├── .qrignore
├── README.md
├── global_market_profiles
    ├── Introduction.ipynb
    ├── Sectors.ipynb
    ├── Primary-vs-Consolidated.ipynb
    └── Shortable-Shares.ipynb
└── LICENSE.txt


/.qrignore:
--------------------------------------------------------------------------------
1 | README.md
2 | LICENSE.txt
3 | 


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/README.md:
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 1 | # global-market-profiles
 2 | 
 3 | Comparative analysis of stock market characteristics for 17 countries, including number of listings, short sale availability, volatility, distribution of sectors, etc.
 4 | 
 5 | ## Clone in QuantRocket
 6 | 
 7 | CLI:
 8 | 
 9 | ```shell
10 | quantrocket codeload clone 'global-market-profiles'
11 | ```
12 | 
13 | Python:
14 | 
15 | ```python
16 | from quantrocket.codeload import clone
17 | clone("global-market-profiles")
18 | ```
19 | 
20 | ## Browse in GitHub
21 | 
22 | Start here: [global_market_profiles/Introduction.ipynb](global_market_profiles/Introduction.ipynb)
23 | 
24 | ***
25 | 
26 | Find more code in QuantRocket's [Codeload Library](https://www.quantrocket.com/code/)
27 | 


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/global_market_profiles/Introduction.ipynb:
--------------------------------------------------------------------------------
 1 | {
 2 |  "cells": [
 3 |   {
 4 |    "cell_type": "markdown",
 5 |    "metadata": {},
 6 |    "source": [
 7 |     "<a href=\"https://www.quantrocket.com\"><img alt=\"QuantRocket logo\" src=\"https://www.quantrocket.com/assets/img/notebook-header-logo.png\"></a><br>\n",
 8 |     "<a href=\"https://www.quantrocket.com/disclaimer/\">Disclaimer</a>"
 9 |    ]
10 |   },
11 |   {
12 |    "cell_type": "markdown",
13 |    "metadata": {},
14 |    "source": [
15 |     "# Global Market Profiles\n",
16 |     "\n",
17 |     "These notebooks provide comparative analysis of stock market characteristics for 17 countries, including number of listings, short sale availability, volatility, distribution of sectors, and more."
18 |    ]
19 |   },
20 |   {
21 |    "cell_type": "markdown",
22 |    "metadata": {},
23 |    "source": [
24 |     "## Prerequisites\n",
25 |     "\n",
26 |     "The notebooks utilize global end-of-day equities data for a variety of exchanges. Data collection is not covered by this tutorial."
27 |    ]
28 |   },
29 |   {
30 |    "cell_type": "markdown",
31 |    "metadata": {},
32 |    "source": [
33 |     "* [Listings Per Country](Num-Listings.ipynb)\n",
34 |     "* [Short Sale Availability by Country](Shortable-Shares.ipynb)\n",
35 |     "* [Most Volatile Countries](Volatility.ipynb)\n",
36 |     "* [Primary Exchange vs Consolidated Prices](Primary-vs-Consolidated.ipynb)\n",
37 |     "* [Sectors by Country](Sectors.ipynb)"
38 |    ]
39 |   }
40 |  ],
41 |  "metadata": {
42 |   "kernelspec": {
43 |    "display_name": "Python 3.9",
44 |    "language": "python",
45 |    "name": "python3"
46 |   },
47 |   "language_info": {
48 |    "codemirror_mode": {
49 |     "name": "ipython",
50 |     "version": 3
51 |    },
52 |    "file_extension": ".py",
53 |    "mimetype": "text/x-python",
54 |    "name": "python",
55 |    "nbconvert_exporter": "python",
56 |    "pygments_lexer": "ipython3",
57 |    "version": "3.9.7"
58 |   }
59 |  },
60 |  "nbformat": 4,
61 |  "nbformat_minor": 4
62 | }
63 | 


--------------------------------------------------------------------------------
/LICENSE.txt:
--------------------------------------------------------------------------------
 1 | Apache License
 2 | Version 2.0, January 2004
 3 | http://www.apache.org/licenses/
 4 | 
 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
 6 | 
 7 | 1. Definitions.
 8 | 
 9 | "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.
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68 | 


--------------------------------------------------------------------------------
/global_market_profiles/Sectors.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "<a href=\"https://www.quantrocket.com\"><img alt=\"QuantRocket logo\" src=\"https://www.quantrocket.com/assets/img/notebook-header-logo.png\"></a><br>\n",
  8 |     "<a href=\"https://www.quantrocket.com/disclaimer/\">Disclaimer</a>"
  9 |    ]
 10 |   },
 11 |   {
 12 |    "cell_type": "markdown",
 13 |    "metadata": {},
 14 |    "source": [
 15 |     "***\n",
 16 |     "[Global Market Profiles](Introduction.ipynb) › Sectors by Country\n",
 17 |     "***"
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "markdown",
 22 |    "metadata": {},
 23 |    "source": [
 24 |     "# Sectors by Country\n",
 25 |     "\n",
 26 |     "This notebooks looks at the distribution of sectors for different countries."
 27 |    ]
 28 |   },
 29 |   {
 30 |    "cell_type": "code",
 31 |    "execution_count": 1,
 32 |    "metadata": {},
 33 |    "outputs": [],
 34 |    "source": [
 35 |     "countries = (\n",
 36 |     "    # North America\n",
 37 |     "    (\"usa-stk\", \"United States\"),\n",
 38 |     "    (\"canada-stk\", \"Canada\"),\n",
 39 |     "    (\"mexico-stk\", \"Mexico\"),\n",
 40 |     "    \n",
 41 |     "    # Asia\n",
 42 |     "    (\"australia-stk\", \"Australia\"),\n",
 43 |     "    (\"japan-stk\", \"Japan\"),\n",
 44 |     "    (\"hongkong-stk\", \"Hong Kong\"),\n",
 45 |     "    (\"singapore-stk\", \"Singapore\"),\n",
 46 |     "    \n",
 47 |     "    # Europe\n",
 48 |     "    (\"spain-stk\", \"Spain\"),\n",
 49 |     "    (\"netherlands-stk\", \"Netherlands\"),\n",
 50 |     "    (\"uk-stk\", \"United Kingdom\"),\n",
 51 |     "    (\"germany-stk\", \"Germany\"),\n",
 52 |     "    (\"france-stk\", \"France\"),\n",
 53 |     "    (\"belgium-stk\", \"Belgium\"),\n",
 54 |     "    (\"swiss-stk\", \"Switzerland\"),\n",
 55 |     "    (\"austria-stk\", \"Austria\"),\n",
 56 |     "    (\"sweden-stk\", \"Sweden\"),\n",
 57 |     "    (\"italy-stk\", \"Italy\"),\n",
 58 |     ")"
 59 |    ]
 60 |   },
 61 |   {
 62 |    "cell_type": "markdown",
 63 |    "metadata": {},
 64 |    "source": [
 65 |     "Get a DataFrame of countries (columns) and sectors (index):"
 66 |    ]
 67 |   },
 68 |   {
 69 |    "cell_type": "code",
 70 |    "execution_count": 2,
 71 |    "metadata": {},
 72 |    "outputs": [],
 73 |    "source": [
 74 |     "from quantrocket.master import download_master_file\n",
 75 |     "import io\n",
 76 |     "import pandas as pd\n",
 77 |     "\n",
 78 |     "all_countries = {}\n",
 79 |     "\n",
 80 |     "for universe, country in countries:\n",
 81 |     "    f = io.StringIO()\n",
 82 |     "    download_master_file(f, universes=universe, fields=\"ibkr_Sector\")\n",
 83 |     "    securities = pd.read_csv(f)\n",
 84 |     "    all_countries[country] = securities.groupby(securities.ibkr_Sector).Sid.count()\n",
 85 |     "    \n",
 86 |     "sectors = pd.concat(all_countries).unstack().T"
 87 |    ]
 88 |   },
 89 |   {
 90 |    "cell_type": "markdown",
 91 |    "metadata": {},
 92 |    "source": [
 93 |     "Convert to percentages:"
 94 |    ]
 95 |   },
 96 |   {
 97 |    "cell_type": "code",
 98 |    "execution_count": 3,
 99 |    "metadata": {},
100 |    "outputs": [],
101 |    "source": [
102 |     "sizes = sectors.sum()\n",
103 |     "sectors = sectors / sizes\n",
104 |     "sectors = sectors.round(3) * 100"
105 |    ]
106 |   },
107 |   {
108 |    "cell_type": "markdown",
109 |    "metadata": {},
110 |    "source": [
111 |     "Transpose:"
112 |    ]
113 |   },
114 |   {
115 |    "cell_type": "code",
116 |    "execution_count": 4,
117 |    "metadata": {},
118 |    "outputs": [],
119 |    "source": [
120 |     "sectors = sectors.fillna(0).T"
121 |    ]
122 |   },
123 |   {
124 |    "cell_type": "markdown",
125 |    "metadata": {},
126 |    "source": [
127 |     "Drop minor sectors to simplify plot:"
128 |    ]
129 |   },
130 |   {
131 |    "cell_type": "code",
132 |    "execution_count": 5,
133 |    "metadata": {},
134 |    "outputs": [],
135 |    "source": [
136 |     "sectors = sectors.drop([\"Funds\",\"Government\", \"Diversified\"], axis=1)"
137 |    ]
138 |   },
139 |   {
140 |    "cell_type": "markdown",
141 |    "metadata": {},
142 |    "source": [
143 |     "Plot:"
144 |    ]
145 |   },
146 |   {
147 |    "cell_type": "code",
148 |    "execution_count": 6,
149 |    "metadata": {},
150 |    "outputs": [],
151 |    "source": [
152 |     "import matplotlib.pyplot as plt\n",
153 |     "import seaborn as sns\n",
154 |     "sns.set(palette=sns.color_palette(\"hls\", n_colors=len(sectors.columns)))"
155 |    ]
156 |   },
157 |   {
158 |    "cell_type": "code",
159 |    "execution_count": 7,
160 |    "metadata": {},
161 |    "outputs": [
162 |     {
163 |      "data": {
164 |       "image/png": 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\n",
165 |       "text/plain": [
166 |        "<Figure size 1152x432 with 1 Axes>"
167 |       ]
168 |      },
169 |      "metadata": {},
170 |      "output_type": "display_data"
171 |     }
172 |    ],
173 |    "source": [
174 |     "ax = sectors.plot(kind=\"bar\", stacked=True, title=\"Sectors by country\", figsize=(16,6))\n",
175 |     "ax.set_ylabel(\"Percentage of total\")\n",
176 |     "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))"
177 |    ]
178 |   },
179 |   {
180 |    "cell_type": "markdown",
181 |    "metadata": {},
182 |    "source": [
183 |     "***\n",
184 |     "\n",
185 |     "[Back to Introduction](Introduction.ipynb)"
186 |    ]
187 |   }
188 |  ],
189 |  "metadata": {
190 |   "kernelspec": {
191 |    "display_name": "Python 3.9",
192 |    "language": "python",
193 |    "name": "python3"
194 |   },
195 |   "language_info": {
196 |    "codemirror_mode": {
197 |     "name": "ipython",
198 |     "version": 3
199 |    },
200 |    "file_extension": ".py",
201 |    "mimetype": "text/x-python",
202 |    "name": "python",
203 |    "nbconvert_exporter": "python",
204 |    "pygments_lexer": "ipython3",
205 |    "version": "3.9.7"
206 |   }
207 |  },
208 |  "nbformat": 4,
209 |  "nbformat_minor": 4
210 | }
211 | 


--------------------------------------------------------------------------------
/global_market_profiles/Primary-vs-Consolidated.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "<a href=\"https://www.quantrocket.com\"><img alt=\"QuantRocket logo\" src=\"https://www.quantrocket.com/assets/img/notebook-header-logo.png\"></a><br>\n",
  8 |     "<a href=\"https://www.quantrocket.com/disclaimer/\">Disclaimer</a>"
  9 |    ]
 10 |   },
 11 |   {
 12 |    "cell_type": "markdown",
 13 |    "metadata": {},
 14 |    "source": [
 15 |     "***\n",
 16 |     "[Global Market Profiles](Introduction.ipynb) › Primary Exchange vs Consolidated Prices\n",
 17 |     "***"
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "markdown",
 22 |    "metadata": {},
 23 |    "source": [
 24 |     "# Primary vs Consolidated\n",
 25 |     "\n",
 26 |     "The purpose of this notebook is to see how different primary exchange prices vs consolidated prices are, and what percentage of trading occurs on the primary exchange."
