Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
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This trading-gym is the first trading for agent to train with episode of short term trading itself.
Analysis of High Frequency Trading on Bitcoin exchanges
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
- source-energy-balance
- canopy
- soil
- radiometric-temperatures
Research experiments exploring uncommon quant techniques.
- analysis
- jupyter-notebook
- python
- quant
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
- fine-tuning
- vgg16
- resnet18
- densenet121
💸 Papers and Code Implements for Quantitative-Trading
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.