advanced-algorithmic-trading

389
commands, so that the positions can be closed or shorted:
def go_short_units(self):
"""
Go short the appropriate number of "units" of the
portfolio to open a new position or to close out
a long position.
"""
for i, ticker in enumerate(self.tickers):
if self.weights[i] < 0.0:
self.events_queue.put(SignalEvent(
ticker, "BOT",
int(floor(-1.0*self.qty*self.weights[i])))
)
else:
self.events_queue.put(SignalEvent(
ticker, "SLD",
int(floor(self.qty*self.weights[i])))
)
zscore_trade takes the latest calculated z-score of the portfolio market price and uses this
to long, short or close a trade. The logic below encapsulates the "Bollinger Bands" aspect of the
strategy.
If the z-score is less than the negative of the entry threshold, a long position is created.
If the z-score is greater than the positive of the entry threshold, a short position is created.
Correspondingly, if the strategy is already in the market and the z-score exceeds the negative of
the exit threshold, any long position is closed. If the strategy is already in the market and the
z-score is less than the exit threshold, a short position is closed:
def zscore_trade(self, zscore, event):
"""
Determine whether to trade if the entry or exit zscore
threshold has been exceeded.
"""
# If we’re not in the market...
if self.invested is None:
if zscore < -self.entry_z:
# Long Entry
print("LONG: %s" % event.time)
self.go_long_units()
self.invested = "long"
elif zscore > self.entry_z:
# Short Entry
print("SHORT: %s" % event.time)
self.go_short_units()
self.invested = "short"
# If we are in the market...