advanced-algorithmic-trading

453
if event.type == EventType.TICK or event.type == EventType.BAR:
self.cur_time = event.time
# Generate any sentiment events here
if self.sentiment_handler is not None:
self.sentiment_handler.stream_next(
stream_date=self.cur_time
)
self.strategy.calculate_signals(event)
self.portfolio_handler.update_portfolio_value()
self.statistics.update(event.time, self.portfolio_handler)
elif event.type == EventType.SENTIMENT:
self.strategy.calculate_signals(event)
elif event.type == EventType.SIGNAL:
self.portfolio_handler.on_signal(event)
elif event.type == EventType.ORDER:
self.execution_handler.execute_order(event)
elif event.type == EventType.FILL:
self.portfolio_handler.on_fill(event)
else:
raise NotImplemented(
"Unsupported event.type ’%s’" % event.type
)
That concludes the modifications to QSTrader. These changes are now in the latest version
found on Github, so if you wish to replicate these strategies, make sure to update your local
QSTrader version.
30.4.2 Sentiment Analysis Strategy Code
The full code listings for this strategy and backtest are presented at the end of the chapter.
The above modifications to QSTrader provide the necessary structure to run a sentiment
analysis strategy. However it remains to be shown how the above entry and exit rules are
actually implemented. As it turns out the majority of the "hard work" has been done in the
above modules. The strategy implementation itself is relatively straightforward.
As always the first task is to import the necessary libraries. There are no surprises here,
simply Python2/3 compatibility and the basic QSTrader objects that interact with a Strategy
subclass:
# sentdex_sentiment_strategy.py
from __future__ import print_function
from qstrader.event import (SignalEvent, EventType)
from qstrader.strategy.base import AbstractStrategy
The new subclass is called SentdexSentimentStrategy. It only requires a list of tickers to
act upon, a handle to the events queue, a sent_buy integer sentiment threshold entry value and