TYBMS SEM 5 Finance: Commodity & Derivatives Market (Q.P. November 2022 with Solution)

Paper/Subject Code: 46006/Finance: Commodity & Derivatives Market

TYBMS SEM 5 

Finance: 

Commodity & Derivatives Market 

(Q.P. November 2022 with Solution)

1. All questions are compulsory. (Subject to internal Choice)

2. Figures to the right indicate full marks.

3. Use of non-programmable calculator, is allowed and mobile phones are not allowed. 

4. Support your answers with diagrams/illustrations, wherever necessary

Q1) A Choose the correct alternative (Any 8 out of 10)                    (8)

1 A contract between a buyer and a seller entered into today regarding a transaction to be fulfilled at a future point in time is called ________. 

A) Fixed contract 

B) Derivative contract

C) Forward contract

D) Future contract

2 Speculators who neither buy nor sell securities in the market but still trade on them are called _________.

A) Wolves

B) Stags

C) Bears

D) Mice

3. An option exercised at the time of maturity it is termed as ________

A) American Option

B) European option

C) Call options

D) South American option 

4. Financial ________ are mainly used for hedging risk.

A) Derivatives 

B) Speculators 

C) Investors 

D) Stacks

5. Elimination of riskless profit opportunities in the futures market is ________.

A) diversification 

B) Arbitrage, 

C) Speculation 

D) Hedging.

6. An option allowing the owner to sell an asset at a future date is a __________.

A) Put option 

B) Call option 

C) Forward option

D) Future contract

7. An option holder is said to take a _________ position.

A) Long 

B) medium

C) short

D) close

8. _______ order is used to limit loss on a trade.

A) Immediate or cancel 

B) Stop loss

C) Daily

D) Formal

9. _________ clearing member is not a trading member. 

A) Self 

B) Professional

C) Amateur

D) Expert

10 For liquid securities, the VaR margins are based on the _________ of the Security. 

A) volatility

B) returns

C) liquidity

D) exposure limit

B State whether True or False (any 7 out of 10)                (7)

1 Both parties have specified obligation under derivative contract.

Ans: True

2 Futures are traded on OTC.

Ans: False

3. If the price of the underlying moves according to the speculators expectation they make small profits.

Ans: False

4. Index options have index as underlying.

Ans: True

5. Derivatives are mostly primary market instruments.

Ans: False

6. Bid price is the price the buyer is willing to pay.

Ans: True

7 Under calendar spread we buy options with different expiry at the same strike price.

Ans: True

8 Higher volatility in price of underlying asset will lead to higher option premium.

Ans: True

9 Monte Carlo Method take a lot of computational power and hence longer tie to estimate results.

Ans: True

10 The National Securities Clearing Corporation Ltd. (NSCCL) assumes the counterparty risk of each member and guarantees financial settlement.

Ans: True

Q2 A Discuss the Participants in derivative market        (08)

Participants in the derivative market can be categorized into four main groups based on their trading objectives and risk appetite:

1. Hedgers

• Objective: Reduce or eliminate price risk associated with their underlying assets.

• Participants: Businesses, farmers, exporters/importers, and financial institutions.

• Example: A wheat farmer hedges against price drops by selling wheat futures contracts.

2. Speculators

• Objective: Profit from price fluctuations in the derivative market by taking calculated risks.

• Participants: Traders, hedge funds, and high-net-worth individuals.

• Example: A trader buys call options on a stock expecting the price to rise before expiration.

3. Arbitrageurs

• Objective: Exploit price differences between markets to make risk-free profits.

• Participants: Institutional investors, hedge funds, and professional traders.

• Example: Buying a stock in one market at a lower price and simultaneously selling it in another market at a higher price.

4. Margin Traders (Market Makers)

• Objective: Provide liquidity to the market by constantly quoting buy and sell prices.

• Participants: Financial institutions, brokerage firms, and proprietary trading firms.

• Example: A market maker buys and sells options contracts to ensure continuous trading.

Q2 B What is Commodity Market? Explain the reasons for investing in commodities.    (07) 

A commodity market is a marketplace where raw materials or primary goods are bought, sold, and traded. These commodities can be either physical (spot market) or derivative contracts (futures & options) traded on recognized exchanges.

In India, major commodity exchanges include:

• Multi Commodity Exchange (MCX) – Focuses on metals, energy, and agricultural commodities.

• National Commodity & Derivatives Exchange (NCDEX) – Primarily for agricultural products.

Types of Commodities Traded

1. Agricultural Commodities – Wheat, cotton, soybean, coffee, sugar, etc.

2. Metals – Gold, silver, copper, aluminum, etc.

3. Energy – Crude oil, natural gas, coal, etc.

4. Livestock – Live cattle, lean hogs, etc. (More common in global markets).

Reasons for Investing in Commodities

1. Portfolio Diversification

• Commodities have low correlation with stocks and bonds.

• Helps reduce overall investment risk during market downturns.

