def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls()
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler, self.events,
self.dataHandler.getStartDate(),
self.assets, self.initialCapital,
self.benchmark, self.portfolioType)
self.executionHanlder = self.executionHanlderCls(
self.events, self.dataHandler, self.portfolio, self.logger)
self.orderBook = OrderBook()
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls()
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler,
self.events,
self.dataHandler.getStartDate(),
self.assets,
self.initialCapital,
self.benchmark,
self.portfolioType)
self.executionHanlder = self.executionHanlderCls(self.events, self.dataHandler, self.portfolio, self.logger)
self.orderBook = OrderBook()
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
class Backtest(object):
def __init__(self,
initial_capital,
heartbeat,
data_handler,
execution_handler,
portfolio,
strategy,
logger,
benchmark=None,
refreshRate=1,
plot=False,
portfolioType=PortfolioType.CashManageable):
self.initialCapital = initial_capital
self.heartbeat = heartbeat
self.dataHandler = data_handler
self.executionHanlderCls = execution_handler
self.portfolioCls = portfolio
self.strategyCls = strategy
self.symbolList = self.dataHandler.symbolList
self.tradable = self.dataHandler.tradableAssets
self.assets = setAssetsConfig(self.tradable)
self.events = queue.Queue()
self.dataHandler.setEvents(self.events)
self.signals = 0
self.orders = 0
self.fills = 0
self.num_strats = 1
self.benchmark = benchmark
self.refreshRate = refreshRate
self.counter = 0
self.plot = plot
self.logger = logger
self.portfolioType = portfolioType
if portfolioType == PortfolioType.FullNotional:
self.initialCapital = np.inf
self._generateTradingInstance()
def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls()
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler,
self.events,
self.dataHandler.getStartDate(),
self.assets,
self.initialCapital,
self.benchmark,
self.portfolioType)
self.executionHanlder = self.executionHanlderCls(self.events, self.dataHandler, self.portfolio, self.logger)
self.orderBook = OrderBook()
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
def _runBacktest(self):
i = 0
while True:
i += 1
if self.dataHandler.continueBacktest:
self.strategy.symbolList, self.strategy.tradableAssets = self.dataHandler.updateBars()
else:
break
while True:
try:
event = self.events.get(False)
except queue.Empty:
break
if event is not None:
if event.type == 'MARKET':
self.counter += 1
self.strategy._updateSubscribing()
self.portfolio.updateTimeindex()
if self.counter % self.refreshRate == 0:
self.strategy._handle_data()
elif event.type == 'SIGNAL':
self.signals += 1
self.portfolio.updateSignal(event)
elif event.type == 'ORDER':
self.orders += 1
event.assetType = self.assets[event.symbol]
self.orderBook.updateFromOrderEvent(event)
fill_event = self.executionHanlder.executeOrder(event)
self.fills += 1
if fill_event:
self.orderBook.updateFromFillEvent(fill_event)
self.portfolio.updateFill(fill_event)
time.sleep(self.heartbeat)
def _outputPerformance(self):
self.logger.info("Orders : {0:d}".format(self.orders))
self.logger.info("Fills : {0:d}".format(self.fills))
self.portfolio.createEquityCurveDataframe()
perf_metric, perf_df, rollingRisk, aggregated_positions, transactions, turnover_rate = self.portfolio.outputSummaryStats(self.portfolio.equityCurve, self.plot)
return self.portfolio.equityCurve, \
self.orderBook.view(), \
self.filledBook.view(), \
perf_metric, perf_df, \
rollingRisk, \
aggregated_positions, \
transactions, \
turnover_rate, \
self.strategy.infoView()
def simulateTrading(self):
self.logger.info("Start backtesting...")
self.strategy._subscribe()
self._runBacktest()
self.logger.info("Backesting finished!")
