ABSTRACT

The commodities markets are one of the fastest growing areas in the investment world. A
commodity market is an exchange for buying and selling of commodities for future
delivery. Commodity trading in India started much before it started in many other
countries. However year of foreign rule, draught and periods of scarcity and government
policies, caused the commodity trading in India to diminish. Commodity trading was
however restarted in India recently, but a lot more developments and initiatives needs to
be taken in this avenue. Investing on commodities offers protection against risk,
diversified portfolio, trading on lower margin and safety.
The study focuses on understanding the concepts and mechanism of commodity trading.
It also aims to analyze the factors that influence the prices of commodity markets

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 CHAPTER-I

INTRODUCTION

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1.1 Introduction:
The commodity market is a market in which forwards, futures and options are traded for
commodities. The commodity markets have experienced considerable growth in recent
years. The scenario is ready for banks to trade commodity futures. This could help
producers of bankers of agricultural products and other participants in commodity
markets. Banks have begun to recognize the commodity derivatives market. In this
context, Punjab National Bank and Corporation Bank have approved loans worth 50
million rupees to commodity futures traders over the past six months.

In the current global economic scenario, due to various factors such as inflation, political
factors, natural factors, changes in the prices of all commodities are a natural
phenomenon. Therefore, from the point of view of commodity growers (in the case of
agricultural products) or metal traders, there is a real need for them, a tool with which
they can cover their risks. Therefore, a future of commodities is one of the most
important derivative values. This can reduce the risks.

The commodities futures market offers liquidity and delivery based on settlement.
Investors can choose between the two. If the buyer chooses to receive the delivery of the
product, a transferable receipt is issued from the warehouse where the goods are stored in
favor of the buyer. By producing this receipt, the buyer can request the goods from the
warehouse. All open contracts not foreseen for delivery are settled in cash. While
speculators and arbitrageurs generally prefer cash settlement, commodity stockist and
wholesalers arrive at delivery.

The option to match the offer or to receive the delivery can be changed before the last
day of expiry of the contract. In the case of basic delivery transactions, the margin
increases to 0-25% of the contract value and the seller must pay sales tax on the
transaction.

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Tradable Commodities:

World-over one will find that a market exits for almost all the commodities. These
commodities can be broadly classified into the following:

Precious Metals: Gold, Silver, Platinum etc

Other Metals: Nickel, Aluminum, zinc, Copper, Lead etc.

Agro-Based Commodities: Wheat, Corn, Cotton, Oils, oilseeds etc.

Soft Commodities: Coffee, Cocoa, Sugar etc.

Live Stock: Live Cattle, Pork Bellies etc.

Energy: Crude Oil, Natural Gas, Gasoline etc.

Commodity Trading Exchanges in India:

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 Vadya Vyapar to facilitate better
risk coverage and delivery of commodities.

The three exchanges:

 National Commodity & Derivatives Exchange Limited (NCDEX)

 Multi Commodity Exchange of India Limited (MCX)
 National Multi-Commodity Exchange of India Limited (NMCEIL)

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1.2 Need of the study:

The study of the perception of the commodity market by the customer should be carried
out to know what a trader expected from the commodity market and to understand their
decision-making behavior in the choice of a particular product for their investment in the
commodity market. Know the customer selection process and the steps he was taking to
reduce risks. The study will be useful to classify people based on their participation in the
commodity market in relation to their ability to take risks and also to identify which
factors influence the trader to actively participate in this commodity market. This study is
also designed to extract a specific product from all other products in this commodity
market that was highly prescribed by the trader and to learn about the factors that
influence the operator to select that particular product.

It also focuses on getting a clear understanding of the commodity market to know what is
happening, what factors influence the trader to invest in the commodity market, and also
where the investor receives advice on his investment.

1.3 Scope of the Study:

The scope of the study is based on “commodity market trading”. The analysis is based on
the prices on daily basis to show the trend of the market. The study is conducted on gold,
silver, crude oil, natural gas, lead, and zinc only

1.4 Objectives of the Study:

 To identify the specified product in the commodities market which was
performing a leading position when compared other products chosen.
 To study the volatility and reasons of fluctuations in the commodities.
 To analyse the risk and related factors in Commodity market (6 products).

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1.5 Company Information:

Goodwill commodities founded in 2008, is India’s best commodity House & the Largest
Distribution Network, providing a wide range of financial services & investment
solutions. Large avenues of investment solutions & financial services under one roof.
Personalized solution & attention offered to each investor. Research support & timely
advice by our high-tech research wing. An extensive network of branch offices. A perfect
blend of latest technology & rich experience of over a decade. Honesty, transparency &
fairness imbibed in all our dealings.

Vision, Mission and Team:

The company has all it takes to ensure efficiency and reliability in its services and more
important, it is driven by a convergent set of vision, mission and value enabling it to work
single minded towards fulfilling the interests and aspirations of its customers.

Vision:

To be seen by the trader and investor communities as a reliable, efficient, trustworthy

partner in their endeavor to prepare for and enjoy a secure, comfortable and prosperous
future at various stages in their lives.

Mission:

To display all the resources, human and technological, at the disposal of our customers
and help them create and preserve wealth through consistently intelligent investment
decisions.

Head Office:

Goodwill he

Goodwill wealth management pvt. Ltd.

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New no #9(old no 4/1) 2nd floor,

Masha Allah building,

Bheemasena Garden Street,

Off royapettah high road,

(Near thiruvalluvar statue), Millipore, Chennai,

Tamilnadu -600004

Tel: +91-8056098464

Fax: +91-44-43536085

Email: admin@gwcindia.in

Website: http://www.gwcindia.in

Full name: goodwill comtraderspvt.ltd

Local Office:

Goodwill Comrades Pvt. Ltd.

206, 2nd Floor, Shamshiri Estates beside Krishna Children Hospital,

Red Hills Road, Lakdikapul, Hyderabad – 500004

Mobile: 8886032026

Through Goodwill Comrades Pvt. Ltd-SEBI Reg. No. INZ000049087

Through Goodwill Wealth Management Pvt. Ltd-SEBI Reg. No - INZ260006739

Incorporation Date: 2008

Trading exchange: MCX,

Broker type: Full service broker.

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Key Management personnel of the Company:

 MR.BASKARAN (MANAGING DIECTOR)

 MR.SARAVARAN (ZONAL MANAGER)
 MR.ANOOP (VICE PRESIDENT)
 MR.N.SHIVA KUMAR (REGIONAL MANAGER)

Roles and responsibilities in organization:

Goodwill will give updates to customers in

 Economic Outlook and Updates

 Sector and company reports
 Technical Recommendations
 Daily Market Report
 Daily Technical Outlook
 Reports on New Fund Offerings
 Fundamental and Technical Analysis of the Financial Products.

Team:

Goodwill will at times have a full-fledged team of experts and support personnel,
dedicated to meeting customer’s goal and available 24*7 for advice and direction.

Main activities:

Activities auxiliary to financial intermediation, except insurance and pension funding.

This Group includes activities involved in or closely related to financial inter-mediation
other than insurance and pension funding but not themselves involving financial inter-
mediation.

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SWOT Analysis of Company:

Table No. 1.51

Table Showing the SWOT Analysis of Company

STRENGTH WEEKNESS

MAN POWER RMS(risk management system)

70%-80% OF SQUARE OFF
LIMIT EXPOSURE

OPPORTUNITIES THREATS

EXPANSION IN FINANCIAL WE ARE ONLY DEALING

PRODUCTS SUCH AS(Equity, WITH MCX TOUGH COMPITITION
Mutual funds, Derivatives, Currency, FROM COMPITITORS
Commodity etc)

Key Learning’s in Organization:

Commodities: The commodity market is a market where forwards, futures and options
contracts are traded on commodities. Commodities are generally divided into two
categories hard commodities and soft commodities. Hard commodities refer to all the
metals and soft commodities refer to all the agricultural products. Goodwill comtrades
deals with hard metals and conducts trade on the metals tradable through MCX.MCX
(Multi Commodity Exchange) is India’s first listed exchange for commodities. It started
its operation on November 2003 under the regulatory framework of the Securities and

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Exchange Board of India (SEBI). ODIN is the software application used for trading in the
organization.

