The information contained on this page is designed to give students a representative example of material covered in the course. Any information related to course assignments, dates, or course materials is illustrative only. For a definitive list of materials, please check the online catalog 3-4 weeks before the course start date.

AG BM 320

AG BM 320 Markets and Prices: Analysis and Forecasting (3) Understand how prices are determined; develop the skill to analyze and forecast how prices change as the underlying conditions change.

Overview

In AG BM 320, Markets and Prices: Analysis and Forecasting, students learn how prices are determined and learn how to analyze and forecast how prices change as the underlying conditions change. This involves learning those tools that are used to analyze and understand how commodity markets work and how prices are determined. The class mixes theory with practical knowledge and examples, and aims to create a balanced representation of the tools used in market analysis. The students learn how to find data, manipulate it and analyze and apply these skills to test the validity of simple economic models, to forecast commodity prices, to understand market trends and learn the use of derivative instruments to manage price risk.

The main objective of this class is to improve the understanding of economic modeling and to increase the familiarity of students when applying statistical functions and regression analysis to solve applied problems. These core competencies rely on previous knowledge of basic statistic tools and data manipulation. In the process, students will learn to analyze market fundamentals and better understand those forces that affect prices. This will also help them better understand supply and demand and the ability of market participants to adjust to changing conditions.

Prerequisite: AG BM 101, AG BM 102, and AG BM 106; SCM 200 or STAT 200

Course Objectives

After having successfully completed this course, students will be able to

Source, transform and analyze data in order to

• build statistical models,
• forecast and understand marketing trends,
• manipulate MS Excel statistical functions and build graphs and other data artifacts
• Analyze and apply variety of data analysis tools

Required Course Materials

There is no required text for this course.

Library Resources

Many of the University Libraries resources can be utilized from a distance. Through the Libraries website, you can

• access magazine, journal, and newspaper articles online using library databases;
• borrow materials and have them delivered to your doorstep—or even your desktop;
• get research help via email, chat, or phone using the Ask a Librarian service; and
• much more.

You can view the Online Students' Library Guide for more information.

You must have an active Penn State Access Account to take full advantage of the Libraries' resources and services. Once you have a Penn State account, you will automatically be registered with the library within 24–48 hours. If you would like to determine whether your registration has been completed, visit the Libraries home page and select  My Account.

Technical Requirements

Many of the University Libraries resources can be utilized from a distance. Through the Libraries website, you can

• access magazine, journal, and newspaper articles online using library databases;
• borrow materials and have them delivered to your doorstep—or even your desktop;
• get research help via email, chat, or phone using the Ask a Librarian service; and
• much more. 

You must have an active Penn State Access Account to take full advantage of the Libraries' resources and service.  The Off-Campus Users page has additional information about these free services.

If you need technical assistance at any point during the course, please contact the Service Desk.

For registration, advising, disability services, help with materials, exams, general problem solving, visit World Campus Student Services!

Course Requirements and Grading

Weekly Quizzes 20%

Quizzes consist of true and false and multiple choice questions.  They are untimed, however you can only submit your answers one.

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Weekly Problem Sets 30%

Every week you will asked to apply what you have learned in the lesson commentary and video tutorials.  Most problem sets will involve manipulating data and running several analyses.  The data files need are listed in the Problem set pages and can also be accessed by the weekly activity folders.

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YouSeeU Presentation 30 %

The goal of this project is to increase your familiarity with the processes of data collection, data analysis, data interpretation, as well as developing more analytical and critical skills necessary to be good market analysts.  As the delivery of your output will be by means of a presentation, another goal will be that of improving your ability of public speaking.

Presentation Project Timeline:

• Select your product and give a brief overview of the product and it's history (due at the end of Lesson 8)
• Collect and analyze your data, provide a write-up (due at the end of Lesson 9)
• Write-up your conclusions and sources (due at the end of Lesson 10)
• Record your final presentation (due at the end Lesson 11)

The development of the project will include (broadly speaking) three steps:

1. Collect data and information on one agricultural commodity/food product/ natural resource of your choice;
2. Analyze the data collected using the tools and models described in this course;
3. Prepare a presentation where you will illustrate your analysis and your findings.

Although you are free to choose any agricultural commodity/food product/natural resource of interest, there are several factors which should motivate your choice, such as the availability of market reports, data, literature, and publications (for example reports and/or publications by cooperatives /association of producers) about your product. You are encouraged to discuss with the instructor your commodity choice as soon as possible so that you will know in a timely fashion whether your choice is suitable.

