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
|
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import portfolio_var as port\n",
"from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio\n",
"from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios\n",
"import datetime\n",
"import pandas as pd\n",
"from pandas.tseries.offsets import BDay, BMonthEnd\n",
"\n",
"#import exploration.swaption_calendar_spread as spread\n",
"import exploration.swaption_calendar_spread as spread"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Oct ME Bond HY Equiv\n",
"report_date = (datetime.date.today() + BMonthEnd(-1)).date()\n",
"bond_HY_equiv = -.12088\n",
"percentile = .95"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#The 95%tile \n",
"df, spread, dur = port.rel_spread_diff(report_date)\n",
"stress = pd.DataFrame()\n",
"stress.at[('2SD_widen', 'spread')] = df.quantile(.975) \n",
"stress.at[('2SD_tighten', 'spread')] = df.quantile(.025) \n",
"stress.at[('worst_widen', 'spread')] = df.max()\n",
"stress['pts'] = -stress * spread * dur/100\n",
"stress['nav_impact'] = bond_HY_equiv * stress['pts']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stress"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"port.cleared_cds_margins(report_date, percentile)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"port.index_curve_margins(report_date)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
