diff --git a/pure_ocean_breeze/__init__.py b/pure_ocean_breeze/__init__.py index 369f934..afb595c 100644 --- a/pure_ocean_breeze/__init__.py +++ b/pure_ocean_breeze/__init__.py @@ -2,8 +2,8 @@ 一个量化多因子研究的框架，包含数据、回测、因子加工等方面的功能 """ -__updated__ = "2022-10-30 20:13:17" -__version__ = "3.4.3" +__updated__ = "2022-10-31 23:27:16" +__version__ = "3.4.4" __author__ = "chenzongwei" __author_email__ = "winterwinter999@163.com" __url__ = "https://github.com/chen-001/pure_ocean_breeze" diff --git a/pure_ocean_breeze/labor/process.py b/pure_ocean_breeze/labor/process.py index de364aa..a1554e9 100644 --- a/pure_ocean_breeze/labor/process.py +++ b/pure_ocean_breeze/labor/process.py @@ -1,4 +1,4 @@ -__updated__ = "2022-10-31 14:03:58" +__updated__ = "2022-10-31 23:24:20" import warnings @@ -4491,13 +4491,13 @@ def test_on_index_four( else: nets = pd.concat([net300, net500, net1000], axis=1) nets.columns = ["300超额", "500超额", "1000超额"] - figs = cf.figures( - nets, - [dict(kind="line", y=list(nets.columns))], - asList=True, - ) coms = coms.reset_index() if iplot: + figs = cf.figures( + nets, + [dict(kind="line", y=list(nets.columns))], + asList=True, + ) coms = coms.rename(columns={list(coms)[0]: "绩效指标"}) table = FF.create_table(coms.iloc[::-1]) table.update_yaxes(matches=None) @@ -4580,9 +4580,168 @@ def test_on_index_four( sp["layout"].update(showlegend=True) cf.iplot(sp) else: + nets.plot() + plt.show() tb = Texttable() tb.set_cols_width([8] + [7] + [8] * 2 + [7] * 2 + [8]) tb.set_cols_dtype(["f"] * 7) tb.header(list(coms.T.reset_index().columns)) tb.add_rows(coms.T.reset_index().to_numpy(), header=True) print(tb.draw()) + + +class pure_star(object): + def __init__( + self, + fac: pd.Series, + code: str = None, + price_opens: pd.Series = None, + iplot: bool = 1, + comments_writer: pd.ExcelWriter = None, + net_values_writer: pd.ExcelWriter = None, + sheetname: str = None, + ): + """择时回测框架，输入仓位比例或信号值，依据信号买入对应的股票或指数，并考察绝对收益、超额收益和基准收益 + 回测方式为，t日收盘时获得信号，t+1日开盘时以开盘价买入，t+2开盘时以开盘价卖出 + + Parameters + ---------- + fac : pd.Series + 仓位比例序列，或信号序列，输入信号序列时即为0和1，输入仓位比例时，将每一期的收益按照对应比例缩小 + code : str, optional + 回测的资产代码，可以为股票代码或基金代码, by default None + price_opens : pd.Series, optional + 资产的开盘价序列, by default None + iplot : bool, optional + 使用cufflinks呈现回测绩效和走势图, by default 1 + comments_writer : pd.ExcelWriter, optional + 绩效评价的存储文件, by default None + net_values_writer : pd.ExcelWriter, optional + 净值序列的存储文件, by default None + sheetname : str, optional + 存储文件的工作表的名字, by default None + """ + if code is not None: + x1 = code.split(".")[0] + x2 = code.split(".")[1] + if (x1[0] == "0" or x1[:2] == "30") and x2 == "SZ": + kind = "stock" + elif x1[0] == "6" and x2 == "SH": + kind = "stock" + else: + kind = "index" + self.kind = kind + if kind == "index": + qdb = Questdb() + price_opens = qdb.get_data( + f"select date,num,close from minute_data_{kind} where code='{code}'" + ) + price_opens = price_opens[price_opens.num == "1"] + price_opens = price_opens.set_index("date").close + price_opens.index = pd.to_datetime(price_opens.index, format="%Y%m%d") + else: + price_opens = read_daily(open=1)[code] + price_opens = price_opens[price_opens.index >= fac.index.min()] + self.price_opens = price_opens + self.price_rets = price_opens.pct_change() + self.fac = fac + self.fac_rets = (self.fac.shift(2) * self.price_rets).dropna() + self.ab_rets = (self.fac_rets - self.price_rets).dropna() + self.price_rets = self.price_rets.dropna() + self.fac_nets = (1 + self.fac_rets).cumprod() + self.ab_nets = (1 + self.ab_rets).cumprod() + self.price_nets = (1 + self.price_rets).cumprod() + self.fac_nets = self.fac_nets / self.fac_nets.iloc[0] + self.ab_nets = self.ab_nets / self.ab_nets.iloc[0] + self.price_nets = self.price_nets / self.price_nets.iloc[0] + self.fac_comments = comments_on_twins(self.fac_nets, self.fac_rets) + self.ab_comments = comments_on_twins(self.ab_nets, self.ab_rets) + self.price_comments = comments_on_twins(self.price_nets, self.price_rets) + self.total_comments = pd.concat( + [self.fac_comments, self.ab_comments, self.price_comments], axis=1 + ) + self.total_nets = pd.concat( + [self.fac_nets, self.ab_nets, self.price_nets], axis=1 + ) + self.total_rets = pd.concat( + [self.fac_rets, self.ab_rets, self.price_rets], axis=1 + ) + self.total_comments.columns = ( + self.total_nets.columns + ) = self.total_rets.columns = ["因子绝对", "因子超额", "买入持有"] + self.total_comments = np.around(self.total_comments, 3) + self.iplot = iplot + self.plot() + if comments_writer is None and sheetname is not None: + from pure_ocean_breeze.state.states import COMMENTS_WRITER + + comments_writer = COMMENTS_WRITER + self.total_comments.to_excel(comments_writer, sheet_name=sheetname) + if net_values_writer is None and sheetname is not None: + from pure_ocean_breeze.state.states import NET_VALUES_WRITER + + net_values_writer = NET_VALUES_WRITER + self.total_nets.to_excel(net_values_writer, sheet_name=sheetname) + + def plot(self): + coms = self.total_comments.copy().reset_index() + if self.iplot: + figs = cf.figures( + self.total_nets, + [dict(kind="line", y=list(self.total_nets.columns))], + asList=True, + ) + coms = coms.rename(columns={list(coms)[0]: "绩效指标"}) + table = FF.create_table(coms.iloc[::-1]) + table.update_yaxes(matches=None) + figs.append(table) + figs = [figs[-1]] + figs[:-1] + figs[1].update_layout( + legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01) + ) + base_layout = cf.tools.get_base_layout(figs) + sp = cf.subplots( + figs, + shape=(2, 10), + base_layout=base_layout, + vertical_spacing=0.15, + horizontal_spacing=0.03, + shared_yaxes=False, + specs=[ + [ + None, + {"rowspan": 2, "colspan": 3}, + None, + None, + {"rowspan": 2, "colspan": 6}, + None, + None, + None, + None, + None, + ], + [ + None, + None, + None, + None, + None, + None, + None, + None, + None, + None, + ], + ], + ) + sp["layout"].update(showlegend=True) + cf.iplot(sp) + else: + self.total_nets.plot() + plt.show() + tb = Texttable() + tb.set_cols_width([8] + [7] + [8] * 2 + [7] * 2 + [8]) + tb.set_cols_dtype(["f"] * 7) + tb.header(list(coms.T.reset_index().columns)) + tb.add_rows(coms.T.reset_index().to_numpy(), header=True) + print(tb.draw()) diff --git "a/\346\233\264\346\226\260\346\227\245\345\277\227/version3.md" "b/\346\233\264\346\226\260\346\227\245\345\277\227/version3.md" index f4adda6..dc3f268 100644 --- "a/\346\233\264\346\226\260\346\227\245\345\277\227/version3.md" +++ "b/\346\233\264\346\226\260\346\227\245\345\277\227/version3.md" @@ -1,5 +1,8 @@ ## 更新日志🗓 — v3 +* v3.4.4 — 2022.10.31 +> 1. 修复了test_on_index_four使用matplotlib画图不显示的bug +> 1. 新增了择时回测框架pure_star * v3.4.3 — 2022.10.31 > 1. 给read_index_three增加了国证2000指数的行情数据 > 1. 给make_relative_comments增加了gz2000参数，用于计算相对国证2000指数的超额收益；增加了show_nets参数，用于同时返回多头超额评价指标和超额净值数据