Requirements of the presentation

The presentation must contain the following components:

1. Introduction: A short introduction illustrating the features of the commodity/product (its uses, its history, its economic importance, production areas, etc…)
2. Descriptive Analysis: A descriptive analysis of the market and its recent trends, including:
   1. demand for the commodity, (farm-level, and/or intermediate, and/or final; disappearances  – shifters, recent shocks, etc…);
   2. supply of the commodity (production cycles; inputs; market concentration; structural shifts, recent shocks etc…);
   3. price of the commodity (variation over time; cycles; seasonality; shocks in related prices etc…). 
   4. all recent shocks that have impacted the market of the commodity directly (including, but not limited to, weather shocks and policy related shocks), and indirectly (for example those shocks affecting the market of one of the inputs used in the production process of the commodity you have chosen).
3. Derivatives: A brief overview of the existing derivative instruments (futures contracts and options) for the commodity, or of those which are closely related to it (if any);
4. Empirical Analysis: At least one of the following empirical analyses:
   1. Estimation of the demand for the commodity (at any level);
   2. Estimation of the supply of the commodity;
   3. Price analysis and/or forecasting; For this part, you must: 
      1. Specify the sources of your data;
      2. Illustrate and motivate the hypotheses underlying your model;
      3. Explain carefully the assumptions of your model;
      4. Justify the appropriateness of your model;
      5. Interpret the results.
5. Outlook and Conclusions: An outlook of the future directions of the market for the commodity in analysis - motivate your predictions with empirical evidence;
6. Source List: All sources used to acquire the information used in the project - including data sources, reports, websites, books and journal articles - should be appropriately cited in the presentation and accurately reported in a document to be handed in to the in to the instructor.  Use the “APA” style. DO NOT use Wikipedia directly as a source.

The presentation should not exceed 10 minutes. 

Grading

What follows are summaries of the grading procedures for the market analysis presentation.

1. Introduction, Uses and History - 40 points
2. Descriptive Analysis (total 80 points) 
   1. Demand - 20 points  
   2. Supply - 20 points
   3. Prices - 20 points
   4. Shocks - 20 points
3. Derivatives (if any) - 20 points
   1. If there are no financial derivatives associated to your commodity, the 20 points will be allocated to the descriptive analysis – 5 points to each component.
4. Empirical Analysis (total 80 points)
   1. Data - 20 points   
   2. Hypothesis - 20 points
   3. Model - 20 points
   4. Results & interpretation - 20 points
5. Outlook/ Conclusions - 20 points
6. Cohesiveness of Presentation - 20 points
7. Clarity of Exposition - 20 points
8. Visual Quality - 10 points
9. Citations/ Reference List - 10 points

A note on point 5: Cohesiveness: all components of the project should fit together and tell one unique story. If the presentation comes through as a patchwork of items having little in common with one another, its effectiveness will be limited.

A note on point 6: Clarity: The information should be delivered in a succinct and clear way. If the language is poor, the information will not be transmitted effectively.

A note on point 7: a good use of visual tools may help your presentation.  Graphs and tables may help conveying crucial points of the plan; I would discourage you from using sounds effects and/ or animation extensively – they can be very distracting.

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Trading Simulation Game 20%

In Lesson 11 you will complete a simulation game based on how hedgers and speculators perform in a market  based on various forces.  You will be asked to give feedback on a players performance and critique their strategy. See the lesson 11 and the schedule pages for more detail.

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Reminder: Please keep in mind that you can use the free Tutor.com services to assist you with your assignments but you may NOT use this service during quizzes or exams.  Students AND instructors have access to transcripts from tutoring sessions.

Additional Information

Please refer to the University Grading Policy for Undergraduate Courses for additional information about University grading policies.

Course Schedule

The schedule below outlines the topics we will be covering in this course, along with the associated time frames and assignments. Note that assignments are due based on Eastern Time (ET). This ensures that all students have the same deadlines regardless of where they live. All lesson assignments must be submitted by 11:59 PM (ET) on the last day of the timeframe indicated below for the lesson.

Lesson 1: Market Analysis Primer

Lesson 1

Readings:	Lesson Commentary  Listen to the NPR podcast: Commodities Trading
Assignments:	YouSeeU Introduction Video All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 2: Data Source and Analysis

Lesson 2

Readings:	Lesson Commentary Video Tutorial: Data Handling
Assignments:	Quiz Problem Sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 3: Regression Analysis

Lesson 3

Readings:	Lesson Commentary Video Tutorial: Regression Analysis
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 4: Demand

Lesson 4

Readings:	Read or listen to the Freakanomics episode on "You eat what you are: Part 1" Lesson Commentary Video Tutorial: Demand for Butter Video Tutorial: Derived Demand
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 5: Price determination and principles of fundamental analysis supply side

Lesson 5

Readings:	Lesson Commentary Video Tutorial: Calculating Long-Run and Short-Run Equlibrium
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 6: Trends and Seasonality

Lesson 6

Readings:	Lesson Commentary Video Tutorial: Seasonality and Shock Trends with Regression Video Tutorial: Moving Averages
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 7: Forecasting

Lesson 7

Readings:	Lesson Commentary Video Tutorial: Methods of forecasting Video Tutorial: Forecasting using auto-regressive models
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 8: Futures on Commodities

