def initialize(context):
# Get continuous futures for Light Sweet Crude Oil...
context.crude_oil = continuous_future('CL', roll='calendar')
# ... and RBOB Gasoline
context.gasoline = continuous_future('RB', roll='calendar')
# If Zipline has trouble pulling the default benchmark, try setting the
# benchmark to something already in your bundle
set_benchmark(context.crude_oil)
# Ignore commissions and slippage for now
set_commission(us_futures=commission.PerTrade(cost=0))
set_slippage(us_futures=slippage.FixedSlippage(spread=0.0))
# Long and short moving average window lengths
context.long_ma = 65
context.short_ma = 5
# True if we currently hold a long position on the spread
context.currently_long_the_spread = False
# True if we currently hold a short position on the spread
context.currently_short_the_spread = False
# Rebalance pairs every day, 30 minutes after market open
schedule_function(func=rebalance_pairs,
date_rule=date_rules.every_day(),
time_rule=time_rules.market_open(minutes=30))
# Record Crude Oil and Gasoline Futures prices everyday
schedule_function(record_price, date_rules.every_day(),
time_rules.market_open())
def initialize(context):
context.fut = continuous_future('ES', roll='calendar')
# Ignore commissions and slippage for now
set_commission(us_futures=commission.PerTrade(cost=0))
set_slippage(us_futures=slippage.FixedSlippage(spread=0.0))
context.i = 0
context.invested = False
def initialize(context):
"""Set initialization params for a backtest"""
# trading pair
context.asset = symbol(trading_pair)
# trading signals, dict, timestamp:amount
context.trades = trades
# transaction cost
if commission_is_per_share:
context.set_commission(
commission.PerShare(cost=commission_cost, min_trade_cost=0))
else:
context.set_commission(commission.PerTrade(cost=commission_cost))
def initialize(context):
# these must ALWAYS be present!
context.transforms = []
context.algo_rules = []
context.max_lookback = 63
context.outstanding = {} # orders which span multiple days
context.raw_data = {}
#############################################################
# set the following parameters as required
context.show_positions = True
# select records to show in algo.show_records()
context.show_records = True
# replace cash_proxy with risk_free if cantec.allow_cash_proxY_replacement is True
# and cash_proxy price is <= average cash_proxy price over last context.cash_proxy_lookback days
context.allow_cash_proxy_replacement = False
context.cash_proxy_lookback = 43 # must be <= context.max_lookback
context.update_metrics = False
# to calculate Sharpe ratio
context.calculate_SR = False
context.SR_lookback = 63 # must be <= context.max_lookback
context.SD_factor = 0
# position only changed if percentage change > threshold
context.threshold = 0.01
# the following can be changed
context.market_proxy = symbols('VFINX')[0]
context.risk_free = symbols('VFISX')[0]
# context.market_proxy = symbols('SPY')[0]
# context.risk_free = symbols('SHY')[0]
set_commission(commission.PerTrade(cost=10.0))
context.leverage = 1.0
#################################################################
# configure strategies
context.rebalance_interval = 3 # set interval to n = no of periods (default: months)
# if you want to change default period, change schedule reallocate below
# Strategy 1
rs0003 = StrategyParameters(
context,
name='rs0003',
portfolios=[symbols('NHMAX', 'FAGIX', 'VFIIX')],
# portfolios=[symbols('HYD','HYD','MBB')],
portfolio_allocation_modes=['EW'],
portfolio_allocation_kwargs=[{}],
security_weights=[None],
portfolio_allocation_formulas=[None],
scoring_methods=['RS'],
scoring_factors=[{
'+momentum': 1.0
}],
n_tops=[1],
protection_modes=['BY_RULE'],
protection_rules=['smma_rule'],
protection_formulas=[None],
cash_proxies=[symbol('VFISX')],
# cash_proxies=[symbol('SHY')],
strategy_allocation_mode='FIXED',
portfolio_weights=[1.0],
strategy_allocation_formula=None,
strategy_allocation_rule=None)
Configurator(context, define_transforms, define_rules, strategies=[rs0003])
############################
# configure algorithm
algo = Algo(context,
strategies=[rs0003.strategy],
allocation_model=AllocationModel(context,
mode='EW',
weights=None,
formula=None),
regime=None)
###########################################################################################################
# generate algo data every day at close
schedule_function(algo.update_data, date_rules.every_day(),
time_rules.market_close())
# daily functions to handle GTC orders
schedule_function(algo.check_for_unfilled_orders, date_rules.every_day(),
time_rules.market_close())
schedule_function(algo.fill_outstanding_orders, date_rules.every_day(),
time_rules.market_open())
if context.update_metrics:
# calculate metrics every day
schedule_function(algo.update_metrics, date_rules.every_day(),
time_rules.market_close())
if context.show_positions:
schedule_function(algo.show_positions,
date_rules.month_start(days_offset=0),
time_rules.market_open())
if context.show_records:
# show records every day
# edit the show_records function to include records required
schedule_function(algo.show_records, date_rules.every_day(),
time_rules.market_close())
schedule_function(algo.rebalance, date_rules.month_end(days_offset=2),
time_rules.market_open())