def test_bond():
df = bond.run_query(query(bond.BOND_BASIC_INFO).limit(10))
print(df)
assert len(df) == 10
df = df.set_index("code").drop("id", axis=1)
item = df.loc["131801"]
assert item.short_name == u"花呗01A1" and str(
item.maturity_date) == "2017-06-15"
item = df.loc["131811"]
assert item.short_name == "R-002" and item.maturity_date is None
pe = pd.read_csv('/Users/caichaohong/Desktop/Zenki/financials/pe_ratio.csv',
index_col='Unnamed: 0',
date_parser=dateparse) # 2924个
net_profit = pd.read_csv(
'/Users/caichaohong/Desktop/Zenki/financials/net_profit_yearly.csv',
index_col='statDate') # 2924个
market_cap = market_cap[close.columns]
pe = pe[close.columns]
#股息率
df_bank = finance.run_query(
query(finance.SW1_DAILY_VALUATION).filter(
finance.SW1_DAILY_VALUATION.code == '801780'))
# 回购
df_bond = bond.run_query(
query(bond.REPO_DAILY_PRICE).filter(
bond.REPO_DAILY_PRICE.name == 'GC182').limit(2000))
df_t1 = pd.merge(df_bond, df_bank, on='date')
df_t1 = df_t1[['date', 'close', 'dividend_ratio']]
df_t1.index = pd.to_datetime(df_t1['date'])
# 当风险偏好<0不持股
df_t1['licha'] = (df_t1['close'].rolling(60).mean() -
df_t1['dividend_ratio'].rolling(60).mean()).diff(1)
df_t1['licha'] = df_t1['licha'].fillna(method='ffill')
df_t1['hs300'] = hs300['net_value']
# 回购和价格行情日期不同
df_repo = pd.DataFrame(columns=['licha'], index=close.index)
datelist = list(set(df_t1.index).intersection(set(df_repo.index)))
df_repo['licha'].loc[datelist] = df_t1['licha'].loc[datelist]
df_repo = df_repo.fillna(method='ffill')
# encoding=utf-8
"""
本脚本对可转债数据进行研究
"""
from DataSource.auth_info import jq_login
from jqdatasdk import bond, query
if __name__ == '__main__':
jq_login()
df = bond.run_query(
query(bond.CONBOND_BASIC_INFO).filter(
bond.CONBOND_BASIC_INFO.bond_form_id == '703011'))
end = 0
