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"end_time": "2018-07-21T20:03:02.791182Z",
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"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
"Installing requirements ..\n",
"Done\n"
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"source": [
"%run \"Retropy_framework.ipynb\""
]
},
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"metadata": {
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"end_time": "2018-07-21T20:03:03.420612Z",
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"outputs": [
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"name": "stderr",
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"text": [
"/home/user/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2698: DtypeWarning:\n",
"\n",
"Columns (2) have mixed types. Specify dtype option on import or set low_memory=False.\n",
"\n"
]
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"source": [
"mdf = pd.read_csv(\"Research/GemelNet.csv\")\n",
"mdf[\"month\"] = pd.to_datetime(mdf[\"month\"], format=\"%Y/%m/%d\")\n",
"mdf[\"month_return\"] = pd.to_numeric(mdf[\"month_return\"].astype(str).str.replace(\"%\", \"\"), errors=\"coerce\")\n",
"mdf[\"net_flow\"] = series_as_float(mdf[\"net_flow\"])\n",
"mdf[\"AUM\"] = series_as_float(mdf[\"AUM\"])\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:33.139421Z",
"start_time": "2018-07-21T20:03:33.058079Z"
},
"collapsed": true
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"outputs": [],
"source": [
"#mdf = mdf.set_index(\"month\")\n",
"\n",
"def getValue(df):\n",
" df = df.set_index(\"month\")\n",
" ser = df[\"month_return\"].dropna().copy()\n",
" if len(ser) == 0:\n",
" return pd.Series()\n",
" prevMonth = ser.index[0] + pd.DateOffset(months=-1)\n",
" ser[prevMonth] = 0 # we want the serie sto start at 1.0\n",
" ser = ser.sort_index()\n",
" ser.index = ser.index + pd.DateOffset(months=1)\n",
" return (1+ser.dropna()/100).cumprod()\n",
"\n",
"#sym = mdf[mdf[\"ID\"] == 1544]\n",
"#ym[\"month_return\"]\n",
"#getValue(sym).plot()\n",
"\n",
"def getKeren(id):\n",
" df = mdf[mdf[\"ID\"] == id]\n",
" name = str(id) + \" | \" + df.iloc[0][\"name\"]\n",
" s = getValue(df)\n",
" usdils = getForex(\"USD\", \"ILS\")\n",
" s = (s/usdils).dropna()\n",
" if len(s) > 0:\n",
" s = s / s[0]\n",
" return wrap(s, name)\n",
" \n",
"def getAum(id):\n",
" df = mdf[mdf[\"ID\"] == id]\n",
" name = str(id) + \" | \" + df.iloc[0][\"name\"]\n",
" usdils = getForex(\"USD\", \"ILS\")\n",
" #aum = pd.to_numeric(df[\"AUM\"].str.replace(\",\", \"\").replace(\"- - -\", \"\"))\n",
" #aum = pd.to_numeric(df[\"AUM\"], errors=\"coerce\")\n",
" aum = series_as_float(df[\"AUM\"])\n",
" aum.index = df[\"month\"]\n",
" aum = aum/usdils\n",
" aum = wrap(aum.dropna(), name + \" AUM\")\n",
" return aum\n",
"\n",
"def getFlow(id):\n",
" df = mdf[mdf[\"ID\"] == id]\n",
" name = str(id) + \" | \" + df.iloc[0][\"name\"]\n",
" usdils = getForex(\"USD\", \"ILS\")\n",
" #flow = pd.to_numeric(df[\"net_flow\"].str.replace(\",\", \"\").replace(\"- - -\", \"\"))\n",
" flow = series_as_float(df[\"net_flow\"])\n",
" flow.index = df[\"month\"]\n",
" flow = flow/usdils\n",
" flow = wrap(flow.dropna(), name + \" flow\")\n",