 27 |    ]
 28 |   },
 29 |   {
 30 |    "cell_type": "code",
 31 |    "execution_count": 1,
 32 |    "metadata": {},
 33 |    "outputs": [],
 34 |    "source": [
 35 |     "from quantrocket import get_prices\n",
 36 |     "import pandas as pd\n",
 37 |     "import seaborn as sns\n",
 38 |     "import matplotlib.pyplot as plt\n",
 39 |     "sns.set()"
 40 |    ]
 41 |   },
 42 |   {
 43 |    "cell_type": "code",
 44 |    "execution_count": 2,
 45 |    "metadata": {},
 46 |    "outputs": [],
 47 |    "source": [
 48 |     "def compare_dbs(primary_db, consolidated_db, start_date, universes=None):\n",
 49 |     "    \"\"\"\n",
 50 |     "    Compare the primary and consolidated db, and return a tuple of scalars: \n",
 51 |     "    primary volume as a percentage of consolidated volume, how often the \n",
 52 |     "    closing price differs by more than 1%, and how often the opening price\n",
 53 |     "    differs by more than 1%.\n",
 54 |     "    \"\"\"\n",
 55 |     "    prices_p = get_prices(primary_db, universes=universes, fields=[\"Close\",\"Open\",\"Volume\"], start_date=start_date)\n",
 56 |     "    prices_c = get_prices(consolidated_db, universes=universes, fields=[\"Close\",\"Open\",\"Volume\"], start_date=start_date)\n",
 57 |     "    shared_columns = prices_p.columns.intersection(prices_c.columns)\n",
 58 |     "    prices_p = prices_p[shared_columns]\n",
 59 |     "    prices_c = prices_c[shared_columns]\n",
 60 |     "    \n",
 61 |     "    volumes_p = prices_p.loc[\"Volume\"].sum(axis=1)\n",
 62 |     "    volumes_c = prices_c.loc[\"Volume\"].sum(axis=1)\n",
 63 |     "    volumes_p.name = \"primary\"\n",
 64 |     "    volumes_c.name = \"consolidated\"\n",
 65 |     "    primary_volume_pct = (1 - (volumes_c-volumes_p)/volumes_c)\n",
 66 |     "    # primary volume sometimes exceeds consolidated volume for Japan stocks, which doesn't make sense; ignore those\n",
 67 |     "    primary_volume_pct = primary_volume_pct.where(primary_volume_pct <= 1)\n",
 68 |     "    primary_volume_pct = primary_volume_pct.mean()\n",
 69 |     "    \n",
 70 |     "    closes_p = prices_p.loc[\"Close\"]\n",
 71 |     "    closes_c = prices_c.loc[\"Close\"]\n",
 72 |     "    closes_pct_diff = ((closes_p-closes_c).abs()/closes_p.where(closes_p > 0))\n",
 73 |     "    closes_differ_alot = (closes_pct_diff > 0.01).astype(int)\n",
 74 |     "    closes_differ_alot = (closes_differ_alot.stack().sum()/closes_differ_alot.stack().count())\n",
 75 |     "    \n",
 76 |     "    opens_p = prices_p.loc[\"Open\"]\n",
 77 |     "    opens_c = prices_c.loc[\"Open\"]\n",
 78 |     "    opens_pct_diff = ((opens_p-opens_c).abs()/opens_p.where(opens_p > 0))\n",
 79 |     "    opens_differ_alot = (opens_pct_diff > 0.01).astype(int)\n",
 80 |     "    opens_differ_alot = (opens_differ_alot.stack().sum()/opens_differ_alot.stack().count())\n",
 81 |     "\n",
 82 |     "    return primary_volume_pct, closes_differ_alot, opens_differ_alot"
 83 |    ]
 84 |   },
 85 |   {
 86 |    "cell_type": "markdown",
 87 |    "metadata": {},
 88 |    "source": [
 89 |     "Countries for which numbers should be run:"
 90 |    ]
 91 |   },
 92 |   {
 93 |    "cell_type": "code",
 94 |    "execution_count": 3,
 95 |    "metadata": {},
 96 |    "outputs": [],
 97 |    "source": [
 98 |     "countries = (\n",
 99 |     "    (\"usa-stk-1d\", \"United States\"),\n",
100 |     "    (\"canada-stk-1d\", \"Canada\"),\n",
101 |     "    (\"australia-stk-1d\", \"Australia\"),\n",
102 |     "    (\"japan-stk-1d\", \"Japan\"),\n",
103 |     "    (\"spain-stk-1d\", \"Spain\"),\n",
104 |     "    (\"netherlands-stk-1d\", \"Netherlands\"),\n",
105 |     "    (\"uk-stk-1d\", \"United Kingdom\"),\n",
106 |     "    (\"germany-stk-1d\", \"Germany\"),\n",
107 |     "    (\"france-stk-1d\", \"France\"),\n",
108 |     "    (\"belgium-stk-1d\", \"Belgium\"),\n",
109 |     "    (\"swiss-stk-1d\", \"Switzerland\"),\n",
110 |     ")"
111 |    ]
112 |   },
113 |   {
114 |    "cell_type": "markdown",
115 |    "metadata": {},
116 |    "source": [
117 |     "Countries where there is no difference between primary and consolidated but which should still be included in the chart:"
118 |    ]
119 |   },
120 |   {
121 |    "cell_type": "code",
122 |    "execution_count": 4,
123 |    "metadata": {},
124 |    "outputs": [],
125 |    "source": [
126 |     "countries_no_difference = (\n",
127 |     "    \"Austria\",\n",
128 |     "    \"Sweden\",\n",
129 |     "    \"Hong Kong\",\n",
130 |     "    \"Singapore\",\n",
131 |     "    \"Italy\",\n",
132 |     "    \"Mexico\",\n",
133 |     ")"
134 |    ]
135 |   },
136 |   {
137 |    "cell_type": "markdown",
138 |    "metadata": {},
139 |    "source": [
140 |     "Run numbers for each country:"
141 |    ]
142 |   },
143 |   {
144 |    "cell_type": "code",
145 |    "execution_count": 5,
146 |    "metadata": {},
147 |    "outputs": [],
148 |    "source": [
149 |     "primary_volume_pct = {}\n",
150 |     "prices_differ_alot = {}\n",
151 |     "start_date = \"2018-01-01\"\n",
152 |     "\n",
153 |     "for db_basename, country in countries:\n",
154 |     "    volume, closes, opens = compare_dbs(primary_db=db_basename+\"-p\", consolidated_db=db_basename, start_date=start_date)\n",
155 |     "    primary_volume_pct[country] = volume\n",
156 |     "    prices_differ_alot[country] = {\"Open\":opens, \"Close\":closes}\n",
157 |     "    \n",
158 |     "for country in countries_no_difference:\n",
159 |     "    primary_volume_pct[country] = 1\n",
160 |     "    prices_differ_alot[country] = {\"Open\":0, \"Close\":0}"
161 |    ]
162 |   },
163 |   {
164 |    "cell_type": "markdown",
165 |    "metadata": {},
166 |    "source": [
167 |     "Generate plots. First, prices:"
168 |    ]
169 |   },
170 |   {
171 |    "cell_type": "code",
172 |    "execution_count": 6,
173 |    "metadata": {},
174 |    "outputs": [
175 |     {
176 |      "data": {
