def buy(input_string):
"""
+ seperated contracts followed by & and then start date & end date & type
:param input_string:
:return:
"""
inputs = input_string.split('&')
print(inputs)
asset_list = inputs[0].split('+')
start_date = int(inputs[1])
end_date = inputs[2]
asset_types = inputs[3]
myport = Portfolio()
# get assets
for contract in asset_list:
if asset_types == 'options':
mT.get_one_option(contract, myport)
elif asset_types == 'stocks':
mT.get_one_stock(contract, myport)
elif asset_types == 'mixed':
mT.get_one_option(contract, myport)
mT.get_one_stock(contract, myport)
result_dict = myport.buy_hold(
datetime.datetime.fromtimestamp(start_date).date(),
datetime.datetime.fromtimestamp(end_date).date())
return flask.jsonify(result_dict)
def run_model(asset_list,
returns_style='calc',
optimization_style='sharpe',
opt_window_start=datetime.date(2018, 10, 28),
opt_time_range=4,
filter_type='expirydate',
expiry_range=52,
reopt_freq=2,
leverage=1,
asset_types='options'):
"""
Inputs: list of assets, returns style, optimization style, optimmization window start date, optimization time range,
filter type, expriry_range, re-optimization frequency, leverage
date ranges are in weeks
:return:
"""
myport = Portfolio()
rets = 'calcreturns'
print(asset_types)
for contract in asset_list:
print(contract)
if asset_types == 'options':
if contract in common_port.holdings:
contracts = common_port.find(contract)
for c in contracts:
if c is not contract:
myport.holdings[c] = common_port.holdings[c]
else:
mT.get_one_option(contract, myport)
elif asset_types == 'stocks':
if contract in common_port.holdings:
myport.holdings[contract] = common_port.holdings[contract]
else:
mT.get_one_stock(contract, myport)
elif asset_types == 'mixed':
if contract in common_port.holdings:
contracts = common_port.find(contract)
for c in contracts:
myport.holdings[c] = common_port.holdings[c]
else:
mT.get_one_option(contract, myport)
mT.get_one_stock(contract, myport)
try:
if optimization_style is 'sharpe':
print('modeling')
result_dict = myport.run(
opt_window_start, opt_time_range,
opt_window_start + datetime.timedelta(days=7 * expiry_range),
reopt_freq)
except any:
abort(404, 'error building model')
return flask.jsonify(result_dict)
def init(asset_list):
"""
This gets common or slowest stocks and options and stores them in a global variable for faster access
:param asset_list:
:return: portfolio for globals
"""
myport = Portfolio()
for contract in asset_list:
print(contract)
mT.get_one_option(contract, myport)
mT.get_one_stock(contract, myport)
return myport
def timing_test_gets():
results = []
myport = Portfolio()
for ticker in SP500:
try:
print(ticker)
start = time.perf_counter()
mT.get_one_stock(ticker, myport)
mT.get_one_option(ticker, myport)
results.append({'ticker': ticker, 'time': time.perf_counter()-start})
except json.decoder.JSONDecodeError:
print("FAILED")
time.sleep(10)
return results
def get_returns(asset_list, type, returns_style='calc'):
"""
Inputs: list of assests and returns style
default returns are calculated returns
:return: dictionary of assets and their returns
"""
myport = Portfolio()
rets = 'calcreturns'
# for asset in list, get them, and add to portfolio
for contract in asset_list:
if type is 'singlecontracts':
mT.get_one_contract(contract, myport)
elif type is 'allcontracts':
mT.get_one_option(contract, myport)
elif type is 'stock':
mT.get_one_stock(contract, myport)
# calculate returns
myport.returns()
if returns_style is 'true':
rets = 'returns'
result_dict = {contract: [rets] for contract in myport.holdings.keys()}
return flask.jsonify(result_dict)