Interdisciplinary Economics: Economodeling
In this 36 week guided and interactive online high school course, students will use Python programming, Excel, and web scraping to get real time economic data to develop a predictive mathematical model of the global economy, using historical data available online and various regression models and economic relationships. Students will publish their findings periodically throughout the course in a blog to get public feedback on what they are learning. They will then convert that model into a user interface in the form of an app in order to make it available to those that have not participated in the modeling process. Through this, they will learn computer programming, mathematical modeling, data-based decision making, and technical communications and design. Please scroll down for more information and some samples of student work!
"And his master praised the unrighteous manager because he had acted shrewdly, for the sons of this age are more shrewd in relation to their own kind than the sons of light...He who is faithful in a very little thing is faithful also in much; and he who is unrighteous in a very little thing is unrighteous also in much. Therefore, if you have not been faithful in the use of unrighteous wealth, who will entrust true riches to you?" -- Luke 16:8, 10-11
Additional REsources required:
- None
so, what's the story?
What if I continued to give you the following week’s edition of the paper every day for the next year? Could you make a million dollars?
This course started with a German stoplight, a joke, a book title, and a science fiction robot. Yes, I realize that this requires a little explanation.
There is an old joke about two men in the woods who encounter a bear. As one man bends down to put on running shoes, his companion points out that a man cannot outrun a bear, no matter the choice of footwear. The other man replies: “I don’t have to outrun the bear; I just have to outrun you!” This is how many economics decisions actually play out. If you are ahead of the crowd, you win!
As I was walking to work in Germany, a stoplight would direct pedestrian traffic across the street.
Over time, I learned the traffic light patterns, so I was able to actually start walking before the pedestrian light allowed it, much to the surprise and dismay of the Germans.
I realized that if this were us buying stocks, I would be rich because I had “outrun” them.
Robert Heinlein, in his book Friday, tells of an android whose job it is to find correlations between all of the events in the world in order to determine causation (and thus, prediction.)
This got me thinking about whether or not it was possible that seemingly unrelated events had a causative “butterfly effect.”
Another book that I read, If It’s Raining In Brazil, Buy Starbucks, moved my speculations out of the realm of science fiction. I realized that the ability to use unlikely indicators, combined with sound analysis and careful modesty, could actually help “outrun” all of the so-called experts who were trying to “outrun the bear.”
Thus was born Econopolicy.
Adult accomplishments:
- Predictive mathematical model of the global economy
- App/user interface to make the predictions accessible to others than just the modelers
- Scholarly economic article submitted to a journal for publication
- Regular economic blog (generally bi-weekly) about your discoveries that you are making from the regression analysis
Transferable skills:
- Ability to predict the global economy to a calculated level of uncertainty
- Ability to mathematically model various problems in life so as to find rational solutions
- Working knowledge of the scholarly publication process
- Ability to design a user interface/app to "translate" technical knowledge to an end user
- Ability to communicate technical information in writing to a broader adult audience
What careers will this course give me a leg up on?
- Broker - Average Salary: $67,310 (https://www.careeronestop.org)
- Hedge Fund Manager - Average Salary: $100,866 (www.payscale.com)
- Investment Banker - Average Salary: $139,451 (https://www.glassdoor.com)
- Personal Financial Planner - Average Salary: $90,530 (https://www.careeronestop.org)
- App Developer - Average Salary: $85,773 (https://www.indeed.com)
- Economics Professor - Average Salary: $95,770 (https://www.careeronestop.org)
- Retired and Living on Your Investment Income - Average Salary: "Sky's the Limit!"
