stock-trader 0.0.4

Stock Trader

Overview

Stock Trader retrieves historical stock data for one or more stocks, runs one or more trading algorithms against the historical data optimizing algorithm settings on each pass, and picks the most profitable way to trade each stock. It then accepts a stream of current information about each of the stocks watching for a buy-in point that has a high probability of profit. It then either alerts the user to buy or, alternatively, can directly send a buy order to a broker’s API. It then continues to monitor the stream of current information about each of the stocks watching for either a drop in the probability of continued profit of the current position or for another stock’s probability of profit to go higher than that of the current position. It will then either alert the user to sell the current position or, alternatively, can directly send a sell order to a broker’s API.

Features

Until version 1.0, this should be considered a work in progress. Not all features exist yet.

Planned features before version 1.0 are:

• Generic Interface for Historical Stock Data Retrieval with several back ends - TD Ameritrade (via tda-api) - More back ends will be added as time permits

• Backtesting Interface - Pluggable profit probability functions

• Generic Broker Interface for placing orders with several back ends - TD Ameritrade (via tda-api) - More back ends will be added as time permits

Dependencies

Python ^3.6.1 Typer ^0.3.2

Colorama ^0.4.4 (optional extra - colorizes command line interface) Shellingham ^1.4.0 (optional extra - detects shell to make adding shell completion easier)

Installation

You can install Stock Trader via pip from PyPI:

$ pip install stock_trader

Usage

Please see the Command-line Reference for details.

Contributing

Contributions are very welcome. To learn more, see the Contributor Guide.

License

Distributed under the terms of the MIT license, Stock Trader is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

Credits

This project’s skeleton was generated from @cjolowicz’s Hypermodern Python Cookiecutter template using Cookiecutter.