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gjlr2000/smile-crypto-options.ipynb

Created April 25, 2019 10:18
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Smile Crypto Options.ipynb
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smile-crypto-options.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Smile Crypto Options.ipynb",
"version": "0.3.2",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/gjlr2000/37e8319316737109a016b30729d34db3/smile-crypto-options.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"metadata": {
"id": "PAFrQQfUoZSQ",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"import json\n",
"import requests\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "eu6cGNWjpFoc",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"deribit = \"https://www.deribit.com/api/v1/public/getsummary?instrument=all\"\n",
"\n",
"q = requests.get(url = deribit)\n",
" \n",
"q_json = q.json() \n"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "GcCZFnG1pXKM",
"colab_type": "code",
"outputId": "fb44ced2-15d1-46ae-d7d8-703c3068b68f",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 54
}
},
"cell_type": "code",
"source": [
"print (q_json)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
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'', 'volumeBtc': '', 'last': 0.1785, 'bidPrice': 0.163, 'askPrice': 0.1705, 'midPrice': 0.16675, 'markPrice': 0.1709, 'uPx': 3888.53, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-26APR19-2000-P', 'openInterest': 295.4, 'high': '', 'low': '', 'volume': '', 'volumeBtc': '', 'last': 0.0005, 'bidPrice': '', 'askPrice': 0.0005, 'midPrice': '', 'markPrice': 0.0002, 'uPx': 3888.53, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}], 'message': ''}\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "ZChI3u3cpnRV",
"colab_type": "code",
"outputId": "a3e06785-f270-4ac9-de4e-c37b95bfd710",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 71
}
},
"cell_type": "code",
"source": [
"print (q_json['result'])\n",
"q_data = q_json['result']\n",
"print (q_data[0])\n",
"\n",
"df = pd.DataFrame.from_records(q_data)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
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'volume': 6904309.0, 'volumeUsd': 69043090, 'volumeBtc': 17695.9025844, 'last': 3889.75, 'bidPrice': 3889.5, 'askPrice': 3889.75, 'midPrice': 3889.63, 'estDelPrice': 3894.96, 'markPrice': 3889.93, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-27SEP19-12000-P', 'openInterest': 6.1, 'high': '', 'low': '', 'volume': '', 'volumeBtc': '', 'last': 1.9095, 'bidPrice': 2.094, 'askPrice': 2.1345, 'midPrice': 2.11425, 'markPrice': 2.1089, 'uPx': 3864.91, 'uIx': 'BTC-28JUN19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-27SEP19-3000-P', 'openInterest': 537.6, 'high': 0.056, 'low': 