ib-trading-models-and-backtester's Introduction

Readme

This is an enhancement to the current version of High Frequency Trading Model with IB @ https://github.com/jamesmawm/High-Frequency-Trading-Model-with-IB.

In this version, I've decoupled modules, used functional programming styles, made things simpler and enable switching between different strategies. Oh, and a custom backtester too with bid/ask price simulated events (Zipline gave my code cancer).

Again, these files are for evaluation purposes only and do not constitute real profitable trading models.

Features

Reuse multiple strategies on the same IB framework. See src/Strat-Empty.py for a template.
src/Backtester/* contains custom backtester which reads in a CSV file. Supports limit orders-based strategies with bid ask price simulation.

Strategies

Strat-Pairs.py: Pairs trading through cointegration, using OLS and Pandas.
Strat-LmtOrdrs.py: Limit-order based strategy with GUI dashboard. Works with backtester.
Strat-CorrelRptr.py: Stores ticks in a dataframe and reports the correlations.

How To

Connecting to IB and getting live ticks in 3 simple steps:

self.ibhft = ibHFT.IbHFT()
self.ibhft.set_connection_with_api_gateway(False)
self.ibhft.start_data_stream(self.on_started
                                 , self.on_tick
                                 , STOCKS_TO_STREAM
                                 , self.on_position_changed)

Same 3 simple steps in getting historical data:

self.ibhft = ibHFT.IbHFT()
self.ibhft.set_connection_with_api_gateway(False)
self.ibhft.start_historical_data_stream(self.stocks_to_stream
                                  , self.duration
                                  , self.interval
                                  , self.process_historical_data)

For backtesting, same 3 simple steps:

self.ibhft = bt.Backtester()
self.ibhft.set_csv_file("ticks 10 mins - Jun 25 2014.csv")
self.ibhft.start_data_stream(self.on_started
                                 , self.on_tick
                                 , STOCKS_TO_STREAM
                                 , self.on_position_changed)

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