diff options
Diffstat (limited to 'python/notebooks/tranche and swaption portfolio strategy.ipynb')
| -rw-r--r-- | python/notebooks/tranche and swaption portfolio strategy.ipynb | 140 |
1 files changed, 116 insertions, 24 deletions
diff --git a/python/notebooks/tranche and swaption portfolio strategy.ipynb b/python/notebooks/tranche and swaption portfolio strategy.ipynb index 3bef916a..0e521ed8 100644 --- a/python/notebooks/tranche and swaption portfolio strategy.ipynb +++ b/python/notebooks/tranche and swaption portfolio strategy.ipynb @@ -12,14 +12,15 @@ "import matplotlib.pyplot as plt\n", "\n", "from analytics.scenarios import run_tranche_scenarios, run_portfolio_scenarios, run_tranche_scenarios_rolldown\n", - "from analytics import Swaption, BlackSwaption, Index, BlackSwaptionVolSurface, Portfolio, ProbSurface\n", + "from analytics import Swaption, BlackSwaption, CreditIndex, BlackSwaptionVolSurface, Portfolio, ProbSurface\n", + "from analytics import DualCorrTranche\n", "from db import dbengine\n", "from datetime import date\n", - "from graphics import plot_time_color_map\n", + "from graphics import plot_color_map\n", "\n", "dawnengine = dbengine('dawndb')\n", "\n", - "value_date = (pd.datetime.today() - pd.offsets.BDay(2)).date()" + "value_date = (pd.datetime.today() - pd.offsets.BDay(1)).date()" ] }, { @@ -31,7 +32,7 @@ "#Construct IG Swaption Portfolio\n", "index = 'IG'\n", "series = 30\n", - "option_delta = Index.from_name(index, series, '5yr')\n", + "option_delta = CreditIndex(index, series, '5yr', value_date=value_date)\n", "option_delta.spread = 65\n", "option1 = BlackSwaption(option_delta, date(2018, 10, 17), 60, option_type=\"payer\")\n", "option1.sigma = .398\n", @@ -43,8 +44,7 @@ "option2.notional = 300_000_000\n", "option_delta.notional = option1.notional * option1.delta + option2.notional * option2.delta\n", "\n", - "portf = Portfolio([option1, option2, option_delta])\n", - "portf.value_date = value_date\n", + "portf = Portfolio([option1, option2, option_delta], trade_ids=['opt1', 'opt2', 'delta'])\n", "portf.reset_pv()" ] }, @@ -67,8 +67,10 @@ "vs = BlackSwaptionVolSurface(index,series, value_date=value_date)\n", "ps = ProbSurface(index,series, value_date=value_date)\n", "vol_surface = vs[vs.list(option_type='payer')[-1]]\n", - "swaption_scens = run_portfolio_scenarios(portf, date_range, spread_shock, np.array([0]),\n", - " vol_surface, params=[\"pnl\", \"delta\"])\n", + "swaption_scens = run_portfolio_scenarios(portf, date_range, params=[\"pnl\", \"delta\"],\n", + " spread_shock=spread_shock,\n", + " vol_shock = np.array([0]),\n", + " vol_surface=vol_surface)\n", "#swaption delta is in protection terms: switch to risk terms\n", "swaption_scens.delta = -swaption_scens.delta" ] @@ -80,21 +82,30 @@ "outputs": [], "source": [ "#Get current Tranche positions\n", - "sql_string = \"select * from list_tranche_marks(%s)\"\n", - "pos = pd.read_sql_query(sql_string, dawnengine, params=(value_date,), parse_dates=['maturity'])\n", - "tranche_port = []\n", - "for i, r in pos.iterrows():\n", - " tranche_port.append(bkt.TrancheBasket(r.p_index, r.p_series, '5yr'))\n", - " tranche_port[i].build_skew()\n", - "pos['basket'] = tranche_port\n", - "#Set Shock Range\n", - "spread_range = (1+ spread_shock) * option_delta.spread\n", - "#Run tranche scenarios\n", - "temp = []\n", - "for i, r in pos.iterrows():\n", - " df = run_tranche_scenarios_rolldown(r.basket, spread_range, date_range, corr_map=False)\n", - " temp.append(r.notional*df.xs(str(r.attach) + \"-\" + str(r.detach), axis=1, level=1))\n", - "tranches_scens = sum(temp)" + "sql_string = (\"select sum(notional * case when protection='Buyer' then -1 else 1 end) as ntl, security_id, attach \"\n", + " \"from cds where swap_type='CD_INDEX_TRANCHE' and termination_cp is null group by security_id, notional, attach\")\n", + "open_pos = pd.read_sql_query(sql_string, dawnengine)\n", + "for i, r in open_pos[open_pos.ntl != 0].iterrows():\n", + " sql_string = \"select id from cds where security_id = %s and attach = %s\" \n", + " trade_ids = pd.read_sql_query(sql_string, dawnengine, params=[r.security_id, r.attach])\n", + " for i1, r1 in trade_ids.iterrows():\n", + " portf.add_trades(bkt.DualCorrTranche.from_tradeid(r1[0]), i1)\n", + "\n", + "#Set up portfolio scenarios\n", + "spread_shock = np.arange(-.05, .05, 0.05)\n", + "corr_shock = np.arange(-.1, .1, 0.1)\n", + "vol_shock = np.arange(-.1, .3, 0.5)\n", + "earliest_expiry = min(portf.swaptions, key=lambda x: x.exercise_date).exercise_date\n", + "date_range = pd.bdate_range(value_date, earliest_expiry - pd.offsets.BDay(), freq='20B')\n", + "vs = BlackSwaptionVolSurface(index,series, value_date=value_date)\n", + "ps = ProbSurface(index,series, value_date=value_date)\n", + "vol_surface = vs[vs.list(option_type='payer')[-1]]\n", + "portf.reset_pv()\n", + "scens = run_portfolio_scenarios(portf, date_range, params=[\"pnl\"],\n", + " spread_shock=spread_shock,\n", + " corr_shock=corr_shock,\n", + " vol_shock = vol_shock,\n", + " vol_surface=vol_surface)" ] }, { @@ -103,6 +114,15 @@ "metadata": {}, "outputs": [], "source": [ + "pos['basket'] = tranche_port\n", + "#Set Shock Range\n", + "spread_range = (1+ spread_shock) * option_delta.spread\n", + "#Run tranche scenarios\n", + "temp = []\n", + "for i, r in pos.iterrows():\n", + " df = run_tranche_scenarios_rolldown(r.basket, spread_range, date_range, corr_map=False)\n", + " temp.append(r.notional*df.xs(str(r.attach) + \"-\" + str(r.detach), axis=1, level=1))\n", + "tranches_scens = sum(temp)\n", "#Create snapshot of the the first scenario date\n", "total_scens = swaption_scens.reset_index().merge(tranches_scens.reset_index(), \n", " left_on=['date', 'spread'], \n", @@ -245,6 +265,78 @@ "metadata": {}, "outputs": [], "source": [ + "#IG Bullish Risk Reversal vs. shorting IG 7-15 risk\n", + "index = 'IG'\n", + "series = 30\n", + "option_delta = Index.from_name(index, series, '5yr', value_date)\n", + "option_delta.spread = 62\n", + "option1 = BlackSwaption(option_delta, date(2018, 9, 19), 60, option_type=\"receiver\")\n", + "option2 = BlackSwaption(option_delta, date(2018, 9, 19), 90, option_type=\"payer\")\n", + "option1.sigma = .344\n", + "option2.sigma = .585\n", + "option1.notional = 200_000_000\n", + "option2.notional = 400_000_000\n", + "option1.direction = 'Long'\n", + "option2.direction = 'Short'\n", + "option_delta.notional = 1\n", + "option_delta.direction = 'Seller' if option_delta.notional > 0 else 'Buyer'\n", + "option_delta.notional = abs(option_delta.notional)\n", + "portf = Portfolio([option1, option2, option_delta])\n", + "#Plot Scenarios Inputs: Portfolio, spread shock tightening%, spread shock widening%, snapshot period)\n", + "portf\n", + "\n", + "portf.reset_pv()\n", + "#Run Swaption sensitivities\n", + "#Set Shock range\n", + "shock_min = -.5\n", + "shock_max = 1\n", + "spread_shock = np.arange(shock_min, shock_max, 0.1)\n", + "#Set Date range\n", + "earliest_expiry = min(portf.swaptions, key=lambda x: x.exercise_date).exercise_date\n", + "date_range = pd.bdate_range(value_date, earliest_expiry - pd.offsets.BDay(), freq='10B')\n", + "#Setup Vol Surface\n", + "vs = BlackSwaptionVolSurface(index,series, value_date=value_date)\n", + "ps = ProbSurface(index,series, value_date=value_date)\n", + "vol_surface = vs[vs.list(option_type='payer')[-1]]\n", + "swaption_scens = run_portfolio_scenarios(portf, date_range, spread_shock, np.array([0]),\n", + " vol_surface, params=[\"pnl\", \"delta\"])\n", + "#swaption delta is in protection terms: switch to risk terms\n", + "swaption_scens.delta = -swaption_scens.delta\n", + "\n", + "notional = -100_000_000\n", + "t = bkt.TrancheBasket('IG', '29', '5yr')\n", + "t.build_skew()\n", + "spread_range = (1+ spread_shock) * option_delta.spread\n", + "tranches_scens = run_tranche_scenarios_rolldown(t, spread_range, date_range, corr_map=False)\n", + "tranches_scens = notional*tranches_scens.xs('7-15', axis=1, level=1)\n", + "\n", + "#Create snapshot of the the first scenario date\n", + "total_scens = swaption_scens.reset_index().merge(tranches_scens.reset_index(), \n", + " left_on=['date', 'spread'], \n", + " right_on=['date', 'spread_range'], \n", + " suffixes=['_s', '_t'])\n", + "total_scens['pnl'] = total_scens['pnl_s'] + total_scens['pnl_t']\n", + "total_scens['delta'] = total_scens['delta_s'] + total_scens['delta_t']\n", + "total_scens_single_date = total_scens.set_index('date').xs(date_range[0])\n", + "total_scens_single_date = total_scens_single_date.set_index('spread', drop=True)\n", + "\n", + "#tranche positions delta at different spreads\n", + "ax = total_scens_single_date.delta_t.plot(title = 'delta vs. spread levels')\n", + "ax.ticklabel_format(style='plain')\n", + "plt.tight_layout()\n", + "\n", + "#Tranche + Swaptions positions delta at different spreads\n", + "ax1 = total_scens_single_date.delta.plot()\n", + "ax1.ticklabel_format(style='plain')\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "dawnengine.dispose()" ] }, @@ -272,7 +364,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.5" + "version": "3.6.6" } }, "nbformat": 4, |