Apart from Commodities the following were also studied being in the organization

 Equity
 Mutual funds
 Tax savings schemes in mutual funds
 Currency

Awards and Achievements:

Goodwill Comtrades has been awarded as Best commodity broker of the year (2016-17)
by MCX (multi commodity exchange of India)

Marketing Strategies:

 Advertisements
 Promotion activities
 Social linkups
 SMS in WhatsApp
 Long term mutual funds schemes in SIP’s (Systematic Investment Plans )
Business Strategies:

 Lowest brokerage
 Highest exposure
 Mobile trading software
 Tab trading software
 Free Opening Account,
 Free Opening Terminal
 Free live chart
 Free training program

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  Same day pay-out
 24*7 back office service
 Free live market calls
 Free support expert –hub
1.6 Industry Profile:

 The process of economic liberalization in India began in 1991. As part of this

process, several capital market reforms were carried out by the capital market
regulator Securities and Exchange Board of India. One such measure was to allow
trading in equities-based derivatives on stock exchanges in 2000. This step proved
to be a shot in the arm of the capital market and volumes soared within three
years.
 The success of the capital market reforms motivated the government and the
Forward Market Commission (the commodities market regulator) to kick off
similar reforms in the commodities market. Thus almost all the commodities were
allowed to be traded in the futures market from April 2003. To make trading in
commodity futures more transparent and successful, multi-commodity exchanges
at national level were conceived and were allowed to start futures trading in
commodities on-line.
 A lot of water has flown since then. Today commodities exchanges have become
an integral part of Indian financial system. Their volumes have gone through the
roof; from a humble Rs 5000 crores in 2003 today it stands worth of Rs 27 lac
crores per year. This rise in volumes has been led by bullion (gold and silver)
trading. Simultaneously, MCX has emerged as the second largest commodity
exchange in the world in terms the number of silver contracts traded. Similarly it
is the third largest commex in the world today considering the number of gold
contracts traded.
 There is yet another feather in the cap of Indian commixes; while the American
commixes still continue to have open outcry system, Indian ones have begun in
style, with every aspect of trading fully computerized. Thus you have trading
engines which match buy and sell orders at the nanosecond basis.

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  Coming to commodities, today Indian investors can trade in a great number of
commodities on these bourses, and the list is getting bigger by the day. No
wonder then that the commodity futures market is being viewed as a significant
business segment by many–businessmen, investors, institutions, brokers, banks.
 In spite of all this flurry of activity during past three-four years, the awareness
about commodities remains low. Many investors are still not aware that they can
invest in commodities as diverse as gold, silver, jeers, and cotton with the click of
a mouse, right from the confines of their living room. No doubt many are unaware
that commodities are completely unrelated to other investment vehicles and thus
can act as a buffer in the times.

Merger of SEBI and FMC

 On December 25th 2015 SEBI and FMC merged, and the regulation of
commodity derivatives under Securities Contracts Regulation Act (SCRA) 1956.

MINISTRY OF CONSUMER AFFAIRS, FOOD AND PUBLIC DISTRIBUTION

SECURITIES CONTRACT REGULATION ACT

INDIAN COMMODITY EXCHANGE

NATIONAL EXCHANGE REGIONAL EXCHANGE

NCDEX MCX NMCEIL NBOT 20 OTHER

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 REGIONAL EXCHANGE

Figure .No 1.61

Merger of SEBI and FMC
1.7 Commodity Profile
Gold:

Gold is the oldest precious metal known to man. Therefore, it is a timely topic for several
reasons. It is the opinion of the more objective market experts that the traditional
investment vehicles of stocks and bonds are in the areas of their historical highs and may
be due to a severe correction.

Why gold is "good as gold" is an intriguing question. However, we believe that the more
pragmatic ancient Egyptians might have been more accurate in observing that the value
of gold was a function of their pleasing physical characteristics and their scarcity.

World Gold Markets

 London as the great clearing house

 New York as the home of futures trading
 Zurich as a physical turntable
 Istanbul, Dubai, Singapore and Hong Kong as doorways to important consuming
regions
 Tokyo where TOCOM sets the mood of Japan.
Silver:

Silver is a chemical element with the symbol Ag (from the Latin argentum, derived from
the H Iner In proto-Indo-European: "shiny" or "white") and atomic number 47. A soft,
white and glossy transition metal exhibits the highest Electrical conductivity, thermal
conductivity and reflectivity of any metal.

The metal is found in the earth's crust in the pure and free elemental form ("native
silver"), as an alloy with gold and other metals, and in minerals such as argentita and

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chloraguita. Most of the silver is produced as a byproduct of copper, gold, lead and zinc
refining.

Silver has long been valued as a precious metal. Silver metal is used in many bullion
coins, sometimes along with gold: although it is more abundant than gold, it is much less
abundant as native metal.

General Characteristics:
 The unique properties of silver make it a very useful 'Industrial Product', even
though it is classified as a precious metal.
 The demand for silver is based on three main pillars; Industrial uses, photography
and jewelry and silverware, representing 342, 205 and 259 million 3, respectively,
in 2002.
 A little more than half of the silver extracted comes from Mexico, Peru and the
United States, respectively, the first, second and fourth producing countries. The
third largest is Australia.
Indian Scenario:
 Imports of silver in India for domestic consumption in 2002 were 3,400 tons less
than 25% of the 4,540 tons registered in 2001.
 Open General License (OGL) imports are the only major source of supply to the
Indian market.
 The silver paid without tariffs for the export sector increased considerably in
2002, up to nearly 200% year-on-year to 150 tons.
 Around 50% of India's silver requirements last year were met through imports of
Chinese silver and other major sources of supply such as the United Kingdom,
CIS, Australia and Dubai.
World Markets:
 London Bullion Market is the global hub of OTC (Over-The-Counter) trading in
silver.
 Comex futures in New York are where most fund activity is focused.

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Crude Oil:

Crude oil is an unrefined natural petroleum product composed of hydrocarbon and other
organic material deposits. A type of fossil fuel, crude oil can be refined to produce usable
products such as gasoline, diesel and various forms of petrochemical products. It is a non-
renewable resource, which means that it cannot be replaced in a natural way at the speed
we consume and, therefore, it is a limited resource.

Categories of Crude oil:

 West Texas Intermediate (WTI) crude oil is of very high quality. Its API gravity
is 39.6 degrees (which makes it a "light" crude oil), and it contains only 0.24
percent sulfur (which makes crude oil "sweet"). In general, the price of WTI is
around $ 2-4 per barrel of premium to the price of the OPEC basket and $ 1-2 per
barrel of premium to Brent, although on a daily basis the price relationships
between these they can be very important
 Brent Crude Oil is a reference for Europe.
 India depends to a large extent on Middle East oil (high sulfur content).OPEC
has identified China and India as its main oil buyers in Asia over the next few
years.
Crude Oil Units (average gravity):

 1 US barrel = 42 US gallons.
 1 US barrel = 158.98 liters.
 1 ton = 7.33 barrels.
 1 short ton = 6.65 barrels.
 Note: barrels per ton vary from origin to origin.
Global Scenario:

 Oil represents 40 percent of the world's total energy demand.

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  The world consumes about 76 million barrels / day of oil.
 The United States (20 million bbl / d), followed by China (5.6 million bbl / d) and
Japan (5.4 million bbl / d) are the main oil consuming countries.
 The recoverable balance of the reserve was estimated at around 142.7 billion tons
(in 2002), of which OPEC was 112 billion tons.
OPEC fact sheet:

OPEC means "Organization of Petroleum Exporting Countries". It is an organization of

eleven developing countries that relay heavily on oil revenues as their main source of
income.

The current Members are Algeria, Indonesia, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar,
Saudi Arabia, the United Arab Emirates and Venezuela.

 OPEC controls almost 40 percent of the world's crude oil.

 Represents about 75 percent of the world's proven oil reserves.
 Its exports represent 55 percent of the oil traded internationally.
Indian Scenario:

 India is among the top 10 oil consuming countries.

 Oil represents approximately 30 percent of India's total energy consumption.The
country’s total oil consumption is around 2.2 million barrels per day. India
imports around 70 percent of its total oil consumption and does not export.
 India faces a large supply deficit, as domestic oil production is unlikely to keep
pace with demand.
 India’s crude output was only 0.8 million barrels per day.
 The country's oil reserves (around 5.4 billion barrels) are found mainly in the
Mumbai High, Upper Assam, Cambay and Krishna-Godavari and Cauvery basins.
 The recoverable balance of the reserve was approximately 733 million tons (in
2003), of which, on the high seas, 394 million tons and on land was 339 million
tons.
 India had a total of 2.1 million barrels per day in refining capacity.

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  The government has allowed foreign participation in oil exploration,an activity
previously restricted to state entities.
 The Government of India in 2002 officially finalized the Managed Price
Mechanism (APM).Now the price of crude oil is having a high correlation with
the price of the international market. As of today, even the prices of raw bi-
products can vary by +/- 10% in line with international crude, Price, subject to
certain rules established by the government.
 The disinvestment / restructuring of public sector units and the complete
deregulation of the Indian retail sector of oil products is being carried out.

