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» A STUDY ON INVESTORS PREFERENCE OF COMMODITY MARKETS WITH SPECIAL REFERENCE TO SHARE KHAN
A STUDY ON INVESTORS PREFERENCE OF COMMODITY MARKETS WITH SPECIAL REFERENCE TO SHARE KHAN
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A STUDY ON INVESTORS PREFERENCE OF COMMODITY MARKETS WITH SPECIAL REFERENCE TO SHARE KHAN
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7927 views, 0 comments, Last Update: Jul 19, 2012.
CHAPTER-I INTRODUCTION 1.1. INTRODUCTION TO THE STUDY The main idea behind the study conducted was to find out the investors preference of commodity market with reference to Share khan Financial Services Pvt. Ltd, Gobi. This study should deal with the investor’s preference from commodity market. To identify the investor’s preference means, it should find out the characteristics of investors who invest under the guidance of different share brokers. It also should concentrate on whether they are satisfied with the services and earnings from the commodity market to provided by the investment an also by the brokers service. They will be expecting different types of commodities from their investment guide. Some of them may not be satisfied with their service and the information they give. My aim is to find out the investors preference from commodity market of the investors from their share brokers. How is investors satisfaction from commodity market satisfaction level can be improved by providing better services. Keeping all these things in mind the primary and secondary objectives of the study are set. MEANING OF INVESTOR: An investor is any party that makes an investment. The term has taken on a specific meaning in finance to describe the particular types of people and companies that regularly purchase equity or debt securities for financial gain in exchange for funding an expanding company. Less frequently, the term is applied to parties who purchase
currency, commodity derivatives, personal property, or other assets. The term implies that a party purchases and holds assets in hopes of achieving capital gain or cash flow, not as a profession or for short-term income. Types of investors: Here is an overlapping, non-exclusive list of investor types:
• Individual investors (including
trusts on behalf of individuals, and umbrella
companies formed for two or more to pool investment funds).
• Collectors of art, antiques, and other things of value. • Angel investors, either individually or in groups. • Venture capital funds, which serve as investment collectives on behalf of
individuals, companies, pension plans, insurance reserves, or other funds.
• Investment banks. • Businesses that make investments, either directly or via a captive fund • Investment trusts, including real estate investment trusts • Mutual funds, hedge funds, and other funds, ownership of which may or may not
be publicly traded (these funds typically pool money raised from their ownersubscribers to invest in securities)
• Sovereign wealth funds
standardized, graded products are bought and sold. Worldwide, there are 48 major commodity exchanges that trade over 96 commodities, ranging from wheat and cotton to silver and oil. Most trading is done in futures contracts, that is, agreements to deliver goods at a set time in the future for a price established at the time of the agreement.
Trading of S&P 500 and other financial futures has broken down some of the barriers that once separated stock, bond, and commodity
markets and made it easier for investors to hedge their stock investments. Critics charge that the futures trading at the commodity markets in Chicago have made stock prices more volatile. The Chicago Board of Trade is the largest futures and options exchange in the United States, the largest in the world is Eurex, an electronic European exchange. Types of traders in a derivatives market: Hedgers: Hedgers are those who protect themselves from the risk associated with the price of an asset by using derivatives. A person keeps a close watch upon the prices discovered in trading and when the comfortable price is reflected according to his wants, he sells futures contracts. In this way he gets an assured fixed price of his produce. In general, hedgers use futures for protection against adverse future price movements in the underlying cash commodity. Hedgers are often businesses, or individuals, who at one point or another deal in the underlying cash commodity. Take an example: A Hedger pay more to the farmer or dealer of a produce if its prices go up. For protection against higher prices of the produce, he hedges the risk exposure by buying enough future contracts of the produce to cover the amount of produce he expects to buy. Since cash and futures prices do tend to move in tandem, the futures position will profit if the price of the produce raise enough to offset cash loss on the produce.
Speculators are some what like a middle man. They are never interested in actual owing the commodity. They will just buy from one end and sell it to the other in anticipation of future price movements. They actually bet on the future movement in the price of an asset. They are the second major group of futures players. These participants include independent floor traders and investors. They handle trades for their personal clients or brokerage firms. Buying a futures contract in anticipation of price increases is known as ‘going long’. Selling a futures contract in anticipation of a price decrease is known as ‘going short’. Speculative participation in futures trading has increased with the availability of alternative methods of participation. Speculators have certain advantages over other investments they are as follows: If the trader’s judgment is good, he can make more money in the futures market faster because prices tend, on average, to change more quickly than real estate or stock prices. Futures are highly leveraged investments. The trader puts up a small fraction of the value of the underlying contract as margin, yet he can ride on the full value of the contract as it moves up and down. The money he puts up is not a down payment on the underlying contract, but a performance bond. The actual value of the contract is only exchanged on those rare occasions when delivery takes place. Arbitrators: According to dictionary definition, a person who has been officially chosen to make a decision between two people or groups who do not agree is known as Arbitrator. In commodity market Arbitrators are the person who takes the advantage of a discrepancy between prices in two different markets. If he finds future prices of a commodity edging out with the cash
price, he will take offsetting positions in both the markets to lock in a profit. Moreover the commodity futures investor is not charged interest on the difference between margin and the full contract value. Uses of Futures Markets: In this chapter, the uses of futures markets, especially in connection with futures commodity and their possible uses for the farmers, traders, banks and others have been reviewed. Hedging: The hedger is a trader who enters the futures market in order to reduce a pre-existing risk position. Having a position does not mean that the trader must actually own a commodity. An individual or a firm who anticipates the need for a certain commodity in the future or a person who plans to acquire a certain commodity later also has a position in that commodity. In many cases, the hedger has a certain hedging horizon – the future date when the hedge will terminate. The hedge can be a long hedge or a short hedge. If the hedger buys futures contract to hedge, it will be a long hedge. For example, a roller flourmill owner may like to lock-in the price of the wheat that he wants to purchase three months later by purchasing wheat futures. If three months later the wheat prices rise, carrying futures prices along with them, the flourmill owner will purchase wheat from the spot market at a higher price. The loss that he may suffer in the cash market will be compensated by sale of futures at a higher price. Similarly, a farmer can sell three-month futures at the prevailing price and lock-in his profits at that level. If the prices fall, the loss suffered by the farmer in the cash market will be compensated by the profit that the farmer will earn by squaring the transaction in the futures market.
In practice, hedging solutions are not as neat as the ones described above. In the above example, the goods in question were exactly the same both in the cash and the futures market, the amounts purchased / sold in the cash market matched the futures contract amounts, and the hedging horizons of the farmer and the mill owner matched the delivery dates of the futures contracts. It will be rare for all factors to match perfectly; they will differ in time span covered, the amount of commodity or the physical characteristics of the commodity that are traded in the cash and the futures markets. Such hedges are known as cross-hedges. In such cases, the hedger must trade the right number and kind of futures contract to control the risk in hedged positions as much as possible. There can be situations where the hedger does not have any definite hedging horizon and may enter into what is known as risk-minimizing hedge. The hedger has many incentives. Tax is a major incentive. In an unhedged situation, the profits fluctuate widely and the person / firm may have to pay taxes in the high profit years while he is not able to utilize the tax credits when he runs into losses. Hedging also serves to minimize the cost of financial distress. Widely fluctuating profits may drive many persons / firms to bankruptcy. In an idealized world with no transaction costs, which is inhabited by ‘homo-economics’ this may not be a factor. In the real world, bankruptcy involves avoidable human misery and prolonged winding up procedures.
Role of Speculators: Derivative markets have long been viewed with suspicion as speculators are the most visible players. We consider it appropriate to
emphasize that functioning derivative markets will have speculators who need to be viewed from the point of view of their economic usefulness and who need to be regulated with a view to preventing systemic instability. A speculator is a trader who enters the futures market in search of profit and, by so doing, willingly accepts increased risks. Different types of speculators may be categorized by the length of time they plan to hold a position. Traditionally, there are three kinds of speculators: scalpers, day traders and position traders. Scalper’s time horizon is the shortest, ranging from the next few seconds to the next few minutes and they make profits that may be only one or two ticks, the minimum allowable price movement. If the prices do not move in the scalper’s direction within a few minutes of assuming a position, the scalper will like to close the position and begin looking for a new opportunity. It is understood that scalpers do not go by the demand and supply positions of the underlying commodity but act on the ‘sentiment’. They generate enormous amounts of transactions and are able to survive as they pay minimum transaction cost. Besides earning profits for themselves, their main role is to provide liquidity in the market. They provide a party willing to take the opposite side of a trade for other traders; hedgers know that their orders can be executed. By actively trading, they generate price quotations thereby allowing markets to discover prices more effectively. By competing for trades, they help close the bid-ask spread. Day Traders close their position before the end of trading each day. Their strategy is to guess the price movements on account of developments during the day, including announcement of government policies and release of data. Position Traders maintain overnight positions, which may run into
weeks or even months. They may hold outright positions in which they run huge risks and may also earn big profits. The more risk averse among them assume spread positions which may involve relative price movements in different contracts on the same underlying commodities or commodities which are closely related. It is pertinent to examine whether hedgers need speculators. Theoretically, if there are sufficiently large numbers of short and long hedgers, they may fulfill each other’s need and the speculators may have no role. However, in practice, there is always a mismatch between the time when the short and long hedgers would approach the market and the speculators fill in this gap. Leading commodity markets of world: Some of the leading exchanges of the world are New York Mercantile Exchange (NYMEX), the London Metal Exchange (LME) and the Chicago Board of Trade (CBOT). Leading commodity markets of India: The government has now allowed national commodity exchanges, similar to the BSE & NSE, to come up and let them deal in commodity derivatives in an electronic trading environment. These exchanges are expected to offer a nation-wide anonymous, order driven; screen based trading system for trading. The Forward Markets Commission (FMC) will regulate these exchanges.
1.2 INTRODUCTION TO THE INDUSTRY PROFILE
Commodity markets are markets where raw or primary products are exchanged. These raw commodities are traded on regulated commodities exchanges, in which they are bought and sold in standardized contracts. This article focuses on the history and current debates regarding global commodity markets. It covers physical product (food, metals, and electricity) markets but not the ways that services, including those of governments, nor investment, nor debt, can be seen as a commodity. Articles on reinsurance markets, stock markets, bond markets and currency markets cover those concerns separately and in more depth. One focus of this article is the relationship between simple commodity money and the more complex instruments offered in the commodity markets. 1. History The modern commodity markets have their roots in the trading of agricultural products. While wheat and corn, cattle and pigs, were widely traded using standard instruments in the 19th century in the United States, other basic foodstuffs such as soybeans were only added quite recently in most markets. For a commodity market to be established there must be very broad consensus on the variations in the product that make it acceptable for one purpose or another. The economic impact of the development of commodity markets is hard to overestimate. Through the 19th century "the exchanges became effective spokesmen for, and innovators of, improvements in transportation, warehousing, and financing, which paved the way to expanded interstate and international trade.”
