Commodity Risk Management Techniques & Hedge

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9/4/2018

COMMODITY RISK MANAGEMENT
TECHNIQUES & HEDGE ACCOUNTING
CHANGES

September 5, 2018

To Receive CPE Credit

Individuals

..

Participate in entire webinar

Answer polls when they are provided

Groups

.

Group leader is the person who registered & logged on to the webinar

....

Answer polls when they are provided

Complete group attendance form Group leader sign bottom of form Submit group attendance form to [email protected] within 24 hours of webinar

If all eligibility requirements are met, each participant will be emailed their CPE certificate within 15 business days of webinar

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9/4/2018

Bryan Wright

Partner | BKD Indianapolis I 317.383.5471

Allen Douglass

Regional Director | INTL FCStone Financial, Inc. FCM Division Indianapolis l 317.732.4660

Disclaimer

The trading of derivatives such as futures, options, and over-the-counter (OTC) products or “swaps” may not be suitable for all investors. Derivatives trading involves substantial risk of loss, and you should fully understand those risks prior to trading. Past financial results are not necessarily indicative of future performance. All references to futures and options on futures trading are made solely on behalf of the FCM Division of INTL FCStone Financial Inc., a member of the National Futures Association (“NFA”) and registered with the U.S. Commodity Futures Trading Commission (“CFTC”) as a futures commission merchant. All references to and discussion of OTC products or swaps are made solely on behalf of INTL FCStone Markets, LLC (“IFM”), a member of the NFA and provisionally registered with the CFTC as a swap dealer. IFM’s products are designed only for individuals or firms who qualify under CFTC rules as an ‘Eligible Contract Participant’ (“ECP”) and who have been accepted as customers of IFM.

This material should be construed as the solicitation of trading strategies and/or services provided by the FCM Division of INTL FCStone Financial Inc., or IFM, as noted in this presentation.

Neither the FCM Division of INTL FCStone Financial Inc. nor IFM is responsible for any redistribution of this material by third parties or any trading decisions taken by persons not intended to view this material. Information contained herein was obtained from sources believed to be reliable, but is not guaranteed. These materials represent the opinions and viewpoints of the author, and do not necessarily reflect the opinions or viewpoints of the FCM Division of INTL FCStone Financial Inc. or IFM.

All forecasting statements made within this material represent the opinions of the author unless otherwise noted. Factual

information believed to reliable, was used to formulate these statements of opinion; but we cannot guarantee the accuracy and completeness of the information being relied upon. Accordingly, these statements do not necessarily reflect the viewpoints employed by the FCM Division of INTL FCStone Financial Inc. or IFM. All forecasts of market conditions are inherently subjective and speculative, and actual results and subsequent forecasts may vary significantly from these forecasts. No assurance or guarantee is made that these forecasts will be achieved. Any examples given are provided for illustrative purposes only, and no representation is being made that any person will or is likely to achieve profits or losses similar to those examples.

Reproduction or use in any format without authorization is forbidden. © Copyright 2018. All rights reserved.

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Risk is ever present… How do we choose to address?

Accept it

  • Don’t Fear it
  • Manage it

Conquer it

If you don’t manage risk, you are assuming risk If you are assuming risk, you are speculating!!!

Normal Business Risks

Buildings
&

Facilities

Equipment, Machinery, Trucks

Family & Employees

Insurance

Health & Safety

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Another Critical Business Risk:

PRICE!!!

Grains

Oilseeds

More Likely
& More Frequent!

Livestock

Know Your Price Risk & Manage It!

Energy

Interest Rates & FX

HOWEVER,

WITHOUT PRICE RISK MANAGEMENT…

Things can get Real UGLY Real fast!
And Bottom Lines & Margins Can Melt Away!

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Is Price Risk Management Difficult?

NO! Just remember,

complex concepts stated simply

creates opportunity!
Success favors the Prepared.

