11.1 KOSPI200 선물 가격 계산.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>선물가격</th>\n",
       "      <th>지수</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>일자</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017/09/01</th>\n",
       "      <td>308.40</td>\n",
       "      <td>307.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017/09/04</th>\n",
       "      <td>305.60</td>\n",
       "      <td>304.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017/09/05</th>\n",
       "      <td>304.85</td>\n",
       "      <td>304.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017/09/06</th>\n",
       "      <td>304.30</td>\n",
       "      <td>303.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017/09/07</th>\n",
       "      <td>308.10</td>\n",
       "      <td>306.97</td>\n",
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      ],
      "text/plain": [
       "              선물가격      지수\n",
       "일자                        \n",
       "2017/09/01  308.40  307.78\n",
       "2017/09/04  305.60  304.19\n",
       "2017/09/05  304.85  304.06\n",
       "2017/09/06  304.30  303.18\n",
       "2017/09/07  308.10  306.97"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('09.2 KOSPI200 F 201712.xlsx', 'Sheet1', index_col='일자')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.base.Index"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index = pd.to_datetime(df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.datetimes.DatetimeIndex"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def futures_price (S, r, d, T, t0):\n",
    "    t = np.busday_count(t0.date(), T.date()) / 252\n",
    "    F = S * np.exp((r-d)*t)\n",
    "    return F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "T = pd.to_datetime('2017-12-14')     # 최종거래일\n",
    "r = 0.0225     # 이자율\n",
    "d = 0.015     # 배당률\n",
    "for n in (df.index):\n",
    "    t0 = n     \n",
    "    S = df.loc[n, '지수']\n",
    "    F = futures_price (S, r, d, T, t0)\n",
    "    f = '{:,.2f}'.format(F)\n",
    "    df.loc[n, '이론가1'] = f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def S_futures_price (S, r, d, T, t0):\n",
    "    t = (T - t0).days / 365\n",
    "    F = S * (1 + (r-d) * t)\n",
    "    return F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = pd.to_datetime('2017-12-14')     # 최종거래일\n",
    "r = 0.0225     # 이자율\n",
    "d = 0.015     # 배당률\n",
    "for n in (df.index):\n",
    "    t0 = n     \n",
    "    S = df.loc[n, '지수']\n",
    "    F = S_futures_price (S, r, d, T, t0)\n",
    "    f = '{:,.2f}'.format(F)\n",
    "    df.loc[n, '이론가2'] = f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>선물가격</th>\n",
       "      <th>지수</th>\n",
       "      <th>이론가1</th>\n",
       "      <th>이론가2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>일자</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-09-01</th>\n",
       "      <td>308.40</td>\n",
       "      <td>307.78</td>\n",
       "      <td>308.46</td>\n",
       "      <td>308.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-04</th>\n",
       "      <td>305.60</td>\n",
       "      <td>304.19</td>\n",
       "      <td>304.85</td>\n",
       "      <td>304.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-05</th>\n",
       "      <td>304.85</td>\n",
       "      <td>304.06</td>\n",
       "      <td>304.71</td>\n",
       "      <td>304.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-06</th>\n",
       "      <td>304.30</td>\n",
       "      <td>303.18</td>\n",
       "      <td>303.82</td>\n",
       "      <td>303.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-07</th>\n",
       "      <td>308.10</td>\n",
       "      <td>306.97</td>\n",
       "      <td>307.61</td>\n",
       "      <td>307.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-08</th>\n",
       "      <td>308.35</td>\n",
       "      <td>307.43</td>\n",
       "      <td>308.06</td>\n",
       "      <td>308.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-11</th>\n",
       "      <td>311.50</td>\n",
       "      <td>309.83</td>\n",
       "      <td>310.46</td>\n",
       "      <td>310.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-12</th>\n",
       "      <td>311.45</td>\n",
       "      <td>310.42</td>\n",
       "      <td>311.04</td>\n",
       "      <td>311.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-13</th>\n",
       "      <td>310.85</td>\n",
