def initialize(context):
# Turn off the slippage model
set_slippage(slippage.FixedSlippage(spread=0.0))
# Set the commission model
set_commission(commission.PerShare(cost=0.01, min_trade_cost=1.0))
context.day = -1 # using zero-based counter for days
context.set_benchmark(symbol('DIA'))
context.assets = []
print('Setup investable assets...')
for ticker in asset_tickers:
#print(ticker)
context.assets.append(symbol(ticker))
context.n_asset = len(context.assets)
context.n_portfolio = 40 # num mean-variance efficient portfolios to compute
context.today = None
context.tau = None
context.min_data_window = 756 # min of 3 yrs data for calculations
context.first_rebal_date = None
context.first_rebal_idx = None
context.weights = None
# Schedule dynamic allocation calcs to occur 1 day before month end - note that
# actual trading will occur on the close on the last trading day of the month
schedule_function(rebalance,
date_rule=date_rules.month_end(days_offset=1),
time_rule=time_rules.market_close())
# Record some stuff every day
schedule_function(record_vars,
date_rule=date_rules.every_day(),
time_rule=time_rules.market_close())
def initialize(context):
# Let's set a look up date inside our backtest to ensure we grab the correct security
#set_symbol_lookup_date('2015-01-01')
# Use a very liquid set of stocks for quick order fills
context.symbol = symbol('SPY')
#context.stocks = symbols(['TWX','AIG','PSX','EMC','YHOO','MDY','TNA','CHK','FXI',
# 'PEP','SBUX','VZ','VWO','TWC','HAL','MDLZ','CAT','TSLA',
# 'MU','PM','WYNN','MET',NOV BRK_B SNDK ESRX YELP])
#set_universe(universe.DollarVolumeUniverse(99.5, 100))
#set_benchmark(symbol('SPY'))
# set a more realistic commission for IB, remove both this and slippage when live trading in IB
set_commission(commission.PerShare(cost=0.014, min_trade_cost=1.4))
# Default slippage values, but here to mess with for fun.
set_slippage(
slippage.VolumeShareSlippage(volume_limit=0.25, price_impact=0.1))
# Use dicts to store items for plotting or comparison
context.next_pred_price = {} # Current cycles prediction
#Change us!
context.history_len = 500 # How many days in price history for training set
context.out_of_sameple_bin_size = 2
context.score_filter = -1000.0
context.action_to_move_percent = 0.0
# Register 2 histories that track daily prices,
# one with a 100 window and one with a 300 day window
add_history(context.history_len, '1d', 'price')
context.i = 0
def initialize(context):
"""
Called once at the start of the algorithm.
"""
set_slippage(slippage.FixedSlippage(spread=0.00))
set_commission(commission.PerShare(cost=0, min_trade_cost=0))
schedule_function(rebalance, TRADE_FREQ,
date_rules.every_day(),
time_rules.market_open(hours=1, minutes=30),
)
schedule_function(record_vars, date_rules.every_day(),
time_rules.market_close())
ml_pipeline = make_ml_pipeline(universe,
n_forward_days=N_FORWARD_DAYS,
window_length=TRAINING_PERIOD)
# Create our dynamic stock selector.
attach_pipeline(ml_pipeline, 'ml_model')
context.past_predictions = {}
context.ic = 0
context.rmse = 0
context.mae = 0
context.returns_spread_bps = 0
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_commission(self, country='US', platform='IB'):
"""Sets commissions
See https://www.quantopian.com/help#ide-commission and
https://www.quantopian.com/docs/api-reference/algorithm-api-reference#zipline.finance.commission.PerDollar
"""
if (country == 'SG'):
set_commission(SGCommission(platform=platform))
else:
# IB broker for US is the top stock broker in US
# https://brokerchooser.com/best-brokers/best-stock-brokers-in-the-us
# Typical commission is USD 0.005 per share, minimum per order USD 1.00
# https://www1.interactivebrokers.com/en/index.php?f=1590&p=stocks
set_commission(commission.PerShare(cost=0.005, min_trade_cost=1))
def initialize(context):
# This code runs once, when the sim starts up
log.debug('scheduling rebalance and recording')
set_slippage(slippage.FixedSlippage(spread=0.0))
set_commission(commission.PerShare(cost=0, min_trade_cost=0))
schedule_function(func=rebalance,
date_rule=date_rules.month_end(),
time_rule=time_rules.market_close(minutes=15))
schedule_function(func=record_daily,
date_rule=date_rules.every_day(),
time_rule=time_rules.market_close())
def initialize(self, context):
add_history(200, '1d', 'price')
set_slippage(slippage.FixedSlippage(spread=0.0))
set_commission(commission.PerShare(cost=0.01, min_trade_cost=1.0))
context.tick = 0
dp_data = self.data
df_data = pd.DataFrame(index=dp_data.axes[1])
df_data['close'] = dp_data[:, :, 'close']
df_data['open'] = dp_data[:, :, 'open']
df_data['high'] = dp_data[:, :, 'high']
df_data['low'] = dp_data[:, :, 'low']
df_data['volume'] = dp_data[:, :, 'volume']
self.atr = atr_per_close(df_data, atrLen = self.atr_len)
context.longstop = 0
def initialize(context):
"""
Called once at the start of the algorithm.
"""
context.n_longs = N_LONGS
context.n_shorts = N_SHORTS
context.min_positions = MIN_POSITIONS
context.universe = assets
set_slippage(slippage.FixedSlippage(spread=0.00))
set_commission(commission.PerShare(cost=0, min_trade_cost=0))
schedule_function(rebalance, date_rules.every_day(),
time_rules.market_open(hours=1, minutes=30))
schedule_function(record_vars, date_rules.every_day(),
time_rules.market_close())
pipeline = compute_signals()
attach_pipeline(pipeline, 'signals')
def initialize(context):
'''
Called once at the very beginning of a backtest (and live trading).
Use this method to set up any bookkeeping variables.
The context object is passed to all the other methods in your algorithm.
Parameters
context: An initialized and empty Python dictionary that has been
augmented so that properties can be accessed using dot
notation as well as the traditional bracket notation.
Returns None
'''
# Turn off the slippage model
set_slippage(slippage.FixedSlippage(spread=0.0))
# Set the commission model (Interactive Brokers Commission)
set_commission(commission.PerShare(cost=0.01, min_trade_cost=1.0))
context.tick = 0
def initialize(context):
context.i = 0
context.sym = symbol('LKTB')
context.hold = False
set_commission(commission.PerShare(cost=0.000008))
set_slippage(slippage.FixedSlippage(spread=0))
def initialize(self, context):
add_history(60, '1d', 'price')
set_slippage(slippage.FixedSlippage(spread=0.0))
set_commission(commission.PerShare(cost=0.01, min_trade_cost=1.0))
context.tick = 0