diff options
Diffstat (limited to 'python/notebooks/Valuation Backtest.ipynb')
| -rw-r--r-- | python/notebooks/Valuation Backtest.ipynb | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/python/notebooks/Valuation Backtest.ipynb b/python/notebooks/Valuation Backtest.ipynb index 870fb33d..77f709b8 100644 --- a/python/notebooks/Valuation Backtest.ipynb +++ b/python/notebooks/Valuation Backtest.ipynb @@ -6,9 +6,9 @@ "metadata": {}, "outputs": [], "source": [ - "from datetime import datetime\n", "from db import dbengine\n", "\n", + "import datetime\n", "import mark_backtest_underpar as mark\n", "import globeop_reports as ops\n", "import pandas as pd\n", @@ -23,8 +23,7 @@ "metadata": {}, "outputs": [], "source": [ - "#exclude sell price that are over 200\n", - "df_long = mark.back_test('2013-01-01', '2018-01-01', sell_price_threshold = 200)" + "date = datetime.date.today() - pd.tseries.offsets.MonthEnd(1)" ] }, { @@ -33,6 +32,8 @@ "metadata": {}, "outputs": [], "source": [ + "#exclude sell price that are over 200\n", + "df_long = mark.back_test('2013-01-01', '2018-12-01', sell_price_threshold = 200)\n", "df_long = df_long[df_long.source != 'PB']" ] }, @@ -95,7 +96,6 @@ "metadata": {}, "outputs": [], "source": [ - "%matplotlib inline\n", "mark.count_sources(df)" ] }, @@ -208,14 +208,15 @@ "outputs": [], "source": [ "#Portfolio MTM Gains/Loss/Net\n", - "df_pnl = ops.get_monthly_pnl()[:date]\n", + "df_pnl = ops.get_monthly_pnl()[:date][['mtdbookunrealmtm', 'mtdbookrealmtm']].sum(axis=1)\n", + "df_pnl.name = 'mtm'\n", "r=[]\n", "for d, g in df_pnl.reset_index('identifier').groupby(pd.Grouper(freq='M')):\n", " sql_string = \"SELECT * FROM risk_positions(%s, 'Subprime') WHERE notional > 0\"\n", " pos = pd.read_sql_query(sql_string, engine, params=[g.index[-1].date()])\n", " pos.identifier = pos.identifier.str[:9]\n", - " pos = pos.merge(df_pnl.groupby('identifier').cumsum().loc[g.index[-1]],\n", - " on='identifier')['mtdtotalbookpl'] / nav.loc[d]\n", + " pos = pos.join(df_pnl.groupby('identifier').cumsum().loc[g.index[-1]],\n", + " on='identifier')['mtm'] / nav.loc[d]\n", " r.append([g.index[-1], pos[pos>=0].sum(), pos[pos<0].sum()])\n", "summary = pd.DataFrame.from_records(r, index='date', columns=['date','gains','loss'])\n", "summary['Net'] = summary.gains + summary.loss\n", |