Tools to Manage Price Risk

Rights to Buy or Sell at Price Levels with Opportunity to Improve
Locked-in Buying & Selling
Price Levels

Variety of Contracts With Physical Delivery Requirements
Creative Financial Products With Pricing Flexibility

*

*OTC products are designed only for individuals or firms who qualify under CFTC rules as an ‘Eligible Contract Participant’ (“ECP”) and who have been accepted as customers of IFM.

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What is Market Risk?

Uncertainty!

Types of Market Risk

  • Local Cash Basis
  • Global Futures Price

Higher
Stronger

No change
Lower
No change
Weaker

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What is a BUYER’S Market Risks?

Buyer’s Cash Basis

Global Benchmark Futures Price

  • Higher
  • Stronger

What is a SELLER’S Market Risks?

  • Global Benchmark Futures Price
  • Seller’s Cash Basis

  • Weaker
  • Lower

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Price Volatility

Source: CME Group

What is Volatility?

Example: March 2019 Corn Futures at $4.00

Compare Market Volatility: 10%, 20%, 30%

  • Annualized Volatility
  • 68% Probability Price Range

10% 20% 30%
$3.60 - $4.40 $3.20 - $4.80 $2.80 - $5.20

At what volatility level is your risk the greatest?
At what volatility level is your opportunity the greatest?

Note: 2 Standard Deviations is 95% probability and 3 Standard Deviations = 99% probability

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Price Risk Management – Summary

Price Risk Management

Remember what I said earlier ???

Stated Simply

Creates
OPPORTUNITY

Basis & Hedging Theory

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Basis

Key to Successful Hedging

Local Supplier or Buyer Price quote
Global Benchmark Price quote
Local Cash Relative to Futures

Cash Price
Futures Price

Basis

Q. If you have more than one “cash” quote, how many basis tables are needed?
A. Each cash market supplier represents a different basis.

Basis Concepts

Merchandisers
& Their Customers should become Students of Basis!

Cash minus Futures

Locational & Quality
Seasonal & Historical Trends
Differences

BASIS

Buyers want
Sellers want

Weaker

Stronger
Less Volatile

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Basis Movement & Opportunity

+30 +20 +10
0

Strengthen

Cash Gains Relative* to Futures
More positive or

Weaken

Cash Declines Relative* to Futures
Less positive or
Less negative
More negative
Benefits Short Hedgers
Benefits Long Hedgers

-10 -20 -30

Commodity Buyers
Commodity Sellers

*Basis can strengthen or weaken regardless of the price direction

Use of Basis in Risk Management

Gulf Export Price - Nearby Corn Futures Basis (Sample 10 year period)

  • Maximum
  • Minimum
  • Average

160 140 120 100
80 60 40 20
0

Week of the Year

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Basis Summary

••

••••••

Cash price relative to a Futures price

Usually less volatile than Futures

Seasonal & Historical trends

Purchasing & Sales Tool

Can have a negative or positive value

Buyers want basis to weaken over time

Sellers want basis to strengthen over time

Key to successful Price Risk Management

True Hedge – Consists of Two Parts

Futures, Options or OTC Swaps

Local
Cash Market

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Hedge Concepts

Fact:

 Most cash markets and futures markets move up and down together  Not necessarily in equal amounts  Relationship between a cash & a futures price: Correlation

Hedge Positions

 Opposite positions in Cash market and Futures market

Hedge Results

 Loss in one market is offset by a gain in the other market  Regardless of price direction, the result is the same!

The “TRUE” hedge result is the combined results of the cash and futures positions

HEDGED RESULTS

Loss in One Market is Offset by a Gain in the Other

Cash Market

Futures Market

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Types of Hedgers

• Long hedger • Risk of rising prices • Attempt to achieve target prices • Short the basis – wants basis to weaken

Consumer

(buy-side)
• Short hedger

Producer

(sell-side)
• Risk of falling prices • Attempt to cover production costs & profit • Long the basis – wants basis to strengthen

Futures Industry Foundation

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Futures Contract: Defined

Corn
5,000 bu. =
127 m.t.