Prevailing Duties & Levies on Crude Oil:

Table 1.7.1 showing the rates of Crude oil

Particulars Rates

Basic Customs Duty 10%

Cess Rs.1800 per metric tonne

NCCD Rs.50 per metric tonne

Education cess 2%

Octroi 3%

Market Influencing Factors:

 OPEC output and supply.

 Terrorism, Weather/storms, War and any other unforeseen geopolitical factors
that causes supply disruptions.
 Global demand particularly from emerging nations.
 Dollar fluctuations.
 DOE / API imports and stocks.

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  Refinery fires & funds buying.

Exchanges Dealing in Crude Futures:

 The New York Mercantile Exchange (NYMEX).

 The International Petroleum Exchange of London (IPE).
 The Tokyo Commodity Exchange (TOCOM).

Natural Gas:

Natural gas is a mixture of natural hydrocarbon gas that consists mainly of methane, but
commonly includes variable amounts of other higher alkanes and, sometimes, a small
percentage of carbon dioxide, nitrogen, hydrogen sulfide or helium.

It is formed when the layers of decomposing plant and animal matter are exposed to
intense heat and pressure below the surface of the Earth for millions of years. The energy
that the plants originally obtained from the sun is stored in the form of chemical bonds in
the gas.

Natural gas is a fossil fuel used as an energy source for heating, cooking and generating
electricity. It is also used as fuel for vehicles and as a chemical feed stock in the
manufacture of plastics and other organic chemical products of commercial importance.
Natural gas based on fossil fuels is a non-renewable resource.

Lead:

Lead is a chemical element with the symbol BP (from the Latin lead) and the atomic
number 82.It is a heavy metal denser than the most common materials. Lead is soft and
malleable, and has a relatively low melting point. When freshly cut, the lead is bluish
white; it dulls to an opaque gray color when exposed to air. Lead has the highest atomic
number of any stable element and three of its isotopes each conclude a chain of
significant decay of heavier elements.

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Lead is a relatively unreactive post-transition metal. Its weak metallic character is
illustrated by its amphoteric character; Lead and lead oxides react with acids and bases,
and tend to form covalent bonds. The exceptions are mainly limited to organic
compounds. Like the lighter members of the group, lead tends to bond with itself; it can
form chains, rings and polyhedral structures.

Zinc:

Zinc is a chemical element with the symbol Zn and the atomic number 30. It is the first
element of group 12 of the periodic table. In some aspects, zinc is chemically similar to
magnesium: both elements exhibit only a normal oxidation state (+2), and the Zn2 + and
Mg2 + ions have a similar size. Zinc is the 24th most abundant element in the earth's
crust and has five stable isotopes. The most common zinc mineral is sphalerite (zinc
blende), a zinc sulphide mineral.

The largest viable sludge is found in Australia, Asia and the United States. Zinc is refined
by flotation by mineral foam, roasting and final extraction using electricity (winning
electro).

Nickel:

Nickel is a chemical element with symbol Ni and atomic number 28. It is a silvery-white
lustrous metal with a slight golden tinge. Nickel belongs to the transition metals and is
hard and ductile. Pure nickel, powdered to maximize the reactive surface area, shows a
significant chemical activity, but larger pieces are slow to react with air under standard
conditions because an oxide layer forms on the Surface and prevents further corrosion
(passivation).Even so, pure native nickel is found in Earth's crust only in tiny amounts,
usually in ultramafic rocks, and in the interiors of larger nickel–iron meteorites that
were not exposed to oxygen when outside earth's atmosphere.

Aluminum:

Aluminum or aluminum is a chemical element with symbol Al and atomic number 13. It
is a silvery-white, soft, nonmagnetic and ductile metal in the boron group. By mass,
aluminum makes up about 8% of the Earth's crust; it is the third most abundant element

19
after oxygen and silicon and the most abundant metal in the crust, though it is less
common in the mantle below. The chief ore of aluminum is bauxite. Aluminum metal is
so chemically reactive that native specimens are rare and limited to extreme reducing
environments. Instead, it is found combined in over 270 different minerals.

Copper:
Copper is a chemical element with symbol Cu (from Latin: cuprum) and atomic number
29. It is a soft, malleable, and ductile metal with very high thermal and electrical
conductivity. A freshly exposed surface of pure copper has a reddish-orange color.
Copper is used as a conductor of heat and electricity, as a building material, and as a
constituent of various metal alloys, such as sterling silver used in jewelry, cupronickel
used to make marine hardware and coins, and constantan used in strain gauges and
thermocouples for temperature measurement

Characteristics of Copper:
 Copper ranks third in world metal consumption after steel and aluminum. It is a
product whose fortunes directly reflect the state of the world's economy.
 Copper is the best non-precious metal conductor of electricity. The metal's
exceptional strength, ductility, and resistance to creeping and corrosion, makes it
the preferred and safest conductor for building wiring.
 Copper is also used in power cables, either insulated or uninsulated, for high,
medium and low voltage applications. Copper is an essential component of energy
efficient motors and transformers and automobiles.
Commodity Futures:

The commodity includes all types of goods. FCRA defines "goods" as "all types of
movable property other than actionable claims, money and securities”. Or any product
that can be used for commerce or an article of commerce that is traded in an authorized
product / commodity.

Commodity futures trading consist of a futures contract, which is a legally binding

agreement that provides for the delivery of the underlying asset or financial entities on a

20
specific date in the future. Like all future contracts, commodity futures are agreements to
buy or sell something at a later date and at a price that the buyer and seller previously set.
Thus, for example, a cotton producer may agree to sell his production to a textile
company many months before the crop is ready for the actual harvest.

This allows you to secure a fixed price and protect your profits from a sharp drop in
cotton prices in the future. The textile company, on the other hand, has been protected
against a possible sharp increase in cotton prices.

The complicating factor is quality. Commodity futures contracts have to specify the
quality of the products that are marketed. The commodity exchanges guarantee that
buyers and sellers will respect the terms of the agreement.

When you buy or sell a futures contract, you are not actually signing a written paper
written by a lawyer; you are assuming a contractual obligation that can be fulfilled in one
of two ways. The first is to make or receive the delivery of the actual product. However,
this is the exception, not the rule, since the actual delivery satisfies less than 2% of all
futures contracts.

The other way to fulfill your obligation, the method that you will probably use, is through
compensation. Very simple, the compensation is to do the opposite, or to offset the sale
or purchase of the same number of contracts bought or sold at some time before the
expiration date of the contract. This can easily be done because futures contracts are
standardized.

Characteristics of Futures Trading:

A “Futures Contract" is a highly standardized contract with certain distinct features.
Some of the important features are as under:-

 A future trading is necessarily organized under the auspices of a market

association so that such trading is confined to or conducted through members of
the association in accordance with the procedure laid down in the Rules & Bye-
laws of the association
 It is invariably entered into for a standard variety known as the "basis variety"

21
 with permission to deliver other identified varieties known as "tender able
varieties".
 The units of price quotation and trading are fixed in these contracts, parties to the
contracts not being capable of altering these units. The delivery periods are
specified.

Commodity Market Structure:

Ministry of Consumer Affairs

FMC

Commodity Exchanges

National Exchanges Regional Exchanges

NCDEX MCX NMCE NBOT 20 Other Regional Exchange

Figure 1.7.2
Figure showing the Commodity market structure

22
Indian Commodity Futures Market:

It looks at six agricultural commodities traded in Indian market. Results indicate that
most of these markets are yet to develop fully as efficient market with better price
discovery. According to Nair (2004), the main bottleneck for growth of commodity
futures market is the fragmented physical market and governmental intervention and
various taxes that hinder the free movement of commodities within the country. Thomas
(2003) highlights the absence of certified warehouse for storage of wide variety of
commodity produced. Bose (2008) comes out clearly with the three tiers of regulators
that govern commodity futures trading in India.

Commodity Trading in India:

Commodity trading in India has a long history. In fact, commodity trading in India started
much before it started in many other countries. However, years of foreign rule, drought
sand periods of scarcity and government policies caused the commodity trading in India
to diminish.

Commodity trading was restarted in India recently. Today, apart from numerous regional
exchanges, India has six national commodity exchanges namely, Multi Commodity
Exchange (MCX), National Commodity and Derivatives Exchange (NCDEX), National
Multi Commodity Exchange (NMCE) and Indian Commodity Exchange (ICEX), the
ACE Derivatives exchange (ACE) and the Universal Commodity Exchange (UCX).

The regulatory body is Forward Markets Commission (FMC) which was set up in 1953.
As of September 2015 FMC was merged with the Securities and Exchange Board of
India, SEBI.

