Backtesting framework for high-frequency trading strategies
A more complete set of examples can be found in the examples directory.
from dyno import Backtest, Strategy
from dyno.helpers import build_basic_signal_strategy
# produce long/short entry signals
class TradeSignals(Strategy):
def on_mid_market_price(self, unix_ts_ns, inputs):
return []
# backtest data and strategy pipeline
events = []
pipeline = build_basic_signal_strategy(TradeSignals)
# the backtest, which can be executed more than once
backtest = Backtest(pipeline, events)
# run the backtest and print results
results = backtest.execute()
print(results)Contains core dyno components: strategy pipeline and backtest class.
The pipeline is a sequence of callable objects which are folded over
from left to right: stage 1 -> stage 2 -> ... -> stage n.
Backtest class expects a pipeline object and an iterator which, when iterated over, produces events to feed into the pipeline.
Used by strategy module. Defines exchange, order book, and bank roll abstractions. Also houses fee schedules for common cryptocurrency exchanges.
Helper functions and classes.
Defines framework for building high-frequency trading strategies on-top of the pipeline and backtest abstractions.
Tests must be run from the root dyno directory. The makefile handles
it all for you. Use make test_all to run all tests. Or test individual
sub-packages:
make test_light
make test_dark
make test_http
make test_level4
make test_pipeworks