Legally binding agreement to accept delivery of or make delivery of a

Wheat
5,000 bu. =
136 m.t.

quantity

standardized _______ and ______

quality

Soybeans: 5,000 bu. =
136 m.t.

place

of a commodity to a standardized _____

time

price

during a standardized ____ period for a ____

Soybean Meal
100 short tons =
92 m.t.

discovered in an organized futures exchange.

Economic Functions of Futures

Price
Discovery

Which impacts the greatest number of people?

Price Reference & Cash Contracts

Futures Markets

Which is the most important economic function?

Risk
Management

For Customers

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Price Discovery:

Supply & Demand

• Prices are Discovered

• Prices are NOT set by the Exchange

• Closest form of “perfect competition”

• Two-way Price Impact

• Transparent Prices

Types of Traders

Merchandisers
& Their Customers

Cash Market

Speculator

Cash Market

Hedger

  • Risk
  • Liquidity

  • Risk
  • Liquidity

Speculators provide what hedgers need!

LIQUIDITY

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Speculators’ Impact on Hedgers

Corn Market Liquidity

3.80

3.85
Seller’s Offer

Hedgers Only

Buyer’s Bid

3.81 New Bid

3.84
Better Offer

Speculator

3.82 New Bid

3.83
Better Offer

Speculators

3.82 1/4 Best Bid

3.82 1/2 Best Offer

S

Closing-out a Futures Position

Offset

Offset: Taking a position opposite to your initial position
• Initial futures position creates market obligation
• Offset removes market obligation

Initial Position Long Futures
Sell Identical
Futures

later

OFFSET

Or

Initial Position Short Futures
Buy Identical
Futures
OFFSET

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Closing-out a Futures Position

Delivery

Transfer of a physical commodity or cash-settlement

Only about 1% of Futures volume ends with delivery

Great majority are “offset”

Initiated “only” by the Seller (short)

Short must have approved “regular for delivery” status Assigned to “oldest” long

Specific Terms & Procedures

Varies by commodity – shipping certificates, warehouse receipts

See Exchange Rule Book for details

••

Cash Price & Futures Price Convergence

Due to threat of delivery in futures contract

Not economically or physically feasible for the Buyer (long)

Seller makes delivery decisions: specific date, quality, location

CBOT Grain & Oilseed Futures Delivery

3-Day Process*

First Delivery Day

First business day of the contract month

First Notice Day

Short delivers the shipping

certificate to the long

••

Last business day of calendar month prior to delivery month. Example: June for July contract.

First Position Day

Long makes payment to the short

by 1:00 p.m.

Business day prior to last business

CME Clearing notifies “oldest

long” by 7:00 a.m. that delivery will take place day of calendar month prior to delivery month. Example: November for December contract
If delivery day is a bank holiday, payment is made by 9:30 a.m. on the next banking day.

Short invoices the long by 4:00

Short positions: First day that

short positions can initiate the delivery process by notifying CME Clearing. Only shorts that have “regular for delivery” status p.m.

*Note: This 3-day process for first delivery also applies to deliveries up to and including the last delivery day. The last delivery day is the 16th of the contract month

Long positions: Ranked according

to the amount of time they have been long. Oldest is ranked first

Daily price limits are removed for remainder of trading of the delivery contract month

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Financial Integrity of Futures

Clearing Models

Bilateral versus Cleared

CLEARED TRADE:

A trade guaranteed by Futures Commission Merchants (FCM) who are members of a clearing house

BI-LATERAL TRADE:

A trade executed between two parties without the benefit of a central clearing house.

Source: CME Group

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Exchange Clearing Services

• Eliminates Counter Party Risk

 Buyer to every Seller and Seller to every Buyer

• Adjust Trading Accounts Daily

 Marked to Market

• Facilitates Trading Processes

 Futures Delivery  Option Exercise

Central Counterparty Clearing

Source: CME Group

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Recommended publications
  • Three Essays in Commodity Risk Management

