def get_data(start, end, symbol, exchange, level):
""" using rqdatac to make an example """
import rqdatac as rq
from rqdatac import get_price, id_convert
username = "******"
password = "******" \
"t7AbdBZEBqRK74fIJH5vsaAfFQgl-tuB8l03axrW8cyN6-nBUho_6Y5VCRI63Mx_PN54nsQOpc1psIGEz" \
"gND8c6Y=bqMVlABkpSlrDNk4DgG-1QXNknJtk0Kkw2axvFDa0E_XPMqOcBxifuRa_DFI2svseXU-8A" \
"eLjchnTkeuvQkKh6nrfehVDiXjoMeq5sXgqpbgFAd4A5j2B1a0gpE3cb5kXb42n13fGwFaGris" \
"8-eKzz_jncvuAamkJEQQV0aLdiw="
host = "rqdatad-pro.ricequant.com"
port = 16011
rq.init(username, password, (host, port))
symbol_rq = id_convert(symbol)
data = get_price(symbol_rq,
start_date=start,
end_date=end,
frequency=level,
fields=None,
adjust_type='pre',
skip_suspended=False,
market='cn',
expect_df=False)
origin = data.to_dict(orient='records')
result = []
for x in origin:
do = {}
do['open_price'] = x['open']
do['low_price'] = x['low']
do['high_price'] = x['high']
do['close_price'] = x['close']
do['datetime'] = datetime.strptime(str(x['trading_date']),
"%Y-%m-%d %H:%M:%S")
do['symbol'] = symbol
do['local_symbol'] = symbol + "." + exchange
do['exchange'] = exchange
result.append(do)
return result
for D in [5,10,20,40]:
for threshold in [0.3]:
print("rank"+str(rank)+"D"+str(D)+"threshold"+str(threshold)+".csv")
position=set_position(rank,threshold,D)
position.to_csv("rank"+str(rank)+"D"+str(D)+"threshold"+str(threshold)+"_position.csv",index=None)
price=pd.read_csv("price.csv")
price=price.pivot(index='trade_date',columns='stcode',values='price')
#转换日期格式
price.index=pd.to_datetime(price.index,format='%Y%m%d')
price.index=price.index.strftime("%Y-%m-%d")
#转换股票代码
import rqdatac as rq
rq.init()
new_col=rq.id_convert(list(price.columns))
price.columns=new_col
##处理个股收益率
def forward_return(price,holding_period):
"""
:param price: 收盘价
:param holding_period:持有期
:return: 收益率序列
"""
df_return=price/price.shift(-1*holding_period)-1
return df_return
forward_return(price,5).to_csv("rt_5.csv")
forward_return(price,10).to_csv("rt_10.csv")
forward_return(price,20).to_csv("rt_20.csv")
forward_return(price,40).to_csv("rt_40.csv")
'CI005008.WI': '建材',
'CI005024.WI': '交通运输',
'CI005004.WI': '电力及公用事业',
'CI005029.WI': '综合',
}
group_list = ['周期', '制造', '医药', '消费', '科技', '金融', '基地', '综合']
temp = w.wset(
"shstockholdings",
f"date={date_end};field=wind_code,sec_name,hold_stocks,change_holdstocks")
sh_holdings = pd.DataFrame(temp.Data, index=temp.Fields).T
temp = w.wset(
"szstockholdings",
f"date={date_end};field=wind_code,sec_name,hold_stocks,change_holdstocks")
sz_holdings = pd.DataFrame(temp.Data, index=temp.Fields).T
sh_holdings['rq_code'] = rq.id_convert(sh_holdings['wind_code'].tolist())
sz_holdings['rq_code'] = rq.id_convert(sz_holdings['wind_code'].tolist())
sh_holdings = sh_holdings.set_index('rq_code')
sz_holdings = sz_holdings.set_index('rq_code')
hk_to_all_stock = (sh_holdings['change_holdstocks'].append(
sz_holdings['change_holdstocks']) * md.loc[date_end]).dropna() / 1e8
citics = rq.get_instrument_industry(hk_to_all_stock.index,
source='citics_2019',
level=1,
date=date_end)
temp_sh = w.wset("shszhkstockholdings", "date=" + date + ";tradeboard=shn")
temp_sz = w.wset("shszhkstockholdings", "date=" + date + ";tradeboard=szn")
sh_holding_detail = pd.DataFrame(temp_sh.Data, index=temp_sh.Fields).T
sh_holding_detail['wind_code'] = sh_holding_detail['wind_code'].apply(
def id_convert(self, ctpCode):
return rq.id_convert(ctpCode)