def initialize(self, context):
if self.verbose: print("Starting the robo advisor")
# Populate Portfolios
self.all_portfolios = initialize_portfolio(self.verbose)
# Set Commission model
self.initialize_commission(country=self.country, platform=self.trading_platform)
# Set Slippage model
set_slippage(slippage.FixedSlippage(spread=0.0)) # assume spread of 0
# Schedule Rebalancing check
rebalance_check_freq = date_rules.month_end()
if (self.rebalance_freq == 'daily'): rebalance_check_freq = date_rules.every_day()
elif (self.rebalance_freq == 'weekly'): rebalance_check_freq = date_rules.week_end()
if self.verbose: print('Rebalance checks will be done %s' % self.rebalance_freq)
schedule_function(
func=self.before_trading_starts,
date_rule=rebalance_check_freq,
time_rule=time_rules.market_open(hours=1))
# record daily weights at the end of each day
schedule_function(
func=record_current_weights,
date_rule=date_rules.every_day(),
time_rule=time_rules.market_close()
)
def initialize(context):
"""
Called once at the start of the algorithm.
"""
feature_num = 11
context.orders_submitted = False
large_num = 9999999
least_num = 0
context.n_components = feature_num
context.security = symbol(SYMBOL) # Trade SPY
set_benchmark(symbol(SYMBOL)) # Set benchmarks
context.model = DecisionTreeClassifier(criterion='entropy',
max_depth=feature_num,
random_state=0)
context.lookback = 350 # Look back 62 days
context.history_range = 350 # Only consider the past 400 days' history
context.threshold = 4.05
context.longprices = large_num
context.shortprices = least_num
set_long_only()
# Generate a new model every week
schedule_function(create_model, date_rules.week_end(),
time_rules.market_close(minutes=10))
"""
# Generate a new model every week
schedule_function(create_model1, date_rules.week_end(), time_rules.market_close(minutes=10))
"""
# Trade at the start of every day
schedule_function(rebalance, date_rules.every_day(),
time_rules.market_open(minutes=1))
def initialize(context):
"""
Called once at the start of the algorithm.
"""
feature_num = 11
context.orders_submitted = False
large_num = 9999999
least_num = 0
context.n_components = feature_num
context.security = symbol(SYMBOL) # Trade SPY
set_benchmark(symbol(SYMBOL)) # Set benchmarks
context.model = SVC(kernel='rbf', tol=1e-3, random_state=0, gamma=0.2, C=10.0, verbose=True) # 8.05 for SVM model
context.lookback = 350 # Look back 62 days
context.history_range = 350 # Only consider the past 400 days' history
context.threshold = 4.05
context.longprices = large_num
context.shortprices = least_num
set_long_only()
# Generate a new model every week
schedule_function(create_model, date_rules.week_end(), time_rules.market_close(minutes=10))
"""
# Generate a new model every week
schedule_function(create_model1, date_rules.week_end(), time_rules.market_close(minutes=10))
"""
# Trade at the start of every day
schedule_function(rebalance, date_rules.every_day(), time_rules.market_open(minutes=1))
def initialize(context):
attach_pipeline(make_pipeline(), 'pipeline')
#Schedule Functions
if not IS_LIVE:
schedule_function(
trade,
#date_rules.every_day(),
#date_rules.week_end(days_offset=1),#0=Fri 1= Thurs
date_rules.month_end(days_offset=3),
time_rules.market_close(minutes=30)
)
schedule_function(record_vars, date_rules.every_day(), time_rules.market_close())
schedule_function(cancel_open_orders, date_rules.week_end(days_offset=2), time_rules.market_close())
context.spy = symbol('SPY') #sid(8554) #SPY
context.TF_filter = False
#context.TF_lookback = 60
#Set number of securities to buy and bonds fund (when we are out of stocks)
context.Target_securities_to_buy = 15 #10 #15 #2 #1 #5 #10 #5
context.bonds = symbol('IEF') #sid(23870) #IEF
context.relative_momentum_lookback = 44 #66 #22 #4 #22 #22 #22 #126 #Momentum lookback
context.momentum_skip_days = 1
context.top_n_relative_momentum_to_buy = 10 #15 #10 #15 #1 #5 #5 #10 #5 #Number to buy
context.stock_weights = pd.Series()
context.bond_weights = pd.Series()
context.auto_close = {} #Initialize portfolio auto_close list.
context.TRACK_ORDERS_ON = False
def initialize(context):
"""
Called once at the start of the algorithm.
