backtest_ETH_CM_Perp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### This notebook represents holding a Deribit coin Margin Perpetual, both Long and Short.  The Perpetuals are \"created\" from the spot index price which is accurate enough to demonstrate my point.\n",
    "\n",
    "Because Deribit credits and debits UNREALISED profits and losses on a daily basis, a short perpetual position does not work to hedge a spot holding, and a long position does not match holding the index.\n",
    "\n",
    "I take no account of Funding Fees since they are irrelevant for this exercise.\n",
    "\n",
    "This is because the coin amounts credited or debited moves in price over the duration of the holding.  With other exchanges, the unrealised P&L will be taken account of for margin but not charged to the account until the trade is closed - which could be any time after the opening.\n",
    "\n",
    "The result as can be seen from the below charts is that hedging 1 ETH for the period shown below results in a loss of both the initial ETH 1 you are attempting to hedge and a further $890.\n",
    "\n",
    "This is because the 1 ETH you are trying to hedge is kept in the same account as the unrealised P&L is debited / credited to. Therefor in a rising market it gets eaten by the losses. You need the 1 ETH left untouched so that ir rises in price to exactly counteract the loss on the short contract, thus leaving you with the original $ amount of the 1 ETH as of the date the hedge was put on.\n",
    "\n",
    "Note also that the long position does not reflect the index - unrealised profits accruing daily boost the profits in a rising market.\n",
    "\n",
    "So if you want to hedge 1 ETH with a perpetual at Deribit you need to have a multi collateral account, deposit 1 ETH and short 1 ETH.  Which sounds acceptable until you realise that in a rising market a dollar debit arises on which you will be charged 0.01% daily.\n",
    "\n",
    "Again, hardly ideal.\n",
    "\n",
    "Unless of course I have made some error in my though process.  And yet the records of my actual account with Deribit support my conclusions.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#imports\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ffn\n",
    "import os\n",
    "import sys\n",
    "import pathlib\n",
    "import datetime\n",
    "from IPython.core.pylabtools import figsize\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "plt.style.use('ggplot')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['deribit_ETH_USD_ETH_funding_rate_history']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "directory = r'C:\\Users\\agarn\\OneDrive\\Documents\\Data\\Funding_Rates\\ETH_USD_ETH'\n",
    "files = [x for x in pathlib.Path(directory).glob('*.csv') if x.is_file()]\n",
    "names = [x.stem for x in files]\n",
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[WindowsPath('C:/Users/agarn/OneDrive/Documents/Data/Funding_Rates/ETH_USD_ETH/deribit_ETH_USD_ETH_funding_rate_history.csv')]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read the CSV file, skipping the header row and assigning column names\n",
    "df = pd.read_csv(files[0], skiprows=1, header=None, names=['date', 'rate', 'index'])\n",
    "\n",
    "# Convert the date column to datetime format\n",
    "df.date = pd.to_datetime(df.date, utc=True)\n",
    "\n",
    "# Set the date column as the index\n",
    "df.set_index(['date'], inplace=True)\n",
    "\n",
    "# Remove duplicate indices, keeping the first occurrence\n",
    "df = df[~df.index.duplicated(keep='first')]\n",
    "\n",
    "# Sort the DataFrame by the index (date) in ascending order\n",
    "df.sort_index(inplace=True)\n",
    "\n",
    "# Optional: Filter the DataFrame by date range and calculate the percentage change\n",
    "# df = df.loc['2019-05-01 07:00:00+00:00':'2023-05-31 23:00:00+00:00']\n",
    "# df['rate_return'] = df['rate'].pct_change().fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>rate</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-05-01 07:00:00+00:00</th>\n",
       "      <td>-0.000288</td>\n",
       "      <td>160.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-01 15:00:00+00:00</th>\n",
       "      <td>-0.000035</td>\n",