Early history of commodity markets
Historically, dating from ancient Sumerian use of sheep or goats, other peoples using pigs, rare seashells, or other items as commodity money, people have sought ways to standardize and trade contracts in the delivery of such items, to render trade itself more smooth and predictable. Commodity money and commodity markets in a crude early form are believed to have originated in Sumer where small baked clay tokens in the shape of sheep or goats were used in trade. Sealed in clay vessels with a certain number of such tokens, with that number written on the outside, they represented a promise to deliver that number. This made them a form of commodity money - more than an I.O.U. but less than a guarantee by a nation-state or bank. However, they were also known to contain promises of time and date of delivery - this made them like a modern futures contract. Regardless of the details, it was only possible to verify the number of tokens inside by shaking the vessel or by breaking it, at which point the number or terms written on the outside became subject to doubt. Eventually the tokens disappeared, but the contracts remained on flat tablets. This represented the first system of commodity accounting. Classical civilizations built complex global markets trading gold or silver for spices, cloth, wood and weapons, most of which had standards of quality and timeliness. Considering the many hazards of climate, piracy, theft and abuse of military fiat by rulers of kingdoms along the trade routes, it was a major focus of these civilizations to keep markets open and trading in these scarce commodities. Reputation and clearing became central concerns, and the states which could handle them most effectively became very powerful empires, trusted by many peoples to manage and mediate trade and commerce. 2. Size of the market
The trading of commodities consists of direct physical trading and derivatives trading. Exchange traded commodities have seen an upturn in the volume of trading since the start of the decade. This was largely a result of the growing attraction of commodities as an asset class and a proliferation of investment options which has made it easier to access this market. The global volume of commodities contracts traded on exchanges increased by a fifth in 2010, and a half since 2008, to around 2.5 billion million contracts. During the three years up to the end of 2010, global physical exports of commodities fell by 2%, while the outstanding value of OTC commodities derivatives declined by two-thirds as investors reduced risk following a five-fold increase in value outstanding in the previous three years. Trading on exchanges in China and India has gained in importance in recent years due to their emergence as significant commodities consumers and producers. China accounted for more than 60% of exchange-traded commodities in 2009, up on its 40% share in the previous year. Commodity assets under management more than doubled between 2008 and 2010 to nearly $380bn. Inflows into the sector totalled over $60bn in 2010, the second highest year on record, down from the record $72bn allocated to commodities funds in the previous year. The bulk of funds went into precious metals and energy products. The growth in prices of many commodities in 2010 contributed to the increase in the value of commodities funds under management.
3. Commodity Trading 3.1. Spot trading
Spot trading is any transaction where delivery either takes place immediately, or with a minimum lag between the trade and delivery due to technical constraints. Spot trading normally involves visual inspection of the commodity or a sample of the commodity, and is carried out in markets such as wholesale markets. Commodity markets, on the other hand, require the existence of agreed standards so that trades can be made without visual inspection. 3.2. Forward contracts A forward contract is an agreement between two parties to
exchange at some fixed future date a given quantity of a commodity for a price defined today. The fixed price today is known as the forward price. 3.3. Futures contracts A futures contract has the same general features as a forward contract but is transacted through a futures exchange. Commodity and futures contracts are based on what’s termed forward contracts. Early on these forward contracts — agreements to buy now, pay and deliver later — were used as a way of getting products from producer to the consumer. These typically were only for food and agricultural products. Forward contracts have evolved and have been standardized into what we know today as futures contracts. Although more complex today, early forward contracts for example, were used for rice in seventeenth century Japan. Modern forward, or futures agreements began in Chicago in the 1840s, with the appearance of the railroads. Chicago, being centrally located, emerged as the hub between Midwestern farmers and producers and the east coast consumer population centers.
In essence, a futures contract is a standardized forward contract in which the buyer and the seller accept the terms in regards to product, grade, quantity and location and are only free to negotiate the price. 3.4. Hedging Hedging, a common practice of farming cooperatives insures against a poor harvest by purchasing futures contracts in the same commodity. If the cooperative has significantly less of its product to sell due to weather or insects, it makes up for that loss with a profit on the markets, since the overall supply of the crop is short everywhere that suffered the same conditions. 3.5. Delivery and condition guarantees In addition, delivery day, method of settlement and delivery point must all be specified. Typically, trading must end two (or more) business days prior to the delivery day, so that the routing of the shipment can be finalized via ship or rail, and payment can be settled when the contract arrives at any delivery point. 4. Standardization U.S. soybean futures, for example, are of standard grade if they are "GMO or a mixture of GMO and Non-GMO No. 2 yellow soybeans of Indiana, Ohio and Michigan origin produced in the U.S.A. (Non-screened, stored in silo)," and of deliverable grade if they are "GMO or a mixture of GMO and Non-GMO No. 2 yellow soybeans of Iowa, Illinois and Wisconsin origin produced in the U.S.A. (Non-screened, stored in silo)." Note the distinction between states, and the need to clearly mention their status as GMO (Genetically Modified Organism) which makes them unacceptable to most organic food buyers.
Similar specifications apply for cotton, orange juice, cocoa, sugar, wheat, corn, barley, pork bellies, milk, feedstuffs, fruits, vegetables, other grains, other beans, hay, other livestock, meats, poultry, eggs, or any other commodity which is so traded. 5. Regulation of commodity markets In the United States, the principal regulator of commodity and futures markets is the Commodity Futures Trading Commission but it is the National Futures Association that enforces rules and regulations put forth by the CFTC. 5.1. Oil Building on the infrastructure and credit and settlement networks established for food and precious metals, many such markets have proliferated drastically in the late 20th century. Oil was the first form of energy so widely traded, and the fluctuations in the oil markets are of particular political interest. Some commodity market speculation is directly related to the stability of certain states, e.g., during the Persian Gulf War, speculation on the survival of the regime of Saddam Hussein in Iraq. Similar political stability concerns have from time to time driven the price of oil. The oil market is an exception. Most markets are not so tied to the politics of volatile regions - even natural gas tends to be more stable, as it is not traded across oceans by tanker as extensively. 5.2 .Commodity markets and protectionism Developing countries (democratic or not) have been moved to harden their currencies, accept International Monetary Fund rules, join
the World Trade Organization (WTO), and submit to a broad regime of reforms that amount to a hedge against being isolated. China's entry into the WTO signaled the end of truly isolated nations entirely managing their own currency and affairs. The need for stable currency and predictable clearing and rules-based handling of trade disputes, has led to global trade hegemony many nations hedging on a global scale against each other's anticipated protectionism, were they to fail to join the WTO. There are signs, however, that this regime is far from perfect. U.S. trade sanctions against Canadian softwood lumber (within NAFTA) and foreign steel (except for NAFTA partners Canada and Mexico) in 2002 signaled a shift in policy towards a tougher regime perhaps more driven by political concerns - jobs, industrial policy, even sustainable forestry and logging practices. 5.3. Commodity Exchanges A brief description of commodity exchanges is those which trade in particular commodities, neglecting the trade of securities, stock index futures and options etc. In the middle of 19th century in the United States, businessmen began organizing market forums to make the buying and selling of commodities easier. These central marketplaces provided a place for buyers and sellers to meet, set quality and quantity standards, and establish rules of business. Agricultural commodities were mostly traded but as long as there are buyers and sellers, any commodity can be traded. In 1872, a group of Manhattan dairy merchants got together to bring chaotic condition in New York market to a system in terms of storage, pricing, and transfer of agricultural products.
In 1933, during the Great Depression, the Commodity Exchange, Inc. was established in New York through the merger of four small exchanges – the National Metal Exchange, the Rubber Exchange of New York, the National Raw Silk Exchange, and the New York Hide Exchange. The major commodity markets are in the United Kingdom and in the USA. In India there are 25 recognized future exchanges, of which there are three national level multi-commodity exchanges. After a gap of almost three decades, Government of India has allowed forward transactions in commodities through Online Commodity Exchanges, a modification of traditional business known as Adhat and Vayda Vyapar to facilitate better risk coverage and delivery of commodities. The three exchanges are:
• • •
National Commodity & Derivatives Exchange Limited (NCDEX) Multi Commodity Exchange of India Limited (MCX) National Multi-Commodity Exchange of India Limited (NMCEIL)
All the exchanges have been set up under overall control of Forward Market Commission (FMC) of Government of India. 6. National Commodity & Derivatives Exchange Limited (NCDEX) National Commodity & Derivatives Exchange Limited (NCDEX) located in Mumbai is a public limited company incorporated on April 23, 2003 under the Companies Act, 1956 and had commenced its operations on December 15, 2003.This is the only commodity exchange in the country promoted by national level institutions. It is promoted by ICICI Bank Limited, Life Insurance Corporation of India (LIC), National Bank for Agriculture and Rural Development (NABARD) and National Stock Exchange of India Limited (NSE). It is a professionally managed online multi commodity exchange. NCDEX is regulated by Forward Market Commission and is subjected to
various laws of the land like the Companies Act, Stamp Act, Contracts Act, Forward Commission (Regulation) Act and various other legislations. 7. Multi Commodity Exchange of India Limited (MCX) Headquartered in Mumbai Multi Commodity Exchange of India Limited (MCX), is an independent and de- mutualised exchange with a permanent recognition from Government of India. Key shareholders of MCX are Financial Technologies (India) Ltd., State Bank of India, Union Bank of India, Corporation Bank, Bank of India and Canara Bank. MCX facilitates online trading, clearing and settlement operations for commodity futures markets across the country. MCX started offering trade in November 2003 and has built strategic alliances with Bombay Bullion Association, Bombay Metal Exchange, Solvent Extractors’ Association of India, Pulses Importers Association and Shetkari Sanghatana. 8. National Multi-Commodity Exchange of India Limited (NMCEIL) National Multi Commodity Exchange of India Limited (NMCEIL) is the first de- mutualized, Electronic Multi-Commodity Exchange in India. On 25th July, 2001, it was granted approval by the Government to organize trading in the edible oil complex. It has operationalised from November 26, 2002. It is being supported by Central Warehousing Corporation Ltd., Gujarat State Agricultural Marketing Board and Neptune Overseas Limited. It got its recognition in October 2002. Commodity exchange in India plays an important role where the prices of any commodity are not fixed, in an organized way. Earlier only the buyer of produce and its seller in the market judged upon the prices. Others never had a say. Today, commodity exchanges are purely speculative in nature. Before discovering the price, they reach to the producers, end-users,
and even the retail investors, at a grassroots level. It brings a price transparency and risk management in the vital market. A big difference between a typical auction, where a single auctioneer announces the bids and the Exchange is that people are not only competing to buy but also to sell. By Exchange rules and by law, no one can bid under a higher bid, and no one can offer to sell higher than someone else’s lower offer. That keeps the market as efficient as possible, and keeps the traders on their toes to make sure no one gets the purchase or sale before they do.
CHAPTER-II 2.1. INTRODUCTION TO THE COMPANY PROFILE: Share khan financial service Pvt. Ltd.
Share khan is India’s leading online retail broking house. Launched on February 8, 2000 as an online trading portal, Share khan has today a panIndia presence with over 1,529 outlets serving 950,000 customers across 450 cities. It also has international presence through its branches in the UAE and Oman. Share khan offers services like portfolio management, trade execution in equities, futures & options, commodities, and distribution of mutual funds, insurance and structured products. These services are backed by quality investment advice from an experienced research team which offers investment and trading ideas based on fundamental and technical research respectively, market related news, statistical information on equities, commodities, mutual funds, IPOs and much more. Sharekhan is a member of the Bombay Stock Exchange, the National Stock Exchange and the country’s two leading commodity exchanges, the NCDEX and MCX. Sharekhan is also registered as a depository participant with National Securities Depository and Central Depository Services. Sharekhan has set category leadership through pioneering initiatives like Trade Tiger, an Internet-based executable application that emulates a broker terminal besides providing information and tools relevant to day traders. Its second initiative, First Step, is targeted at empowering the first-time investors. Sharekhan has also set its global footprint through the “India First” initiative, a series of seminars conducted by Sharekhan to help the non-resident Indians participate and benefit from the huge investment opportunities in India.
