda is a good company to invest because they have an optimum return at an optimum risk level. TVS motors has a high cut off point, less stock return at a high risk. They can reduce their risk level, because it might involve large sum of investment. 36 ________________________________________ ________________________________________ CONCLUSION According to our findings we suggest that Hero Honda is the best Automobile company in India to invest and the investment can range up to 42% as per our analysis. Although India has been much discussed in recent years, and has been the recipient of major foreign investment in its automotive industry, it has in many ways not received the attention of the world’s other major developing country, China – but this is about to change. With the world’s second largest and fastest-growing population, there is no denying India’s potential in both economic and population terms and the effect it will have on the auto industry in the years to come. The country is already off to a good start, with a well-developed components industry and a production level of one million four-wheeled vehicles a year, plus a further five million two- and three-wheelers. India also has substantial strength in mass production techniques and is particularly well served in the fields of research and development and software design. Therefore, as always, the question is when will expansion occur and to what level? The implications, market drivers and scope of a future massive Indian vehicle market are covered in the India Strategic Market Profile, a brand-new forecast of Indian automotive and related activity to 2020. 37 BIBLIOGRAPHY Robert A. Strong, year, Portfolio Management, 82-85,123-131. Jeff Madura, 2009, Finance Markets and Institutions, 243-283. Dr. G. Ramesh Babu, 2007, Portfolio Management Including Security Analysis, 577-647. www. nseindia. com www. moneycontrol. com www. springerlink. com www. proquest. com www. sciencedirect. com www. jstor. org www. informaworld. com 38

Review on Currency Number Recognition

Reappraisal on Currency Number Recognition Abstraction Over the past old ages, a great technological progresss in colour printing, duplicating and scanning, forging jobs arrived. In the yesteryear, merely the printing house has the ability to do imitative paper currency, but today merely by utilizing a computing machine and optical maser pressman at house, it is possible to publish imitative bank notes. Therefore the issue of expeditiously separating forgery bills from echt via automatic machines has become more of import. Counterfeit notes are job of every state. Thus such a system is required, which is helpful in confirmation and acknowledgment of paper currency notes with fast velocity and less clip demand. These currencies will be verified by utilizing image processing techniques. This consists of image processing with feature extraction of paper currency. Image processing includes the nature of an image to better its ocular information for human reading. The consequence will be whether currency is echt or forgery. General FootingsImage Processing:Digital image processing has become of import in many Fieldss of research, industrial and military applications. The processing on planar informations, or images, utilizing a digital computing machine or other digital hardware.Feature Extraction:Feature extraction method is for bettering velocity and truth between two factors. Most normally used characteristic extraction method is image processing. It effects on design and public presentation of the system intensively. Keywords MATLAB Image Processing Toolbox, GUI ( Graphical User Interface )1. IntroductionFeature extraction of images is the disputing work in digital image processing. The feature extraction of Indian currency notes involves the extraction of characteristics like consecutive Numberss, watermarking of currency. Feature extraction is that of pull outing the natural information from the given information. Probabilities of paper currencies with assorted states are likely rises progressively. This is a challenge for conventional paper currency acknowledgment systems. The acknowledgment of the consecutive Numberss of the Indian paper currency such as 100, 500 or 1000 can be detected utilizing assorted methods. The consecutive Numberss are used as identifiers that average IDs of bills.2. CURRENCY RECOGNITION METHODS2.1 A Reliable Method for Paper Currency RecognitionBy Junfang Guo, Yanyun Zhao, Anni Cai, IEEE Transactions, Proceedings of IC-NIDC2010,978-1-4244-6853-9/10. A Reliable Method for Paper Currency Recognition is based on LBP that means traditional local double star form ( LBP ) method, an improved LBP algorithm, besides called block-LBP algorithm, which is used for characteristic extraction. LBP tool is used for texture description. Advantages of this method have simpleness and high velocity. 