Code Monkey home page Code Monkey logo

rl-finalproject's Introduction

RL-FinalProject

Optimizing grid bot trading strategy with RL.
For now to run in you can simple do (right it uses the best parameters we were able to find by default)

grid_bot = GridBot()
grid_bot.trade(df_path)

It will contain all the relevant info inside.

To reproduce mentioned results with RL application, use venv (we used python3.9) defined by requirements.txt and run all cels in src/models/grid_bot_rl/test.ipynb

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
│   ├── processed           <- Market data with features.
│   └── raw                 <- Market data.
│
├── docs                    <- A default Sphinx project; see sphinx-doc.org for details
│
├── models                  <- Regular grid bot
│
├── notebooks               <- Jupyter notebooks. (Visualization & metrics)
│
├── references              <- Data dictionaries, manuals, and all other explanatory materials.
│
├── 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`
│
├── setup.py                <- makes project pip installable (pip install -e .) so src can be imported
├── src                     <- Source code for use in this project.
│   ├── __init__.py         <- Makes src a Python module
│   │
│   ├── data                <- Scripts to download market data
│   │   └── make_dataset.py
│   │
│   ├── features            <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models              <- Scripts to train models and then use trained models to make
│   │   │                      predictions
│   │   └── grid_bot_rl     <- Grid bot with adaptive orders.
│   │       │
│   │       └── test.ipynb  <- Notebook with experiment setup
│   │
│   └── visualization       <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini                 <- tox file with settings for running tox; see tox.readthedocs.io

Results for Regular bot 1 day

https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/total_1.png

Results for Regular bot 3 days

https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/total_3.png

Results for Regular bot 7 days

https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/total_7.png

Results of RL approach

https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/RL_3.png https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/RL_1.png https://github.com/sacr1f1ce/RL-FinalProject/blob/main/reports/figures/RL_act.png


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

rl-finalproject's People

Contributors

sacr1f1ce avatar viroslav avatar v-vskv-v avatar

Stargazers

 avatar

Watchers

 avatar

Forkers

viroslav

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.