def get_stock_holdings(
self, year=None, season=None, date=yesterdayobj(), threhold=100
):
"""
获取整个基金组合的底层股票持仓总和和细节，组合穿透
:param year: 基于的基金季报年份
:param season: 基于的基金季报季度
:param date: 默认昨天
:param threhold: 默认100。小于100元的底层股票将不在最后的结果中展示
:return: pd.DataFrame column: name, code, value, ratio
"""
d = {}
if year is None or season is None:
rd = convert_date(date) - pd.Timedelta(days=120)
if not year:
year = rd.year
if not season:
season = int((rd.month - 0.1) / 3) + 1
logger.debug("use %s, %s for fund report" % (year, season))
for f in self.fundtradeobj:
if isinstance(f, itrade):
if f.get_type() == "股票":
code = f.code
elif f.get_type() == "场内基金":
code = f.code[2:]
else:
continue
else:
code = f.code
value = f.briefdailyreport(date).get("currentvalue", 0)
if value > 0:
if code.startswith("SH") or code.startswith("SZ"):
stock = code
d[stock] = d.get(stock, 0) + value
elif code == "mf":
continue
else:
df = get_fund_holdings(code, year, season)
if df is None:
continue
for _, row in df.iterrows():
stock = row["code"]
stock = ttjjcode(stock)
d[stock] = d.get(stock, 0) + row["ratio"] / 100 * value
# print("%s has %s contribution from %s" %(stock, row["ratio"] / 100 * value, f.name))
l = []
for code, value in sorted(d.items(), key=lambda item: -item[1]):
if value >= threhold:
try:
name = get_rt(code)["name"]
except:
name = code
l.append([name, code, value])
fdf = pd.DataFrame(l, columns=["name", "code", "value"])
fdf["ratio"] = fdf["value"] / fdf["value"].sum()
return fdf
def __init__(self,
code,
bondrate=None,
riskfreerate=None,
volatility=None,
name=None):
"""
:param code: str. 转债代码，包含 SH 或 SZ 字头
:param bondrate: Optional[float]. 评估所用的债券折现率，默认使用中证企业债对应信用评级对应久期的利率
:param riskfreerate: Optioal[float]. 评估期权价值所用的无风险利率，默认使用国债对应久期的年利率。
:param volatility: Optional[float]. 正股波动性百分点，默认在一个范围浮动加上历史波动率的小幅修正。
:param name: str. 对于历史回测，可以直接提供 str，免得多次 get_rt 获取 name
"""
# 应该注意到该模型除了当天外，其他时间估计会利用现在的转股价，对于以前下修过转股价的转债历史价值估计有问题
self.code = code
self.refbondrate = bondrate
self.bondrate = self.refbondrate
self.refriskfreerate = riskfreerate
self.riskfreerate = self.refriskfreerate
self.refvolatility = volatility
self.volatility = self.refvolatility
self.name = name
r = rget("https://www.jisilu.cn/data/convert_bond_detail/" + code[2:])
r.encoding = "utf-8"
b = BeautifulSoup(r.text, "lxml")
self.rlist = [
float(re.search(r"[\D]*([\d]*.[\d]*)\%", s).group(1))
for s in b.select("td[id=cpn_desc]")[0].string.split("、")
]
self.rlist.append(float(b.select("td[id=redeem_price]")[0].string))
self.rlist[-1] -= self.rlist[-2] # 最后一年不含息返多少
self.scode = (b.select("td[class=jisilu_nav]")
[0].contents[1].string.split("-")[1].strip())
self.scode = ttjjcode(self.scode) # 标准化股票代码
self.zgj = float(b.select("td[id=convert_price]")[0].string) # 转股价
self.rating = b.select("td[id=rating_cd]")[0].string
self.enddate = b.select("td[id=maturity_dt]")[0].string