" return flow\n",
"\n",
"def getFlowSum(id):\n",
" return getFlow(id).cumsum()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### השוואה של קרן השתלמות מחקה ממדי חול איי-בי-איי למדדי חול"
]
},
{
"cell_type": "code",
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"end_time": "2018-07-21T20:03:33.972973Z",
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""
],
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""
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],
"source": [
"s = getKeren(1544)\n",
"bench = get(\"URTH\")\n",
"bench = wrap(get(\"SPY:50|VGK:30|EEM:13|EWJ:7\", mode=\"NTR\"), \"ntr\")\n",
"benchTR = get(\"SPY:50|VGK:30|EEM:13|EWJ:7\", mode=\"TR\")\n",
"vt = get(\"VT\", mode=\"NTR\")\n",
"show(s / bench, s, bench, vt, trim=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### השוואה של קרן השתלמות מחקה סנופי איי-בי-איי לסנופי"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:34.226267Z",
"start_time": "2018-07-21T20:03:33.975157Z"
}
},
"outputs": [
{
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"source": [
"s = getKeren(2265)\n",
"bench = get(\"SPXNTR@IC\")\n",
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},
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"### כל קרנות ההשתלמות מגמל.נט"
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"2048 | *** מגדל השתלמות הלכה\n",
"1537 | אינפיניטי השתלמות מניות בחו\"ל\n",
"8704 | \"אינטרגמל השתלמות\"-מדד \"תל בונד 20\"\n",
"8705 | \"אינטרגמל השתלמות\"-מסלול מזומנים ושווי מזומנים\n",
"1542 | אקסלנס השתלמות בניהול אישי\n",
"2055 | *** מיטב דש השתלמות חו\"ל\n",
"1544 | *** אי.בי.אי השתלמות פאסיבי - מדדי מניות חו\"ל\n",
"1034 | *** הראל השתלמות מסלול חו\"ל\n",
"2058 | הלמן-אלדובי השתלמות שריעה\n",
"1038 | ילין לפידות קרן השתלמות מסלול אג\"ח עד 25% מניות\n",
"7703 | אנליסט השתלמות כללי פאסיבי\n",
"2041 | ** מורים תיכוניים - מסלול הלכה\n",
"1059 | *** פסגות שיא השתלמות פאסיבי-כללי\n",
"554 | *** מיטב דש השתלמות עד 6 שנות וותק\n",
"2091 | *** אקסלנס השתלמות אג\"ח עד 20% מניות\n",
"558 | *** אלטשולר שחם השתלמות אג\"ח עד 15% במניות\n",
"2100 | אי.בי.אי השתלמות בניהול אישי\n",
"566 | *** הראל השתלמות לטווח ארוך\n",
"(מסלול לאוכלוסיית יעד) \n",
"8761 | הראל השתלמות IRA IRA\n",
"1083 | אינפיניטי השתלמות כללי\n",
"1084 | אינפיניטי השתלמות אג\"ח\n",
"1085 | אינפיניטי השתלמות מניות בישראל\n",
"2114 | אינפיניטי השתלמות IRA בניהול אישי\n",
"579 | *** מגדל השתלמות כללי\n",
"580 | ** שיבולת - השתלמות\n",
"1093 | *** אלטשולר שחם השתלמות כללי\n",
"2115 | כלל השתלמות אג\"ח\n",
"9802 | ** אומגה קרן השתלמות אג\"ח עד 15% מניות\n",
"8779 | אנליסט השתלמות חו\"ל\n",
"1100 | *** אקסלנס השתלמות אג\"ח עד 15% מניות\n",
"9803 | ** אומגה קרן השתלמות אג\"ח עד 25% מניות\n",
"7253 | מגדל השתלמות לבני 50 ומטה\n",
"1110 | *** מנורה השתלמות אג\"ח קונצרני\n",
"599 | *** מגדל השתלמות אג\"ח עד 10% מניות\n",
"7254 | מגדל השתלמות לבני 50 עד 60\n",
"7256 | מגדל השתלמות פאסיבי כללי\n",
"1114 | *** מנורה השתלמות שקלי לטווח קצר\n",
"610 | *** פסגות שיא השתלמות אג\"ח\n",
"611 | *** פסגות שיא השתלמות כספי\n",
"612 | *** פסגות שיא השתלמות מניות\n",
"11929 | קל השתלמות מניות מניות \n",
"11931 | קל השתלמות מניות פאסיבי\n",
"1149 | *** מנורה השתלמות אג\"ח עד 10% מניות\n",
"132 | *** הלמן-אלדובי השתלמות כללי\n",
