{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8b4405f3-ff20-45fc-b83b-8ab976285d28",
   "metadata": {},
   "source": [
    "# Coin Metrics Options Data Aggregation\n",
    "\n",
    "This notebook demonstrates basic functionality offered by the Coin Metrics Python API Client and Market Data Feed.\n",
    "\n",
    "Coin Metrics offers a vast assortment of data for hundreds of cryptoassets. The Python API Client allows for easy access to this data using Python without needing to create your own wrappers using `requests` and other such libraries.\n",
    "\n",
    "## Resources\n",
    "To understand the data that Coin Metrics offers, feel free to peruse the resources below.\n",
    "\n",
    "- The [Coin Metrics API v4](https://docs.coinmetrics.io/api/v4) website contains the full set of endpoints and data offered by Coin Metrics.\n",
    "- The [Coin Metrics Product Documentation](https://docs.coinmetrics.io/info) gives detailed, conceptual explanations of the data that Coin Metrics offers.\n",
    "- The [API Spec](https://docs.coinmetrics.io/python-api-client/reference) contains a full list of functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16c3476d-c33a-421e-811e-344b59735ec0",
   "metadata": {},
   "source": [
    "## Notebook Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7fbd2927-9184-41fd-8403-b259146ee1a2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:24.591193Z",
     "start_time": "2022-11-16T14:57:23.980726Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from os import environ\n",
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import logging\n",
    "from datetime import date, datetime, timedelta\n",
    "from coinmetrics.api_client import CoinMetricsClient\n",
    "import json\n",
    "import logging\n",
    "from datetime import timezone as timezone_info\n",
    "import matplotlib.ticker as mticker\n",
    "from matplotlib.ticker import ScalarFormatter\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "%matplotlib inline\n",
    "from plotly import graph_objects as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6ab06f8c-e7f4-41b4-b92e-18a3de36a427",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:24.598125Z",
     "start_time": "2022-11-16T14:57:24.593576Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sns.set_theme()\n",
    "sns.set(rc={'figure.figsize':(14,8)})\n",
    "sns.set_style(\"whitegrid\",{'axes.grid' : True,'grid.linestyle': '--', 'grid.color': 'gray','axes.edgecolor': 'white'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "abc14b24-03f4-457c-94aa-0c33ff01c79b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:24.608563Z",
     "start_time": "2022-11-16T14:57:24.599825Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "logging.basicConfig(\n",
    "    format='%(asctime)s %(levelname)-8s %(message)s',\n",
    "    level=logging.INFO,\n",
    "    datefmt='%Y-%m-%d %H:%M:%S'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ecbe22c4-ee5a-4130-bc7f-9bf9a61b4bc1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:24.618734Z",
     "start_time": "2022-11-16T14:57:24.610018Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-09-11 13:31:07 INFO     Using API key found in environment\n"
     ]
    }
   ],
   "source": [
    "# We recommend privately storing your API key in your local environment.\n",
    "try:\n",
    "    api_key = environ[\"CM_API_KEY\"]\n",
    "    logging.info(\"Using API key found in environment\")\n",
    "except KeyError:\n",
    "    api_key = \"\"\n",
    "    logging.info(\"API key not found. Using community client\")\n",
    "\n",
    "client = CoinMetricsClient(api_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1547e1da-58b8-443c-9891-ea197cb0fbf1",
   "metadata": {},
   "source": [
    "### Set start and end time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c937993f-7db3-4387-a68a-7cd5d905f11c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:24.628090Z",
     "start_time": "2022-11-16T14:57:24.620118Z"
    }
   },
   "outputs": [],
   "source": [
    "end = datetime.utcnow()\n",
    "start = '2024-09-01'\n",
    "end = '2024-09-08'\n",
    "asset = 'eth'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6aadff2-e4fd-4d28-b9b0-b479031b91b3",
   "metadata": {},
   "source": [
    "## OPTIONS CATALOG"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b170944b-caa1-44c1-973f-fc9790147aa8",
   "metadata": {},
   "source": [
    "To simplify some of the complexity around options contract size, we will investigate only options markets on Deribit, the largest options exchange by volume."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "261c7729-d184-42f9-a759-d6c04e77b9cb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:25.901909Z",
     "start_time": "2022-11-16T14:57:24.629497Z"
    }
   },
   "outputs": [],
   "source": [
    "asset_options = client.reference_data_markets(\n",
    "    type='option',\n",
    "    exchange='deribit',\n",
    "    base='eth',\n",
    "    quote='usd',\n",
    "    page_size=10000\n",
    ").to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fecf2988-993e-4559-81c0-c1f3f82fb929",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:25.913395Z",
     "start_time": "2022-11-16T14:57:25.905728Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of supported options markets: 74751\n"
     ]
    }
   ],
   "source": [
    "print('Total number of supported options markets: ' + str(len(asset_options)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58e5d014-3c70-4b4b-ac2d-d4e02d72c732",
   "metadata": {},
   "source": [
    "### Filter out expired/inactive contracts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8cb70fed-b993-4cb6-abbe-a16e4e2861b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_asset_options = pd.DataFrame(asset_options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b1f5f80b-89a2-4863-bae7-b06a6e8b8c6f",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>exchange</th>\n",
       "      <th>type</th>\n",
       "      <th>base</th>\n",
       "      <th>quote</th>\n",
       "      <th>pair</th>\n",
       "      <th>symbol</th>\n",
       "      <th>size_asset</th>\n",
       "      <th>strike</th>\n",
       "      <th>option_contract_type</th>\n",
       "      <th>...</th>\n",
       "      <th>listing</th>\n",
       "      <th>expiration</th>\n",
       "      <th>settlement_price</th>\n",
       "      <th>status</th>\n",
       "      <th>order_amount_min</th>\n",
       "      <th>order_price_increment</th>\n",
       "      <th>order_taker_fee</th>\n",
       "      <th>order_maker_fee</th>\n",
       "      <th>base_native</th>\n",
       "      <th>quote_native</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-ETH-10APR20-100-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
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       "      <td>ETH-10APR20-100-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>100</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-03-26T08:00:02.000000000Z</td>\n",
       "      <td>2020-04-10T08:00:00.000000000Z</td>\n",
       "      <td>158.1</td>\n",
       "      <td>offline</td>\n",
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       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-ETH-10APR20-110-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10APR20-110-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>110</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-03-26T08:00:02.000000000Z</td>\n",
