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',