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-rw-r--r--python/notebooks/VaR.ipynb112
1 files changed, 88 insertions, 24 deletions
diff --git a/python/notebooks/VaR.ipynb b/python/notebooks/VaR.ipynb
index fd48ded2..3bb3e83d 100644
--- a/python/notebooks/VaR.ipynb
+++ b/python/notebooks/VaR.ipynb
@@ -6,12 +6,17 @@
"metadata": {},
"outputs": [],
"source": [
- "from analytics.curve_trades import curve_pos\n",
- "from analytics import Index, Portfolio\n",
+ "from analytics.curve_trades import curve_pos, on_the_run\n",
+ "from analytics.index_data import get_index_quotes\n",
+ "from analytics.scenarios import run_portfolio_scenarios\n",
+ "from analytics import Swaption, BlackSwaption, CreditIndex, BlackSwaptionVolSurface, Portfolio, ProbSurface, DualCorrTranche\n",
+ "from db import dbconn\n",
"\n",
"import datetime\n",
"import exploration.VaR as var\n",
- "import pandas as pd"
+ "import pandas as pd\n",
+ "\n",
+ "conn = dbconn('dawndb')"
]
},
{
@@ -34,7 +39,7 @@
"source": [
"#IG Curve VaR\n",
"portf = curve_pos(date, index_type)\n",
- "ig_curve_var = abs(var.hist_var(portf, quantile=quantile))\n",
+ "ig_curve_var = abs(var.hist_var(portf, quantile=quantile, years=5))\n",
"ig_curve_var"
]
},
@@ -47,7 +52,7 @@
"#EU Curve VaR\n",
"index_type = \"EU\"\n",
"portf = curve_pos(date, index_type)\n",
- "eu_curve_var = abs(var.hist_var(portf, quantile=quantile))\n",
+ "eu_curve_var = abs(var.hist_var(portf, quantile=quantile, years=5))\n",
"eu_curve_var"
]
},
@@ -58,9 +63,8 @@
"outputs": [],
"source": [
"#Mortgage Hedge VaR - use IG spread relative move for VaR\n",
- "df = var.get_pos(date)\n",
- "df = df[df.strategy == 'HEDGE_MBS']\n",
- "portf = Portfolio([Index.from_name(row.p_index, row.p_series, row.tenor,\n",
+ "df = var.get_pos(date, 'HEDGE_MBS')\n",
+ "portf = Portfolio([CreditIndex(row.p_index, row.p_series, row.tenor,\n",
" report_date, -row.notional)\n",
" for row in df[['p_index', 'tenor', 'p_series', 'notional']].\n",
" itertuples(index=False)])\n",
@@ -76,10 +80,10 @@
"outputs": [],
"source": [
"#Import the IM at the FCM account: calculate the IM share of different strategies as a share of VaR\n",
- "filename = date.strftime('%Y%m%d') + \"_OTC_MARGIN_EX_DEF.csv\"\n",
- "margin_df = pd.read_csv(\"/home/serenitas/Daily/SG_reports/\" + filename, index_col='Currency')\n",
- "morg_hedge_im = mort_hedge_var + mort_hedge_var/(mort_hedge_var + ig_curve_var) * margin_df.loc[('USD', 'SG IMR')]\n",
- "morg_hedge_im"
+ "filename = date.strftime('%Y%m%d') + \"_OTC_MARGIN.csv\"\n",
+ "margin_df = pd.read_csv(\"/home/serenitas/Daily/SG_reports/\" + filename, index_col='System Currency')\n",
+ "mortg_hedge_im = mort_hedge_var + mort_hedge_var/(mort_hedge_var + ig_curve_var) * margin_df.loc[('USD', 'SG Settlement Margin')]\n",
+ "mortg_hedge_im"
]
},
{
@@ -99,15 +103,18 @@
"metadata": {},
"outputs": [],
"source": [
- "#95%tile \n",
- "df, spread, dur = var.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']\n",
- "stress"
+ "#Calculate amount of stress for reports\n",
+ "df = get_index_quotes('HY', list(range(on_the_run('HY') - 10, on_the_run('HY') + 1)),\n",
+ " tenor=['5yr'], years=5)\n",
+ "df = df.xs('5yr', level='tenor')['close_spread'].groupby(['date', 'series']).last()\n",
+ "\n",
+ "widen, tighten = [], []\n",
+ "#approximately 1,3,6 months move (22 each months)\n",
+ "for days in [22, 66, 132]: \n",
