namitrakali/stock-gan-simulation

An experiment to determine whether Transformer Generative Adversarial Networks can simulate stock movements, similar to Monte Carlo Simulations.

RL-GAN-Stonk-Prediction

An experiment to see if Transformer Generative Adversarial Networks can forecast a range of movement for a stock like in Monte Carlo Simulation.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
                          generated with `pip freeze > requirements.txt`

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Project based on the cookiecutter data science project template. #cookiecutterdatascience