https://github.com/alexracape/lego-learner

Using machine learning and principles from finance to trade lego sets
https://github.com/alexracape/lego-learner

Last synced: 3 months ago
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Using machine learning and principles from finance to trade lego sets

• Host: GitHub
• URL: https://github.com/alexracape/lego-learner
• Owner: alexracape
• Created: 2023-04-30T22:48:56.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-11-22T16:53:21.000Z (about 1 year ago)
• Last Synced: 2023-11-22T17:46:26.525Z (about 1 year ago)
• Language: Python
• Size: 6.56 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-lego-machine-learning - Lego Learning: Using Machine Learning to Predict the Future Value of Lego Sets [2023.11 - Using machine learning algorithms to predict future prices of sets. (Price Prediction / Code)

README

        
# lego-learner

Using machine learning and principles from finance to trade lego sets

## The Data

This project uses a combination of data from two API's

- Current Price - Bricklink API as of 05/10/2023

- List prices and features - Brickset API as of 05/10/2023

Check it out on [Kaggle](https://www.kaggle.com/datasets/alexracape/lego-sets-and-prices-over-time)

## The Model

Used a random forest and neural network and contrasted resulsts across the two models

## The Results

The models were able to predict list price and current market price extremely well from our selected features.

Our model was able to consistently beat the S&P 500 and an equal weighted portfolio across all lego sets produced in that year.

We analyzed feature importanace for determining list price.

We used the model to make a price forecast for the next five years.

Detailed results, plots, and analysis are all in `poster.pdf`.