def get_roll_yield(date=None, var="LR", symbol1=None, symbol2=None, df=None):
"""
指定交易日指定品种（主力和次主力）或任意两个合约的展期收益率
Parameters
------
date: string 某一天日期 format： YYYYMMDD
var: string 合约品种如RB、AL等
symbol1: string 合约 1如 rb1810
symbol2: string 合约 2 如 rb1812
df: DataFrame或None 从dailyBar得到合约价格，如果为空就在函数内部抓dailyBar，直接喂给数据可以让计算加快
Return
-------
tuple
roll_yield
near_by
deferred
"""
# date = "20200304"
date = cons.convert_date(
date) if date is not None else datetime.date.today()
if date.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % date.strftime("%Y%m%d"))
return None
if symbol1:
var = symbol_varieties(symbol1)
if not isinstance(df, pd.DataFrame):
market = symbol_market(var)
df = get_futures_daily(start_date=date, end_date=date, market=market)
if var:
df = df[~df["symbol"].str.contains(
"efp")] # 20200304 由于交易所获取的数据中会有比如 "CUefp"，所以在这里过滤
df = df[df["variety"] == var].sort_values("open_interest",
ascending=False)
df["close"] = df["close"].astype("float")
if len(df["close"]) < 2:
return None
symbol1 = df["symbol"].tolist()[0]
symbol2 = df["symbol"].tolist()[1]
close1 = df["close"][df["symbol"] == symbol1.upper()].tolist()[0]
close2 = df["close"][df["symbol"] == symbol2.upper()].tolist()[0]
a = re.sub(r"\D", "", symbol1)
a_1 = int(a[:-2])
a_2 = int(a[-2:])
b = re.sub(r"\D", "", symbol2)
b_1 = int(b[:-2])
b_2 = int(b[-2:])
c = (a_1 - b_1) * 12 + (a_2 - b_2)
if close1 == 0 or close2 == 0:
return False
if c > 0:
return np.log(close2 / close1) / c * 12, symbol2, symbol1
else:
return np.log(close2 / close1) / c * 12, symbol1, symbol2
def get_roll_yield_bar(type_method="var",
var="RB",
date="20200622",
start_day=None,
end_day=None,
plot=False):
"""
展期收益率
:param type_method: 'symbol': 获取指定交易日指定品种所有交割月合约的收盘价; 'var': 获取指定交易日所有品种两个主力合约的展期收益率(展期收益率横截面); 'date': 获取指定品种每天的两个主力合约的展期收益率(展期收益率时间序列)
:param var: 合约品种如 "RB", "AL" 等
:param date: 指定交易日 format： YYYYMMDD
:param start_day: 开始日期 format：YYYYMMDD
:param end_day: 结束日期 format：YYYYMMDD
:param plot: True or False 是否作图
:return: pandas.DataFrame
展期收益率数据(DataFrame)
ry 展期收益率
index 日期或品种
"""
date = cons.convert_date(
date) if date is not None else datetime.date.today()
start_day = (cons.convert_date(start_day)
if start_day is not None else datetime.date.today())
end_day = (cons.convert_date(end_day)
if end_day is not None else cons.convert_date(
cons.get_latest_data_date(datetime.datetime.now())))
if type_method == "symbol":
df = get_futures_daily(start_date=date,
end_date=date,
market=symbol_market(var))
df = df[df["variety"] == var]
if plot:
_plot_bar_2(df[["symbol", "close"]])
return df
if type_method == "var":
df = pd.DataFrame()
for market in ["dce", "cffex", "shfe", "czce"]:
df = df.append(
get_futures_daily(start_date=date,
end_date=date,
market=market))
var_list = list(set(df["variety"]))
if "IO" in var_list:
var_list.remove("IO") # IO 为期权
df_l = pd.DataFrame()
for var in var_list:
ry = get_roll_yield(date, var, df=df)
if ry:
df_l = df_l.append(
pd.DataFrame([ry],
index=[var],
columns=["roll_yield", "near_by",
"deferred"]))
df_l["date"] = date
df_l = df_l.sort_values("roll_yield")
if plot:
_plot_bar(df_l["roll_yield"])
return df_l
if type_method == "date":
df_l = pd.DataFrame()
while start_day <= end_day:
try:
ry = get_roll_yield(start_day, var)
if ry:
df_l = df_l.append(
pd.DataFrame(
[ry],
index=[start_day],
columns=["roll_yield", "near_by", "deferred"],
))
except:
pass
start_day += datetime.timedelta(days=1)
if plot:
_plot(df_l["roll_yield"])
return df_l