return self._outputPerformance()
class Backtest(object):
def __init__(self,
initial_capital,
heartbeat,
data_handler,
execution_handler,
portfolio,
strategy,
logger,
benchmark=None,
refreshRate=1,
plot=False,
portfolioType=PortfolioType.CashManageable):
self.initialCapital = initial_capital
self.heartbeat = heartbeat
self.dataHandler = data_handler
self.executionHanlderCls = execution_handler
self.portfolioCls = portfolio
self.strategyCls = strategy
self.symbolList = self.dataHandler.symbolList
self.tradable = self.dataHandler.tradableAssets
self.assets = setAssetsConfig(self.tradable)
self.events = queue.Queue()
self.dataHandler.setEvents(self.events)
self.signals = 0
self.orders = 0
self.fills = 0
self.num_strats = 1
self.benchmark = benchmark
self.refreshRate = refreshRate
self.counter = 0
self.plot = plot
self.logger = logger
self.portfolioType = portfolioType
if portfolioType == PortfolioType.FullNotional:
self.initialCapital = np.inf
self._generateTradingInstance()
def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls()
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler, self.events,
self.dataHandler.getStartDate(),
self.assets, self.initialCapital,
self.benchmark, self.portfolioType)
self.executionHanlder = self.executionHanlderCls(
self.events, self.dataHandler, self.portfolio, self.logger)
self.orderBook = OrderBook()
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
def _runBacktest(self):
i = 0
while True:
i += 1
if self.dataHandler.continueBacktest:
self.strategy.symbolList, self.strategy.tradableAssets = self.dataHandler.updateBars(
)
else:
break
while True:
try:
event = self.events.get(False)
except queue.Empty:
break
if event is not None:
if event.type == 'MARKET':
self.counter += 1
self.strategy._updateTime()
self.strategy._updateSubscribing()
self.portfolio.updateTimeindex()
if self.counter % self.refreshRate == 0:
self.strategy._handle_data()
elif event.type == 'SIGNAL':
self.signals += 1
self.portfolio.updateSignal(event)
elif event.type == 'ORDER':
self.orders += 1
event.assetType = self.assets[event.symbol]
self.orderBook.updateFromOrderEvent(event)
fill_event = self.executionHanlder.executeOrder(event)
self.fills += 1
if fill_event:
self.orderBook.updateFromFillEvent(fill_event)
self.portfolio.updateFill(fill_event)
time.sleep(self.heartbeat)
def _outputPerformance(self):
self.logger.info("Orders : {0:d}".format(self.orders))
self.logger.info("Fills : {0:d}".format(self.fills))
self.portfolio.createEquityCurveDataframe()
perf_metric, perf_df, rollingRisk, aggregated_positions, transactions, turnover_rate = self.portfolio.outputSummaryStats(
self.portfolio.equityCurve, self.plot)
return self.portfolio.equityCurve, \
self.orderBook.view(), \
self.filledBook.view(), \
perf_metric, perf_df, \
rollingRisk, \
aggregated_positions, \
transactions, \
turnover_rate, \
self.strategy.infoView()
def simulateTrading(self):
self.logger.info("Start backtesting...")
self.strategy._subscribe()
self._runBacktest()
self.logger.info("Backesting finished!")
return self._outputPerformance()
class Backtest(object):
def __init__(self,
initial_capital,
heartbeat,
data_handler,
execution_handler,
portfolio,
strategy,
logger,
benchmark=None,
refreshRate=1,
plot=False,
portfolioType=PortfolioType.CashManageable,
strategyParameters=()):
self.initialCapital = initial_capital
self.heartbeat = heartbeat
self.dataHandler = data_handler
self.executionHanlderCls = execution_handler
self.portfolioCls = portfolio
if not isinstance(strategy, Strategy):
self.strategyCls = strategy
else:
raise TypeError('strategy paramater should be a class type not a strategy instance')
self.strategyParameters = strategyParameters
self.symbolList = self.dataHandler.whole_symbols
self.tradable = self.dataHandler.allTradableAssets
self.assets = setAssetsConfig(self.tradable)
self.events = queue.Queue()
self.dataHandler.setEvents(self.events)
self.signals = 0
self.num_strats = 1
self.benchmark = benchmark
self.refreshRate = refreshRate
self.counter = 0
self.plot = plot
self.logger = logger
self.portfolioType = portfolioType
if portfolioType == PortfolioType.FullNotional:
self.initialCapital = np.inf
self._generateTradingInstance()
def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls(*self.strategyParameters)
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler,
self.events,
self.dataHandler.getStartDate(),
self.assets,
self.initialCapital,
self.benchmark,
self.portfolioType)
self.executionHanlder = self.executionHanlderCls(self.events, self.dataHandler, self.portfolio, self.logger)
self.portfolio.orderBook = OrderBook(self.logger)
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
def _runBacktest(self):
i = 0
while True:
i += 1
if self.dataHandler.continueBacktest:
self.dataHandler.checkingDayBegin()
self.strategy.symbolList, self.strategy.tradableAssets = self.dataHandler.updateBars()
else:
break
while True:
try:
event = self.events.get(False)
except queue.Empty:
break
if event is not None:
if event.type == 'MARKET':
self.counter += 1
self.strategy._updateTime()
self.strategy._updateSubscribing()
self.portfolio.updateTimeindex()
# update still alive orders
# for order in self.portfolio.orderBook:
# if order.symbol in self.strategy.tradableAssets:
# self.executionHanlder.executeOrder(order,
# self.assets[order.symbol],
# self.portfolio.orderBook,
# self.portfolio)
# cancel all the legacy orders
self.portfolio.cancelOrders(event.timeIndex, self.strategy._posBook)
if self.counter % self.refreshRate == 0:
self.strategy._handle_data()
elif event.type == 'SIGNAL':
self.signals += 1
self.portfolio.updateSignal(event)
elif event.type == 'ORDER':
self.portfolio.orderBook.updateFromOrderEvent(event)
self.executionHanlder.executeOrder(event.to_order(),
self.assets[event.symbol],
self.portfolio.orderBook,
self.portfolio)
self.strategy.handle_order(event)
elif event.type == 'FILL':
self.strategy.handle_fill(event)
elif event.type == 'DAYBEGIN':
self.strategy.checkingPriceLimit()
self.strategy.current_datetime = event.timeIndex
self.strategy.day_begin()
time.sleep(self.heartbeat)
def _outputPerformance(self):
self.portfolio.createEquityCurveDataframe()
other_curves = self.strategy.plotCurves()
perf_metric, perf_df, rollingRisk, aggregated_positions, transactions, turnover_rate = \
self.portfolio.outputSummaryStats(self.portfolio.equityCurve, other_curves, self.plot)
return self.portfolio.equityCurve, \
self.portfolio.orderBook.view(), \
self.filledBook.view(), \
perf_metric, perf_df, \
rollingRisk, \
aggregated_positions, \
transactions, \
turnover_rate, \
self.strategy.infoView()
def simulateTrading(self):
self.logger.info("Start backtesting...")