"""
feature_num = 11
context.orders_submitted = False
large_num = 9999999
least_num = 0
context.n_components = feature_num
context.security = symbol(SYMBOL) # Trade SPY
set_benchmark(symbol(SYMBOL)) # Set benchmarks
context.model2 = SVC(kernel='rbf',
tol=1e-3,
random_state=0,
gamma=0.2,
C=10.0,
verbose=True) # 8.05 for SVM model
context.model3 = KNeighborsClassifier(
n_neighbors=feature_num, p=3, metric='minkowski') # 7.05 for model
context.model = DecisionTreeClassifier(criterion='entropy',
max_depth=feature_num,
random_state=0)
context.model4 = RandomForestClassifier(criterion='entropy',
n_estimators=feature_num,
random_state=1,
n_jobs=2) # 5.2 for randomforest
context.model1 = LogisticRegression(random_state=0,
solver='lbfgs',
multi_class='multinomial')
context.modellist = {
'SVM': context.model2,
'KNeighbors': context.model3,
'DecisionTree': context.model,
'RandomForest': context.model4,
'LogisticRegression': context.model1
}
context.lookback = 350 # Look back 62 days
context.history_range = 350 # Only consider the past 400 days' history
context.threshold = 4.05
context.longprices = large_num
context.shortprices = least_num
set_long_only()
# Generate a new model every week
schedule_function(create_model, date_rules.week_end(),
time_rules.market_close(minutes=10))
"""
# Generate a new model every week
schedule_function(create_model1, date_rules.week_end(), time_rules.market_close(minutes=10))
"""
# Trade at the start of every day
schedule_function(rebalance, date_rules.every_day(),
time_rules.market_open(minutes=1))
def initialize(context):
__build_factor_basic_strategy(context)
attach_pipeline(make_pipeline(context), 'my_pipeline')
schedule_function(rebalance,
date_rules.week_end(days_offset=0),
half_days=True)
# record my portfolio variables at the end of day
schedule_function(func=recording_statements,
date_rule=date_rules.every_day(),
time_rule=time_rules.market_close(),
half_days=True)
print("initialize over")
pass
def initialize(context):
context.security = sid(8554) # Trade SPY
context.model = RandomForestRegressor()
context.lookback = 3 # Look back 3 days
context.history_range = 400 # Only consider the past 400 days' history
# Generate a new model every week
schedule_function(create_model, date_rules.week_end(),
time_rules.market_close(minutes=10))
# Trade at the start of every day
schedule_function(trade, date_rules.every_day(),
time_rules.market_open(minutes=1))
def initialize(context):
"""
Called once at the start of the algorithm.