0.056, 'volume': 15.0, 'volumeBtc': 15.0, 'last': 0.056, 'bidPrice': 0.0575, 'askPrice': 0.0595, 'midPrice': 0.058499999999999996, 'markPrice': 0.0589, 'uPx': 3864.91, 'uIx': 'BTC-28JUN19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-28JUN19-4500-C', 'openInterest': 341.7, 'high': 0.0535, 'low': 0.049, 'volume': 16.4, 'volumeBtc': 16.4, 'last': 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'markPrice': 0.0007, 'uPx': 3888.55, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-27SEP19-3500-C', 'openInterest': 336.9, 'high': 0.208, 'low': 0.205, 'volume': 1.9, 'volumeBtc': 1.9, 'last': 0.205, 'bidPrice': 0.2, 'askPrice': 0.2045, 'midPrice': 0.20224999999999999, 'markPrice': 0.2029, 'uPx': 3864.91, 'uIx': 'BTC-28JUN19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-26APR19-5500-P', 'openInterest': 1.0, 'high': '', 'low': '', 'volume': '', 'volumeBtc': '', 'last': 0.4535, 'bidPrice': 0.4155, 'askPrice': 0.426, 'midPrice': 0.42074999999999996, 'markPrice': 0.4156, 'uPx': 3888.55, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-26APR19-3250-C', 'openInterest': 32.0, 'high': '', 'low': '', 'volume': '', 'volumeBtc': '', 'last': 0.1785, 'bidPrice': 0.163, 'askPrice': 0.1705, 'midPrice': 0.16675, 'markPrice': 0.1709, 'uPx': 3888.53, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}, {'instrumentName': 'BTC-26APR19-2000-P', 'openInterest': 295.4, 'high': '', 'low': '', 'volume': '', 'volumeBtc': '', 'last': 0.0005, 'bidPrice': '', 'askPrice': 0.0005, 'midPrice': '', 'markPrice': 0.0002, 'uPx': 3888.53, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}]\n",
"{'instrumentName': 'BTC-26APR19-5000-C', 'openInterest': 519.6, 'high': 0.004, 'low': 0.0035, 'volume': 20.5, 'volumeBtc': 20.5, 'last': 0.0035, 'bidPrice': 0.002, 'askPrice': 0.0035, 'midPrice': 0.00275, 'markPrice': 0.0028, 'uPx': 3888.53, 'uIx': 'BTC-29MAR19', 'iR': 0.0, 'created': '2019-03-26 13:15:33 GMT'}\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "1KgmjH4aqLLs",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"\n",
"# new data frame with split value columns \n",
"new = df[\"instrumentName\"].str.split(\"-\", n = 4, expand = True) \n",
" \n",
"# making seperate first name column from new data frame \n",
"df[\"expiry\"]= new[1] \n",
" \n",
"# making seperate last name column from new data frame \n",
"df[\"strike\"]= pd.to_numeric(new[2]) \n",
"df['optionType']= new[3]\n",
"df['crypto'] = new[0]\n",
"\n",
"expiry_date = '29MAR19'\n",
"expiry_date = '26APR19'\n",
"\n",
"df[(df['expiry'] == expiry_date) & (df['optionType'] == 'C')].head()\n",
"\n",
"call_chain = df[(df['expiry'] == expiry_date) & (df['optionType'] == 'P')].sort_values(by=['strike'])\n",
"call_chain = df[(df['expiry'] == expiry_date) & (df['optionType'] == 'C')].sort_values(by=['strike'])\n",
