imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict
A hybrid ARIMA-LSTM neural network model that predicts future price correlation coefficients between two assets for portfolio optimization.
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The project combines ARIMA and LSTM neural networks to forecast correlation coefficients between asset pairs. ARIMA handles linear patterns in historical price data while LSTM captures temporal dependencies and nonlinear relationships. The hybrid model outperformed traditional financial prediction methods including the full historical model, constant correlation model, single index model, and multi group model in empirical testing.
Frequently asked
- What is imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict?
- A hybrid ARIMA-LSTM neural network model that predicts future price correlation coefficients between two assets for portfolio optimization.
- Is ARIMA-LSTM-hybrid-corrcoef-predict open source?
- Yes — imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict is an open-source project tracked on heatdrop.
- What language is ARIMA-LSTM-hybrid-corrcoef-predict written in?
- imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict is primarily written in Jupyter Notebook.
- How popular is ARIMA-LSTM-hybrid-corrcoef-predict?
- imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict has 433 stars on GitHub.
- Where can I find ARIMA-LSTM-hybrid-corrcoef-predict?
- imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict is on GitHub at https://github.com/imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict.