回测 回撤 hline

import pandas as pd

def first(df):
    #流通市值 30 45 60 90 120 日均价 以及在4日内高点发生回撤时候的比率
    df['lt']=df['amount']/(1000000*df['turn'])
    df['hc30']=(df['high']-df['p30'])/df['p30']
    df['hc45']=(df['high']-df['p45'])/df['p45']
    df['hc60']=(df['high']-df['p60'])/df['p60']
    df['hc90']=(df['high']-df['p90'])/df['p90']
    df['hc120']=(df['high']-df['p120'])/df['p120']
    is_pivot_high = df['high'] == df['high'].rolling(window=5, center=True).max()
    high_df = df[is_pivot_high][['mcode','date','open','close','low','high','p30','p45','p60','p90','p120','amount','turn','lt','hc30','hc45','hc60','hc90','hc120']]
    return high_df

        
results=[]
# 执行每个
results.append(first(df))

final_df=pd.concat(results,ignore_index=True)
final_df.to_csv("xxx.csv",index=False,encoding="utf-8-sig")