Lesson 8

Readings:	Lesson Commentary
Assignments:	YouSeeU Presentation Overview Intial presentation product and history Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 9: Speculations by Spreading Orders and Margins

Lesson 9

Readings:	Lesson Commentary Video Tutorial: Margin Requirements
Assignments:	Quiz Problem sets Inital presentation data collection and analysis All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 10: Technical Analysis

Lesson 10

Readings:	CME Futures Trading Manual, Chapter 8 Lesson Commentary Video Tutorial: Trading with Charts: Triangles Video Tutorial: Trading with Charts: Head and Shoulders Video Tutorial: Trading with Charts: Practice
Assignments:	Quiz Problem sets Inital presentation write-up of conlusions All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 11: Feedback and Trade

Lesson 11

Readings:	Lesson Commentary
Assignments:	Upload completed presentaiton and supporting documentes to YouSeeU Complete simulation Critique Complete simulation Assessment All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 12: Hedging

Lesson 12

Readings:	Lesson Commentary
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 13: Options and Futures

Lesson 13

Readings:	CME Futures Trading Manual, Chapter 9 CME Group Self Self-Study Guide to Hedging with Grain and Oilseed Futures and Options, Chapter Lesson Commentary
Assignments:	Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Lesson 14: Price Risk Management

Lesson 14

Readings:

Lesson Commentary Video Tutorial: Strategies to Protect Against High Prices, Long Futures Video Tutorial: Strategies to Protect Against High Prices, Long Call Video Tutorial: Strategies to Protect Against High Prices, Long Call Spread Video Tutorial: Strategies to Protect Against High Prices, Short Put Call Video Tutorial: Strategies to Protect Against High Prices, Short Put and Long Call Video Tutorial: Strategies to Protect Against Low Prices, Short Futures Video Tutorial: Strategies to Protect Against Low Prices, Long Put Option Video Tutorial: Strategies to Protect Against Low Prices, Long Put Spread Video Tutorial: Strategies to Protect Against Low Prices, Short Call Option Video Tutorial: Strategies to Protect Against Low Prices, Short Call and Long Put

Assignments:

Quiz Problem sets All lesson assignments must be submitted by 11:59 PM (ET) on Sunday

Note: If you are planning to graduate this semester, please communicate your intent to graduate to your instructor. This will alert your instructor to the need to submit your final grade in time to meet the published graduation deadlines. For more information about graduation policies and deadlines, please go to the Graduation Information on the My Penn State Online Student Portal.

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Academic Integrity

According to Penn State policy G-9: Academic Integrity , an academic integrity violation is “an intentional, unintentional, or attempted violation of course or assessment policies to gain an academic advantage or to advantage or disadvantage another student academically.” Unless your instructor tells you otherwise, you must complete all course work entirely on your own, using only sources that have been permitted by your instructor, and you may not assist other students with papers, quizzes, exams, or other assessments. If your instructor allows you to use ideas, images, or word phrases created by another person (e.g., from Course Hero or Chegg) or by generative technology, such as ChatGPT, you must identify their source. You may not submit false or fabricated information, use the same academic work for credit in multiple courses, or share instructional content. Students with questions about academic integrity should ask their instructor before submitting work.

Students facing allegations of academic misconduct may not drop/withdraw from the affected course unless they are cleared of wrongdoing (see G-9: Academic Integrity ). Attempted drops will be prevented or reversed, and students will be expected to complete course work and meet course deadlines. Students who are found responsible for academic integrity violations face academic outcomes, which can be severe, and put themselves at jeopardy for other outcomes which may include ineligibility for Dean’s List, pass/fail elections, and grade forgiveness. Students may also face consequences from their home/major program and/or The Schreyer Honors College.

How Academic Integrity Violations Are Handled
World Campus students are expected to act with civility and personal integrity; respect other students' dignity, rights, and property; and help create and maintain an environment in which all can succeed through the fruits of their own efforts. An environment of academic integrity is requisite to respect for oneself and others, as well as a civil community.

In cases where academic integrity is questioned, the Policy on Academic Integrity indicates that procedure requires an instructor to inform the student of the allegation. Procedures allow a student to accept or contest a charge. If a student chooses to contest a charge, the case will then be managed by the respective college or campus Academic Integrity Committee. If that committee recommends an administrative sanction (Formal Warning, Conduct Probation, Suspension, Expulsion), the claim will be referred to the Office of Student Accountability and Conflict Response.

All Penn State colleges abide by this Penn State policy, but review procedures may vary by college when academic dishonesty is suspected. Information about Penn State's academic integrity policy and college review procedures is included in the information that students receive upon enrolling in a course. To obtain that information in advance of enrolling in a course, please contact us by going to the Contacts & Help page .

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In order to apply for reasonable accommodations, you must contact the appropriate disability resources office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation based on the documentation guidelines. If the documentation supports your request for reasonable accommodations, your campus's disability resources office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

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