Example: When stock markets crash, gold prices often rise, balancing losses.

2. Inflation Hedge

• Commodity prices increase with inflation, preserving purchasing power.

• Unlike cash, commodities retain value during inflationary periods.

Example: During inflation, crude oil and agricultural product prices usually rise.

3. High Return Potential

• Commodities experience strong price movements due to supply-demand shifts.

• Speculators and traders can profit from short-term price fluctuations.

Example: Crude oil prices surged due to geopolitical tensions, giving traders opportunities.

4. Hedging Against Risks

• Businesses and producers use commodities to hedge against price volatility.

• Farmers, oil companies, and metal industries use futures contracts to lock in prices.

Example: A wheat farmer sells futures contracts to secure a fixed price before harvest.

5. Leverage in Trading

• Commodity futures allow traders to take large positions with a small margin.

• This amplifies potential profits (but also increases risks).

Example: A trader can control ₹10 lakh worth of gold with a margin of just ₹1 lakh.

6. Growing Global Demand

• As economies develop, demand for metals, energy, and food rises.

• Long-term investors benefit from commodity price appreciation.

Example: Electric vehicle growth has increased demand for lithium and copper.

OR

Q.2 C Distinguish between Forward & Futures

	Forward Contract	Future Contract
Definition	A private agreement between two parties to buy or sell an asset at a future date for a predetermined price.	A standardized contract traded on an exchange to buy or sell an asset at a future date for a predetermined price.
Trading Venue	Over-the-Counter (OTC)	Exchange-traded
Standardization	Customized contract terms (quantity, price, expiration date, etc.)	Highly standardized with fixed contract sizes, expiration dates, and specifications.
Counterparty Risk	High, as the contract is private and not regulated by an exchange.	Low, as clearing houses act as intermediaries and guarantee the trade.
Liquidity	Low, as contracts are tailor-made and not easily tradable.	High, as contracts are standardized and actively traded on exchanges.
Margin Requirement	No margin requirement; settlement occurs at maturity.	Requires margin deposits and daily mark-to-market settlements.
Settlement	Settled at the contract’s expiration (physical or cash settlement).	Marked-to-market daily, meaning profits/losses are settled daily.
Flexibility	More flexible in terms of contract terms and conditions.	Less flexible due to standardization.
Example	A farmer agrees with a mill to sell 1000 bushels of wheat at $5 per bushel in 3 months.	A trader buys an oil futures contract on the Chicago Mercantile Exchange (CME) with set expiry and contract size.

Q2 D Write note on different types of derivatives traded in India

Derivatives are financial instruments whose value is derived from an underlying asset, such as stocks, indices, commodities, currencies, or interest rates. In India, derivatives trading is regulated by the Securities and Exchange Board of India (SEBI) and takes place on exchanges like the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). The major types of derivatives traded in India include:

1. Futures

Futures contracts are standardized agreements to buy or sell an asset at a predetermined price on a specified future date. They are traded on exchanges and are subject to daily settlement.

Types of Futures in India:

• Stock Futures – Based on individual stocks (e.g., Reliance, TCS).

• Index Futures – Based on stock indices (e.g., Nifty 50, Bank Nifty).

• Commodity Futures – Based on commodities like gold, silver, crude oil, and agricultural products (traded on MCX and NCDEX).

• Currency Futures – Based on currency pairs like USD/INR, EUR/INR (traded on NSE).

• Interest Rate Futures (IRF) – Based on government securities and interest rates.

2. Options

Options give the holder the right, but not the obligation, to buy (Call Option) or sell (Put Option) an asset at a predetermined price before or at expiration.

Types of Options in India:

• Stock Options – Available on major stocks like Infosys, HDFC Bank.

• Index Options – Based on indices (e.g., Nifty 50, Bank Nifty).

• Currency Options – Options on currency pairs (e.g., USD/INR, EUR/INR).

• Commodity Options – Available on commodities like gold, crude oil.

📌 Example: A trader buys a Nifty 50 Call Option at a strike price of 18,000. If Nifty moves above 18,000, they can exercise the option to buy at the lower price.

3. Swaps (Over-the-Counter - OTC)

Swaps are agreements between two parties to exchange cash flows based on predefined terms. In India, swaps are traded over the counter (OTC) and are mainly used by financial institutions.

Common Swaps in India:

• Interest Rate Swaps (IRS) – Used by banks to hedge interest rate fluctuations.

• Currency Swaps – Used by companies to hedge currency exchange risk.

Example: A company with a rupee loan but revenue in dollars may enter a currency swap to reduce forex risk.

4. Forwards (OTC)

Forwards are customized contracts between two parties to buy or sell an asset at a future date for a fixed price. Unlike futures, they are not traded on exchanges but through over-the-counter (OTC) markets.

Types of Forwards in India:

• Currency Forwards – Used for forex hedging.

• Commodity Forwards – Used by farmers and producers to hedge against price fluctuations.

