/
test_trade.py
193 lines (163 loc) · 6.61 KB
/
test_trade.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
import sys
sys.path.insert(0, "../")
import xalpha as xa
import pytest
import pandas as pd
path = "demo.csv"
path1 = "demo1.csv"
path2 = "demo2.csv"
cm = xa.fundinfo("164818")
cm.rate = 0.0
# 工银传媒分级转型后，天天基金显示的申购费率变化为1.0，无折扣，之前的测试数据似乎基于免申购费, 赎回费率信息也发生了变化
feeinfo = [
"小于7天",
"1.50%",
"大于等于7天，小于1年",
"0.70%",
"大于等于1年，小于2年",
"0.25%",
"大于等于2年",
"0.00%",
] # 老赎回信息
cm.set_feeinfo(feeinfo)
cm.set_price("comment", "20201125", -1.041)
statb = xa.record(path).status
statl = xa.record(path1, format="list").status
statnb = xa.record(path2)
print(cm.feeinfo)
cm_t = xa.trade(cm, statb)
ioconf = {"save": True, "fetch": True, "path": "pytest", "form": "csv"}
def test_trade():
assert cm_t.cftable.loc[2, "share"] == -129.14
assert round(cm_t.xirrrate("2018-03-03"), 3) == -0.24
assert cm_t.dailyreport("2018-07-29").iloc[0]["单位成本"] == 1.346
cm_t.v_tradecost("2018-08-01")
cm_t.v_totvalue("2018-07-31")
cm_t.v_tradevolume(freq="M")
def test_customize_fee():
df = pd.DataFrame(
{"date": ["2020-05-28", "2020-06-01"], "519732": [500.005, -0.505]}
)
df["date"] = pd.to_datetime(df["date"])
dqzf = xa.trade(xa.fundinfo("519732"), df)
assert dqzf.dailyreport("2020-06-02")["基金分红与赎回"].iloc[0] == 2.22
assert dqzf.dailyreport("2020-05-31")["持有份额"].iloc[0] == 116.5
# issue 59
df = pd.DataFrame(
{"date": ["2020-05-28", "2020-06-01"], "519732": [10000.005, -0.505]}
)
df["date"] = pd.to_datetime(df["date"])
dqzf = xa.trade(xa.fundinfo("519732"), df)
assert round(dqzf.dailyreport("2020-05-28").iloc[0]["基金现值"], 0) == 10000.0
def test_ttjj_oversea_trade():
stt = pd.DataFrame({"date": ["20200921"], "100032": [1000], "968012": [1034]})
s = xa.mul(status=xa.record(stt))
df = s.summary("2020-09-30")
assert df[df["基金代码"] == "968012"].iloc[0]["基金收益总额"] == -20.01
def test_mul():
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=200)
assert str(excinfo.value) == "You cannot sell first when you never buy"
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=300)
assert str(excinfo.value) == "the initial total cash is too low"
cm_m = xa.mulfix(cm_t, totmoney=500)
cm_m.bcmkset(xa.indexinfo("1399971"), start="2016-09-28")
assert round(cm_m.xirrrate("2018-07-29"), 3) == -0.129
assert round(cm_m.sharpe("2018-07-30"), 3) == -1.734
cm_m.v_netvalue(benchmark=False)
assert round(cm_m.total_return("2018-07-01"), 3) == -0.209
assert round(cm_m.benchmark_volatility("2018-07-22"), 3) == 0.192
assert round(cm_m.max_drawdown("2018-08-01")[2], 2) == -0.24
cm_m.v_tradevolume()
cm_m.v_tradecost()
def test_mul_properties():
hl_m = xa.mul(status=statnb, **ioconf)
assert (
round(
hl_m.totcftable[hl_m.totcftable["date"] == "2020-03-06"].iloc[0]["cash"], 2
)
== 339.89
)
assert round(hl_m.fundtradeobj[2].cftable.iloc[1]["cash"], 2) == 1000
d = hl_m.get_portfolio_holdings(date="20190801")
d2 = hl_m.get_industry_holdings(date="20190201")