"\n"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "ZI5lYzLhJ-ZR",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"call_chain['askPrice'] = pd.to_numeric(call_chain['askPrice'])\n",
"call_chain['bidPrice'] = pd.to_numeric(call_chain['bidPrice'])\n",
"call_chain['midPrice'] = pd.to_numeric(call_chain['midPrice'])"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "WEUjdWmUx0wj",
"colab_type": "code",
"outputId": "16cb1a14-f89a-4e29-9971-962b065c49a6",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 508
}
},
"cell_type": "code",
"source": [
"\n",
"#call_chain['midPrice'] = (call_chain['askPrice'] + call_chain['bidPrice'])/2\n",
"#price = 'askPrice'\n",
"price = 'midPrice'\n",
"#price = 'bidPrice'\n",
"\n",
"call_chain['butterfly'] = -2*call_chain[price] + call_chain[price].shift(-1) +call_chain[price].shift(1)\n",
"\n",
"call_chain['spread'] = -call_chain[price] + call_chain[price].shift(1)\n",
"call_chain['midStrike'] = (call_chain['strike'] + call_chain['strike'].shift(1))/2\n",
"call_chain['strikeSpread'] = ( call_chain['strike'] - call_chain['strike'].shift(1))\n",
"call_chain['spreadUSD'] = call_chain['spread'] * call_chain['uPx']\n",
"call_chain['butterflyUSD'] = call_chain['butterfly'] * ( call_chain['uPx'])\n",
"call_chain['impliedCumProb'] = (1 - call_chain['spreadUSD'] / call_chain['strikeSpread'])*100\n",
"call_chain['impliedRangeProb'] = (call_chain['butterflyUSD'] / call_chain['strikeSpread'])*100\n",
"call_chain['strikeReturn'] = (call_chain['strike'] - call_chain['uPx']) / call_chain['uPx']\n",
"call_chain['midStrikeReturn'] = (call_chain['midStrike'] - call_chain['uPx']) / call_chain['uPx']\n",
"\n",
"call_chain.tail()"
],
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
"data": {
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" <td>22.359047</td>\n",
" <td>84.445880</td>\n",
" <td>8.943619</td>\n",
" <td>0.157250</td>\n",
" <td>0.125104</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>0.0060</td>\n",
" <td>0.0050</td>\n",
" <td>2019-03-26 13:15:33 GMT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0065</td>\n",
" <td>0.0</td>\n",
" <td>BTC-26APR19-4750-C</td>\n",
" <td>0.006</td>\n",
" <td>...</td>\n",
" <td>0.00150</td>\n",
" <td>0.00425</td>\n",
" <td>4625.0</td>\n",
" <td>250.0</td>\n",
" <td>16.526253</td>\n",
" <td>5.832795</td>\n",
" <td>93.389499</td>\n",
" <td>2.333118</td>\n",
" <td>0.221541</td>\n",
" <td>0.189395</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.0035</td>\n",
" <td>0.0020</td>\n",
" <td>2019-03-26 13:15:33 GMT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.004</td>\n",
" <td>0.0</td>\n",
" <td>BTC-26APR19-5000-C</td>\n",
" <td>0.0035</td>\n",
" <td>...</td>\n",
" <td>0.00175</td>\n",
" <td>0.00275</td>\n",
" <td>4875.0</td>\n",
" <td>250.0</td>\n",
" <td>10.693457</td>\n",
" <td>6.804927</td>\n",
