Elon Early Warning System (EEWS)

Overview

The stock price prediction program, named for the volatility of Tesla (TSLA) stock caused by Elon Musks' tweets on X, formerly known as Twitter, is a project that bridges the gap between coding and my stock portfolio. This project is still in the early stages of development, as such, it still has a long way to go before it will be deployed for real trading decisions.

(GitHub Link)

Quick Summary

  • Currently, only predictions based on past closing prices, opening prices, high, low, and adjusted close per day are supported.

  • This project is still under construction.

  • Future prospects:

    • Model training will be improved by implementing data regarding bollinger bands, moving averages, and stochastic oscillators.
    • Implementing a web scraper combined with the Hugging face transformer library and a localized and distilled LLM to quantify the effects of Musk’s tweets on the stocks being tracked.

Key Features

  • Applied a Long Short-Term Memory (LSTM) model leveraging Adaptive Moment Estimation (ADAM) optmizer for gradient descent calculation.
  • As of now, the model is mainly trained on the daily closing prices, opening prices, high, low, and adjusted close of each stock it predicts.
  • In the future, it will take into account opening prices, trade volume, bollinger bands, and the stochastic oscillator.
  • The current dataset used has 6 features and 28 million entries.

Tools Used

  • Cuda
  • cuDNN
  • Adam Optimizer
  • LSTM
  • Jupyter Notebook
  • PyTorch
  • Python

Images

Price Predictions vs Historical Data

Predictions NVDA