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linanqiu/Options Homework.ipynb

Created October 15, 2018 02:31
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Options Homework.ipynb
{
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"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [],
"source": [
"import pandas\n",
"import math\n",
"\n",
"import matplotlib.pyplot as plt\n",
"plt.style.use('ggplot')\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'svg'"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [],
"source": [
"class Call:\n",
" def __init__(self, strike, direction):\n",
" self.strike = strike\n",
" self.direction = direction\n",
" self.sec = 'Call %s @%s' % (self.direction, self.strike)\n",
" \n",
" def value_at(self, price):\n",
" value = max(price - self.strike, 0)\n",
" if (self.direction == 'buy'):\n",
" return value\n",
" else:\n",
" return -value\n",
"\n",
"class Put:\n",
" def __init__(self, strike, direction):\n",
" self.strike = strike\n",
" self.direction = direction\n",
" self.sec = 'Put %s @%s' % (self.direction, self.strike)\n",
" \n",
" def value_at(self, price):\n",
" value = max(self.strike - price, 0)\n",
" if (self.direction == 'buy'):\n",
" return value\n",
" else:\n",
" return -value"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"7\n",
"0\n",
"0\n",
"3\n",
"Put buy @150\n"
]
}
],
"source": [
"# tests\n",
"c_test_in = Call(150, 'buy')\n",
"c_test_out = Call(160, 'buy')\n",
"print(c_test_in.value_at(157))\n",
"print(c_test_out.value_at(157))\n",
"\n",
"p_test_in = Put(150, 'buy')\n",
"p_test_out = Put(160, 'buy')\n",
"print(p_test_in.value_at(157))\n",
"print(p_test_out.value_at(157))\n",
"print(p_test_in.sec)"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [],
"source": [
"def calculate_data(options, prices):\n",
" values = []\n",
" for price in prices:\n",
" portfolio_value = {}\n",
" portfolio_value['price'] = price\n",
" option_values = portfolio_value_at(options, price)\n",
" value_sum = 0\n",
" for option in options:\n",
" option_value = option.value_at(price)\n",
" portfolio_value[option.sec] = option_value\n",
" value_sum += option_value\n",
" portfolio_value['portfolio_value'] = value_sum\n",
" values.append(portfolio_value)\n",
"\n",
" data = pandas.DataFrame.from_dict(values).set_index('price')\n",
" return data"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"options = [\n",
" Put(140, 'buy'),\n",
" Put(145, 'sell'),\n",
" Call(145, 'buy'),\n",
" Call(150, 'sell'),\n",
" Call(160, 'sell'),\n",
" Call(170, 'buy')\n",
"]\n",
"\n",
"prices = range(130, 180)\n",
"\n",
"data_hw = calculate_data(options, prices)\n",
"data_hw[['portfolio_value']].plot()"
]
}
],
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"kernelspec": {
"display_name": "Python 3",
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