def test_long_trans_unclose():
"""
"""
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = "2017-03-20"
data["open_detail"] = [{
"orig_trd_amt": "6000.0",
"orig_trd_qty": "600",
"trd_amt": "6000.0",
"weighted_term": str(5.0 + 0.5),
"trd_qty": "800",
"open_type": "trade",
"close_amt": str(200.0 + 3600),
"unclose_qty": "400",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": str(400 * 4.5)
}, {
"orig_trd_amt": "5000.0",
"orig_trd_qty": "500",
"trd_amt": "5000.0",
"weighted_term": "6.0",
"trd_qty": "1000",
"open_type": "trade",
"close_amt": str(500.0),
"unclose_qty": "1000",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": str(1000 * 4.5)
}]
re = []
for i in data["open_detail"]:
re.append(long_trans_unclose(data, i))
re = [{
"unclose_qty": i["unclose_qty"],
"unclose_amt": i["unclose_amt"],
"return": i["return"],
"return_rate": i["return_rate"]
} for i in re]
_re = [{
"unclose_qty": 400,
"unclose_amt": 400 * 4.5,
"return": 400 * 4.5 + 200 + 400 * 9 - 6000,
"return_rate": (400 * 4.5 + 200 + 400 * 9 - 6000) / 6000.0
}, {
"unclose_qty": 1000,
"unclose_amt": 1000 * 4.5,
"return": 1000 * 4.5 + 500 - 5000,
"return_rate": (1000 * 4.5 + 500 - 5000) / 5000.0
}]
assert_dict_equal(re[0], _re[0])
assert_dict_equal(re[1], _re[1])
def test_short_compute():
"""
分红分股情况下，正常做空
"""
busi_date = "2017-03-21"
yesterday = "2017-03-20"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = busi_date
data["open_detail"] = [{
"orig_trd_amt": "-1439280.0",
"orig_trd_qty": "-14400",
"trd_amt": "-1439280.0",
"weighted_term": "1.0",
"trd_qty": "-14400",
"open_type": "trade_exception",
"close_amt": "0.0",
"unclose_qty": "-14400",
"exception_label": "0",
"open_date": "2017-03-20",
"open_timestamp": "1489993201",
"unclose_amt": "-1439280.0"
}]
data["now_trd"] = [{
"timestamp": 1490108421,
"trd_qty": -36000,
"trd_cash_flow": 0.0,
"amortize_label": 1
}, {
"timestamp": 1490108420,
"trd_qty": 0,
"trd_cash_flow": 1440.0,
"amortize_label": 1
}]
data["liab_qty"] = -50400
data["mkt_val"] = -1453032.0
re = short_compute(data, busi_date, yesterday)
_re = {
"orig_trd_amt": "-1439280.0",
"orig_trd_qty": "-14400",
"trd_amt": "-1439280.0",
"weighted_term": "2.0",
"trd_qty": "-50400",
"open_type": "trade_exception",
"close_amt": "1440.0",
"unclose_qty": "-50400",
"exception_label": "0",
"open_date": "2017-03-20",
"open_timestamp": "1489993201",
"unclose_amt": "-1453032.0"
}
assert_dict_equal(re["open_detail"][0], _re)
def test_short_compute2():
"""
考虑在分红分股情况下的，做空异常处理
"""
busi_date = "2017-03-20"
yesterday = "2017-03-17"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = busi_date
data["open_detail"] = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "4.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-100",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "-1000"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": "3.0",
"trd_qty": "-600",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-600",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": "-6000"
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "3.0",
"trd_qty": "-500",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-500",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": "-5000"
}]
data["now_trd"] = [{
"timestamp": 1489993205,
"trd_qty": 0,
"trd_cash_flow": 700.0,
"amortize_label": 1
}, {
"timestamp": 1489993206,
"trd_qty": -700,
"trd_cash_flow": 0.0,
"amortize_label": 1
}, {
"timestamp": 1489993204,
"trd_qty": 500,
