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-rw-r--r--python/notebooks/Valuation Backtest.ipynb15
1 files changed, 13 insertions, 2 deletions
diff --git a/python/notebooks/Valuation Backtest.ipynb b/python/notebooks/Valuation Backtest.ipynb
index bd8cab29..698a25f1 100644
--- a/python/notebooks/Valuation Backtest.ipynb
+++ b/python/notebooks/Valuation Backtest.ipynb
@@ -31,6 +31,15 @@
"metadata": {},
"outputs": [],
"source": [
+ "df_long = df_long[df_long.source != 'PB']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
"#%matplotlib nbagg\n",
"%matplotlib inline\n",
"mark.pretty_plot(df_long)\n",
@@ -140,13 +149,14 @@
"outputs": [],
"source": [
"#%matplotlib nbagg\n",
- "to_plot = ['mark_closest_all', 'mark_mean_all']\n",
+ "#Filtered takes out PB\n",
+ "to_plot = ['mark_closest_all', 'mark_filtered_mean']\n",
"to_plot1 = ['mark_manager']\n",
"plot_df0 = results[1][to_plot]\n",
"plot_df1 = results[1][to_plot1]\n",
"\n",
"plot_df0 = plot_df0.rename(columns = {'mark_closest_all': 'Third-pary mark closest to LMCG valuation', \\\n",
- " 'mark_mean_all': 'Average of all third-party marks'})\n",
+ " 'mark_filtered_mean': 'Average of all third-party marks'})\n",
"plot_df1 = plot_df1.rename(columns = {'mark_manager': 'Marks per fund valuation policy'})\n",
"\n",
"ax = plot_df0.plot(figsize = [10, 3.5])\n",
@@ -155,6 +165,7 @@
"ax.set_xlabel('')\n",
"ax.set_ylabel('NAV', weight = 'bold')\n",
"ax.set_title('Fund Return Using Different Valuation Methods', weight = 'bold')\n",
+ "ax.xaxis.grid(False)\n",
"lgd = ax.legend(loc='upper center', bbox_to_anchor=(0.5, -.1), shadow=True, ncol=3)\n",
"ax.figure.savefig(\"/home/serenitas/edwin/PythonGraphs/Valuation_1.png\", bbox_extra_artists=(lgd,), bbox_inches='tight')"
]