main_notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as image\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = [12.0, 6.0]\n",
    "\n",
    "import okama as ok\n",
    "\n",
    "pd.options.display.float_format = \"{:,.5f}\".format\n",
    "np.set_printoptions(precision=5)\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "'1.3.2'"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ok.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "         symbol ticker                                               name  \\\n0     ABIO.MOEX   ABIO                                             ARTGEN   \n1     ABRD.MOEX   ABRD                                    Abrau Durso OAO   \n2     ACKO.MOEX   ACKO       Public joint-stock company Asko-Strakhovanie   \n3     AFKS.MOEX   AFKS                                        AFK Sistema   \n4     AFLT.MOEX   AFLT                                           Aeroflot   \n..          ...    ...                                                ...   \n345   YRSB.MOEX   YRSB                           TNS Energo Yaroslavl PAO   \n346  YRSBP.MOEX  YRSBP  Public Joint Stock Company TNS Energo Yaroslav...   \n347   YUAN.MOEX   YUAN                                     YUAN Bonds ETF   \n348   ZILL.MOEX   ZILL                                        AMO ZIL PAO   \n349   ZVEZ.MOEX   ZVEZ                                         Zvezda OAO   \n\n    country exchange currency          type          isin  \n0    Russia     MOEX      RUB  Common Stock                \n1    Russia     MOEX      RUB  Common Stock  RU000A0JS5T7  \n2    Russia     MOEX      RUB  Common Stock  RU000A0JXS91  \n3    Russia     MOEX      RUB  Common Stock  RU000A0DQZE3  \n4    Russia     MOEX      RUB  Common Stock  RU0009062285  \n..      ...      ...      ...           ...           ...  \n345  Russia     MOEX      RUB  Common Stock  RU000A0D8760  \n346  Russia     MOEX      RUB  Common Stock                \n347  Russia     MOEX      RUB           ETF                \n348  Russia     MOEX      RUB  Common Stock  RU0009086193  \n349  Russia     MOEX      RUB  Common Stock  RU0009091300  \n\n[350 rows x 8 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>symbol</th>\n      <th>ticker</th>\n      <th>name</th>\n      <th>country</th>\n      <th>exchange</th>\n      <th>currency</th>\n      <th>type</th>\n      <th>isin</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>ABIO.MOEX</td>\n      <td>ABIO</td>\n      <td>ARTGEN</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td></td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>ABRD.MOEX</td>\n      <td>ABRD</td>\n      <td>Abrau Durso OAO</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU000A0JS5T7</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>ACKO.MOEX</td>\n      <td>ACKO</td>\n      <td>Public joint-stock company Asko-Strakhovanie</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU000A0JXS91</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>AFKS.MOEX</td>\n      <td>AFKS</td>\n      <td>AFK Sistema</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU000A0DQZE3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>AFLT.MOEX</td>\n      <td>AFLT</td>\n      <td>Aeroflot</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU0009062285</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>345</th>\n      <td>YRSB.MOEX</td>\n      <td>YRSB</td>\n      <td>TNS Energo Yaroslavl PAO</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU000A0D8760</td>\n    </tr>\n    <tr>\n      <th>346</th>\n      <td>YRSBP.MOEX</td>\n      <td>YRSBP</td>\n      <td>Public Joint Stock Company TNS Energo Yaroslav...</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td></td>\n    </tr>\n    <tr>\n      <th>347</th>\n      <td>YUAN.MOEX</td>\n      <td>YUAN</td>\n      <td>YUAN Bonds ETF</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>ETF</td>\n      <td></td>\n    </tr>\n    <tr>\n      <th>348</th>\n      <td>ZILL.MOEX</td>\n      <td>ZILL</td>\n      <td>AMO ZIL PAO</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU0009086193</td>\n    </tr>\n    <tr>\n      <th>349</th>\n      <td>ZVEZ.MOEX</td>\n      <td>ZVEZ</td>\n      <td>Zvezda OAO</td>\n      <td>Russia</td>\n      <td>MOEX</td>\n      <td>RUB</td>\n      <td>Common Stock</td>\n      <td>RU0009091300</td>\n    </tr>\n  </tbody>\n</table>\n<p>350 rows × 8 columns</p>\n</div>"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ok.symbols_in_namespace(namespace=\"MOEX\")"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## DCF"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\common\\helpers\\helpers.py:456: FutureWarning: The 'convention' keyword in DataFrame.resample is deprecated and will be removed in a future version. Explicitly cast PeriodIndex to DatetimeIndex before resampling instead.\n",
      "  for x in ror.resample(rule=self.pandas_frequency, convention=\"start\"):\n",
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\common\\helpers\\helpers.py:456: FutureWarning: Resampling with a PeriodIndex is deprecated. Cast index to DatetimeIndex before resampling instead.\n",
      "  for x in ror.resample(rule=self.pandas_frequency, convention=\"start\"):\n"
     ]
    },
    {