assert round(d["stock"], 2) == 299.85
assert round(d2["银行"], 2) == 48.29
hl_m2 = xa.mul(status=statnb, property={"002758": 0}, **ioconf)
# print(hl_m2.fundtradeobj[2].cftable)
assert round(hl_m2.fundtradeobj[2].cftable.iloc[1]["share"], 2) == -926.0
def test_mulfix():
tot = xa.mulfix(cm_t, status=statb, totmoney=5000)
tot.v_positions()
tot.v_positions_history("2017-01-01")
assert round(tot.summary("2018-08-04").iloc[0]["投资收益率"], 1) == 1.0
assert round(tot.xirrrate(date="2020-01-01", startdate="2018-05-01"), 2) == 0.04
eva = tot.evaluation()
assert round(eva.correlation_table(end="2018-07-30").iloc[0, 3], 3) == 0.095
def test_policy_buyandhold():
allin = xa.policy.buyandhold(cm, "2015-06-01")
cm_t2 = xa.trade(cm, allin.status)
cm_m2 = xa.mulfix(cm_t2)
cm_m2.bcmkset(xa.indexinfo("1399971"))
assert round(cm_m2.correlation_coefficient("2018-07-01"), 3) == 0.980
assert round(cm_m2.information_ratio("2016-07-01"), 3) == -0.385
allin.sellout("2018-06-01")
cm_t2 = xa.trade(cm, allin.status)
assert round(cm_t2.xirrrate("2019-08-12", guess=-0.9), 2) == -0.33
def test_weekly_price():
# see https://github.com/refraction-ray/xalpha/issues/27
ryjh = xa.fundinfo("008969")
bah = xa.policy.buyandhold(ryjh, start="2019-01-01", totmoney=100000)
bah.sellout("2020-05-12") # 选定日期全部卖出
jshstrade = xa.trade(ryjh, bah.status)
assert round(jshstrade.xirrrate("2020-05-01", startdate="2020-02-01"), 1) == 0.2
def test_policy_scheduled():
auto = xa.policy.scheduled(
cm, 1000, pd.date_range("2015-07-01", "2018-07-01", freq="W-THU")
)
cm_t3 = xa.trade(cm, auto.status)
cm_t3.v_tradevolume(freq="W")
assert round(cm_t3.dailyreport("2018-08-03").iloc[0]["投资收益率"], 2) == -42.07
auto2 = xa.policy.scheduled_tune(
cm,
1000,
pd.date_range("2015-07-01", "2018-07-01", freq="M"),
[(0.9, 2), (1.2, 1)],
)
auto3 = xa.policy.scheduled_window(
cm,
1000,
pd.date_range("2015-07-01", "2018-07-01", freq="M"),
[(-1, 2), (1.5, 1)],
)
def test_policy_grid():
gr = xa.policy.grid(cm, [0, 2, 2], [3, 3, 3], "2018-06-23", "2018-08-03")
tr = xa.trade(cm, gr.status)
assert round(tr.xirrrate("2018-07-13"), 2) == 11.78
def test_policy_indicator_cross():
cm.bbi()
techst = xa.policy.indicator_cross(
cm, col=["netvalue", "BBI"], start="2018-01-01", end="2018-07-07"
)
cm_tt = xa.trade(cm, techst.status)
assert round(cm_tt.dailyreport("2018-07-09").iloc[0].loc["换手率"], 1) == 14.1
def test_policy_indicator_points():
zz500 = xa.indexinfo("0000905")
zz500.psy()
st = xa.policy.indicator_points(
zz500,
col="PSYMA12",
start="2017-01-01",
buy=[(0.6, 1), (0.7, 1)],
sell=[(0.4, 1), (0.3, 1)],
buylow=False,
)
zz500_t = xa.trade(zz500, st.status)
assert (
zz500_t.dailyreport("2018-05-01").iloc[0].loc["基金收益总额"] == -6302.32
) # -6302.26
# still confused about this, seems to be a data source change, as old commits gives new results as well
def test_record_list():
tot = xa.mulfix(status=statl, totmoney=50000, **ioconf)
assert round(tot.combsummary("2019-05-04").iloc[0]["投资收益率"], 1) == 10.5