def run(config, testing, tickers, filename):
# Backtest information
title = ['Monthly Liquidate/Rebalance on 60%/40% SPY/AGG Portfolio']
initial_equity = 500000.0
start_date = datetime.datetime(2006, 11, 1)
end_date = datetime.datetime(2016, 10, 12)
# Use the Monthly Liquidate And Rebalance strategy
events_queue = queue.Queue()
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
ticker_weights = {
"SPY": 0.6,
"AGG": 0.4,
}
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Set up the backtest
backtest = TradingSession(
config,
strategy,
tickers,
initial_equity,
start_date,
end_date,
events_queue,
position_sizer=position_sizer,
title=title,
benchmark=tickers[0],
)
results = backtest.start_trading(testing=testing)
return results
def run_monthly_rebalance(config, testing, filename, benchmark, ticker_weights,
title_str, start_date, end_date, equity):
config = settings.from_file(config, testing)
tickers = [t for t in ticker_weights.keys()]
# Set up variables needed for backtest
events_queue = queue.Queue()
csv_dir = config.CSV_DATA_DIR
initial_equity = PriceParser.parse(equity)
# Use Yahoo Daily Price Handler
price_handler = YahooDailyCsvBarPriceHandler(csv_dir,
events_queue,
tickers,
start_date=start_date,
end_date=end_date)
# Use the monthly liquidate and rebalance strategy
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
strategy = Strategies(strategy, DisplayStrategy())
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Use an example Risk Manager
risk_manager = ExampleRiskManager()
# Use the default Portfolio Handler
portfolio_handler = PortfolioHandler(initial_equity, events_queue,
price_handler, position_sizer,
risk_manager)
# Use the ExampleCompliance component
compliance = ExampleCompliance(config)
def run_monthly_rebalance(tickers, ticker_weights, title, start_date, end_date,
initial_equity):
testing = False
config = settings.from_file(settings.DEFAULT_CONFIG_FILENAME, testing)
# Use the Monthly Liquidate And Rebalance strategy
events_queue = queue.Queue()
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Set up the backtest
backtest = TradingSession(
config,
strategy,
tickers,
initial_equity,
start_date,
end_date,
events_queue,
position_sizer=position_sizer,
title=[title],
benchmark=tickers[0],
)
results = backtest.start_trading(testing=testing)
return results
def run(config, testing, tickers, filename):
# Set up variables needed for backtest
events_queue = queue.Queue()
csv_dir = config.CSV_DATA_DIR
initial_equity = PriceParser.parse(500000.00)
start_date = datetime.datetime(2006, 11, 1)
end_date = datetime.datetime(2016, 10, 12)
# Use Yahoo Daily Price Handler
price_handler = YahooDailyCsvBarPriceHandler(csv_dir,
events_queue,
tickers,
start_date=start_date,
end_date=end_date)
# Use the monthly liquidate and rebalance strategy
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
strategy = Strategies(strategy, DisplayStrategy())
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
ticker_weights = {
"SPY": 0.6,
"AGG": 0.4,
}
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Use an example Risk Manager
risk_manager = ExampleRiskManager()
# Use the default Portfolio Handler
portfolio_handler = PortfolioHandler(initial_equity, events_queue,
price_handler, position_sizer,
risk_manager)
# Use the ExampleCompliance component
compliance = ExampleCompliance(config)
# Use a simulated IB Execution Handler
execution_handler = IBSimulatedExecutionHandler(events_queue,
price_handler, compliance)
# Use the default Statistics
title = ["US Equities/Bonds 60/40 ETF Strategy"]
benchmark = "SPY"
statistics = TearsheetStatistics(config, portfolio_handler, title,
benchmark)
# Set up the backtest
backtest = Backtest(price_handler, strategy, portfolio_handler,
execution_handler, position_sizer, risk_manager,
statistics, initial_equity)
results = backtest.simulate_trading(testing=testing)
statistics.save(filename)
return results
class TestLiquidateRebalancePositionSizer(unittest.TestCase):
def setUp(self):
price_handler_mock = PriceHandlerMock()
ticker_weights = {"AAA": 0.3, "BBB": 0.7}
self.position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
self.portfolio = Portfolio(price_handler_mock,
PriceParser.parse(10000.00))
def test_will_add_positions(self):
"""
Tests that the position sizer will open up new positions with
the correct weights.
"""
order_a = SuggestedOrder("AAA", "BOT", 0)
order_b = SuggestedOrder("BBB", "BOT", 0)
sized_a = self.position_sizer.size_order(self.portfolio, order_a)
sized_b = self.position_sizer.size_order(self.portfolio, order_b)
self.assertEqual(sized_a.action, "BOT")
self.assertEqual(sized_b.action, "BOT")
self.assertEqual(sized_a.quantity, 60)
self.assertEqual(sized_b.quantity, 70)
def test_will_liquidate_positions(self):
"""
Ensure positions will be liquidated completely when asked.