• Stock Forwards – Rarely used due to the popularity of futures contracts.

Example: An exporter expecting $1 million in 3 months may enter a USD/INR forward contract to lock in today's exchange rate and avoid currency risk.

Regulatory Framework

• SEBI regulates equity and index derivatives.

• Reserve Bank of India (RBI) oversees currency and interest rate derivatives.

• Multi Commodity Exchange (MCX) and National Commodity & Derivatives Exchange (NCDEX) handle commodity derivatives.

Q3 A Explain the following Terminologies:

i. Tick Size

Definition:

• A tick size is the smallest possible increment by which the price of a financial instrument can change.
• It essentially sets the minimum price fluctuation allowed for a particular asse

• Aspects:

• Exchange-Determined:
• Tick sizes are typically set by the exchanges where the financial instruments are traded.
• This standardization ensures order and consistency in price movements.

• Variability:
• Tick sizes can vary significantly across different asset classes (stocks, futures, options, etc.) and even within the same asset class, depending on factors like price and trading volume.

• Impact on Trading:
  • Liquidity: Smaller tick sizes can encourage more frequent trading, potentially increasing market liquidity.
  • Volatility: Tick sizes can influence market volatility. Smaller ticks can lead to more frequent price changes.
  • Trading Strategies: Traders factor in tick sizes when setting profit targets and stop-loss orders.
  • Price Discovery: Tick sizes play a role in the process of price discovery, where market forces determine the fair value of an asset.

Example:

• If a stock has a tick size of $0.01, its price can only move in increments of one cent. So, it could go from $10.00 to $10.01 or $9.99, but not to $10.005.

ii. Contract Cycle

A contract cycle refers to the lifetime of a derivative contract, from its listing to its expiration. Futures and options contracts are available for multiple expiration months, and they follow a predefined contract cycle.

Features of a Contract Cycle

1. Duration: Contracts are available for different periods, such as near-month, next-month, and far-month contracts.
2. Expiration Date: Every derivative contract has a fixed expiry date, after which it ceases to exist.
3. Renewal: Once a contract expires, a new contract for a later expiry month is introduced.
4. Rolling Over: Traders can roll over positions by closing an expiring contract and opening a new one.

Types of Contract Cycles

1. Monthly Contract Cycle (Most Common) 

• Futures and options contracts have three-month trading cycles:
  Near Month (Current Month)
  Next Month (Following Month)
  Far Month (Third Month)

Example: In April, contracts available would be:

• April (Near Month)

• May (Next Month)

• June (Far Month)
  At the end of April, a new July contract is introduced, maintaining the three-month cycle.

2. Weekly Contract Cycle 

• Used mostly in index options (Nifty, Bank Nifty, etc.)

• Shorter expiry periods provide traders with more frequent trading opportunities.
  Example: Bank Nifty options have weekly expiries every Thursday.

Contract Expiry Dates

• Stock and Index Derivatives (NSE, BSE) → Expire on the last Thursday of the month

• Commodity Futures (MCX, NYMEX, etc.) → Have different expiry rules depending on the commodity

Example: If April 25 is the last Thursday, then the April Nifty Futures contract expires on April 25, 2024.

iii. Initial Margin

Initial Margin is the minimum amount of money that a trader must deposit with the exchange to enter a futures or options contract. It acts as collateral to cover potential losses and ensures smooth trade execution.

Features of Initial Margin

Mandatory Requirement – Traders must deposit it before entering a derivative position.
Determined by Risk – Higher volatility means higher margin requirements.
Calculated by SPAN Method – Exchanges use SPAN (Standard Portfolio Analysis of Risk) or VaR (Value at Risk) models to determine the margin.
 Protects the Market – Reduces counterparty risk by ensuring traders have enough capital.

Initial Margin Calculated?

Initial Margin = Lot Size x Futures Price x Margin

 Example:

• Nifty 50 Futures Price = ₹22,000

• Lot Size = 50

• Margin Requirement = 15%

$$\text{Initial Margin }=22,000\times 50\times 15\%=₹1,65,000$$

The trader must deposit ₹1,65,000 to take a position in Nifty Futures.

Initial Margin Important

 Prevents Default – Ensures traders have funds to cover losses.
 Controls Excessive Leverage – Stops traders from taking oversized positions.
 Maintains Market Stability – Reduces systemic risk in volatile markets.

iv. Lot Size

"lot size" refers to the standardized quantity of an underlying asset that is traded in a single contract.

• Standardization:
• Exchanges standardize lot sizes to ensure uniformity in trading. This allows for efficient and transparent transactions.   
• For example, a futures contract for crude oil might represent 1,000 barrels, and that 1000 barrels is the lot size.  

• Futures Contracts:
• In futures trading, lot size dictates the amount of the commodity or financial instrument that will be delivered or received if the contract is held until expiration.
• So, if you buy one crude oil futures contract, you're agreeing to buy 1,000 barrels of oil.   

