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-rw-r--r--python/notebooks/Valuation Backtest.ipynb25
1 files changed, 23 insertions, 2 deletions
diff --git a/python/notebooks/Valuation Backtest.ipynb b/python/notebooks/Valuation Backtest.ipynb
index 77f709b8..ca6ae02d 100644
--- a/python/notebooks/Valuation Backtest.ipynb
+++ b/python/notebooks/Valuation Backtest.ipynb
@@ -44,7 +44,7 @@
"outputs": [],
"source": [
"#%matplotlib nbagg\n",
- "%matplotlib inline\n",
+ "#%matplotlib inline\n",
"mark.pretty_plot(df_long)\n",
"#file saved in serenitas shared drive/edwin/"
]
@@ -188,6 +188,7 @@
"metadata": {},
"outputs": [],
"source": [
+ "#Annual Return using different methodology\n",
"round(mark.annual_performance(results[1])*100,2)"
]
},
@@ -197,6 +198,16 @@
"metadata": {},
"outputs": [],
"source": [
+ "#Return using different methodology - Same calulation as above but monthly \n",
+ "(results[1]/results[1].shift(1) - 1)[-24:][['mark_manager', 'mark_closest_all', 'mark_filtered_mean']]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
"#A positive impact % means the alternative methodology results in a higher NAV than the fund's valuation policy.\n",
"round(pd.DataFrame(mark.alt_nav_impact())*100,2)"
]
@@ -229,6 +240,16 @@
"metadata": {},
"outputs": [],
"source": [
+ "summary.iloc[-2]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#Trade winners/performance\n",
"df = ops.trade_performance()\n",
"df = df.set_index('trade_date')\n",
"df.days_held = df.days_held.dt.days\n",
@@ -260,7 +281,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.6"
+ "version": "3.7.0"
}
},
"nbformat": 4,