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TEAM
Algebros
Sailun Zhan, Xinwu Yang, Aolong Li, Amin Idelhaj, Zongze Liu
![clear.png](https://static.wixstatic.com/media/55f531_b9f3f13ce3aa4af78af2cc6d3563b81b~mv2.png/v1/fill/w_3,h_3,al_c,lg_1,q_85,enc_auto/clear.png)
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.
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