2.2 TOP MANAGEMENT: Mr. Tarun Shah CEO, Sharekhan A Science graduate from St. Xavier’s College, Mumbai, Tarun Shah started his professional life in sales and marketing in a chemicals company. His hands-on approach and rich experience in sales led him to higher challenges that the capital markets provided. In 1987, Mr Shah joined SSKI, a brokerage firm with over five decades of legendary service to its credit. The capital market at that time was undergoing a sea change in terms of character and SSKI under the vision and guidance of Shripal Morakhia and the commitment and hard work of Mr Shah was able to change and adopt the new business practices to achieve a significant growth in a competitive environment. Since then SSKI has achieved growth in each of its businesses: Institutional broking, retail broking and corporate Finance. Starting with the retail broking business of SSKI in Bombay and developing a sub-broker network across the country, Mr Shah was also instrumental in successfully setting up the Institutional Trading Desk of SSKI. Accepting new challenges is a way of life for Mr Shah. To ensure that SSKI’s foray into retail stock broking business through Sharekhan is as successful as every other venture of SSKI, Mr Shah moved in to spearhead this new effort as the CEO of Sharekhan, the retail broking arm of SSKI. Mr. Jaideep Arora Director, Product Development
Jaideep Arora, completed his B.Tech from IIT (Kanpur) and his PGDM from IIM, Kolkata.He worked with ICICI for 8 years where his work spanned a gamut of functions, which included project finance, equity sales and brokerage, investments etc. During his tenure there he set up and headed the Institutional Equity Brokerage Desk at ICICI Securities & Finance Co. Ltd. Mr Arora joined Sharekhan in June 2000 as the head of the Product development division. A year later he took over the reins of the online business of Sharekhan. At present Mr Arora’s responsibilities include spearheading Sharekhan’s online foray as well as its overall customer acquisition effort. Mr. Shanker Vailaya Director, Operations, Finance and Legal Functions A graduate in Commerce from the University of Mangalore and an Associate of The Member of the Institute of Chartered Accountants of India, Shankar Vailaya heads the operations, finance and legal functions of Sharekhan. He is responsible for settlements, depository operations, risk and compliance, regulatory and other legal commitments, and treasury. Mr.Vailaya has managed Sharekhan’s broking operations through the most turbulent times in the aftermath of the securities scam in 1992 and successfully steered the company clear of a flurry of bad papers that hit the market during 1994-95. 2.3 PRODUCTS & SERVICES: I.FIRST STEP: Let the experts guide you!
Always wanted help on what the stock market is all about? Been wondering about how all this works? Well, you don't need to fret any more the Sharekhan First Step is a brand new program designed especially for those who are new to investing in shares. All you have to do is open a Sharekhan First Step account and we'll guide you through the investing process. Click here to learn more about the Sharekhan First Step program. Looking for Answers? Do you have a lot of unanswered questions about stocks and the stock market? We've created special information tools for you, to help answer any queries you may have. All you have to do is sign up to receive all the tools you need to understand the markets and invest in shares! Click here to get a free FirstStep Information Kit. What does the program consist of? In the complex world of investing in shares in India, interested beginners like you didn't have any place they could start out from. This is why we started the First Step program - to assist and guide new investors when they take their first steps into the world of investing in shares. This program is explicitly designed for beginners. You will not feel unintelligent when asking questions like "Who owns the Stock Market?" or "What is a stock-split?" since our people are trained to assist those taking their first step in the market. II.CLASSIC ACCOUNT: Hassle Free Investing, Online, Anytime Anywhere Presenting the easiest way to control your investments with a click of a button. With live stock prices, online cash transfer and instant order execution you get complete freedom from boring paper-work. Our friendly
customer service representatives are accessible via toll-free phone, email and live online chat Proven Research, Timely Advice. Get live analysis before, during & after market hours. From daily intra-day calls to long-term stock recommendations, you will get timely advice with well-defined profit targets. In addition, you can invest in the companies that form part of our Top Picks research basket III.ULTIMATE ONLINE TRADING PLATFORM-TRADE TIGER: Advantages: ? ? ? ? ? ? ? ? ? ? Multiple Exchange Internatinational Market Watch 24 Hour Market Access One Click Filter Unlimited Charts Create your own technical rules for trading A single Trading Screen for all segments Live Streaming Quotes Access all Trading Calls Advanced Charting features Features:
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NCDEX, Mutual Funds, IPOs.
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powered with various Studies.
4. Graph Studies include Average, Band- Bollinger, Know Sure Thing,
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7. User-defined alert settings on an input Stock Price trigger. 8. Tools available to gauge market such as Tick Query, Ticker, Market
Summary, Action Watch, Option Premium Calculator, Span Calculator.
9. Shortcut key for FAST access to order placements & reports. 10. Online fund transfer activated with 12 Banks.
IV.MUTUAL FUND INVESTMENT: Mutual Funds Online Freedom & Flexibility: Invest in Mutual Funds online with your Sharekhan Account. Get access to a number of exclusive mutual fund research reports and ability to invest in Flexible Systematic Investment Plans. Or just download the PDF of the application form and send it to the nearest Sharekhan ShareShop in your city. Alternatively, just call up our toll-free customer care number, and we will dispatch the application form. Benefit from trading in Mutual Funds Online ? ? ? Freedom from filling forms Set up SIPs and Flexi-SIPs Get access to the latest, free research reports with analysis of
Mutual Fund schemes. V.PORTFOLIO MANAGEMENT SERVICES
Post sales services: ? ? ? ? ?
Detailed portfolio reports are available at timely basis like. Investment Summary Portfolio Holding Transaction Statement Bank Book Realized/Unrealized Gain Loss Details Fees Charged Statement (Debit Note) Corporate Benefit (Bonus / Dividend / Right issues declared, etc.) Fund Manager's Report Dedicated Client Servicing Team to address your queries.
? ? ? ?
Why PMS? 1. Leave it to the Experts Who's your Money Expert? Your health, your accounts, your legal matters – you have professionals to manage the entire thing that are most important to you. Do you have an expert to manage your hard-earned money? Share khan Portfolio Management Services (PMS) use the expert management skills of our independent Fund Managers, backed by the
expertise of 35 Financial Research Analysts, to get the best possible returns for you. 2. Disciplined Approach ? We are investing the funds and not just allocating to the sectors to We diversify the portfolio to reduce the risk. We would like to be in stocks with fewer burdens on Balance sheet
achieve decent growth of the corpus. ?
and good earning visibility. 3. Time is Money ? Few Years ago you never imagined that you would have so
much money. And never imagined that you would have so little Time.
?Success has extorted a fee from you: Time Leaving you very few
hours for all the things you think are important. Which is why at Sharekhan Portfolio Management Services, we do not expect you to invest your precious time.
4. Complete Transparency ? The third advantage of PMS is the transparent fee structure. With
transparent fees and AMC charges there are no hidden costs. 5. Structurally Better ? Portfolio management services registered with SEBI are permitted to
exit or enter 100% at any time as long as they don’t leverage and don’t do intraday trading.
The second big advantage of PMS services is that they can hold
fewer stocks and be more aggressive in their stance towards stocks or sectors. ? The third advantage of PMS is the transparent fee structure. With flat fees and AMC charges there are no hidden costs. 6. Risk Disclosure Document Sharekhan Limited PORTFOLIO MANAGEMENT SERVICES – DISCLOSURE DOCUMENT
This Document has been updated up to 31st
March, 2011 and has
been filed with the Securities and Exchange Board of India (SEBI) along with the certificate in the prescribed format in terms of Regulation 14 of the SEBI (Portfolio Managers) Regulations, 1993.
The purpose of this Document is to provide essential information about
the portfolio services in a manner to assist and enable you in making informed decision for engaging us as a Portfolio Manager.
This document gives necessary information about us as ‘Portfolio
Manager’ required by you as an investor before investing. You are advised to read this document and retain this document for future reference.
The name, phone number, e-mail address of the principal officer
designated by us as portfolio manager is as follows: Name of the Shankar Vailaya Phone number 022-61150000, 67481897 principal officer E-mail address firstname.lastname@example.org; VI.COMMODITIES: email@example.com
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2.4 SHAREKHAN RESEARCH: 1. FUNDAMENTAL: Stock Ideas: Aimed at investors. Presents our stock pick and discusses reasons for the same. It comes with a price target and a time frame over which gains can be materialized Investors' Eye: A daily fundamental newsletter to help you take right decisions. ?
Contents Views on most important news reports of the day Reco’s using the bottom-up approach Stock Update reports Special reports Other reports
? ? ?
Share khan Top Picks: A model portfolio comprising of 12 stocks for investors with a horizon of more than a year. Portfolio is updated with new stocks replacing existing stocks as and when required to optimize performance. View Point: Views on companies we don't track. Views on economy, policy changes and government initiatives Special Reports: Specialized reports on unique market opportunities.
Reports like - Selectivity pays monetary policy review, Hurricane gains, Dividend yield stocks, etc. IPO Flash: Report on forthcoming IPOs - only those IPOs which are covered by our research team Sector Reports: View on various sectors and its constituents (Eg. sugar and Balrampur Chini, KCP Sugar Industries, Upper Ganges) Market Outlook: Bi-monthly Fundamental view on the market. 2. TECHNICAL: Punter Call: A daily view on how the market and major indices are expected to trade for the day the closest support and resistance levels are provided to help traders take decisions. Calls created for tomorrow: These calls are for a one-day period and are created today to buy in cash or futures. For selling tomorrow at the target price. Buy with a stop loss or square off by 3.30pm the day after. Smart Charts: It presents the best positional trading calls in the market. Each call is introduced along with a Reco (Go Long/Go Short), a price target, a stop loss and a chart depicting the trend in the stock. Derivative Calls: Toolkit for derivative traders. 3. MUTUAL FUND: Mutual Fund Industry Update: This report provides all the latest news in the industry like fund flows, investment trends, performance of various categories of equity funds, performance in sector funds etc.