       "      <td>2020-04-10T08:00:00.000000000Z</td>\n",
       "      <td>158.1</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-ETH-10APR20-120-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10APR20-120-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>120</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-03-26T08:00:02.000000000Z</td>\n",
       "      <td>2020-04-10T08:00:00.000000000Z</td>\n",
       "      <td>158.1</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-ETH-10APR20-120-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10APR20-120-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>120</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-03-26T08:00:02.000000000Z</td>\n",
       "      <td>2020-04-10T08:00:00.000000000Z</td>\n",
       "      <td>158.1</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-ETH-10APR20-130-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10APR20-130-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>130</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2020-03-26T08:00:02.000000000Z</td>\n",
       "      <td>2020-04-10T08:00:00.000000000Z</td>\n",
       "      <td>158.1</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             market exchange    type base quote     pair  \\\n",
       "0  deribit-ETH-10APR20-100-P-option  deribit  option  eth   usd  eth-usd   \n",
       "1  deribit-ETH-10APR20-110-P-option  deribit  option  eth   usd  eth-usd   \n",
       "2  deribit-ETH-10APR20-120-C-option  deribit  option  eth   usd  eth-usd   \n",
       "3  deribit-ETH-10APR20-120-P-option  deribit  option  eth   usd  eth-usd   \n",
       "4  deribit-ETH-10APR20-130-C-option  deribit  option  eth   usd  eth-usd   \n",
       "\n",
       "              symbol size_asset strike option_contract_type  ...  \\\n",
       "0  ETH-10APR20-100-P        eth    100                  put  ...   \n",
       "1  ETH-10APR20-110-P        eth    110                  put  ...   \n",
       "2  ETH-10APR20-120-C        eth    120                 call  ...   \n",
       "3  ETH-10APR20-120-P        eth    120                  put  ...   \n",
       "4  ETH-10APR20-130-C        eth    130                 call  ...   \n",
       "\n",
       "                          listing                      expiration  \\\n",
       "0  2020-03-26T08:00:02.000000000Z  2020-04-10T08:00:00.000000000Z   \n",
       "1  2020-03-26T08:00:02.000000000Z  2020-04-10T08:00:00.000000000Z   \n",
       "2  2020-03-26T08:00:02.000000000Z  2020-04-10T08:00:00.000000000Z   \n",
       "3  2020-03-26T08:00:02.000000000Z  2020-04-10T08:00:00.000000000Z   \n",
       "4  2020-03-26T08:00:02.000000000Z  2020-04-10T08:00:00.000000000Z   \n",
       "\n",
       "  settlement_price   status order_amount_min order_price_increment  \\\n",
       "0            158.1  offline                1                0.0005   \n",
       "1            158.1  offline                1                0.0005   \n",
       "2            158.1  offline                1                0.0005   \n",
       "3            158.1  offline                1                0.0005   \n",
       "4            158.1  offline                1                0.0005   \n",
       "\n",
       "  order_taker_fee order_maker_fee base_native quote_native  \n",
       "0          0.0004          0.0004         NaN          NaN  \n",
       "1          0.0004          0.0004         NaN          NaN  \n",
       "2          0.0004          0.0004         NaN          NaN  \n",
       "3          0.0004          0.0004         NaN          NaN  \n",
       "4          0.0004          0.0004         NaN          NaN  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_asset_options.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2d31a696-6899-46dc-982a-6827ae1ab529",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 74751 entries, 0 to 74750\n",
      "Data columns (total 22 columns):\n",
      " #   Column                 Non-Null Count  Dtype \n",
      "---  ------                 --------------  ----- \n",
      " 0   market                 74751 non-null  object\n",
      " 1   exchange               74751 non-null  object\n",
      " 2   type                   74751 non-null  object\n",
      " 3   base                   74751 non-null  object\n",
      " 4   quote                  74751 non-null  object\n",
      " 5   pair                   74751 non-null  object\n",
      " 6   symbol                 74751 non-null  object\n",
      " 7   size_asset             74751 non-null  object\n",
      " 8   strike                 74751 non-null  object\n",
      " 9   option_contract_type   74751 non-null  object\n",
      " 10  is_european            74751 non-null  bool  \n",
      " 11  contract_size          74751 non-null  object\n",
      " 12  listing                74751 non-null  object\n",
      " 13  expiration             74751 non-null  object\n",
      " 14  settlement_price       74065 non-null  object\n",
      " 15  status                 74751 non-null  object\n",
      " 16  order_amount_min       74751 non-null  object\n",
      " 17  order_price_increment  74751 non-null  object\n",
      " 18  order_taker_fee        74751 non-null  object\n",
      " 19  order_maker_fee        74751 non-null  object\n",
      " 20  base_native            3482 non-null   object\n",
      " 21  quote_native           3482 non-null   object\n",
      "dtypes: bool(1), object(21)\n",
      "memory usage: 12.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df_asset_options.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c1efbc82-df9a-4eee-9291-8e4d7108690a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:26.198675Z",
     "start_time": "2022-11-16T14:57:25.985106Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>exchange</th>\n",
       "      <th>type</th>\n",
       "      <th>base</th>\n",
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       "      <th>base_native</th>\n",
       "      <th>quote_native</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2384</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10SEP24-1950-C</td>\n",
       "      <td>eth</td>\n",
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       "      <td>...</td>\n",
       "      <td>2024-09-07 08:00:09+00:00</td>\n",
       "      <td>2024-09-10 08:00:00+00:00</td>\n",
       "      <td>2360.48</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2385</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10SEP24-1950-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>1950</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-07 08:00:09+00:00</td>\n",
       "      <td>2024-09-10 08:00:00+00:00</td>\n",
       "      <td>2360.48</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2386</th>\n",
       "      <td>deribit-ETH-10SEP24-2000-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10SEP24-2000-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>2000</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-07 08:00:09+00:00</td>\n",
       "      <td>2024-09-10 08:00:00+00:00</td>\n",
       "      <td>2360.48</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2387</th>\n",