    Three Essays in Commodity Risk Management

    THREE ESSAYS IN COMMODITY RISK MANAGEMENT by Phat Vinh Luong A Dissertation Submitted To The Graduate School Of Business Of Rutgers, The State University of New Jersey In Partial Fulfillment Of The Requirements For The Degree Of Doctor Of Philosophy Written under the direction of Ben Sopranzetti (Principal Adviser) And approved by Xiaowei Xu Bruce Mizrach Weiwei Chen Newark, NJ. May 2018 © Copyright by Phat Vinh Luong 2018 All Rights Reserved Abstract This thesis includes three essays. These essays focus on the commodity market and cover a wide range of topics. Their topics range from the roles of inventory, pricing strategies to impacts of government policies on the commodity market. The first essay provides an analytical framework to distinguish the roles of inventory by investigating their behaviors in a frequency domain. If inventory was used as a buffer for demand shocks, then the stock level should decrease at all frequencies under both the production smoothing and the stockout avoidance strategies. The inventory investment is negative at all frequencies under the stockout avoidance strategy while it is negative at high frequencies (short-term) and is positive at low frequencies (long-term). On the other hand, if inventory is used as a speculative tool, then its level and the inventory investment should increase with the increases in demand and prices at all frequencies. The volatilities of inventory investment also reveal the roles of inventory. Under production smoothing theory, inventory investment is as volatile as the demand at all frequencies while it is as volatile as the output if growth is persistent but less volatile than output if growth is not persistent.
  • Factor-Based Commodity Investing

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    Factor-Based Commodity Investing January 2018 Athanasios Sakkas Assistant Professor in Finance, Southampton Business School, University of Southampton Nikolaos Tessaromatis Professor of Finance, EDHEC Business School, EDHEC-Risk Institute JEL Classification: G10, G11, G12, G23 Keywords: Commodities; Factor Premia; Momentum; Basis, Basis-Momentum, Variance Timing, Commodity Return Predictability EDHEC is one of the top five business schools in France. Its reputation is built on the high quality of its faculty and the privileged relationship with professionals that the school has cultivated since its establishment in 1906. EDHEC Business School has decided to draw on its extensive knowledge of the professional environment and has therefore focused its research on themes that satisfy the needs of professionals. EDHEC pursues an active research policy in the field of finance. EDHEC-Risk Institute carries out numerous research programmes in the areas of asset allocation and risk management in both the 2 traditional and alternative investment universes. Copyright © 2018 EDHEC Abstract A multi-factor commodity portfolio combining the high momentum, low basis and high basis- momentum commodity factor portfolios significantly, economically and statistically outperforms, widely used commodity benchmarks. We find evidence that a variance timing strategy applied to commodity factor portfolios improves the return to risk trade-off of unmanaged commodity portfolios. In contrast, dynamic commodities strategies based on commodity return prediction models provide little value added once variance timing has been applied to commodity portfolios. 1. Introduction There is growing evidence that commodity prices can be explained by a small number of priced commodity factors. Commodity portfolios exposed to commodity factors earn significant risk premiums, in addition to the premium offered by a broadly diversified commodity index.
  • Agricultural Commodity Risk Management

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    Agricultural Commodity Risk Management: Policy Options and Practical Instruments with Emphasis on the Tea Economy Alexander Sarris Director, Trade and Markets Division, FAO Presentation at the Intergovernmental Group of Tea, nineteenth session, Delhi India, May 12, 2010 Outline of presentation • Background and motivation • Risks faced by rural households • Risks in the tea economy • Agricultural productivity and credit • Constraints to expanding intermediate input use in agriculture • The demand for commodity price insurance • The demand for weather insurance • Operationalizing the use of price and weather insurance • Possibilities for the tea economy Background and motivation: Some major questions relevant to agricultural land productivity and risk • Is agricultural land productivity a factor in growth and poverty reduction? • What are the factors affecting land productivity? Is risk a factor? • Are there inefficiencies in factor use among smallholders? If yes in which markets? Why? • Determinants of intermediate input demand and access to seasonal credit • What are the impacts or risk at various segments of the value chain? Background and Motivation: Uncertainty and Risk • Small (and medium size) agricultural producers face many income and non-income risks • Individual risk management and risk coping strategies maybe detrimental to income growth as they lead to low returns low risk activities. Considerable residual income risk and vulnerability • Is there a demand for additional price and weather related income insurance in light of individual existing risk management strategies? • Can index insurance crowd in credit and how? • Is there a rationale for market based or publicly supported price and weather based safety nets • What are appropriate institutional structures conducive to combining index insurance with credit? Farmer Exposure to Risk.
  • Banks As Regulated Traders