"1157 | *** מגדל השתלמות ביג כללי לפחות 30% מניות\n",
"1162 | ילין לפידות קרן השתלמות מסלול כללי\n",
"7819 | אי.בי.אי השתלמות פאסיבי - כללי\n",
"9869 | הלמן-אלדובי השתלמות פאסיבי -כללי\n",
"9870 | הלמן-אלדובי השתלמות חו\"ל\n",
"9871 | הלמן-אלדובי השתלמות ישראל\n",
"11408 | מנורה מבטחים השתלמות פאסיבי כללי\n",
"11409 | מנורה מבטחים השתלמות פאסיבי אג\"ח עד 15% במניות\n",
"8339 | ** מסלול - אג\"ח\n",
"12435 | ** השתלמות רופאים מניות \n",
"11414 | עובדי המדינה הלכתי הלכה יהודית\n",
"11926 | קל השתלמות כללי\n",
"11928 | קל השתלמות אג\"ח אג\"ח\n",
"11927 | קל השתלמות כללי פאסיבי\n",
"154 | הראל השתלמות כללי\n",
"9882 | אקסלנס השתלמות אג\"ח עד 10% מניות\n",
"11930 | קל השתלמות אג\"ח פאסיבי\n",
"11933 | קל השתלמות מדד אג\"ח ישראל\n",
"1182 | ** קרן השתלמות של עובדי האוניברסיטה העברית\n",
"1183 | *** פסגות שיא השתלמות ישראל\n",
"11935 | קל השתלמות אג\"ח צמוד מדד בינוני\n",
"11936 | קל השתלמות חו\"ל חו\"ל\n",
"11937 | קל השתלמות חו\"ל פאסיבי\n",
"11934 | קל השתלמות מדד חו\"ל\n",
"11932 | קל השתלמות מדד מניות ישראל\n",
"1190 | *** אקסלנס השתלמות אג\"ח עד 25% מניות\n",
"686 | *** אקסלנס השתלמות לטווח קצר\n",
"1202 | *** אי.בי.אי השתלמות אג\"ח ללא מניות\n",
"1203 | אי.בי.אי קרן השתלמות מסלול אג\"ח עד 10% מניות\n",
"1204 | *** אי.בי.אי השתלמות כללי\n",
"1205 | *** אי.בי.אי השתלמות מניות\n",
"8885 | מיטב דש השתלמות אג\"ח עד 25% במניות\n",
"11957 | אינפיניטי השתלמות אג\"ח עד 25% מניות\n",
"1210 | אינפיניטי השתלמותאג\"ח ממשלת ישראל\n",
"8891 | ** רעות אג\"ח עד 10% במניות\n",
"2236 | איי.אר.איי ישראל השתלמות בניהול אישי\n",
"8890 | מגדל השתלמות בניהול אישי IRA\n",
"8382 | ** מסלול מישור אג\"ח \n",
"9919 | אקסלנס השתלמות פאסיבי- מדדי חו\"ל\n",
"1218 | *** פסגות שיא השתלמות כללי\n",
"2244 | פסגות שיא השתלמות חו\"ל\n",
"199 | *** מגדל השתלמות אג\"ח\n",
"8394 | ** מורים על יסודי מסלול הלכה\n",
"715 | *** אקסלנס השתלמות שקלי טווח קצר\n",
"716 | *** אקסלנס השתלמות אג\"ח ללא מניות\n",
"2252 | אינפיניטי השתלמות אג\"ח עד 15% מניות\n",
"2254 | אינפיניטי השתלמות לחוסכים מוטי סיכון\n",
"8395 | ** מישור מסלול הלכה\n",
"1240 | *** מיטב דש השתלמות אג\"ח ללא מניות\n",
"2264 | *** אי.בי.אי השתלמות מחקה מדד ת\"א 35\n",
"2265 | אי.בי.אי השתלמות מחקה מדד S&P500\n",
"2270 | אי.בי.אי השתלמות פאסיבי משולב עד 10% מניות\n",
"2271 | אי.בי.אי השתלמות פאסיבי משולב עד 25% מניות\n",
"736 | *** הלמן-אלדובי השתלמות אג\"ח\n",
"737 | *** הלמן-אלדובי השתלמות שקלי\n",
"738 | *** הלמן-אלדובי השתלמות מניות\n",
"1256 | *** מנורה השתלמות-מניות\n",
"1257 | ** רום רביד אג\"ח ללא מניות\n",
"1258 | ** רום ספיר מניות\n",
"9451 | אינטרגמל השתלמות -מניות S&P500\n",
"1262 | ** מינהל - השתלמות - מניות\n",
"763 | הראל השתלמות מסלול מניות\n",
"764 | הראל השתלמות אג\"ח עד 10% מניות \n",
"768 | *** מיטב דש השתלמות כהלכה\n",
"8702 | \"אינטרגמל השתלמות\"-אג\"ח ממשלת ישראל, צמוד מדד לטווח של 5-10 שנים\n",
"9479 | עובדי מדינה - מניות\n",
"1290 | אלטשולר שחם השתלמות כללי ב'\n",
"8703 | \"אינטרגמל השתלמות\"-אג\"ח ממשלתי שקלי בריבית קבועה\n",
"282 | ** מישור\n",
"284 | ** מורים וגננות - מסלול כללי\n",
"285 | ** מורים תיכוניים - מסלול כללי\n",
"286 | ** אומגה קרן השתלמות מסלול כללי\n",
"797 | *** אקסלנס השתלמות מניות\n",
"288 | ** קרן השתלמות לאקדמאים במדעי החברה והרוח מסלול כללי\n",
"289 | ** קרן השתלמות לעובדי בנק ישראל\n",