" <td>95.722617</td>\n",
" <td>2.721971</td>\n",
" <td>0.285833</td>\n",
" <td>0.253687</td>\n",
" </tr>\n",
" <tr>\n",
" <th>186</th>\n",
" <td>0.0025</td>\n",
" <td>0.0010</td>\n",
" <td>2019-03-26 13:15:33 GMT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.003</td>\n",
" <td>0.0</td>\n",
" <td>BTC-26APR19-5250-C</td>\n",
" <td>0.003</td>\n",
" <td>...</td>\n",
" <td>0.00050</td>\n",
" <td>0.00100</td>\n",
" <td>5125.0</td>\n",
" <td>250.0</td>\n",
" <td>3.888530</td>\n",
" <td>1.944265</td>\n",
" <td>98.444588</td>\n",
" <td>0.777706</td>\n",
" <td>0.350125</td>\n",
" <td>0.317979</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.0020</td>\n",
" <td>0.0005</td>\n",
" <td>2019-03-26 13:15:33 GMT</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0015</td>\n",
" <td>0.0</td>\n",
" <td>BTC-26APR19-5500-C</td>\n",
" <td>0.0015</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.00050</td>\n",
" <td>5375.0</td>\n",
" <td>250.0</td>\n",
" <td>1.944265</td>\n",
" <td>NaN</td>\n",
" <td>99.222294</td>\n",
" <td>NaN</td>\n",
" <td>0.414416</td>\n",
" <td>0.382270</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 34 columns</p>\n",
"</div>"
],
"text/plain": [
" askPrice bidPrice created currentFunding estDelPrice \\\n",
"54 0.0105 0.0090 2019-03-26 13:15:33 GMT NaN NaN \n",
"142 0.0060 0.0050 2019-03-26 13:15:33 GMT NaN NaN \n",
"0 0.0035 0.0020 2019-03-26 13:15:33 GMT NaN NaN \n",
"186 0.0025 0.0010 2019-03-26 13:15:33 GMT NaN NaN \n",
"2 0.0020 0.0005 2019-03-26 13:15:33 GMT NaN NaN \n",
"\n",
" funding8h high iR instrumentName last ... \\\n",
"54 NaN 0.012 0.0 BTC-26APR19-4500-C 0.01 ... \n",
"142 NaN 0.0065 0.0 BTC-26APR19-4750-C 0.006 ... \n",
"0 NaN 0.004 0.0 BTC-26APR19-5000-C 0.0035 ... \n",
"186 NaN 0.003 0.0 BTC-26APR19-5250-C 0.003 ... \n",
"2 NaN 0.0015 0.0 BTC-26APR19-5500-C 0.0015 ... \n",
"\n",
" butterfly spread midStrike strikeSpread spreadUSD butterflyUSD \\\n",
"54 0.00575 0.01000 4375.0 250.0 38.885300 22.359047 \n",
"142 0.00150 0.00425 4625.0 250.0 16.526253 5.832795 \n",
"0 0.00175 0.00275 4875.0 250.0 10.693457 6.804927 \n",
"186 0.00050 0.00100 5125.0 250.0 3.888530 1.944265 \n",
"2 NaN 0.00050 5375.0 250.0 1.944265 NaN \n",
"\n",
" impliedCumProb impliedRangeProb strikeReturn midStrikeReturn \n",
"54 84.445880 8.943619 0.157250 0.125104 \n",
"142 93.389499 2.333118 0.221541 0.189395 \n",
"0 95.722617 2.721971 0.285833 0.253687 \n",
"186 98.444588 0.777706 0.350125 0.317979 \n",
"2 99.222294 NaN 0.414416 0.382270 \n",
"\n",
"[5 rows x 34 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 29
}
]
},
{
"metadata": {
"id": "Tj-6eL6n_PQu",
"colab_type": "code",
"outputId": "868f0540-217e-4cc4-81bd-274f15b089c7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1354
}
},
"cell_type": "code",
"source": [
"#call_chain.plot.scatter(x = 'midStrike', y = 'impliedProb')\n",
