def back_test_ichimoku(self):
if len(self.candles) <= 52:
return None
signal_events = SignalEvents()
tenkan, kijun, senkou_a, senkou_b, chikou = ichimoku_cloud(self.closes)
for i in range(1, len(self.candles)):
if (chikou[i - 1] < self.candles[i - 1].high
and chikou[i] >= self.candles[i].high
and senkou_a[i] < self.candles[i].low
and senkou_b[i] < self.candles[i].low
and tenkan[i] > kijun[i]):
signal_events.buy(product_code=self.product_code,
time=self.candles[i].time,
price=self.candles[i].close,
units=1.0,
save=False)
if (chikou[i - 1] > self.candles[i - 1].low
and chikou[i] <= self.candles[i].low
and senkou_a[i] > self.candles[i].high
and senkou_b[i] > self.candles[i].high
and tenkan[i] < kijun[i]):
signal_events.sell(product_code=self.product_code,
time=self.candles[i].time,
price=self.candles[i].close,
units=1.0,
save=False)
return signal_events
def add_ichimoku(self):
if len(self.closes) >= 9:
tenkan, kijun, senkou_a, senkou_b, chikou = ichimoku_cloud(
self.closes)
self.ichimoku_cloud = IchimokuCloud(tenkan, kijun, senkou_a,
senkou_b, chikou)
return True
return False
def trade(self):
logger.info('action=trade status=run')
params = self.optimized_trade_params
if params is None:
return
df = DataFrameCandle(self.product_code, self.duration)
df.set_all_candles(self.past_period)
if params.ema_enable:
ema_values_1 = talib.EMA(np.array(df.closes), params.ema_period_1)
ema_values_2 = talib.EMA(np.array(df.closes), params.ema_period_2)
if params.bb_enable:
bb_up, _, bb_down = talib.BBANDS(np.array(df.closes), params.bb_n, params.bb_k, params.bb_k, 0)
if params.ichimoku_enable:
tenkan, kijun, senkou_a, senkou_b, chikou = ichimoku_cloud(df.closes)
if params.rsi_enable:
rsi_values = talib.RSI(np.array(df.closes), params.rsi_period)
if params.macd_enable:
macd, macd_signal, _ = talib.MACD(np.array(df.closes), params.macd_fast_period, params.macd_slow_period, params.macd_signal_period)
for i in range(1, len(df.candles)):
buy_point, sell_point = 0, 0
if params.ema_enable and params.ema_period_1 <= i and params.ema_period_2 <= i:
if ema_values_1[i - 1] < ema_values_2[i - 1] and ema_values_1[i] >= ema_values_2[i]:
buy_point += 1
if ema_values_1[i - 1] > ema_values_2[i - 1] and ema_values_1[i] <= ema_values_2[i]:
sell_point += 1
if params.bb_enable and params.bb_n <= i:
if bb_down[i - 1] > df.candles[i - 1].close and bb_down[i] <= df.candles[i].close:
buy_point += 1
if bb_up[i - 1] < df.candles[i - 1].close and bb_up[i] >= df.candles[i].close:
sell_point += 1
if params.ichimoku_enable:
if (chikou[i-1] < df.candles[i-1].high and
chikou[i] >= df.candles[i].high and
senkou_a[i] < df.candles[i].low and
senkou_b[i] < df.candles[i].low and
tenkan[i] > kijun[i]):
buy_point += 1
if (chikou[i - 1] > df.candles[i - 1].low and
chikou[i] <= df.candles[i].low and
senkou_a[i] > df.candles[i].high and
senkou_b[i] > df.candles[i].high and
tenkan[i] < kijun[i]):
sell_point += 1
if params.macd_enable:
if macd[i] < 0 and macd_signal[i] < 0 and macd[i - 1] < macd_signal[i - 1] and macd[i] >= macd_signal[i]:
buy_point += 1
if macd[i] > 0 and macd_signal[i] > 0 and macd[i-1] > macd_signal[i - 1] and macd[i] <= macd_signal[i]:
sell_point += 1
if params.rsi_enable and rsi_values[i-1] != 0 and rsi_values[i-1] != 100:
if rsi_values[i-1] < params.rsi_buy_thread and rsi_values[i] >= params.rsi_buy_thread:
buy_point += 1
if rsi_values[i-1] > params.rsi_sell_thread and rsi_values[i] <= params.rsi_sell_thread:
sell_point += 1
if buy_point > 0:
if not self.buy(df.candles[i]):
continue
self.stop_limit = df.candles[i].close * self.stop_limit_percent
if sell_point > 0 or self.stop_limit > df.candles[i].close:
if not self.sell(df.candles[i]):
continue
self.stop_limit = 0.0
self.update_optimize_params(is_continue=True)
