async def load_symbol_data(
self,
symbol: str,
days: int,
) -> None:
start_date = date.today() - timedelta(days=days)
_minute_data = get_historical_data_from_polygon_by_range(
self.data_api, [symbol], start_date, "day")
for index, row in _minute_data[symbol].iterrows():
indicators: Dict = {}
if self.indicators:
for indicator in self.indicators:
if indicator == "mama":
mama, fama = MAMA(
_minute_data[symbol]["close"][:index].dropna())
indicators["mama"] = (
mama[-1] if not math.isnan(mama[-1]) else None)
indicators["fama"] = (
fama[-1] if not math.isnan(fama[-1]) else None)
daily_bar = StockOhlc(
symbol=symbol,
symbol_date=index,
open=row["open"],
high=row["high"],
low=row["low"],
close=row["close"],
volume=int(row["volume"]),
indicators=indicators,
)
await daily_bar.save()
tlog(f"saved {len(_minute_data[symbol].index)} days for {symbol}")
def _calc_indicator(self, OHLCV_input):
"""
Calculates the EMA technical indicator using a wrapper for the TA-lib
Args:
:param OHLCV_input: the dataframe with the Open, High, Low, Close and Volume values
:type OHLCV_input: pandas DataFrame
Returns:
DataFrame with the indicators values.
"""
try:
close = OHLCV_input['close'].values[:, 0]
except IndexError:
close = OHLCV_input['close'].values
return DataFrame(MAMA(close, self.__fastlimit, self.__slowlimit))
async def run(
self,
symbol: str,
shortable: bool,
position: int,
minute_history: df,
now: datetime,
portfolio_value: float = None,
trading_api: tradeapi = None,
debug: bool = False,
backtesting: bool = False,
) -> Tuple[bool, Dict]:
data = minute_history.iloc[-1]
mama, fama = MAMA(minute_history["close"])
if mama[-1] > fama[-1]:
buy_price = data.close
stop_price = data.close * 0.98
target_price = data.close * 1.05
stop_prices[symbol] = stop_price
target_prices[symbol] = target_price
if portfolio_value is None:
if trading_api:
retry = 3
while retry > 0:
try:
portfolio_value = float(
trading_api.get_account().portfolio_value)
break
except ConnectionError as e:
tlog(
f"[{symbol}][{now}[Error] get_account() failed w/ {e}, retrying {retry} more times"
)
await asyncio.sleep(0)
retry -= 1
if not portfolio_value:
tlog(
"f[{symbol}][{now}[Error] failed to get portfolio_value"
)
return False, {}
else:
raise Exception(
f"{self.name}: both portfolio_value and trading_api can't be None"
)
shares_to_buy = (portfolio_value * config.risk //
(data.close - stop_prices[symbol]))
if not shares_to_buy:
shares_to_buy = 1
buy_indicators[symbol] = {
"mama": mama[-5:].tolist(),
"fama": fama[-5:].tolist(),
}
tlog(
f"[{self.name}][{now}] Submitting buy for {shares_to_buy} shares of {symbol} at {buy_price} target {target_prices[symbol]} stop {stop_prices[symbol]}"
)
return True, {
"side": "buy",
"qty": str(shares_to_buy),
"type": "limit",
"limit_price": str(buy_price),
}
if (await self.is_sell_time(now) and position
and last_used_strategy[symbol].name == self.name
and not open_orders.get(symbol)):
mama, fama = MAMA(minute_history["close"])
to_sell: bool = False
if data.close < stop_prices[symbol]:
reason = "stopped"
to_sell = True
elif data.close >= target_prices[symbol]:
reason = "target reached"
to_sell = True
elif mama[-1] < fama[-1]:
reason = "fama below mama"
to_sell = True
if to_sell:
tlog(
f"[{self.name}][{now}] Submitting sell for {position} shares of {symbol} at market {data.close} w reason {reason}"
)
sell_indicators[symbol] = {
"mama": mama[-5:].tolist(),
"fama": fama[-5:].tolist(),
"reason": reason,
}
return (
True,
{
"side": "sell",
"qty": str(position),
"type": "market",
},
)
return False, {}
async def run(
self,
symbol: str,
shortable: bool,
position: int,
now: datetime,
minute_history: df,
portfolio_value: float = None,
debug: bool = False,
backtesting: bool = False,
) -> Tuple[bool, Dict]:
data = minute_history.iloc[-1]
mama, fama = MAMA(minute_history["close"])
if mama[-1] > fama[-1]:
buy_price = data.close
stop_price = data.close * 0.98
target_price = data.close * 1.05
stop_prices[symbol] = stop_price
target_prices[symbol] = target_price
shares_to_buy = ((portfolio_value * config.risk //
(data.close - stop_prices[symbol]))
if portfolio_value else 0)
if not shares_to_buy:
shares_to_buy = 1
buy_indicators[symbol] = {
"mama": mama[-5:].tolist(),
"fama": fama[-5:].tolist(),
}
tlog(
f"[{self.name}][{now}] Submitting buy for {shares_to_buy} shares of {symbol} at {buy_price} target {target_prices[symbol]} stop {stop_prices[symbol]}"
)
return True, {
"side": "buy",
"qty": str(shares_to_buy),
"type": "limit",
"limit_price": str(buy_price),
}
if (await self.is_sell_time(now) and position
and last_used_strategy[symbol].name == self.name
and not open_orders.get(symbol)):
mama, fama = MAMA(minute_history["close"])
to_sell: bool = False
if data.close < stop_prices[symbol]:
reason = "stopped"
to_sell = True
elif data.close >= target_prices[symbol]:
reason = "target reached"
to_sell = True
elif mama[-1] < fama[-1]:
reason = "fama below mama"
to_sell = True
if to_sell:
tlog(
f"[{self.name}][{now}] Submitting sell for {position} shares of {symbol} at market {data.close} w reason {reason}"
)
sell_indicators[symbol] = {
"mama": mama[-5:].tolist(),
"fama": fama[-5:].tolist(),
"reason": reason,
}
return (
True,
{
"side": "sell",
"qty": str(position),
"type": "market",
},
)
return False, {}