Top SIP Fund Picks: This report provides details on the SIP performances of various funds across different categories for various time periods. Top SIP fund picks are provided in Large-cap funds, Multi-cap funds, Mid-cap funds and ELSS funds categories, after analyzing risk return parameters. Top Equity Fund Picks: This report provides details of the Top Funds in Large-cap funds, Mid-cap Funds, Multi-cap funds, balanced funds, thematic funds, ELSS funds etc. Take an informed decision, depending on your risk taking appetite, and stay ahead of the ups and downs of the market. Top Debt Fund Picks: This report provides details of the Top Funds in Monthly income plans, Income funds, Short-term debt funds, Ultra short term funds, Floating rate funds, Liquid funds, Gilt funds etc. 4. COMMODITY: Commodities Buzz: Daily newsletter on commodities fundamentals Riveting Metals: Daily newsletter with Technical calls on metals Eagle Eye (Commodities): Daily newsletter with technical calls on commodities CHAPTER III REVIEW OF LITERATURE 3.1 According to Sahadevan, the Sagging Agricultural Commodity Exchanges Growth Constraints and Revival Policy Options: “Commodity derivatives have a crucial role to play in managing price risk especially in agriculture dominated economies. However, they have been utilized in a very limited scale in India. As long as prices of many commodities are restrained to certain extent by Government intervention in production, supply and distribution, forwards and futures markets for hedging rice risk in those commodities have only limited practical relevance. A review of the
nature of institutional and policy level constraints facing this segment calls for more focused and pragmatic approach from government, the regulator and the exchanges for making the agricultural futures markets a vibrant segment for risk management”. 3.2 According to Peter Gibbon Danish Institute for International Studies, Copenhagen. The commodity question: new thinking on old problems - “This paper reviews more and less mainstream policy options in relation to the „commodity question? in the light both of its classical definition and of the emerging concern about oligopoly. It begins by updating the evidence concerning commodity price decline and volatility, and examining the implications of these phenomena for macro-economic performance and livelihoods in producing countries”. 3.3 According to Stephen Craig,"The Self-Regulation of Commodity Exchanges: The Case of Market Manipulation."-“The paper deals with Price dissemination that every Mandy becomes a monopoly to the local producers, especially once they come to the market. Farmers typically face a short period between the time that they harvest and the time that they can sell the crop”. 3.4 According to Katherine Dusak, Futures Trading and Investor Returns: An Investigation of Commodity Market Risk Premiums. “The long-standing controversy over whether speculators in a futures market earn a risk premium is analyzed within the context of the capital asset pricing model recently developed by harpe, Lintner, and others. Under that approach the risk premium required on a futures contract should depend not on the variability of prices but on the extent to which the variations in prices are systematically related to variations in the return on total wealth. The systematic risk was estimated for a sample of wheat, corn, and soybean futures contracts over the period 1952 to 1967 and found to be close to zero in all three cases. Average realized holding period returns on the contracts
over the same period were close to zero”. 3.5 According to Susan Thomas, Agricultural commodity markets in India-Policy issues for growth: “Strengthening institutions in spot and derivative markets for commodities is a necessary ingredient of the liberalization process in agriculture, and can impact upon the lives of millions. n this paper, we describe the existing market design prevalent on both the spot and the futures markets. We show some evidence on the role played by the nascent futures markets in price discovery. We document the problems of both the spot and the futures markets. We offer three policy proposals: using reference rates for strengthening transparency, exploring a greater role for cash settlement, and treating warehouse receipts as securities”. 3.6 According to N.Sathish Kumar, Asst. Professor & Head, Department of Business Management. Vivekananda PG College, Karimnagar “After almost two years that commodity trading is finding favor with Indian investors and is been seen as a separate asset class with good growth opportunities. For diversification of portfolio beyond shares, fixed deposits and mutual funds, commodity trading offers a good option for long-term investors and arbitrageurs and speculators. And, now, with daily global volumes in commodity trading touching three times that of equities, trading in commodities cannot be ignored by Indian investors. Online commodity exchanges need to revamp certain laws governing futures in commodities to make the markets more attractive. The national multi-commodity exchanges have unitedly proposed to the government that in view of the growth of the commodities market, foreign institutional investors, too, should be given the go-ahead to invest in commodity futures in India. Their entry will deepen and broad base the commodity futures market. As a matter of fact, derivative instruments, such as futures, can help India become a global trading hub for select commodities.
Commodity trading in India is poised for a big take-off in India on the back of factors like global economic recovery and increasing demand from China for commodities. Considering the huge volatility witnessed in the equity markets recently with the Sensex touching 6900 level commodities could add the required zing to investors' portfolio. Therefore, it won't be long before the market sees the emergence of a completely redefined set of retail investors. 3.7 According to Chua, Jess H., Gordon Sick, and Richard S. Woodward (1990). "Diversifying with Gold Stocks" “The authors extend Jaffe’s (1989) study by examining the relative investment benefits of investing in gold equities versus gold bullion during the period September 1971 through December 1988. By splitting their sample period into two sub periods, the authors show that the diversification benefits of gold bullion are much more consistent than the diversification benefits of gold equities. In particular, they find that the beta of gold equities more than doubled between the 1970s and 1980s, whereas the beta of gold bullion remained largely unchanged at approximately zero in both periods. Thus, the authors question the diversification benefits of gold equities, particularly over short investment horizons.” 3.8 According to de Roon, Frans A., Theo E. Nijman, and Chris Veld (2000). "Hedging Pressure Effects in Futures Markets " Journal of Finance, “We present a simple model implying that futures risk premium depend on both own-market and cross-market hedging pressures. Empirical evidence from 20 futures markets, divided into four groups (financial, agricultural, mineral, and currency) indicate that, after controlling for systematic risk, both the futures own hedging pressure and cross-hedging pressures from within the group significantly affect futures returns. These effects remain significant after controlling for a measure of price pressure. Finally, we show that hedging pressure also contains explanatory power for returns on the underlying asset, as predicted by the model.” (p. 1437). 3.9 According to Dusak, Katherine (1973). "Futures Trading and
Premiums." Journal of Political Economy, Vol. 81, No. 6 (November/December): 1387-1406. “The long-standing controversy over whether speculators in a futures market earn a risk premium is analyzed within the context of the capital asset pricing model recently developed by Sharpe, Linter, and others. Under that approach the risk premium required on a futures contract should depend not on the variability of prices but on the extent to which the variations in prices are systematically related to variations in the return on total wealth. The systematic risk was estimated for a sample of wheat, corn, and soybean futures contracts over the period 1952 to 1967 and found to be close to zero in all three cases. Average realized holding period returns on the contracts over the same period were close to zero.” (p. 1387) 3.10. According to Edwards, Franklin R., and Jimmy Liew (1999). "Managed Commodity Futures" Journal of Futures Markets, Vol. 19, No. 4 (June): 377-411. “The authors examine the performance of managed commodity futures as represented by public commodity funds, commodity pool operators, and commodity trading advisers. The authors indicate that the costs associated with investing in CPOs and CTAs may be quite large because the funds may incur significant transaction costs, which are added to a number of fees charged to investors, including management fees, profit-based incentive fees, and loads. Despite these relatively high costs, the authors find that the net return to commodity fund investments is frequently relatively attractive. Each individual fund, however, has relatively volatile returns, so the stand-alone performance of managed commodity futures is poor relative to traditional investments. The authors find that, in general, adding a portfolio of CPOs or CTAs to a traditional investment portfolio enhances portfolio performance. In addition, the authors compare the returns to CTAs and CPOs with the returns to the passive Reuters/Jefferies CRB Index and the MLM. The MLM is a dynamic index based on momentum in commodity prices, which is consistent with the strategy followed by many managed futures funds. The authors find a significant positive
relationship between the returns to managed futures and the MLM but no significant relationship between managed funds and the CRB. This finding is consistent with the contention that the MLM provides a general indicator of the performance of managed futures. The authors also find, however, that neither the MLM nor the CRB supplants managed futures in their derived efficient portfolios.”
CHAPTER IV RESEARCH METHODOLOGY The methodology of research indicates the general pattern of organizing the procedure of gathering valid and reliable data for the problem under investigations (Kothari, 1996). The methodology of this study includes the choice of the research approach, sampling technique, development of the tool, data collection procedure and method of analysis based on the statement and objectives of the study. Research approach The selection of the research approach is the basic procedure for the
conduct of research. A research approach tells the investigator as to what data to collect and how to analyze it. It also suggests possible conclusion to be drawn from the data. The research approach refers to the investigator overall plan for obtaining answers to the research question and for testing the research hypothesis. It spells out the strategies that the investigator adopts to develop information that is accurate, objective and interpretable. It is set of flexible guide spots designed to keep the investigator in the right direction. ( Polit and Hungler, 1999). 4.1 OBJECTIVES OF THE STUDY
To study about the investors preferences towards commodity market in Share khan Financial Services Pvt. Ltd, Gobi. To find out very high preference of commodity market. To analyze the various factors influencing investor’s preference on commodity market. To find out the investors awareness regarding commodity market. To study about the investors acceptance level of rumors in commodity market. To find some suggested measures to improve the present level.
4.2 SCOPE OF THE STUDY
It assesses the preference of choosing the market by the respondents. The study helps us to know about the Investor’s preferences towards commodity market. It helped to bring out various investment opportunities and preference in commodity market. The specific reason to why people preference commodity market one mode of investment and earning high return
4.3 RESEARCH DESIGN Research design constitutes the blue print for the collection and analysis of the data. Research design is essential as it facilitates the smooth sailing of various research operations so as to make the research as efficient as possible yielding maximum information with minimum of effort, time, and money. "Decisions regarding what, when, how, how much by what means concerning a research constitutes the research design.” DESCRIPTIVE RESEARCH: Descriptive Research includes surveys and fact - finding --C.R. Kothari
enquiries of different kinds of the major purpose of descriptive research is description of the state of affairs as it exists at present. In social science and business research we quite often use the term ex post facto research for description research studies. SAMPLING UNIT Business Men, Professionals, Employed personnel, others like House wife etc. SAMPLE SIZE A sample size of 120 investors was selected for the study in the Gobi Region. METHOD OF DATA COLLECTION Here the researcher mainly used primary data. A. PRIMARY DATA Data are collected for the first time for a specific purpose in mind
using the questionnaire method and interview method. B. SECONDARY DATA The secondary data was collected from the company Journals, Reports, Magazines, Internet and Materials obtained from the commodity product in the regional Office. 4.4 SAMPLING TECHNIQUE This sampling method involves purposive or deliberate selection of particular units of the universe for consulting a sample, which represents the universe. Non Probability- Convenience Sampling: When population elements are selected for inclusion in the sample based on the ease of access it can be called convenience sampling 4.5 TOOLS FOR ANALYSIS
1. Simple No. of Respondents in (%) analysis
2. Chi-Square Test 3. Correlation Analysis 4. Weighted Average 5. ANOVA 1. SIMPLE NO.OF RESPONDENTS IN (%) ANALYSIS No. of Respondents in (%) analysis is a simple and effective method used for analyzing collect data. It provides clear distribution of respondent’s responses. Using this method we can get clear view of how customer respondents to a specific query distributed among different options. No. of Respondents in (%) = (Number of Respondent/ Total
Respondents) X 100 2. CHI-SQUARE TEST The chi-square test is an important test amongst the several tests of significant'. Chi- Square, symbolically written as ?² (Pronounced as Ki Square), is a statistical measure used in the context of sampling analysis for comparing a variance to a theoretical variance. It can also be used to make comparisons between theoretical populations and actual data when categories are used. Thus, the chi-square test is applicable in large number of problems. The tests is, in fact, a technique through the use of which it is possible for all researchers to (i) Test the goodness of fit; (ii) Test the significant of association between two attributes, and
(iii) Test the homogeneity or the significance of population variance.
?² =? (Oij- Eij) ² / Eij Where, Oij = Observed frequency of the cell in ith row and jth column. Eij = Expected frequency of the cell in ith row and jth column. 3. CORRELATION ANALYSIS: It is helps to determine the strength of linear between the two variables X &Y. In other words as to how strongly are these two variables correlated. Karl Pearson, in 1986 developed and index or co-efficient of these association in case where the relationship is a linear one. i.e. where the trend of the relationship can be described by a straight line.
N ? dx dy – (? dx) (? dy) r = -----------------------------------------?N?dx² - (? dx) ² ?N? dy² - (? dy) ² 4. WEIGHTED AVERAGE: Weighted average may be defined as the average obtained multiplying the various item in serious by certain values know as weighted and the total of products so obtained is dividend by the total of weighted. Weighted Average Where, W- No. of Respondents favoring in the opinion X- Value of the score to the option. 5. ANOVA: Analysis of variance (Abbreviated as ANOVA) is an extremely useful technique concerning researches in the field of economics, biology, education, psychology, sociology, business/industry in researches of several other disciplines. This technique is used here since multiple sample cases are involved. The significance of the difference between the means of two samples can be judged through either Z-test or T- Test but the difficulties arise when we happen to examine the significance of the difference amongst more than two sample means at the same time. The ANOVA techniques enable us to perform this simultaneous test and as such are considered to be an important tool of analysis in the hands of a researcher. Using this technique, one can draw inferences about whether the samples have been drawn from populations having the same mean.