177 |       "image/png": 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1UNX15NcRcU1W47LU0Lq9eynnZ2pLkWdVyphZIzVYvu+l3Iz3WpXSbfIB+unu1ioz/8YLXYLeS2kFs2y1zdf2Lle1jlqFoY9lqPN5IuXGeufMfDwi9qe0CBlI77X05b4vRMQMYOWI6Ggp2qzK4IXX/pZvbQU31DX/igHm35aZrxpk3b6ef99FxJKULma9770zKS2w1qfk8qcvXn2BzHedVF2wlmX+c9p6/HcBV2bmljW3P9zP/KOqddarWtm8mxd3LRxVEfESSpfmmZRxm+7KMjbPNZTumZLU1hyDR5JG39XAv4BPRsSUKAO7bkc11kF1Q/UU5ZvZ31RN6x+gtA4ZqMAz6Db78QDw8qpLD1VR6LvAf1XfmhIRK8fgY0QMZZeIWLu6gfsCcF5LS4TRNJVyszoL6IqIz1Fa8AzldMp4DdtTbpgG8m3gy1XhhYjojoh3VT8vXq17GLAH5eawd4DOC4EVI2L/KOOBTK26agzlpZSbmlnVPvagjJMxpKp705+AIyNi0Yj4N8p10OtMYLuIeEdEdEbE4hHxlogY7CZ/n4h4eZRxSA4Dzq0TC2UcoPuAoyPipdW+Nqte+zbw6apgQkQsHWX8kv6cB2wbEZtX1+sXWMC/TxbkOo+IbSPilVUB4zFK660Fuo6rrm6/A46q8rEepYVMnULXUAbL9znAARGxRlUs6B2Ta8in6kXELhHRXeWut6XGPMpYPNtExBZRxgA7iNLq4XdDbHKo8zmVkucnogzg+x991n+AMo5Qr+8Ce0fEG6I82eqlEbFNlDGwfk/5bPh4RHRFxHspXdkGs3y1/JTqmnwNZXyhOr4HHBwRG1WxvLL63Pgj8FhEfCoiXlK999aNiNcPsq13tuToi8DVvV0lq25C11AK0z+uutaNhrOBPSJigyiD7n+l2u/tAyx/IbBWROxa5WtKRLw+Xhi/qa++524oUykDUv8zyvhhhwxj3RepPq8XqyYXi/nHaev1GUo3vHspY2pFRKxAGb/q1pHsX5ImAgs8kjTKqrFRtqd8Q/gQZfyU3TLzlpbFrqR0ibqzZbqD8s32gm6z1a8oYyTcHxEPVfM+RRnv4A8R8RhlgOB+B8ep6QzK01ruBxanjHnThEuAiymtle6gtHQaqvsXVYuc54DrBrmBgdL94eeULjqPU8Yg6S3UHAXcnZknVmO27AJ8KSJeVbXQ2JJSYLmf8nSvt9aI6ybKQNC/p9wQvZby5J66PkAZnPZhymDK51JuvHsLDO+iFGpmUfJ0CIP/vj+bMnj3rdW/L9UJoirmbUcZyPhOSou0narXzqcMdvyD6lr7C+Xa7W87N1LGOTqbUsCYXW1rQQ33On9VtcwTlHPyrRzgqWM17Uzpencv5QleR/SOYzMSg+WbMgjxGZQun7dR3iP79bOZ/mxNGbvlCcp74f2Z+XRmJuV6/2/KZ852lAGmnx0izqHO58HA/wEepxRv+hYUj6SMs/PPiHhflifP7UVp2TGbcm53r/b1LKXV0e7VazsBPxnieK+mnPOHKE9b2yGrp+0NJcvYWV+uju1xSsuaZVrOzQaU/D9EKQYtPcjmzqaMN/MIZYDkD/R5/TTKZ8Nwu0MNFv/lwGcpTy67j9IaacAuSdVn3FbVMvdSPue+ygtFlL6OB3aIiNkRMdgTxHp9nvK0skcpg8MPde6G8hTlfQxwCy90eQRKJYdyPP8NkJn3UR6ZfiPl99enkaQ219HTMyot6CVJk0iUxwk//+jgiSoifgWcPdHjHImIOBe4JcvT1Ia77u2Up4L9cohFpbYX1Vhpmbn5eMcylIh4M6VF3uoDjMsmSdKLOAaPJGmhVHWP2JDSomWhUR3XI5SWAltRjm84gwJLmsCqLnGfAL5ncUeSNBwWeCRJC50ojxZ/N/CJPk80WhisSOnKsCyl68t/ZGa/XfsktZdqfJs/UZ7utMcQi0uSNB+7aEmSJEmSJLU5B1mWJEmSJElqcxOqi9asWY+Pa3OiadOWYPbsJ8czhHFnDswBmAMwB5P9+MEcgDkAcwDmAMwBmAMwB2AOJvvxgzmAiZGD7u6pHf3NtwVPi66uzvEOYdyZA3MA5gDMwWQ/fjAHYA7AHIA5AHMA5gDMAZiDyX78YA5gYufAAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW2ua7wDkCRJkiRJqmO7k68b1e1d8OENay338MMP8Y1vHMtf/3oLnZ1drLjiSnz84wdx+OGHcMYZPxzVmBaUBR5JkiRJkqQB9PT0cNhhhzBz5jZ861snMGvW4/ztb8ns2Y+Md2jzscAjSZIkSZI0gOuu+xNdXV28+907PD/vVa8K7rvv3uenn3nmGY499mhuueUmOjs72W+/A9lww4259dZ/cNRRn2fOnLn09DzHl770NVZZZVUuueQizjvvB8yZM5e1116Hgw46lM7OzhHFaYFHkiRJkiRpALfe+g8iXj3oMj/5yY8AOP30c7njjts54IB9OOecn/Czn/2YHXfcma22msmcOXN47rl53H77bVx++WWceOIpdHV1ccwxR3PppRczc+a2I4rTAo8kSZIkSdII/PnP17PDDjsBsNpqq7Piiitx1113ss4663H66afw4IMPMGPG21hllVW59to/knkze+65GwDPPPM006ZNG3EMjRZ4IuIAYE+gB/h/wB6Z+XST+5QkjXzwuT8cOmOUIpEkSZLa2xprrMkVV1w+xFI9/c7daqutWWeddfnd737LgQfux6GHfoaenh5mztyWvffed1TjbOwx6RGxMvBxYOPMXBfoBN7f1P4kSZIkSZJG20YbvZ5nn32Wn//8/Ofn3Xzzjdx//33PT6+//uu49NKLAbjzzjt44IH7WXXV1bjnnruZPn1ldtzx/Wy++Zv5xz/+xkYbbcIVV1z+/CDNjz326HzbWlBNd9HqAl4SEXOAJYB7h1hekiRJkiSpX3Ufaz6aOjo6OOqoYzj++GM555zT6eycwkorlcek93rPe3bkmGOOYrfddqKzs5PDDz+SRRddlF/96jIuueRiurq6WGaZZdljjz1Zaqml2Wuv/+CAA/alp+c5Oju7OPDAT7HiiiuNKM7GCjyZeU9EHAPcCTwFXJqZlza1P0mSJEmSpCYst1w3X/zi0XR3T2XWrMefn3/GGT8EYLHFFuPww4980Xq77roHu+66x4vmb7HFVmyxxVajGmNHT0///cRGKiKmAT8GdgL+CfwIOC8zzxxonblz5/V0dY3ssWCSJNj06CtHtL5j8EiSJEkTVkd/M5vsovV24LbMnAUQET8B3ggMWOCZPfvJBsMZWt9K3GRkDswBmAMwB8CkP36vAXMA5gDMAZgDMAdgDsAcTPbjB3MAEyMH3d1T+53fZIHnTmDTiFiC0kVrC+BPDe5PkiRJkiRpUmrsKVqZeTVwHnAd5RHpiwAnNbU/SZIkSZKkyarRp2hl5hHAEU3uQ5IkSZIkabJrrAWPJEmSJEmSxkajLXgkSZIkSZJGy5X3PjGq25sxfclayz344AMcd9xXueuuO5gzZy5vfOOb2GefTzBlypRRjWckbMEjSZIkSZI0gJ6eHg4//BDe9Ka3cOmll3LOOT/hqaee5KSTvjXeoc3HFjySJEmSJEkDuPbaa1h00cXYZpvtAejs7OTjHz+QHXd8FyutNJ0//vH3PPvsHO677x623HJrPvShjwBwySUXcd55P2DOnLmsvfY6HHTQoXR2drLllm9ihx3ez+9+91sWW2wxjj76WJZZZtkRx2kLHkmSJEmSpAHcdtutRLx6vnkvfemSrLDCCsybN4+bb76RI474Iqeeeja//vUvueWWm7j99tu4/PLLOPHEUzj11LNZZJFOLr30YgCeeuop1lnntZx22jlssMHr+PnPzx+VOG3BI0mSJEmSNICenh46Ojr6mQ8dHbDxxm9g6aVfBsCMGW/jz3++ns7OTjJvZs89dwPgmWeeZtq0aQBMmTKFzTZ7EwARr+Gaa64elTgt8EiSJEmSJA1gjTXW5MorfzXfvH/96wkefPABFlmks5/iTwc9PT3MnLkte++974u219XV9fw6iyyyCPPmzRuVOO2iJUmSJEmSNICNN96Ep59+mosvvhCAefPmccIJX2fmzG1ZfPHFueaaq3nssUd55pmnueqqK1hvvfXZaKNNuOKKy5k9+xEAHnvsUe6//75G47QFjyRJkiRJagt1H2s+mjo6OvjKV/6TY4/9Kmee+X3mzJnLv/3bZnz0o/vwy19ewnrrbcAXv/g57r77Lrbccmte/eq1Adhrr//ggAP2pafnOTo7uzjwwE+x4oorNRanBR5J0oucd8PIv10Yj1++kiRJUhNWWGFFvva1/6K7eyqzZj0+32vTpk3jwAOPftE6W2yxFVtssdWL5l922VXP//zWt76dt7717aMSo120JEmSJEmS2pwteCRJkiRJkhbAO9+5He9853bjHQZgCx5JkiRJkqS2Z4FHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktqcBR5JkiRJkqQ2Z4FHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktqcBR5JkiRJkqQ2Z4FHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktqcBR5JkiRJkqQ2Z4FHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktpcV1MbjogAzm2ZtSbwucz8elP7lCRJkiRJmowaK/BkZgIbAEREJ3APcH5T+5MkSZIkSZqsxqqL1hbAPzLzjjHanyRJkiRJ0qTR0dPT0/hOIuIU4LrMPGGw5ebOndfT1dXZeDyStLDb9OgrR7T+wTPXGnEMO6y/0oi3IUmSJOlFOvqb2VgXrV4RsSiwPfDpoZadPfvJpsMZVHf3VGbNenxcYxhv5sAcgDkAczAa2j1/XgPmAMwBmAMwB2AOwByAOZjsxw/mACZGDrq7p/Y7fyy6aM2ktN55YAz2JUmSJEmSNOmMRYFnZ+CcMdiPJEmSJEnSpNRogScilgC2BH7S5H4kSZIkSZIms0bH4MnMJ4Flm9yHJEmSJEnSZDdWj0mXJEmSJElSQyzwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5oYs8ETEgRGxdPXzGRFxS0Rs1XxokiRJkiRJqqNOC57dM/PRiHgrsDzwIeArzYYlSZIkSZKkurpqLDOv+v+twFmZ+buIqNW1KyJeBnwPWBfoAT6Umb9foEglSZIkSZLUrzqFmqci4nDgA8ClEdEBLFpz+8cD/5OZrwbWB25esDAlSZIkSZI0kFpdtIBu4JDMvB9YEzhrqJUiYingzcDJAJn5bGb+c8FDlSRJkiRJUn86enp6ai0YEd2ZOavuhiNiA+Ak4CZK651rgU9k5r8GWmfu3Hk9XV2ddXchSRrApkdfOaL1D5651ohj2GH9lUa8DUmSJEkv0tHfzCHH4ImINwA/pLT2WSUiNgY+kpkfGWLVLmBDYL/MvDoijgcOBT470AqzZz85VDiN6u6eyqxZj49rDOPNHJgDMAdgDkZDu+fPa8AcgDkAcwDmAMwBmAMwB5P9+MEcwMTIQXf31H7n1+midRwwE3gIIDP/BGxWY727gbsz8+pq+jxKwUeSJEmSJEmjqE6BZ9HMvKnPvGeHWqkar+euiIhq1haU7lqSJEmSJEkaRXUek/5MRCxJecw5EbE28HTN7e8HnBURiwK3AnssUJSSJEmSJEkaUJ0Cz5eBS4HpEXEqsDWwS52NZ+b1wMYLHJ0kSZIkSZKGNGSBJzMvjogE3kEZqflLmfn3xiOTJEmSJElSLXWeovXJzPwokV9UAAAgAElEQVQacGI/8yRJkiRJkjTO6gyy/P6a8yRJkiRJkjQOBmzBExFbAltRxt5pba2zdONRSZIkSZIkqbbBWvA8CzxBeXrWv1r+3QK8t/nQJEmSJEmSVMeALXgy80rgyoj4cWb+ZQxjkiRJkiRJ0jDUeYrWXyJiK2ADYPGW+V9oMjBJkiRJkiTVU+cpWkcDrwfWAX4GvAv4ZcNxSZIkSZIkqaY6T9HaBngH8EBmfhTYCFiy0agkSZIkSZJUW50Cz9OZORfoiYgpmXkPsErDcUmSJEmSJKmmIbtoAY9HxBLA74DTIuI+YG6zYUmSJEmSJKmuOi14dgbmAQcDN1Eem75jk0FJkiRJkiSpvjpP0XqgZfJLDcYiSZIkSZKkBTBggScirqG01ulXZm7SSESSJEmSJEkalsFa8Bxc/b8N8Grg5Gp6D+C6JoOSJEmSJElSfQMWeDLzSoCIOBJ4W2b2VNMXAr8EvjAWAUqSJEmSJGlwdQZZfjmweMv0YsDKzYQjSZIkSZKk4arzmPRzgd9HxLnV9PuqeZIkSZIkSZoAhmzBk5mfAT4DLAd0A5/JzM82HZgkSZIkSZLqqdOCh8y8ELiw4VgkSZIkSZK0AOqMwSNJkiRJkqQJzAKPJEmSJElSm7PAI0mSJEmS1OYGHIMnItYebMXMvGn0w5EkSZIkSdJwDTbI8i8Gea0HWHOUY5EkSZIkSdICGLDAk5lrjGUgkiRJkiRJWjC1HpMOEBHLA4v3TmfmnY1EJEmSJEmSpGEZssATEW8DTgNWAOYBiwIPA8vXWPd24PFqvbmZufEIYpUkSZIkSVI/6rTg+U9gC+BcYENgT2DVYezjrZn50ALEJkmSJEmSpBpqPSY9M/8KTMnMnsz8LjCj2bAkSZIkSZJUV50WPHOq/++JiO2A24GX19x+D3BpRPQA38nMkwZbeNq0Jejq6qy56WZ0d08d1/1PBObAHEB752DTo68c8Tb+cOiMts7BRLAw5G9hOIaRMgfmAMwBmAMwB2AOwBxM9uMHcwATNwd1CjzHR8Q04DPAOcDSwAE1t79ZZt5bDdB8WUTckpm/GWjh2bOfrLnZZnR3T2XWrMfHNYbxZg7MAZiDXuZgZNo9f74PzAGYAzAHYA7AHIA5AHMw2Y8fzAFMjBwMVGCqU+D5RWY+BlwDvBIgIpaqs9PMvLf6/8GIOB/YBBiwwCNJkiRJkqThqzMGzxU1580nIl4aEVN7fwa2Av4ynOAkSZIkSZI0tAFb8EREF+WR6ItExEuAjuqlpYElamx7BeD8iOjdz9mZ+T8jC1eSJEmSJEl9DdZF63DgCMpAyf9qmf8YcOxQG87MW4H1RxSdJEmSJEmShjRggSczPw98PiJOyMx9xzAmSZIkSZIkDcOQgyxn5r4RsSywKaU1zx8y85HGI5MkSZIkSVItQw6yHBHvAG4B9qc8Hv3miNiy6cAkSZIkSZJUT53HpH8ZeHNm3gwQEa8GzgQuazIwSZIkSZIk1VPnMelTeos7AJl5CzCluZAkSZIkSZI0HHUKPLMiYvfeiYj4IDCrsYgkSZIkSZI0LHW6aO0NnBkRJ1bT1wO7NBeSJEmSJEmShqPOU7T+DmwaEUsCHZn5ePNhSZIkSZIkqa46T9H6LUBmPtFb3OmdJ0mSJEmSpPFXZwyeJVonIqITWKaZcCRJkiRJkjRcA3bRiohDgE8CS0fEgy0vLQGc1XRgkiRJkiRJqmewMXhOAn4EnADs0zL/scyc3WhUkiRJkiRJqm3AAk9mPgo8Cmw7duFIkiRJkiRpuOqMwSNJkiRJkqQJzAKPJEmSJElSmxuwwBMRB1X/bzZ24UiSJEmSJGm4BmvB84Hq//8ei0AkSZIkSZK0YAZ7itZTEXEBsHpE/LDvi5n5vubCkiRJkiRJUl2DFXi2A7YE1gN+MTbhSJIkSZIkabgGe0z6I8C5EfFAZl4xdiFJkiRJkiRpOAZrwdPryoj4KPB2oAe4DPheZvY0GpkkSZIkSZJqqVPg+SqwIfD9avqDwKuATzYVlCRJkiRJkuqrU+DZGtgwM+cCVAMuX4sFHkmSJEmSpAlhsMek9+qgdM3q1VPNkyRJkiRJ0gRQpwXPJcDFEXEqpbizO/A/DcYkSZIkSZKkYahT4Pkk8BHgvZSWO+cDJzUZlCRJkiRJkuobssCTmc8B367+SZIkSZIkaYKp04JnRCKiE/gTcE9mbtv0/iRJkiRJkiabOoMsj9QngJvHYD+SJEmSJEmTUqMFnoh4ObAN8L0m9yNJkiRJkjSZ1eqiFRFbAK/JzBMiYgVg6cz8a41Vv04ZpHlqnf1Mm7YEXV2ddRZtTHd3rVAXaubAHIA5AHMwUgtD/haGYxgpc2AOwByAOQBzAOYAzMFkP34wBzBxczBkgSciDgXeCawEnABMAU4BNh9ivW2BBzPz2oh4S51gZs9+ss5ijenunsqsWY+PawzjzRyYAzAHvczByLR7/nwfmAMwB2AOwByAOQBzAOZgsh8/mAOYGDkYqMBUp4vWzsAWwBMAmXk3sFSN9TYDto+I24EfAG+LiDNrrCdJkiRJkqRhqFPgeSoz5/SZ1zPUSpn56cx8eWauDrwf+FVm7rIAMUqSJEmSJGkQdcbguSsiNgd6ImIR4DDgxmbDkiRJkiRJUl11Cjz7AacD6wJPAlcBHxjOTjLzCuCKYcYmSZIkSZKkGoYs8GTm/cBWEbEEsEhmPtF8WJIkSZIkSaqrzlO03tlnGuBR4C+Z+WhDcUmSJEmSJKmmOl20Pgu8HvhzNf1a4HpglYjYMzMvbCo4SZIkSZIkDa3OU7T+DrwhMzfMzA2BNwDXAm8FvtRkcJIkSZIkSRpanQLP+pl5be9EZl4HbJSZNwMdjUUmSZIkSZKkWuoUeJ6MiJ17J6qf51WTPY1EJUmSJEmSpNrqjMGzB3BGRJxCKejcBHyweqrWIU0GJ0mSJEmSpKHVeUz6zcDGETEV6MjMx1pevqyxyCRJkiRJklRLnRY8RMTSQACLV49JJzN/02BckiRJkiRJqmnIAk9E7AQcA0wD7gFeCdwAbNhsaJIkSZIkSaqjziDLhwEbAX/LzAC2Bq5uNCpJkiRJkiTVVqfAMzczH6Rq7ZOZlwHrNRqVJEmSJEmSaqszBs8zEdEB/C0i9gNuB7objUqSJEmSJEm11SnwfAZYCvgUcCKwNPCxJoOSJEmSJElSfXUKPPdm5qPAo8DbASLi1Y1GJUmSJEmSpNrqjMFzds15kiRJkiRJGgcDtuCJiOWA5YHFI+I1QEf10tLAS8cgNkmSJEmSJNUwWBetDwD7A9OBi1rmPwp8rcmgJEmSJEmSVN+ABZ7MPB44PiIOy8yvjGFMkiRJkiRJGoYhB1nOzK9ExBLAy1uXz8ybmgxMkiRJkiRJ9QxZ4ImIjwFfBWYD86rZPcCaDcYlSZIkSZKkmuo8Jv1gYN3MvKPpYCRJkiRJkjR8dR6Tfr/FHUmSJEmSpImrTgueyyLia8APgKd7ZzoGjyRJkiRJ0sRQp8CzW/X/ji3zHINHkiRJkiRpgqjzFK01xiIQSZIkSZIkLZg6Y/AQEVtExL7Vz8tHxFrNhiVJkiRJkqS66jwm/VDgncBKwAnAosApwOZDrLc48BtgsWo/52XmESMNWJIkSZIkSfOr04JnZ2AL4AmAzLwbWKrGes8Ab8vM9YENgK0jYtMFDVSSJEmSJEn9q1PgeSoz5/SZ1zPUSpnZk5lPVJNTqn9DridJkiRJkqThqfMUrbsiYnOgJyIWAQ4Dbqyz8YjoBK4FXgl8MzOvHmz5adOWoKurs86mG9PdPXVc9z8RmANzAOYAzMFILQz5WxiOYaTMgTkAcwDmAMwBmAMwB5P9+MEcwMTNQZ0Cz37A6cC6wJPAVcAudTaemfOADSLiZcD5EbFuZv5loOVnz36yzmYb0909lVmzHh/XGMabOTAHYA56mYORaff8+T4wB2AOwByAOQBzAOYAzMFkP34wBzAxcjBQganOY9LvB7aKiCWARVq6XdWWmf+MiCuArYEBCzySJEmSJEkavjpP0doVuDAzZ1fTywAzM/OsIdbrBuZUxZ2XAG8HvjoKMUuSJEmSJKlFnS5aB2fmGb0TmflIRBwMDFrgoTxW/bRqHJ5FgB9m5oULHqokSZIkDd92J1834m384dAZoxCJJDWnToGnP0OOhJyZfwZet4DblyRJkiRJUk11HpN+f0S8t3ciIv4deLC5kCRJkiRJkjQcdVrw7A/8NCK+Vk3PBd7VXEiSJEmSJEkajjoFnnuBtYEAOoBbqsefS5IkSZIkaQIYtMATER3AbzJzfeCmsQlJkiRJkiRJwzHoGDyZ2QPcGhHTxigeSZIkSZIkDVOdLlpPAP8bERdVPwOQmZ9sLCpJkiRJkiTVVqfA8/fqnyRJkiRJkiagIQs8mfn5sQhEkiRJkiRJC2bIAk9ELA8cB6yamW+OiPWAN2bmtxuPTpIkSZIkSUOq00Xru8DFwMeq6VuAMwELPJIkSZrwtjv5uhGt/4dDZ4xSJJIkNWfQp2hVVq5a68wDyMxngecajUqSJEmSJEm11SnwzG2diIiXAR3NhCNJkiRJkqThqtNF68cR8R1gakTsTumqdUqjUUmSJEmSJE0w591w34jWnzF9yVGK5MWGbMGTmf8J/Aa4Fngn8I3MPL6xiCRJkiRJkjQsg7bgiYhlgDWACzLzrLEJSZIkSZIkScMxYAueiNgJuBu4CLgzIt42ZlFJkiRJkiSptsG6aB0OvDEzVwDeA3xubEKSJEmSJEnScAxW4HkuM68HyMxfA0uNTUiSJEmSJEkajsHG4Fk0Il7DC49EX7x1OjNvajo4SZIkSZIkDW2wAs8SlPF3WvVO9wBrNhKRJEmSJEmShmXAAk9mrj6GcUiSJEmSJGkBDTYGjyRJkiRJktqABR5JkiRJkqQ2Z4FHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktqcBR5JkiRJkqQ2N+Bj0kcqIlYBTgdWBJ4DTsrM45vanyRJkiRJ0mTVZAueucBBmfkaYFNgn4hYu8H9SZIkSZIkTUqNFXgy877MvK76+XHgZmDlpvYnSZIkSZI0WTXWRatVRKwOvA64erDlpk1bgq6uzrEIaUDd3VPHdf8TwWTPwXk33Dei9XdYf6VRimR8TfbrAMzBSC0M+VsYjmGk2j0Hmx595YjW/8OhM9o+B6PBHJgDMAdgDsAcTPbjB3PAvU+MaPUm89d4gScilgR+DOyfmY8Ntuzs2U82Hc6gurunMmvW4+Maw3gzByO3MOTP66AwByPT7vnzfWAOek32HHgdFJM9B14HxWTPwWS/Dib78YM5GA2jkb+BikSNPkUrIqZQijtnZeZPmtyXJEmSJEnSZNVYgSciOoCTgZsz87im9iNJkiRJkjTZNdlFazNgV+D/RcT11bzDMvOiBvc5IiMde2XG9CVHKRJJkiRJkqT6GivwZOZvgY6mti9JkiRJkqSi0TF4JEmSJEmS1DwLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSW3OAo8kSZIkSVKbs8AjSZIkSZLU5rrGOwBptG138nUjWv/gmWuNUiSSJEmSJI0NW/BIkiRJkiS1OQs8kiRJkiRJbc4CjyRJkiRJUpuzwCNJkiRJktTmLPBIkiRJkiS1OQs8kiRJkiRJbc4CjyRJkiRJUpuzwCNJkiRJktTmLPBIkiRJkiS1OQs8kiRJkiRJba6rqQ1HxCnAtsCDmbluU/uRJEmSJEma7JpswXMqsHWD25ckSZIkSRINFngy8zfAI01tX5IkSZIkSUVjXbQWxLRpS9DV1Tl+Adz7xIhW7+6eOkqBjK+F5TjGy8KSv4XlOEbCHIzMwpC/heEYRsocmAMwB2AOwByAOQBzMNmPH8zBRK4bTKgCz+zZT453CCMya9bj4x3CiHV3T10ojmM8LQz58zoozMHItHv+fB+Yg16TPQdeB8Vkz4HXQTHZczDZr4PJfvxgDkbDaORvoCKRT9GSJEmSJElqcxZ4JEmSJEmS2lyTj0k/B3gLsFxE3A0ckZknN7U/SZIkSZLUnPNuuG9E68+YvuQoRaL+NFbgycydm9q2JEmSJEmSXmAXLUmSJEmSpDZngUeSJEmSJKnNTajHpEuSJEmS1ITtTr5uROv/4dAZoxTJ+BlpDg6eudYoRTJ+FuYc2IJHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktqcBR5JkiRJkqQ2Z4FHkiRJkiSpzVngkSRJkiRJanM+Jl3Si5x3w30jWn/G9CVHKRJJkiRpYhjp38jg38lqli14JEmSJEmS2pwFHkmSJEmSpDZngUeSJEmSJKnNWeCRJEmSJElqcxZ4JEmSJEmS2pwFHkmSJEmSpDZngUeSJEmSJKnNWeCRJEmSJElqcxZ4JEmSJEmS2pwFHkmSJEmSpDZngUeSJEmSJKnNWeCRJEmSJElqcxZ4JEmSJEmS2lzXeAcgSZIkTWTn3XDfiNafMX3JUYpEkqSB2YJHkiRJkiSpzVngkSRJkiRJanMWeCRJkiRJktpco2PwRMTWwPFAJ/C9zDy6yf1Jgu1Ovm7E2zh45lqjEEl7c7wFSeBngaQX+HkgaaJrrAVPRHQC3wRmAmsDO0fE2k3tT5IkSZIkabJqsovWJsDfM/PWzHwW+AHwrgb3J0mSJEmSNCk1WeBZGbirZfruap4kSZIkSZJGUUdPT08jG46IHYF3ZOae1fSuwCaZuV8jO5QkSZIkSZqkmmzBczewSsv0y4F7G9yfJEmSJEnSpNTkU7SuAV4VEWsA9wDvB/5Pg/uTJEmSJEmalBprwZOZc4F9gUuAm4EfZuaNTe1PkiRJkiRpsmpsDB5JkiRJkiSNjSbH4JEkSZIkSdIYsMAjSZIkSZLU5izwSJIkSZIktTkLPJIkSZIkSUOIiEUiYqnxjmMgDrIsVSJiPWB1oKt3Xmb+ZNwCGgcRsTyweO90Zt45juGMi4jYHHhVZn4/IrqBJTPztvGOayxExDHA9yfrEw8j4gKg7y/FR4E/Ad/JzKfHPqqxFxHrZuZfxjuO8RIRmwFHAqtRfh90AD2ZueZ4xjUeImJ94E3V5FWZecN4xjPWqmvh+sz8V0TsAmwIHJ+Zd4xzaJI0ZiKiE9iGF98nHTdeMY21iDgb2BuYB1wLLA0cl5n/Oa6B9aNr6EUWXhGxOPBhYB3mv6n90LgFNcbMQRERpwDrATcCz1Wze4BJUeCJiO2BY4HpwIOUG5ubKdfFpBERRwAbAwF8H5gCnAlsNp5xjaFbgJMiooty/Odk5qPjHNNYuhXoBs6ppncCHgDWAr4L7DpOcY21b0fEosCpwNmZ+c9xjmesnQwcQPkDbt44xzJuIuITwF688HvwzIg4KTP/exzDGmsnAutXha5PUq6N04EZ4xrVGImItSg5WCEz162+CNs+M780zqGNmYh4L/BVYHlKsbe34Dthv70fbRGxGPDvvPjm/gvjFdNYqc7/gCbRF8EXAE8D/48X7pMmm7Uz87GI+ABwEfApyt8JFngmmDMoNzTvAL4AfIByUzuZmINi08z/396dR8tVVfse/55EkB5EQEQviDQ/5CqdIO0FQWxQAREUaQQBUS8onU/0ItLItUNABXyQEEREBdGIdAaEEIg0EUkEAsrPjlZFDCDE0Ifz/lhr59TpEt4YZq9KrfkZ44yq2pWMMXNyzq6951pzTq9fOoiCTgK2AK61vbGk7YG9CsdUwm7AxsAMANt/lbRs2ZDaY3sCMEGSgAOAOyXdBJxje0rZ6Fqxse1tO15fLmmq7W0lVbOryfY2ktYBDgRuk3QraWfXNYVDa8sTtieVDqILHARsbnsOgKSvAbcANSV4XrDdL2lX0s6dcyXtXzqoFp0DfAYYB2D7zryKXU2CBzgZ2Nl2jdfGjUtJu1mnA88WjqVtO+fHVYCtgOvy6+2B66lkIRh4re0NSgdR2GKSFgPeB5xp+3lJXVkKVXsPnrVtfwGYY/t80tazNxWOqW3xPUhukVRzgud5248CYySNyTfzG5UOqoDnbPeTy3QkLV04ntblbbjr5a9ZwB3AUZIuKhpYO1aWtHrzIj9fKb98rkxIZdj+A3AsaYVqO+B0SfcsaDWzR0yR9HVJW0rapPkqHVQBfQzewTQ3H6vJbEn/A+wLXJnPj4sVjqlNS9m+dcixF4pEUs7fK0/uQLq539P2ybZPbb5KB9UG2wfYPoB0Xbi+7d1t705lO9yBSZLeUTqIwsYB9wFLA1MlrQE8WTSiUdS+g+f5/PhPSW8EHiZtP6xJfA+S80lJnodJqxPNFtxastX/lLQMMBX4gaRHqO8iDuBiSeOAFSQdTNrBcE7hmFoj6TRgF2Ay8OWOC/uvSXK5yFrzaeBGSX8inQPWBA7Jib7zi0bWolyGcQAp4X8NafV6hqTVSDs4en3FcvP8uGnHsX5ghwKxlHQe8CtJl+TX7yOVKNVkT2Bv4CDbD+ekb9dtx1+IZklai4FFjz2Av5UNqXW3SfoR8DM6dq9UVJoDcLOkN9meWTqQgl5nu/NnvynfrsU04BJJY0j3jtWVKto+HTi949D9ueKh69Se4Bkv6RXAF4DLgGWA48qG1Lr4HiTfIfXXqLW2dFdSbe2RpDK95Ukle1WxfYqkt5My8gKOq6gsBeAu4FjbT43w3lvaDqZttn+eS5PWI1283NPRWPmb5SJr3ZnABOAY2083B3PJ4rHlwmqH7a68YGub7dMkXQ9sQ/p9OMD2b8pG1S7bDwOndbx+gNSDpxaHAuOB9ST9BbiXdI1Qk+WAp4DO3QvV9GjMtgE+Iule6lwEBbhe0tWkHn39wIeAGkrXG6cCWwIz80736kh6FfBlYDXbO+XKjy3pwoWPmKIVAiDpOtu1rc6GISStCfytuamXtCSpueR9RQNrkaTXMDA9CADbU8tF1C5JWzG8kWRNN3QBkPQehg8fqCrpLWkL4G7bs/PrZUklCr8qG9nCJ2k2wyfqzVPDqnVeqd/D9sV5F+OY5mch1CWXogxT2zS5XKLcTBWcavuS+f35XpKTWzvZrnERHABJk0g7Wz9ve8M8kOQ3truutUmVO3gk7Wv7+5KOGun9Gka+xfdgmHty48DLqWgLblzEDvNjUhO9xtx8bLMy4bRL0ldJq1K/ZaD3Rj+pdK/nSboAWAu4ncH//ioSPJJmMvL5oKrVWklnA0uRmmhOAPYAhvYhqcFZpLHgjTkjHOtJtpcFkPRFUun6BaTfg32AKhrv235R0ieBi5tG2zWRdLTtkyWdwQjnRduHFQirCNv3S9oGWMf2eZJWJu34r0q+J+jp+4L5+BtpF9MkBt8n1XS/uFJOeP8PgO0XJHXlpM0qEzyk5khQyYf0KOJ7MNiSpBNWVVtw4yJ2mJfZntdM1/ZzeVx0LXYDZLu2KRmNTUk7FGrd2vre0gF0ia1sbyDpTtsnSjqVHv8sGEVf5+9CvuGv7brxnbY373h9lqRfkSYr1eAaSf8H+BEpwQeA7cfKhdSaprHybUWj6AKSjid9Poq0g2Ex4PvA1iXjalPevfM10jStPurrQXNv/lo8f9VojqRXMtCTbAvSdLmuU9sHNQC2m3GPJ5aOpRTb4/I0iCdtf6N0PKXlDvk1q/0itvEPSbvYvgwgj8adVTimNv2ZdOFWa4LnLmBV6msiCtS33X4+mr5DT+XG0o+SGm7X5s+SDiPt2gE4hHSOqMlcSfsAF5Eu6vdi8GSxXndgfjy041g/8PoCsbTK9uX5sZoG+/OxG7AxMAPm9WOrbRHwZNLAgSonqjX3zPn/vd/2vwqHVMJRpH61a0m6CVgZ+EDZkEZWZYJH0unze7+WbZe250raBag+wSPpPEbegnvgCH+8F9V+Edv4BGmK2Jmk1ZkHgf3KhtSqp4DbJU1m8BbcKs6JpJHov5V0K4P//buUC6l9eVXqDOANpJW6scCcilYqr5C0Amla0gzSObGaaXodPkGaGHIs6XswGfhY0YjatzfwrfzVD9yUj1XBdo2JzUFyOdJngfUZ3JOrpr6Nz9nul9TsXFh6QX+hB/291uQOQJ60fAGwYn49C9jP9t1FA2vX3cB2pJ1sfYCBMUUjGkWVCR5geukAusjN+WZ26PbbGeVCKuKKjudLkFYr/loolhKqvoht2P4TsEUeGd9XYUPJy/JXrU4oHUCXOJPUi+nHpG35+wFrF42oRbZPyk8nSroCWMJ2V27DXphsP0L6OahWbrC/a+k4SpG0GPDfwLb50PXAONvPFwuqfT8gXSO/h5T03B/4R9GI2nexpHHACpIOJu3sqi3pfZukHwE/o6JenR3GA0fZngIg6a2kn4Gt5veXeswttjchJXoAkDSDLuxLF1O0KidppBF//ZWtTAyTp0dcW/v3oTaSXg7szvApSlVNz6lZHoPZNNW+Nd/kVkXSbbY3zT1oNsjHbrZdxYWcpCVI5UjbkBLeNwJnNdP1el00lx2Qd28czPDPhCp290qaQCrbbcqUPgzMtf3RclG1S9J0228ecj68wfZ2pWNrk6S3k/pU9gFX276mcEityjv9h+qv6Fxwh+0NF3SsF0laFXgNqe/U3qTfAYDlgLNtr1cqttHUuoMHiG2X2UG2B9XUS+r52uqXYB1g9dJBtCXf0BzE8LHAVXxwdbiU1DBtOhX2oZG0DvAVhp8TqzgnSPogqSznetIH+BmSPmP7J0UDa99Tubn47ZJOJvUkqmlL/veA2aQyNUglqxfQpbX2C0E0lx1wKfBL4FrqLFvebMgN3HWS7igWTRnNbqW/SXoPaXf3awvGU0RO6FSV1OkUvTr5s6QvkD4LAfYlNV2uwTuBj5B+7zunhs0Gjja0ya4AABr4SURBVCkR0IJUneAhtl0C/IThW8t+DLy5QCzFdIwL78uPD5OSf7W4ALiHdBL7ImmKVo21xq+1/a7SQRR0HnA8qS/X9sABDKxU1ODzpBuaR2DeIsC1pPNkTT5Mqiv/JHAk8B/A+4tG1C4NuamdUtNNbdNcFvjR0F1LklYqEFJJS9mu6VpgqLmS1srly80CYG2Jrv+VtDzwaVLSdznSebHndVwbj6iivmyxEJrK8k4kTZTsA6aSrhF7Xm60fr6k3W1PLB3PS1F7gueVts+VdLjtG4AbJN1QOqg2SFqPdJJaPo/+ayxHx4mrFs248IqtbfsDkna1fb6kHwJXlw6qgJslvcn2zNKBFLKk7cmS+vJEpRMk/ZKU9KnBmCElWY/SpQ30FrL32f4W8Azpgg5Jh5N6dNXgN5K2sD0NQNLmpL5ktblV0sc6vg+7k3b4rVs2rFZdIendtn9eOpBCPkNKcP6ZdFO3BpXc1DVsNz0anyAtfFSjuTaW9EXSwucFpJ+DfYDarpurXgi1/ThQTXnuSGxPzLv4hib5uq6NQ+0Jnpq3XQp4L7ACsHPH8dmkevMqSFrP9j2SRmyQVVGz6eZ34Z+5U/7DpJ4DtdkG+Iike0klWn2kGusNyobVmmdy/6k/SPok8BdglcIxtekqSVcDF+bXewKTCsZTyv4MT+Z8ZIRjvWpzYD9JD+TXqwO/kzSTus4H+wDfkXQ9sBrwSqCmEnaAw4FjJD1L+pxsPhOq2LmQE/7rMDA15h7bVZUv511L3wK2BF4EbgGOHNreoMe90/bmHa/PkvQr0ujwWlS5ECrpcua/i6uaKaOSzgaWIiV6JwB7ALcWDWoUtSd4qt12aftS4FJJW9q+pXQ8BR1FGvt66gjv9VPPxex4Sa8AvkCaorQMcFzZkIrYqXQAhR1B+vA6DDiJ9PO/f9GIWmT7M3lH4zakm5nxpIkZVZC0F6mB4JqSOqepLUvazVSLmss057E9U9KXSCvXs4FtbT9UOKxW1b67d4SG47+UdHYtDcezHwLfJk1XhTRZ7kJSIrgWcyXtA1xE+jnYi/pK9WpdCD0lP74fWJXUaBjSz8B9JQIqaCvbG+SG6ydKOpVUstZ1qk3wSBoLrJO3Xla37bLDbpLuBp4GrgI2BI6w/f35/7XeYPtj+bHW/38AbE/IT28AqmioO5JcloSkVaizVPHX+em/qGgbvqT9c411M/L0p/n4YqSL+70Khtemm0kNlVdicNJ7NnBnkYgKGO08YPuBUf9SD5J0LrAWsAGpLOtySWfa/nbZyNqVFz/WYfDPwtRyEbWq9objAH22L+h4/f28w7Ume5N2MX2LlOC5KR+rSZULobmFCZJOsr1tx1uXS6rlPNh4Oj8+JWk10sLXmgXjGVW1CR7bcyXtQmomWrN32D5a0m7AQ6QP7SkMZGirMKQPUeMJYGYNY5JjPHiSzwmnksoRHiH1G/gdqd6250nalNRoeA0G/xz0eknK4ZJebnt8c0DS0qTdO9Xc1OfExv2kUoRq1X4e6HAX8FHb/cC9krZg8ASRnifpo6QyrdcCtwNbkEp0atndW3XD8WyKpM8xsHtlT+BKSSsC2H6sZHBtsH0fsGvpOEqKhVBWlvT6pjRR0prAyoVjatsVklYgTVudQTofTJj/Xymj2gRPdrOkM0mTtOY0ByvquwKwWH58N3Ch7ccklYynlININzVT8uu3AtOAdSV9ccjqTS+qejx4h5NIF/DX2t5Y0vbUs3sD0mTBzwAzSb0GarEjqf/OErZPz9Ozfg5Mtv25wrG1Zj4TU6rqO0KcBwCw/Q1JS0pa3ckTpM/KmhwObAZMs719HlBxYuGY2hQNx1NCB1I5PwxMljyQdL7s+Zt9SesCZwGvsv1GSRsAu9j+38KhLXSSjprf+7ZrSXofCVyfG65DWhD+eLlwijg59yCbKOkK0q7OrixXrT3Bs1V+7NylUFPfFUhb7O4hbTs7JN/YdOUP60L2IvAG238HkPQq0ofZ5qRRgL2e4Kl9PHjjeduPShojaYztKZK+VjqoFv3D9mUL/mO9JSe2dwQm5W23uwJn2T69cGitqr3fSIfazwMASNqZ1H9hcVJfpo2AL9bUVBN4xvYzksi7/O5RXatg1TYcl7QZ8KDtNfPr/Uk7ne8DTqhh506Hc0iLP+MAbN+Zmwz3fIKH+qaFjcj2Vbnh+nr5UHUN10m7NzcByP/2ZyXNaI51k9oTPAcN7YKfu+VXw/bn8oXrk7lsbQ51bsN8XZPcyR4B1s03fs+P9pd6SO3jwRv/lLQMKan3A0mPAC8UjqlNx0uaAEymYydX7kvTszpKNMeTSlAmAw81x3v93x+Gac4Dv6TO80DjBOAtwPUAtm/P2/Jr8lDekv8z4BpJj5Mmrtai5oWfcaTdnUjaFvgK8ClgI9JnxR7lQmvdUrZvHZLbrOKcmJvpjgUOs11tW48RWlmsJamKVhaSVgVeAywpaWMGdvEtRxpM0nVqT/D8hOFZtx8Dby4QSxGS9ut43vnW99qPpqhf5u12P86vdwem5j4c/ywXVmtqHw/e2JW0m+1I0ojg5Rm8w6/XHUBanVmMgRKtfrp0SsC/0c4dzy8bcqyGf38YbBfSTtbDgX1JF3E1leU0XrD9xJBrg1HH5fYi283kpBMkTSF9JlxVMKRWVd5wfGzHLp09gfG2J5LKM24vGFcJsyStRf79l7QHqSF/FaJvKzDQyuI60j3CW6mnlcU7gY+QerGdykCCZzZwTKGY5qvKBE+uof5PYPkhGcnlqG9yzmYdz5cA3kZqHFVbgudQUlJna9Iv7veAibm5ZA0TtmofD95M1rvU9o6k5Mb5hUMqYUPbbyodRNtsVzMxLIxulB5EzYXccZL+BHze9uR2IyvmLkl7A2Pz1vzDSJPWel7TQHeIZofrMkAV5TmVNxwfK+lltl8gXRt/rOO92u6fDiXtWlpP0l+Ae0mLYDWpvW9rta0s8pTV8yXtnpO8Xa+2E1RDwHuBFRi8cjsbOLhIRIXY/lTna0nL08O/pKPJiZyf5K/q1D4eHOat0DwlafncTLRG0yStb/u3pQMJoW3z60GUE8BvJDUif2NrQZX1KdJUvWeBC4GrSQ2oazCdlOzr6zjWvK6isW5Wc8PxC4EbJM0i7ez9JYCktUlDKaqR21nsmHe1j7E9u3RMBdTet7XaVha5H92dTXJH0nGkTQH3A4fbvrdkfCOpMsFj+1LgUklb2r6ldDxd5ilg3dJBtCWmxiSVr9J1egaYKekaBq/QHFYupFZtA+wfpXohDGZ7LnCHpDNKx9IW20+REjyfLx1L22yvKakP+I9KypFGU23DcdtfkjQZeDXwi7wQCDCGlPysRt69OI2U5JoKVLcIZLuG3fzzU3Mriy+REt1Iei+pdHsvYGPgbFIJV1epMsHTYTdJd5My81cBGwJH2P5+2bDaI+lyBhIcY4E3ABeXi6hdMTVmnppX6Tpdmb9qVXNDzRAWyPa40jEsbJLmO0mvlilatvslXUJFfRlHUPXggWY8/JBjvy8RS2Hrk0px/gs4Jbe6uKOjR1XPyyVJXwZWs72TpPWBLW2fWzi0ttTcyqI/L3gAvB841/Z0YLqkQwrGNaraEzzvsH20pN2Ah4APAFOAahI8pBGojRdIv7Q13tgjaRtgHdvnSVoJWLYbt90tJNWu0gFIWt32A7nOtkqSxgBX2q6l/GSYEaZEQNqK3/NTIkLosCXwIKlE5VcMLlOqzTRJm9n+delACtmVtLO11sEDIZkLPJ8fXwT+TtrtXZPvAucxsKPx96R+PFUkeCpvZdGXE91Pkfpx/d+O97qyrUXtCZ7F8uO7gQtzHWHJeFpn+wZJGwF7Ax8kNU5bJBpI/TtJOh7YlNSf6TxgcVKib+uScbWo6lU60gjcTQAkTbS9e+F4Wmf7RUl3NMmu0vEU0kyJmJJfv5V6pkSE0FgVeDtpsWdv0q7GC23fXTSqMrYHPiHpPlLZblVlq7bndLysdgEk8CSpyfhpwDm2Hy0cTwkr2b5Y0v8A2H5B0tzSQbUlL4B9DViFdB6sqZXFN4HbSb8Hv7N9G0Aemd6V0+RqT/BcLukeUonWIZJWJq1U9DxJ6wIfIl3APUrKQvdVXGO6G6mWcgaA7b9K6vnyrdws8FUMHw++BnXVmHeuUNfSPHMkrwbulnQrg3sQVVGSQcVTIkJo5H5DVwFXSXo56Trh+pzkrKYHUVb1hMlR+hQ+AdwGfDo33w29by9Sj75DgI9KuhmYWtFEQYA5kl7JwKj4Lair2fbJwM62f1c6kLbZ/o6kq0nJrTs63noY6MoprFUneGx/LpehPJkn6Mwh3ejW4B5Ss7Sdbf8RQNKRZUMq6rlcb9+cuJcuHVBLvgkc07FK9yJpFOCmwAkMnjLXy/pHeV6bE0sHUFi1UyJC6JQTO+8h3di9Djgd+GnJmEqwff+Q8u2VSWPSa3Ea8Ffgh6SFkA+RdngZ+A5pl2PocR3DadYjJT2PAI4GliwaWLs+DVwGrCXpJmBlUmuPWvy9xuROw/ZfgL8MOdaVu3eg8gSPpP06nne+9b32o2nd7qQP6imSrgIuou46+4sljQNWkHQwcCBwTuGY2vA623cOPWj7NkmvKxBPKRtKepL0O7Bkfg51bUFtSjbXIN3MXCtpKVLz9VrUPCUiBAAknU8aBT8JONH2XYVDKmaE8u3FqKt8+122N+94PV7SNNtflHRMsahCqyRNBDYC/khaHP4wcGvRoFpme7qk7Ujngr50yDUt/Nwm6UeklgbPNgdtV5f4XxRUneABNut4vgSpcdIMKkjw2L4EuCTfuLyPVJrzKklnAZfY/kXRAFtm+xRJbyfVVwo4zvY1hcNqw/yag1WzMmO7piTGqHJy82PAisBawGtIIyDfVjKuFtU8JSKExodJJZrrAod1LIBVlfDOqizf7vCipA8y0Fh1j473at7tWgVJm5Earn+V9DuwL+kzchXgLippawHzRsV/3fbZHceusP3egmG1aTlSk+F3dBzrp8KdnYuCqhM8tgf1GJG0PJX1WMilOT8gNdZdkbTd8HNAVQkegJzQuSZP0KqlgdyvJR1se9BuJUkHAdMLxRTKORR4C2lyDrb/IGmVsiG1p/IpESEAYHtM6Ri6SK3l2419gG+Rpsb0k5rO7ytpSeCTJQMLrRgH7Gj715K2Bb5C6s+4ETCewQm/Xvc8sL2kzYGP236OtAhWBdtd2WumDfn+eFS2H2srlpeq6gTPCJ4irVhVKf+AjstfVchN0r4KPAacRErwrQSMkbSf7atKxteCI0g7ufZhIKGzKWmK2G7FogqlPGv7uWbFXtLLqGiVtvIpESGE4Wot3wYgN1EerRffjW3GEooY23Hzuicw3vZEYKKk2wvGVcJTtveUdDSpnPuDVHB9JOlo2ydLOoMR/r22DysQVtumk/7tfcDqwOP5+QrAA8Ca5UIbWdUJHkmXM/DDOhZ4A3BxuYhCAWcCxwDLA9cBO9melhvJXUiaJNKzckPZrSRtT+q5AHCl7esKhhXKuSH3VVgylyweAlxeOKY2VTslIoQwXMXl2wDkptIHkxptz7tnsH1gqZhCq8ZKepntF0il2h/reK+2e8g+gJzsmA5cTSpn73XN9dBtRaMoyPaaAJLOBi6z/fP8eidgx5Kxjaa2X86hTul4/gLpl3evQrGEMl7W9BvKI2CnAdi+Z0jj7Z5mewowpXQcobjPAQcBM0kXclfanlA2pFZVPSUihDBcU75dOo5CLiU11b0WmFs4ltC+C0kLP7OAp0k/C0ham7pGhAMc1zyxPVnSO4H9C8bTlgcAbJ8/9A1J/91+OEVtZvsTzQvbkySdVDKg0VSd4MkTYzYC9gY+CNwLTCwbVWjZix3Pnx7yXs9vvQwBQNKuwGttfxs4J5cirAy8WdI/bdfSkyamRIQQ5omyTZay/dnSQYQybH9J0mTg1cAvcp86gDGkXjw1OYKOHc22789TtXrdJZI+YHtQX05JJ5LKN88qE1YRsyQdS5qk2E9qOt6VPVurTPBIWpc0Inwv0n/Mj4A+2zElpT7zG489vwlTIfSSo0nnxMbiwJuBZUijgWtJ8MSUiBBCp9rLNq+Q9O6mJCHUp9nZPuTY70vEUoKkJYClgJUkvYJcqkW6XlitWGDt+QDwY0n72L5FUh8pqbMu8NaikbVvL+B44BLSteFUurTyp8oED3APaZvhzrb/CCDpyLIhhRJiPHYIACxu+8GO1zfmxoqP1TQ1puYpESGEEdVetnk4cIykZ0lThGrbwRTCx0m7d1YjjYpvPAl8u0hELbI9XdL7SDt5DiX15AJ4V54kVo18XXy4pGVs/6t0PPPT199fXxWKpN1Iq9VbkZroXgRMaJoohRBCTST90fbao7z3J9trtR1TCZJeC5wBbE1anbkRONz2Q0UDCyG0KpdmAWwHrEqUbYZQNUmfsn1G6Tja1jEifH3SefBa4JPkFhfdOCJ8YZG0FTABWMb26pI2BD5u+5DCoQ1T5Q4e25eQMpFLA+8DjgReJeks4JKm6W4IIVTiV5IOtj1o/K+kjwO3FoqphPOAH5K2JEOqrz4PeHuxiEIIJXSOBq+ubFPSennYxCYjvW97xkjHQ+g1knbIk2X/0pH4naeCZG8zIhxgNrA56bqwLx9/faG4SvgG8E7gMgDbd0jatmxII6sywdOwPQf4AfCDnKH8AGmKTCR4Qgg1ORL4maS9GdiC/Gbg5aQkeC1Wtn1ex+vvSjqiWDQhhCKack1JW9u+qfM9SVuXiapVR5EmKZ7acaxzy/8O7YYTQjHbAdcxOOnb6Plkb1S3DGb7wSFTlrtyumDVCZ5OeYvZuPwVQgjVsP0IsJWkHYD/zIevzKtWNZklaV/SaFgYaMQfQqjTGcDQXSwjHes1EySt2gwfkbQ/sDtwH3BCwbhCaJXt4/Nj9OgLD+YyrX5JiwOHAV3Zoy0SPCGEEADICZ3akjqdDgTOJG3D7QduzsdCCBWRtCWpT+PKko7qeGs5oIbhDGcDOwLkEoSvkMZibwSMB/YoF1oI7ZP0J2AaaUjPVNu/LRxSaN8ngG8BrwEeIlX8dF3/HYgETwghhACA7QeAXUrHEUIobnFgGdJ18rIdx5+kjuTG2I7mqXsC421PBCZKur1gXCGUsj6p/8x/AadIWg+4w/ZuZcMKLZLtfQYdSCW7N43y54uJBE8IIYSqSTqDwf0lBrF9WIvhhBAKs30DcIOk79q+X9LSuW9jLcZKepntF4C3kfrxNOLeIdRoLvB8fnwR+DvwSNGIWtAxRWtENU3RYhEq2Y2TdAghhNrd1vH8ROD4UoGEELrKapImkXbzdPVY3H+zC0kJrlnA06SyFCStDTxRMrAQCnkSmAmcBpxju5b+fM0UrT5gdeDx/HwF4AGg55swL4olu5HgCSGEUDXb5zfPJR3R+TqEULVvsoiMxf13sv0lSZOBVwO/sN3scBxD6sUTQm32ArYh9Vz5qKSbSb14JpcNa+FqpmhJOhu4zPbP8+udyH26KrDIlexGgieEEEIYMGqpVgihPovKWNx/N9vTRjj2+xKxhFCa7UuBS3PvnZ2AI4CjgSWLBtaezWx/onlhe5Kkk0oG1JahJbul43kpIsETQgghhBDCcIvMWNwQwsIjaSJpitwfSSWLHwZuLRpUu2ZJOhb4PmkhbF+gijI1Sd+0fQRwpqRhi4C2u244RyR4QgghVE3SbAZ27iwl6cn8vA/ot71cmchCCIWNNBb30KIRhRBaI2kz4EHgq8AMUmJjd2AV4C7gmXLRtWovUn/CS0jXS1PzsRpckB9PKRrF/4e+/v7YjR5CCCGEEEIIITQkzQB2tP1Y7r91EakP1UbAG2x3ZQ+WhUXSMrb/VTqOMH+xgyeEEEIIIYRM0nHzebvfdhW9J0IIjO0YBb4nMN72RGCipNsLxtWqXKo6gfomCs4jaWvgBGANUg6l2eX9+pJxjWRM6QBCCCGEEELoInNG+AI4CPhsqaBCCK0bK6nZEPE24LqO92raKPEN0kTBRyFNFAR6fqLgEOcCp5GmqW0GbJofu05NP5ghhBBCCCHMl+1Tm+eSlgUOBw4glWecOtrfCyH0nAtJE5RmAU+TGiwjaW3giZKBta3WiYIdnrA9qXQQL0UkeEIIIYQQQuggaUXgKGAf4HxgE9uPl40qhNAm21+SNBl4NfAL203z2jGkXjy1iImCMEXS14GfAs82B23PKBfSyCLBE0IIIYQQQpYv4t8PjAfeFE1FQ6iX7WkjHPt9iVgKGmmiYDX9d7LN8+OmHcf6gR0KxDJfMUUrhBBCCCGETNKLpBXaF0gX8I2mqeZyRQILIYQCJG1t+6YFHQvdIXbwhBBCCCGEkNmOISQhhDDgDGCTl3Cs50g6asihfmAWcKPtewuEtECR4AkhhBBCCCGEEMI8krYEtgJWHpLoWA4YWyaq1i07wrHXAZ+XdILti1qOZ4EiwRNCCCGEEEIIIYROiwPLkHIGnYmOJ4E9ikTUMtsnjnQ8N+K/ljRdsatED54QQgghhBBCCCEMI2kN2/eXjqPbSPqN7Y1LxzFU7OAJIYQQQgghhBDCPJK+afsI4ExJw3aF2N6lQFhdQdIOwOOl4xhJJHhCCCGEEEIIIYTQ6YL8eErRKAqSNJPB0xQBVgT+CuzXfkQLFiVaIYQQQgghhBBCCB0krTHkUD/wqO05JeJ5KSLBE0IIIYQQQgghhGEkbQ2cAKxBqgDqA/ptv75kXGFkUaIVQgghhBBCCCGEkZwLHAlMB+YWjiUsQCR4QgghhBBCCCGEMJInbE8qHUR4aaJEK4QQQgghhBBCCMNI+iowFvgp8Gxz3PaMYkGFUcUOnhBCCCGEEEIIIYxk8/y4acexfmCHArGEBYgdPCGEEEIIIYQQQgiLuNjBE0IIIYQQQgghhHkkHTXkUD8wC7jR9r0FQgovwZjSAYQQQgghhBBCCKGrLDvkazlSmdYkSR8qGVgYXZRohRBCCCGEEEIIYYEkrQhca3uT0rGE4WIHTwghhBBCCCGEEBbI9mNAX+k4wsgiwRNCCCGEEEIIIYQFkrQD8HjpOMLIoslyCCGEEEIIIYQQ5pE0k9RYudOKwF+B/dqPKLwUkeAJIYQQQgghhBBCp/cOed0PPGp7TolgwksTTZZDCCGEEEIIIYQQFnHRgyeEEEIIIYQQQghhERcJnhBCCCGEEEIIIYRFXCR4QgghhBBCCCGEEBZxkeAJIYQQQgghhBBCWMT9P5ksnaLMkUXiAAAAAElFTkSuQmCC\n",
178 |       "text/plain": [
179 |        "<Figure size 1152x432 with 1 Axes>"
180 |       ]
181 |      },
182 |      "metadata": {},
183 |      "output_type": "display_data"
184 |     }
185 |    ],
186 |    "source": [
187 |     "sns.set_palette(sns.color_palette(\"Blues_r\", n_colors=2))\n",
188 |     "prices = pd.DataFrame(prices_differ_alot).T.round(3)*100\n",
189 |     "ax = prices.sort_index().plot(kind=\"bar\", title=\"How often primary exchange price differs from consolidated price by more than 1%\", figsize=(16,6))\n",
190 |     "ax.set_ylabel(\"Percentage of total dates\")\n",
191 |     "plt.tight_layout()"
192 |    ]
193 |   },
194 |   {
195 |    "cell_type": "markdown",
196 |    "metadata": {},
197 |    "source": [
198 |     "Then volume:"
199 |    ]
200 |   },
201 |   {
202 |    "cell_type": "code",
203 |    "execution_count": 7,
204 |    "metadata": {},
205 |    "outputs": [
206 |     {
207 |      "data": {
208 |       "image/png": 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\n",
209 |       "text/plain": [
210 |        "<Figure size 1152x432 with 1 Axes>"
211 |       ]
212 |      },
213 |      "metadata": {},
214 |      "output_type": "display_data"
215 |     }
216 |    ],
217 |    "source": [
218 |     "sns.set_palette(sns.color_palette(\"Blues_r\", n_colors=2))\n",
219 |     "primary_volumes = pd.Series(primary_volume_pct).round(2) * 100\n",
220 |     "primary_volumes = primary_volumes.sort_index()\n",
221 |     "primary_volumes.name = \"primary exchange\"\n",
222 |     "other_volumes = 100 - primary_volumes\n",
223 |     "other_volumes.name = \"other exchanges\"\n",
224 |     "volumes = pd.concat([primary_volumes, other_volumes], axis=1)\n",
225 |     "ax = volumes.plot(kind=\"bar\", stacked=True, title=\"Primary exchange volume as percentage of total volume\", figsize=(16,6))\n",
226 |     "ax.set_ylabel(\"Percentage of total volume\")\n",
227 |     "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))"
228 |    ]
229 |   },
230 |   {
231 |    "cell_type": "markdown",
232 |    "metadata": {},
233 |    "source": [
234 |     "***\n",
235 |     "\n",
236 |     "[Back to Introduction](Introduction.ipynb)"
237 |    ]
238 |   }
239 |  ],
240 |  "metadata": {
241 |   "kernelspec": {
242 |    "display_name": "Python 3.9",
243 |    "language": "python",
244 |    "name": "python3"
245 |   },
246 |   "language_info": {
247 |    "codemirror_mode": {
248 |     "name": "ipython",
249 |     "version": 3
250 |    },
251 |    "file_extension": ".py",
252 |    "mimetype": "text/x-python",
253 |    "name": "python",
254 |    "nbconvert_exporter": "python",
255 |    "pygments_lexer": "ipython3",
256 |    "version": "3.9.7"
257 |   }
258 |  },
259 |  "nbformat": 4,
260 |  "nbformat_minor": 4
261 | }
262 | 


--------------------------------------------------------------------------------
/global_market_profiles/Shortable-Shares.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "<a href=\"https://www.quantrocket.com\"><img alt=\"QuantRocket logo\" src=\"https://www.quantrocket.com/assets/img/notebook-header-logo.png\"></a><br>\n",
  8 |     "<a href=\"https://www.quantrocket.com/disclaimer/\">Disclaimer</a>"
  9 |    ]
 10 |   },
 11 |   {
 12 |    "cell_type": "markdown",
 13 |    "metadata": {},
 14 |    "source": [
 15 |     "***\n",
 16 |     "[Global Market Profiles](Introduction.ipynb) › Short Sale Availability\n",
 17 |     "***"
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "markdown",
 22 |    "metadata": {},
 23 |    "source": [
 24 |     "# Short Sale Availability\n",
 25 |     "\n",
 26 |     "This notebook explores the percentage of listings that are shortable by country, above a given dollar volume threshold."
 27 |    ]
 28 |   },
 29 |   {
 30 |    "cell_type": "code",
 31 |    "execution_count": 1,
 32 |    "metadata": {},
 33 |    "outputs": [],
 34 |    "source": [
 35 |     "from quantrocket import get_prices\n",
 36 |     "from quantrocket.fundamental import download_ibkr_shortable_shares, NoFundamentalData\n",
 37 |     "from quantrocket.account import download_exchange_rates\n",
 38 |     "from quantrocket.master import get_securities_reindexed_like\n",
 39 |     "import pandas as pd\n",
 40 |     "import io"
 41 |    ]
 42 |   },
 43 |   {
 44 |    "cell_type": "markdown",
 45 |    "metadata": {},
 46 |    "source": [
 47 |     "Get exchange rates (for converting non-USD stocks to USD dollar volume):"
 48 |    ]
 49 |   },
 50 |   {
 51 |    "cell_type": "code",
 52 |    "execution_count": 2,
 53 |    "metadata": {},
 54 |    "outputs": [],
 55 |    "source": [
 56 |     "f = io.StringIO()\n",
 57 |     "download_exchange_rates(f, latest=True, base_currencies=\"USD\")\n",
 58 |     "rates = pd.read_csv(f)\n",
 59 |     "rates = rates.set_index(\"QuoteCurrency\").Rate.to_dict()"
 60 |    ]
 61 |   },
 62 |   {
 63 |    "cell_type": "code",
 64 |    "execution_count": 3,
 65 |    "metadata": {},
 66 |    "outputs": [],
 67 |    "source": [
 68 |     "def get_sids(db, start_date, min_dollar_volume=0, max_dollar_volume=None, universes=None):\n",
 69 |     "    \"\"\"\n",
 70 |     "    Return the list of sids for the db, optionally with average dollar volume above or below the threshold(s).\n",
 71 |     "    \"\"\"\n",
 72 |     "\n",
 73 |     "    prices = get_prices(\n",
 74 |     "        db, \n",
 75 |     "        start_date=start_date, \n",
 76 |     "        universes=universes, \n",
 77 |     "        fields=[\"Close\",\"Volume\"])\n",
 78 |     "        \n",
 79 |     "    closes = prices.loc[\"Close\"]\n",
 80 |     "    volumes = prices.loc[\"Volume\"]\n",
 81 |     "    securities = get_securities_reindexed_like(closes, fields=[\"Currency\",\"Multiplier\",\"PriceMagnifier\"])\n",
 82 |     "    currencies = securities.loc[\"Currency\"]\n",
 83 |     "    multipliers = securities.loc[\"Multiplier\"]\n",
 84 |     "    magnifiers = securities.loc[\"PriceMagnifier\"]\n",
 85 |     "    exchange_rates = currencies.applymap(lambda x: rates[x])\n",
 86 |     "    exchange_rates = exchange_rates.reindex(closes.index, method=\"ffill\")\n",
 87 |     "    closes = closes * multipliers.fillna(1) / magnifiers.fillna(1)\n",
 88 |     "    dollar_volumes = closes.div(exchange_rates) * volumes\n",
 89 |     "    avg_dollar_volumes = dollar_volumes.mean()\n",
 90 |     "    \n",
 91 |     "    if min_dollar_volume:\n",
 92 |     "        avg_dollar_volumes = avg_dollar_volumes[avg_dollar_volumes >= min_dollar_volume]\n",
 93 |     "    if max_dollar_volume:\n",
 94 |     "        avg_dollar_volumes = avg_dollar_volumes[avg_dollar_volumes <= max_dollar_volume]\n",
 95 |     "    \n",
 96 |     "    sids = list(avg_dollar_volumes.index)\n",
 97 |     "\n",
 98 |     "    return sids"
 99 |    ]
100 |   },
101 |   {
102 |    "cell_type": "code",
103 |    "execution_count": 4,
104 |    "metadata": {},
105 |    "outputs": [],
106 |    "source": [
107 |     "def get_shortable_universe_size(sids, start_date):\n",
108 |     "    \"\"\"\n",
109 |     "    Queries shortable shares and counts the unique sids.\n",
110 |     "    \"\"\"\n",
111 |     "    f = io.StringIO()\n",
112 |     "    try:\n",
113 |     "        download_ibkr_shortable_shares(f, sids=sids, start_date=start_date)\n",
114 |     "    except NoFundamentalData:\n",
115 |     "        return 0\n",
116 |     "    else:\n",
117 |     "        return len(pd.read_csv(f).Sid.unique())"
118 |    ]
119 |   },
120 |   {
121 |    "cell_type": "code",
122 |    "execution_count": 5,
123 |    "metadata": {},
124 |    "outputs": [],
125 |    "source": [
126 |     "def get_shortable_ratio(db, min_dollar_volume=None, max_dollar_volume=None):\n",
127 |     "    \"\"\"\n",
128 |     "    Divides count of shortable sids by total sids in the last 90 days.\n",
129 |     "    \"\"\"\n",
130 |     "    start_date = pd.Timestamp.today() - pd.Timedelta('90D')\n",
131 |     "    start_date = start_date.date().isoformat()\n",
132 |     "    sids = get_sids(db, start_date, min_dollar_volume=min_dollar_volume, max_dollar_volume=max_dollar_volume)\n",
133 |     "    shortable_size = get_shortable_universe_size(sids, start_date)\n",
134 |     "    return (shortable_size/len(sids)) * 100  "
135 |    ]
136 |   },
137 |   {
138 |    "cell_type": "markdown",
139 |    "metadata": {},
140 |    "source": [
141 |     "Countries for which numbers should be run:"
142 |    ]
143 |   },
144 |   {
145 |    "cell_type": "code",
146 |    "execution_count": 6,
147 |    "metadata": {},
148 |    "outputs": [],
149 |    "source": [
150 |     "countries = (\n",
151 |     "    # North America\n",
152 |     "    (\"usa-stk-1d\", \"United States\"),\n",
153 |     "    (\"canada-stk-1d\", \"Canada\"),\n",
154 |     "    (\"mexico-stk-1d\", \"Mexico\"),\n",
155 |     "    \n",
156 |     "    # Asia\n",
157 |     "    (\"australia-stk-1d\", \"Australia\"),\n",
158 |     "    (\"japan-stk-1d\", \"Japan\"),\n",
159 |     "    (\"hongkong-stk-1d\", \"Hong Kong\"),\n",
160 |     "    (\"singapore-stk-1d\", \"Singapore\"),\n",
161 |     "    \n",
162 |     "    # Europe\n",
163 |     "    (\"spain-stk-1d\", \"Spain\"),\n",
164 |     "    (\"netherlands-stk-1d\", \"Netherlands\"),\n",
165 |     "    (\"uk-stk-1d\", \"United Kingdom\"),\n",
166 |     "    (\"germany-stk-1d\", \"Germany\"),\n",
167 |     "    (\"france-stk-1d\", \"France\"),\n",
168 |     "    (\"belgium-stk-1d\", \"Belgium\"),\n",
169 |     "    (\"swiss-stk-1d\", \"Switzerland\"),\n",
170 |     "    (\"austria-stk-1d\", \"Austria\"),\n",
171 |     "    (\"sweden-stk-1d\", \"Sweden\"),\n",
172 |     "    (\"italy-stk-1d\", \"Italy\"),\n",
173 |     ")"
174 |    ]
175 |   },
176 |   {
177 |    "cell_type": "markdown",
178 |    "metadata": {},
179 |    "source": [
180 |     "Run numbers for each country, first with no dollar volume filter:"
181 |    ]
182 |   },
183 |   {
184 |    "cell_type": "code",
185 |    "execution_count": 7,
186 |    "metadata": {},
187 |    "outputs": [
188 |     {
189 |      "name": "stdout",
190 |      "output_type": "stream",
191 |      "text": [
192 |       "United States\n",
193 |       "Canada\n",
194 |       "Mexico\n",
195 |       "Australia\n",
196 |       "Japan\n",
197 |       "Hong Kong\n",
198 |       "Singapore\n",
199 |       "Spain\n",
200 |       "Netherlands\n",
201 |       "United Kingdom\n",
202 |       "Germany\n",
203 |       "France\n",
204 |       "Belgium\n",
205 |       "Switzerland\n",
206 |       "Austria\n",
207 |       "Sweden\n",
208 |       "Italy\n"
209 |      ]
210 |     }
211 |    ],
212 |    "source": [
213 |     "all_countries = {}\n",
214 |     "\n",
215 |     "for db, country in countries:\n",
216 |     "    print(country)\n",
217 |     "    all_countries[country] = get_shortable_ratio(db, min_dollar_volume=0)\n",
218 |     "    \n",
219 |     "shortable_ratios = pd.Series(all_countries, name=\"shortable\").to_frame()\n",
220 |     "shortable_ratios[\"not shortable\"] = 100 - shortable_ratios"
221 |    ]
222 |   },
223 |   {
224 |    "cell_type": "code",
225 |    "execution_count": 8,
226 |    "metadata": {},
227 |    "outputs": [],
228 |    "source": [
229 |     "import seaborn as sns\n",
230 |     "import matplotlib.pyplot as plt\n",
231 |     "sns.set(palette=sns.color_palette(\"Reds_r\", n_colors=2))"
232 |    ]
233 |   },
234 |   {
235 |    "cell_type": "code",
236 |    "execution_count": 9,
237 |    "metadata": {},
238 |    "outputs": [
239 |     {
240 |      "data": {
241 |       "image/png": 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\n",
242 |       "text/plain": [
243 |        "<Figure size 1152x432 with 1 Axes>"
244 |       ]
245 |      },
246 |      "metadata": {},
247 |      "output_type": "display_data"
248 |     }
249 |    ],
250 |    "source": [
251 |     "ax = shortable_ratios.sort_index().plot(kind=\"bar\", stacked=True, title=\"Percentage of stocks that are shortable\", figsize=(16,6))\n",
252 |     "ax.set_ylabel(\"Percentage of total\")\n",
253 |     "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))"
254 |    ]
255 |   },
256 |   {
257 |    "cell_type": "markdown",
258 |    "metadata": {},
259 |    "source": [
260 |     "Repeat with a dollar volume threshold of $1M USD."
261 |    ]
262 |   },
263 |   {
264 |    "cell_type": "code",
265 |    "execution_count": 10,
266 |    "metadata": {},
267 |    "outputs": [
268 |     {
269 |      "name": "stdout",
270 |      "output_type": "stream",
271 |      "text": [
272 |       "United States\n",
273 |       "Canada\n",
274 |       "Mexico\n",
275 |       "Australia\n",
276 |       "Japan\n",
277 |       "Hong Kong\n",
278 |       "Singapore\n",
279 |       "Spain\n",
280 |       "Netherlands\n",
281 |       "United Kingdom\n",
282 |       "Germany\n",
283 |       "France\n",
284 |       "Belgium\n",
285 |       "Switzerland\n",
286 |       "Austria\n",
287 |       "Sweden\n",
288 |       "Italy\n"
289 |      ]
290 |     }
291 |    ],
292 |    "source": [
293 |     "all_countries = {}\n",
294 |     "\n",
295 |     "for db, country in countries:\n",
296 |     "    print(country)\n",
297 |     "    all_countries[country] = get_shortable_ratio(db, min_dollar_volume=1000000)\n",
298 |     "    \n",
299 |     "shortable_ratios = pd.Series(all_countries, name=\"shortable\").to_frame()\n",
300 |     "shortable_ratios[\"not shortable\"] = 100 - shortable_ratios"
301 |    ]
302 |   },
303 |   {
304 |    "cell_type": "code",
305 |    "execution_count": 11,
306 |    "metadata": {},
307 |    "outputs": [
308 |     {
309 |      "data": {
310 |       "image/png": 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\n",
311 |       "text/plain": [
312 |        "<Figure size 1152x432 with 1 Axes>"
313 |       ]
314 |      },
315 |      "metadata": {},
316 |      "output_type": "display_data"
317 |     }
318 |    ],
319 |    "source": [
320 |     "ax = shortable_ratios.sort_index().plot(kind=\"bar\", stacked=True, title=\"Percentage of stocks with average daily dollar volume above $1M that are shortable\", figsize=(16,6))\n",
321 |     "ax.set_ylabel(\"Percentage of total\")\n",
322 |     "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))"
323 |    ]
324 |   },
325 |   {
326 |    "cell_type": "markdown",
327 |    "metadata": {},
328 |    "source": [
329 |     "Limit to stocks below $1M USD dollar volume:"
330 |    ]
331 |   },
332 |   {
333 |    "cell_type": "code",
334 |    "execution_count": 8,
335 |    "metadata": {},
336 |    "outputs": [
337 |     {
338 |      "name": "stdout",
339 |      "output_type": "stream",
340 |      "text": [
341 |       "United States\n",
342 |       "Canada\n",
343 |       "Mexico\n",
344 |       "Australia\n",
345 |       "Japan\n",
346 |       "Hong Kong\n",
347 |       "Singapore\n",
348 |       "Spain\n",
349 |       "Netherlands\n",
350 |       "United Kingdom\n",
351 |       "Germany\n",
352 |       "France\n",
353 |       "Belgium\n",
354 |       "Switzerland\n",
355 |       "Austria\n",
356 |       "Sweden\n",
357 |       "Italy\n"
358 |      ]
359 |     }
360 |    ],
361 |    "source": [
362 |     "all_countries = {}\n",
363 |     "\n",
364 |     "for db, country in countries:\n",
365 |     "    print(country)\n",
366 |     "    all_countries[country] = get_shortable_ratio(db, max_dollar_volume=1000000)\n",
367 |     "    \n",
368 |     "shortable_ratios = pd.Series(all_countries, name=\"shortable\").to_frame()\n",
369 |     "shortable_ratios[\"not shortable\"] = 100 - shortable_ratios"
370 |    ]
371 |   },
372 |   {
373 |    "cell_type": "code",
374 |    "execution_count": 9,
375 |    "metadata": {},
376 |    "outputs": [
377 |     {
378 |      "data": {
379 |       "text/plain": [
380 |        "<matplotlib.legend.Legend at 0x7fece7df68d0>"
381 |       ]
382 |      },
383 |      "execution_count": 9,
384 |      "metadata": {},
385 |      "output_type": "execute_result"
386 |     },
387 |     {
388 |      "data": {
389 |       "image/png": 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\n",
390 |       "text/plain": [
391 |        "<Figure size 1152x432 with 1 Axes>"
392 |       ]
393 |      },
394 |      "metadata": {},
395 |      "output_type": "display_data"
396 |     }
397 |    ],
398 |    "source": [
399 |     "ax = shortable_ratios.sort_index().plot(kind=\"bar\", stacked=True, title=\"Percentage of stocks with average daily dollar volume below $1M that are shortable\", figsize=(16,6))\n",
400 |     "ax.set_ylabel(\"Percentage of total\")\n",
401 |     "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))"
402 |    ]
403 |   },
404 |   {
405 |    "cell_type": "markdown",
406 |    "metadata": {},
407 |    "source": [
408 |     "***\n",
409 |     "\n",
410 |     "[Back to Introduction](Introduction.ipynb)"
411 |    ]
412 |   }
413 |  ],
414 |  "metadata": {
415 |   "kernelspec": {
416 |    "display_name": "Python 3.9",
417 |    "language": "python",
418 |    "name": "python3"
419 |   },
420 |   "language_info": {
421 |    "codemirror_mode": {
422 |     "name": "ipython",
423 |     "version": 3
424 |    },
425 |    "file_extension": ".py",
426 |    "mimetype": "text/x-python",
427 |    "name": "python",
428 |    "nbconvert_exporter": "python",
429 |    "pygments_lexer": "ipython3",
430 |    "version": "3.9.7"
431 |   }
432 |  },
433 |  "nbformat": 4,
434 |  "nbformat_minor": 4
435 | }
436 | 


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