       "      <td>310.00</td>\n",
       "      <td>310.61</td>\n",
       "      <td>310.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-14</th>\n",
       "      <td>313.60</td>\n",
       "      <td>312.52</td>\n",
       "      <td>313.13</td>\n",
       "      <td>313.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-15</th>\n",
       "      <td>314.55</td>\n",
       "      <td>313.69</td>\n",
       "      <td>314.29</td>\n",
       "      <td>314.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-18</th>\n",
       "      <td>320.05</td>\n",
       "      <td>318.93</td>\n",
       "      <td>319.53</td>\n",
       "      <td>319.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-19</th>\n",
       "      <td>319.40</td>\n",
       "      <td>318.51</td>\n",
       "      <td>319.10</td>\n",
       "      <td>319.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-20</th>\n",
       "      <td>319.15</td>\n",
       "      <td>318.48</td>\n",
       "      <td>319.06</td>\n",
       "      <td>319.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-21</th>\n",
       "      <td>319.40</td>\n",
       "      <td>318.25</td>\n",
       "      <td>318.82</td>\n",
       "      <td>318.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-22</th>\n",
       "      <td>317.10</td>\n",
       "      <td>316.71</td>\n",
       "      <td>317.27</td>\n",
       "      <td>317.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-25</th>\n",
       "      <td>317.15</td>\n",
       "      <td>316.40</td>\n",
       "      <td>316.95</td>\n",
       "      <td>316.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-26</th>\n",
       "      <td>315.15</td>\n",
       "      <td>314.29</td>\n",
       "      <td>314.82</td>\n",
       "      <td>314.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-27</th>\n",
       "      <td>314.75</td>\n",
       "      <td>313.82</td>\n",
       "      <td>314.34</td>\n",
       "      <td>314.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-28</th>\n",
       "      <td>314.95</td>\n",
       "      <td>313.85</td>\n",
       "      <td>314.36</td>\n",
       "      <td>314.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-29</th>\n",
       "      <td>317.65</td>\n",
       "      <td>316.27</td>\n",
       "      <td>316.78</td>\n",
       "      <td>316.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-10</th>\n",
       "      <td>323.50</td>\n",
       "      <td>322.49</td>\n",
       "      <td>322.94</td>\n",
       "      <td>322.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-11</th>\n",
       "      <td>326.60</td>\n",
       "      <td>326.12</td>\n",
       "      <td>326.57</td>\n",
       "      <td>326.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-12</th>\n",
       "      <td>329.00</td>\n",
       "      <td>328.11</td>\n",
       "      <td>328.55</td>\n",
       "      <td>328.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-13</th>\n",
       "      <td>328.65</td>\n",
       "      <td>327.35</td>\n",
       "      <td>327.78</td>\n",
       "      <td>327.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-16</th>\n",
       "      <td>328.85</td>\n",
       "      <td>327.82</td>\n",
       "      <td>328.24</td>\n",
       "      <td>328.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-17</th>\n",
       "      <td>329.15</td>\n",
       "      <td>328.51</td>\n",
       "      <td>328.92</td>\n",
       "      <td>328.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-18</th>\n",
       "      <td>329.20</td>\n",
       "      <td>328.40</td>\n",
       "      <td>328.80</td>\n",
       "      <td>328.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-19</th>\n",
       "      <td>327.45</td>\n",
       "      <td>326.47</td>\n",
       "      <td>326.86</td>\n",
       "      <td>326.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-20</th>\n",
       "      <td>329.60</td>\n",
       "      <td>328.89</td>\n",
       "      <td>329.27</td>\n",
       "      <td>329.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-03</th>\n",
       "      <td>339.70</td>\n",
       "      <td>338.83</td>\n",
       "      <td>339.12</td>\n",
       "      <td>339.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-06</th>\n",
       "      <td>337.50</td>\n",
       "      <td>337.40</td>\n",
       "      <td>337.68</td>\n",