= (? XW/? W)
The essence of ANOVA is that the total amount of variation in set of data is broken down into two types, that amount which can be attributed to chance and that amount which can be attributed to specific causes. The technique involves the following steps: 1. The Correlation factor (C.F) = (T) ² / N Where, T = Grand Total N = No. Of observation 2. Total SS - (SS between Columns + SS Between rows) = SS for residual or error Variance 3. Degree of freedom (d.f.) can be worked out under: d.f. for total variance ( c. r -1) d.f.for variance between columns d.f. for variance between rows d.f. for residual variance Where, c = Number of columns r = Number of rows 4. ANOVA table can be setup in the usual fashion as shown below: Source of variation Sum of square SS Degree of freedom (d.f) Mean Square (ms) SS Between Columns / ( c-1 ) Between Rows ? ( ( Ti )² / ni )(T)²/n))
= = =
Between columns treatment
? ( ( Tj )² / nj )(T)²/n))
( c-1 )
MS between Columns / MS residual
SS Between rows /
MS between rows / MS residual
(r–1) SS Residual / (c–1) (r–1)
Residual or Error
Total SS – ( SS between columns + SS between Rows ) ? x²ij-((T)²/n))
( c. r -1)
4.6 LIMITATIONS OF THE STUDY Though at most care was taken to do the research articulately, it is liable to certain limitations viz. ?
The survey was limited to Gobi only. The respondents were less interested in answering the questionnaire, as All respondents were not very much open in giving their details. Limited time period of the study. Difficulties to see the investors, since most of the investors were trading in
they felt that it was an interruption to their regular work. ? ? ?
their home itself. 4.7 CHAPTER SCHEME: The whole study has been divided into five chapters as detailed below: • The first chapter provides an idea about the investor’s preference of
The second chapter deals the overview about the industry profile The third chapter devoted to literature survey. The researcher
and, company profile. attempted an exhaustive review of literature relating to the field of study and has analyzed the various studies which focused on the investor’s preference of commodity market. • The fourth chapter deals with research methodology adopted in the study. In this chapter, the objectives set for the study, data collection sources, data collection tools, limitation of the study and chapter of schemes are explained. • The fifth chapter deals with analysis and interpretation of data are undertaken, the analysis and interpretation have been supplemented and strengthened with appropriate tables. A systematic and scientific analysis of data has been made using different types of financial and statistical tools. • The sixth chapter brings out a comprehensive list of various findings of the study. The systematic way of analysis and interpretation of data has resulted in arriving at logical findings and on the basis of finding of the study; the researcher has come out with certain practical suggestions and conclusion. In this chapter, the researcher also has outlined the directions for further research which could be undertaken by future researchers in this area of study.
CHAPTER – V ANALYSIS AND INTERPRETATION
1. SIMPLE NO.OF RESPONDENTS IN PERCENTAGE ANALYSIS
Table No 5.1: The table showing the Age Group of the Respondents S.No Age group No. of Respondents 1 2 3 4 Inference: From the above table, it is clear that 15.8% of the respondents are belongs to the age below 25yrs, 34.2% of the respondents are belongs the age between 25 years to 50 years.43.3% of the respondents are belonging the age between 50 years to 75 years. 6.7% of the respondents are belongs to above 75yrs of age group. Hence, the investors belongs the age between 50 to 75 years are major investors in the market. Chart No 5.1: Age Group of the Respondents Below 25 yrs 25-50 yrs 50-75 yrs Above75 yrs Total 19 41 52 8 120 No. of Respondents in (%) 15.8 34.2 43.3 6.7 100
Table No 5.2: The table showing occupation of the Respondents S.No 1 2 3 4 Total Inference: From the above table, it is reveals that 27.5% of the respondents are Businessmen, 38.3% of the respondents are professional, 22.5% of the respondents are Employed & 11.6% of the respondents are private others. Hence, most of the respondents are professionals. Chart No: 5.2 The chart showing occupation of the Respondents Occupation Business Profession Employed Others No. of Respondents 33 46 27 14 120 No. of Respondents in (%) 27.5 38.33 22.5 11.66 100
Table No. : 5.3 The table showing Gender of the Respondents No. of Respondents in (%) 76.7 23.3 100
No. of Respondents 92 28 120
Male Female Total
Inference: From the above table, it is notified that 76.7% of the respondents are Male and 23.3% of the respondents are Female. Chart No: 5.3: The chart showing Gender of the Respondents
Table No.5.4: The table showing Educational Qualifications of the Respondents Educational Qualifications Up to 12th UG PG Others Total Inference: From the above table, it is shows that 16.7% of the respondents are in the category of up to 12th, 40% of the respondent’s Educational
S.No 1 2 3 4
No. of Respondents 20 48 38 14 120
No. of Respondents in (%) 16.7 40 31.7 11.7 100
qualifications are UG, 31.7% of the respondents are belongs to PG and 11.7% of the respondent’s Educational qualifications are others. Hence, majority of the respondents are falls in UG. Chart No. 5.4: The chart showing Educational Qualifications of the Respondents
Table No.5.5: The table showing Annual Income of the Respondents No. of Respondents 40 28 23 29 120 No.of Respondents in (%) 33.3 23.3 19.2 24.2 100
S.No 1 2 3 4
Annual Income Below 2 Lakhs 2 Lakhs -4 Lakhs 4 Lakhs-6 Lakhs Above 6 Lakhs Total
Inference: From the above table, it is inferred that 33% of the respondent’s Annual income is Below 2 Lakhs, 23.3% of the respondent’s Annual income is 2 Lakhs - 4 Lakhs, 19.2% of the respondent’s Annual income is 4 laks-6 lakhs
and 24.2% of the respondents are belongs to above 6 Lakhs. Hence, most of the respondent’s annual income falls in below 2 lakhs. Chart No: 5.5 : The chart showing Annual Income of the Respondents
Table No.5.6: The table showing Investment Objectives of the Respondents S.No 1 2 3 4 Investment Objectives High income Reasonable income for safety For Retirement welfare Tax benefit Total Inference: From the above table, it is identified that 64.16% of the respondent’s investment objective is to earn high Income, 29.16% of the respondent’s aim is as reasonable income for safety. 6.66% of the respondent’s objective is to
No. of Respondent s 77 35 8 0 120
No.of Respondents in (%) 64.1 29.1 6.7 0 100
for retirement benefit and 0% of the respondent’s objective is to for tax Benefits. Hence, Most of the investors are aims at earning the high income. Chart No.5.6: The chart showing Investment Objectives of the Respondents
Table No.5.7: The table showing Investment portion of the Respondents income S.No 1 2 3 4 Inference: From the above table, it is find that 30.83% of the respondent’s investment portion of income is below 25%. 35.83% of the respondent’s investment portion of income is between 25%-50%, 29.16% of the respondent’s investment portion of income is between 50%-75%, and 4.16% Investment portion Below 25% 25% -50% 50%-75% Above 75% Total No. of Respondent s 37 43 35 5 120 No. of Respondents in (%) 30.83 35.83 29.16 4.16 100
of the respondent’s investment portion of income is above 4%. Hence, majority of the respondent’s investment portion are in between 25 to 50%. Chart No.5.7: The chart showing Investment portion of the Respondents income
Table No.5.8: The table showing Risk taking capacity of the Respondents S.No 1 2 3 4 5 Risk taking capacity Very high High Medium Low Very low Total No. of Respondent s 20 24 26 26 24 120 No. of Respondents in (%) 16.66 20 21.66 21.66 20 100
Inference: From the above table, it is clearly shows that 16.67% of the respondent’s risk taking capacity is very high, 20% of the respondent’s risk
taking capacity is high, 21.66% of the respondent’s risk taking capacity is Medium, 21.66% of the respondent’s risk taking capacity is low and 20% of the respondent’s risk taking capacity is very low. Hence, majority of the respondents are willing to take medium risk in their investment. Chart No.5.8: The chart showing Risk taking capacity of the Respondents
Table No.5.9: The table showing Current Investment of the Respondents No. of Respondents in (%) 49.16 27.5 14.16 9.16 100
S.No 1 2 3 4
Current Investment Below 1 lakhs 1 Lakhs -2 Lakhs 2 Lakhs -3 Lakhs Above 3 Lakhs Total
No. of Respondents 59 33 17 11 120
From the above table, it is reveals that 49.16% of the respondent’s current investment amount is below 1 Lakhs.27.5% of the respondent’s current investment amount is between 1 Lakhs -2 Lakhs, 14.16% of the respondent’s current investment amount is between 2 Lakhs -3 Lakhs, and 9.16% of the respondent’s current investment amount is above 3 Lakhs. Hence, most of the respondents (59) investment amount falls below 1 lakhs. Chart No.5.9: The chart showing Current Investment of the Respondents
Table No.5.10: The table showing Investment advice of the Respondents No. of Respondent s 59 21 9 31
S.No 1 2 3 4
Investment advice Friends Family Consultants others
No. of Respondents in (%) 49.16 17.5 7.5 25.83
From the above table, it shows that 49.16% of the respondents are getting investment advice from their friends.17.5% of the respondents are getting investment advice from their family, 7.5% of the respondents are getting investment advice from their consultants and 25.83% of the respondents are getting investment advice from their others. Hence, It is found that majority of the respondents are advised by their friends. Chart No.5.10: The chart showing Investment advice of the Respondents
Table No.5.11: The table showing Various Investment preferences of the Respondents S.No 1 2 3 Investment avenues Share Mutual funds Commodity market
No. of Respondent s 52 26 32
No. of Respondents in (%) 43.33 21.66 26.66
Other savings Total
Inference: From the above table, it is noted that 43.33% of the respondents are prefer shares, 21.66% of the respondents are like to invest in mutual investments ,26.66% of the respondents are preferring commodity market investment avenues, and 8.33% of the respondents are like to invest only in other savings like insurance , saving deposits.. Hence, we can understand that majority of the respondents are interested to invest in shares only. Chart No.5.11: The chart showing Various Investment preferences of the Respondents
Table No.5.12: The table showing Source of know about the commodity market of the Respondents Source of know about S.No 1 2 3 the commodity market of the Respondents Friends Dealers Mass media No. of Respondents 59 5 25
No. of Respondents in (%) 49.16 4.166 20.83
Officials of investment org. Total Inference:
From the above table, it is inferred that 49.16% of the respondents are getting know about commodity market through friends, 4.16% of the respondents are knowing through dealers, 20.83% of the respondents are getting know about commodity market through mass medias, and 19.16% of the respondents are came to know about commodity market through officials of investment organizations. Hence, it’s clearly understood that most of the respondents are came to know about commodity market through their friends. Chart No.5.12: The chart showing Source of know about the commodity market of the Respondents
No. of R espondentsto knowabout C m om odityMark Throug et h
21% Friends Dealers 53% Mass m edia Officialsof investm ent organization
Table No.5.13: The table showing Experience of the Respondents in commodity Trading S.No 1 2 3 4 Experience in commodity market Below 1 year 1-2 years 2-3 ears More than 3 years
