Sailun Zhan, Xinwu Yang, Aolong Li, Amin Idelhaj, Zongze Liu
The objective of this project is to predict the short-term high and low prices of the SPY ETF, leveraging historical price data and technical indicators. Using high-frequency 1-minute interval data from AlphaVantage, we will employ machine learning and time-series analysis techniques (e.g. LSTM) to process prior price movements and technical indicators like moving averages. The goal is to create a versatile model capable of providing accurate short-term price forecasts to aid investment decision-making, with the understanding that financial market predictions inherently carry a degree of uncertainty due to various unpredictable factors.