General syllabus (Subject to change as needed)
- Course Start: 22 August 2022
- Week 1:
- Template setup
- Python User-Defined Function
- Google Finance Tutorial
- Local Article Analysis
- Week 2:
- Start Data Gathering Engine (Google Finance)
- Python: write a column of data to an Excel column/sheet/file
- National Article Analysis
- Week 3:
- Python: Write the elements of an Excel row into a column
- International Article Analysis
- Week 4:
- Python: Graph two columns of data with respect to each other
- Local Article Analysis
- Week 5:
- Template Check
- Python: Graph two columns of data with respect to time
- National Article Analysis
- Week 6:
- Blog relationship between two Analytically Linked Variables
- Python: Sort two columns of data and then copy the sorted data to another Excel location
- International Article Analysis
- Week 7:
- Python: Perform calculations (Technical Indicators) on one column of data and write it in another column
- Local Article Analysis
- Limits Bounding Analysis (LBA) #1
- Journey of Learning Narrative (JOLN) #1
- Week 8:
- Blog relationship between one Study Variable and its Technical Indicators (based on graphs)
- National Article Analysis
- Week 9:
- Template Check
- Python: Perform quadratic and cubic regression on two Study Variables
- International Article Analysis
- Week 10:
- Blog relationship between two Study Variables (based on regression analysis)
- Python: use curve_fit with long objective function on two Study Variables
- Local Article Analysis
- Week 11:
- Python: Write data column to Excel, based on User-Inputted ticker symbol
- National Article Analysis
- Week 12:
- Blog a Sector Study Variable
- Python: User defined function returning a third variable's value when two other data sets "intersect"
- International Article Analysis
- Week 13:
- Model Setup
- Python: Web scraping a single data point from a financial data website
- Local Article Analysis
- Week 14: Thanksgiving Week
- Blog Industry Study Variable
- Python: Automate web scraping function to update the model daily
- National Article Analysis
- Week 15:
- Python: Full Model Setup (extended deadline)
- International Article Analysis
- LBA #2
- JOLN #2
- Week 16:
- Python: Initial UI for Full Model
- Local Article Analysis
- Christmas Break: 13 December 2022 - 2 January 2023
- Week 17:
- Python: UI Refinement
- National Article Analysis
- Week 18:
- Blog Commodities Study Variable
- Python: Add Bayesian calculations to model (extended deadline)
- International Article Analysis
- Week 19:
- Local Article Analysis
- Week 20:
- Blog Currency Study Variable
- Python: UI and Program Refinement to convert to executable file
- National Article Analysis
- LBA #3
- JOLN #3
- Week 21:
- Python: UI and Program automation refinement for Beta Testing
- International Article Analysis
- Week 22:
- Blog Country Market Index Study Variable
- Python: Create Executable File
- Local Article Analysis
- Week 23:
- Beta Test #1
- National Article Analysis
- Week 24:
- Blog Country Sovereign Bond Study Variable
- Beta Test #2
- International Article Analysis
- Week 25:
- Python: Model Refinement
- Python: UI Refinement
- Local Article Analysis
- Week 26:
- Blog your "win rate" on your Article Predictions
- Beta Test #3
- National Article Analysis
- Week 27:
- Python: Model Refinement
- Beta Test #4
- International Article Analysis
- Week 28:
- Blog Markets Study Variable
- Python: Model and Program Refinement
- Local Article Analysis
- Week 29:
- App distribution research and decisions
- Python: Model and UI Refinement
- Beta Test #5
- National Article Analysis
- LBA #4
- JOLN #4
- Week 30:
- Blog Top-Performing Study Variable
- APP RELEASED!!!
- International Article Analysis
- Spring Break: 11 - 17 April 2023
- Week 31:
- Scholarly Publication Research
- Local Article Analysis
- Week 32:
- Draft Scholarly Article on most interesting finding
- National Article Analysis
- Week 33:
- Article Peer Critique
- International Article Analysis
- Week 34:
- ARTICLE REVISION AND SUBMISSION!!!
- Local Article Analysis
- Week 35:
- Blog on Journey of Learning Through the Course
- National Article Analysis
- Week 36:
- Final LBA
- Final JOLN
- Course End: 27 May 2023
Expected work load
- Typically one or more tasks that you must perform to move your project iteratively "down the road"
- One or more discussion questions from the teacher to answer
***All of this is designed to take you about 5 focused hours per week, which is less than you would have if you were attending class in a traditional school.
How can I write this course up on a high school transcript?
- As an Economics credit, given the breadth of coverage of the prediction model that the students are developing and the interrelationships that they have explored in the creation of their model, as well as the scholarly writing that they will submit as their article to a scholarly journal
- As an Applied Mathematics credit, given the extensive use of regression modeling and conditional probability that is built into the modeling process for calculating the predictions and the level of uncertainty associated with those predictions.
- As a Computer credit, given the different applications that the students will be both using and developing in order to create a user interface that is accessible and useful.
- As a Technical Writing credit, given the students' regular blog posts about their growing mathematical model.