No. of Respondent s 18 42 23 37
No. of Respondents in (%) 15 35 19.16 30.83
From the above table, it is clearly indentified that 15% of the respondents are trading in commodity market below 1 year, 35% of the respondents are experienced between 1-2 years, 19.16% of the respondents are trading between 2-3 years and 30.83% of the respondents are experienced in commodity market more than 3 years. Hence, It’s concluded that majority of the respondents are experienced in commodity market below 1-2 years. Chart No.5.13: The chart showing Experience of the Respondents in commodity Trading
Table No.5.14: The table showing the Frequency of Trading in commodity market of the respondents S.No 1 2 3 4 Frequency of Trading Daily Weekly Monthly Every season No. of Respondent s 103 7 3 2
No. of Respondents in (%) 85.83 5.83 2.5 1.66
5 6 Inference:
Occasionally Rarely Total
3 2 120
2.5 1.66 100
From the above table, it is clear that 85.83% of the respondents are trading in commodity market in daily basis, 5.83% of the respondent’s frequency of trading falls in weekly basis, 2.5% of the respondents are trading in monthly basis, 1.66% of the respondents are trading in commodity market in every seasons, 2.5% of the respondent’s trading frequency is in occasional basis, and 1.66% of the respondents are trading in commodity market in rarely. Hence, it’s reveals that most of the investors are trading in commodity market in daily basis. Chart No.5.14: The chart showing Frequency of Trading in commodity market of the respondents
Table No.5.15: The table showing Awareness level of commodity market regulations and its circular S.No 1 2 Experience in commodity market Very high High
No. of Respondents 70 30
No.of Respondents in (%) 58.33 25
3 4 5 Inference:
Medium low Very low Total
10 7 3 120
8.33 5.83 2.5 100
From the above table, it is inferred that 58.33% of the respondent’s awareness level of market’s regulations and its circulars is very high, 25% of the respondent’s awareness level falls in high, 8.33% of the respondents are moderately aware about market’s regulations and its circulars, 5.83% of the respondents are having low level awareness of market’s regulations and its circulars, and 2.5% of the respondents are not aware of market’s regulations and its circulars. Hence, it’s concluded that out of the sample most of the respondent’s awareness level falls in the very high category. Chart No.5.15: The chart showing Awareness level of commodity market regulations and its circular
Table No.5.16: The table showing Reason for Choosing Commodity Market of the Respondents S.No 1 2 3 Reason for Choosing Commodity High return Moderate return Safe return
Respondents Respondents in (%) 82 68.33 4 4 3.33 3.33
Low Margin Total
From the above table, it is found that 68.33% of the respondents are choosing the commodity market for getting High return, 3.33% of the respondent’s reason for choosing commodity market is moderate return, 3.33% of the respondents are prefer to choose the commodity market is for earning safety return, and 25% of the respondent’s reason for choosing commodity market falls in low Margin. Hence, It’s inferred that majority of the respondents are likely to choose the commodity market for getting high return. Chart No.5.16: The chart showing Reasons for Choosing Commodity Market of the Respondents
Table No.5.17: The table showing Investors preference of commodity market of the respondents
Types of commodities Plantation Products: Rubber, Spices: Pepper, Ver y Hig h 17 17 % Hig h % Mediu m % low % very Low %
12.5 16.6 6
11.6 6 15
28.3 3 26.6 6
Turmeric, Jeera, chilli, coriander Pulses: Chana Fibres: V-797 kapas , shankar kapas Cereals: Wheat, Barley, Oil and Oil seeds: Castor seeds, Others: Guar Seeds, Guar Gum, Metals: Steel, Copper, Zinc, Energy: Crude Oil, Thermal Coal, Precious Metals: Gold, Gold (100 gms), Gold International, Silver, Silver (5kg), Silver International, Platinum Others: CER, Polyvinyl Chloride
16.6 6 10
19.1 6 22.5 20.8 3 17.5 18.3 3 9.16 6
36.6 6 25 25.8 3 26.6 6 27.5
23 22 15
19.16 18.33 12.5
15 15 14
12.5 12.5 11.6 6 26.6 6 16.6 6
25 21 22
31 32 33
26 30 36
21.66 25 30
13.3 3 16.6 6
Inference: From the above table it’s clearly found that ? ? 33.3% of the respondents are not ready to prefer the plantation products, Majority of the respondents i.e. 75.5% of the respondents are prefer only
low level of spices products,
36.7% of the respondents are likely to
prefer only low level of pulses
products, ? ? ? ? ? 25 % of the respondent’s preference falls in low level of Fibers products, 25.8% of the respondents are prefer low level of cereals products, 26.7% of the respondents are prefer low level of oil seeds products and 30% of the respondents are not prefer other foods products, 41% of the respondents are very highly given their preference is metal 43% of the respondents are very highly preferred the Energy products like 50% of the respondent’ s preference falls in the Precious products like 33.3% of the respondents are not prefer other metal products like Hence, from the above consolidated table it shows that majority of the
products like steel, copper, etc.
crude oil, natural gas etc. ? gold, ? polyvinyl, ? investors preference is metal, energy and precious metals.
Chart No.5.17: The chart showing Investors preference of commodity market of the respondents
Table No.5.18: The table showing Opinion of the respondents about the specialty of trading in commodity market S.No Specialty of
commodity market 1 2 3 4 Inference: Price hedging Regulated marketing Low risk Quality products Total
Respondent s 51 39 20 10 120
Respondents in (%) 42.5 32.5 16.66 8.33 100
From the above table, it is clearly notify that 42.5% of the respondents are saying the specialty of the commodity trading are price hedging, 32.5% of the respondents are saying the specialty of the commodity trading are regulated market, 16.66% of the respondent’s opinion about specialty of trading are low risk, and 8.33% of the respondents given their opinion about the specialty of the commodity trading are quality products. Hence, form the above table it’s clearly reveals that most of the respondents i.e., (51) are given their opinion about the specialty of this market is price hedging. Chart No.5.18: The chart showing Opinion of the respondents about the specialty of trading in commodity market
Table No.5.19: The table showing Level of acceptance of the respondents about luring advertisement, rumors etc. S.No Level of acceptance of luring advertisement, 66 No. of Respondents No.of Respondents in (%)
rumors etc 1 2 3 4 5 Inference: From the above table, it is found that 67.5% of the respondent’s level of acceptance about rumors and luring advertisements is very high, 20.83% of the respondents are highly accepting about rumors and luring advertisements, 10% of the respondent’s level of acceptance about rumors and luring advertisements falls in medium, 0.83% of the respondents are having very low level of acceptance about rumors and luring advertisements, and 0.83% of the respondents are not accepting the rumors and luring advertisements. Hence, It’s concluded that majority of the investors are very highly accepting the rumors & luring advertisements. Chart No.5.19: The chart showing Level of acceptance of the respondents about luring advertisement, rumors etc Total Very high High Medium Low Very low 81 25 12 1 1 120 67.5 20.83 10 0.83 0.83 100
Table No.5.20: The table showing Respondents recommendation of others entering into the commodity market Respondents S.No recommendation to others
No. of Respondent s
No. of Respondents in (%)
1 2 3 4 Inference:
Definitely Probably Not sure Never Total
75 33 12 0 120
62.5 27.5 10 0 100
From the above table, it is indentified that 62.5% of the respondents are recommends others enter into the commodity, 27.5 % of the respondents are probably recommends others enter into commodity market, and 10% of the respondents are saying not sure to other entering into the commodity market. Hence, from the above table it’s clearly understood that out of the total sample most of the respondents’ i.e. 75 of them are definitely recommending others to enter into the market. Chart No.5.20: The chart showing Respondents recommendation of others entering into the commodity market
2. CHI-SQUARE ANALAYSIS Table No.5.21: The table showing Relationship between Annual Income and Pulses
Income * Pulses Cross tabulation Pulses 1 Count Below two lakhs Expected Count Two Lakhs Four Lakhs Inco me Count Expected Count 4 6.0 8 4.2 4 3.4 2 4.4 18 18.0 2 6 6.7 5 4.7 6 3.8 3 4.8 20 20.0 3 8 7.7 3 5.4 4 4.4 8 5.6 23 23.0 4 14 14.7 11 10.3 7 8.4 12 10.6 44 44.0 5 8 5.0 1 3.5 2 2.9 4 3.6 15 15.0 Total 40 40.0 28 28.0 23 23.0 29 29.0 120 120.0
Count Four Lakhs - Six Expected Lakhs Count Count Above Six Lakhs Expected Count Count Total Expected Count
Step1 : Null Hypothesis (H0): There is no significant relationship between Annual Income and Pulses. Step2 : Alternate Hypothesis (H1): There is significant relationship between Annual Income and Pulses. Step 3 : calculation of chi-square ?² =? (Oij- Eij) ² / Eij
Table No.22: calculation of chi-square S.No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Oij 4 6 8 14 8 8 5 3 11 1 4 6 4 7 2 2 3 8 12 4 Chi square(?² Eij 6 6.67 7.67 14.67 5 4.2 4.67 5.37 10.26 3.5 3.45 3.83 4.4 8.43 2.85 4.35 4.83 5.56 10.63 3.63 OijEij -2 -0.67 0.33 -0.67 3 3.8 0.33 -2.37 0.74 -2.5 0.55 2.17 -0.4 -1.43 -0.85 -2.35 -1.83 2.44 1.37 0.37 (Oij-Eij)² 4 0.4489 0.1089 0.4489 9 14.44 0.1089 5.6169 0.5476 6.25 0.3025 4.7089 0.16 2.0449 0.7225 5.5225 3.3489 5.9536 1.8769 0.1369 (Oij-Eij)²/Eij 0.6666 0.06730 0.01419 0.03059 1.8 3.4380 0.0233 1.0459 0.0533 1.7857 0.0876 1.2294 0.0363 0.2425 0.2535 1.2695 0.6933 1.0707 0.1765 0.0377 14.0228
=? (Oij- Eij) ² / Eij )
Step4 : Therefore, the Degree of freedom in this case
= (r-1) (c-1) = 12 Step5 : Conclusion: The table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the hypothesis. We can, thus, conclude that there is no influencing of income to prefer the pulses. (Null Hypothesis Accepted)
Table No.5.23: The table showing Relationship between Annual Income and Fibres
Income * Fibers Cross tabulation Fibres 1 Count Below two lakhs Expected Count Two Lakhs Four Lakhs Incom e Count Expected Count 8 8.7 10 6.1 3 5.0 5 6.3 26 26.0 2 5 4.0 3 2.8 3 2.3 1 2.9 12 12.0 3 8 9.0 4 6.3 6 5.2 9 6.5 27 27.0 4 10 10.0 6 7.0 6 5.8 8 7.2 30 30.0 5 9 8.3 5 5.8 5 4.8 6 6.0 25 25.0 Total 40 40.0 28 28.0 23 23.0 29 29.0 120 120.0
Count Four Lakhs - Six Expected Lakhs Count Above Six Lakhs Count Expected Count Count Total Expected Count
Step1 : Null Hypothesis (H0): There is no significant relationship between Annual Income and Fibers. Step2 : Alternate Hypothesis (H1): There is significant relationship between Annual Fibers. Step 3: calculation of chi-square ?² =? (Oij- Eij) ² / Eij
Table No.5.24: calculation of chi-square
S.No Oij Eij Oij-Eij (Oij-Eij)² 1 8 8.7 -0.7 0.49 2 5 4 1 1 3 8 9 -1 1 4 10 10 0 0 5 9 8.3 0.7 0.49 6 10 6.1 3.9 15.21 7 3 2.8 0.2 0.04 8 4 6.3 -2.3 5.29 9 6 7 -1 1 10 5 5.8 -0.8 0.64 11 3 5 -2 4 12 3 2.3 0.7 0.49 13 6 5.2 0.8 0.64 14 6 5.8 0.2 0.04 15 5 4.8 0.2 0.04 16 5 6.3 -1.3 1.69 17 1 2.9 -1.9 3.61 18 9 6.5 2.5 6.25 19 8 7.2 0.8 0.64 20 6 6 0 0 Chi square(?² =? (Oij- Eij) ² / Eij )
(Oij-Eij)²/Eij 0.0563 0.25 0.1111 0 0.0590 2.4934 0.0142 0.8396 0.1428 0.1103 0.8 0.2130 0.1230 0.0068 0.0083 0.2682 1.2448 0.9615 0.0888 0 7.7919
Step4 : Therefore, the Degree of freedom in this case = (r-1) (c-1) = 12 Step5 : Conclusion: The table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the hypothesis. We can, thus, conclude that there is no influencing of income to prefer the fibers. (Null Hypothesis Accepted).
