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import numpy as np | ||
from collections import OrderedDict | ||
from czsc.analyze import CZSC, BI, Direction | ||
from czsc.signals.tas import update_cci_cache | ||
from czsc.utils import create_single_signal, get_sub_elements | ||
from loguru import logger | ||
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def cci_decision_V240620(c: CZSC, **kwargs) -> OrderedDict: | ||
"""根据CCI指标逆势用法,判断买卖决策区域 | ||
参数模板:"{freq}_N{n}CCI_决策区域V240620" | ||
**信号逻辑:** | ||
取最近N根K线,如果最小的CCI值小于 -100,开多;如果最大的CCI值大于 100,开空。 | ||
**信号列表:** | ||
- Signal('15分钟_N4CCI_决策区域V240620_开多_2次_任意_0') | ||
- Signal('15分钟_N4CCI_决策区域V240620_开多_1次_任意_0') | ||
- Signal('15分钟_N4CCI_决策区域V240620_开空_1次_任意_0') | ||
- Signal('15分钟_N4CCI_决策区域V240620_开空_2次_任意_0') | ||
:param c: CZSC对象 | ||
:param kwargs: 无 | ||
:return: 信号识别结果 | ||
""" | ||
n = int(kwargs.get("n", 2)) | ||
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freq = c.freq.value | ||
k1, k2, k3 = f"{freq}_N{n}CCI_决策区域V240620".split("_") | ||
v1 = "其他" | ||
cache_key = update_cci_cache(c, timeperiod=14) | ||
if len(c.bars_raw) < 100: | ||
return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1) | ||
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cci_seq = [x.cache[cache_key] for x in c.bars_raw[-n:]] | ||
short_cci = [x for x in cci_seq if x > 100] | ||
long_cci = [x for x in cci_seq if x < -100] | ||
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v2 = "任意" | ||
if min(cci_seq) < -100: | ||
v1 = "开多" | ||
v2 = f"{len(long_cci)}次" | ||
if max(cci_seq) > 100: | ||
v1 = "开空" | ||
v2 = f"{len(short_cci)}次" | ||
return create_single_signal(k1=k1, k2=k2, k3=k3, v1=v1, v2=v2) | ||
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def check(): | ||
from czsc.connectors import research | ||
from czsc.traders.base import check_signals_acc | ||
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symbols = research.get_symbols("A股主要指数") | ||
bars = research.get_raw_bars(symbols[0], "15分钟", "20181101", "20210101", fq="前复权") | ||
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signals_config = [{"name": cci_decision_V240620, "freq": "15分钟", "n": 4}] | ||
check_signals_acc(bars, signals_config=signals_config, height="780px", delta_days=5) # type: ignore | ||
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if __name__ == "__main__": | ||
check() |