"290 | ** הנדסאים וטכנאים - מסלול כללי\n",
"1820 | ** ק.ס.מ אג\"ח \n",
"292 | ** השתלמות משפטנים\n",
"293 | ** ק.ס.מ\n",
"294 | ** השתלמות שופטים\n",
"295 | ** ק.ה.ר\n",
"1318 | ** הנדסאים וטכנאים - מסלול מניות\n",
"1316 | ** רעות - אג\"ח ללא מניות\n",
"1317 | ** רעות מניות \n",
"299 | ** מינהל-השתלמות - כללי\n",
"1319 | ילין לפידות קרן השתלמות מסלול אג\"ח\n",
"9528 | אקסלנס השתלמות הלכה\n",
"828 | *** מנורה מבטחים השתלמות כללי\n",
"1348 | כלל השתלמות אג\"ח צמוד מדד\n",
"1861 | מנורה מבטחים השתלמות טווח ארוך\n",
"1350 | כלל השתלמות מניות\n",
"1351 | כלל השתלמות שקלי טווח קצר\n",
"1353 | *** מיטב דש השתלמות מעל 6 שנות וותק \n",
"1354 | *** הפניקס השתלמות - מסלול אג\"ח\n",
"9545 | הפניקס השתלמות - מסלול פאסיבי - מדדי אג\"ח \n",
"9546 | הפניקס השתלמות - מסלול פאסיבי - מדדי אג\"ח חו\"ל \n",
"9549 | הפניקס השתלמות - מסלול מתמחה שקלי טווח קצר \n",
"9548 | הפניקס השתלמות - מסלול פאסיבי- מדדי מניות חו\"ל \n",
"9547 | הפניקס השתלמות מסלול פאסיבי - מדדי מניות \n",
"1361 | ילין לפידות קרן השתלמות מסלול אג\"ח ממשלת ישראל\n",
"1367 | הלמן-אלדובי השתלמות אג\"ח עד 15% במניות\n",
"1369 | הראל השתלמות מסלול שקלי\n",
"1370 | *** מיטב דש השתלמות שקלי טווח קצר\n",
"864 | *** מגדל השתלמות שקלי טווח קצר\n",
"865 | *** מגדל השתלמות אג\"ח ממשלתי ישראלי\n",
"1378 | *** אלטשולר שחם השתלמות אג\"ח ללא מניות\n",
"1377 | *** אלטשולר שחם השתלמות מניות\n",
"868 | *** מגדל השתלמות חו\"ל\n",
"869 | *** מגדל השתלמות מניות\n",
"9568 | הראל השתלמות כללי פאסיבי \n",
"1384 | ** הנדסאים וטכנאים מסלול אג\"ח\n",
"1385 | ** מינהל - השתלמות - אג\"ח\n",
"1387 | *** מיטב דש השתלמות אג\"ח ממשלת ישראל\n",
"880 | *** מיטב דש השתלמות כללי\n",
"881 | *** מיטב דש השתלמות אג\"ח צמוד מדד\n",
"883 | *** מיטב דש השתלמות מניות\n",
"8563 | ילין לפידות קרן השתלמות מסלול מניות\n",
"1398 | אלטשולר שחם השתלמות כספי\n",
"1399 | אלטשולר שחם השתלמות אג\"ח ממשלות\n",
"378 | ** ק.ל.ע מסלול כללי\n",
"8058 | *** הראל השתלמות אג\"ח קונצרני \n",
"1404 | ** עובדי המדינה - אג\"ח ממשלת ישראל\n",
"382 | ** עובדי מדינה - כללי\n",
"1408 | *** מנורה השתלמות-אג\"ח ממשלת ישראל\n",
"1409 | מנורה מבטחים השתלמות-מניות חו\"ל\n",
"1410 | ** קרן החיסכון לצבא הקבע מסלול אג\"ח ללא מניות\n",
"1411 | ** קרן החיסכון לצבא הקבע מניות\n",
"392 | ** רעות-כללי\n",
"394 | ** קרן השתלמות עוצ\"מ\n",
"395 | *** הלמן-אלדובי השתלמות אג\"ח עד 25% במניות\n",
"396 | *** פסגות שיא השתלמות כללי\n",
"1424 | *** פסגות שיא השתלמות אגח עד 10% מניות\n",
"1429 | *** פסגות שיא השתלמות אג\"ח ממשלת ישראל\n",
"1430 | ** רעות שיקלי\n",
"8597 | *** הפניקס השתלמות - מסלול אג\"ח עד 25% מניות\n",
"408 | ** רום קרן השתלמות לעובדי רשויות מקומיות - קלאסי כללי\n",
"1433 | ** ק.ל.ע מסלול אג\"ח עד 25% מניות\n",
"416 | *** הראל השתלמות אג\"ח עד 20% מניות \n",
"418 | ** אחים ואחיות - מסלול כללי\n",
"419 | ** השתלמות רופאים כללי\n",
"420 | ** פ.ר.ח - כללי\n",
"1443 | *** אי.בי.אי השתלמות פאסיבי - מדדי אג\"ח ממשלת ישראל\n",
"1445 | ** אומגה קרן השתלמות מסלול אג\"ח\n",
"423 | ** קרן השתלמות עובדי חברת חשמל\n",
"1446 | ** אומגה קרן השתלמות מסלול מניות\n",
"1451 | ** קרן השתלמות לאקדמאים במדעי החברה והרוח מסלול אג\"ח\n",
"1452 | ** קרן השתלמות לאקדמאים במדעי החברה והרוח מסלול מניות\n",
"1454 | ** השתלמות משפטנים מנייתי\n",
"1455 | ** השתלמות משפטנים ללא מניות\n",
"1456 | ** אחים ואחיות - מסלול ללא מניות\n",