+ " calc = df.unstack().pct_change(freq= str(days)+'B').stack().groupby('date').last()\n",
+ " widen.append(calc.max())\n",
+ " tighten.append(calc.min())\n",
+ "pd.DataFrame([widen, tighten], columns=['1M', '3M', '6M'], index=['widen', 'tighten'])"
]
},
{
@@ -116,7 +123,62 @@
"metadata": {},
"outputs": [],
"source": [
- "port.cleared_cds_margins(report_date, percentile)"
+ "#Current tranche and swaptions positions\n",
+ "t_sql_string = (\"SELECT id, sum(notional * case when protection='Buyer' then -1 else 1 end) \"\n",
+ " \"OVER (partition by security_id, attach) AS ntl_agg \"\n",
+ " \"FROM cds WHERE swap_type='CD_INDEX_TRANCHE' AND termination_cp IS NULL \"\n",
+ " \"AND trade_date <= %s\")\n",
+ "swaption_sql_string = (\"select id, security_desc from swaptions where date(expiration_date) \"\n",
+ " \"> %s and swap_type = 'CD_INDEX_OPTION' \"\n",
+ " \"AND trade_date <= %s\")\n",
+ "index_sql_string = (\"SELECT id, sum(notional * case when protection='Buyer' then -1 else 1 end) \"\n",
+ " \"OVER (partition by security_id, attach) AS ntl_agg \"\n",
+ " \"FROM cds WHERE swap_type='CD_INDEX' AND termination_cp IS null \"\n",
+ " \"AND folder = 'IGOPTDEL' OR folder = 'HYOPTDEL' \"\n",
+ " \"AND trade_date <= %s\")\n",
+ "conn = dbconn('dawndb')\n",
+ "with conn.cursor() as c:\n",
+ " #Get Tranche Trade Ids\n",
+ " c.execute(t_sql_string, (date,))\n",
+ " t_trade_ids = [dealid for dealid, ntl in c if ntl != 0]\n",
+ " #Get Swaption Trade Ids\n",
+ " c.execute(swaption_sql_string, (date, date))\n",
+ " swaption_trades = c.fetchall()\n",
+ " #Get Index/deltas Trade Ids\n",
+ " c.execute(index_sql_string, (date,))\n",
+ " index_trade_ids = [dealid for dealid, ntl in c if ntl != 0]\n",
+ " \n",
+ "portf = Portfolio([DualCorrTranche.from_tradeid(dealid) for dealid in t_trade_ids],\n",
+ " t_trade_ids)\n",
+ "for row in swaption_trades:\n",
+ " option_delta = CreditIndex(row[1].split()[1], row[1].split()[3][1:], '5yr', date)\n",
+ " option_delta.mark()\n",
+ " portf.add_trade(BlackSwaption.from_tradeid(row[0], option_delta), 'opt_' + str(row[0]))\n",
+ "for index_id in index_trade_ids:\n",
+ " portf.add_trade(CreditIndex.from_tradeid(index_id), 'index_' + str(index_id))\n",
+ " \n",
+ "#Update manually - positive notional = long risk\n",
+ "non_trancheSwap_risk_notional = 33763230\n",
+ "portf.add_trade(CreditIndex('HY', on_the_run('HY'), '5yr', value_date = date, notional = -non_trancheSwap_risk_notional), 'port')\n",
+ " \n",
+ "portf.value_date = date\n",
+ "portf.mark()\n",
+ "portf.reset_pv()\n",
+ " \n",
+ "vs = BlackSwaptionVolSurface(portf.swaptions[0].index.index_type, portf.swaptions[0].index.series, value_date=date)\n",
+ "vol_surface = vs[vs.list(option_type='payer')[-1]]\n",
+ "vol_shock = [0]\n",
+ "corr_shock = [0]\n",
+ "spread_shock = widen + tighten\n",
+ "date_range = [pd.Timestamp(date)]\n",
+ "\n",
+ "scens = run_portfolio_scenarios(portf, date_range, params=[\"pnl\"],\n",
+ " spread_shock=spread_shock,\n",
+ " vol_shock=vol_shock,\n",
+ " corr_shock=corr_shock,\n",
+ " vol_surface=vol_surface)\n",
+ "\n",
+ "scens.sum(axis=1)"
]
},
{
@@ -124,7 +186,9 @@
"execution_count": null,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "var.cleared_cds_margins(report_date)"
+ ]
}
],
"metadata": {
@@ -143,7 +207,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.5"
+ "version": "3.7.0"
}
},
"nbformat": 4,
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2025-12-22 23:43:40 +0000