Symposium

Of Rising ScholarsFall 2022

Dhruva will be presenting at The Symposium of Rising Scholars on Saturday, September 24th! To attend the event and see Dhruva's presentation,

Register here!
Go to Polygence Scholars page
Dhruva Paul's cover illustration
Polygence Scholar2022
Dhruva Paul's profile

Dhruva Paul

BASIS Independent Silicon ValleyClass of 2023Fremont, California

About

Projects

  • "Neural Network model predictions of monthly changes in Apple stock based on the company’s current and past financial data" with mentor Ethan (Sept. 6, 2022)

Project Portfolio

Neural Network model predictions of monthly changes in Apple stock based on the company’s current and past financial data

Started Apr. 16, 2022

Abstract or project description

Neural Network model predictions of monthly changes in Apple stock based on the company’s current and past financial data

With the rise of increasingly powerful machine learning algorithms, many have applied these concepts to the stock market in the hopes of creating a portfolio with the maximum amount of profit possible. However, most predictors simply rely on data derived from stock prices themselves in order to make these predictions, such as candlestick trends and patterns. The model this project is working on will focus on one company, Apple, and predict its stock with not only previous stock prices of the company, but also the stock prices of the NASDAQ, of which Apple is a part of. The model will also take into account the stock prices of the other major players of the NASDAQ, such as Amazon and Netflix. In addition, the model will input the financial data of the company, including variables such as the company’s revenue, gross profit, as well as other financial metrics such as gross profit margin and return on equity. The global price of materials of Apple’s most bought products will also be accounted for. These series extend from 2017 to 2022, providing 5 years worth of data. The model will utilize a neural network to identify patterns within this data and determine the monthly change in Apple stock. I chose a neural network in order to use a deep learning model to go through hundreds of data points in order to find trends within the data that would take a human ages to uncover.