       "      <td>337.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-07</th>\n",
       "      <td>337.10</td>\n",
       "      <td>336.76</td>\n",
       "      <td>337.03</td>\n",
       "      <td>337.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-08</th>\n",
       "      <td>338.60</td>\n",
       "      <td>337.80</td>\n",
       "      <td>338.06</td>\n",
       "      <td>338.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-09</th>\n",
       "      <td>337.00</td>\n",
       "      <td>337.14</td>\n",
       "      <td>337.39</td>\n",
       "      <td>337.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-10</th>\n",
       "      <td>336.25</td>\n",
       "      <td>335.96</td>\n",
       "      <td>336.20</td>\n",
       "      <td>336.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-13</th>\n",
       "      <td>334.90</td>\n",
       "      <td>334.33</td>\n",
       "      <td>334.56</td>\n",
       "      <td>334.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-14</th>\n",
       "      <td>334.65</td>\n",
       "      <td>333.62</td>\n",
       "      <td>333.84</td>\n",
       "      <td>333.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-15</th>\n",
       "      <td>332.50</td>\n",
       "      <td>332.17</td>\n",
       "      <td>332.38</td>\n",
       "      <td>332.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-16</th>\n",
       "      <td>334.65</td>\n",
       "      <td>334.36</td>\n",
       "      <td>334.56</td>\n",
       "      <td>334.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-17</th>\n",
       "      <td>334.30</td>\n",
       "      <td>334.18</td>\n",
       "      <td>334.37</td>\n",
       "      <td>334.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-20</th>\n",
       "      <td>332.80</td>\n",
       "      <td>332.92</td>\n",
       "      <td>333.10</td>\n",
       "      <td>333.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-21</th>\n",
       "      <td>334.20</td>\n",
       "      <td>333.51</td>\n",
       "      <td>333.68</td>\n",
       "      <td>333.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-22</th>\n",
       "      <td>335.90</td>\n",
       "      <td>335.49</td>\n",
       "      <td>335.65</td>\n",
       "      <td>335.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-23</th>\n",
       "      <td>334.80</td>\n",
       "      <td>334.51</td>\n",
       "      <td>334.66</td>\n",
       "      <td>334.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-24</th>\n",
       "      <td>335.60</td>\n",
       "      <td>335.44</td>\n",
       "      <td>335.58</td>\n",
       "      <td>335.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-27</th>\n",
       "      <td>329.25</td>\n",
       "      <td>329.53</td>\n",
       "      <td>329.66</td>\n",
       "      <td>329.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-28</th>\n",
       "      <td>331.05</td>\n",
       "      <td>330.99</td>\n",
       "      <td>331.11</td>\n",
       "      <td>331.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-29</th>\n",
       "      <td>331.05</td>\n",
       "      <td>330.68</td>\n",
       "      <td>330.79</td>\n",
       "      <td>330.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-30</th>\n",
       "      <td>325.60</td>\n",
       "      <td>325.25</td>\n",
       "      <td>325.35</td>\n",
       "      <td>325.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>325.20</td>\n",
       "      <td>324.78</td>\n",
       "      <td>324.87</td>\n",
       "      <td>324.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-04</th>\n",
       "      <td>328.35</td>\n",
       "      <td>328.77</td>\n",
       "      <td>328.85</td>\n",
       "      <td>328.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-05</th>\n",
       "      <td>329.95</td>\n",
       "      <td>329.61</td>\n",
       "      <td>329.68</td>\n",
       "      <td>329.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-06</th>\n",
       "      <td>325.00</td>\n",
       "      <td>324.52</td>\n",
       "      <td>324.58</td>\n",
       "      <td>324.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-07</th>\n",
       "      <td>324.05</td>\n",
       "      <td>323.59</td>\n",
       "      <td>323.64</td>\n",
       "      <td>323.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-08</th>\n",
       "      <td>324.75</td>\n",
       "      <td>324.68</td>\n",
