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
|
import serenitas.analytics
import numpy as np
from serenitas.analytics import on_the_run, CreditIndex, BlackSwaptionVolSurface
from copy import deepcopy
from .tranches import get_tranche_portfolio
from .swaptions import get_swaption_portfolio
from .bonds import subprime_risk, clo_risk, crt_risk
from .indices import get_index_portfolio
from serenitas.utils.db import dbconn, dbengine
from pandas.tseries.offsets import BDay
def hy_equiv_trade(value_date, notional):
return CreditIndex("HY", on_the_run("HY", value_date), "5yr", value_date, notional)
def build_portfolio(position_date, value_date=None, fund="SERCGMAST"):
"""
Output two portfolios:
1) All synthetic + curve with just delta-proxy + dummy index as cash bonds proxy (portf)
2) All synthetic (portf_syn)
"""
serenitas.analytics._local = False
if value_date is None:
value_date = position_date
serenitas.analytics.init_ontr(value_date)
conn = dbconn("dawndb")
portf = get_tranche_portfolio(position_date, conn, False, fund)
swaption_portf = get_swaption_portfolio(position_date, conn, fund)
portf += swaption_portf
syn_portf = deepcopy(portf)
curve_portf = get_index_portfolio(
position_date, conn, fund, include_strategies="%CURVE"
)
nocurve_portf = get_index_portfolio(
position_date, conn, fund, exclude_strategies="%CURVE"
)
portf += nocurve_portf
curve_portf.value_date = value_date
curve_portf.mark()
portf.add_trade(
hy_equiv_trade(value_date, curve_portf.hy_equiv),
("curve_trades", "curve_trades"),
)
syn_portf += curve_portf + nocurve_portf
# get bond risks:
rmbs_pos = subprime_risk(position_date, conn, dbengine("rmbs_model"), fund=fund)
crt_pos = crt_risk(position_date, conn, dbengine("crt"), fund=fund)
portf.add_trade(
hy_equiv_trade(value_date, -rmbs_pos.get("hy_equiv", np.zeros(1)).sum()),
("rmbs_bonds", "rmbs_bonds"),
)
portf.add_trade(
hy_equiv_trade(value_date, -crt_pos.get("hy_equiv", np.zeros(1)).sum()),
("crt_bonds", "crt_bonds"),
)
with dbconn("etdb") as etconn:
clo_pos = clo_risk(position_date, conn, etconn, fund=fund)
if clo_pos is not None:
portf.add_trade(
hy_equiv_trade(value_date, -clo_pos["hy_equiv"].sum()),
("clo_bonds", "clo_bonds"),
)
for p in [portf, syn_portf]:
p.value_date = value_date
p.mark(interp_method="bivariate_linear")
p.reset_pv()
return portf, syn_portf
def generate_vol_surface(portf, try_days_back=5, source="MS"):
vol_surface = {}
for trade in portf.swaptions:
try:
vs = BlackSwaptionVolSurface(
trade.index.index_type,
trade.index.series,
value_date=portf.value_date,
interp_method="bivariate_linear",
)
except:
vs = BlackSwaptionVolSurface(
trade.index.index_type,
trade.index.series,
value_date=portf.value_date - BDay(try_days_back),
interp_method="bivariate_linear",
)
vol_surface[
(trade.index.index_type, trade.index.series, trade.option_type)
] = vs[vs.list(source=source, option_type=trade.option_type)[-1]]
return vol_surface
|