"8628 | אקסלנס השתלמות פאסיבי-מדדי אג\"ח עד 25% במדדי מניות\n",
"8629 | *** אקסלנס השתלמות פאסיבי - כללי\n",
"438 | ** קרן החיסכון לצבא הקבע כללי\n",
"8631 | *** אקסלנס השתלמות פאסיבי-מדדי אג\"ח\n",
"8630 | *** אקסלנס השתלמות פאסיבי-מדדי מניות \n",
"9662 | מנורה השתלמות אג\"ח עד 20% מניות\n",
"1471 | ** פ.ר.ח - אג\"ח ללא מניות\n",
"1472 | ** השתלמות רופאים אג\"ח ממשלת ישראל\n",
"8129 | אנליסט השתלמות כללי אג\"ח עד 10% מניות\n",
"962 | *** אנליסט השתלמות כללי \n",
"963 | אנליסט השתלמות מניות\n",
"964 | *** אקסלנס השתלמות כללי\n",
"456 | *** כלל השתלמות כללי\n",
"968 | *** אקסלנס השתלמות מניות\n",
"1821 | ** ק.ס.מ מניות \n",
"1483 | *** הפניקס השתלמות -שיטת הפניקס\n",
"972 | אנליסט השתלמות אג\"ח\n",
"973 | אנליסט השתלמות אג\"ח ממשלת ישראל\n",
"1485 | הראל השתלמות אג\"ח ללא מניות \n",
"1487 | מיטב השתלמות בניהול אישי\n",
"9676 | אינטרגמל השתלמות מעורב מחקה מדדים\n",
"1489 | הלמן-אלדובי השתלמות בניהול אישי\n",
"1491 | אינפיניטי השתלמות אג\"ח קונצרני\n",
"7635 | ** עובדי מדינה - משולב-אג\"ח עד 15 אחוז מניות\n",
"470 | מגדל השתלמות לבני 60 ומעלה\n",
"12256 | אלטשולר שחם השתלמות הלכה\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"481 | מיטב דש השתלמות כללי פאסיבי\n",
"482 | ** מורים על יסודי\n",
"2018 | *** פסגות שיא השתלמות הלכה\n",
"484 | ** מורים וגננות - מסלול כללי\n",
"485 | ** מורים תיכוניים - מסלול כללי\n",
"8679 | אנליסט השתלמות אג\"ח עד 20% במניות\n",
"2024 | הפניקס השתלמות בניהול אישי\n",
"1515 | פסגות השתלמות בניהול אישי\n",
"1523 | *** הראל השתלמות מסלול כהלכה\n",
"2036 | ** מורים וגננות - מסלול אג\"ח\n",
"2035 | ** מורים וגננות - מסלול הלכה\n",
"2038 | ** מורים תיכוניים - מסלול אג\"ח\n",
"2039 | ** מורים וגננות - מסלול הלכה\n",
"2040 | ** מורים וגננות - מסלול אג\"ח\n",
"2037 | ** מורים תיכוניים - מסלול הלכה\n",
"2042 | ** מורים תיכוניים - מסלול אג\"ח\n",
"8701 | \"אינטרגמל השתלמות\"-מדד \"מניות תל אביב 35\"\n",
"1534 | כלל השתלמות הלכה\n",
"1535 | אנליסט השתלמות שקלי טווח קצר\n"
]
}
],
"source": [
"allKranotIDs = set(mdf.loc[mdf[\"type\"]==\"קרן השתלמות\", \"ID\"].values)\n",
"allKranot = []\n",
"for id in allKranotIDs:\n",
" keren = getKeren(id)\n",
" allKranot.append(keren)\n",
" print(keren.name)\n",
"allKranot = [s for s in allKranot if len(s.s) > 0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### השוואה של כל קרנות ההשתלמות במסלול כללי לתיק 60\\40 פשוט"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:41.431151Z",
"start_time": "2018-07-21T20:03:41.427177Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"def getMedianSer(lst):\n",
" df = pd.DataFrame([s.s for s in lst]).T\n",
" return wrap(df.median(axis=1), \"median\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:41.444514Z",
"start_time": "2018-07-21T20:03:41.433537Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"['1204 | *** אי.בי.אי השתלמות כללי',\n",
" '1083 | אינפיניטי השתלמות כללי',\n",
" '1093 | *** אלטשולר שחם השתלמות כללי',\n",
" \"1290 | אלטשולר שחם השתלמות כללי ב'\",\n",
" '962 | *** אנליסט השתלמות כללי ',\n",
" '964 | *** אקסלנס השתלמות כללי',\n",
" '132 | *** הלמן-אלדובי השתלמות כללי',\n",
" '154 | הראל השתלמות כללי',\n",
" '1162 | ילין לפידות קרן השתלמות מסלול כללי',\n",
" '456 | *** כלל השתלמות כללי',\n",
" '579 | *** מגדל השתלמות כללי',\n",