     "data": {
      "text/plain": "symbol                                              retirement_portf.PF\nassets                [RGBITR.INDX, RUCBTRNS.INDX, MCFTR.INDX, GC.COMM]\nweights                                        [0.32, 0.31, 0.18, 0.19]\nrebalancing_period                                                 year\ncurrency                                                            RUB\ninflation                                                      RUB.INFL\nfirst_date                                                      2003-01\nlast_date                                                       2023-12\nperiod_length                                        21 years, 0 months\ndtype: object"
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = [0.32, 0.31, 0.18, 0.19]\n",
    "portf = ok.Portfolio(\n",
    "    [\"RGBITR.INDX\", \"RUCBTRNS.INDX\", \"MCFTR.INDX\", \"GC.COMM\"],\n",
    "    ccy=\"RUB\",\n",
    "    weights=weights,\n",
    "    inflation=True,\n",
    "    symbol=\"retirement_portf.PF\",\n",
    "    rebalancing_period=\"year\",\n",
    "    cashflow=200_000,\n",
    "    initial_amount=39_000_000,\n",
    "    discount_rate=None,\n",
    ")\n",
    "portf"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\common\\helpers\\helpers.py:456: FutureWarning: The 'convention' keyword in DataFrame.resample is deprecated and will be removed in a future version. Explicitly cast PeriodIndex to DatetimeIndex before resampling instead.\n",
      "  for x in ror.resample(rule=self.pandas_frequency, convention=\"start\"):\n",
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\common\\helpers\\helpers.py:456: FutureWarning: Resampling with a PeriodIndex is deprecated. Cast index to DatetimeIndex before resampling instead.\n",
      "  for x in ror.resample(rule=self.pandas_frequency, convention=\"start\"):\n"
     ]
    },
    {
     "data": {
      "text/plain": "21.0"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portf.dcf.survival_period"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "outputs": [
    {
     "data": {
      "text/plain": "Timestamp('2023-12-31 00:00:00')"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portf.dcf.survival_date"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rolling and expanding risk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "assets             [SPY.US, BND.US]\ncurrency                        USD\nfirst_date                  2007-05\nlast_date                   2024-01\nperiod_length    16 years, 9 months\ninflation                  USD.INFL\ndtype: object"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al = ok.AssetList([\"SPY.US\", \"BND.US\"])\n",
    "al"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='date'>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1200x800 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "al.risk_annual.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='date'>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1200x800 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "al.get_rolling_risk_annual(window=12 * 5).plot()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\asset.py:175: FutureWarning: Resampling with a PeriodIndex is deprecated. Cast index to DatetimeIndex before resampling instead.\n",
      "  return div.resample(\"M\").sum()\n",
      "C:\\Users\\Sergey\\PycharmProjects\\okama\\okama\\asset.py:175: FutureWarning: Resampling with a PeriodIndex is deprecated. Cast index to DatetimeIndex before resampling instead.\n",
      "  return div.resample(\"M\").sum()\n"
     ]
    },
    {
     "data": {
      "text/plain": "                  property              period   SPY.US   BND.US inflation\n0          Compound return                 YTD  0.01590 -0.00160   0.00540\n1                     CAGR             1 years  0.20603  0.02105   0.03089\n2                     CAGR             5 years  0.14194  0.00782   0.04148\n3                     CAGR            10 years  0.12509  0.01565   0.02805\n4                     CAGR  16 years, 9 months  0.09404  0.02918   0.02419\n5   Annualized mean return  16 years, 9 months  0.10801  0.03024       NaN\n6           Dividend yield                 LTM  0.01374  0.03090       NaN\n7                     Risk  16 years, 9 months  0.17617  0.04695       NaN\n8                     CVAR  16 years, 9 months  0.40832  0.15194       NaN\n9            Max drawdowns  16 years, 9 months -0.50780 -0.17534       NaN\n10     Max drawdowns dates  16 years, 9 months  2009-02  2022-10       NaN\n11          Inception date                None  1993-02  2007-05   2007-05\n12         Last asset date                None  2024-02  2024-02   2024-01\n13   Common last data date                None  2024-01  2024-01   2024-01",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>property</th>\n      <th>period</th>\n      <th>SPY.US</th>\n      <th>BND.US</th>\n      <th>inflation</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Compound return</td>\n      <td>YTD</td>\n      <td>0.01590</td>\n      <td>-0.00160</td>\n      <td>0.00540</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>CAGR</td>\n      <td>1 years</td>\n      <td>0.20603</td>\n      <td>0.02105</td>\n      <td>0.03089</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>CAGR</td>\n      <td>5 years</td>\n      <td>0.14194</td>\n      <td>0.00782</td>\n      <td>0.04148</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>CAGR</td>\n      <td>10 years</td>\n      <td>0.12509</td>\n      <td>0.01565</td>\n      <td>0.02805</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>CAGR</td>\n      <td>16 years, 9 months</td>\n      <td>0.09404</td>\n      <td>0.02918</td>\n      <td>0.02419</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Annualized mean return</td>\n      <td>16 years, 9 months</td>\n      <td>0.10801</td>\n      <td>0.03024</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Dividend yield</td>\n      <td>LTM</td>\n      <td>0.01374</td>\n      <td>0.03090</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Risk</td>\n      <td>16 years, 9 months</td>\n      <td>0.17617</td>\n      <td>0.04695</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>CVAR</td>\n      <td>16 years, 9 months</td>\n      <td>0.40832</td>\n      <td>0.15194</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Max drawdowns</td>\n      <td>16 years, 9 months</td>\n      <td>-0.50780</td>\n      <td>-0.17534</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Max drawdowns dates</td>\n      <td>16 years, 9 months</td>\n      <td>2009-02</td>\n      <td>2022-10</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Inception date</td>\n      <td>None</td>\n      <td>1993-02</td>\n      <td>2007-05</td>\n      <td>2007-05</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>Last asset date</td>\n      <td>None</td>\n      <td>2024-02</td>\n      <td>2024-02</td>\n      <td>2024-01</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Common last data date</td>\n      <td>None</td>\n      <td>2024-01</td>\n      <td>2024-01</td>\n      <td>2024-01</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.describe()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Dividends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "assets           [SBERP.MOEX, LKOH.MOEX]\n",
       "currency                             RUB\n",
       "first_date                       2006-09\n",
       "last_date                        2023-12\n",
       "period_length         17 years, 4 months\n",
       "inflation                       RUB.INFL\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al = ok.AssetList([\"SBERP.MOEX\", \"LKOH.MOEX\"], ccy=\"RUB\")\n",
    "al"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SBERP.MOEX</th>\n",
       "      <th>LKOH.MOEX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.46500</td>\n",
       "      <td>38.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.65000</td>\n",
       "      <td>42.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.63000</td>\n",
       "      <td>50.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.45000</td>\n",
       "      <td>52.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>1.15000</td>\n",
       "      <td>59.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>2.59000</td>\n",
       "      <td>115.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>3.20000</td>\n",
       "      <td>100.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>3.20000</td>\n",
       "      <td>120.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.45000</td>\n",
       "      <td>159.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>1.97000</td>\n",
       "      <td>187.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>6.00000</td>\n",
       "      <td>205.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>12.00000</td>\n",
       "      <td>225.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>16.00000</td>\n",
       "      <td>347.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>18.70000</td>\n",
       "      <td>396.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>18.70000</td>\n",
       "      <td>553.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>793.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>25.00000</td>\n",
       "      <td>1,290.56000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SBERP.MOEX   LKOH.MOEX\n",
       "2006     0.00000     0.00000\n",
       "2007     0.46500    38.00000\n",
       "2008     0.65000    42.00000\n",
       "2009     0.63000    50.00000\n",
       "2010     0.45000    52.00000\n",
       "2011     1.15000    59.00000\n",
       "2012     2.59000   115.00000\n",
       "2013     3.20000   100.00000\n",
       "2014     3.20000   120.00000\n",
       "2015     0.45000   159.00000\n",
       "2016     1.97000   187.00000\n",
       "2017     6.00000   205.00000\n",
       "2018    12.00000   225.00000\n",
       "2019    16.00000   347.00000\n",
       "2020    18.70000   396.00000\n",
       "2021    18.70000   553.00000\n",
       "2022     0.00000   793.00000\n",
       "2023    25.00000 1,290.56000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.dividends_annual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>SBERP.MOEX</th>\n",
       "      <th>LKOH.MOEX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-09</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-11</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08</th>\n",
