Risk and Return Analyis and Portfolio Management of Indian Automobile Companies

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.

Order custom essay Risk and Return Analyis and Portfolio Management of Indian Automobile Companies with free plagiarism report

450+ experts on 30 subjects Starting from 3 hours delivery

Get Essay Help

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.

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.

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.

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.

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.

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.

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 "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.

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.

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.

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.

Literature review

“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 of 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,
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 covariance forms,
3. Two multi-index models with orthogonal indexes,
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 parameters, 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 “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 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. “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. “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 various 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', suggesting 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. “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.

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).

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.

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.

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.

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.

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.

References

1. Robert A. Strong, year, Portfolio Management, 82-85,123-131. Jeff Madura, 2009, Finance Markets and Institutions, 243-283.
2. Dr. G. Ramesh Babu, 2007, Portfolio Management Including Security Analysis, 577-647.
3. www. nseindia. com
4. www. moneycontrol. com
5. www. springerlink. com
6. www. proquest. com
7. www. sciencedirect. com
8. www. jstor. org
9. www. informaworld. com

Don't let plagiarism ruin your grade

Run a free check or have your essay done for you

Check my essay Hire Writer