Table No.5.25: The table showing Relationship between Annual Income and Energy
Occupation * Energy Cross tabulation Energy 1 Count Business Expected Count Count Expected Count Count Expected Count Count Expected Count Count Total Expected Count Step1 13 14.3 22 19.9 15 11.7 2 6.1 52 52.0 2 3 5.5 10 7.7 3 4.5 4 2.3 20 20.0 3 4 4.1 6 5.8 3 3.4 2 1.8 15 15.0 4 8 5.5 3 7.7 4 4.5 5 2.3 20 20.0 5 5 3.6 5 5.0 2 2.9 1 1.5 13 13.0 Total 33 33.0 46 46.0 27 27.0 14 14.0 120 120.0
Professio Occupati on n Employe d
: Null Hypothesis (H0): There is no significant relationship between Annual Income and Energy.
: Alternate Hypothesis (H1): There is significant relationship between Annual Energy.
calculation of chi-square ?²
=? (Oij- Eij) ² / Eij
Table No.5.26: calculation of chi-square S.No 1 2 Oij 13 3 Eij 14.3 5.5 Oij-Eij -1.3 -2.5
(Oij-Eij)² 1.69 6.25
(Oij-Eij)²/Eij 0.1181 1.1363
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
4 8 5 22 10 6 3 5 15 3 3 4 2 2 4 2 5 1
4.125 5.5 3.575 19.93 7.667 5.75 7.667 4.983 11.7 4.5 3.375 4.5 2.925 6.067 2.333 1.75 2.333 1.517
-0.125 2.5 1.425 2.0667 2.3334 0.25 -4.6666 0.0167 3.3 -1.5 -0.375 -0.5 -0.925 -4.0666 1.6667 0.25 2.6667 -0.5166
0.0156 6.25 2.0306 4.2712 5.44475 0.0625 21.7771 0.0002 10.89 2.25 0.1406 0.25 0.8556 16.5372 2.7778 0.0625 7.1112 0.2668
0.0037 1.1363 0.5680 0.2142 0.7101 0.0108 2.8405 5.5964 0.9307 0.5 0.0416 0.0555 0.2925 2.7259 1.1905 0.0357 3.0477 0.1759 15.7354
=? (Oij- Eij) ² / Eij )
Step4 : Therefore, the Degree of freedom in this case = (r-1) (c-1) Step5 : Conclusion: The table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the
= (4-1) (5-1)
hypothesis. We can, thus, conclude that there is no influencing of Occupation to prefer the Energy. (Null Hypothesis Accepted).
3. ANNOVA Table No.5.27: The table showing Relationship between Occupation and Metals
Occupation * Metals Cross tabulation Metals 1 Business Professio n Occupati on Employe d Others Total 13 21 13 3 50 2 7 16 5 4 32 3 5 2 1 3 11 4 6 2 4 4 16 5 2 5 4 0 11 Total 33 46 27 14 120
Step 1 : Null Hypothesis (Ho): There is no significant relationship between occupation and Preference of the Metal Commodity. Step 2 : Alternative Hypothesis (H1): There is significant difference between occupation and Metal Commodity Preference. Step3 : T=120, n=20, Therefore, Correction factor = (T) ² / n = 120²/20 = 720 Step4 : Total SS =169+49+25+36+4+441+256+4+4+25+169+25+1+16+16+9+16+9+9 = 570 Step 5 : SS between Columns Treatment: = (50²/4) + (32²/4) + (11²/4) + (16²/4) + (11²/4) - 720 (correction Factor) = 285.5
Step 6 : SS between Rows Treatment: = (33²/5) + (46²/5) + (27²/5) + (14²/5) - 720 (correction Factor) = 106 Step 7: SS Residual or Error = Total SS – (SS B/w Columns + SS B/w Rows) = 570 – (285.5 + 106) = 178.5 Step 8: Calculation of Anova Table No.5.28: The Anova Table 5% FLimit (or the table values)
Source of variation Between columns (i.e. between occupation ) Between Rows (i.e. between Metal Preference level ) Residual or
= ( c-1 ) 285.5 = ( 5 – 1 ) =4
= 285.5 / 4 = 71.375
= 71.375 / 14.875 = 4.7983
F ( 4 , 12 ) = 5.9117
=(r–1) 106 =(4–1) =3
= 106 / 3 = 35.3333
= 35.3333 / 14.875 = 2.3753
F ( 3 , 12 ) = 8.7446
= 178.5 /
(r–1) Error 5 =4x3 = 12 Total 570 (4 x 3 ) – 1 = 11
12 = 14.875
Inference: It is noted from the above table that, the calculated ANOVA value is less than the table value. So, there is no relationship between Occupation and Metal preference. (Null hypothesis accepted.)
Table No.5.29: The table showing Relationship between Risk Taking Capacity and Age Group
Risk Taking * Age Cross tabulation Age Below 25 yrs Very high High Risk taking Medium Low Very low Total 0 0 19 0 0 19 25-50 yrs 19 1 5 6 10 41 50-75 yrs 1 23 2 20 6 52 Above 75 yrs 0 0 0 0 8 8 Total
20 24 26 26 24 120
Step 1 : Null Hypothesis (Ho): There is no significant relationship between Risk Taking Capacity and age Group for investing in commodity market. Step 2: Alternative Hypothesis (H1): There is significant difference between Risk Taking Capacity and Age Group for investing in commodity market. Step3 : T=120, n=20, Therefore, Correction factor = (T) ² / n = 120²/20 = 720 Step4 : Total SS 64
= 0 + 1 + 529 + 0 + 361 + 25 + 4 + 36 + 400 + 100 + 36 +
= 1556 – 720 (correction Factor) = 836 Step 5 : SS between Columns Treatment: = (19²/5) + (41²/5) + (52²/5) + (8²/5) - 720 (correction Factor) = 962 – 720 (correction Factor) = 242 Step 6 : SS between Rows Treatment: = (20²/4) + (24²/4) + (26²/5) + (26²/5) + (24²/5) - 720 (correction Factor) = 726 – 720 (correction Factor) =6 Step 7: SS Residual or Error = Total SS – (SS B/w Columns + SS B/w Rows) = 836 – (242 + 6) = 588 Step 8: Calculation of ANOVA
Table No.5.30: The ANOVA Table
Source of variation Between columns (i.e. between occupation) Between Rows (i.e. between Metal Preference level )
5% FLimit (or the table values) F ( 3 , 12 ) = 8.7446
= ( c-1 ) ; 242 =(4–1) =3
= 242 / 3 = 80.6666
= 80.6666/ 49 = 4.7983
=(r–1) 6 =(5–1) =4 =(c–1)
= 6/ 4 = 1.5
= 1.5/ 49 = 0.3061
F ( 4 , 12 ) = 5.9117
Residual or Error
(r–1) =3x4 = 12
= 588 / 12 = 49
(3 x 4 ) – 1 = 11
Inference: It is identified from the above table that, the calculated ANOVA value is less than the table value. So, there is no relationship between Risk taking capacity and age of the respondents. Hence, the null hypothesis accepted.
4. CORRELATION ANALYSIS
Table No.5.31: The table showing Correlation between Spices and metals Spices (X) Metal (Y) 17 50 20 32 18 11 32 16 33 11
Step 1: Calculation of Correlation N ? dx dy – (? dx) (? dy) r = -----------------------------------------?N?dx² - (? dx) ² ?N? dy² - (? dy) ² Step2: Table No.5.32: Correlation between Spices and metals X 17 20 18 32 33 120 r = (X-24) dx -7 -4 -6 8 9 0 -0.5980 dx² 49 16 36 64 81 246 Y 50 32 11 16 11 120 (Y-25) dy 25 7 -14 -9 -14 -5 dy² 625 49 196 81 196 1147 dx dy -175 -28 84 -72 -126 -317
Inference: Since the correlation value should lies between -1 & +1. Here, r value is Negative, so there is No relationship between spices and metals preference of the respondents.
Table No.33: The table showing correlation between Risk Taking capacity and precious metals Risk Taking capacity (X) precious metals (Y) 20 60 24 19 26 11 26 15 24 15
Step 1: Calculation of Correlation N ? dx dy – (? dx) (? dy) r = -----------------------------------------?N?dx² - (? dx) ² ?N? dy² - (? dy) ² Step2: Table No.5.34: Calculation of Correlation X 20 24 26 26 24 120 r = (X-26) dx -6 -2 0 0 -2 -10 dx² 36 4 0 0 4 44 Y 60 19 11 15 15 120 (Y-30) dy 30 -11 -19 -15 -15 -30 dy² 900 121 361 225 225 1832 dx dy -180 22 0 0 30 -128
Inference: Since the correlation value should lies between -1 & +1.Here, r value is Negative, so there is no relationship between Risk Taking capacity and precious metals preference of the respondents. 5. WEIGHTED AVERAGE ANALYSIS
Table No.5.35: The table showing opinion of the respondent’s preference of commodity market rating in Share khan Financial Services Pvt. Ltd, Gobi
Types of commodities Plantation Products: Rubber, Score Spices: Pepper, Turmeric, Jeera,chilli, coriander Score Pulses: Chana Score Fibres: V-797 kapas , shankar kapas Score Cereals: Wheat, Barley, Score Oil and Oil seeds: Castor seeds, Score Others: Guar Seeds, Guar Gum, Score Metals: Steel, Copper, Zinc, Score Energy: Crude Oil, Thermal Coal, Very High 17 85 17 85 18 90 26 130 23 115 22 110 15 75 50 250 52 Hig h 15 60 20 80 20 80 12 48 15 60 15 60 14 56 32 128 20 Mediu m 14 42 18 54 23 69 27 81 25 75 21 63 22 66 11 33 15 low 34 68 32 64 44 88 30 60 31 62 32 64 33 66 16 32 20 very Low 40 40 33 33 15 15 25 25 26 26 30 30 36 36 11 11 13 Total 120 295 120 316 120 342 120 344 120 338 120 327 120 299 120 454 120 2 4 Ranki ng
Score Precious Metals: Gold, Gold (100 gms), Gold International, Silver, Silver (5kg), Silver International, Platinum Score Others: CER, Polyvinyl Chloride Score
300 2 10
76 0 0
33 15 45
30 40 80
15 63 63
454 120 198
Inference: From the above table by the weighted average method, it’s observed that Precious Metals: Gold, Gold (100 gms), Gold International, Silver, Silver (5kg), Silver International, Platinum commodities have 1 rank of investor’s preference, Energy: Crude Oil, Thermal Coal, commodities having the 2nd Rank of the Investors preference. Fibres: V-797 kapas, Shankar kapas commodities having the 3rd rank of among the investors preference. Therefore from the weighted average method majority of the respondents very highly prefer to invest in the commodities like Precious Metal, Energy and Fibres.
CHAPTER – VI FINDINGS, SUGGESTIONS & CONCLUSION 6.1 FINDINGS OF THE STUDY
15.8% of the respondents are belongs 25yrs of age Group, 34.2% of
the respondents are age group between 25 yrs to 50 yrs.,43.3% of the respondents are between 50 to 75 yrs of age group, and 6.7% of the respondents are the above 75 Yrs. ? 27.5 % of the respondents are business people, 46% of the respondents are professionals, 27% of the respondents are employed, and 14 % of the respondents are other occupations.
76.7% of the respondents are male investors, and 23.3% of the 16.7 % of the respondent’s qualification is below schooling, 40% of qualification is post graduates and 11.7 % of the
respondents are female investors. ? the respondent’s qualification is only under graduates, 31.7% of the respondent’s respondent’s qualification is others like diplomas.
