MZ

Sep 2022 – Dec 2022 · 4 mos

Wall Street, New York/ remote

I have:

• Design an imputation algorithm that interpolates the missing values using the data from the surrounding values justified by correlations.
• Training the model on the whole dataset to find the best prediction for future stock market changes.
• Applied time series analysis to model the data and build the forecasting model (LSTM) with MSE: 0.11 given range of output [-30, 30].

matt@localhost:~/> echo forecasting_sp500.png; echo lstm.png