{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "5cff81eb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: yfinance in c:\\users\\paolo\\anaconda3\\lib\\site-packages (0.2.20)\n", "Requirement already satisfied: pandas>=1.3.0 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (1.5.3)\n", "Requirement already satisfied: numpy>=1.16.5 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (1.23.4)\n", "Requirement already satisfied: requests>=2.26 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (2.28.1)\n", "Requirement already satisfied: multitasking>=0.0.7 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (0.0.11)\n", "Requirement already satisfied: lxml>=4.9.1 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (4.9.1)\n", "Requirement already satisfied: appdirs>=1.4.4 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (1.4.4)\n", "Requirement already satisfied: pytz>=2022.5 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (2022.7)\n", "Requirement already satisfied: frozendict>=2.3.4 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (2.3.8)\n", "Requirement already satisfied: cryptography>=3.3.2 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (39.0.1)\n", "Requirement already satisfied: beautifulsoup4>=4.11.1 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (4.11.1)\n", "Requirement already satisfied: html5lib>=1.1 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from yfinance) (1.1)\n", "Requirement already satisfied: soupsieve>1.2 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from beautifulsoup4>=4.11.1->yfinance) (2.3.2.post1)\n", "Requirement already satisfied: cffi>=1.12 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from cryptography>=3.3.2->yfinance) (1.15.1)\n", "Requirement already satisfied: six>=1.9 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from html5lib>=1.1->yfinance) (1.16.0)\n", "Requirement already satisfied: webencodings in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from html5lib>=1.1->yfinance) (0.5.1)\n", "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from pandas>=1.3.0->yfinance) (2.8.2)\n", "Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (2.0.4)\n", "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (3.4)\n", "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (1.26.14)\n", "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from requests>=2.26->yfinance) (2023.7.22)\n", "Requirement already satisfied: pycparser in c:\\users\\paolo\\anaconda3\\lib\\site-packages (from cffi>=1.12->cryptography>=3.3.2->yfinance) (2.21)\n" ] } ], "source": [ "!pip install yfinance" ] }, { "cell_type": "code", "execution_count": 2, "id": "5cff81ea", "metadata": {}, "outputs": [], "source": [ "import yfinance as yf\n", "import pandas as pd\n", "import numpy as np\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "id": "774c9a0e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[*********************100%***********************] 1 of 1 completed\n" ] }, { "data": { "text/plain": [ "Date\n", "1997-12-31 24402.000000\n", "1998-01-02 24914.000000\n", "1998-01-05 25734.000000\n", "1998-01-06 25734.000000\n", "1998-01-07 25961.000000\n", " ... \n", "2023-10-13 28237.000000\n", "2023-10-16 28392.000000\n", "2023-10-17 28367.000000\n", "2023-10-18 28136.000000\n", "2023-10-19 27770.490234\n", "Name: Adj Close, Length: 6598, dtype: float64" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dati = yf.download(\"FTSEMIB.MI\")[\"Adj Close\"]\n", "dati" ] }, { "cell_type": "code", "execution_count": 4, "id": "558af0ff", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 584500.000000\n", "mean 0.568294\n", "std 32.834780\n", "min -67.210517\n", "25% -26.342204\n", "50% -1.984252\n", "75% 24.990848\n", "max 92.115400\n", "Name: Adj Close, dtype: float64" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rendimento3anni = ( dati/dati.shift(251*3)-1 ).dropna()\n", "rendimento3anni.describe()*100" ] }, { "cell_type": "code", "execution_count": 5, "id": "2bec9fc3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 % -67.21051674417396\n", "10 % -44.83568322763446\n", "20 % -32.14172194053601\n", "30 % -17.80068967180441\n", "40 % -8.578689098194934\n", "50 % -1.9842519685039361\n", "60 % 6.110632801345408\n", "70 % 17.72448604518794\n", "80 % 33.49361431036509\n", "90 % 47.12186698040445\n", "100 % 92.11540037701829\n" ] } ], "source": [ "for i in range(11):\n", " print(i*10,\"%\", rendimento3anni.quantile(i/10)*100)" ] }, { "cell_type": "code", "execution_count": 6, "id": "218ab50d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-0,6721051674417396\n", "-0,3214172194053601\n", "-0,08578689098194935\n", "-0,01984251968503936\n", "0,06110632801345407\n", "0,3349361431036509\n", "0,9211540037701829\n" ] } ], "source": [ "for i in [0,2,4,5,6,8,10]:\n", " print(str(rendimento3anni.quantile(i/10)).replace(\".\",\",\"))" ] }, { "cell_type": "markdown", "id": "7068024a", "metadata": {}, "source": [ "# Rendimento a 33 mesi vs a 36 mesi" ] }, { "cell_type": "code", "execution_count": 7, "id": "eee529bb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[*********************100%***********************] 1 of 1 completed\n" ] }, { "data": { "text/html": [ "
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Adj Closer33mr36m
Date
2000-08-3148135.00.2802230.246131
2000-09-0148322.00.2723850.240542
2000-09-0448564.00.2597770.216167
2000-09-0548322.00.2574900.217357
2000-09-0648357.00.2538110.202619
............
2023-07-1728609.00.1859660.164139
2023-07-1828707.00.1880690.166830
2023-07-1928712.00.1864330.164947
2023-07-2028816.00.1771780.152077
2023-07-2128855.00.1644060.135142
\n", "