2.2 Feature Extraction for Paper Currency RecognitionH. Hassanpour, A. Yaseri, G. Ardeshiri aˆâ€ ¢Feature Extraction for Paper Currency Recognition, IEEE Transactions, 1-4244-0779-6/07,2007. In the techniques for paper currency acknowledgment, three features of paper currencies include size ; colour and texture are used in the acknowledgment. By utilizing image histogram, with the mention paper currency plenty of different colourss in a paper currency is computed and compared. 2.3 Feature Extraction for Bank Note Classification Using Wavelet Transform Euisun Choi, Jongseok Lee and Joonhyun Yoon presented this paper in March, 2006 at IEEE International conference.In this paper probe to have extraction for bank note categorization by working the ripple transform. In the proposed method, high frequence coefficients taken from the ripple sphere and are examined to pull out characteristics. We foremost perform border sensing on measure images to ease the ripple characteristic extraction. The characteristic vectors is so conducted by thresholding and numeration of ripple coefficients. The proposed characteristic extraction method can be used to sorting any sort of bank note. However, in this paper scrutiny of Korean won measures of 1000, 5000 and 10000 won types. The textured parts of different measure images can be easy described by break uping the texture into several frequence sub-bands. In the proposed method, high frequence bomber sets are explored to pull out characteristics from transformed images. 2.4 Texture Based Recognition Techniques Texture is a most utile characteristic for Currency acknowledgment. Textural characteristics related to human ocular perceptive are really utile for characteristic choice and texture analyser design. There are some set of texture characteristics that have been used often for image retrieval. Tamura characteristics ( saltiness, directivity, contrast ) , Tamura saltiness is defined as the norm of coarseness steps at each and every pel location inside a texture part. These characteristics can calculate straight from the full image without any similarity. In general the public presentations of this characteristic are non satisfactory. The saltiness information utilizing a histogram should be considered. The Gabor characteristic usage filters to pull out texture information at multiple graduated tables and orientations. As for texture characteristics, there is a comparing of the public presentation of Tamura characteristics, border histogram, MRSAR, Gabor texture characteristic, and pyram id-structured and tree-structured ripple transform characteristics. Harmonizing to author the experimental consequences indicated that MRSAR and Gabor characteristics perform other texture characteristics. However, to accomplish such good public presentation from MRSAR, the Mahalanobis distance based on an image-dependent Covariance matrix has to be used and it increases the size of characteristic and hunt complexness. The extraction of Gabor characteristic is much slower than other texture characteristics, which makes its usage in big databases. Generally Tamura characteristics are non every bit good as MRSAR, Gabor, TWT and PWT characteristics. 2.5 Placement Rule In the yesteryear, there were some troubles in texture analysis due to miss of equal tools to qualify different graduated tables of texture efficaciously. There are some texture based techniques. The work done in this country was carried out by Tamura. Harmonizing to him, for ocular texture is hard. Its construction is attributed to the insistent forms in which elements are arranged harmonizing to a arrangement regulation. Hence it can be written as f= R ( vitamin E ) , Where R is denoting a arrangement regulation ( or relation ) and e is denoting an component. There is a set of characteristics utilizing this all input forms are measured and gives good distributed consequences. So it is required to hold both extremes defines for each characteristic. e.g. , harsh versus mulct for saltiness. Coarseness is a extremely of import factor in texture. In order to better the other characteristics, its consequences should be utilized. 