       "      <td>158.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-01 23:00:00+00:00</th>\n",
       "      <td>-0.000111</td>\n",
       "      <td>157.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-02 07:00:00+00:00</th>\n",
       "      <td>-0.000047</td>\n",
       "      <td>158.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-02 15:00:00+00:00</th>\n",
       "      <td>-0.000008</td>\n",
       "      <td>157.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                               rate   index\n",
       "date                                       \n",
       "2019-05-01 07:00:00+00:00 -0.000288  160.49\n",
       "2019-05-01 15:00:00+00:00 -0.000035  158.36\n",
       "2019-05-01 23:00:00+00:00 -0.000111  157.39\n",
       "2019-05-02 07:00:00+00:00 -0.000047  158.96\n",
       "2019-05-02 15:00:00+00:00 -0.000008  157.87"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>rate</th>\n",
       "      <th>index</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2025-01-31 23:00:00+00:00</th>\n",
       "      <td>0.000061</td>\n",
       "      <td>3295.6</td>\n",
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      "text/plain": [
       "                               rate   index\n",
       "date                                       \n",
       "2025-01-31 23:00:00+00:00  0.000061  3295.6"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df.tail(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>counter</th>\n",
       "      <th>index</th>\n",
       "      <th>rate</th>\n",
       "      <th>interest</th>\n",
       "      <th>cum_interest</th>\n",
       "      <th>position</th>\n",
       "      <th>coin_long</th>\n",
       "      <th>coin_short</th>\n",
       "      <th>dollars_long</th>\n",
       "      <th>dollars_short</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2019-05-01 07:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>160.49</td>\n",
       "      <td>-0.000288</td>\n",
       "      <td>-0.000653</td>\n",
       "      <td>-0.000653</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-01 15:00:00+00:00</th>\n",
       "      <td>1</td>\n",
       "      <td>158.36</td>\n",
       "      <td>-0.000035</td>\n",
       "      <td>-0.000081</td>\n",
       "      <td>-0.000734</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>-0.013450</td>\n",
       "      <td>1.013450</td>\n",
       "      <td>-2.130000</td>\n",
       "      <td>160.490000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-01 23:00:00+00:00</th>\n",
       "      <td>2</td>\n",
       "      <td>157.39</td>\n",
       "      <td>-0.000111</td>\n",
       "      <td>-0.000258</td>\n",
       "      <td>-0.000992</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>-0.019613</td>\n",
       "      <td>1.019613</td>\n",
       "      <td>-3.086953</td>\n",
       "      <td>160.476953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-02 07:00:00+00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>158.96</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>-0.000107</td>\n",
       "      <td>-0.001099</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>-0.009737</td>\n",
       "      <td>1.009737</td>\n",
       "      <td>-1.547746</td>\n",
       "      <td>160.507746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-02 15:00:00+00:00</th>\n",
       "      <td>4</td>\n",
       "      <td>157.87</td>\n",
       "      <td>-0.000008</td>\n",
       "      <td>-0.000018</td>\n",
       "      <td>-0.001116</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>-0.016641</td>\n",
       "      <td>1.016641</td>\n",
       "      <td>-2.627133</td>\n",
       "      <td>160.497133</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                           counter   index      rate  interest  cum_interest  \\\n",
       "date                                                                           \n",
       "2019-05-01 07:00:00+00:00        0  160.49 -0.000288 -0.000653     -0.000653   \n",
       "2019-05-01 15:00:00+00:00        1  158.36 -0.000035 -0.000081     -0.000734   \n",
       "2019-05-01 23:00:00+00:00        2  157.39 -0.000111 -0.000258     -0.000992   \n",
       "2019-05-02 07:00:00+00:00        3  158.96 -0.000047 -0.000107     -0.001099   \n",