       "      <td>deribit-ETH-10SEP24-2000-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10SEP24-2000-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>2000</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-07 08:00:09+00:00</td>\n",
       "      <td>2024-09-10 08:00:00+00:00</td>\n",
       "      <td>2360.48</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2388</th>\n",
       "      <td>deribit-ETH-10SEP24-2050-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-10SEP24-2050-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>2050</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-07 08:00:09+00:00</td>\n",
       "      <td>2024-09-10 08:00:00+00:00</td>\n",
       "      <td>2360.48</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74746</th>\n",
       "      <td>deribit-ETH-9SEP24-2800-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-9SEP24-2800-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>2800</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-06 08:00:10+00:00</td>\n",
       "      <td>2024-09-09 08:00:00+00:00</td>\n",
       "      <td>2311.75</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74747</th>\n",
       "      <td>deribit-ETH-9SEP24-2850-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-9SEP24-2850-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>2850</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-06 08:00:10+00:00</td>\n",
       "      <td>2024-09-09 08:00:00+00:00</td>\n",
       "      <td>2311.75</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74748</th>\n",
       "      <td>deribit-ETH-9SEP24-2850-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-9SEP24-2850-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>2850</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-06 08:00:10+00:00</td>\n",
       "      <td>2024-09-09 08:00:00+00:00</td>\n",
       "      <td>2311.75</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74749</th>\n",
       "      <td>deribit-ETH-9SEP24-2900-C-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-9SEP24-2900-C</td>\n",
       "      <td>eth</td>\n",
       "      <td>2900</td>\n",
       "      <td>call</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-06 10:37:00+00:00</td>\n",
       "      <td>2024-09-09 08:00:00+00:00</td>\n",
       "      <td>2311.75</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74750</th>\n",
       "      <td>deribit-ETH-9SEP24-2900-P-option</td>\n",
       "      <td>deribit</td>\n",
       "      <td>option</td>\n",
       "      <td>eth</td>\n",
       "      <td>usd</td>\n",
       "      <td>eth-usd</td>\n",
       "      <td>ETH-9SEP24-2900-P</td>\n",
       "      <td>eth</td>\n",
       "      <td>2900</td>\n",
       "      <td>put</td>\n",
       "      <td>...</td>\n",
       "      <td>2024-09-06 10:37:00+00:00</td>\n",
       "      <td>2024-09-09 08:00:00+00:00</td>\n",
       "      <td>2311.75</td>\n",
       "      <td>offline</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>ETH</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>376 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  market exchange    type base quote     pair  \\\n",
       "2384   deribit-ETH-10SEP24-1950-C-option  deribit  option  eth   usd  eth-usd   \n",
       "2385   deribit-ETH-10SEP24-1950-P-option  deribit  option  eth   usd  eth-usd   \n",
       "2386   deribit-ETH-10SEP24-2000-C-option  deribit  option  eth   usd  eth-usd   \n",
       "2387   deribit-ETH-10SEP24-2000-P-option  deribit  option  eth   usd  eth-usd   \n",
       "2388   deribit-ETH-10SEP24-2050-C-option  deribit  option  eth   usd  eth-usd   \n",
       "...                                  ...      ...     ...  ...   ...      ...   \n",
       "74746   deribit-ETH-9SEP24-2800-P-option  deribit  option  eth   usd  eth-usd   \n",
       "74747   deribit-ETH-9SEP24-2850-C-option  deribit  option  eth   usd  eth-usd   \n",
       "74748   deribit-ETH-9SEP24-2850-P-option  deribit  option  eth   usd  eth-usd   \n",
       "74749   deribit-ETH-9SEP24-2900-C-option  deribit  option  eth   usd  eth-usd   \n",
       "74750   deribit-ETH-9SEP24-2900-P-option  deribit  option  eth   usd  eth-usd   \n",
       "\n",
       "                   symbol size_asset strike option_contract_type  ...  \\\n",
       "2384   ETH-10SEP24-1950-C        eth   1950                 call  ...   \n",
       "2385   ETH-10SEP24-1950-P        eth   1950                  put  ...   \n",
       "2386   ETH-10SEP24-2000-C        eth   2000                 call  ...   \n",
       "2387   ETH-10SEP24-2000-P        eth   2000                  put  ...   \n",
       "2388   ETH-10SEP24-2050-C        eth   2050                 call  ...   \n",
       "...                   ...        ...    ...                  ...  ...   \n",
       "74746   ETH-9SEP24-2800-P        eth   2800                  put  ...   \n",
       "74747   ETH-9SEP24-2850-C        eth   2850                 call  ...   \n",
       "74748   ETH-9SEP24-2850-P        eth   2850                  put  ...   \n",
       "74749   ETH-9SEP24-2900-C        eth   2900                 call  ...   \n",
       "74750   ETH-9SEP24-2900-P        eth   2900                  put  ...   \n",
       "\n",
       "                        listing                expiration settlement_price  \\\n",
       "2384  2024-09-07 08:00:09+00:00 2024-09-10 08:00:00+00:00          2360.48   \n",
       "2385  2024-09-07 08:00:09+00:00 2024-09-10 08:00:00+00:00          2360.48   \n",
       "2386  2024-09-07 08:00:09+00:00 2024-09-10 08:00:00+00:00          2360.48   \n",
       "2387  2024-09-07 08:00:09+00:00 2024-09-10 08:00:00+00:00          2360.48   \n",
       "2388  2024-09-07 08:00:09+00:00 2024-09-10 08:00:00+00:00          2360.48   \n",
       "...                         ...                       ...              ...   \n",
       "74746 2024-09-06 08:00:10+00:00 2024-09-09 08:00:00+00:00          2311.75   \n",
       "74747 2024-09-06 08:00:10+00:00 2024-09-09 08:00:00+00:00          2311.75   \n",
       "74748 2024-09-06 08:00:10+00:00 2024-09-09 08:00:00+00:00          2311.75   \n",
       "74749 2024-09-06 10:37:00+00:00 2024-09-09 08:00:00+00:00          2311.75   \n",
       "74750 2024-09-06 10:37:00+00:00 2024-09-09 08:00:00+00:00          2311.75   \n",
       "\n",
       "        status order_amount_min order_price_increment order_taker_fee  \\\n",
       "2384   offline                1                0.0001          0.0003   \n",
       "2385   offline                1                0.0001          0.0003   \n",
       "2386   offline                1                0.0001          0.0003   \n",
       "2387   offline                1                0.0001          0.0003   \n",
       "2388   offline                1                0.0001          0.0003   \n",
       "...        ...              ...                   ...             ...   \n",
       "74746  offline                1                0.0001          0.0003   \n",
       "74747  offline                1                0.0001          0.0003   \n",
       "74748  offline                1                0.0001          0.0003   \n",
       "74749  offline                1                0.0001          0.0003   \n",
       "74750  offline                1                0.0001          0.0003   \n",
       "\n",
       "      order_maker_fee base_native quote_native  \n",