" '1157 | *** מגדל השתלמות ביג כללי לפחות 30% מניות',\n",
" '880 | *** מיטב דש השתלמות כללי',\n",
" '828 | *** מנורה מבטחים השתלמות כללי',\n",
" '1059 | *** פסגות שיא השתלמות פאסיבי-כללי',\n",
" '1218 | *** פסגות שיא השתלמות כללי',\n",
" '396 | *** פסגות שיא השתלמות כללי']"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lst = [s for s in allKranot if s.index[0].year < 2010 and \"כללי\" in s.name]\n",
"lst = [s for s in lst if not \" ** \" in s.name] # exclude exclusive funds for specific sectors\n",
"lst = sorted(lst, key=lambda s: s.name.split(\"|\")[1].strip(\" *\").split(\" \")[0])\n",
"[s.name for s in lst]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:41.868280Z",
"start_time": "2018-07-21T20:03:41.447146Z"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
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],
"layout": {
"hovermode": "closest",
"legend": {},
"margin": {
"b": 30,
"l": 30,
"pad": 0,
"r": 30,
"t": 30
},
"shapes": [
{
"line": {
"color": "red",
"width": 1
},
"opacity": 1,
"type": "line",
"x0": 0,
"x1": 1,
"xref": "paper",
"y0": 1,
"y1": 1,
"yref": "x"
}
],
"showlegend": false,
"title": null,
"yaxis": {
"autorange": true,
"type": "log"
}
}
},
"text/html": [
""
],
"text/vnd.plotly.v1+html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"base = get(\"VT:60|VFITX:40\", mode=\"NTR\")\n",
"basem = bom(base)\n",
"\n",
"lst = [s.dropna() for s in lst]\n",
"medianSer = getMedianSer(lst)\n",
"\n",
"show(lst, base, basem, base/medianSer, 1, ta=True, legend=False)\n",
"shown = show(lst, basem, ta=True, silent=True);"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:44.292988Z",
"start_time": "2018-07-21T20:03:41.870296Z"
}
},
"outputs": [
{
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O0vLs5fr6vK8r4AuoYHKBEuISHJ4WAID7R+wBAACAq1Q3VdthpyxUptNXTkuS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\nAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"allbases = mix(\"VT\", \"VFITX\", n=10, mode=\"NTR\")\n",
"allbases = list(map(bom, allbases))\n",
"allbases = trimBy(allbases, shown)\n",
"\n",
"showRiskReturn(shown + allbases) \n",
"showRiskReturn(allbases, setlim=False, lines=True, color=\"green\")\n",
"showRiskReturn([allbases[6]], setlim=False, lines=True, color=\"red\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### השוואה של כל קרנות ההשתלמות במסלול כללי לתיק 60\\40 פשוט - השוואה יחסית בין הקרנות"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:44.480536Z",
"start_time": "2018-07-21T20:03:44.294879Z"
}
},
"outputs": [
{
"data": {
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"layout": {
"hovermode": "closest",
"legend": {},
"margin": {
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"l": 30,
"pad": 0,
"r": 30,
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"shapes": [],
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"text/html": [
""
],
"text/vnd.plotly.v1+html": [
""
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"metadata": {},
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],
"source": [
"lst = trimBy(lst, lst)\n",
"lst = [s / s[0] for s in lst]\n",
"# finals = [(s, s[-1]) for s in lst]\n",
"# finals = sorted(finals, key=lambda x: x[1])\n",
"# medianSer = finals[len(finals) // 2][0]\n",