• Options Contracts:
  • In options trading, lot size determines the number of underlying assets that one options contract controls.   
  • Also in the indian markets, the Securities and Exchange Board of India(SEBI) regulates the lot sizes of derivative contracts to try to manage the amount of speculation that occurs in the markets. Recently SEBI has increased the lot sizes of many index derivative contracts   
• Considerations:
  • Risk Management: Lot size significantly impacts the risk associated with a trade. Larger lot sizes mean greater potential profits or losses.   
  • Margin Requirements: Exchanges require traders to maintain a certain amount of funds (margin) in their accounts to cover potential losses. Larger lot sizes typically result in higher margin requirements
  • Accessibility: Lot sizes can influence the accessibility of a market to different traders.
    Larger lot sizes may require more capital, limiting participation by smaller investors. 

Q3 B Elaborate the concept of Convergence

Convergence refers to the process where two values, prices, or market conditions gradually come closer together over time. This concept is widely used in finance, economics, and trading, particularly in futures markets, interest rates, and economic theories.

1. Convergence in Futures Markets

In derivatives trading, convergence describes how the price of a futures contract moves closer to the spot price of the underlying asset as the contract approaches expiration.

How It Works:

• Futures contracts are priced based on expectations of future prices.

• As the expiration date nears, uncertainty reduces, and the futures price gradually moves toward the actual market price of the asset (spot price).

• At expiration, the futures price and spot price must be equal to prevent arbitrage opportunities.

Example:

• Suppose crude oil is trading at $100 per barrel in the spot market.

• A 3-month crude oil futures contract is currently priced at $105 due to market expectations.

• As expiration approaches, the futures price will gradually converge toward $100 if market conditions remain unchanged.

🔹 Why? Arbitrageurs will exploit price differences by buying in the lower-priced market and selling in the higher-priced market until prices equalize.

2. Convergence in Interest Rates

Convergence also occurs when interest rates of two different economies or financial instruments move toward each other due to market forces, policy decisions, or economic integration.

Examples:

• Fixed vs. Floating Interest Rates: Over time, the difference between fixed and floating interest rates may converge as market conditions change.

• Developed vs. Emerging Market Rates: As developing economies grow and integrate into global markets, their interest rates may converge with those of developed economies.

3. Convergence in Economic Theories

In macroeconomics, convergence theory suggests that poorer economies will gradually catch up with wealthier economies due to capital accumulation, technology transfer, and globalization.

Types of Economic Convergence:

1. Absolute Convergence:

   • Poor countries will eventually reach the income levels of rich countries.

2. Conditional Convergence:

   • Countries with similar policies and institutions will converge at a similar growth rate.

3. Club Convergence:

   • Only economies that share common characteristics (e.g., governance, education) will converge.

Example: The European Union promotes economic convergence by aligning fiscal and monetary policies among member states.

4. Convergence in Statistical & Computational Models

• In numerical analysis and machine learning, convergence refers to the process of an algorithm or model improving over time and approaching an optimal solution.

• Example: In Gradient Descent, convergence happens when the algorithm reaches a minimum error value.

OR

Q.3 C The spot price of gold is Rs 39,000. The locker rent is Rs 500 and insurance charges are Rs 750. Interest rate on borrowed funds is 12% pa compounded on monthly basis. What will be the fair value of 3 months futures contracts?                                 (08)

Q.3 D An investor takes the position in the futures market through the following transaction:     (07)

i.  Buys 10 contracts on Hindalco Ltd at Rs 5,500 with a lot size of 200 which expires at a final settlement price of Rs 5,800. 

ii. Sells Vedanta 7 contracts at Rs 855 with a lot size of 100 which expires at Rs 825.

Determine the net profit or loss for the investor from both the positions. Also draw pay off diagrams for the respective positions.

Q.4 A What are the factors affecting the option premium?        (08)

The option premium (price of an option) is influenced by several key factors. These factors are based on the Black-Scholes model and general market conditions.

1. Underlying Asset Price (S)

• For Call Options:

  • Higher underlying price → Higher premium (option becomes more valuable).

• For Put Options:

  • Higher underlying price → Lower premium (option becomes less valuable).

2. Strike Price (K)

• The price at which the option holder can buy (call) or sell (put) the asset.

• For Call Options: Lower strike price = Higher premium.

• For Put Options: Higher strike price = Higher premium.

3. Time to Expiration (T)

• Longer time to expiry = Higher option premium (more time for favorable movements).

• Shorter time to expiry = Lower premium (less time for movement).

• Exception: Deep in-the-money European options may see lower time value.

4. Volatility (σ)

• Measures how much the underlying asset fluctuates.

• Higher volatility = Higher premium (higher chance of reaching profitability).

• Lower volatility = Lower premium (lower chance of significant movement).

5. Interest Rates (r)

• Affects the cost of carrying an option position.

• Higher interest rates → Higher call option premium (reduces present value of strike price).