       "      <td>324.72</td>\n",
       "      <td>324.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-11</th>\n",
       "      <td>324.85</td>\n",
       "      <td>325.09</td>\n",
       "      <td>325.12</td>\n",
       "      <td>325.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-12</th>\n",
       "      <td>323.80</td>\n",
       "      <td>324.07</td>\n",
       "      <td>324.09</td>\n",
       "      <td>324.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-13</th>\n",
       "      <td>326.20</td>\n",
       "      <td>326.18</td>\n",
       "      <td>326.19</td>\n",
       "      <td>326.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-14</th>\n",
       "      <td>327.65</td>\n",
       "      <td>324.74</td>\n",
       "      <td>324.74</td>\n",
       "      <td>324.74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              선물가격      지수    이론가1    이론가2\n",
       "일자                                        \n",
       "2017-09-01  308.40  307.78  308.46  308.44\n",
       "2017-09-04  305.60  304.19  304.85  304.82\n",
       "2017-09-05  304.85  304.06  304.71  304.68\n",
       "2017-09-06  304.30  303.18  303.82  303.80\n",
       "2017-09-07  308.10  306.97  307.61  307.59\n",
       "2017-09-08  308.35  307.43  308.06  308.04\n",
       "2017-09-11  311.50  309.83  310.46  310.43\n",
       "2017-09-12  311.45  310.42  311.04  311.01\n",
       "2017-09-13  310.85  310.00  310.61  310.59\n",
       "2017-09-14  313.60  312.52  313.13  313.10\n",
       "2017-09-15  314.55  313.69  314.29  314.27\n",
       "2017-09-18  320.05  318.93  319.53  319.50\n",
       "2017-09-19  319.40  318.51  319.10  319.07\n",
       "2017-09-20  319.15  318.48  319.06  319.04\n",
       "2017-09-21  319.40  318.25  318.82  318.80\n",
       "2017-09-22  317.10  316.71  317.27  317.25\n",
       "2017-09-25  317.15  316.40  316.95  316.92\n",
       "2017-09-26  315.15  314.29  314.82  314.80\n",
       "2017-09-27  314.75  313.82  314.34  314.32\n",
       "2017-09-28  314.95  313.85  314.36  314.35\n",
       "2017-09-29  317.65  316.27  316.78  316.76\n",
       "2017-10-10  323.50  322.49  322.94  322.92\n",
       "2017-10-11  326.60  326.12  326.57  326.55\n",
       "2017-10-12  329.00  328.11  328.55  328.53\n",
       "2017-10-13  328.65  327.35  327.78  327.77\n",
       "2017-10-16  328.85  327.82  328.24  328.22\n",
       "2017-10-17  329.15  328.51  328.92  328.90\n",
       "2017-10-18  329.20  328.40  328.80  328.78\n",
       "2017-10-19  327.45  326.47  326.86  326.85\n",
       "2017-10-20  329.60  328.89  329.27  329.26\n",
       "...            ...     ...     ...     ...\n",
       "2017-11-03  339.70  338.83  339.12  339.12\n",
       "2017-11-06  337.50  337.40  337.68  337.66\n",
       "2017-11-07  337.10  336.76  337.03  337.02\n",
       "2017-11-08  338.60  337.80  338.06  338.05\n",
       "2017-11-09  337.00  337.14  337.39  337.38\n",
       "2017-11-10  336.25  335.96  336.20  336.19\n",
       "2017-11-13  334.90  334.33  334.56  334.54\n",
       "2017-11-14  334.65  333.62  333.84  333.83\n",
       "2017-11-15  332.50  332.17  332.38  332.37\n",
       "2017-11-16  334.65  334.36  334.56  334.55\n",
       "2017-11-17  334.30  334.18  334.37  334.37\n",
       "2017-11-20  332.80  332.92  333.10  333.08\n",
       "2017-11-21  334.20  333.51  333.68  333.67\n",
       "2017-11-22  335.90  335.49  335.65  335.64\n",
       "2017-11-23  334.80  334.51  334.66  334.65\n",
       "2017-11-24  335.60  335.44  335.58  335.58\n",
       "2017-11-27  329.25  329.53  329.66  329.65\n",
       "2017-11-28  331.05  330.99  331.11  331.10\n",
       "2017-11-29  331.05  330.68  330.79  330.78\n",
       "2017-11-30  325.60  325.25  325.35  325.34\n",
       "2017-12-01  325.20  324.78  324.87  324.87\n",
       "2017-12-04  328.35  328.77  328.85  328.84\n",
       "2017-12-05  329.95  329.61  329.68  329.67\n",
       "2017-12-06  325.00  324.52  324.58  324.57\n",
       "2017-12-07  324.05  323.59  323.64  323.64\n",
       "2017-12-08  324.75  324.68  324.72  324.72\n",
       "2017-12-11  324.85  325.09  325.12  325.11\n",
       "2017-12-12  323.80  324.07  324.09  324.08\n",
       "2017-12-13  326.20  326.18  326.19  326.19\n",
       "2017-12-14  327.65  324.74  324.74  324.74\n",
       "\n",
       "[69 rows x 4 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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