Problem Statement: Are the forecasting methods taught in the classroom profitable trading strategies?
This repository contains all the code and data that I will be using to predict the next days price of NVIDIA (NVDA). This project will be used as a refresher/learning project for me. I want to improve upon my ML skills and solidify my traditional forecasting knowledge, and hopefully teach others that find this page along the way! I have implemented the models in this repository using R before, but this project will be based in Python, which I have not used for traditional forecasting methods. All of my code will provide in-depth explanations. I will have my code drafts in the repository, which will be updated daily.
Finished product: Website that contains daily forecasting and trading updates. Additionally, there will be videos to watch to teach yourself the basics of forecasting.
Models to use for forecasting
- Smoothing models
- Autoregressive Model/Moving Average Model
- ARMA/ARIMA
- LSTM
- Maybe up down forecast w Logistic Regression?
- Random Walk or coin flip comparison
Sources:
- https://economics.ut.ac.ir/documents/3030266/14100645/Jeffrey_M._Wooldridge_Introductory_Econometrics_A_Modern_Approach__2012.pdf
- https://vipul-bhatt.github.io/Econ-483-Notes/ (Shoutout Prof. Bhatt @ James Madison University)
- https://www.sas.upenn.edu/~fdiebold/Teaching221/FullBook.pdf
- https://otexts.com/fpp2/