"""
feature_num = 11
context.orders_submitted = False
large_num = 9999999
least_num = 0
context.n_components = 11
context.n_components = 6
context.SP500_symbol = [
'AAPL', 'ABT', 'ABBV', 'ACN', 'ACE', 'ADBE', 'ADT', 'AAP', 'AES',
'AET', 'AFL', 'AMG', 'A', 'GAS', 'ARE', 'APD', 'AKAM', 'AA', 'AGN',
'ALXN', 'ALLE', 'ADS', 'ALL', 'ALTR', 'MO', 'AMZN', 'AEE', 'AAL',
'AEP', 'AXP', 'AIG', 'AMT', 'AMP', 'ABC', 'AME', 'AMGN', 'APH', 'APC',
'ADI', 'AON', 'APA', 'AIV', 'AMAT', 'ADM', 'AIZ', 'T', 'ADSK', 'ADP',
'AN', 'AZO', 'AVGO', 'AVB', 'AVY', 'BHI', 'BLL', 'BAC', 'BK', 'BCR',
'BXLT', 'BAX', 'BBT', 'BDX', 'BBBY', 'BRK.B', 'BBY', 'BLX', 'HRB',
'BA', 'BWA', 'BXP', 'BSX', 'BMY', 'BRCM', 'BF.B', 'CHRW', 'CA', 'CVC',
'COG', 'CAM', 'CPB', 'COF', 'CAH', 'HSIC', 'KMX', 'CCL', 'CAT', 'CBG',
'CBS', 'CELG', 'CNP', 'CTL', 'CERN', 'CF', 'SCHW', 'CHK', 'CVX', 'CMG',
'CB', 'CI', 'XEC', 'CINF', 'CTAS', 'CSCO', 'C', 'CTXS', 'CLX', 'CME',
'CMS', 'COH', 'KO', 'CCE', 'CTSH', 'CL', 'CMCSA', 'CMA', 'CSC', 'CAG',
'COP', 'CNX', 'ED', 'STZ', 'GLW', 'COST', 'CCI', 'CSX', 'CMI', 'CVS',
'DHI', 'DHR', 'DRI', 'DVA', 'DE', 'DLPH', 'DAL', 'XRAY', 'DVN', 'DO',
'DTV', 'DFS', 'DISCA', 'DISCK', 'DG', 'DLTR', 'D', 'DOV', 'DOW', 'DPS',
'DTE', 'DD', 'DUK', 'DNB', 'ETFC', 'EMN', 'ETN', 'EBAY', 'ECL', 'EIX',
'EW', 'EA', 'EMC', 'EMR', 'ENDP', 'ESV', 'ETR', 'EOG', 'EQT', 'EFX',
'EQIX', 'EQR', 'ESS', 'EL', 'ES', 'EXC', 'EXPE', 'EXPD', 'ESRX', 'XOM',
'FFIV', 'FB', 'FAST', 'FDX', 'FIS', 'FITB', 'FSLR', 'FE', 'FISV',
'FLIR', 'FLS', 'FLR', 'FMC', 'FTI', 'F', 'FOSL', 'BEN', 'FCX', 'FTR',
'GME', 'GPS', 'GRMN', 'GD', 'GE', 'GGP', 'GIS', 'GM', 'GPC', 'GNW',
'GILD', 'GS', 'GT', 'GOOGL', 'GOOG', 'GWW', 'HAL', 'HBI', 'HOG', 'HAR',
'HRS', 'HIG', 'HAS', 'HCA', 'HCP', 'HCN', 'HP', 'HES', 'HPQ', 'HD',
'HON', 'HRL', 'HSP', 'HST', 'HCBK', 'HUM', 'HBAN', 'ITW', 'IR', 'INTC',
'ICE', 'IBM', 'IP', 'IPG', 'IFF', 'INTU', 'ISRG', 'IVZ', 'IRM', 'JEC',
'JBHT', 'JNJ', 'JCI', 'JOY', 'JPM', 'JNPR', 'KSU', 'K', 'KEY', 'GMCR',
'KMB', 'KIM', 'KMI', 'KLAC', 'KSS', 'KRFT', 'KR', 'LB', 'LLL', 'LH',
'LRCX', 'LM', 'LEG', 'LEN', 'LVLT', 'LUK', 'LLY', 'LNC', 'LLTC', 'LMT',
'L', 'LOW', 'LYB', 'MTB', 'MAC', 'M', 'MNK', 'MRO', 'MPC', 'MAR',
'MMC', 'MLM', 'MAS', 'MA', 'MAT', 'MKC', 'MCD', 'MCK', 'MJN', 'MMV',
'MDT', 'MRK', 'MET', 'KORS', 'MCHP', 'MU', 'MSFT', 'MHK', 'TAP',
'MDLZ', 'MON', 'MNST', 'MCO', 'MS', 'MOS', 'MSI', 'MUR', 'MYL', 'NDAQ',
'NOV', 'NAVI', 'NTAP', 'NFLX', 'NWL', 'NFX', 'NEM', 'NWSA', 'NEE',
'NLSN', 'NKE', 'NI', 'NE', 'NBL', 'JWN', 'NSC', 'NTRS', 'NOC', 'NRG',
'NUE', 'NVDA', 'ORLY', 'OXY', 'OMC', 'OKE', 'ORCL', 'OI', 'PCAR',
