def construct_backtest(ticker, vendor_ticker, sma_period, data_source, start_date, quandl_api_key): backtest = Backtest() br = BacktestRequest() # Set all the parameters for the backtest br.start_date = start_date br.finish_date = datetime.datetime.utcnow() br.spot_tc_bp = 2.5 # 2.5 bps bid/ask spread br.ann_factor = 252 tech_params = TechParams() tech_params.sma_period = sma_period indicator = 'SMA' md_request = MarketDataRequest( start_date=start_date, finish_date=datetime.date.today(), freq='daily', data_source=data_source, tickers=ticker, fields=['close'], vendor_tickers=vendor_ticker, quandl_api_key=quandl_api_key) market = Market(market_data_generator=MarketDataGenerator()) # Download the market data (the asset we are trading is also # being used to generate the signal) asset_df = market.fetch_market(md_request) spot_df = asset_df # Use technical indicator to create signals # (we could obviously create whatever function we wanted for generating the signal dataframe) # However, finmarketpy has some technical indicators built in (and some signals too) tech_ind = TechIndicator() tech_ind.create_tech_ind(spot_df, indicator, tech_params); signal_df = tech_ind.get_signal() # use the same data for generating signals backtest.calculate_trading_PnL(br, asset_df, signal_df, None, False) # Get the returns and signals for the portfolio port = backtest.portfolio_cum() port.columns = [indicator + ' = ' + str(tech_params.sma_period) + ' ' + str(backtest.portfolio_pnl_desc()[0])] signals = backtest.portfolio_signal() # returns = backtest.pnl() return port, signals
# get all asset data br.start_date = "02 Jan 1990" br.finish_date = datetime.datetime.utcnow() br.spot_tc_bp = 2.5 # 2.5 bps bid/ask spread br.ann_factor = 252 # have vol target for each signal br.signal_vol_adjust = True br.signal_vol_target = 0.05 br.signal_vol_max_leverage = 3 br.signal_vol_periods = 60 br.signal_vol_obs_in_year = 252 br.signal_vol_rebalance_freq = 'BM' br.signal_vol_resample_freq = None tech_params = TechParams(); tech_params.sma_period = 200; indicator = 'SMA' # pick USD crosses in G10 FX # note: we are calculating returns from spot (it is much better to use to total return # indices for FX, which include carry) logger.info("Loading asset data...") tickers = ['EURUSD', 'USDJPY', 'GBPUSD', 'AUDUSD', 'USDCAD', 'NZDUSD', 'USDCHF', 'USDNOK', 'USDSEK'] vendor_tickers = ['FRED/DEXUSEU', 'FRED/DEXJPUS', 'FRED/DEXUSUK', 'FRED/DEXUSAL', 'FRED/DEXCAUS', 'FRED/DEXUSNZ', 'FRED/DEXSZUS', 'FRED/DEXNOUS', 'FRED/DEXSDUS'] md_request = MarketDataRequest( start_date = "01 Jan 1989", # start date finish_date = datetime.date.today(), # finish date
br.start_date = "02 Jan 1990" br.finish_date = datetime.datetime.utcnow() br.spot_tc_bp = 2.5 # 2.5 bps bid/ask spread br.ann_factor = 252 # have vol target for each signal br.signal_vol_adjust = True br.signal_vol_target = 0.05 br.signal_vol_max_leverage = 3 br.signal_vol_periods = 60 br.signal_vol_obs_in_year = 252 br.signal_vol_rebalance_freq = 'BM' br.signal_vol_resample_freq = None tech_params = TechParams() tech_params.sma_period = 200 indicator = 'SMA' # pick USD crosses in G10 FX # note: we are calculating returns from spot (it is much better to use to total return # indices for FX, which include carry) logger.info("Loading asset data...") tickers = [ 'EURUSD', 'USDJPY', 'GBPUSD', 'AUDUSD', 'USDCAD', 'NZDUSD', 'USDCHF', 'USDNOK', 'USDSEK' ] vendor_tickers = [ 'FRED/DEXUSEU', 'FRED/DEXJPUS', 'FRED/DEXUSUK', 'FRED/DEXUSAL', 'FRED/DEXCAUS', 'FRED/DEXUSNZ', 'FRED/DEXSZUS', 'FRED/DEXNOUS',