"#plt.scatter(call_chain.midStrike, call_chain.impliedCumProb )\n",
"plt.plot(call_chain.midStrike, call_chain.impliedCumProb, linestyle = ':', marker = 'o' )\n",
"plt.show()\n",
"plt.plot(call_chain.midStrikeReturn, call_chain.impliedCumProb, linestyle = ':', marker = 'o' )\n",
"\n",
"\n",
"plt.show()\n",
"#plt.scatter(call_chain.strike, call_chain.impliedRangeProb )\n",
"#plt.plot(call_chain.strike, call_chain.impliedRangeProb, linestyle = ':', marker = 'o' )\n",
"plt.bar(call_chain.strike, call_chain.impliedRangeProb, width = 250*0.8)\n",
"plt.show()\n",
"\n",
"#plt.plot(call_chain.strikeReturn, call_chain.impliedRangeProb, linestyle = ':', marker = 'o' )\n",
"plt.bar(call_chain.strikeReturn, call_chain.impliedRangeProb, width = 1/20)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "display_data",
"data": {
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BAYQlwzA0Z+ZwfeOMoUqIi7a6HKBPEdYAwkLxpkqtKCpReVWTUpNidelZJ2ny6CyCGrZA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\nWAMAEOIIawAAQhxhDQBAiCOsAQAIcf8fy0B2Nop0uAoAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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Cju0QbGgD6/miDXocyB988IGefPJJPf3004qNjVVUVJQaGhoUERGhkpISpaam\ndnqN8vK6nn68pVyuWLnd1VaXEdTs2gaN9U1yJUQqNTbMlvX5ml3bIZjQBtbrTht0FNw9GrKurq7W\ngw8+qOXLlyshIUGSNG3aNOXk5EiS1q1bp5kzZ/bk0oBfO3Nggn5941QNSqPHAqB7etRDfvPNN1Ve\nXq7bbrvNe+z+++/XXXfdpRUrVigjI0OXXnqpz4oE7G7n/nINSotRVESoHA42/wDQfYbZ1QnfXuCv\nwywMEVnPTm1QWlmv//jjx3LFR2jZP08Jqt247NQOwYo2sJ6vhqzZqQs4TYmx4bpoyiClJUYGVRgD\n8C0CGThNIQ6Hvj9jiNVlAPBzBDLQTXk7SrQ2N1+FpbVKiAnXFecN07lj+lldFgA/RyAD3ZC3o0TL\n12z3vi6vbtQf3tghwzA0dXSahZUB8Hdssgt0w9rc/FMc39+ndQAIPAQy0A1Fpe1vZlNcVtvHlQAI\nNAQy0EWmaSoyvP2tXnneMYDTRSAD3TCsf3y7xxdkZfZxJQACDYu6gC4yDEO3Xj5OH31xSOs+Oaji\nslqlJ0drQVYmC7oAnDYCGejEuo8PKDLcqZnjM2QYhmaMS9eMcelWlwUgwBDIQAdq6pv119z9CnU6\nNHlUqiLC+CcDoHfwvwvQgZjIUN2ZPVEOh0EYA+hVLOoC2rFzf7nqG1skSf1dMayiBtDrCGTgW/Yf\nqtbDr3ymx1Z9IQsfhgYgyDAGB3zLgNRoTTsrXVNGpcrg6U0A+giBDHyjuaVVoc4QhTgcuuHikVaX\nAyDIMGQNSCp012jJ8o3astttdSkAghSBDEiqqmtWXUOLquuarS4FQJBiyBqQNCozUfffkqX46DCr\nSwEQpOghI2hV1jbp//62W80tHkkijAFYikBG0Frz4dda98lBbdx+yOpSAIAhawSvq84froGpMexL\nDcAW6CEjqDQ1t6rAXSNJCgsN0XkT+3OvMQBbIJARNEzT1JOvb9dvXtykgsM1VpcDACdgyBpBwzAM\nnTum7bnFaUlRFlcDACcikBHwPKYpQ22BPGVUmiaPZEtMAPbDkDUCmmmaevnd3XohZ5c83zwogjAG\nYEf0kBHQGppatftghVpNUw2NrYqK4K88AHvifycEtMhwp+7InqjmFg9hDMDWGLJGQPrw82KVHKmT\nJEVFhCo+JtziigCgYwQyAk6Bu0bPvvml/nf1NpnfzBsDgN0xhoeAM8AVo+suHKHh/eNZwAXAbxDI\nCBilFfVKSYiUJJ03sb/F1QBA9zBkjYCw60C5fvl0nt7YkG91KQDQI/SQ4Zfe31Kgl3N2qqi0Thkp\nUZo5PkMp8REa3C/W6tIAoEeHkDm4AAALqklEQVQIZPidvB0lWr5mu/d1gbtWL7+7Wzd9d5TGDk22\nsDIA6DmGrOF31ubmt3v8rY0H+7QOAPAlesiwpZr6Zh0qq9OgtBiFhYbI4zF1/0ublRAdpqLSunZ/\nT3FZbR9XCQC+Qw8ZlvB4jt0fXFHTqBV/363c7Ye8x9Z8+LXue3GTCkvbQtbhMFRR3aiqumZlpLT/\npKb05OjeLRoAehE9ZPRY3o4Src3N9y6sWpA1WFNHp51wTmVNo3YXVGpgWozSEtuC9NHXPteO/HI9\n/rNZcjgMeTymcj4+qMkjU5U1pp8k6ayhSXI6HYo+brvL+2/JksMwTppDPmpBVmbv/bAA0MsIZPRI\newurlq/Zrr9vLvBuzCFJuw5W6MnXt2vh3DM0f3JbICfGhmtgWozqm1oUHRGqhNhwLb3ubKUlRnqv\nN25YisYNSznhMx3fbPIxdXSa4uIi9HLOLhWX1So9OVoLsjJP+jIAAP6EQEaXNLd49HVxlUKdDg1J\njzvlwqp9RVUqr270vh6aEaerzh+ukZmJ3mPXXjDihN/jMAwN7x/frXpmTRygUQO693sAwM6YQ0a7\ntnzl1oq/7/Y+Q7i6rkn3/3mz3tq4X5JOubDKlHT/zVne1ynxkbpwyiANTI3p9ZoBwJ8RyEGqpdXj\n/fWBkmr9/tWt+uiLYu+xT3YdVs7HB1VaUS+pbZh5QVamd473VAurMpKj5XCwfzQAdBdD1n6us4VV\nLa0eHSqrU0JsuGIiQyVJD/x5sw5X1OuhRdMltQ0Zf763TP2SjoXsRVMG6fxJA5QYGyFJMgxDl80e\n5n1/QdZgFlYBgA8RyH7sVAur9hVVauG8MyVJ728t0ovrvtKNl4zStLPSJbX1dk21zQuHOh1KT4nS\nI7fO9Aa2JA1K63gLyqOhvzZ3PwurAMAHfB7I9913n7Zu3SrDMLR06VKNGzfO1x9xkq7cfuPvmppb\nddBdo8gwpzJS2u63feW9Pe2e+96WIm8gD8uI16zxGUqJP7aC+cffG3PC+SEOh2Iiuz97MXV0WsD9\nOQOAVXwayB9//LH279+vFStWaO/evVq6dKlWrFjhy484yal6iZL6LCxO9wtBRU2j8g9Va6ArRsnx\nbUPEf37nK+0vqdbSa8+WJJVVNejXz2/SrPHpuuHiUW2/77jVzMfzeI7ND2f2i9UNF4/s4U8GAOgr\nPl3UlZubq3nz5kmShg0bpsrKStXU1PjyI05yqttv1ua2rQZ+5e979N6WQu/xkvI6vb+1SIeOHFsl\nXHC4RnsLK727R3lMU9V1TWpqbu30849+IShw18pjmt4vBHk7SiRJ+w9V64PPi9TY1HatllaP7v3T\np3rqjWNfIrbtO6JHVn6uHflHTqjzQEm1Gr+pISk2QhdOGaixQ4/dm5ue0v7OVBkprGgGAH/j0x5y\naWmpxow5NhyalJQkt9utmJj2AyIxMUpOZ8hpfWZR2an3NU5KjtHbHx/Q2GEpuvKCtl7i5/nleu6t\nnfrplRM0dkRbL/aRVV/os6/cWvXAJQp1hqi8ukE3PvCepo/P0JJ/mixJWvvhPv3fO1/p59mT5HLF\nyuWK1X+/vFm5x61MPl7OJwd1yezhWrF+r3I27tc5Y9LlcrXNy5bXNCohNtz7+pyzpFbD0MSRqd5j\n/3nzNDlDHDKMYyuW//WqSSd8xjUXjdRvX9x00mcvvHCE9zqBLBh+Rn9AO1iPNrCeL9qgVxd1mabZ\n4fvl5e2HaXdkJEepwH3yQwXSk6NVWlqte26YLKfTIbe7WpLULz5cP1owSukJEd5jE4clq19ipMqP\n1MowDFXXNensES71T4rynlNf36SIsBDV1bYNE7vd1dqVf0T1jS3t1nWwpFpud7UmDktWRmKkWpta\nvNd66F+myTAM7+sIhzR7bD/vdbtq1IB43fy9MSctrBo1IL5b1/FHLldswP+M/oB2sB5tYL3utEFH\nwe3TQE5NTVVpaan39eHDh+VyuXz5ESfp6PYbh2Eo81sPrE9NjFJq4on30M4cn3HC69ioMC36wdgT\njs2e0F+zJ/Q/4di9N07Vf/wxT4Wn+EIgSWcOTNCZAxNOeO/4Xu/pYmEVAAQGn84hT58+XTk5OZKk\n7du3KzU19ZTD1b4ydXSabv7eGA1wxSjEYWiAK0Y3f29Mn4XUJVmD2z3O/bgAgO7waQ950qRJGjNm\njK6++moZhqF77rnHl5c/JSt7idyPCwDwBZ/PIf/iF7/w9SVtj2FjAMDpYi9rAABsgEAGAMAGCGQA\nAGyAQAYAwAYIZAAAbIBABgDABghkAABsgEAGAMAGCGQAAGzAMDt7JBMAAOh19JABALABAhkAABsg\nkAEAsAECGQAAGyCQAQCwAQIZAAAbcFpdgD9obm7WkiVLVFRUpJCQEP3mN7/RwIED2z335z//ucLC\nwnT//ff3cZWBrStt8Oabb+qZZ56Rw+FQVlaWfvazn1lUbeC57777tHXrVhmGoaVLl2rcuHHe9zZs\n2KCHH35YISEhmjVrlhYtWmRhpYGrozbYuHGjHn74YTkcDg0ZMkS//vWv5XDQ3/K1jtrgqIceekif\nffaZXnjhhe5/gIlOrVq1yly2bJlpmqb5wQcfmLfeemu753344YfmZZddZt555519WV5Q6KwN6urq\nzDlz5pjV1dWmx+MxL7/8cnP37t1WlBpw8vLyzB//+MemaZrmnj17zCuvvPKE9y+++GKzqKjIbG1t\nNRcuXMifey/orA3mz59vFhcXm6ZpmosXLzbXr1/f5zUGus7awDRNc/fu3eZVV11lXnvttT36DL5C\ndUFubq7mz58vSZo2bZo2b9580jlNTU164okn9JOf/KSvywsKnbVBZGSk1qxZo5iYGBmGoYSEBFVU\nVFhRasDJzc3VvHnzJEnDhg1TZWWlampqJEkHDx5UfHy80tPT5XA4NHv2bOXm5lpZbkDqqA0kadWq\nVerXr58kKSkpSeXl5ZbUGcg6awNJuv/++