Include a long & a short.
"""
self.portfolio._add_position("BOT", "AAA", 100,
PriceParser.parse(60.00), 0.0)
self.portfolio._add_position("BOT", "BBB", -100,
PriceParser.parse(60.00), 0.0)
exit_a = SuggestedOrder("AAA", "EXIT", 0)
exit_b = SuggestedOrder("BBB", "EXIT", 0)
sized_a = self.position_sizer.size_order(self.portfolio, exit_a)
sized_b = self.position_sizer.size_order(self.portfolio, exit_b)
self.assertEqual(sized_a.action, "SLD")
self.assertEqual(sized_b.action, "BOT")
self.assertEqual(sized_a.quantity, 100)
self.assertEqual(sized_a.quantity, 100)
def run_monthly_rebalance(config, testing, filename, benchmark, ticker_weights,
title_str, start_date, end_date, equity):
config = settings.from_file(config, testing)
tickers = [t for t in ticker_weights.keys()]
# Set up variables needed for backtest
events_queue = queue.Queue()
csv_dir = config.CSV_DATA_DIR
initial_equity = PriceParser.parse(equity)
# Use Yahoo Daily Price Handler
price_handler = YahooDailyCsvBarPriceHandler(csv_dir,
events_queue,
tickers,
start_date=start_date,
end_date=end_date)
# Use the monthly liquidate and rebalance strategy
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
#strategy = Strategies(strategy, DisplayStrategy())
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Use an example Risk Manager
risk_manager = ExampleRiskManager()
# Use the default Portfolio Handler
portfolio_handler = PortfolioHandler(initial_equity, events_queue,
price_handler, position_sizer,
risk_manager)
# Use the ExampleCompliance component
compliance = ExampleCompliance(config)
# Use a simulated IB Execution Handler
execution_handler = IBSimulatedExecutionHandler(events_queue,
price_handler, compliance)
# Use the default Statistics
title = [title_str]
statistics = TearsheetStatistics(config, portfolio_handler, title,
benchmark)
# Set up the backtest
backtest = Backtest(price_handler, strategy, portfolio_handler,
execution_handler, position_sizer, risk_manager,
statistics, initial_equity)
results = backtest.simulate_trading(testing=testing)
statistics.save(filename)
return results
def run(config, testing, tickers, filename):
# Backtest information
title = ['Monthly Liquidate/Rebalance on 60%/40% SPY/AGG Portfolio']
initial_equity = 500000.0
start_date = datetime.datetime(2006, 11, 1)
end_date = datetime.datetime(2016, 10, 12)
# Use the Monthly Liquidate And Rebalance strategy
events_queue = queue.Queue()
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
ticker_weights = {
"ewg.us": 0.4,
"ewq.us": 0.6,
}
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Set up the backtest
backtest = TradingSession(
config,
strategy,
tickers,
initial_equity,
start_date,
end_date,
events_queue,
position_sizer=position_sizer,
price_handler=DailyCsvBarPriceHandler('~/Desktop/stock-data/ETFs',
ext_data='txt',
init_tickers=tickers,
events_queue=events_queue,
start_date=start_date,
end_date=end_date),
title=title,
benchmark=tickers[0],
)
results = backtest.start_trading(testing=testing)
return results
def run(config, testing, tickers, filename):
# Backtest information
title = [
'Monthly Liquidate/Rebalance on 40%/30% 30% sz50/zz500/cyb Portfolio'
]
initial_equity = 300000.0
start_date = datetime.datetime(2010, 11, 1)
end_date = datetime.datetime(2018, 8, 18)
# Use the Monthly Liquidate And Rebalance strategy
events_queue = queue.Queue()
strategy = MonthlyLiquidateRebalanceStrategy(tickers, events_queue)
# Use the liquidate and rebalance position sizer
# with prespecified ticker weights
ticker_weights = {
"510050": 0.4,
"510500": 0.3,
"159915": 0.3,
}
position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
# Set up the backtest
backtest = TradingSession(
config,
strategy,
tickers,
initial_equity,
start_date,
end_date,
events_queue,
price_handler='tushare',
position_sizer=position_sizer,
title=title,
benchmark=tickers[0],
)
results = backtest.start_trading(testing=testing)
return results
def setUp(self):
price_handler_mock = PriceHandlerMock()
ticker_weights = {"AAA": 0.3, "BBB": 0.7}
self.position_sizer = LiquidateRebalancePositionSizer(ticker_weights)
self.portfolio = Portfolio(price_handler_mock,
PriceParser.parse(10000.00))