self.strategy._subscribe()
self._runBacktest()
self.logger.info("Backesting finished!")
return self._outputPerformance()
class Backtest(object):
def __init__(self,
initial_capital,
heartbeat,
data_handler,
execution_handler,
portfolio,
strategy,
logger,
benchmark=None,
refreshRate=1,
plot=False,
portfolioType=PortfolioType.CashManageable,
strategyParameters=()):
self.initialCapital = initial_capital
self.heartbeat = heartbeat
self.dataHandler = data_handler
self.executionHanlderCls = execution_handler
self.portfolioCls = portfolio
if not isinstance(strategy, Strategy):
self.strategyCls = strategy
else:
raise TypeError('strategy paramater should be a class type not a strategy instance')
self.strategyParameters = strategyParameters
self.symbolList = self.dataHandler.whole_symbols
self.tradable = self.dataHandler.allTradableAssets
self.assets = setAssetsConfig(self.tradable)
self.events = queue.Queue()
self.dataHandler.setEvents(self.events)
self.signals = 0
self.num_strats = 1
self.benchmark = benchmark
self.refreshRate = refreshRate
self.counter = 0
self.plot = plot
self.logger = logger
self.portfolioType = portfolioType
if portfolioType == PortfolioType.FullNotional:
self.initialCapital = np.inf
self._generateTradingInstance()
def _generateTradingInstance(self):
Settings.defaultSymbolList = self.symbolList
self.strategy = self.strategyCls(*self.strategyParameters)
self.strategy.events = self.events
self.strategy.bars = self.dataHandler
self.strategy.symbolList = self.symbolList
self.strategy.logger = self.logger
self.portfolio = self.portfolioCls(self.dataHandler,
self.events,
self.dataHandler.getStartDate(),
self.assets,
self.initialCapital,
self.benchmark,
self.portfolioType)
self.executionHanlder = self.executionHanlderCls(self.events, self.dataHandler, self.portfolio, self.logger)
self.portfolio.orderBook = OrderBook(self.logger)
self.filledBook = FilledBook()
self.portfolio.filledBook = self.filledBook
self.strategy._port = self.portfolio
self.strategy._posBook = self.portfolio.positionsBook
def _runBacktest(self):
i = 0
while True:
i += 1
if self.dataHandler.continueBacktest:
self.dataHandler.checkingDayBegin()
self.strategy.symbolList, self.strategy.tradableAssets = self.dataHandler.updateBars()
else:
break
while True:
try:
event = self.events.get(False)
except queue.Empty:
break
if event is not None:
if event.type == 'MARKET':
self.counter += 1
self.strategy._updateTime()
self.strategy._updateSubscribing()
self.portfolio.updateTimeindex()
# update still alive orders
for order in self.portfolio.orderBook:
if order.symbol in self.strategy.tradableAssets:
self.executionHanlder.executeOrder(order,
self.assets[order.symbol],
self.portfolio.orderBook,
self.portfolio)
if self.counter % self.refreshRate == 0:
self.strategy._handle_data()
elif event.type == 'SIGNAL':
self.signals += 1
self.portfolio.updateSignal(event)
elif event.type == 'ORDER':
self.portfolio.orderBook.updateFromOrderEvent(event)
self.executionHanlder.executeOrder(event.to_order(),
self.assets[event.symbol],
self.portfolio.orderBook,
self.portfolio)
self.strategy.handle_order(event)
elif event.type == 'FILL':
self.strategy.handle_fill(event)
elif event.type == 'DAYBEGIN':
self.strategy.checkingPriceLimit()
self.strategy.current_datetime = event.timeIndex
self.portfolio.cancelOrders(event.timeIndex, self.strategy._posBook)
self.strategy.day_begin()
time.sleep(self.heartbeat)
def _outputPerformance(self):
self.portfolio.createEquityCurveDataframe()
other_curves = self.strategy.plotCurves()
perf_metric, perf_df, rollingRisk, aggregated_positions, transactions, turnover_rate = \
self.portfolio.outputSummaryStats(self.portfolio.equityCurve, other_curves, self.plot)
return self.portfolio.equityCurve, \
self.portfolio.orderBook.view(), \
self.filledBook.view(), \
perf_metric, perf_df, \
rollingRisk, \
aggregated_positions, \
transactions, \
turnover_rate, \
self.strategy.infoView()
def simulateTrading(self):
self.logger.info("Start backtesting...")
self.strategy._subscribe()
self._runBacktest()
self.logger.info("Backesting finished!")
return self._outputPerformance()