"trd_cash_flow": 4500.0,
"amortize_label": 0
}]
data["liab_qty"] = None
data["mkt_val"] = None
re = short_compute(data, busi_date, yesterday)
_re = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "6.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "900.0",
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": "5.0",
"trd_qty": "-800",
"open_type": "trade",
"close_amt": str(200.0 + 3600 + 2000),
"unclose_qty": "0",
"exception_label": "1",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "5.0",
"trd_qty": "-1000",
"open_type": "trade",
"close_amt": str(500.0 + 5000),
"unclose_qty": "0",
"exception_label": "1",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": "0.0"
}]
for i in range(len(_re)):
assert_dict_equal(re["open_detail"][i], _re[i])
def test_short_trans_close():
"""
"""
data = {}
busi_date = "2017-03-20"
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = "2017-03-20"
data["open_detail"] = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "6.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "900.0",
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": str(5.0 + 0.5),
"trd_qty": "-800",
"open_type": "trade",
"close_amt": str(200.0 + 3600 + 400 * 6.0),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": str(0.0)
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "6.0",
"trd_qty": "-1000",
"open_type": "trade",
"close_amt": str(1000 * 6.0 + 500),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": str(0.0)
}, {
"orig_trd_amt": "-1100.0",
"orig_trd_qty": "-200",
"trd_amt": "-1100.0",
"weighted_term": "0.0",
"trd_qty": "-200",
"open_type": "trade",
"close_amt": str(100 * 6.0 + 100 * 5.9),
"unclose_qty": "0",
"exception_label": "0",
"open_date": busi_date,
"open_timestamp": "1489993207",
"unclose_amt": str(0.0)
}]
re = []
for i in data["open_detail"]:
re.append(short_trans_close(data, i))
_re = [{
"return_rate": 100 / 900.0,
"weighted_term": 6.0,
"trd_qty": -100,
"prd_no": "prd_no",
"open_type": "trade",
"close_date": "2017-03-20",
"open_timestamp": 1489993201,
"return": 100.0,
"trade_id": "trade_id",
"secu_acc_id": "secu_acc_id",
"trd_amt": -1000.0,
"busi_date": "2017-03-20",
"orig_trd_qty": -100,
"open_date": "2017-01-01",
"exception_label": 0,
"close_amt": 900.0,
"orig_trd_amt": -1000.0
}]
assert_dict_equal(re[0], _re[0])
assert_less(abs(re[1]["return"] - (6000.0 - 9.0 * 400 - 200.0 - 400 * 6)),
1e-4)
assert_less(
abs(re[1]["return_rate"] - re[1]["return"] /
(9.0 * 400 + 200.0 + 400 * 6)), 1e-4)
assert_less(abs(re[2]["return"] - (5000 - 500 - 1000.0 * 6)), 1e-4)
assert_less(
abs(re[2]["return_rate"] - re[2]["return"] / (500 + 1000.0 * 6)), 1e-4)
assert_less(abs(re[3]["return"] - (1100 - 100 * 6.0 - 100 * 5.9)), 1e-4)
assert_less(
abs(re[3]["return_rate"] - re[3]["return"] / (100 * (6 + 5.9))), 1e-4)
def test_short_compute3():
"""
考虑正常做空情况下分红分股处理
"""
busi_date = "2017-03-20"
yesterday = "2017-03-17"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = busi_date
data["open_detail"] = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "4.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-100",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "-1000"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": "3.0",
"trd_qty": "-600",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-600",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": "-6000"
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "3.0",
