LSTM Networks
Experimenting with architectures for time-series forecasting
This is a note where I downloaded publically available stock price data and compared a few different ways to implement LSTM for the purpose of time series forecasting. The note also includes EDA and hypothesis testing, discusses value-at-risk (VaR) as a risk measure through historical sampling.
More information can be found on github.