'PLL', 'PH', 'PDCO', 'PAYX', 'PNR', 'PBCT', 'POM', 'PEP', 'PKI',
'PRGO', 'PFE', 'PCG', 'PM', 'PSX', 'PNW', 'PXD', 'PBI', 'PCL', 'PNC',
'RL', 'PPG', 'PPL', 'PX', 'PCP', 'PCLN', 'PFG', 'PG', 'PGR', 'PLD',
'PRU', 'PEG', 'PSA', 'PHM', 'PVH', 'QRVO', 'PWR', 'QCOM', 'DGX', 'RRC',
'RTN', 'O', 'RHT', 'REGN', 'RF', 'RSG', 'RAI', 'RHI', 'ROK', 'COL',
'ROP', 'ROST', 'RLD', 'R', 'CRM', 'SNDK', 'SCG', 'SLB', 'SNI', 'STX',
'SEE', 'SRE', 'SHW', 'SPG', 'SWKS', 'SLG', 'SJM', 'SNA', 'SO', 'LUV',
'SWN', 'SE', 'STJ', 'SWK', 'SPLS', 'SBUX', 'HOT', 'STT', 'SRCL', 'SYK',
'STI', 'SYMC', 'SYY', 'TROW', 'TGT', 'TEL', 'TE', 'TGNA', 'THC', 'TDC',
'TSO', 'TXN', 'TXT', 'HSY', 'TRV', 'TMO', 'TIF', 'TWX', 'TWC', 'TJX',
'TMK', 'TSS', 'TSCO', 'RIG', 'TRIP', 'FOXA', 'TSN', 'TYC', 'UA', 'UNP',
'UNH', 'UPS', 'URI', 'UTX', 'UHS', 'UNM', 'URBN', 'VFC', 'VLO', 'VAR',
'VTR', 'VRSN', 'VZ', 'VRTX', 'VIAB', 'V', 'VNO', 'VMC', 'WMT', 'WBA',
'DIS', 'WM', 'WAT', 'ANTM', 'WFC', 'WDC', 'WU', 'WY', 'WHR', 'WFM',
'WMB', 'WEC', 'WYN', 'WYNN', 'XEL', 'XRX', 'XLNX', 'XL', 'XYL', 'YHOO',
'YUM', 'ZBH', 'ZION', 'ZTS'
]
context.model2 = SVC(kernel='rbf',
tol=1e-3,
random_state=0,
gamma=0.2,
C=10.0,
verbose=True) # 8.05 for SVM model
context.model3 = KNeighborsClassifier(
n_neighbors=feature_num, p=3, metric='minkowski') # 7.05 for model
context.model5 = DecisionTreeClassifier(criterion='entropy',
max_depth=feature_num,
random_state=0)
context.model4 = RandomForestClassifier(criterion='entropy',
n_estimators=feature_num,
random_state=1,
n_jobs=2) # 5.2 for randomforest
context.model1 = LogisticRegression(random_state=0,
solver='lbfgs',
multi_class='multinomial')
context.model = KMeans(n_clusters=8,
init='k-means++',
max_iter=300,
tol=1e-4,
random_state=0)
#context.model = DBSCAN(eps=0.2,min_samples=3,metric='euclidean')
context.lookback = 350 # Look back 62 days
context.history_range = 350 # Only consider the past 400 days' history
context.threshold = 4.05
context.longprices = large_num
context.shortprices = least_num
context.times = 0
set_long_only()
# Generate a new model every week
schedule_function(create_model, date_rules.week_end(),
time_rules.market_close(minutes=10))
"""
# Generate a new model every week
schedule_function(create_model1, date_rules.week_end(), time_rules.market_close(minutes=10))
"""
# Trade at the start of every day
schedule_function(rebalance, date_rules.every_day(),
time_rules.market_open(minutes=1))
def initialize(context):
print("hello world")
attach_pipeline(make_pipeline(), 'my_pipeline')
schedule_function(rebalance,
date_rules.week_end(days_offset=0),
half_days=True)
def initialize(context, date_limits, verbose, symbols):
