"""
Helper for creating a sell order
"""
import analysis_engine.consts as ae_consts
import analysis_engine.utils as ae_utils
import spylunking.log.setup_logging as log_utils
log = log_utils.build_colorized_logger(name=__name__)
[docs]def build_sell_order(
ticker,
num_owned,
close,
balance,
commission,
date,
details,
use_key,
minute=None,
shares=None,
version=1,
auto_fill=True,
is_live_trading=False,
backtest_shares_default=10,
reason=None):
"""build_sell_order
Create an algorithm sell order as a dictionary
:param ticker: ticker
:param num_owned: integer current owned
number of shares for this asset
:param close: float closing price of the asset
:param balance: float amount of available capital
:param commission: float for commission costs
:param date: string trade date for that row usually
``COMMON_DATE_FORMAT`` (``YYYY-MM-DD``)
:param minute: optional - string with the minute that the
order was placed. format is
``COMMON_TICK_DATE_FORMAT`` (``YYYY-MM-DD HH:MM:SS``)
:param details: dictionary for full row of values to review
all sells after the algorithm finishes.
(usually ``row.to_json()``)
:param use_key: string for redis and s3 publishing of the algorithm
result dictionary as a json-serialized dictionary
:param shares: optional - integer number of shares to sell
if None sell all ``num_owned`` shares at the ``close``.
:param version: optional - version tracking integer
:param auto_fill: optional - bool for not assuming the trade
filled (default ``True``)
:param is_live_trading: optional - bool for filling trades
for live trading or for backtest tuning filled
(default ``False`` which is backtest mode)
:param backtest_shares_default: optional - integer for
simulating shares during a backtest even if there
are not enough funds
(default ``10``)
:param reason: optional - string for recording why the algo
decided to sell for review after the algorithm finishes
"""
status = ae_consts.TRADE_OPEN
s3_bucket_name = ae_consts.ALGO_SELLS_S3_BUCKET_NAME
s3_key = use_key
redis_key = use_key
s3_enabled = True
redis_enabled = True
cost_of_trade = None
sell_price = 0.0
new_shares = num_owned
new_balance = balance
created_date = None
tradable_funds = balance - commission
if num_owned == 0:
status = ae_consts.TRADE_NO_SHARES_TO_SELL
elif close > 0.1 and tradable_funds > 10.0:
cost_of_trade = commission
if shares:
if shares > num_owned:
shares = num_owned
else:
shares = num_owned
sell_price = ae_consts.to_f(
val=(shares * close) + commission)
if cost_of_trade > balance:
status = ae_consts.TRADE_NOT_ENOUGH_FUNDS
else:
created_date = ae_utils.utc_now_str()
if auto_fill:
new_shares = num_owned - shares
new_balance = ae_consts.to_f(balance + sell_price)
status = ae_consts.TRADE_FILLED
else:
new_shares = shares
new_balance = balance
else:
status = ae_consts.TRADE_NOT_ENOUGH_FUNDS
order_dict = {
'ticker': ticker,
'status': status,
'balance': new_balance,
'shares': new_shares,
'sell_price': sell_price,
'prev_balance': balance,
'prev_shares': num_owned,
'close': close,
'details': details,
'reason': reason,
'date': date,
'minute': minute,
'created': created_date,
's3_bucket': s3_bucket_name,
's3_key': s3_key,
'redis_key': redis_key,
's3_enabled': s3_enabled,
'redis_enabled': redis_enabled,
'version': version
}
use_date = minute
if not use_date:
use_date = date
log.debug(
f'{ticker} {use_date} sell '
f'{ae_consts.get_status(status=order_dict["status"])} '
f'order={ae_consts.ppj(order_dict)}')
return order_dict
# end of build_sell_order