5842 rows × 3 columns

\n", "
" ], "text/plain": [ " Adj Close r33m r36m\n", "Date \n", "2000-08-31 48135.0 0.280223 0.246131\n", "2000-09-01 48322.0 0.272385 0.240542\n", "2000-09-04 48564.0 0.259777 0.216167\n", "2000-09-05 48322.0 0.257490 0.217357\n", "2000-09-06 48357.0 0.253811 0.202619\n", "... ... ... ...\n", "2023-07-17 28609.0 0.185966 0.164139\n", "2023-07-18 28707.0 0.188069 0.166830\n", "2023-07-19 28712.0 0.186433 0.164947\n", "2023-07-20 28816.0 0.177178 0.152077\n", "2023-07-21 28855.0 0.164406 0.135142\n", "\n", "[5842 rows x 3 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dati = yf.download(\"FTSEMIB.MI\")[\"Adj Close\"].to_frame()\n", "dati[\"r33m\"]= ( ( dati[\"Adj Close\"] / dati[\"Adj Close\"].shift(21*33) ) **(12/33) ) -1\n", "dati[\"r36m\"] = ( ( dati[\"Adj Close\"].shift(-21*3) / dati[\"Adj Close\"].shift(21*33) ) **(12/36) ) -1\n", "dati.dropna(inplace=True)\n", "dati" ] }, { "cell_type": "code", "execution_count": 8, "id": "a75669fe", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Adj Closer33mr36mottimo
Date
2000-08-3148135.00.2802230.246131False
2000-09-0148322.00.2723850.240542False
2000-09-0448564.00.2597770.216167False
2000-09-0548322.00.2574900.217357False
2000-09-0648357.00.2538110.202619False
...............
2023-07-1728609.00.1859660.164139False
2023-07-1828707.00.1880690.166830False
2023-07-1928712.00.1864330.164947False
2023-07-2028816.00.1771780.152077False
2023-07-2128855.00.1644060.135142False
\n", "

5842 rows × 4 columns

\n", "
" ], "text/plain": [ " Adj Close r33m r36m ottimo\n", "Date \n", "2000-08-31 48135.0 0.280223 0.246131 False\n", "2000-09-01 48322.0 0.272385 0.240542 False\n", "2000-09-04 48564.0 0.259777 0.216167 False\n", "2000-09-05 48322.0 0.257490 0.217357 False\n", "2000-09-06 48357.0 0.253811 0.202619 False\n", "... ... ... ... ...\n", "2023-07-17 28609.0 0.185966 0.164139 False\n", "2023-07-18 28707.0 0.188069 0.166830 False\n", "2023-07-19 28712.0 0.186433 0.164947 False\n", "2023-07-20 28816.0 0.177178 0.152077 False\n", "2023-07-21 28855.0 0.164406 0.135142 False\n", "\n", "[5842 rows x 4 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dati[\"ottimo\"] = np.where( dati[\"r33m\"]<0.09, np.where(dati[\"r36m\"]>0.09 , True, False), False)\n", "dati" ] }, { "cell_type": "code", "execution_count": 9, "id": "ea6c826e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False 5742\n", "True 100\n", "Name: ottimo, dtype: int64" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dati[\"ottimo\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 10, "id": "c8e746a7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.7117425539198903 %\n" ] } ], "source": [ "print(100*(100/(5742+100)),\"%\")" ] }, { "cell_type": "code", "execution_count": 11, "id": "7f921644", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dati[\"ottimo_quanto\"] = np.where( dati[\"ottimo\"], dati[\"r36m\"], np.nan)\n", "dati[\"ottimo_quanto\"].plot(kind=\"hist\",bins=15)" ] }, { "cell_type": "code", "execution_count": null, "id": "f2de76e4", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }