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