       "2019-05-02 15:00:00+00:00        4  157.87 -0.000008 -0.000018     -0.001116   \n",
       "\n",
       "                             position  coin_long  coin_short  dollars_long  \\\n",
       "date                                                                         \n",
       "2019-05-01 07:00:00+00:00  364.359486   0.000000    1.000000      0.000000   \n",
       "2019-05-01 15:00:00+00:00  364.359486  -0.013450    1.013450     -2.130000   \n",
       "2019-05-01 23:00:00+00:00  364.359486  -0.019613    1.019613     -3.086953   \n",
       "2019-05-02 07:00:00+00:00  364.359486  -0.009737    1.009737     -1.547746   \n",
       "2019-05-02 15:00:00+00:00  364.359486  -0.016641    1.016641     -2.627133   \n",
       "\n",
       "                           dollars_short  \n",
       "date                                      \n",
       "2019-05-01 07:00:00+00:00       0.000000  \n",
       "2019-05-01 15:00:00+00:00     160.490000  \n",
       "2019-05-01 23:00:00+00:00     160.476953  \n",
       "2019-05-02 07:00:00+00:00     160.507746  \n",
       "2019-05-02 15:00:00+00:00     160.497133  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Initialize variables\n",
    "results = []\n",
    "counter = -1\n",
    "add_to_position = 200000000000000 # Add to position every \"add_to_position\" /3  days\n",
    "dollars_long = 0\n",
    "dollars_short = 0\n",
    "coin_long = 0\n",
    "coin_short = 1\n",
    "position = coin * df['index'].iloc[0]  # Initialize position\n",
    "interest = 0\n",
    "cum_interest = 0  # Initialize cumulative interest\n",
    "\n",
    "# Iterate through the rows\n",
    "for i in range(0, df.shape[0]):  \n",
    "    counter += 1\n",
    "    interest = (df['rate'].iloc[i] * position) / df['index'].iloc[i]\n",
    "    cum_interest += interest\n",
    "    if counter == add_to_position:\n",
    "        if cum_interest > 0:\n",
    "            position += (cum_interest * df['index'].iloc[i])\n",
    "        cum_interest = 0\n",
    "        counter = 0\n",
    "    #dollar_equity = position + (cum_interest * df['index'].iloc[i])\n",
    "    if i > 0:\n",
    "        coin_short += (df['index'].iloc[i-1] - df['index'].iloc[i]) / df['index'].iloc[i]\n",
    "        coin_long += (df['index'].iloc[i] - df['index'].iloc[i-1]) / df['index'].iloc[i]\n",
    "        dollars_short = coin_short * df['index'].iloc[i]\n",
    "        dollars_long = coin_long * df['index'].iloc[i]\n",
    "    results.append((df.index[i], counter, df['index'].iloc[i], df['rate'].iloc[i], \\\n",
    "                    interest, cum_interest, position, coin_long, coin_short, dollars_long, dollars_short))\n",
    "\n",
    "# Create DataFrame from results\n",
    "stats = pd.DataFrame(results, columns=['date', 'counter','index', 'rate', 'interest', 'cum_interest', \\\n",
    "                                       'position', 'coin_long', 'coin_short','dollars_long','dollars_short'])\n",
    "\n",
    "# Convert date column to datetime and set as index\n",
    "stats['date'] = pd.to_datetime(stats['date'], utc=True)\n",
    "stats.set_index('date', inplace=True)\n",
    "\n",
    "# Display the resulting DataFrame\n",
    "stats.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>counter</th>\n",
       "      <th>index</th>\n",
       "      <th>rate</th>\n",
       "      <th>interest</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
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       "      <th>2025-01-30 15:00:00+00:00</th>\n",
       "      <td>6303</td>\n",
       "      <td>3270.66</td>\n",
       "      <td>6.645822e-05</td>\n",
       "      <td>7.403608e-06</td>\n",
       "      <td>0.091531</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>1.263197</td>\n",
       "      <td>-0.263197</td>\n",
       "      <td>4131.488594</td>\n",
       "      <td>-860.828594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-01-30 23:00:00+00:00</th>\n",
       "      <td>6304</td>\n",
       "      <td>3261.09</td>\n",
       "      <td>4.372877e-05</td>\n",
       "      <td>4.885787e-06</td>\n",
       "      <td>0.091536</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>1.260263</td>\n",
       "      <td>-0.260263</td>\n",
       "      <td>4109.829797</td>\n",
       "      <td>-848.739797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-01-31 07:00:00+00:00</th>\n",
       "      <td>6305</td>\n",
       "      <td>3262.50</td>\n",
       "      <td>-5.445785e-08</td>\n",
       "      <td>-6.081911e-09</td>\n",
       "      <td>0.091536</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>1.260695</td>\n",
       "      <td>-0.260695</td>\n",
       "      <td>4113.016767</td>\n",
       "      <td>-850.516767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-01-31 15:00:00+00:00</th>\n",
       "      <td>6306</td>\n",
       "      <td>3351.04</td>\n",
       "      <td>4.357873e-05</td>\n",
       "      <td>4.738327e-06</td>\n",
       "      <td>0.091541</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>1.287116</td>\n",
       "      <td>-0.287116</td>\n",
       "      <td>4313.178684</td>\n",
       "      <td>-962.138684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025-01-31 23:00:00+00:00</th>\n",
       "      <td>6307</td>\n",
       "      <td>3295.60</td>\n",
       "      <td>6.075443e-05</td>\n",
       "      <td>6.716972e-06</td>\n",
       "      <td>0.091548</td>\n",
       "      <td>364.359486</td>\n",
       "      <td>1.270294</td>\n",
       "      <td>-0.270294</td>\n",
       "      <td>4186.380948</td>\n",
       "      <td>-890.780948</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           counter    index          rate      interest  \\\n",
       "date                                                                      \n",
       "2025-01-30 15:00:00+00:00     6303  3270.66  6.645822e-05  7.403608e-06   \n",
       "2025-01-30 23:00:00+00:00     6304  3261.09  4.372877e-05  4.885787e-06   \n",
       "2025-01-31 07:00:00+00:00     6305  3262.50 -5.445785e-08 -6.081911e-09   \n",
       "2025-01-31 15:00:00+00:00     6306  3351.04  4.357873e-05  4.738327e-06   \n",
       "2025-01-31 23:00:00+00:00     6307  3295.60  6.075443e-05  6.716972e-06   \n",
       "\n",
       "                           cum_interest    position  coin_long  coin_short  \\\n",
       "date                                                                         \n",
       "2025-01-30 15:00:00+00:00      0.091531  364.359486   1.263197   -0.263197   \n",
       "2025-01-30 23:00:00+00:00      0.091536  364.359486   1.260263   -0.260263   \n",
       "2025-01-31 07:00:00+00:00      0.091536  364.359486   1.260695   -0.260695   \n",
       "2025-01-31 15:00:00+00:00      0.091541  364.359486   1.287116   -0.287116   \n",
       "2025-01-31 23:00:00+00:00      0.091548  364.359486   1.270294   -0.270294   \n",
       "\n",
       "                           dollars_long  dollars_short  \n",
       "date                                                    \n",
       "2025-01-30 15:00:00+00:00   4131.488594    -860.828594  \n",
       "2025-01-30 23:00:00+00:00   4109.829797    -848.739797  \n",
       "2025-01-31 07:00:00+00:00   4113.016767    -850.516767  \n",
       "2025-01-31 15:00:00+00:00   4313.178684    -962.138684  \n",
       "2025-01-31 23:00:00+00:00   4186.380948    -890.780948  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot dollars_long\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(stats.index, stats['dollars_long'], label='Dollars Long', color='blue', linestyle='-', marker='o')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Dollars Long')\n",
    "plt.title('Dollar Value of Long Contract Account Over Time')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Plot Index\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(df.index, df['index'], label='Index', color='green', linestyle='-', marker='o')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Index')\n",
    "plt.title('Index Over Time')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Plot dollars_short\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(stats.index, stats['dollars_short'], label='Dollars Short', color='red', linestyle='-', marker='o')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Dollars Short')\n",
    "plt.title('Dollar Value of Account Over Time')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  }
 ],
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