问财量化选股策略逻辑
选取振幅大于1,前25天至少有一天涨停,RSI小于65的股票进入待投资池。
选股逻辑分析
- 振幅大于1表明该股票波动性较大,有较大概率出现较高的涨幅;
- 前25天至少有一天涨停,代表该股票有望超额表现;
- RSI小于65,代表当前股票处于不是过度买入的状态,有望持续上涨。
有何风险?
- 过分依赖技术指标和历史数据;
- 忽略了股票的基本面和市场情况等因素。
如何优化?
- 将选股逻辑与股票的基本面、市场行情等维度相结合;
- 对于涨停股票,需进行更加详细的分析,避免出现个别情况影响整体判断;
- 尝试将结合更多量化指标进行综合判断。
最终的选股逻辑
选取振幅大于1,前25天至少有一天涨停,RSI小于65的股票进入待投资池。
同花顺指标公式代码参考
//振幅大于1
COND1:=(HIGH-LOW)/LOW > 0.01;
//涨停,只选取前25天,这里举例取18
COND2:=REF(MAX(HIGH,1),1)/REF(CLOSE,1)>1.097 AND (HIGH=LOW) AND (CLOSE-REF(CLOSE,1))/REF(CLOSE,1)<0.009 AND (BARSSINCE(CLOSE=REF(MAX(HIGH,1),1))/COUNT>COUNT-18;
//RSI指标
RSI6: RSI(CLOSE,6);
COND3:= RSI6 < 65;
//综合条件
CONDITION:=COND1 AND COND2 AND COND3;
SIGNAL:=CHECKCOND(CONDITION,1);
Python代码参考
import pandas as pd
import akshare as ak
from talib import abstract
def get_trade_data(stock_code):
stock_history_df = ak.stock_zh_a_daily(symbol=stock_code, adjust="hfq")
stock_history_df.rename(columns={"交易日期":"date","开盘价":"open","最高价":"high","最低价":"low","收盘价":"close","成交量":"volume","成交额":"amount"}, inplace=True)
stock_history_df.sort_values("date", ascending=True, inplace=True)
stock_history_df['pct_chg'] = stock_history_df['close'].pct_change() * 100
stock_history_df['net_volume'] = stock_history_df['close'] * stock_history_df['volume'] * stock_history_df['pct_chg'] / 100 /10000
df = stock_history_df[['date','open','high','low','close','volume','net_amount','pct_chg','net_volume']].copy()
# 振幅
cond1 = (df['high'] - df['low']) / df['low'] > 0.01
# 涨停
cond2 = (df['high'] / df['close'].shift(1) > 1.097) & (df['high'] == df['low']) & (df['close'] / df['close'].shift(1) - 1 < 0.009) & (df['close'] == df['high'].shift(1))
cond2 = cond2.rolling(window=18).sum() > 0
# RSI指标
rsi = abstract.RSI(df, timeperiod=6)
cond3 = rsi < 65
# 综合条件
basic_cond = cond1 & cond2 & cond3
df = df[basic_cond].reset_index(drop=True)
return df
def select(df):
return df
## 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。
