def test_trending_up():
df = to_dataframe(data)
ma = TA.HMA(df)
assert isinstance(trending_up(ma, 10), Series)
assert not trending_up(ma, 10).values[-1]
def buy(self,
period: int = 14,
period2: int = 14,
lower_bound: int = 10) -> np.bool_:
"""
:param period:
:param period2:
:param lower_bound:
:return:
"""
try:
raw_mfi = TA.MFI(self.df, period)
except TradeSignalException as error:
raise error
else:
buying = raw_mfi.iloc[-1] > lower_bound and raw_mfi.iloc[
-2] <= lower_bound and trending_up(
raw_mfi.iloc[:-2], period=int(period / 2)).iloc[-1]
if SU.is_valid_dataframe(self.df2):
try:
raw_mfi2 = TA.MFI(self.df2, period2)
except TradeSignalException as error:
raise error
else:
buying = buying and raw_mfi2.iloc[
-1] > lower_bound and raw_mfi2.iloc[
-2] <= lower_bound and trending_up(
raw_mfi2.iloc[:-2], period=int(
period2 / 2)).iloc[-1]
return buying
def buy(self,
period_fast: int = 12,
period_slow: int = 26,
signal: int = 9,
column: str = "close",
adjust: bool = True,
period_fast2: int = 12,
period_slow2: int = 26,
signal2: int = 9) -> np.bool_:
"""Calculate a moving average convergence-divergence buy signal from a bullish signal crossover.
An optional second dataframe can be used to calculate the signal for a different time period
:param period_fast:
:param period_slow:
:param signal:
:param column:
:param adjust:
:param period_fast2:
:param period_slow2:
:param signal2:
:return bool:
"""
try:
raw_macd = TA.MACD(self.df, period_fast, period_slow, signal, column, adjust)
except TradeSignalException as error:
raise error
else:
_is_negative = raw_macd["MACD"].iloc[-1] < 0
_below_signal = raw_macd["MACD"].iloc[-1] < raw_macd["SIGNAL"].iloc[-1]
_trending_up = trending_up(raw_macd["MACD"].iloc[:-2], period=int(period_fast/2)).iloc[-1]
buying = _is_negative and _below_signal and _trending_up
if SU.is_valid_dataframe(self.df2):
try:
raw_macd2 = TA.MACD(self.df2, period_fast2, period_slow2, signal2, column, adjust)
except TradeSignalException as error:
raise error
else:
_is_negative2 = raw_macd2["MACD"].iloc[-1] < 0
_below_signal2 = raw_macd2["MACD"].iloc[-1] < raw_macd2["SIGNAL"].iloc[-1]
_trending_up2 = trending_up(raw_macd2["MACD"].iloc[:-2], period=int(period_fast2/2)).iloc[-1]
buying = buying and _is_negative2 and _below_signal2 and _trending_up2
return buying
def buy(self, column: str = "close", lookback: int = 5) -> np.bool_:
try:
raw_obv = TA.OBV(self.df, column)
except TradeSignalException as error:
raise error
else:
buying = trending_up(self.df["close"], lookback).iloc[-1] and trending_down(raw_obv, lookback).iloc[-1]
if SU.is_valid_dataframe(self.df2):
try:
raw_obv2 = TA.OBV(self.df2, column)
except TradeSignalException as error:
raise error
else:
buying = buying and trending_up(self.df2["close"], lookback).iloc[-1] and trending_down(raw_obv2, lookback).iloc[-1]
return buying
def buy(self,
period: int = 14,
ema_period: int = 60,
column: str = "close",
adjust: bool = True,
period2: int = 14,
ema_period2: int = 60) -> np.bool_:
"""Bullish buy signal calculation based on volume zone oscillator (VZO).
The flag is generated based on a number of conditional statements generated from technical indicators.
The basic buy rule is to buy when a bullish crossover happens -- the VZO crossing over the -40% line
Along with the bullish crossover, we can use a 14 period average directional index (ADX), directional
movement index (DMI), and a 60 period EMA to confirm the trend. We do this by making sure the ADX is
at least 20, the DMI is trending upward (DI+ > DI-) and that the close price has crossed over the 60 day EMA.
An example usage might look like:
if vzo.buy() and some_other_indicator():
execute_buy_order()
:param period:
:param ema_period:
:param column:
:param adjust:
:param period2:
:param ema_period2:
:return bool:
"""
try:
# grab the indicators we need (VZO, ADX, DMI, EMA) for this signal
vzo = TA.VZO(self.df, period, column, adjust)
adx = TA.ADX(self.df, period, adjust)
dmi = TA.DMI(self.df, period, adjust)
ema = TA.EMA(self.df, ema_period, column, adjust)
except TradeSignalException as error:
raise error
else:
_vzo_bullish_cross = vzo.iloc[-1] > -40 and trending_up(vzo.iloc[:-2], period=int(period/2)).iloc[-1]
_adx_trending = adx.iloc[-1] > 20
_dmi_positive = dmi["DI+"].iloc[-1] > dmi["DI-"].iloc[-1]
_ema_bullish_cross = self.df["close"].iloc[-1] > ema.iloc[-1] and \
trending_up(self.df["close"].iloc[:-2], period=int(period/2)).iloc[-1]
buying = _vzo_bullish_cross and \
(_adx_trending or _dmi_positive) and \
_ema_bullish_cross
if SU.is_valid_dataframe(self.df2):
try:
# grab the indicators we need (VZO, ADX, DMI, EMA) for this signal
vzo2 = TA.VZO(self.df2, period2, column, adjust)
adx2 = TA.ADX(self.df2, period2, adjust)
dmi2 = TA.DMI(self.df2, period2, adjust)
ema2 = TA.EMA(self.df2, ema_period2, column, adjust)
except TradeSignalException as error:
raise error
else:
_vzo_bullish_cross2 = vzo2.iloc[-1] > -40 and trending_up(vzo2.iloc[:-2], period=int(period2/2)).iloc[-1]
_adx_trending2 = adx2.iloc[-1] > 20
_dmi_positive2 = dmi2["DI+"].iloc[-1] > dmi2["DI-"].iloc[-1]
_ema_bullish_cross2 = self.df2["close"].iloc[-1] > ema2.iloc[-1] and \
trending_up(self.df2["close"].iloc[:-2], period=int(period2/2)).iloc[-1]
buying = buying and _vzo_bullish_cross2 and (_adx_trending2 or _dmi_positive2) and _ema_bullish_cross2
return buying