问财量化选股策略逻辑
选股逻辑：选择换手率在3%到12%之间，涨跌幅乘以超大单净量大于0，并且股票代码以60开头。
选股逻辑分析
该选股逻辑在原有的基础上加入了股票代码首位数字限制，过滤掉不符合规定的股票。同时，该选股逻辑综合考虑了交易活跃程度和市场热度等因素，并要求每只股票必须满足一定的换手率和涨跌幅条件。通过选择这些具有活跃交易和上涨空间的股票，有望获得不错的选股效果。
有何风险？
该选股策略可能会漏掉一些未来表现较好但目前交易不活跃的股票，并且股票代码限制可能会导致某些优质股票被过滤掉。
如何优化？
可以加入更多筛选条件，如基本面指标、盈利能力等等，进一步筛选具有投资价值的股票。此外，可以采用机器学习等方法，提高选股的精度和效率。
最终的选股逻辑
选择换手率在3%到12%之间，涨跌幅乘以超大单净量大于0，并且股票代码以60开头的股票为选股范围。
同花顺指标公式代码参考
以下是同花顺指标所需公式：
选股公式：
-- 计算涨跌幅乘以超大单净量
SuperVolume: (C*Big)/10000;
-- 计算选股
SELECT STOCK_SYMBOL FROM (
SELECT STOCK_SYMBOL AS code, (C1 / C0) * SuperVolume AS Score FROM
(
SELECT STOCK_SYMBOL AS code, CLOSE AS C0 FROM CandlesMin WHERE Cdl[:1] = LAST AND TIME = [TIME-1] AND Year(DATE) = YEAR(TODAY) AND LEFT(code, 2) = '60'
) ST,
(
SELECT STOCK_SYMBOL AS code, CLOSE AS C1 FROM CandlesMin WHERE Cdl[:1] = LAST AND TIME = [TIME-0] AND Year(DATE) = YEAR(TODAY) AND LEFT(code, 2) = '60'
) MT,
(
SELECT STOCK_SYMBOL AS code, BUY_VOL_L_VOL AS Big FROM CandlesDay WHERE Cdl[:1] = LAST AND TIME = [TIME-1] AND Year(DATE) = YEAR(TODAY) AND LEFT(code, 2) = '60'
) BT
WHERE ST.code = MT.code AND MT.code = BT.code AND ST.O / MA10 >= 0.98 AND ST.O / MA10 <= 1.02 AND VOL >= 1000000 AND Score > 0 AND C1 >= 5
ORDER BY Score DESC
LIMIT 10
Python代码参考
以下是Python代码实现该选股逻辑：
import pandas as pd
from typing import List
from datetime import datetime, timedelta
def select_stock(data: pd.DataFrame, n=10) -> List[str]:
selected_stocks = []
for code, df in data.groupby(level=0):
df = df.sort_values('trade_time', ascending=True)
if (df['float_shares'].iloc[-1] / 1000000000 <= 5.5) and \
(df['volume'].iloc[-1] / df['volume'].iloc[-6:-1].mean() > 3) and \
(df['turnover_rate'].iloc[-1] > 3) and (df['turnover_rate'].iloc[-1] < 12) and \
(df['pct_chg'].iloc[-1] * abs(df['buy_volume'].iloc[-1] - df['sell_volume'].iloc[-1]) / 10000 > 0) and \
(df['ts_code'].iloc[-1][0:2] == '60'):
s_weight = df['turnover_rate'].mean() * df['volume'].mean() / (df['close'].iloc[-1] * 10000)
selected_stocks.append((code, s_weight))
selected_stocks.sort(key=lambda x: x[1], reverse=True)
selected_stocks = selected_stocks[:n]
return [x[0] for x in selected_stocks]
## 如何进行量化策略实盘？
请把您优化好的选股语句放入文章最下面模板的选股语句中即可。
select_sentence = '市值小于100亿' #选股语句。
模板如何使用？
点击图标右上方的复制按钮，复制到自己的账户即可使用模板进行回测。
## 如果有任何问题请添加 下方的二维码进群提问。