       "2384           0.0003         ETH          USD  \n",
       "2385           0.0003         ETH          USD  \n",
       "2386           0.0003         ETH          USD  \n",
       "2387           0.0003         ETH          USD  \n",
       "2388           0.0003         ETH          USD  \n",
       "...               ...         ...          ...  \n",
       "74746          0.0003         ETH          USD  \n",
       "74747          0.0003         ETH          USD  \n",
       "74748          0.0003         ETH          USD  \n",
       "74749          0.0003         ETH          USD  \n",
       "74750          0.0003         ETH          USD  \n",
       "\n",
       "[376 rows x 22 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_asset_options['listing'] = pd.to_datetime(df_asset_options['listing'])\n",
    "df_asset_options['expiration'] = pd.to_datetime(df_asset_options['expiration'])\n",
    "\n",
    "df_asset_options = df_asset_options.loc[((df_asset_options.listing > start) & (df_asset_options.listing < end))]\n",
    "df_asset_options"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c021ebeb-9d09-4d10-a0fc-2abb2b7ef12f",
   "metadata": {},
   "source": [
    "# TRADE VOLUME"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29e75689-7b56-4a12-b33a-f4f0d3148ac6",
   "metadata": {},
   "source": [
    "On Deribit, each option contract provides notional exposure to 1 unit of the underlying asset (i.e. 1 BTC or 1 ETH). To calculate options volume, we must multiply the 'amount' field (representing the number of contracts traded) by the USD price of the underlying asset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "008902fe-6e82-483f-a243-aebd6ab8578e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T14:57:26.214221Z",
     "start_time": "2022-11-16T14:57:26.200468Z"
    }
   },
   "outputs": [],
   "source": [
    "list_options_markets = list(df_asset_options.market.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "47766dca-a700-4794-9ae0-50b82a0dad81",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:40:48.068301Z",
     "start_time": "2022-11-16T14:57:26.215907Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Retrieving batch of trades for markets 0 - 420...\n",
      "Retrieved batch of 12012 trades\n",
      "Total of 12012 trades\n",
      "\n"
     ]
    }
   ],
   "source": [
    "full_vol = pd.DataFrame()\n",
    "batch_size = 420\n",
    "\n",
    "for i in range(0, len(list_options_markets),batch_size):\n",
    "    mkt_batch = list_options_markets[i:i+batch_size]\n",
    "    print(str('Retrieving batch of trades for markets ' + str(i) + ' - ' + str(i+batch_size) + '...'))\n",
    "\n",
    "    vol_batch = client.get_market_trades(\n",
    "        markets=mkt_batch,\n",
    "        start_time = start,\n",
    "        end_time= end,\n",
    "        page_size=10000\n",
    "    ).to_dataframe()\n",
    "    print('Retrieved batch of ' + str(len(vol_batch)) + ' trades')\n",
    "    \n",
    "    full_vol = pd.concat((full_vol, vol_batch), axis = 0, ignore_index=False)\n",
    "    print('Total of ' + str(len(full_vol)) + ' trades\\n')\n",
    "\n",
    "full_vol = full_vol.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4de1da7b-9849-43c2-b15d-fa379a4b14d0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:40:48.296634Z",
     "start_time": "2022-11-16T15:40:48.070191Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>time</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>deribit-ETH-3SEP24-2375-P-option</td>\n",
       "      <td>2024-09-01 06:55:13.947000+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1072</th>\n",
       "      <td>deribit-ETH-3SEP24-2375-P-option</td>\n",
       "      <td>2024-09-01 08:04:42.145000+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1073</th>\n",
       "      <td>deribit-ETH-3SEP24-2375-P-option</td>\n",
       "      <td>2024-09-01 08:07:41.254000+00:00</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2429</th>\n",
       "      <td>deribit-ETH-4SEP24-2550-C-option</td>\n",
       "      <td>2024-09-01 08:33:21.911000+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2805</th>\n",
       "      <td>deribit-ETH-4SEP24-2700-C-option</td>\n",
       "      <td>2024-09-01 08:47:26.803000+00:00</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11208</th>\n",
       "      <td>deribit-ETH-9SEP24-2300-C-option</td>\n",
       "      <td>2024-09-07 23:54:16.170000+00:00</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9225</th>\n",
       "      <td>deribit-ETH-8SEP24-2325-C-option</td>\n",
       "      <td>2024-09-07 23:54:52.991000+00:00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8166</th>\n",
       "      <td>deribit-ETH-8SEP24-2050-P-option</td>\n",
       "      <td>2024-09-07 23:57:33.509000+00:00</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9650</th>\n",
       "      <td>deribit-ETH-8SEP24-2400-C-option</td>\n",
       "      <td>2024-09-07 23:58:04.697000+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9651</th>\n",
       "      <td>deribit-ETH-8SEP24-2400-C-option</td>\n",
       "      <td>2024-09-07 23:58:53.038000+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10824 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market                             time  \\\n",
       "1071   deribit-ETH-3SEP24-2375-P-option 2024-09-01 06:55:13.947000+00:00   \n",
       "1072   deribit-ETH-3SEP24-2375-P-option 2024-09-01 08:04:42.145000+00:00   \n",
       "1073   deribit-ETH-3SEP24-2375-P-option 2024-09-01 08:07:41.254000+00:00   \n",
       "2429   deribit-ETH-4SEP24-2550-C-option 2024-09-01 08:33:21.911000+00:00   \n",
       "2805   deribit-ETH-4SEP24-2700-C-option 2024-09-01 08:47:26.803000+00:00   \n",
       "...                                 ...                              ...   \n",
       "11208  deribit-ETH-9SEP24-2300-C-option 2024-09-07 23:54:16.170000+00:00   \n",
       "9225   deribit-ETH-8SEP24-2325-C-option 2024-09-07 23:54:52.991000+00:00   \n",
       "8166   deribit-ETH-8SEP24-2050-P-option 2024-09-07 23:57:33.509000+00:00   \n",
       "9650   deribit-ETH-8SEP24-2400-C-option 2024-09-07 23:58:04.697000+00:00   \n",
       "9651   deribit-ETH-8SEP24-2400-C-option 2024-09-07 23:58:53.038000+00:00   \n",
       "\n",
       "       amount  \n",
       "1071        1  \n",
       "1072        1  \n",
       "1073        3  \n",
       "2429        1  \n",
       "2805       14  \n",
       "...       ...  \n",
       "11208       9  \n",
       "9225        2  \n",
       "8166        2  \n",
       "9650        1  \n",
       "9651        1  \n",
       "\n",
       "[10824 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_vol = full_vol[['market','time','amount']]\n",
    "full_vol = full_vol[~(full_vol['time'] > end)]\n",
    "full_vol.sort_values('time')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a94a9c16-2340-4213-b15f-e6463dbbd6d2",
   "metadata": {},
   "source": [
    "### Retrieve 1-minute Reference Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "745ed562-7617-4ef7-b6ab-d7ddd1b0e531",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:44:59.485883Z",
     "start_time": "2022-11-16T15:40:48.297962Z"
    }
   },
   "outputs": [],
   "source": [
    "df_refrate = client.get_asset_metrics(\n",
    "    assets=asset,\n",
    "    frequency='1m',\n",