09rZI5A7oLS0lIlJSVJkhwOhwzDUFNT0wnnLF++XAsX\nLlRMTIwVJQa8rrTB0T/7Xbt2qbCwUOPHj+/zOgNRaWmpEhMTva+TkpLkdrslSW6329su334PvtNR\nG0jH/u4fPnxYH330kWbPnt3nNQa6ztpg1apVmjJlivr379/jz2AO+VteffVVvfrqqycc27p16wmv\nzW/tNpqfn69t27Zp8eLFysvL6/UaA11P2uCo/Px8/eIXv9BDDz2k0NDQXqsxmJ3qzx59p702KCsr\n0y233KJ77rnnhOBA7zi+DSoqKrRq1So9++yzKikp6fE1CeRvueKKK3TFFVeccGzJkiVyu90aOXKk\nmpubZZqmwsLCvO+vX79eRUVFuvLKK1VTU6MjR47oqaee0k033dTX5QeEnrSBJB06dEiLFi3Sgw8+\nqFGjRvVlyQEtNTVVpaWl3teHDx+Wy+Vq972SkhKlpqb2eY2BrqM2kKSamhrddNNNuu222zRjxgwr\nSgx4HbXBxo0bdeTIEV1zzTVqamrSgQMHdN9992np0qXd+gyGrLtg+vTpevvttyVJ7733nqZOnXrC\n+zfccIPeeOMNvfLKK7rnnnt03nnnEcY+1lkbSNIvf/lLLVu2TGPGjOnr8gLa9OnTlZOTI0navn27\nUlNTvUOkAwYMUE1NjQoKCtTS0qL33ntP06dPt7LcgNRRG0htc5fXX3+9Zs2aZVWJAa+jNrjooov0\n5ptv6pVXXtFjjz2mMWPGdDuMJXrIXfKd73xHGzZs0MKFC0+4pekPf/iDJk+erIkTJ1pcYeDrrA0S\nEhL06aef6pFHHvH+nhtuuEFz5861quSAMWnSJI0ZM0ZXX321DMPQPffco1WrVik2Nlbz58/XsmXL\ndPvtt0tqa6chQ4ZYXHHg6agNZsyYodWrV2v//v1auXKlJOmSSy7RVVddZXHVgaWzfwe+wOMXAQCw\nAYasAQCwAQIZAAAbIJABALABAhkAABsgkAEAsAECGQAAGyCQAQCwAQIZAAAb+P97PtqGrgaD+gAA\nAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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339bOnTsDt8vLy/XZZ58Fbg8YMEBDhgwJ3H7ttdcUExPTgjEBAMCPhVXiU6dO1dSpUyVJ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\nTkSuQmCC\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<BarContainer object of 15 artists>"
]
},
"metadata": {
"tags": []
},
"execution_count": 30
},
{
"output_type": "display_data",
"data": {
"image/png": 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37tW+ffv8y2VlZfrkk0/8y7GxsYqLi/Mvv/322woNDW1HmQAABA9L4Txt2jRNmzZNknT8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\nQmCC\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"metadata": {
"id": "r6IlnNy0m6lz",
"colab_type": "code",
"outputId": "0de20555-4745-4590-820e-9068c6fae710",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 514
}
},
"cell_type": "code",
"source": [
"call_chain[['midStrikeReturn', 'impliedCumProb']].head(50)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
"data": {
"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>midStrikeReturn</th>\n",
" <th>impliedCumProb</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>67</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>-0.453521</td>\n",
" <td>0.064779</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-0.389229</td>\n",
" <td>-0.324074</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>-0.324938</td>\n",
" <td>0.842485</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>-0.260646</td>\n",
" <td>2.786750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>-0.196354</td>\n",
" <td>4.342162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>117</th>\n",
" <td>-0.132063</td>\n",
" <td>16.396605</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>-0.067771</td>\n",