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  • Commodity Risks and the Cross-Section of Equity Returns

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  • Documentary Risk in Commodity Trade

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  • Rapid Agricultural Supply Chain Risk Assessment: a Conceptual Framework

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  • The Term Structure of Commodity Risk Premiums and the Role of Hedging

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  • Risk Management Strategies for Commodity Processors

    Risk Management Strategies for Commodity Processors

    RISK MANAGEMENT STRATEGIES FOR COMMODITY PROCESSORS A Thesis Submitted to the Graduate Faculty of the North Dakota State University of Agriculture and Applied Science By Songjiao Chen In Partial Fulfillment for the Degree of MASTER OF SCIENCE Major Department: Agribusiness and Applied Economics May 2013 Fargo, North Dakota North Dakota State University Graduate School Title Risk Management Strategies for Commodity Processors By Songjiao Chen The Supervisory Committee certifies that this disquisition complies with North Dakota State University’s regulations and meets the accepted standards for the degree of MASTER OF SCIENCE SUPERVISORY COMMITTEE: William Wilson Chair Ryan Larsen Dragan Miljkovic Ruilin Tian Approved: 6/21/2013 William Nganje Date Department Chair ABSTRACT Recent years have witnessed an increase in agricultural commodity price volatilities. This thesis analyzes different models to derive optimal hedge strategies for commodity processors, with two components addressed. One is the dependence structure and joint distribution among inputs, outputs, and hedging instruments that impact hedging effectiveness. The second refers to different procurement and sales scenarios a processor may encounter. A domestic flour mill company is used to demonstrate alternative hedging strategies under different processing scenarios. Copula is a relatively new method used to capture flexible dependence structure and joint distribution among assets. The applications of copulas in the agricultural literature are recent. This thesis integrates the concept of copula and widely studied risk measurement Value at Risk (VaR) to derive the optimal risk management strategy. Mean-VaR with copula calculation is shown to be an efficient and confident approach to analyze empirical studies. iii ACKNOWLEDGMENTS I would like to take this opportunity to thank my adviser, Dr.
  • Deriving the Economic Impact of Derivatives

    Deriving the Economic Impact of Derivatives

    Deriving the Economic Impact of Derivatives Growth Through Risk Management March 2014 Deriving the Economic Impact of Derivatives Growth Through Risk Management Apanard (Penny) Prabha, Keith Savard, and Heather Wickramarachi Research Support Stephen Lin, Donald Markwardt, and Nan Zhang Project Directors Ross DeVol and Perry Wong March 2014 ACKNOWLEDGMENTS This project evolved from discussions with various stakeholders of the Milken Institute who encouraged us to examine derivatives markets in the aftermath of the financial crisis and Great Recession. It was made possible through the support of the CME Group. The views expressed in the report, however, are solely those of the Milken Institute. The Milken Institute would like to give special thanks to the research department of the CME Group for their valuable suggestions, feedback, and overall leadership throughout the research process. The authors appreciate the indispensable efforts of Milken Institute Managing Director Mindy Silverstein in securing the resources required to convert a methodological outline into a final product. Additionally, we appreciate the encouragement provided by Milken Institute CEO Michael Klowden in this undertaking. The Milken Institute Research team is grateful for the advice, counsel, and expertise provided by reviewers Richard Sandor, chairman and CEO of Environmental Financial Products LLC; Ross Levine, Willis H. Booth Chair in Banking and Finance at the Haas School of Business, University of California at Berkeley; and James Barth, the Lowder Eminent Scholar in Finance at Auburn University. All are Senior Fellows of the Milken Institute. Richard Sandor is a true financial innovator known as the “father of financial futures.” Ross Levine is among the most highly regarded researchers in the operations of financial systems and functioning of the economy.