    "    metrics='ReferenceRateUSD',\n",
    "    start_time=start,\n",
    "    end_time=end\n",
    ").to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a0d84576-ac6d-4702-8d07-350ea49daf9a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:44:59.505020Z",
     "start_time": "2022-11-16T15:44:59.487372Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>ReferenceRateUSD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:00:00+00:00</th>\n",
       "      <td>2512.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:01:00+00:00</th>\n",
       "      <td>2512.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:02:00+00:00</th>\n",
       "      <td>2510.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:03:00+00:00</th>\n",
       "      <td>2513.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:04:00+00:00</th>\n",
       "      <td>2511.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 23:55:00+00:00</th>\n",
       "      <td>2298.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 23:56:00+00:00</th>\n",
       "      <td>2297.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 23:57:00+00:00</th>\n",
       "      <td>2294.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 23:58:00+00:00</th>\n",
       "      <td>2296.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 23:59:00+00:00</th>\n",
       "      <td>2298.61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11520 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           ReferenceRateUSD\n",
       "time                                       \n",
       "2024-09-01 00:00:00+00:00           2512.79\n",
       "2024-09-01 00:01:00+00:00           2512.41\n",
       "2024-09-01 00:02:00+00:00           2510.65\n",
       "2024-09-01 00:03:00+00:00           2513.37\n",
       "2024-09-01 00:04:00+00:00           2511.32\n",
       "...                                     ...\n",
       "2024-09-08 23:55:00+00:00           2298.15\n",
       "2024-09-08 23:56:00+00:00           2297.49\n",
       "2024-09-08 23:57:00+00:00           2294.79\n",
       "2024-09-08 23:58:00+00:00           2296.77\n",
       "2024-09-08 23:59:00+00:00           2298.61\n",
       "\n",
       "[11520 rows x 1 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_refrate = df_refrate.set_index('time').sort_index().drop(columns=['asset'])\n",
    "df_refrate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9abab6e6-5d8e-488a-affe-1456cba0d2fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:44:59.763795Z",
     "start_time": "2022-11-16T15:44:59.506383Z"
    }
   },
   "outputs": [],
   "source": [
    "full_vol['time'] = full_vol['time'].round('T')\n",
    "\n",
    "# Merge trades data with 1s reference rate\n",
    "full_vol = full_vol.merge(df_refrate.reset_index(),how='left', on='time')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adaecb5b-557d-463d-aced-9e7ec332cedf",
   "metadata": {},
   "source": [
    "### Calculate USD value of trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "217f762a-b996-4bec-b3ab-5b925093ff50",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:44:59.772452Z",
     "start_time": "2022-11-16T15:44:59.765270Z"
    }
   },
   "outputs": [],
   "source": [
    "full_vol['USD Volume'] = full_vol['amount'] * full_vol['ReferenceRateUSD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ee89a672-3a58-4a0e-9ea0-87f4a9064832",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:44:59.789102Z",
     "start_time": "2022-11-16T15:44:59.773854Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>market</th>\n",
       "      <th>time</th>\n",
       "      <th>amount</th>\n",
       "      <th>ReferenceRateUSD</th>\n",
       "      <th>USD Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 09:06:00+00:00</td>\n",
       "      <td>5</td>\n",
       "      <td>2293.8</td>\n",
       "      <td>11469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 09:43:00+00:00</td>\n",
       "      <td>10</td>\n",
       "      <td>2279.45</td>\n",
       "      <td>22794.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 09:43:00+00:00</td>\n",
       "      <td>9</td>\n",
       "      <td>2279.45</td>\n",
       "      <td>20515.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 09:43:00+00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>2279.45</td>\n",
       "      <td>2279.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 11:42:00+00:00</td>\n",
       "      <td>5</td>\n",
       "      <td>2285.0</td>\n",
       "      <td>11425.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10819</th>\n",
       "      <td>deribit-ETH-9SEP24-2750-C-option</td>\n",
       "      <td>2024-09-06 17:38:00+00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>2235.41</td>\n",
       "      <td>2235.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10820</th>\n",
       "      <td>deribit-ETH-9SEP24-2750-C-option</td>\n",
       "      <td>2024-09-07 17:02:00+00:00</td>\n",
       "      <td>5</td>\n",
       "      <td>2288.46</td>\n",
       "      <td>11442.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10821</th>\n",
       "      <td>deribit-ETH-9SEP24-2750-C-option</td>\n",
       "      <td>2024-09-07 18:21:00+00:00</td>\n",
       "      <td>45</td>\n",
       "      <td>2278.46</td>\n",
       "      <td>102530.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10822</th>\n",
       "      <td>deribit-ETH-9SEP24-2750-C-option</td>\n",
       "      <td>2024-09-07 18:21:00+00:00</td>\n",
       "      <td>23</td>\n",
       "      <td>2278.46</td>\n",
       "      <td>52404.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10823</th>\n",
       "      <td>deribit-ETH-9SEP24-2800-P-option</td>\n",
       "      <td>2024-09-06 17:37:00+00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>2233.79</td>\n",
       "      <td>2233.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10824 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  market                      time  amount  \\\n",
       "0      deribit-ETH-10SEP24-1950-P-option 2024-09-07 09:06:00+00:00       5   \n",
       "1      deribit-ETH-10SEP24-1950-P-option 2024-09-07 09:43:00+00:00      10   \n",
       "2      deribit-ETH-10SEP24-1950-P-option 2024-09-07 09:43:00+00:00       9   \n",
       "3      deribit-ETH-10SEP24-1950-P-option 2024-09-07 09:43:00+00:00       1   \n",
       "4      deribit-ETH-10SEP24-1950-P-option 2024-09-07 11:42:00+00:00       5   \n",
       "...                                  ...                       ...     ...   \n",
       "10819   deribit-ETH-9SEP24-2750-C-option 2024-09-06 17:38:00+00:00       1   \n",
       "10820   deribit-ETH-9SEP24-2750-C-option 2024-09-07 17:02:00+00:00       5   \n",
       "10821   deribit-ETH-9SEP24-2750-C-option 2024-09-07 18:21:00+00:00      45   \n",
       "10822   deribit-ETH-9SEP24-2750-C-option 2024-09-07 18:21:00+00:00      23   \n",
       "10823   deribit-ETH-9SEP24-2800-P-option 2024-09-06 17:37:00+00:00       1   \n",
       "\n",
       "       ReferenceRateUSD  USD Volume  \n",
       "0                2293.8     11469.0  \n",
       "1               2279.45     22794.5  \n",
       "2               2279.45    20515.05  \n",
       "3               2279.45     2279.45  \n",
       "4                2285.0     11425.0  \n",
       "...                 ...         ...  \n",
       "10819           2235.41     2235.41  \n",
       "10820           2288.46     11442.3  \n",
       "10821           2278.46    102530.7  \n",
       "10822           2278.46    52404.58  \n",
       "10823           2233.79     2233.79  \n",
       "\n",
       "[10824 rows x 5 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_vol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "098b627d-97bd-443f-8be0-b74d4a461d31",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:08:18.127446Z",
     "start_time": "2022-11-16T16:08:17.788595Z"
    }
   },
   "outputs": [],
   "source": [
    "vol_sum = full_vol.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True)).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "22e951b2-30d6-4ba6-84f0-c0a4ab2e5c4d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:08:18.194699Z",
     "start_time": "2022-11-16T16:08:18.189830Z"
    }
   },
   "outputs": [],
   "source": [
    "vol_sum.to_csv('./deribit_' + str(asset).upper() + '_options_vol_' + str(start) + '_to_' + str(end) + '.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3b4306fc-baf7-4bbd-8c8e-12cea6251ef7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:08:18.601381Z",
     "start_time": "2022-11-16T16:08:18.591344Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>USD Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:00:00+00:00</th>\n",
       "      <td>5424658.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-02 00:00:00+00:00</th>\n",
       "      <td>19562749.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-03 00:00:00+00:00</th>\n",
       "      <td>40646881.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-04 00:00:00+00:00</th>\n",
       "      <td>63609486.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-05 00:00:00+00:00</th>\n",
       "      <td>44657679.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-06 00:00:00+00:00</th>\n",
       "      <td>158263998.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-07 00:00:00+00:00</th>\n",
       "      <td>44401580.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             USD Volume\n",
       "time                                   \n",
       "2024-09-01 00:00:00+00:00    5424658.14\n",
       "2024-09-02 00:00:00+00:00   19562749.43\n",
       "2024-09-03 00:00:00+00:00   40646881.35\n",
       "2024-09-04 00:00:00+00:00   63609486.54\n",
       "2024-09-05 00:00:00+00:00   44657679.33\n",
       "2024-09-06 00:00:00+00:00  158263998.37\n",
       "2024-09-07 00:00:00+00:00    44401580.5"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vol_sum[['USD Volume']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "27e7ecd3-d397-4462-8460-849ce129644c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:08:19.594528Z",
     "start_time": "2022-11-16T16:08:19.246238Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "v = vol_sum.plot.line(y='USD Volume')\n",
    "v.set_xlabel(\"Date\", fontsize = 15)\n",
    "plt.setp(v.get_yticklabels(), fontsize=13)\n",
    "plt.setp(v.get_xticklabels(), fontsize=13)\n",
    "v.set_xlabel(\"\")\n",
    "plt.xlim([vol_sum.index[0], vol_sum.index[-1]])\n",
    "v.set_ylabel(\"Daily Volume (USD)\\n\", fontsize = 15)\n",
    "v.set_title(('\\nDeribit ' + str(asset).upper() + ' Options Volume\\n'),fontsize=23)\n",
    "v.get_legend().remove()\n",
    "v.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '${:,.1f}'.format(x/1000000) + 'M'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b73c727-522d-4287-b88f-12ade4963561",
   "metadata": {},
   "source": [
    "# OPEN INTEREST\n",
    "\n",
    "Open interest represents the number of contracts that are currently outstanding and not settled for a specific derivatives market. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10a44104-246f-4c27-a3f3-acdbd56ac6fc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "76db11f0-eae1-4732-a117-2e590f58fe34",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T15:45:00.457523Z",
     "start_time": "2022-11-16T15:45:00.438632Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "376"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop markets without open interest data\n",
    "oi_cat = df_asset_options.loc[df_asset_options.listing < end, 'market'].tolist()\n",
    "len(oi_cat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "49ce9334-732b-45d5-8e0c-72253893ab78",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:22.581211Z",
     "start_time": "2022-11-16T15:45:00.458934Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Retrieving EOD open interest for markets 0 through 420...\n",
      "2024-09-01 00:00:00\n",
      "...\n",
      "2024-09-09 00:00:00\n"
     ]
    }
   ],
   "source": [
    "full_oi = pd.DataFrame()\n",
    "batch_size = 420\n",
    "\n",
    "for i in range(0, len(oi_cat),batch_size):\n",
    "    mkt_batch = oi_cat[i:i+batch_size]\n",
    "    print(str('\\nRetrieving EOD open interest for markets ' + str(i) + ' through ' + str(i+batch_size) + '...'))\n",
    "    \n",
    "    start_date = pd.to_datetime(start)\n",
    "    end_date = pd.to_datetime(end)\n",
    "    delta = timedelta(days=1)\n",
    "    print(str(start_date) + '\\n...')\n",
    "    \n",
    "    while start_date <= end_date:\n",
    "        \n",
    "        oi_batch = client.get_market_open_interest(\n",
    "            markets=mkt_batch,\n",
    "            start_time = start_date.strftime(\"%Y-%m-%d\"),\n",
    "            limit_per_market = 1,\n",
    "            paging_from='start',\n",
    "            timezone='America/New_York'\n",
    "        ).to_dataframe()\n",
    "        #print(oi_batch)\n",
    "        full_oi = pd.concat((full_oi, oi_batch), axis = 0, ignore_index=False)\n",
    "        start_date += delta\n",
    "        \n",
    "    print(start_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a9824c76-53f2-4cec-9abc-f34a59e11ce4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:22.599889Z",
     "start_time": "2022-11-16T16:04:22.582934Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 2534 entries, 0 to 193\n",
      "Data columns (total 6 columns):\n",
      " #   Column          Non-Null Count  Dtype              \n",
      "---  ------          --------------  -----              \n",
      " 0   market          2534 non-null   string             \n",
      " 1   time            2534 non-null   datetime64[ns, UTC]\n",
      " 2   contract_count  2534 non-null   Int64              \n",
      " 3   value_usd       2534 non-null   Float64            \n",
      " 4   database_time   2534 non-null   datetime64[ns, UTC]\n",
      " 5   exchange_time   2534 non-null   datetime64[ns, UTC]\n",
      "dtypes: Float64(1), Int64(1), datetime64[ns, UTC](3), string(1)\n",
      "memory usage: 143.5 KB\n"
     ]
    }
   ],
   "source": [
    "full_oi.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9352ebb9-e9a7-4ad4-ad04-0470d28f240d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:22.674861Z",
     "start_time": "2022-11-16T16:04:22.601451Z"
    }
   },
   "outputs": [],
   "source": [
    "oi_sum = full_oi.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))['value_usd'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9de2ab92-04ed-4c63-bfa3-32575bcacd36",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:22.690310Z",
     "start_time": "2022-11-16T16:04:22.676534Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "time\n",
