[新手小白] 量价共振分时策略 为什么回测无任何交易数据
由bqg7lmdh创建，最终由bqg7lmdh 被浏览 7 用户
小白第一次使用这个工具，折腾了几天都是没有交易数据，不知道问题出在哪里，请大神指教。
我在ai策略助手里测试提示词如下：
量价共振策略：5分钟分时周期，当量比> 1.5 且股票价格涨幅 > 0.5% 时买入总资金的10%，买入价格回落1%，立即止损止盈；上涨超过3%，分批止盈；初始资金为100万；手续费按行业规则设置（买0.03%，卖0.13%，单笔最低5元）
测试代码：
from bigmodule import M
# <aistudiograph>
import pandas as pd
from datetime import datetime, timedelta
# 近一年到今天
today = datetime.today()
end_date = today.strftime('%Y-%m-%d 15:00:00')
start_date = (today - timedelta(days=365)).strftime('%Y-%m-%d 09:30:00')
# @param(id="m5", name="initialize")
def m5_initialize_bigquant_run(context):
from bigtrader.finance.commission import PerOrder
context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))
context.stop_profit_level = dict() # 止盈层级跟踪
context.last_buy_price = dict() # 记录买入成本
# @param(id="m5", name="handle_data")
def m5_handle_data_bigquant_run(context, data):
import numpy as np
current_dt = getattr(data, "current_dt", None)
if current_dt is None:
return
today_df = pd.DataFrame()
try:
if hasattr(context, "data") and isinstance(context.data, pd.DataFrame):
time_str = current_dt.strftime("%Y-%m-%d %H:%M:%S")
today_df = context.data[context.data["date"] == time_str]
except Exception:
pass
account_positions = set(context.get_account_positions().keys())
target_instruments = set(today_df.get("instrument", []))
for instrument in account_positions - target_instruments:
try:
context.order_target_percent(instrument, 0)
except Exception:
pass
context.stop_profit_level.pop(instrument, None)
context.last_buy_price.pop(instrument, None)
for _, x in today_df.iterrows():
ins = x.instrument
try:
position = context.get_position(ins)
except Exception:
position = None
if position is not None and getattr(position, "amount", 0) > 0:
continue
try:
context.order_target_percent(ins, 0.1)
except Exception:
continue
context.stop_profit_level[ins] = 0
context.last_buy_price[ins] = None
for ins in list(account_positions):
try:
position = context.get_position(ins)
except Exception:
continue
if position is None or getattr(position, "amount", 0) == 0:
continue
last_price = getattr(position, "last_price", None)
cost_price = getattr(position, "cost_price", None)
if context.last_buy_price.get(ins) is None and cost_price is not None and cost_price > 0 and np.isfinite(cost_price):
context.last_buy_price[ins] = cost_price
buy_price = context.last_buy_price.get(ins, cost_price)
if buy_price is None or buy_price == 0 or not np.isfinite(buy_price):
continue
if last_price is None or not np.isfinite(last_price):
continue
try:
return_pct = (float(last_price) - float(buy_price)) / float(buy_price)
except Exception:
continue
if not np.isfinite(return_pct):
continue
# 止损：跌超1%立即清仓
if return_pct <= -0.01:
try:
context.order_target_percent(ins, 0)
except Exception:
pass
context.stop_profit_level.pop(ins, None)
context.last_buy_price.pop(ins, None)
continue
# 止盈：涨3%即全部止盈（如需分级止盈可自行扩展）
if return_pct >= 0.03 and context.stop_profit_level.get(ins, 0) < 1:
try:
context.order_target_percent(ins, 0)
except Exception:
pass
context.stop_profit_level[ins] = 1
context.last_buy_price.pop(ins, None)
# @module(comment="A股基础筛选，非ST，上市满20天")
m1 = M.cn_stock_basic_selector.v8(
drop_suspended=True, # 分钟级容易抽中停牌，多加保护
m_name="m1"
)
# @module(comment="输入分时量价因子表达式")
m2 = M.input_features_dai.v30(
input_1=m1.data,
mode="表达式",
expr="volume/m_avg(volume, 48) AS vol_rate\n(close/m_lag(close, 1)-1) AS pct_chg\nclose, open\nvol_rate AS score",
expr_filters="amount > 0\nlist_days > 20\nst_status = 0\nvol_rate > 1.5\npct_chg > 0.005",
expr_tables="cn_stock_prefactors",
extra_fields="date, instrument",
order_by="date, instrument",
expr_drop_na=True,
extract_data=False,
m_name="m2"
)
# @module(comment="抽取5分钟分时周期数据")
m3 = M.extract_data_dai.v20(
sql=m2.data,
start_date=start_date,
start_date_bound_to_trading_date=True,
end_date=end_date,
end_date_bound_to_trading_date=True,
before_start_days=7,
keep_before=False,
debug=False,
m_name="m3"
)
# @module(comment="评分分仓，等权0.1持仓")
m4 = M.score_to_position.v4(
input_1=m3.data,
score_field="score DESC",
hold_count=0,
position_expr="0.1 AS position",
total_position=1,
extract_data=True,
m_name="m4"
)
# @module(comment="高频回测，5分钟open成交，严格止损止盈")
m5 = M.bigtrader.v43(
data=m4.data,
start_date=start_date,
end_date=end_date,
initialize=m5_initialize_bigquant_run,
handle_data=m5_handle_data_bigquant_run,
capital_base=1000000,
frequency="minute",
product_type="股票",
rebalance_period_type="交易日",
rebalance_period_days="1",
rebalance_period_roll_forward=True,
backtest_engine_mode="标准模式",
before_start_days=0,
volume_limit=1,
order_price_field_buy="open",
order_price_field_sell="open",
benchmark="沪深300指数",
plot_charts=False,
debug=False,
backtest_only=True, # 防止回测后处理因NaN报错
m_name="m5"
)
# </aistudiograph>
回测结果如下：\n