33.3 % of the respondents annual incomes level is below than 2
Lakh, 23.3% of the respondents annual incomes level is between 2 Lakh to 4Lakh, 19.2% of the respondent’s annual incomes level is in between 4 lakh to 6 lakh, and 24.2% of the respondents annual incomes level is above 6 lakh.
64.2 % of the respondents investment objectives is High Income ,
29.2% of the respondents investment objectives is Reasonable income for safety , 6.7% of the respondents investment objectives is for retirement welfare and 0% of the respondents an investment objective is tax benefits.
30.8% of the respondents of investments portion from their income
is below 25 %,35.8% of the respondents of investments portion from their income is between 25% to 50%, 29.2% of the respondents of investments portion from their income is between 50% to 75% and 4.2 % of the respondents of investments portion from their income is above 75%.
16.7 % of the respondents risk taking capacity is very high, 20% of
the respondents risk taking capacity is high, 21.7 % of the respondents risk
taking capacity is medium, 21.7% of the respondents risk taking capacity is low, and 20% of the respondents risk taking capacity is very low.
49.2% of the respondent’s current investment is below 1 lakh, 27.5%
of the respondent’s current investment is between 1 lakh to 2 lakh, 14.2% of the respondents’ current investment is between 2 lakh to 3 lakh, 9.2% of the respondent’s current investment is above 3 lakh.
49.2% of the respondents are getting investments advice from their
friends, 17.5% of the respondents are getting investments advice from their family members,7.5% of the respondents are getting investments advice from investment consultants and 25.8% of the respondents are getting investments advice from others sources.
43.3 % of the respondent’s higher preference of their investment
avenues is shares, 21.7% of the respondent’s investment preference is mutual funds, 26.7% of the respondent’s investment preference is commodity markets and 8.3 % of the respondent’s investment preference is other savings. ? 93.3 % of the respondents are well known about commodity market trading, and 6.7 % f the respondents are not having much aware about commodity marketing. ? 49.2% of the respondents are know about commodity market trading through their friends ,4.2% of the respondents are know about commodity market trading through their investment traders, 20.8% of the respondents are know about commodity market trading through mass media, 19.2% of the respondents are know about commodity market trading through the official investment organizations. ?
100% of the respondents are involved in commodity trading. 15% of the respondents are having experience in commodity trading
below 1 yr. 35% of the respondents are having experience in commodity trading between 1 to 2 yrs, 19.2% of the respondents are having
experience in commodity trading between 2 to 3 yrs, and 30.8% of the respondents are having experience in commodity trading more than 3 yrs.
85.8 % of the respondents are daily traders, 5.8% of the respondents
are weekly traders, 2.5% of the respondents are monthly traders, 1.7% of the respondents are season traders, 2.5% of the respondents are occasionally trade, and 1.7% of the respondents are trade rarely.
58.3% of the respondents are very high aware of the commodity
markets circular and its regulations , 25% of the respondents are high level awareness of the commodity markets circular and its regulations, 8.3% of the respondents are medium level of awareness about the commodity markets circular and its regulations, 5.8% of the respondents are having low level of awareness about their commodity markets circular and its regulations, and 2.5% of the respondents are having very low level of awareness about their commodity markets circular and its regulations,
68.3% of the respondents are choosing commodity trade for high
return. 3.3% of the respondents are choosing commodity trade for moderate return, 3.3% of the respondents are choosing commodity trade for safely return, and 25% of the respondents are choosing commodity trading because it’s required only low margin.
14.2% of the respondents are very highly prefer the plantation
products like rubber, 12.5% of the respondents are highly prefer the plantation products like rubber, 11.7% of the respondents are prefer medium level of preference of the plantation products like rubber, and 28.3% of the respondents are prefer low .33.3% of the respondents are very low to prefer the plantation products like rubber
14.2% of the respondents are very highly prefer the spices products
like pepper,turmeric,jeera,chilli,coriander, 16.7% of the respondents are highly prefer the spices products like pepper,turmeric,jeera,chilli,coriander, 15% of the respondents are moderate level of preference of spices products like pepper, turmeric, jeera, chilli, coriander, 26.7 % of the respondents are prefer low level of preference of the spices products like
pepper, turmeric, jeera, chilli, coriander, and 27.5% of the respondents are very low to prefer the spices products like pepper,turmeric,jeera,chilli,coriander.
15% of the respondents are very highly prefer the pulses products
like Chana, 16.7% of the respondents are highly prefer the pulses products like Chana, 19.2% of the respondents are moderate level of preference in pulses products like Chana, 36.7 % of the respondents are prefer low level of preference of the pulses products like Chana, and 12.5% of the respondents are very low to prefer the pulses products like Chana.
21.7% of the respondents are very highly prefer the Fibers products
like V-797 Kapas, Shankar Kapas, 10% of the respondents are highly prefer the Fibers products like V-797 Kapas, Shankar Kapas, 22.5% of the respondents are moderate level of preference in Fibers products like V-797 Kapas, Shankar Kapas, 25 % of the respondents are prefer low level of preference of the Fibers products like V-797 Kapas, Shankar Kapas, and 20.8% of the respondents are very low to prefer the Fibers products like V797 Kapas, Shankar Kapas.
19.2% of the respondents are very highly prefer the Cereals
products like wheat, barley, maize-feed/industrial Grade, 12.5% of the respondents are highly prefer the Cereals products like wheat, barley, maize-feed/industrial Grade, 20.8% of the respondents are moderate level of preference in Cereals products like wheat, barley, maize-feed/industrial Grade, 25.8 % of the respondents are prefer low level of preference of the Cereals products like wheat, barley, maize-feed/industrial Grade, and 21.7% of the respondents are very low to prefer the Cereals products like wheat, barley, maize-feed/industrial Grade. ? 18.3% of the respondents are very high to prefer the oil and oil seeds, 12.5% of the respondents are highly to prefer the oil and oil seeds, 17.5% of the respondents are prefer it only the moderate level, 26.7% of the respondents are prefer only low level and 25% of the respondents are very low to prefer the oil and oil seeds.
12.5% of the respondents are very high to prefer the other products
like Guar Seeds, potato .11.7 % of the respondents are prefer high level, 18.3 %of the respondents are prefer these products only moderate level, 27.5 % of the respondents are prefer it low level and 30 % of the respondents are not to prefer the other products. ? 41.7% of the respondents are very highly prefer metal products like steel, copper and nickel, 26.7% of the respondents are highly prefer metal products like steel, copper and nicke.9.2l % of the respondents are prefer it only moderate levels, 13.3% of the respondents are prefer only low level and 9.2 % of the respondents are not to prefer the metals to invest. ? 43.3% of respondents are very high to prefer the energy products, 16.7 % of the respondents are highly prefer it, 12.5 % of the respondents are only moderate level of preference, and 16.7% of the respondents are very low to prefer it. and 10.81% of the respondents are not ready to prefer it ? 50% of respondents are very high to prefer the Precious metals products, 15.8% of the respondents are highly prefer it, 9.2% of the respondents are only moderate level of preference, 12.5% of the respondents are very low to prefer, and 12.5 % of the respondents are not prefer it. ? 1.7% of the respondents are very highly prefer other products like Polyvinyl, 12.5 % of the respondents are moderate level of preference , 33.3 % of the respondents are very low to prefer it ,52.5 % of the respondents are not to prefer its.
42.5 % of the respondents are saying about commodity market is
price hedging, 32.5% of the respondents are saying about commodity market is regulated marketing, 16.7% of the respondents are saying about commodity market is low risk, and 8.3 % of the respondents are saying about commodity market is quality products.
67.5% of the respondents are very highly accepted the commodity
market advertisement and its rumors. 20.8% of the respondents are highly accept the commodity market advertisement and its rumors, 10% of the respondents are moderate level of acceptance of the commodity market advertisement and its rumors, 0.8% of the respondents are very low accepting the commodity market advertisement and its rumors and 0.8% of the respondents are not to accept the commodity market advertisement and its rumors. ? 62.5% of the respondents are saying definitely recommend commodity trading to others, 27.5 % of the respondents are probably others to trade in commodity market, 12% of the respondents are not ready to recommend others to do in commodity trading.
From the chi square analysis between the income and pulses calculation,
the table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the hypothesis. We can conclude that there is no influencing of income to prefer the pulses. (Null Hypothesis Accepted)
From the chi square analysis between the income and fibers calculation,
the table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the hypothesis. We can, conclude that there is no influencing of income to prefer the fibers. (Null Hypothesis Accepted)
From the chi square analysis between the occupation and energy
calculation the table value of ?² for 12 degree of freedom at 5% level of significance is 21.000. The calculated value ?² is much less than the tabulated value and hence the result of the experiment supports the hypothesis. We can, thus, conclude that there is no influencing of Occupation to prefer the Energy. (Null Hypothesis Accepted)
It is noted from the ANOVA calculation between occupation and precious
metal, the calculated ANOVA value is less than the table value. So, there is no relationship between Occupation and Metal. (Null hypothesis accepted.) ? It is noted from the ANOVA calculation between risk taking capacity and age of the respondents, the calculated ANOVA value is less than the table value. So, there is no relationship between Risk taking capacity and age of the respondents. (Null hypothesis accepted). ? The correlation calculation between spices and metal, the correlation value i.e. r value is Negative, so there is No relationship between spices and metals preference of the respondents.
The correlation calculation between Risk Taking capacity and precious Risk Taking capacity and precious metals preference of the
metals, the correlation i.e. r value is Negative, so there is no relationship between respondents.
From the weighted average method, it’s observed that Precious Metals:
Gold, Gold (100 gms), Gold International, Silver, Silver (5kg), Silver International, Platinum commodities have 1st rank of investor’s preference, Energy: Crude Oil, Thermal Coal, commodities having the 2nd Rank of the Investors preference. Fibres: V-797 kapas, Shankar kapas commodities having the 3rd rank of among the investors preference. Therefore from the weighted average method majorly of the respondents are very highly preferring to invest in the commodities like Precious Metal, Energy and Fibres.
Most of the investors are in male category. So Share khan Financial
Services Pvt. Ltd advised to concentrate more on getting the investment from female investors also.
Compared to Agri, energy, pharmacy sectors, the investors are willing to
prefer bullion sector (GOLD). So the firm should create awareness over other sectors.
Most of the investors getting the information from their friends, so the firm Some investors are hesitating to recommend investing in commodity
should increase the no. of experts available in the market.
market to other people. So, the firm has to give proper guidelines to the investors about the investment in commodity market.
The arrangement of experts and specialist seminar for investors will help The newsletters and special publishing will helps to create high awareness Through appropriate publicity and mass media advertisements the The present trend of commodity market should be continuously informed
to improve their awareness.
of commodity market among the investors. ? awareness of investors will raise up.
to the investors through telephone or other devices.
The study is made to find out the investors preference towards commodity market. The study reveals that commodity market is in a nascent stage in Gobi. The investment avenues of individual investors depend mainly on annual income and risk taking capacity .The female investors in Gobi are not much aware of commodity market so proper awareness program should be conducted to improve the awareness level of among them. The major finds of the study is the majority of the respondents preference falls on precious metals.
Banking and Insurance
A STUDY ON INVESTORS PREFERENCE OF COMMODITY MARKETS WITH SPECIAL REFERENCE TO SHARE KHAN FINANCIAL
A STUDY ON INVESTORS PREFERENCE OF COMMODITY MARKETS WITH SPECIAL REFERENCE TO SHARE KHAN FINANCIAL SERVICES PVT. LTD, GOBI
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