def run(cache_name, cache_backend, expire_after, data_source, start, end, config, testing, tickers, filename, n, n_window): # Set up variables needed for backtest events_queue = queue.Queue() initial_equity = PriceParser.parse(500000.00) session = init_session(cache_name, cache_backend, expire_after) period = 86400 # Seconds in a day if len(tickers) == 1: data = web.DataReader(tickers[0], data_source, start, end, session=session) else: data = web.DataReader(tickers, data_source, start, end, session=session) # Use Generic Bar Handler with Pandas Bar Iterator price_event_iterator = PandasBarEventIterator(data, period, tickers[0]) price_handler = GenericPriceHandler(events_queue, price_event_iterator) # Use the Display Strategy strategy1 = DisplayStrategy(n=n, n_window=n_window) strategy2 = BuyAndHoldStrategy(tickers, events_queue) strategy = Strategies(strategy1, strategy2) # Use an example Position Sizer position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # 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): # Set up variables needed for backtest events_queue = queue.Queue() csv_dir = config.CSV_DATA_DIR initial_equity = Decimal("500000.00") # heartbeat = 0.0 # max_iters = 10000000000 # Use Yahoo Daily Price Handler price_handler = YahooDailyCsvBarPriceHandler( csv_dir, events_queue, tickers ) # Use the Buy and Hold Strategy strategy = BuyAndHoldStrategy(tickers, events_queue) strategy = Strategies(strategy, DisplayStrategy()) # Use an example Position Sizer position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # Set up the backtest backtest = Backtest( tickers, 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, n, n_window): # Set up variables needed for backtest events_queue = queue.Queue() ig_service = IGService(config.IG.USERNAME, config.IG.PASSWORD, config.IG.API_KEY, config.IG.ACCOUNT.TYPE) ig_stream_service = IGStreamService(ig_service) ig_session = ig_stream_service.create_session() accountId = ig_session[u'accounts'][0][u'accountId'] ig_stream_service.connect(accountId) initial_equity = PriceParser.parse(500000.00) # Use IG Tick Price Handler price_handler = IGTickPriceHandler(events_queue, ig_stream_service, tickers) # Use the Display Strategy strategy = DisplayStrategy(n=n, n_window=n_window) # Use an example Position Sizer position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # 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, n, n_window): # Set up variables needed for backtest events_queue = queue.Queue() csv_dir = config.CSV_DATA_DIR initial_equity = PriceParser.parse(500000.00) # Use Yahoo Daily Price Handler price_handler = YahooDailyCsvBarPriceHandler( csv_dir, events_queue, tickers ) # Use the Display Strategy strategy = DisplayStrategy(n=n, n_window=n_window) # Use an example Position Sizer position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # 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): # Set up variables needed for backtest events_queue = queue.Queue() csv_dir = config.CSV_DATA_DIR initial_equity = PriceParser.parse(500000.00) # Use Yahoo Daily Price Handler price_handler = YahooDailyCsvBarPriceHandler(csv_dir, events_queue, tickers) # Use the MAC Strategy strategy = MovingAverageCrossStrategy(tickers, events_queue) strategy = Strategies(strategy, DisplayStrategy()) # Use an example Position Sizer, position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # 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, n, n_window): # Set up variables needed for backtest events_queue = queue.Queue() csv_dir = config.CSV_DATA_DIR initial_equity = PriceParser.parse(500000.00) d_tickers = OrderedDict() for ticker in tickers: ticker_path = os.path.join(csv_dir, "%s.csv" % ticker) df = pd.io.parsers.read_csv( ticker_path, header=0, parse_dates=True, dayfirst=True, index_col=1, names=("Ticker", "Time", "Bid", "Ask") ) del df["Ticker"] d_tickers[ticker] = df if len(tickers) == 1: ticker = tickers[0] data = d_tickers[ticker] else: data = pd.Panel.from_dict(d_tickers) data = data.transpose(2, 1, 0) print(data) print("Null:") print(data.isnull().sum()) # Use Generic Tick Handler with Pandas Tick Iterator price_event_iterator = PandasTickEventIterator(data, tickers[0]) price_handler = GenericPriceHandler(events_queue, price_event_iterator) # Use the Display Strategy and ExampleStrategy strategy1 = DisplayStrategy(n=n, n_window=n_window) strategy2 = ExampleStrategy(tickers, events_queue) strategy = Strategies(strategy1, strategy2) # strategy = ExampleStrategy(tickers, events_queue) # Use an example Position Sizer position_sizer = FixedPositionSizer() # 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 statistics = SimpleStatistics(config, portfolio_handler) # 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