" <td>32.728431</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>-0.003479</td>\n",
" <td>51.393375</td>\n",
" </tr>\n",
" <tr>\n",
" <th>171</th>\n",
" <td>0.060812</td>\n",
" <td>70.836025</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>0.125104</td>\n",
" <td>84.445880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>0.189395</td>\n",
" <td>93.389499</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.253687</td>\n",
" <td>95.722617</td>\n",
" </tr>\n",
" <tr>\n",
" <th>186</th>\n",
" <td>0.317979</td>\n",
" <td>98.444588</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.382270</td>\n",
" <td>99.222294</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" midStrikeReturn impliedCumProb\n",
"67 NaN NaN\n",
"126 -0.453521 0.064779\n",
"3 -0.389229 -0.324074\n",
"40 -0.324938 0.842485\n",
"74 -0.260646 2.786750\n",
"197 -0.196354 4.342162\n",
"117 -0.132063 16.396605\n",
"76 -0.067771 32.728431\n",
"66 -0.003479 51.393375\n",
"171 0.060812 70.836025\n",
"54 0.125104 84.445880\n",
"142 0.189395 93.389499\n",
"0 0.253687 95.722617\n",
"186 0.317979 98.444588\n",
"2 0.382270 99.222294"
]
},
"metadata": {
"tags": []
},
"execution_count": 31
}
]
},
{
"metadata": {
"id": "QUEYY7pQu7bS",
"colab_type": "code",
"outputId": "2a385446-3a72-4855-ed2b-ee1180d38ee7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 728
}
},
"cell_type": "code",
"source": [
"#print (24*60/5, np.sqrt(24*60/5), 7/17)\n",
"days_to_expiry = 31\n",
"trading_hours_per_day = 7.5\n",
"trading_hours_per_day = 24\n",
"\n",
"minutes_to_expiry = days_to_expiry*trading_hours_per_day*60\n",
"time_factor = np.sqrt(minutes_to_expiry) / 100\n",
"\n",
"print(call_chain['midStrikeReturn'].iloc[1])\n",
"print(100 * call_chain['midStrikeReturn'].iloc[1] / np.sqrt(minutes_to_expiry))\n",
"\n",
"\n",
"plt.plot(call_chain.midStrikeReturn / time_factor, call_chain.impliedCumProb, linestyle = ':', marker = 'o' )\n",
"\n",
"\n",
"plt.show()\n",
"\n",
"#plt.plot(call_chain.strikeReturn, call_chain.impliedRangeProb, linestyle = ':', marker = 'o' )\n",
"plt.bar(call_chain.strikeReturn/ time_factor, call_chain.impliedRangeProb, width = 1/20)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"-0.4535209963662361\n",
"-0.21465218080476992\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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cbrfvqgT8SHlVo6TO4I6LYVgcgO/0ayLa3//+d23YsEFPPPGEzjvvPM920+zb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\nh38+WyXwAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<BarContainer object of 15 artists>"
]
},
"metadata": {
"tags": []
},
"execution_count": 38
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 576x396 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
}
]
}
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