advanced-algorithmic-trading

441
self.minutes += 1
# Allow enough time to pass to populate the
# returns feature vector
if self.minutes > (self.lags + 2):
pred = self.model.predict(
self.cur_returns.reshape((1, -1))
)[0]
# Long only strategy
if not self.invested and pred == 1:
print("LONG: %s" % event.time)
self.events_queue.put(
SignalEvent(
self.tickers[0], "BOT", self.qty
)
)
self.invested = True
if self.invested and pred == -1:
print("CLOSING LONG: %s" % event.time)
self.events_queue.put(
SignalEvent(
self.tickers[0], "SLD", self.qty
)
)
self.invested = False
# intraday_ml_backtest.py
import click
import datetime
from qstrader import settings
from qstrader.compat import queue
from qstrader.price_parser import PriceParser
from qstrader.price_handler.iq_feed_intraday_csv_bar import \
IQFeedIntradayCsvBarPriceHandler
from qstrader.strategy import Strategies, DisplayStrategy
from qstrader.position_sizer.naive import NaivePositionSizer
from qstrader.risk_manager.example import ExampleRiskManager
from qstrader.portfolio_handler import PortfolioHandler
from qstrader.compliance.example import ExampleCompliance
from qstrader.execution_handler.ib_simulated import \
IBSimulatedExecutionHandler
from qstrader.statistics.tearsheet import TearsheetStatistics
from qstrader.trading_session.backtest import Backtest