Crypto-currencies (Bitcoin) trading & Transfer Learning applications

An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates strategy robustness by applying Rademacher random vectors for anti-overfitting analysis.

Method to use rolling optimization with 3D LSTM arrays. Explores integrating multi-asset portfolio with embedding layer.

Utilized time series, statistic, ML and NLP models to practice. Topics include stock forecasting (algorithm trading), US 2024 presidential election and customer sentimental review.

Oil Production Flow Rate Prediction with Deep Neural Network Algorithm such as Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM). This Model will testing with Validation method called Walk-Forward Validation (WFV). Basically the validation seperate in two part, the first WFV over actual data and WFV over predicted data.