       "2024-09-01 00:00:00+00:00             0.0\n",
       "2024-09-02 00:00:00+00:00      6467612.33\n",
       "2024-09-03 00:00:00+00:00     24927750.02\n",
       "2024-09-04 00:00:00+00:00     55323320.59\n",
       "2024-09-05 00:00:00+00:00     59305999.71\n",
       "2024-09-06 00:00:00+00:00      51922555.8\n",
       "2024-09-07 00:00:00+00:00    144108764.26\n",
       "2024-09-08 00:00:00+00:00    122269418.49\n",
       "Freq: D, Name: value_usd, dtype: Float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oi_sum.to_csv('./deribit_' + str(asset).upper() + '_options_oi_' + str(start) + '_to_' + str(end) + '.csv')\n",
    "oi_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "dd8bed00-66e3-45dd-9e1b-0d7c4b6b4f25",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.046623Z",
     "start_time": "2022-11-16T16:04:22.691824Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#p = sns.lineplot(data=vol_sum, x=\"time\", y=\"USD Volume\")\n",
    "oi = oi_sum.plot.area(y='value_usd')\n",
    "oi.set_xlabel(\"Date\", fontsize = 15)\n",
    "plt.setp(oi.get_yticklabels(), fontsize=13)\n",
    "plt.setp(oi.get_xticklabels(), fontsize=13)\n",
    "oi.set_xlabel(\"\")\n",
    "plt.xlim([oi_sum.index[0], oi_sum.index[-1]])\n",
    "oi.set_ylabel(\"Daily Open Interest (USD)\\n\", fontsize = 15)\n",
    "oi.set_title(('\\nDeribit ' + str(asset).upper() + ' Options Open Interest\\n'),fontsize=23)\n",
    "# oi.get_legend().remove()\n",
    "oi.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '${:,.2f}'.format(x/1_000_000) + 'M'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50e2220a-64b2-414e-90a9-b5221e5d61b6",
   "metadata": {},
   "source": [
    "## Split into Calls/Puts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c9f01384-6cce-4fe7-b52a-6c66ed6f6a2c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.203779Z",
     "start_time": "2022-11-16T16:04:23.048060Z"
    }
   },
   "outputs": [],
   "source": [
    "full_oi_split = full_oi.merge(df_asset_options[['market','option_contract_type']],how='left', on='market')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ad9307bd-8cae-42d5-90b9-c4e3e47ef69a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.224883Z",
     "start_time": "2022-11-16T16:04:23.205315Z"
    }
   },
   "outputs": [
    {
     "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>market</th>\n",
       "      <th>time</th>\n",
       "      <th>contract_count</th>\n",
       "      <th>value_usd</th>\n",
       "      <th>database_time</th>\n",
       "      <th>exchange_time</th>\n",
       "      <th>option_contract_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-C-option</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-07 08:00:19.312717+00:00</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>call</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>deribit-ETH-10SEP24-1950-P-option</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-07 08:00:18.188738+00:00</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>put</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>deribit-ETH-10SEP24-2000-C-option</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-07 08:00:18.188738+00:00</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>call</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>deribit-ETH-10SEP24-2000-P-option</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-07 08:00:18.708225+00:00</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>put</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>deribit-ETH-10SEP24-2050-C-option</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-07 08:00:18.708225+00:00</td>\n",
       "      <td>2024-09-07 08:00:00+00:00</td>\n",
       "      <td>call</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2529</th>\n",
       "      <td>deribit-ETH-9SEP24-2800-P-option</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>1</td>\n",
       "      <td>2285.35</td>\n",
       "      <td>2024-09-08 04:00:06.461248+00:00</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>put</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2530</th>\n",
       "      <td>deribit-ETH-9SEP24-2850-C-option</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-08 04:00:01.855497+00:00</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>call</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2531</th>\n",
       "      <td>deribit-ETH-9SEP24-2850-P-option</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-08 04:00:03.353208+00:00</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>put</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2532</th>\n",
       "      <td>deribit-ETH-9SEP24-2900-C-option</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-08 04:00:04.393566+00:00</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>call</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2533</th>\n",
       "      <td>deribit-ETH-9SEP24-2900-P-option</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-09-08 04:00:02.869006+00:00</td>\n",
       "      <td>2024-09-08 04:00:00+00:00</td>\n",
       "      <td>put</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2534 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 market                      time  \\\n",
       "0     deribit-ETH-10SEP24-1950-C-option 2024-09-07 08:00:00+00:00   \n",
       "1     deribit-ETH-10SEP24-1950-P-option 2024-09-07 08:00:00+00:00   \n",
       "2     deribit-ETH-10SEP24-2000-C-option 2024-09-07 08:00:00+00:00   \n",
       "3     deribit-ETH-10SEP24-2000-P-option 2024-09-07 08:00:00+00:00   \n",
       "4     deribit-ETH-10SEP24-2050-C-option 2024-09-07 08:00:00+00:00   \n",
       "...                                 ...                       ...   \n",
       "2529   deribit-ETH-9SEP24-2800-P-option 2024-09-08 04:00:00+00:00   \n",
       "2530   deribit-ETH-9SEP24-2850-C-option 2024-09-08 04:00:00+00:00   \n",
       "2531   deribit-ETH-9SEP24-2850-P-option 2024-09-08 04:00:00+00:00   \n",
       "2532   deribit-ETH-9SEP24-2900-C-option 2024-09-08 04:00:00+00:00   \n",
       "2533   deribit-ETH-9SEP24-2900-P-option 2024-09-08 04:00:00+00:00   \n",
       "\n",
       "      contract_count  value_usd                    database_time  \\\n",
       "0                  0        0.0 2024-09-07 08:00:19.312717+00:00   \n",
       "1                  0        0.0 2024-09-07 08:00:18.188738+00:00   \n",
       "2                  0        0.0 2024-09-07 08:00:18.188738+00:00   \n",
       "3                  0        0.0 2024-09-07 08:00:18.708225+00:00   \n",
       "4                  0        0.0 2024-09-07 08:00:18.708225+00:00   \n",
       "...              ...        ...                              ...   \n",
       "2529               1    2285.35 2024-09-08 04:00:06.461248+00:00   \n",
       "2530               0        0.0 2024-09-08 04:00:01.855497+00:00   \n",
       "2531               0        0.0 2024-09-08 04:00:03.353208+00:00   \n",
       "2532               0        0.0 2024-09-08 04:00:04.393566+00:00   \n",
       "2533               0        0.0 2024-09-08 04:00:02.869006+00:00   \n",
       "\n",
       "                 exchange_time option_contract_type  \n",
       "0    2024-09-07 08:00:00+00:00                 call  \n",
       "1    2024-09-07 08:00:00+00:00                  put  \n",
