Quant stuff

Python code samples:

1. Tensorflow RNN LSTM-based stock / ETF return forecasting system (multiple time-frames). The system includes (A) forward test (B) batch training (C) required data transformations (normalization, etc.) https://github.com/wolfws/quant/tree/master/ann

2. PCA process (for factor research): https://github.com/wolfws/quant/tree/master/linear

3. Monte-Carlo simulation generic process including Cholesky decomposition. Can be used for pricing and other scenario path simulations: https://github.com/wolfws/quant/tree/master/mc

4. Portfolio Factors, including (A) define alphas / factors (B) regress factors against the instruments returns (C) choose the factors that best explain the target returns (D) use those factors to explain out of sample datasets, etc. https://github.com/wolfws/quant/tree/master/portfolio/factors

5. Basic portfolio optimization using convex optimization library https://github.com/wolfws/quant/tree/master/portfolio/optimization

6. Portfolio rebalancing & continuous risk / PnL calculations: https://github.com/wolfws/quant/tree/master/portfolio/rebalancing

7. Double diagonal calendar spread trading algorithm (base scenarions): https://github.com/wolfws/quant/tree/master/strats/options/diagonal