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Trade Timings:

Trading on exchange platform takes place on all days of the week (except Saturdays,
Sundays and holidays declared by the Exchange) Market timings are as follows

Table No.1.7.3
Table showing Trading timings of Commodity Market

Particulars Trading Timings

WEEK-DAYS

10:00 a.m. to 5:00 p.m.

Agri Commodities

Bullion,Metals,CrudeOil and
Internationally linked Agri
10:00 a.m. to 11:30 p.m.
Commodities

The client code modification will be allowed only during 5.00 p.m. to 05.15 p.m.in
respect of contracts traded up to 05.00 p.m. and during 11.30 p.m. to 11.45 for contracts
trade up to 11.30 p.m. on all trading days. In respect of the trading days when the trading
take place up to 11.55 p.m., the client code modification will be allowed only from 11.55
p.m.up to 11.59 p.m

24
 CHAPTER II

REVIEW OF LITERATURE

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2.1 REVIEW OF LITERATURE

Giot, Pierre; Laurent, Sébastien

We put forward Value-at-Risk models relevant for commodity traders who have long and
short trading positions in commodity markets. In a five-year out-of-sample study on
aluminum, copper, nickel, Brent crude oil and WTI crude oil daily cash prices and cocoa
nearby futures contracts, we assess the performance of the RiskMetrics, skewed Student
APARCH and skewed student ARCH models. While the skewed Student APARCH
model performs best in all cases, the skewed Student ARCH model delivers good results
and its estimation does not require non-linear optimization procedures. As such this new
model could be relatively easily integrated in a spreadsheet-like environment and used by
market practitioners

Cretibc Marc Joëts

This paper investigates the links between price returns for 25 commodities and stocks
over the period from January 2001 to November 2011, by paying a particular attention to
energy raw materials. Relying on the dynamic conditional correlation (DCC) GARCH
methodology, we show that the correlations between commodity and stock markets
evolve through time and are highly volatile, particularly since the 2007–2008 financial
crises. The latter has played a key role, emphasizing the links between commodity and
stock markets, and underlining the financialization of commodity markets. At the
idiosyncratic level, a speculation phenomenon is highlighted for oil, coffee and cocoa,
while the safe-haven role of gold is evidenced.

Ing-Haw Cheng1 and Wei Xiongmodity

The large inflow of investment capital to commodity futures markets in the past decade
has generated a heated debate about whether financialization distorts commodity prices.
Rather than focusing on the opposing views concerning whether investment flows caused
a price bubble, we critically review academic studies through the perspective of how
financial investors affect risk sharing and information discovery in commodity markets.
We argue that financialization has substantially changed commodity markets through
26
these mechanisms.
Christopher L.Gilbert
It is widely believed that International Commodity Agreements have lapsed because they
have failed. The reality is more complex. The tin agreement did collapse, but for sugar
and cocoa adverse market conditions and lack of general support made stabilization
impractical. Control of the coffee market ceased largely because of disagreements both
between and within the producing countries on the division of the benefits resulting from
higher prices. Overall, commodity control fits uneasily in an increasingly globalized and
competitive world, and this perception has resulted in a diminished willingness to resolve
the practical difficulties of price stabilization.
Saban Nazlioglu
This study examines volatility transmission between oil and selected agricultural
commodity prices (wheat, corn, soybeans, and sugar). We apply the newly developed
causality in variance test and impulse response functions to daily data from 01 January
1986 to 21 March 2011. In order to identify the impact of the food price crisis, the data
are divided into two sub-periods: the pre-crisis period (01 January 1986 to 31 December
2005) and the post-crisis period (01 January 2006–21 March 2011). The variance
causality test shows that while there is no risk transmission between oil and agricultural
commodity markets in the pre-crisis period, oil market volatility spills on the agricultural
markets —with the exception of sugar — in the post-crisis period. The impulse response
analysis also indicates that a shock to oil price volatility is transmitted to agricultural
markets only in the post-crisis period. This paper thereby shows that the dynamics of
volatility transmission changes significantly following the food price crisis. After the
crisis, risk transmission emerges as another dimension of the dynamic interrelationships
between energy and agricultural markets
Shahidur Rashid
Improving price discovery, linking smallholders to markets, reducing transactions costs,
and increasing agricultural export earnings are some of the popular claims about benefits
of Agricultural Commodity Exchanges (ACX) in developing countries. Based on the case
studies, and a review of available literature, this paper examines the validity of these
popular claims and associated public policies. Our analysis suggests that most of these

27
popular claims cannot be supported by empirical evidence. While agricultural commodity
exchanges have been successful in emerging countries, they have either failed or remain
in operation with government or donor supports. Underlying reasons for the failures,
considerations for future investments in such institutions, and implications for
alternatives to centralized exchanges are discussed.
Harold MauriceObstfeld
This paper evaluates the social gains from international risk sharing in some simple
general-equilibrium models with output uncertainty. A simulation model calibrated to
selected moments of U.S. and Japanese data estimates the incremental loss from a ban on
international portfolio diversification to be on the order of 0.20 percent of output per
year. Even the theoretical gains from asset trade may disappear under alternative sets of
assumptions on preferences and technology. The paper argues that the small magnitude
of potential trade gains may help explain the apparently inconsistent findings of empirical
studies on the degree of international capital mobility.
Xue-ZhongHeaFrank H.Westerh

We develop a behavioral commodity market model with consumers, producers and

heterogeneous speculators to characterize the nature of commodity price fluctuations and
to explore the effectiveness of price stabilization schemes. Within our model, we analyze
how nonlinear interactions between market participants can create either bull or bear
markets, or irregular price fluctuations between bull and bear markets through a (global)
homoclinic bifurcation. Both the imposition of a bottoming price level (to support
producers) and a topping price level (to protect consumers) can eliminate such
homoclinic bifurcations and hence reduce market price volatility. However, simple policy
rules, such as price limiters, may have unexpected consequences in a complex
environment: a minimum price level decreases the average price while a maximum price
limit increases the average price. In addition, price limiters influence the price dynamics
in an intricate way and may cause volatility clustering. Compare the accuracy, efficiency
and stability of different numerical strategies for computing approximate solutions to the
nonlinear rational expectations commodity market model. I find that polynomial and
spline function collocation methods are superior to the space discretization, linearization
and least squares curve-fitting methods that have been preferred by economists in the

28
past.
Primary Commodity Prices, Manufactured Goods Prices, and the Terms of Trade
of Developing Countries: What the Long Run Shows
The authors revisit in this article the empirical foundation of the alleged secular decline in
the prices of primary commodities relative to those of manufactures. They use a newly
constructed index of commodity prices and two modified indexes of manufactured goods
prices, and find that from 1900 to 1986 the relative prices of all primary commodities fell
on trend by 0.5 percent a year and those of nonfuel primary commodities by 0.6 percent a
year. They thus confirm the sign, but not the magnitude, of the trend implicit in the work
of Prebisch. But even the more limited secular decline shown by their relative price
indexes may be magnified by an incomplete account of quality improvements in
manufactures. They then show that the evolution of the terms of trade of nonfuel primary
commodities is not the same as that of the net barter terms of trade of non-oil-exporting
developing countries. Finally, they find that despite the decline that has probably
occurred during the current century in the terms of trade of nonfuel primary commodities,
the purchasing power
Raymond M. Leuthold, Editor
In 1970 the Chicago Mercantile Exchange (CME) instituted Fellowships in Futures
program designed to provide opportunities for members of the academic community to
study commodity futures markets. There are five categories in the program — the
Graduate Student Research Fellowships, the Ph.D. Dissertation Fellowships, the Faculty
Research Fellowships, the Visiting Professor Fellowships, and the Graduate Student
Summer Intern Fellowships. More than $100,000 has now been disbursed through this
program, allowing many scholars to conduct empirical commodity futures-market
research. This volume contains selected reports, not previously readily available, from the
Faculty Research Fellowships category of the program. It is important that these papers
be drawn to the attention of scholars and analysts as futures-market research tends to
build upon itself. Most of the papers state and empirically test basic hypotheses relating
to commodity futures markets. The empirical tests are conducted on those commodities
traded on the Chicago Mercantile Exchange, either livestock or foreign currencies. The
studies vary widely in sophistication, technique, theoretical modeling, quality, and

29
results, ranging from rewritten dissertation chapters to extension-type material for firm
managers or traders. Most of diese papers and fellowship requirements were completed
prior to the task of organizing them into this volume, so they are printed here with only
minor editing for consistency. No attempt was made to return manuscripts to authors for
revision and many of the papers have never been subjected to peer review.
However, the quality of these papers is similar to much of the research on futures markets
currently being conducted and published.