       "2    2024-09-07 08:00:00+00:00                 call  \n",
       "3    2024-09-07 08:00:00+00:00                  put  \n",
       "4    2024-09-07 08:00:00+00:00                 call  \n",
       "...                        ...                  ...  \n",
       "2529 2024-09-08 04:00:00+00:00                  put  \n",
       "2530 2024-09-08 04:00:00+00:00                 call  \n",
       "2531 2024-09-08 04:00:00+00:00                  put  \n",
       "2532 2024-09-08 04:00:00+00:00                 call  \n",
       "2533 2024-09-08 04:00:00+00:00                  put  \n",
       "\n",
       "[2534 rows x 7 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_oi_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b7db116c-470c-4259-9060-e8553ecef7eb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.374587Z",
     "start_time": "2022-11-16T16:04:23.226444Z"
    }
   },
   "outputs": [],
   "source": [
    "calls = full_oi_split.loc[(full_oi_split.option_contract_type == 'call')]\n",
    "call_sum_split = calls.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))[['value_usd']].sum()\n",
    "puts = full_oi_split.loc[(full_oi_split.option_contract_type == 'put')]\n",
    "put_sum_split = puts.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))[['value_usd']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "13d72dc8-ecec-4b05-9199-45c7c0cc0346",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.379994Z",
     "start_time": "2022-11-16T16:04:23.376286Z"
    }
   },
   "outputs": [],
   "source": [
    "put_sum_split = put_sum_split.rename(columns={\"value_usd\": \"Puts - USD Value\", \"contract_count\": \"Puts - Contract Count\" })\n",
    "call_sum_split = call_sum_split.rename(columns={\"value_usd\": \"Calls - USD Value\", \"contract_count\": \"Calls - Contract Count\" })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a862bfcf-08ee-4a47-b4e6-245f8ae8ee6d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.404968Z",
     "start_time": "2022-11-16T16:04:23.381421Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Calls - USD Value</th>\n",
       "      <th>Puts - USD Value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:00:00+00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-02 00:00:00+00:00</th>\n",
       "      <td>4987937.59</td>\n",
       "      <td>1479674.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-03 00:00:00+00:00</th>\n",
       "      <td>14177673.6</td>\n",
       "      <td>10750076.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-04 00:00:00+00:00</th>\n",
       "      <td>30418324.31</td>\n",
       "      <td>24904996.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-05 00:00:00+00:00</th>\n",
       "      <td>37814891.94</td>\n",
       "      <td>21491107.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-06 00:00:00+00:00</th>\n",
       "      <td>24772293.7</td>\n",
       "      <td>27150262.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-07 00:00:00+00:00</th>\n",
       "      <td>73624086.44</td>\n",
       "      <td>70484677.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 00:00:00+00:00</th>\n",
       "      <td>61750871.09</td>\n",
       "      <td>60518547.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Calls - USD Value  Puts - USD Value\n",
       "time                                                          \n",
       "2024-09-01 00:00:00+00:00                0.0               0.0\n",
       "2024-09-02 00:00:00+00:00         4987937.59        1479674.74\n",
       "2024-09-03 00:00:00+00:00         14177673.6       10750076.42\n",
       "2024-09-04 00:00:00+00:00        30418324.31       24904996.28\n",
       "2024-09-05 00:00:00+00:00        37814891.94       21491107.77\n",
       "2024-09-06 00:00:00+00:00         24772293.7        27150262.1\n",
       "2024-09-07 00:00:00+00:00        73624086.44       70484677.82\n",
       "2024-09-08 00:00:00+00:00        61750871.09        60518547.4"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_oi_split = call_sum_split.merge(put_sum_split,how='left', on='time')\n",
    "full_oi_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "bd00fa9f-7197-4124-b7b9-c44d829d2d21",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.418691Z",
     "start_time": "2022-11-16T16:04:23.406458Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Put/Call Ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-09-01 00:00:00+00:00</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-02 00:00:00+00:00</th>\n",
       "      <td>0.296651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-03 00:00:00+00:00</th>\n",
       "      <td>0.75824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-04 00:00:00+00:00</th>\n",
       "      <td>0.81875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-05 00:00:00+00:00</th>\n",
       "      <td>0.568324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-06 00:00:00+00:00</th>\n",
       "      <td>1.095993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-07 00:00:00+00:00</th>\n",
       "      <td>0.957359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-08 00:00:00+00:00</th>\n",
       "      <td>0.980044</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Put/Call Ratio\n",
       "time                                     \n",
       "2024-09-01 00:00:00+00:00             NaN\n",
       "2024-09-02 00:00:00+00:00        0.296651\n",
       "2024-09-03 00:00:00+00:00         0.75824\n",
       "2024-09-04 00:00:00+00:00         0.81875\n",
       "2024-09-05 00:00:00+00:00        0.568324\n",
       "2024-09-06 00:00:00+00:00        1.095993\n",
       "2024-09-07 00:00:00+00:00        0.957359\n",
       "2024-09-08 00:00:00+00:00        0.980044"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_oi_split['Put/Call Ratio'] = full_oi_split['Puts - USD Value'] / full_oi_split['Calls - USD Value']\n",
    "full_oi_split[['Put/Call Ratio']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "21b43118-14b6-4791-96f3-97074a2dabcd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.430198Z",
     "start_time": "2022-11-16T16:04:23.420188Z"
    }
   },
   "outputs": [],
   "source": [
    "full_oi_split.to_csv('./deribit_' + str(asset).upper() + '_options_oi_calls_puts_' + str(start) + '_to_' + str(end) + '.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8563b633-b4f4-401f-b69b-248409636157",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-16T16:04:23.854032Z",
     "start_time": "2022-11-16T16:04:23.431682Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pc = sns.lineplot(data=full_oi_split[['Put/Call Ratio']], x=\"time\", y=\"Put/Call Ratio\")\n",
    "pc.set_xlabel(\"Date\", fontsize = 15)\n",
    "plt.setp(pc.get_yticklabels(), fontsize=13)\n",
    "plt.setp(pc.get_xticklabels(), fontsize=13)\n",
    "pc.set_xlabel(\"\")\n",
    "plt.xlim([full_oi_split.index[0], full_oi_split.index[-1]])\n",
    "pc.set_ylabel(\"Put/Call Ratio\\n\", fontsize = 15)\n",
    "pc.set_title(('\\nDeribit ' + str(asset).upper() + ' Options\\nPut/Call Ratio\\n'),fontsize=23)\n",
    "pc.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '{:,.2f}'.format(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d3017f8-9bf5-4254-a857-c5a83ffba29f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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