"\n",
"medianSer = getMedianSer(lst)\n",
"lst2 = [s / medianSer for s in lst]\n",
"\n",
"show(lst2, base, ta=False, legend=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## סך נכסים מנוהלים וצבירה נטו לפי סוג קופה"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:19:20.100228Z",
"start_time": "2018-07-21T20:19:19.941684Z"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
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"2016-09-01",
"2016-10-01",
"2016-11-01",
"2016-12-01",
"2017-01-01",
"2017-02-01",
"2017-03-01",
"2017-04-01",
"2017-05-01",
"2017-06-01",
"2017-07-01",
"2017-08-01",
"2017-09-01",
"2017-10-01",
"2017-11-01",
"2017-12-01",
"2018-01-01",
"2018-02-01",
"2018-03-01",
"2018-04-01",
"2018-05-01"
],
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},
{
"name": "Total",
"text": "Total",
"type": "scatter",
"x": [
"1999-01-01",
"1999-02-01",
"1999-03-01",
"1999-04-01",
"1999-05-01",
"1999-06-01",
"1999-07-01",
"1999-08-01",
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"2000-05-01",
"2000-06-01",
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"2003-01-01",
"2003-02-01",
"2003-03-01",
"2003-04-01",
"2003-05-01",
"2003-06-01",
"2003-07-01",
"2003-08-01",
"2003-09-01",
"2003-10-01",
"2003-11-01",
"2003-12-01",
"2004-01-01",
"2004-02-01",
"2004-03-01",
"2004-04-01",
"2004-05-01",
"2004-06-01",
"2004-07-01",
"2004-08-01",
"2004-09-01",
"2004-10-01",
"2004-11-01",
"2004-12-01",
"2005-01-01",
"2005-02-01",
"2005-03-01",
"2005-04-01",
"2005-05-01",
"2005-06-01",
"2005-07-01",
"2005-08-01",
"2005-09-01",
"2005-10-01",
"2005-11-01",
"2005-12-01",
"2006-01-01",
"2006-02-01",
"2006-03-01",
"2006-04-01",
"2006-05-01",
"2006-06-01",
"2006-07-01",
"2006-08-01",
"2006-09-01",
"2006-10-01",
"2006-11-01",
"2006-12-01",
"2007-01-01",
"2007-02-01",
"2007-03-01",
"2007-04-01",
"2007-05-01",
"2007-06-01",
"2007-07-01",
"2007-08-01",
"2007-09-01",
"2007-10-01",
"2007-11-01",
"2007-12-01",
"2008-01-01",
"2008-02-01",
"2008-03-01",
"2008-04-01",
"2008-05-01",
"2008-06-01",
"2008-07-01",
"2008-08-01",
"2008-09-01",
"2008-10-01",
"2008-11-01",
"2008-12-01",
"2009-02-01",
"2009-03-01",
"2009-04-01",
"2009-05-01",
"2009-06-01",
"2009-07-01",
"2009-08-01",
"2009-09-01",
"2009-10-01",
"2009-11-01",
"2009-12-01",
"2010-01-01",
"2010-02-01",
"2010-03-01",
"2010-04-01",
"2010-05-01",
"2010-06-01",
"2010-07-01",
"2010-08-01",
"2010-09-01",
"2010-10-01",
"2010-11-01",
"2010-12-01",
"2011-01-01",
"2011-02-01",
"2011-03-01",
"2011-04-01",
"2011-05-01",
"2011-06-01",
"2011-07-01",
"2011-08-01",
"2011-09-01",
"2011-10-01",
"2011-11-01",
"2011-12-01",
"2012-01-01",
"2012-02-01",
"2012-03-01",
"2012-04-01",
"2012-05-01",
"2012-06-01",
"2012-07-01",
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"2013-12-01",
"2014-01-01",
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"2014-03-01",
"2014-04-01",
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"2015-01-01",
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"2015-04-01",
"2015-05-01",
"2015-06-01",
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"2015-08-01",
"2015-09-01",
"2015-10-01",
"2015-11-01",
"2015-12-01",
"2016-01-01",
"2016-02-01",
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"2017-05-01",