30
 CHAPTER III

RESEARCH METHODOLOGY

31
3.1 Research Methodology:

Methodology states that how the research studies should be undertaken. This includes the
design specifications, sources of data, methods of primary data collection, methods used
for collecting secondary data etc. Mainly secondary data has been used for the study.
Secondary data consists of collecting information from the various financial sites. It
includes the records and reports of research experts. For analysis and interpretation
statistical tools are used.

In this study Beta is used for calculating Risk and Return of commodity futures.

Type of Data:

Secondary Data:

Mainly secondary data has been used for the study.

Secondary data has been used for the research that has been collected from

Financial websites,

MCX websites,

Companies’ websites,

Reserch Journals and Books.

Sample Design:

NCDEX and MCX are the India’s the two major exchanges for commodity trading and as
many as more than 55 commodities are listed.

Tools used for Analysis:

BETA is used for analysis by using statistical tools.

Each product has been analyzed and the results tabulated, therein are presented the
evaluation of the same has been given under the caption ‘Interpretation

32
Rate of return = (closing rate−opening rate)/(opening rate)*100

Beta = n ∑ xy−¿ ¿¿

Stock price return(Y) = (closing-opening) /

(opening)*100

Market return(X) = (closing-opening) / (opening)*100(of index price)

N=Number of days

Sample of the Study:

a) Bullions (Gold, Silver)

b) Metals (Zinc, Lead)

c) Energy (Crude oil, Natural Gas)

Sources of Data:

The required information or data collected from the stock brokers and major exchanges
i.e. MCXINDIA Websites and etc.

The spot prices of commodity were collected from for one month from websites.

The secondary data were the basis for the study.

Period of Study:

The study has been conducted for 30 days (May 1st 2019 to May 31st 2019) about volatility
of several commodities traded in Goodwill Comtrades Pvt. Ltd with MCX because i have
done trading for same month.

33
 CHAPTER V

DATA ANALYSIS AND INTERPRETATION

34
Data Analysis & Interpretation:

For the purpose of the study, only secondary data are used. In relation to the study of
secondary data was collected from different exchange websites such as MCXINDIA etc.
The main data has been compiled to cover all aspects of the study.

For the purpose of data analysis and interpretation the following commodities have been
chosen:-

(a)Gold

(b)Silver

(c)Crude oil

(d)Natural gas

(e)Zinc

(f)Lead

Analysis of data done through selection of commodities with respect to the

metal index and calculated the rate of return and beta values of commodities.

Calculations of Gold Futures:

35
 Table - 4.1
Showing the Calculation of Gold and Metal Index

Date Open Close Returns(y) Open Close Returns(X) XY Y2 X2

01-May- 31740.0
19 31713.00 0 0.0851386 5241.75 5182.79 1.12482 -0.09576518 0.00724858 1.265209
02-May- 31345.0
19 31681.00 0 -1.0605726 5179.40 5139.73 -0.7659188 0.812312514 1.1248142 0.586632
03-May- 31447.0
19 31331.00 0 0.3702403 5142.69 5162.61 0.38734592 0.143411085 0.13707791 0.150037
06-May- 31563.0
19 31500.00 0 0.2 5165.67 5170.34 0.09040454 0.018080907 0.04 0.008173
07-May- 31729.0
19 31585.00 0 0.4559126 5168.14 5159.18 -0.1733699 -0.07904153 0.20785631 0.030057
08-May- 31685.0
19 31750.00 0 0.2047244 5163.22 5145.52 0.3428093 0.070181438 0.04191208 0.117518
09-May- 31916.0
19 31713.00 0 0.640116 5143.81 5160.55 0.3254397 0.208319174 0.40974855 0.105911
10-May- 31904.0
19 31906.00 0 -0.0062684 5165.23 5161.90 -0.0644695 0.000404122 3.9293E-05 0.004156
13-May- 32498.0
19 31987.00 0 1.597524 5161.33 5176.55 0.29488523 0.471086235 2.55208291 0.086957
14-May- 32241.0
19 32450.00 0 -0.6440678 5173.87 5175.76 0.03652972 -0.02352761 0.41482333 0.001334
15-May- 32259.0
19 32320.00 0 -0.1887376 5178.99 5207.00 0.54083904 -0.10207668 0.03562189 0.292507
16-May- 31976.0
19 32162.00 0 -0.5783222 5219.15 5200.20 -0.3630859 0.209980677 0.33445662 0.131831
17-May- 31791.0
19 31981.00 0 -0.5941027 5215.96 5184.73 -0.5987393 0.355712637 0.35295808 0.358489
20-May- 31537.0
19 31679.00 0 -0.4482465 5199.74 5141.89 -1.1125556 0.498699136 0.2009249 1.23778
21-May- 31416.0
19 31480.00 0 -0.2033037 5159.92 5152.11 -0.1513589 0.030771829 0.04133239 0.02291
22-May- 31422.0
19 31440.00 0 -0.0572519 5168.64 5141.22 -0.5305071 0.030372541 0.00327778 0.281438
23-May- 31667.0
19 31347.00 0 1.0208313 5138.68 5160.55 0.42559568 0.434461406 1.04209662 0.181132

24-May- 31530.0
19 31646.00 0 -0.366555 5160.66 5188.85 0.54624796 -0.20022993 0.13436258 0.298387
27 31613.0
May19 31555.00 0 0.1838061 5190.41 5209.91 0.37569286 0.069054623 0.03378467 0.141145
28-May- 31540.0
19 31621.00 0 -0.2561589 5208.94 5169.99 -0.7477529 0.191543547 0.06561737 0.559134
29-May- 31733.0
19 31634.00 0 0.3129544 5169.63 5178.91 0.17950995 0.05617843 0.09794047 0.032224
30-May- 31809.0
19 31560.00 0 0.7889734 5176.62 5179.19 0.04964629 0.039169605 0.622479 0.002465

31-May- 31821.00 32098.0 0.8704943 5175.77 5173.11 -0.0513933 -0.04473759 0.75776037 0.002641

36
 19 0

TOTAL 1.9176793 -2.77463 3.094361388 8.6582159 5.898067

Rate of Return Calculation:

CLOSING RATE−OPENING RATE

RATE OF RETURN =
OPENING RATE
X 100

= (32908 –

= 0.8074

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n =23

=23*3.094361388-(-2.7746389)(1.9176793)/ 23*5.898067-(-2.7746389) (-2.7746389)

=0.59778851

Interpretation: Since the beta value for the gold is 0.59778851 it states that the beta
value is less than 1, thus it implies that it has less volatility. It means less risk.

Rate of Return vs Market Index of Gold:

37
 3

0 RETURNS(Y)
9 9 9 9 9 9 9 9
-1y-1 y-1 y-1 y-1 y-1 y-1 y-1 y-1 Returns(X)
a a a a a a a a
-M -M -M -M -M -M -M -M
31 -228 23 20 15 10 07 02
-3

-4

Fig 4.1.1
The above graph Shows the Rate of Return vs Market Index of Gold
Interpretation:
The Return Y blue line indicates gold.

The Return X red line indicates metal index.

Calculation of Silver Futures:

Table - 4.2
Showing the Calculation of Silver and Metal Index
Date Open Close return(Y) metal Close return(X) xy X2 Y2

38
 Open
01-May-
19 38021.00 37692.00 -0.86531 5241.75 5182.79 -1.12482 0.973315263 1.265209202 0.748764
02-May-
19 37526.00 37259.00 -0.71151 5179.40 5139.73 -0.76592 0.544956372 0.586631658 0.506242
03-May-
19 37335.00 37929.00 1.591 5142.69 5162.61 0.387346 0.616267518 0.150036863 2.531282
06-May-
19 37885.00 37897.00 0.031675 5165.67 5170.34 0.090405 0.002863546 0.00817298 0.001003
07-May- -
19 37900.00 37951.00 0.134565 5168.14 5159.18 -0.17337 0.023329461 0.030057128 0.018108
08-May-
19 37994.00 37908.00 -0.22635 5163.22 5145.52 -0.34281 0.077595417 0.117518238 0.051235
09-May-
19 37895.00 37904.00 0.02375 5143.81 5160.55 0.32544 0.007729139 0.105911 0.000564
10-May-
19 37903.00 37877.00 -0.0686 5165.23 5161.90 -0.06447 0.004422362 0.004156322 0.004705
13-May-
19 37705.00 38149.00 1.177563 5161.33 5176.55 0.294885 0.347245839 0.086957301 1.386654
14-May- -
19 38140.00 38052.00 -0.23073 5173.87 5175.76 0.03653 0.008428461 0.00133442 0.053236
15-May-
19 38084.00 38056.00 -0.07352 5178.99 5207.00 0.540839 -0.0397634 0.292506871 0.005405
16-May-
19 37985.00 37367.00 -1.62696 5219.15 5200.20 -0.36309 0.590725583 0.131831402 2.646992