"trd_qty": "-500",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "-500",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": "-5000"
}]
data["now_trd"] = [{
"timestamp": 1489993205,
"trd_qty": 0,
"trd_cash_flow": 700.0,
"amortize_label": 1
}, {
"timestamp": 1489993206,
"trd_qty": -700,
"trd_cash_flow": 0.0,
"amortize_label": 1
}, {
"timestamp": 1489993204,
"trd_qty": 500,
"trd_cash_flow": 4500.0,
"amortize_label": 0
}]
data["liab_qty"] = -1400
data["mkt_val"] = -6300.0
re = short_compute(data, busi_date, yesterday)
_re = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "6.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "900.0",
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": str(5.0 + 0.5),
"trd_qty": "-800",
"open_type": "trade",
"close_amt": str(200.0 + 3600),
"unclose_qty": "-400",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": str(-400 * 4.5)
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "6.0",
"trd_qty": "-1000",
"open_type": "trade",
"close_amt": str(500.0),
"unclose_qty": "-1000",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": str(-1000 * 4.5)
}]
for i in range(len(_re)):
assert_dict_equal(re["open_detail"][i], _re[i])
# Day 2
busi_date = "2017-03-21"
yesterday = "2017-03-20"
data["now_trd"] = [{
"timestamp": 1489993208,
"trd_qty": 1500,
"trd_cash_flow": 9000.0,
"amortize_label": 0
}, {
"timestamp": 1489993207,
"trd_qty": -200,
"trd_cash_flow": -1100.0,
"amortize_label": 0
}, {
"timestamp": 1489993209,
"trd_qty": 100,
"trd_cash_flow": 590.0,
"amortize_label": 0
}]
data["qty"] = None
data["mkt_val"] = None
re = short_compute(data, busi_date, yesterday)
_re = [{
"orig_trd_amt": "-1000.0",
"orig_trd_qty": "-100",
"trd_amt": "-1000.0",
"weighted_term": "6.0",
"trd_qty": "-100",
"open_type": "trade",
"close_amt": "900.0",
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "-6000.0",
"orig_trd_qty": "-600",
"trd_amt": "-6000.0",
"weighted_term": str(5.0 + 0.5),
"trd_qty": "-800",
"open_type": "trade",
"close_amt": str(200.0 + 3600 + 400 * 6.0),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": str(0.0)
}, {
"orig_trd_amt": "-5000.0",
"orig_trd_qty": "-500",
"trd_amt": "-5000.0",
"weighted_term": "6.0",
"trd_qty": "-1000",
"open_type": "trade",
"close_amt": str(1000 * 6.0 + 500),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": str(0.0)
}, {
"orig_trd_amt": "-1100.0",
"orig_trd_qty": "-200",
"trd_amt": "-1100.0",
"weighted_term": "0.0",
"trd_qty": "-200",
"open_type": "trade",
"close_amt": str(100 * 6.0 + 100 * 5.9),
"unclose_qty": "0",
"exception_label": "0",
"open_date": busi_date,
"open_timestamp": "1489993207",
"unclose_amt": str(0.0)
}]
for i in range(len(_re)):
assert_dict_equal(re["open_detail"][i], _re[i])
def test_long_compute():
"""
考虑正常情况下普通交易
"""
busi_date = "2017-03-20"
yesterday = "2017-03-17"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = busi_date
data["open_detail"] = [{
"orig_trd_amt": "2846482.0",
"orig_trd_qty": "296200",
"trd_amt": "2846482.0",
"weighted_term": "1.0",
"trd_qty": "296200",
"close_amt": "0.0",
"unclose_qty": "296200",
"exception_label": "0",
"open_date": "2017-03-16",
"open_timestamp": "1489626000",
"unclose_amt": "2825748.0"
}, {
"orig_trd_amt": "958.24",
"orig_trd_qty": "100",
"trd_amt": "958.24",
"weighted_term": "1.0",
"trd_qty": "100",
"close_amt": "0.0",
"unclose_qty": "100",
"exception_label": "0",
"open_date": "2017-03-17",
"open_timestamp": "1489748407",
"unclose_amt": "954.0"
}]
data["now_trd"] = [{
"timestamp": 1490004007,
"trd_qty": -296300,
"trd_cash_flow": -2828957.76,
"amortize_label": 0
}]
data["qty"] = None
data["mkt_val"] = None
re = long_compute(data, busi_date, yesterday)
amt = [float(i["close_amt"]) for i in re["open_detail"]]
term = [float(i["weighted_term"]) for i in re["open_detail"]]
assert_less(abs(sum(amt) - 2828957.76), 1e-4)
assert_less(abs(amt[0] / amt[1] - 2962), 1e-4)
assert_array_almost_equal(term, [3.0, 3.0])
_re = [{
"orig_trd_amt": "2846482.0",
"orig_trd_qty": "296200",
"trd_amt": "2846482.0",
"weighted_term": "3.0",
"trd_qty": "296200",
"close_amt": str(296200 / 296300. * 2828957.76),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-03-16",
"open_timestamp": "1489626000",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "958.24",
"orig_trd_qty": "100",
"trd_amt": "958.24",
"weighted_term": "3.0",
"trd_qty": "100",
"close_amt": str(100 / 296300. * 2828957.76),
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-03-17",
"open_timestamp": "1489748407",
"unclose_amt": "0.0"
}]
assert_dict_equal(re["open_detail"][0], _re[0])
assert_dict_equal(re["open_detail"][1], _re[1])
def test_long_compute4():
"""
考虑在配股情况下，正常做多交易
"""
busi_date = "2017-03-20"
yesterday = "2017-03-17"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data["busi_date"] = busi_date
data["open_detail"] = [{
"orig_trd_amt": "1000.0",
"orig_trd_qty": "100",
"trd_amt": "1000.0",
"weighted_term": "4.0",
"trd_qty": "100",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "100",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "1000"
}, {
"orig_trd_amt": "6000.0",
"orig_trd_qty": "600",
"trd_amt": "6000.0",
"weighted_term": "3.0",
"trd_qty": "600",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "600",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": "6000"
}, {
"orig_trd_amt": "5000.0",
"orig_trd_qty": "500",
"trd_amt": "5000.0",
"weighted_term": "3.0",
"trd_qty": "500",
"open_type": "trade",
"close_amt": "0.0",
"unclose_qty": "500",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": "5000"
}]
data["now_trd"] = [{
"timestamp": 1489993205,
"trd_qty": 0,
"trd_cash_flow": -700.0,
"amortize_label": 1
}, {
"timestamp": 1489993206,
"trd_qty": 700,
"trd_cash_flow": 700.0,
"amortize_label": 1
}, {
"timestamp": 1489993204,
"trd_qty": -500,
"trd_cash_flow": -4500.0,
"amortize_label": 0
}]
data["qty"] = 1400
data["mkt_val"] = 6300.0
re = long_compute(data, busi_date, yesterday)
_re = [{
"orig_trd_amt": "1000.0",
"orig_trd_qty": "100",
"trd_amt": "1000.0",
"weighted_term": "6.0",
"trd_qty": "100",
"open_type": "trade",
"close_amt": "900.0",
"unclose_qty": "0",
"exception_label": "0",
"open_date": "2017-01-01",
"open_timestamp": "1489993201",
"unclose_amt": "0.0"
}, {
"orig_trd_amt": "6000.0",
"orig_trd_qty": "600",
"trd_amt": "6200.0",
"weighted_term": str(5.0 + 0.5),
"trd_qty": "800",
"open_type": "trade",
"close_amt": str(200.0 + 3600),
"unclose_qty": "400",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993202",
"unclose_amt": str(400 * 4.5)
}, {
"orig_trd_amt": "5000.0",
"orig_trd_qty": "500",
"trd_amt": "5500.0",
"weighted_term": "6.0",
"trd_qty": "1000",
"open_type": "trade",
"close_amt": str(500.0),
"unclose_qty": "1000",
"exception_label": "0",
"open_date": "2017-01-02",
"open_timestamp": "1489993203",
"unclose_amt": str(1000 * 4.5)
}]
for i in range(len(_re)):
assert_dict_equal(re["open_detail"][i], _re[i])