print "in initialize"
start_time_initialize = time.time()
context.verbose = verbose
# Define rebalance frequency
context.scheduler = SCHEDULER
if context.scheduler == 'Daily':
schedule_function(rebalance)
if context.scheduler == 'Weekly':
schedule_function(rebalance, date_rules.week_end())
elif context.scheduler == 'Monthly':
schedule_function(rebalance, date_rules.month_end())
context.date_limits = date_limits
# Set slippage model and commission model
set_slippage(slippage.FixedSlippage(spread=SLIPPAGE_SPREAD))
set_commission(commission.PerShare(cost=COMMISSION_COST_PER_SHARE, min_trade_cost=COMMISSION_MIN_TRADE_COST))
context.symbols = symbols
symbol_membership = utils.get_underlying(context.symbols, sep = ' / ')
symbol_membership.index = context.symbols
context.symbol_membership = symbol_membership
if REFERENCE_GROUP_SYMBOL['Cash'] in context.symbol_membership.index:
context.symbol_membership.loc[REFERENCE_GROUP_SYMBOL['Cash']] = 'Cash'
asset_keys = utils.get_asset_keys_db()
if RETS_READER is not None:
returns = utils.get_returns_db(RETS_READER, context.symbols, asset_keys)
else:
returns = None
if VOL_READER is not None and CORR_READER is not None:
volatility = utils.get_volatilities_db(VOL_READER, context.symbols, asset_keys)
correlations = utils.get_correlations_db(CORR_READER, context.symbols, asset_keys)
else:
volatility, correlations = [None]*2
data_dict = {'returns': returns, 'volatility': volatility, 'correlations': correlations}
context.data_dict = data_dict
#print returns
#print ''
#print ''
#print volatility
#print ''
#print ''
#print correlations
#print asfasfasf
# Group
group = "Top"
if len(sys.argv) >= 3 and 'ASSETTYPE=' in sys.argv[2]:
group = sys.argv[2].split('=')[-1]
params_dict = {}
params_dict.update(data_dict)
params_dict.update(PARAMS['params'])
ag_name = 'Top'
if group == 'Equity':
ag_name = PARAMS['params']['group']
context.group = AbstractGroup(context.symbols, name = ag_name, start=START_DATE_BT_STR, end = END_DATE_BT_STR, verbose = verbose, strategy_id = ID, scheduler = SCHEDULER , **params_dict)
#print "DEBUG [context.group.updated_symbols] : \n", context.group.updated_symbols
context.round_weights = 4
context.ref_group_df = pd.DataFrame(pd.Series({v:k for k,v in REFERENCE_GROUP_SYMBOL.items()}))
context.active_orders = []
if verbose:
print "INFO: Initialize took %f s." % (time.time() - start_time_initialize)
def initialize(context):
context.has_ordered = False
set_commission(commission.PerShare(cost=0.0, min_trade_cost=0.0))
set_slippage(slippage.FixedSlippage(spread=0.0))
schedule_function(func0, date_rules.week_end())