17-May-
19 37352.00 37093.00 -0.6934 5215.96 5184.73 -0.59874 0.415167774 0.358488694 0.480808
20-May-
19 36960.00 36852.00 -0.29221 5199.74 5141.89 -1.11256 0.325097424 1.237780025 0.085385
21-May-
19 36830.00 36753.00 -0.20907 5159.92 5152.11 -0.15136 0.031644415 0.022909527 0.04371
22-May- -
19 36775.00 36810.00 0.095173 5168.64 5141.22 -0.53051 0.050490135 0.281437739 0.009058

23-May-
19 36600.00 37162.00 1.535519 5138.68 5160.55 0.425596 0.653510304 0.181131681 2.357819
24-May-
19 37095.00 36888.00 -0.55803 5160.66 5188.85 0.546248 -0.30482094 0.298386834 0.311394

27-May- -
19 36969.00 36944.00 -0.06762 5190.41 5209.91 0.375693 0.025405939 0.141145128 0.004573

28-May-
19 36967.00 36411.00 -1.50404 5208.94 5169.99 -0.74775 1.124653376 0.559134402 2.262149
29-May-
19 36555.00 36780.00 0.615511 5169.63 5178.91 0.17951 0.110490324 0.032223821 0.378854

30-May-
19 36555.00 36901.00 0.946519 5176.62 5179.19 0.049646 0.046991158 0.002464755 0.895898

31-May- -
19 36861.00 36923.00 0.168199 5175.77 5173.11 -0.05139 0.008644328 0.002641273 0.028291

39
 TOTAL -0.80787 -2.77464 2.551065995 5.898067266 14.81213

Rate of Return Calculation:

CLOSING RATE−OPENING RATE

RATE OF RETURN =
OPENING RATE
X 100

= (37692.0 –

= -0.86531

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n =23

= 23*2.551065995-(-2.77464)(-0.80787)/23*(7.698621297) (-2.77464) (-2.77464)

= 0.333194.

Interpretation: Since the beta value for the silver is 0.333194 it states that the beta value
is less than 1, thus it implies that it has less volatility. It means less risk.

Rate of Return vs Market Index of Silver:

40
 2

1.5

0.5

0
9 19 19 19 19 19 19 19
-0.5y/1
return(Y)
/ / / / / / /
a ay ay ay ay ay ay ay return(X)
/M /M /M /M /M /M /M /M
01 -106 09 14 17 22 27 30
-1.5

-2

-2.5

-3

Fig 4.2.1

The above graph Shows the Rate of Return vs Market Index of Silver
Interpretation:

The Return X blue line indicates silver.

The Return Y red line indicates metal index.

Calculation of Crude oil Futures:

Table 4.3
Showing the Calculation of Crude oil and Metal Index
metal return(
Date Open Close return(Y) Close xy X2 Y2
Open X)
01-May-
19 4461.00 4446.00 -0.33625 3097.58 3082.35 -0.49 0.165324 0.241743 0.113062
02-May-
19 4451.00 4301.00 -3.37003 3082.35 2991.61 -2.94 9.920887 8.666299 11.3571
03-May- 4307.00 4329.00 0.510796 2996.06 3001.86 0.19 0.098884 0.037476 0.260913

41
 19
06-May-
19 4231.00 4369.00 3.26164 3002.14 3017.71 0.52 1.691585 0.268977 10.6383
07-May-
19 4347.00 4286.00 -1.40327 3017.42 2975.65 -1.38 1.942535 1.916273 1.969157
08-May-
19 4331.00 4356.00 0.577234 2976.21 3028.15 1.75 1.007373 3.045627 0.333199
09-May-
19 4321.00 4349.00 0.647998 3007.92 3024.11 0.54 0.348782 0.289708 0.419902
10-May-
19 4368.00 4348.00 -0.45788 3035.09 3029.65 -0.18 0.082068 0.032126 0.20965
13-May-
19 4348.00 4340.00 -0.18399 3028.27 3028.88 0.02 -0.00371 0.000406 0.033853
14-May-
19 4352.00 4383.00 0.712316 3030.53 3057.12 0.88 0.624989 0.769838 0.507394
15-May-
19 4352.00 4400.00 1.102941 3057.12 3058.34 0.04 0.044015 0.001593 1.216479
16-
May19 4413.00 4450.00 0.838432 3061.39 3095.99 1.13 0.9476 1.277365 0.702968
17-May-
19 4465.00 4445.00 -0.44793 3105.75 3102.54 -0.10 0.046296 0.010683 0.20064

20-May-
19 4470.00 4400.00 -1.566 3108.83 3079.84 -0.93 1.460299 0.869566 2.452342
21-May- 4430.00 4415.00 -0.3386 3087.69 3078.85 -0.29 0.096941 0.081967 0.11465
19
22-May- 4390.00 4276.00 -2.59681 3083.08 2990.77 -2.99 7.77507 8.964538 6.743427
19

23-May- 4278.00 4036.00 -5.65685 2989.93 2854.51 -4.53 25.62102 20.51368 31.99994
19
24-May- 4070.00 4071.00 0.02457 2872.04 2875.44 0.12 0.002909 0.014014 0.000604
19
27-May- 4092.00 4132.00 0.977517 2876.23 2906.82 1.06 1.039633 1.131128 0.95554
19
28-May- 4126.00 4143.00 0.412021 2909.00 2915.67 0.23 0.094472 0.052573 0.169762
19
29-May- 4123.00 4116.00 -0.16978 2917.30 2914.84 -0.08 0.014317 0.007111 0.028825
19
30-May- 4126.00 3989.00 -3.32041 2913.78 2820.04 -3.22 10.68217 10.34991 11.0251
19
31-May- 3973.00 3775.00 -4.98364 2799.60 2676.19 -4.41 21.96853 19.43161 24.83666
19
TOTAL -15.766 -15.08 237.744 227.3937 248.5653

Rate of Return Calculation:

42
 CLOSING RATE−OPENING RATE
RATE OF RETURN =
OPENING RATE
X 100

= (4446.00

= -0.33625

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n = 23

= 23*237.744-(-15.08)(-15.766)/23*(227.3937)-[(-15.08)(-15.08)]

=1.045518

Interpretation: Since the beta value for the crude oil is 1.045518 it states that the beta
value is more than 1, thus it implies that it has high volatility. It means more risk.

Rate of Return vs Market Index of Crude oil:

43
 5

0
t e 1 9 19 19 1 9 1 9
Da ay- ay- ay- ay- ay-
M M M M M
-506- 10- 16- 22- 28-
Return Y
Return X
-10

-15

-20

Fig 4.3.1
The above graph shows the Rate of Return vs Market Index of Crude oil
Interpretation:

The Return X blue line indicates crude oil.

The Return Y red line indicates metal index.

Calculation of Natural gas Futures:

Table 4.4
Showing the Calculation of Natural gas and Metal Index
metal
Date Open Close return(Y) Close return(X) xy X2 Y2
Open
01-May-
19 187.50 187.80 0.16 2799.60 2676.19 -4.40813 -0.7053 19.43161 0.0256
02-May-
19 188.00 187.50 -0.26596 2913.78 2820.04 -3.21713 0.855619 10.34991 0.070733
03-May- 187.40 185.30 -1.1206 2917.30 2914.84 -0.08432 0.094494 0.007111 1.255739

44
 19
06-May-
19 184.40 182.40 -1.0846 2909.00 2915.67 0.229288 -0.24869 0.052573 1.176354
07-May-
19 182.10 182.30 0.10983 2876.23 2906.82 1.063545 0.116809 1.131128 0.012063
08-May-
19 183.40 186.90 1.908397 2872.04 2875.44 0.118383 0.225921 0.014014 3.641979
09-May-
19 187.90 187.90 0 2989.93 2854.51 -4.5292 0 20.51368 0
10-May-
19 187.00 188.30 0.695187 3083.08 2990.77 -2.99408 -2.08145 8.964538 0.483285
13-May-
19 189.40 190.60 0.63358 3087.69 3078.85 -0.2863 -0.18139 0.081967 0.401423
14-May-
19 191.70 192.30 0.312989 3108.83 3079.84 -0.93251 -0.29186 0.869566 0.097962
15-May-
19 192.80 190.90 -0.98548 3105.75 3102.54 -0.10336 0.101856 0.010683 0.971165
16-May-
19 190.00 190.90 0.473684 3061.39 3095.99 1.130206 0.535361 1.277365 0.224377
17-May-
19 191.20 191.40 0.104603 3057.12 3058.34 0.039907 0.004174 0.001593 0.010942
20-May-
19 190.00 192.80 1.473684 3030.53 3057.12 0.877404 1.293017 0.769838 2.171745
21-May-
19 190.80 187.80 -1.57233 3028.27 3028.88 0.020144 -0.03167 0.000406 2.472212
22-May-
19 187.80 183.10 -2.50266 3035.09 3029.65 -0.17924 0.448569 0.032126 6.263319
23-May-
19 180.80 183.30 1.382743 3007.92 3024.11 0.538246 0.744256 0.289708 1.911979
24-May-
19 184.70 182.80 -1.0287 2976.21 3028.15 1.745173 -1.79525 3.045627 1.058214
27-May-
19 185.00 182.10 -1.56757 3017.42 2975.65 -1.3843 2.169976 1.916273 2.457268
28-May-
19 183.50 182.40 -0.59946 3002.14 3017.71 0.51863 -0.3109 0.268977 0.359346
29-May-
19 183.00 187.00 2.185792 2996.06 3001.86 0.193588 0.423142 0.037476 4.777688
30-May-
19 185.40 180.30 -2.75081 3082.35 2991.61 -2.94386 8.097991 8.666299 7.56695
31-May-
19 181.00 174.10 -3.81215 3097.58 3082.35 -0.49167 1.874338 0.241743 14.53252
TOTAL -7.84981 -15.0796 118.3719 227.3937 61.61956

Rate of Return Calculation:

CLOSING
45 RATE−OPENING RATE
RATE OF RETURN =
OPENING RATE
X 100
 =187.80-187.50/187.50*100

=0.16

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n = 23

= 23*118.3937-(-15.0796)(118.3719)/23*(227.3937)-[(-7.84981)(-7.84981)]

= 0.520559

Interpretation: Since the beta value for the natural gas is 0.520559 it states that the beta
value is less than 1, thus it implies that it has less volatility. It means less risk.

Rate of Return vs Market Index of Natural gas:

46
 4
2
0
e 9 9 9 9 9 9 9
-2Dat y-1 y-1 y-1 y-1 y-1 y-1 y-1
a a a a a a a
M M M M M M M
-403- 08- 13- 16- 21- 24- 29-
Return Y
-6
RETURN X
-8
-10
-12
-14
-16

Fig 4.4.1

The above graph shows the Rate of Return vs Market Index of natural gas
Interpretation:

The Return X blue line indicates natural gas.

The Return Y red line indicates metal index.

Calculation of Lead Futures:

Table 4.5
Showing the Calculation of Lead and Metal Index
Date Open Close return(Y) metal Close return(X) xy
X2 Y2
Open
01-
May-19 152.10 148.00 -2.6956 5241.75 5182.79 -1.12482 3.032046 1.265209 7.266232
02-
May-19 147.65 147.80 0.101592 5179.40 5139.73 -0.76592 -0.07781 0.586632 0.010321

47
03-
May-19 148.00 147.85 -0.10135 5142.69 5162.61 0.387346 -0.03926 0.150037 0.010272
06-
May-19 147.00 147.70 0.47619 5165.67 5170.34 0.090405 0.04305 0.008173 0.226757
07-
May-19 148.35 151.10 1.853724 5168.14 5159.18 -0.17337 -0.32138 0.030057 3.436294
08-
May-19 151.20 152.20 0.661376 5163.22 5145.52 -0.34281 -0.22673 0.117518 0.437418
09-
May-19 152.00 151.30 -0.46053 5143.81 5160.55 0.32544 -0.14987 0.105911 0.212084
10-
May-19 151.05 150.00 -0.69513 5165.23 5161.90 -0.06447 0.044815 0.004156 0.483211
13-
May-19 148.85 148.90 0.033591 5161.33 5176.55 0.294885 0.009905 0.086957 0.001128
14-
May-19 149.25 148.95 -0.20101 5173.87 5175.76 0.03653 -0.00734 0.001334 0.040403
15-
May-19 149.00 148.60 -0.26846 5178.99 5207.00 0.540839 -0.14519 0.292507 0.072069
16-
May-19 148.55 149.75 0.807809 5219.15 5200.20 -0.36309 -0.2933 0.131831 0.652555
17-
May-19 149.45 149.65 0.133824 5215.96 5184.73 -0.59874 -0.08013 0.358489 0.017909
20-
May-19 148.05 147.30 -0.50659 5199.74 5141.89 -1.11256 0.563605 1.23778 0.256629
21-
May-19 148.15 147.80 -0.23625 5159.92 5152.11 -0.15136 0.035758 0.02291 0.055813

22-
May-19 147.95 147.70 -0.16898 5168.64 5141.22 -0.53051 0.089643 0.281438 0.028553
2May-
19 147.00 148.90 1.292517 5138.68 5160.55 0.425596 0.55009 0.181132 1.6706
24-
May-19 149.35 149.85 0.334784 5160.66 5188.85 0.546248 0.182875 0.298387 0.11208
27-
May-19 149.70 150.90 0.801603 5190.41 5209.91 0.375693 0.301157 0.141145 0.642568
28-
May-19 150.00 150.15 0.1 5208.94 5169.99 -0.74775 -0.07478 0.559134 0.01
29-
May-19 150.00 150.70 0.466667 5169.63 5178.91 0.17951 0.083771 0.032224 0.217778
30-
May-19 150.40 151.40 0.664894 5176.62 5179.19 0.049646 0.03301 0.002465 0.442084
31-
May-19 151.15 150.00 -0.76083 5175.77 5173.11 -0.05139 0.039102 0.002641 0.578868
TOTA 1.63386 -2.77464 3.593038 5.898067 16.88163
L

48
Rate of Return Calculation:

CLOSING RATE−OPENING RATE

RATE OF RETURN =
OPENING RATE
X 100

=148.00-

= -2.6956

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n = 23

= 23*(3.593038)-(-2.77464) (1.63386)/23(5.898067)-[(-2.77464) (-2.77464)]

= 0.68127

Interpretation: Since the beta value for the lead is 0.68127 it states that the beta value is
less than 1, thus it implies that it has less volatility. It means less risk.

Rate of Return vs Market Index of Lead:

49
 3

0
Return Y
9 9 9 9 9 9 9 9
y / 1 y/ 1 y/1 y/ 1 y/ 1 y/1 y/1 y/1 Return X
a
-1 a a a a a a a
/M /M /M /M /M /M /M /M
0 1 0 6 09 1 4 1 7 22 27 30
-2

-3

-4

Fig 4.5.1

The above graph shows the Rate of Return vs Market Index of Lead

Interpretation:

The Return X blue line indicates lead.

The Return Y red line indicates metal index.

Calculation of Zinc Futures:

Table 4.6
Showing the Calculation of Zinc and Metal Index
Date Open Close return(Y) metal Close return(X) xy
X2 Y2
Open
01-May-
19 221.25 218.15 -1.40113 5241.75 5182.79 -1.12482 1.576012 1.265209 1.963165
02-May-
19 217.75 216.10 -0.75775 5179.40 5139.73 -0.76592 0.580375 0.586632 0.574185

50
 03-May-
19 216.80 217.65 0.392066 5142.69 5162.61 0.387346 0.151865 0.150037 0.153716
06-May-
19 216.00 216.85 0.393519 5165.67 5170.34 0.090405 0.035576 0.008173 0.154857
07-May-
19 215.60 214.30 -0.60297 5168.14 5159.18 -0.17337 0.104537 0.030057 0.363571
08-May-
19 214.65 212.05 -1.21127 5163.22 5145.52 -0.34281 0.415236 0.117518 1.467185
09-May-
19 211.40 212.20 0.37843 5143.81 5160.55 0.32544 0.123156 0.105911 0.143209
10-May-
19 212.40 212.85 0.211864 5165.23 5161.90 -0.06447 -0.01366 0.004156 0.044887
13-May-
19 212.15 210.20 -0.91916 5161.33 5176.55 0.294885 -0.27105 0.086957 0.844857
14-May-
19 210.45 210.75 0.142552 5173.87 5175.76 0.03653 0.005207 0.001334 0.020321
15-May-
19 211.75 213.95 1.038961 5178.99 5207.00 0.540839 0.561911 0.292507 1.07944
16-May-
19 213.45 213.80 0.163973 5219.15 5200.20 -0.36309 -0.05954 0.131831 0.026887
17-May-
19 212.70 211.85 -0.39962 5215.96 5184.73 -0.59874 0.239271 0.358489 0.159699
20-May-
19 209.00 208.85 -0.07177 5199.74 5141.89 -1.11256 0.079848 1.23778 0.005151
21-May-
19 209.50 209.85 0.167064 5159.92 5152.11 -0.15136 -0.02529 0.02291 0.027911