2.6 Pattern Based Recognition Techniques The Pattern acknowledgment is based on anterior cognition as a characteristic. This is the categorization of objects based on a set of images. These techniques are focused on Vector quantisation based histogram mold. Vector quantisation ( VQ ) is a method of trying a d-dimensional infinite where each point,tenJ, in a set of informations is replaced by one of the L paradigm points. The paradigm points are selected such that the amount of the distances ( deformation ) from each information point,tenJ, to its nearest paradigm point is minimized. The work in this country was completed out by Seth McNeillIn et Al. Author gives the method for acknowledgment of coins by pattern acknowledgment. This differentiates between the bald bird of Jove on the one-fourth, the torch of autonomy on the dime, Thomas Jefferson ‘s house on the Ni, and the Lincoln Memorial on the penny. First collects the information, during the informations aggregation phase assorted background colourss, including bl ack, white, ruddy, and blue, were tested for segmentability. Adobe Photoshop was used to find the RGB values of the coin and its background. Then Segmentation was applied to these images. After the informations aggregation next is Coin Segmentation and Cropping. In this measure coins were segmented from their backgrounds by utilizing some alteration of Nechyba’s codification. Croping plan was implemented to turn up the borders of coin. After this Features were extracted from the coins by texture templets with each image, with border sensing templets. and The consequence of this method is 94 % accurate. 2.7 Color Based Recognition Technique The Wei-Ying Maetal. in describes Color histogram ( CH ) method for an image. It is created by numbering the figure of pels of each colour. Histogram describes the colour distribution in an image. It is easy to calculate and is insensitive to little alterations in sing place ( VP ) . The calculation of colour histogram involves numbering the figure of pels of specified colour. Therefore in an image with declaration m*n, the clip complexness of calculating colour histogram is O ( manganese ) . It overcomes some of the jobs with colour histogram techniques such as high-dimensional characteristic vectors, spacial localisation, and indexing and distance calculation.3. SYSTEM OVERVIEW3.1 Flow of Image Processing Fig 1. Flow of System This system is designed by using image Processing tool chest and other related Matlab tool chest. The system is divided into some subdivision to back up the hereafter acknowledgment procedure.4. RecognitionsA thesis work of such a great significance is non possible without the aid of several people, straight or indirectly. First and foremost I have huge felicity in showing my sincere thanks to my usher, Prof. Vishal Bhope for his valuable suggestions, co-operation and uninterrupted counsel. I am really much thankful to all my module members.5. Reference[ 1 ] Hanish Aggarwal and Padam Kumar, â€Å"Localization of Indian Currency Note in Color Images† , ICCCNT 2012. ( Unpublished ) . [ 2 ] Wei-Ying Ma and HongJiang Zhang, â€Å"Benchmarking of Image Features for Content-based Retrieval† Hewlett- Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA 94304-1126. [ 4 ] Hideyuki Tamura, Shunji Mori, and Takashi, â€Å"Textural Features Matching to Visual Perception† , Member IEEE. [ 5 ] Seth McNeill, Joel Schipper, Taja Sellers, Michael C. Nechybaâ€Å"Coin Recognition utilizing Vector Quantization and Histogram Modelling† Machine Intelligence Laboratory University of Florida Gainesville, FL 32611. [ 6 ] Michael C. Nechyba, â€Å"Vector Quantization a confining Case of EM† , EEL6825: Pattern Recognition Class Material, Fall 2002. [ 7 ] Jing Huang, S Ravi Kumar, Mandar Mitra, Wei-Jing Zhu, Ramin Zabi, â€Å"Image Indexing Using Color Correlograms† , Cornell University Ithaca, NY 14853. [ 8 ] John R. Smith and Shih-Fu Chang, â€Å"Tools and Techniques for Color Image Retrieval† , Columbia University Department of Electrical Engineering and Centre for Telecommunications Research New York, N.Y. 10027.

Ronald Reagan The 40th President of the United States Essay

On February 6, 1911, Ronald Reagan was born in Tampico, Illinois. His parents were Nelle and John Reagan. Ronald Reagans father, Jack Reagan mostly sold shoes. He was a part owner of a shoe store. His mother worked as a sales clerk and seamstress at a local dress shop. Ronald did have a brother his name was Neil, he was a couple years older than him. Ronald Reagan did have a great education, He attended high school in nearby Dixon, and after that he decided to go and attend collage over in Eureka collage. There at the collage he went and studied economics and sociology. While attending collage he played football and did acts in some of the plays. He became a radio sports announcer. Screen tests in 1937 won him a contract in Hollywood.†¦show more content†¦On June 5, 2004, Ronald Reagan, the 40th President of the United States, died after having suffered from Alzheimers disease for nearly a decade. His seven-day state funeral followed. 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