In this Final Year Engineering project, the aim is to predict the stock prices based on the historical and current trends of a particular stock and predicting how that stock may perform shortly. The initial steps in building this project are: -
- Data gathering for the stocks. i.e. collecting as much as possible data, for training the machine learning algorithm.
- Back-testing the algorithm with the past events and observing the output of the algorithm and matching it with the correct output to minimize the error coefficient in the stock prediction.
- Finally, as the machine learns from the inputs it receives, it will start to create stronger correlations in patterns and refine its forecasts over time. As new data and drivers become known or available, they can be used to update the model, closing the iteration loop
Link for demo of the neural network model - https://youtu.be/uw-NUykRE6k
All the resources for the project (source code, project report, poster draft etc) - https://drive.google.com/drive/folders/1iWzr6DhuEu3YpqLMc6k_XwXtI8wbh90i?usp=sharing