diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/mark_backtest_underpar.py | 4 | ||||
| -rw-r--r-- | python/notebooks/Valuation Backtest.ipynb | 15 |
2 files changed, 15 insertions, 4 deletions
diff --git a/python/mark_backtest_underpar.py b/python/mark_backtest_underpar.py index 56e1a2b7..307a1f9a 100644 --- a/python/mark_backtest_underpar.py +++ b/python/mark_backtest_underpar.py @@ -22,7 +22,7 @@ def get_mark_df(asset_class = 'Subprime'): df = df_trades.merge(df_external_marks).dropna() return df.set_index(['date','identifier']) -def calc_mark_diff(df, sources= ['PRICESERVE', 'PRICINGDIRECT','BVAL','MARKIT','BROKER', 'REUTERS', 'S&P', 'PB', 'IDC']): +def calc_mark_diff(df, sources= ['PRICESERVE', 'PRICINGDIRECT','BVAL','MARKIT','BROKER', 'REUTERS', 'S&P', 'IDC']): #All Sources (including manager...?!) - average, manager mark only, median, closest g = df.groupby(level = ['date','identifier']) @@ -147,7 +147,7 @@ def pretty_plot(df_long): sb.set_style("whitegrid") sb.set_context("notebook") - order = ['LMCG','BROKER','BVAL','IDC','MARKIT','PB','PRICESERVE','PRICINGDIRECT','REUTERS','S&P'] + order = ['LMCG','BROKER','BVAL','IDC','MARKIT','PRICESERVE','PRICINGDIRECT','REUTERS','S&P'] sb.set_palette(sb.hls_palette(10, l=.4, s=.8)) grid = sb.FacetGrid(df_long, hue='source', hue_kws={'s':[50] + [20]*9, 'marker': ["o"]+["s"]*9, 'alpha': [1]+[.4]*9}, legend_out=True, aspect = 2.1, size = 4, hue_order = order) 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')" ] |