Multi-asset, multi-strategy, event-driven trade execution and management platform for trading common markets autonomously on 1min+ timeframes.
Trade FX, crypto, CFD's, traditional markets etc (any venue with an API) with unified portfolio management
Allocation-based risk management (allocate x% exposure to specific strategies)
Strategy feature library - assemble new strategies from existing features
Trade consent via Telegram (or write your own messaging client) - Accept, veto or tweak trade setups prior to triggering
Account multicasting - trade as many accounts on as many platforms as desired
UI - web dashboard for portfolio stats and individual trade metrics
Integration with Backtrader
Blockchain-based strategy auditing - publish trade signals to IPFS and Ethereum/BSC to empirically prove win rate over time
Accounting and compliance reporting
|Binance||NA||Crypto spot & derivatives|
|FTX||NA||Crypto spot, options & derivatives|
|Deribit||NA||Crypto derivatives & options|
|IG Markets||NA||FX, equity, commodity & index CFD's|
|Interactive Brokers||NA||FX, equity, commodity & index CFD's|
|Huobi Global||NA||Crypto spot|
1 minute resolution OHLCV bars for all watched instruments are stored with MongoDB (or please write your own DB wrapper and submit a pull request).
Software currently works for 1Min+ resolution strategies with tick-resolution strategy support planned later. With this in mind, the software converts tick data to 1 min bars where live tick data is available, but doesn't store ticks locally (i.e. it can handle tick data but doesnt yet use it).
Strategy implementations are not included. A simple moving average cross model is included as a guide only. Custom strategy implementations, collaboration or any other enquiries: firstname.lastname@example.org.
Pull requests and discussion regarding new features are very welcome, please reach out.
TA-LIB - https://mrjbq7.github.io/ta-lib/
Backtrader - https://www.backtrader.com/
Based on architecture described by Michael Halls-Moore at QuantStart.com (qsTrader), and written works by E. Chan and M. Lopez de Prado. Thanks all.