       "      <td>0.09425</td>\n",
       "      <td>0.22437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09</th>\n",
       "      <td>0.09580</td>\n",
       "      <td>0.22950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10</th>\n",
       "      <td>0.09320</td>\n",
       "      <td>0.21406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11</th>\n",
       "      <td>0.09058</td>\n",
       "      <td>0.21095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12</th>\n",
       "      <td>0.09173</td>\n",
       "      <td>0.19069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>208 rows × 2 columns</p>\n",
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       "         SBERP.MOEX  LKOH.MOEX\n",
       "2006-09     0.00000    0.00000\n",
       "2006-10     0.00000    0.00000\n",
       "2006-11     0.00000    0.00000\n",
       "2006-12     0.00000    0.00000\n",
       "2007-01     0.00000    0.00000\n",
       "...             ...        ...\n",
       "2023-08     0.09425    0.22437\n",
       "2023-09     0.09580    0.22950\n",
       "2023-10     0.09320    0.21406\n",
       "2023-11     0.09058    0.21095\n",
       "2023-12     0.09173    0.19069\n",
       "\n",
       "[208 rows x 2 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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   "source": [
    "al.dividend_yield"
   ]
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  {
   "cell_type": "code",
   "execution_count": 9,
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   "outputs": [
    {
     "data": {
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       "      <th>LKOH.MOEX</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.00667</td>\n",
       "      <td>0.01834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.07174</td>\n",
       "      <td>0.04368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.00913</td>\n",
       "      <td>0.02952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.00599</td>\n",
       "      <td>0.02985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>0.01943</td>\n",
       "      <td>0.03469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.03848</td>\n",
       "      <td>0.05749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.03999</td>\n",
       "      <td>0.04902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.08488</td>\n",
       "      <td>0.05393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.00588</td>\n",
       "      <td>0.06778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.01518</td>\n",
       "      <td>0.05422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.03175</td>\n",
       "      <td>0.06148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.07221</td>\n",
       "      <td>0.04503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.07008</td>\n",
       "      <td>0.05625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>0.07768</td>\n",
       "      <td>0.07663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>0.06723</td>\n",
       "      <td>0.08417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.19472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>0.09173</td>\n",
       "      <td>0.19069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SBERP.MOEX  LKOH.MOEX\n",
       "2006     0.00000    0.00000\n",
       "2007     0.00667    0.01834\n",
       "2008     0.07174    0.04368\n",
       "2009     0.00913    0.02952\n",
       "2010     0.00599    0.02985\n",
       "2011     0.01943    0.03469\n",
       "2012     0.03848    0.05749\n",
       "2013     0.03999    0.04902\n",
       "2014     0.08488    0.05393\n",
       "2015     0.00588    0.06778\n",
       "2016     0.01518    0.05422\n",
       "2017     0.03175    0.06148\n",
       "2018     0.07221    0.04503\n",
       "2019     0.07008    0.05625\n",
       "2020     0.07768    0.07663\n",
       "2021     0.06723    0.08417\n",
       "2022     0.00000    0.19472\n",
       "2023     0.09173    0.19069"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.dividend_yield_annual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SBERP.MOEX</th>\n",
       "      <th>LKOH.MOEX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.00667</td>\n",
       "      <td>0.01834</td>\n",
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       "      <th>2008</th>\n",
       "      <td>0.07174</td>\n",
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       "      <th>2009</th>\n",
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       "      <th>2010</th>\n",
       "      <td>0.00599</td>\n",
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       "      <th>2011</th>\n",
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       "      <th>2012</th>\n",
       "      <td>0.03848</td>\n",
       "      <td>0.05749</td>\n",
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       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.03999</td>\n",
       "      <td>0.04902</td>\n",
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       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.08488</td>\n",
       "      <td>0.05393</td>\n",
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       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.00588</td>\n",
       "      <td>0.06778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.01518</td>\n",
       "      <td>0.05422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.03175</td>\n",
       "      <td>0.06148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.07221</td>\n",
       "      <td>0.04503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.07008</td>\n",
       "      <td>0.05625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>0.07768</td>\n",
       "      <td>0.07663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>0.06723</td>\n",
       "      <td>0.08417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.19472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>0.09173</td>\n",
       "      <td>0.19069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SBERP.MOEX  LKOH.MOEX\n",
       "2006     0.00000    0.00000\n",
       "2007     0.00667    0.01834\n",
       "2008     0.07174    0.04368\n",
       "2009     0.00913    0.02952\n",
       "2010     0.00599    0.02985\n",
       "2011     0.01943    0.03469\n",
       "2012     0.03848    0.05749\n",
       "2013     0.03999    0.04902\n",
       "2014     0.08488    0.05393\n",
       "2015     0.00588    0.06778\n",
       "2016     0.01518    0.05422\n",
       "2017     0.03175    0.06148\n",
       "2018     0.07221    0.04503\n",
       "2019     0.07008    0.05625\n",
       "2020     0.07768    0.07663\n",
       "2021     0.06723    0.08417\n",
       "2022     0.00000    0.19472\n",
       "2023     0.09173    0.19069"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.dividend_yield.resample(rule=\"Y\").last()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
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     "execution_count": 12,
     "metadata": {},
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "al.dividend_yield_annual.plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SBERP.MOEX   -1.00000\n",
       "LKOH.MOEX     0.28652\n",
       "dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.get_dividend_mean_growth_rate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SBERP.MOEX   0.05166\n",
       "LKOH.MOEX    0.08849\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al.get_dividend_mean_yield(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Plot Wealth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def plot_wealth(\n",
    "    al: object,\n",
    "    first_date: str,\n",
    "    last_date: str,\n",
    "    legend: list,\n",
    "    title: str = None,\n",
    "    logy: bool = False,\n",
    "    figsize: list = [12, 10],\n",
    "):\n",
    "    fig, ax = plt.subplots(figsize=figsize)\n",
    "    # fig.subplots_adjust(bottom=0.2, top=1.5)\n",
    "    first_date_dt = pd.to_datetime(first_date)\n",
    "    last_date_dt = pd.to_datetime(last_date)\n",
    "\n",
    "    wealth = al.wealth_indexes\n",
    "    wealth = wealth.loc[first_date:last_date, :]\n",
    "    index = wealth.index.to_timestamp()\n",
    "    min_value = wealth.to_numpy().min()\n",
    "    for i, asset in enumerate(wealth):\n",
    "        if i == len(wealth.columns) - 1:\n",
    "            # Inflation is in the last column\n",
    "            continue\n",
    "        ax.plot(index, wealth[asset], linewidth=2)\n",
    "    ax.fill_between(index, min_value, wealth.iloc[:, -1], facecolor=\"grey\", alpha=0.2, label=\"Инфляция\")\n",
    "\n",
    "    # Log scale\n",
    "    y_scale = \"log\" if logy else \"linear\"\n",
    "    ax.set_yscale(y_scale)\n",
    "\n",
    "    # границы графика\n",
    "    ax.set_xlim(first_date_dt, last_date_dt + pd.DateOffset(months=0))\n",
    "    ax.set_ylim(bottom=min_value)\n",
    "\n",
    "    # регулирования надписей оси Х\n",
    "    years = mdates.YearLocator()  # ежегодный формат\n",
    "    years_fmt = mdates.DateFormatter(\"%Y\")\n",
    "    # назначение формата надписей\n",
    "    ax.xaxis.set_major_locator(years)\n",
    "    ax.xaxis.set_major_formatter(years_fmt)\n",
    "\n",
    "    ax.legend(legend + [\"Инфляция\"], loc=\"upper left\")\n",
    "    ax.set_title(title)\n",
    "\n",
    "    # ax.set_ylabel('Инфляция за 12 месяцев, %')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "assets           [MCFTR.INDX, SP500TR.INDX]\ncurrency                                RUB\nfirst_date                          1997-10\nlast_date                           2024-02\nperiod_length            26 years, 5 months\ninflation                              None\ndtype: object"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks = ok.AssetList([\"MCFTR.INDX\", \"SP500TR.INDX\"], ccy=\"RUB\", inflation=False)\n",
    "stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1272.73x909.091 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_wealth(\n",
    "    al=stocks, first_date=\"2003-01\", figsize=(14 / 1.1, 10 / 1.1), last_date=\"2023-01\", legend=[\"Индекс ОФЗ\"], logy=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "py311",
   "language": "python",
   "display_name": "py311"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}