• Higher interest rates → Lower put option premium (reduces attractiveness of put options).

6. Dividends (D)

• Expected dividends reduce the price of the underlying stock, affecting options:

• Higher dividends → Lower call premiums (stock price drops).

• Higher dividends → Higher put premiums (lower stock price benefits put holders).

7. Market Sentiment & Liquidity

• Higher demand = Higher premium (increased buying interest).

• Lower demand = Lower premium (less trading activity).

• Liquidity can affect bid-ask spreads, impacting trading costs.

Q/4 B What is Binomial option Pricing Model? What are its advantages and disadvantages? (07)

The Binomial Option Pricing Model is a mathematical method used to price options by modeling possible future price movements of the underlying asset over multiple time steps. It was developed by Cox, Ross, and Rubinstein in 1979.

The model assumes that, at each time step, the asset price can move up or down by a specific factor, creating a binomial tree of possible prices. By working backward from expiration, the model determines the fair value of the option.

How the Model Works

1. The time to expiration is divided into small intervals.

2. In each step, the asset price either increases (up factor "u") or decreases (down factor "d").

3. At expiration, the option's value is determined using the intrinsic value.

4. The expected value of the option is calculated at each previous step using risk-neutral probabilities.

5. The present value of the option is obtained using the risk-free rate.

Advantages of the Binomial Model

Flexibility:

• Can handle American-style options (which can be exercised early).

• Can be adapted to price exotic options and derivatives.

Intuitive and Easy to Implement:

• Uses a step-by-step approach, making it simpler to understand compared to models like Black-Scholes.

Handles Dividend Payments:

• Can incorporate discrete dividends, which some models struggle with.

More Accurate for Short-term Options:

• Works well when the number of steps is high, leading to better accuracy.

Disadvantages of the Binomial Model

Computationally Intensive:

• More steps increase accuracy but require more calculations.

Less Efficient for Long-term Options:

• Can be slow and inefficient when dealing with options with a long expiration period.

assumes a Constant Risk-Free Rate and Volatility:

• Real-world market conditions are more complex, where interest rates and volatility change over time.

Only Two Possible Price Movements per Step:

• The assumption of only an "up" or "down" movement may not fully reflect real market behavior.

OR

Q.4 C IRCTC Futures trade on NSE as one, two- and three-month's contracts. (08) Money can be borrowed at 16% pa. What will be the price of one unit of new two months futures contract on IRCTC, if no dividends are expected during the two months period assuming spot price of the IRCTC is Rs 3,7707

Q4 D Justin buys a call option of Texas Ltd at an exercise price of Rs 600 with a premium of Rs 30. Calculate the profit or loss on the option position for Justin if the spot price on expiry is as follows:, Rs 580, Rs 590, Rs 600, Rs 610, Rs 620, Rs 630, Rs 640, Rs 650, Rs 660, Rs 670. Also draw the payoff diagram for the same.   (07)

Problem Breakdown:

• Type of Option: Call option
• Exercise Price (Strike Price): Rs 600
• Premium Paid: Rs 30
• Spot Prices on Expiry: Rs 580, Rs 590, Rs 600, Rs 610, Rs 620, Rs 630, Rs 640, Rs 650, Rs 660, Rs 670

Formula for Profit or Loss on a Call Option:

For a call option, the profit or loss is calculated as:

$$\text{Profit/Loss}= \max (\text{Spot Price}-\text{Strike Price},0)-\text{Premium Paid}$$

Where:

• Spot Price is the price of the stock on the expiry date.
• Strike Price is the exercise price (Rs 600).
• Premium Paid is Rs 30 (the price Justin paid for the option).

Step-by-Step Calculation of Profit or Loss:

Let's calculate the profit or loss for each spot price.

Profit or Loss for Each Spot Price:

• Spot Price = Rs 580: Loss of Rs 30
• Spot Price = Rs 590: Loss of Rs 30
• Spot Price = Rs 600: Loss of Rs 30
• Spot Price = Rs 610: Loss of Rs 20
• Spot Price = Rs 620: Loss of Rs 10
• Spot Price = Rs 630: Break-even (0 profit/loss)
• Spot Price = Rs 640: Profit of Rs 10
• Spot Price = Rs 650: Profit of Rs 20
• Spot Price = Rs 660: Profit of Rs 30
• Spot Price = Rs 670: Profit of Rs 40

Payoff Diagram

A payoff diagram for a call option typically shows the relationship between the spot price at expiry and the profit or loss. The x-axis represents the spot price, and the y-axis represents the profit or loss.

The payoff starts at a loss equal to the premium paid (Rs 30) when the spot price is below the strike price (Rs 600), and then increases as the spot price goes above the strike price, starting to break even at Rs 630, and increasing thereafter.

Q5 A Bring out the major recommendations of Dr L. C. Gupta Committee to strengthen the regulatory framework of SEBI.        (08)

The Dr. L. C. Gupta Committee was set up by the Government of India in 1997 to review the working of the Securities and Exchange Board of India (SEBI) and to recommend measures for strengthening its regulatory framework. The committee, headed by Dr. L. C. Gupta, a former chairman of SEBI, made several important recommendations to enhance the functioning and independence of SEBI, improve investor protection, and create a more efficient and transparent securities market. Below are the major recommendations made by the committee:

1. Strengthening SEBI's Autonomy and Independence

• Independent Board: The committee recommended that SEBI should have greater operational autonomy, and its board should be independent of government control. This was to ensure that SEBI could function without political interference.
• Financial Independence: SEBI should be given the authority to generate its own revenue, thereby reducing dependence on government grants. This would enhance its financial independence.

2. Enhancement of SEBI’s Powers

• Expanded Enforcement Powers: The committee recommended granting SEBI the authority to take action against insider trading, market manipulation, and other financial crimes. It suggested giving SEBI powers similar to those of a quasi-judicial body, enabling it to impose penalties and issue orders independently.
• Regulation of Intermediaries: It emphasized strengthening the regulation of market intermediaries, such as brokers, portfolio managers, merchant bankers, and investment advisers, to ensure that they adhere to proper standards and practices.
• Power to Prosecute: The committee recommended that SEBI be given more powers to prosecute violations of securities laws, including the ability to pursue cases in courts, thereby improving investor confidence.

3. Regulation of Capital Market Products

• Introduced Mutual Fund Regulations: The committee recommended a comprehensive regulatory framework for mutual funds, including the introduction of guidelines for the establishment, operation, and management of mutual funds.
• Derivatives Market: It recommended the regulation of derivative products and futures trading in securities. This was a forward-looking recommendation as the derivatives market was still in its infancy at the time.
• Collective Investment Schemes (CIS): The committee suggested that SEBI should have the power to regulate Collective Investment Schemes (CIS) to prevent fraudulent activities by unscrupulous entities in the capital markets.

4. Investor Protection and Market Transparency

• Investor Education and Awareness: It recommended setting up programs to educate investors about the functioning of the securities markets, risks associated with investing, and their rights as investors.
• Strengthening Disclosures: The committee emphasized improving the transparency of corporate disclosures and making it mandatory for companies to provide more detailed financial statements, including the disclosure of related-party transactions and corporate governance practices.
• Investor Grievance Redressal Mechanism: It suggested establishing a more effective mechanism for addressing investor complaints and grievances, including setting up investor protection funds to compensate investors in cases of fraud or mismanagement.

5. Corporate Governance and Listing Standards

• Corporate Governance Framework: The committee recommended improving corporate governance standards in listed companies by mandating more transparency in the workings of boards of directors, promoting the concept of independent directors, and strengthening audit committees.
• Listing Agreement Reforms: The committee also recommended changes to the listing agreement, ensuring that companies listed on stock exchanges comply with disclosure and corporate governance norms.

6. Market Infrastructure and Surveillance

• Strengthening Market Surveillance: The committee recommended enhancing SEBI’s surveillance mechanisms to detect and prevent market manipulation, insider trading, and other forms of market abuse. It emphasized the need for stronger surveillance systems and the use of technology for real-time monitoring.
• Electronic Trading and Settlement: The committee recommended the introduction of electronic trading and settlement systems to improve efficiency and reduce the scope for manipulation and errors. It also suggested that the trading and settlement systems should be fully automated to eliminate the reliance on paper-based processes.

7. Regulation of Foreign Institutional Investors (FIIs)

• Clear Guidelines for FIIs: The committee recommended establishing clear guidelines for Foreign Institutional Investors (FIIs) operating in India to ensure their activities are transparent and consistent with the country’s economic interests. It also advocated for allowing more liberal FII participation in the Indian securities market.
• Foreign Direct Investment (FDI): The committee suggested that the regulatory framework for Foreign Direct Investment (FDI) should be harmonized with the regulations for FIIs to ensure smoother market operations.

8. Strengthening the Role of Stock Exchanges

• Stock Exchange Reforms: The committee suggested reforms in stock exchanges, including their demutualization, to make them more transparent and accountable. It proposed that stock exchanges should operate on commercial lines, separate from brokers and their interests.
• Greater Role for SEBI in Stock Exchange Governance: It recommended that SEBI should play a more active role in overseeing the functioning of stock exchanges, including ensuring that they adhere to fair practices and adequate transparency.

9. Regulating Primary Market (Public Issues)

• Public Issue Guidelines: The committee recommended the establishment of clearer guidelines for public offerings, ensuring that investors have adequate information before subscribing to new issues. This included making the prospectus more comprehensive and requiring companies to disclose all material information.
• Underwriting and Pricing of Issues: It emphasized the need for better regulation of the underwriting process and pricing of public issues to avoid manipulation or overpricing of securities.

10. Amendments to SEBI Act and Other Legal Frameworks

• Strengthening Legal Framework: The committee recommended amendments to the SEBI Act, Securities Contracts (Regulation) Act (SCRA), and other relevant laws to enhance SEBI’s powers, including enforcement capabilities, as well as its ability to regulate various market participants effectively.
• Settlement Mechanism: It suggested improving the dispute resolution mechanism within SEBI to facilitate faster and more effective resolution of conflicts in the market.

 B What are the different methods of calculating VaR?         (07)

Value at Risk (VaR) is a measure of the potential loss in value of a portfolio or investment over a specified time period for a given confidence interval. There are several methods for calculating VaR, each with its strengths and weaknesses. The primary methods are:

1. Historical Simulation

• Description: This method uses past historical data of returns to simulate future potential losses. It does not assume any specific distribution for the returns.
• Process:
  • Gather historical returns data for the assets in the portfolio.
  • Calculate the portfolio returns for each historical period.
  • Sort the portfolio returns from worst to best.
  • Identify the return at the desired percentile (e.g., the 5th percentile for a 95% confidence level).
• Pros:
  • Simple to understand and implement.
  • Does not require assumptions about the distribution of returns.
• Cons:
  • Relies heavily on historical data and may not predict future risks well if the market conditions change.
  • May be less effective in handling extreme events or non-normal distributions.

2. Variance-Covariance (Parametric) Method

• Description: This is a statistical approach that assumes the returns of the assets are normally distributed. It uses the mean (expected return) and the standard deviation (volatility) of the returns along with the correlation between assets.
• Process:
  • Calculate the mean return and standard deviation (volatility) of each asset in the portfolio.
  • Estimate the correlation between assets in the portfolio.
  • Use the formula to calculate the portfolio's overall standard deviation.
  • Multiply the portfolio's standard deviation by the Z-score corresponding to the desired confidence level (e.g., 1.645 for 95% confidence) to estimate the potential loss.
• Pros:
  • Computationally efficient.
  • Useful when returns are approximately normally distributed.
• Cons:
  • Assumes returns are normally distributed, which may not always be accurate, especially in the case of fat tails or extreme events.
  • It can underestimate the risk during periods of high market volatility or during "black swan" events.

3. Monte Carlo Simulation

• Description: This method involves running simulations to generate a large number of random scenarios for asset prices and returns based on assumptions about their distributions.
• Process:
  • Define the probability distributions for the returns of each asset in the portfolio.
  • Generate a large number of random paths for the asset prices based on these distributions.
  • For each simulation, calculate the portfolio's value at the end of the specified time period.
  • Sort the simulated portfolio values and identify the return at the desired percentile.
• Pros:
  • Flexible and can handle complex portfolios with various asset types and distributions.
  • Can model non-normal distributions and capture extreme events better than the parametric method.
• Cons:
  • Computationally intensive, especially for large portfolios with many assets.
  • Requires assumptions about the underlying distributions, which may not always be accurate.

4. Extreme Value Theory (EVT)

• Description: EVT focuses on modeling the tail behavior of asset returns, particularly extreme losses or "black swan" events.
• Process:
  • Fit an extreme value distribution to the tail of the historical returns data.
  • Estimate the value at risk by calculating the tail of the distribution at the desired confidence level.
• Pros:
  • Better suited for modeling extreme events or rare, severe losses.
  • Can capture risks not accounted for by the other methods, especially for portfolios with high exposure to tail risks.
• Cons:
  • Requires specialized knowledge to apply.
  • May be less reliable with insufficient data on extreme events.

5. Bootstrap Method

• Description: This non-parametric method resamples the historical data with replacement to create multiple "bootstrap" samples.
• Process:
  • Collect historical data on portfolio returns.
  • Resample the data with replacement to create a large number of simulated return paths.
  • Calculate the portfolio return for each bootstrap sample.
  • Identify the loss at the desired percentile.
• Pros:
  • Does not assume a particular distribution for returns.
  • Can handle non-normal distributions and extreme events better than the variance-covariance method.
• Cons:
  • Computationally intensive.
  • May not work well with small datasets or when historical data is not representative of future conditions.

6. Conditional VaR (CVaR) or Expected Shortfall (ES)

• Description: While not a distinct VaR calculation method, CVaR is often used alongside VaR. It measures the expected loss given that the loss has exceeded the VaR threshold (i.e., the average of the worst losses beyond the VaR cutoff).
• Process:
  • Calculate the VaR as usual.
  • For any loss greater than the VaR, calculate the average of these losses to estimate CVaR.
• Pros:
  • Provides a more comprehensive view of the tail risk by considering the severity of extreme losses.
  • Useful in risk management as it accounts for the worst-case scenarios.
• Cons:
  • Requires more computational effort than VaR alone.
  • Can be difficult to estimate accurately, particularly in the tail.

Conclusion

• Historical Simulation is good when you have plenty of data and want to avoid assumptions about return distributions.
• Variance-Covariance is efficient but may not perform well with non-normal distributions.
• Monte Carlo Simulation is highly flexible but computationally expensive.
• Extreme Value Theory is suited for modeling extreme risks but requires advanced statistical knowledge.
• Bootstrap Method provides flexibility but can be computationally demanding.
• Conditional VaR (CVaR) complements VaR by providing insights into tail risk beyond the VaR threshold.

OR

Q.5 Write Short Notes (Any 3)            (15)

1 Mark to Market Margin

Mark to Market (MTM) margin is a financial process used in futures and derivatives trading to assess and adjust the value of open positions based on current market prices. At the end of each trading day, the market value of a contract is re-evaluated against the actual closing market prices, rather than its original purchase price. This process ensures that traders’ accounts reflect the real-time profit or loss associated with their positions.

If the market value moves unfavorably, the trader might face a margin call, requiring them to deposit additional funds to cover potential losses. Conversely, if the position gains value, the excess funds are credited to the trader’s account. MTM margin is crucial for maintaining transparency and financial stability in markets, as it mitigates the risk of large, unrecognized losses accumulating in accounts. This mechanism helps clearinghouses and exchanges to manage risk and ensures that traders are always in compliance with margin requirements.

2 Imperfect Hedge

An imperfect hedge is a risk management strategy where the hedge does not fully offset the potential losses or risks associated with the underlying asset or exposure. Unlike a perfect hedge, which completely eliminates the risk, an imperfect hedge provides only partial protection, leaving some residual risk. This can happen when the hedging instrument does not have an exact correlation with the underlying asset, leading to basis risk—the risk that the hedge and the asset will move differently in response to market factors.

For instance, a company with exposure to currency risk might use a hedge in the form of a futures contract, but if the futures contract does not precisely match the exposure in timing or currency type, the hedge will be imperfect. Imperfect hedges are common when perfect hedging instruments are unavailable, too costly, or impractical. While they do not eliminate all risk, imperfect hedges can significantly reduce potential losses, making them useful in managing financial risk within acceptable levels.

3 Cost of Carry Model

The Cost of Carry Model is a financial theory used to determine the fair price of a futures or forward contract based on the costs and benefits of holding (or carrying) the underlying asset until the contract's expiration. The model considers several "carry costs," such as storage, financing (interest rate costs), and insurance, as well as potential "carry benefits," like dividends or convenience yields (if the asset generates income or utility over time).

In its basic form, the Cost of Carry Model suggests that the futures price should equal the spot price of the asset plus the net carrying cost (costs minus benefits) over the life of the contract. This relationship can be expressed mathematically as:

$$\text{Futures Price}=\text{Spot Price}+\text{Net Cost of Carry}\text{<br>}$$

This model is widely used for pricing futures and forwards on assets like commodities, securities, and currencies. It helps investors understand the premium or discount on futures relative to the spot price, thereby aiding in arbitrage opportunities and in assessing the true cost of holding an asset over time.

4 SPAN Margin

SPAN Margin (Standard Portfolio Analysis of Risk) is a risk-based margining system developed by the Chicago Mercantile Exchange (CME) that is widely used to determine margin requirements for futures and options portfolios. Unlike traditional margin methods, which may only consider the value of individual positions, SPAN evaluates the overall risk of an entire portfolio by simulating potential price movements and assessing the impact on the portfolio under various market conditions.

The SPAN system calculates margin requirements by evaluating 16 hypothetical scenarios, including price changes, volatility shifts, and time decay, to estimate the maximum potential loss. This approach allows it to account for offsetting positions and correlations within the portfolio, leading to more accurate margin requirements that reflect actual risk exposure.

SPAN Margin is widely adopted by exchanges worldwide for its ability to optimize margin requirements, which helps both exchanges and traders manage risk more efficiently without unnecessarily tying up capital.

5 Types of Margin

Margins are funds that traders must deposit with their broker or exchange to initiate and maintain positions in futures, options, or other leveraged financial instruments. Margins act as a safeguard to ensure that traders can cover potential losses. There are several types of margin used in trading, each serving a different purpose:

1. Initial Margin: This is the minimum amount required to open a new position. It acts as a performance bond, ensuring that the trader has some funds at risk and can cover potential losses.

2. Maintenance Margin: This is the minimum balance that must be maintained in a trading account to keep a position open. If the account balance falls below this level due to market losses, the trader may receive a "margin call" and be required to deposit additional funds to restore the account to the initial margin level.

3. Variation Margin: This margin reflects the daily profit or loss on a position and is used in mark-to-market adjustments. If the market moves against the position, additional variation margin may be required to cover losses, ensuring that the account remains sufficiently funded on a day-to-day basis.

4. SPAN Margin: A risk-based margining system (Standard Portfolio Analysis of Risk) primarily used for futures and options, which calculates margin based on potential portfolio-wide risk under various market conditions.

5. Cross Margin: This type of margining system allows a trader to use the equity from profitable positions to support other positions in the same account, effectively reducing margin requirements by balancing gains and losses across positions.