PyTrendFollow
Unverified Trend strategy on Multi by chrism2671. BotFinder score 18 out of 100.
PyTrendFollow - systematic futures trading using trend following
Source: github
BotFinder analysis pending.
PyTrendFollow
PyTrendFollow - Systematic Futures Trading using Trend Following Introduction This program trades futures using a systematic trend following strategy, similar to most managed futures hedge funds. It produces returns of around ~20% per year, based on a volatility of 25%. You can read more about trend following in the /docs folder. Start with introduction to trend following. If you just want to play with futures data, see working with prices. Features Integration with Interactive Brokers for fully automated trading. Automatic downloading of contract data from Quandl & Interactive Brokers. Automatic rolling of futures contracts. Trading strategies backtesting on historical data Designed to use Jupyter notebook as an R&D environment. Installation Data sources The system supports downloading of price data from 1. Quandl 1. Interactive Brokers (IB) It is recommended (though not required) to have data subscriptions for both Quandl and IB. Quandl has more historical contracts and works well for backtesting, while IB data is usually updated more frequently and is better for live trading. To u
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