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"layout": {
"hovermode": "closest",
"legend": {
"bgcolor": "#FFFFFFBB",
"bordercolor": "#888888",
"borderwidth": 1,
"font": {
"color": "#000",
"family": "sans-serif",
"size": 12
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"traceorder": "normal",
"x": 0,
"y": 1
},
"margin": {
"b": 30,
"l": 30,
"pad": 0,
"r": 30,
"t": 30
},
"shapes": [],
"showlegend": true,
"title": "Cumulative Net Flow",
"yaxis": {
"autorange": true,
"type": null
}
}
},
"text/html": [
""
],
"text/vnd.plotly.v1+html": [
""
]
},
"metadata": {},
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],
"source": [
"aum = mdf.groupby([\"month\", \"type\"])[\"AUM\"].sum()\n",
"aum = aum.unstack()\n",
"show(aum, ta=False, log=False, title=\"AUM\")\n",
"\n",
"net_flow = mdf.groupby([\"month\", \"type\"])[\"net_flow\"].sum()\n",
"net_flow = net_flow.unstack()\n",
"net_flow = net_flow.cumsum()\n",
"total = net_flow.sum(axis=1)\n",
"total.name = \"Total\"\n",
"show(net_flow, total, ta=False, log=False, title=\"Cumulative Net Flow\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## סך נכסים מנוהלים וצבירה נטו בקרנות השתלמות במסלול כללי"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:56.584557Z",
"start_time": "2018-07-21T20:03:44.482482Z"
}
},
"outputs": [],
"source": [
"aums = list(map(getAum, allKranotIDs))\n",
"flowSums = list(map(getFlowSum, allKranotIDs))"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:56.602463Z",
"start_time": "2018-07-21T20:03:56.592137Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"aums = [s for s in aums if \"כללי\" in s.name]\n",
"aums = [s for s in aums if not \" ** \" in s.name] # exclude exclusive funds for specific sectors\n",
"\n",
"flowSums = [s for s in flowSums if \"כללי\" in s.name]\n",
"flowSums = [s for s in flowSums if not \" ** \" in s.name] # exclude exclusive funds for specific sectors"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"ExecuteTime": {
"end_time": "2018-07-21T20:03:56.857128Z",
"start_time": "2018-07-21T20:03:56.604736Z"
}
},
"outputs": [
{
"data": {
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"data": [
{
"name": "7703 | אנליסט השתלמות כללי פאסיבי AUM",
"text": "7703 | אנליסט השתלמות כללי פאסיבי AUM",
"type": "scatter",
"x": [
"2016-10-01",
"2016-11-01",
"2016-12-01",
"2017-01-01",
"2017-02-01",
"2017-03-01",
"2017-04-01",
"2017-05-01",
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"source": [
"id = 1093\n",
"flowsum = getFlowSum(id)\n",
"aum = getAum(id)\n",
"gains = getKeren(id)\n",
"show(aum , flowsum, gains, ta=True)"
]
},
{
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"metadata": {
"ExecuteTime": {
"start_time": "2018-07-21T20:26:43.762Z"
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},
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""
]
},
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},
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"text": [
"Publishing GemelNetPlay.ipynb ..\n"
]
}
],
"source": [
"# be sure to save before you publish\n",
"# when done, you will get a public link to an HTML file with the results\n",
"publish()"
]
}
],
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