tradingbuddy - cs50p final project

Video Demo: https://youtu.be/Ogssa1nArto

about this project...

i've been involved in financial markets for nearly ten years. with that experience i've learned that simple statistics can be a useful aid when deciding which markets to trade. tradingbuddy is a python application that when given a dictionary of futures contract symbols generates a .pdf report with statistics and visuals to get a mathematical feel for a markets' movement.

summary statistics include:

• current price relative to 3-month high and low
• daily move standard deviations
• 3-month percent return

here's a simple schema of what the .pdf looks like!

trading buddy currently supports

• data download from databento
• statistical calculations via pandas
• plot generation with matplotlib
• pdf writing using fpdf2

** please note that project.py is the entire project in one file per cs50p's submission standards. during development i tried to break functionality into separate modules. those modules, in order of process, are za_databento.py, zb_pandas.py, zc_matplotlib.py and zd_fpdf.py. app.py contains the primary application logic and imports the required functions from each z_ module. **

stack...

tradingbuddy uses end of day closing prices over a three month period. the data is fetched via the databento API.

the data comes in very cleanly from databento and i use pandas and numpy to run calculations. the .csv data is stored on disk along with a percentage return graphic generated with matplotlib. the results for each symbol's statistics are stored in in-memory ordered dictionary.

finally, the results for each symbol are written to a .pdf using a custom pdf class from the fpdf2 library. modifying the default class allowed me to easily embed shapes with custom text, headers, and footers.

---

notes:

• databento docs
• databento python wrapper
• databento smart symbology
• fpdf2 docs

---

reference:

virtual environments

Create a Python3 Virtual Environment: python3 -m venv env

Activate the Virtual Environment: source env/bin/activate

Deactivate the Virtual Environment: deactivate

To Remove a Virtual Environment: sudo em -rf venv

requirements.txt

Automagically create a requirements.txt file: pip3 freeze > requirements.txt

pytest

python3 -m pytest

future features:

1. additional pages for more asset classes
2. aws pdf hosting & mailchimp automations?
3. pairs trading ratios
4. hedge ratios
5. always styling

broken up into five main asset classes

• equities: /MES, /MNQ, /MYM, /M2K
• interest rates: /2YY, /5YY, /10Y, /30Y
• cryptos: /MBT, /MET
• foreign exchange: /M6E, /M6A, /M6B
• commodities: /MGC, /SIL, /MHG, /MCL