22-May-
19 209.55 207.65 -0.9067 5168.64 5141.22 -0.53051 0.481013 0.281438 0.822114
23-May-
19 206.75 206.75 0 5138.68 5160.55 0.425596 0 0.181132 0
24-May-
19 206.65 209.70 1.475925 5160.66 5188.85 0.546248 0.806221 0.298387 2.178356
27-May-
19 210.00 212.20 1.047619 5190.41 5209.91 0.375693 0.393583 0.141145 1.097506
28-May-
19 211.45 209.45 -0.94585 5208.94 5169.99 -0.74775 0.707262 0.559134 0.894632
29-May-
19 209.30 209.35 0.023889 5169.63 5178.91 0.17951 0.004288 0.032224 0.000571
30-May- 209.55 210.15 0.286328 5176.62 5179.19 0.049646 0.014215 0.002465 0.081984
19
31-May- 208.75 206.35 -1.1497 5175.77 5173.11 -0.05139 0.059087 0.002641 1.321811
19
TOTAL -2.64374 -2.77464 5.969135 5.898067 13.42601

Rate of Return Calculation:

51
 CLOSING RATE−OPENING RATE
RATE OF RETURN =
OPENING RATE
X 100

= (218.15-

= -1.40113

Beta Calculation:

Beta = n ∑ xy−¿ ¿¿

n = 23

= 23*5.969135-(-2.77464) (-2.64374) / 23(5.898067)-[(-2.77464) (-2.77464)]

= 1.015613

Interpretation: Since the beta value for the zinc is 1.015613 it states that the beta value
is more than 1, thus it implies that it has high volatility. It means more risk.

Rate of Return vs Market Index of Zinc:

52
 2
1.5
1
0.5
0
e 9 9 9 9 9 9 9 Return Y
-0.5Dat y-1 y-1 y-1 y-1 y-1 y-1 y-1
a a a a a a a Return X
-13 -M 8-M 3-M 6-M 1-M 4-M 9-M
0 0 1 1 2 2 2
-1.5
-2
-2.5
-3

Fig 4.6.1
The above graph shows the Rate of Return vs Market Index of Zinc

Interpretation:

The Return X blue line indicates zinc.

The Return Y red line indicates metal index.

Analysis of Beta Values:

Beta value of Gold = 0.059778851

Beta value of Silver = 0.333194

Beta value of Crude Oil = 1.045518

Beta value of Natural Gas = 0.520559

Beta value of Lead = 0.68127

53
Beta value of Zinc = 1.015613

BETA VALUE ANALYSIS

1.2
1.05 1.02
1

0.8 0.68
0.6
Beta

0.6 0.52

0.4 0.33

0.2

0
Gold Silver Crude Oil Natural Gas Lead Zinc
Commodities

Figure 4.7
Beta values analysis
Interpretation: Here it can be seen that the value of Silver is low when compared to all
other commodities, thus it implies that it has less volatility and it is considered to be less
risky, the price variation and return is comparatively low among all the other
commodities. It can be seen that the value of crude oil and zinc is high when compared to
all other commodities, thus it implies that it has more volatility and it is considered to be
high risky, the price variation and return is comparatively high among all the other
commodities.

54
 CHAPTER V

FINDINGS, CONCLUSIONS AND SUGGESTIONS

Findings:

1) To identify the specified product in the commodities market which was

performing a leading position when compared other products chosen.

1. The beta value of Gold less than 1, it is considered to be less risky, the price variation
and return is comparatively low.

2. The beta value of Silver less than 1, it is considered to be less risky, the price variation
and return is comparatively low.

3. The beta value of Crude oil more than 1, it is considered to be high risky, the price
variation and return is comparatively high.

55
4. The beta value of Natural gas less than 1, it is considered to be less risky, the price
variation and return is comparatively low.

5. The beta value of Zinc more than 1, it is considered to be high risky, the price variation
and return is comparatively high.

6. The beta value of lead less than 1, it is considered to be less risky, the price variation
and return is comparatively less.

CRUDE OIL and ZINC is performing the leading position in Market

2) To study the volatility and reasons of fluctuations in the commodities.

 Commodity price fluctuation main reasons are

a) Increase in money supply

b) Inflation

c) Government polices

3) To analyse the risk and related factors in Commodity market (6 products)

 Price of a commodity is dependent on its demand and supply of that commodity

in the market as well as global market.
 The investor should know the market idea, within a range he has to play. In spot
market for commodity, the investors have to understand price movement and in
future market it is difficult to play without knowing the spot market.
 If investor is ready to take risk, invest in this these commodities if not invest in
other commodities.
Limitations of the Study:

 The project does not cover the details of other derivatives (cash & currency

56
 derivatives), it only studies the commodity derivatives
 Out of many other commodities (silver, copper, natural gas etc.) being traded on
MCX only gold and crude oil derivatives are studied in detail
 The data collected is confined to a specified period of time
 Due to non-availability of sufficient time one month data was taken for analysis
 The data are available in the date of the expiry of the contract
 Most of the information gathered for the study is from Internet and magazines
etc.that is in the printed form. Hence, the level of accuracy cannot be expressed to
be 100 percent.

Suggestions:
 Better analytical tools should be used to make better predictions.
 Client should be advised not to make their opinion while negotiating, since a
wrong position can be very risky.
 The investor must carefully study the market and the risks involved before
investing.
 The investor must understand the commodity futures contract and the obligations
before entering into such contracts.
 Given that commodity futures are a new concept, greater awareness should be
created by properly marketing this investment instrument. People who have

57
 already invested in commodity futures, to recommend their friends and family
who also invest here, can create this awareness.

Conclusion:
 The commodity future is the part of derivatives. The commodity futures markets
are experiencing tremendous growth in the recent past. This can be emphasized
by the fact that the trading volume of most commodities is increasing.
 There are many types of risks involved in commodity futures trading but
commodity futures are less risky than equity futures but it is highly volatile. The
various risk management techniques can be used to minimize the risk, and hence
forth from the different price movements.
 Commodity futures trading included the intermediary and trading participants
likes brokers who make use of the various technical analysis tools in order to
make predictions of the price movement’s they also take into consideration the
fundamental analysis. Thus with the help of the various analysis tools, efficient
price predictions can be made, where the investors in commodity futures can
benefit from the price movements.
 If investor is ready to take high risk and high return invest in zinc and crude oil if
not invest in other commodities.

Bibliography:

Books:

 Gupta S.L. (2005) Financial Derivatives (theory, concepts and Problems), PHI
Learning Pvt. Ltd.
Websites:

 Commodity derivative market. Available from,

www.slideshare.net/manishnandal1/commodity-derivatives-market

 Commodity trading. Available from

http://www.bnrsecurities.com/Static/CommodityTrading.aspx

58
  Gold prices historical data . Available from
www.investing.com/commodities/gold-historical-data

 Inflation rate data. Available from www.inflation.eu/inflation-

rates/...inflation/cpi-inflation-india-2013.aspx

Journal articles:
 Colin A. Carter, “commodity futures markets: a survey”, Australian Journal of
Agricultural and Resource Economics, volume 43 ,issue 2, 18 December 2002,
pp. 209- 247
 Gray, Roger W., and David J.S. Rutledge. “The Economics of Commodity
Futures Markets: A Survey.” Review of Marketing and Agricultural Economics
39(1971):57-108.
 Tomek, William G, and R. M. Leuthold. “Developments in the Livestock Futures
Literature.” in Proceedings Livestock Futures Research Symposium, eds. R. M.
Leuthold & P. Dixon. Chicago Mercantile Exchange, 1980, pp.
39-67.

 Working, Holbrook. “Review of Commodity Exchanges and Futures Trading.”

American Economic Review 39(1949):1043-1045.

 “The Self-Regulation of Commodity Exchanges: The Case of Market

Manipulation.” The Journal of Law and Economics, April, 1995.

World Wide Web:

 www.finance.yahoo.com

 www.moneycontrol.com

 www.mcxindia.com

 www.sebi.in

 www.gwcindia.in

59
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commodity markets’ volatility. Energy Economics, 37, 16–28.
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‘Market of One’? CFTC Working Paper.
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futures and traditional asset markets. J. Altern. Invest. 12 (3), 61–75.

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 Doyle, E., Hill, J., Jack, I., 2007. Growth in commodity investment: risk and
challenges for commodity market participants. Financial Services Authority
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61