入门课：Neural networks for algorithmic trading. Simple time series forecasting
https://medium.com/machine-learning-world/neural-networks-for-algorithmic-trading-part-one-simple-time-series-forecasting-f992daa1045a

用于金融时序预测的神经网络：可改善经典的移动平均线策略
https://www.jiqizhixin.com/articles/2017-10-21

Deep-Trading Github
https://github.com/Rachnog/Deep-Trading

Kaggle: Predict stock prices with LSTM

https://www.kaggle.com/pablocastilla/predict-stock-prices-with-lstm

Binary Classification

1. https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python
2. https://www.kaggle.com/ldfreeman3/a-data-science-framework-to-achieve-99-accuracy

3. https://www.kaggle.com/mrisdal/exploring-survival-on-the-titanic

4. Nice GradientBoostingClassifier http://d0evi1.com/sklearn/gbdt/

Indicators/Signal Classifications

Stock Market Index Data and indicators for Day Trading as a Binary Classification problem
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5219605/

Stanford SL Book

http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf

Ernie Chan

The following example is inspired on the ‘Buy-on-Gap Model’ from Ernie Chan’s book: ‘Algorithmic Trading: Winning Strategies and Their Rationale’:

Pairs Trading Selection

https://www.maths.ox.ac.uk/system/files/attachments/593233.pdf

D.E Shaw

https://www.deshaw.com/articles/Alpha_2.pdf

Others

Pair Trading: https://r-forge.r-project.org/scm/viewvc.php/*checkout*/pkg/inst/doc/IntroductionToPairTrading.pdf?revision=6&root=pairtrading&pathrev=6

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.864.6632&rep=rep1&type=pdf

Pandas iterrow speed https://engineering.upside.com/a-beginners-guide-to-optimizing-pandas-code-for-speed-c09ef2c6a4d6

System

ShanCe http://www.shancetech.com/service