36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
"""强势高开 — 高开 > 3% 且保持上涨, 集合竞价强势"""
|
|
import polars as pl
|
|
|
|
META = {
|
|
"id": "strong_open",
|
|
"name": "强势高开",
|
|
"description": "高开 > 3% 且收盘高于开盘价, 集合竞价强势",
|
|
"tags": ["高开", "强势"],
|
|
"params": [
|
|
{"id": "min_open_gap", "label": "最低高开%", "type": "float",
|
|
"default": 3.0, "min": 1.0, "max": 10.0, "step": 0.5},
|
|
{"id": "min_change", "label": "最低涨幅%", "type": "float",
|
|
"default": 3.0, "min": 1.0, "max": 10.0, "step": 0.5},
|
|
],
|
|
"scoring": {"change_pct": 0.4, "amplitude": 0.2, "amount": 0.4},
|
|
"order_by": "score",
|
|
"descending": True,
|
|
"limit": 50,
|
|
}
|
|
|
|
ENTRY_SIGNALS = []
|
|
EXIT_SIGNALS = ["signal_ma20_breakdown"]
|
|
STOP_LOSS = -0.05
|
|
MAX_HOLD_DAYS = 10
|
|
ALERTS = []
|
|
|
|
|
|
def filter(df: pl.DataFrame, params: dict) -> pl.Expr:
|
|
min_gap = params.get("min_open_gap", 3.0) / 100.0
|
|
min_chg = params.get("min_change", 3.0) / 100.0
|
|
return (
|
|
(pl.col("open") > pl.col("prev_close") * (1 + min_gap))
|
|
& (pl.col("close") > pl.col("open"))
|
|
& (pl.col("change_pct") > min_chg)
|
|
)
|