Aggregating Options Data

Coin Metrics Options Data Aggregation

This notebook demonstrates basic functionality offered by the Coin Metrics Python API Client and Market Data Feed.

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.

Resources

To understand the data that Coin Metrics offers, feel free to peruse the resources below.

• The Coin Metrics API v4 website contains the full set of endpoints and data offered by Coin Metrics.

• The Coin Metrics Product Documentation gives detailed, conceptual explanations of the data that Coin Metrics offers.

• The API Spec contains a full list of functions.

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Download the entire notebook as either a jupyter notebook to run yourself or as a pdf from the two links below

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Notebook Setup

import os
from os import environ
import sys
import pandas as pd
import numpy as np
import seaborn as sns
import logging
from datetime import date, datetime, timedelta
from coinmetrics.api_client import CoinMetricsClient
import json
import logging
from datetime import timezone as timezone_info
import matplotlib.ticker as mticker
from matplotlib.ticker import ScalarFormatter
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
%matplotlib inline
from plotly import graph_objects as go

sns.set_theme()
sns.set(rc={'figure.figsize':(14,8)})
sns.set_style("whitegrid",{'axes.grid' : True,'grid.linestyle': '--', 'grid.color': 'gray','axes.edgecolor': 'white'})

logging.basicConfig(
    format='%(asctime)s %(levelname)-8s %(message)s',
    level=logging.INFO,
    datefmt='%Y-%m-%d %H:%M:%S'
)

# We recommend privately storing your API key in your local environment.
try:
    api_key = environ["CM_API_KEY"]
    logging.info("Using API key found in environment")
except KeyError:
    api_key = ""
    logging.info("API key not found. Using community client")

client = CoinMetricsClient(api_key)

2024-09-12 08:53:59 INFO     Using API key found in environment

Set start and end time

end = datetime.utcnow()
start = '2024-09-01'
end = '2024-09-08'
asset = 'eth'

OPTIONS CATALOG

To simplify some of the complexity around options contract size, we will investigate only options markets on Deribit, the largest options exchange by volume.

asset_options = client.reference_data_markets(
    type='option',
    exchange='deribit',
    base='eth',
    quote='usd',
    page_size=10000
).to_list()

print('Total number of supported options markets: ' + str(len(asset_options)))

Total number of supported options markets: 74827

Filter out expired/inactive contracts

df_asset_options = pd.DataFrame(asset_options)

df_asset_options.head()

	market	exchange	type	base	quote	pair	symbol	size_asset	strike	option_contract_type	...	listing	expiration	settlement_price	status	order_amount_min	order_price_increment	order_taker_fee	order_maker_fee	base_native	quote_native
0	deribit-ETH-10APR20-100-P-option	deribit	option	eth	usd	eth-usd	ETH-10APR20-100-P	eth	100	put	...	2020-03-26T08:00:02.000000000Z	2020-04-10T08:00:00.000000000Z	158.1	offline	1	0.0005	0.0004	0.0004	NaN	NaN
1	deribit-ETH-10APR20-110-P-option	deribit	option	eth	usd	eth-usd	ETH-10APR20-110-P	eth	110	put	...	2020-03-26T08:00:02.000000000Z	2020-04-10T08:00:00.000000000Z	158.1	offline	1	0.0005	0.0004	0.0004	NaN	NaN
2	deribit-ETH-10APR20-120-C-option	deribit	option	eth	usd	eth-usd	ETH-10APR20-120-C	eth	120	call	...	2020-03-26T08:00:02.000000000Z	2020-04-10T08:00:00.000000000Z	158.1	offline	1	0.0005	0.0004	0.0004	NaN	NaN
3	deribit-ETH-10APR20-120-P-option	deribit	option	eth	usd	eth-usd	ETH-10APR20-120-P	eth	120	put	...	2020-03-26T08:00:02.000000000Z	2020-04-10T08:00:00.000000000Z	158.1	offline	1	0.0005	0.0004	0.0004	NaN	NaN
4	deribit-ETH-10APR20-130-C-option	deribit	option	eth	usd	eth-usd	ETH-10APR20-130-C	eth	130	call	...	2020-03-26T08:00:02.000000000Z	2020-04-10T08:00:00.000000000Z	158.1	offline	1	0.0005	0.0004	0.0004	NaN	NaN

5 rows × 22 columns

df_asset_options.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 74827 entries, 0 to 74826
Data columns (total 22 columns):
 #   Column                 Non-Null Count  Dtype 
---  ------                 --------------  ----- 
 0   market                 74827 non-null  object
 1   exchange               74827 non-null  object
 2   type                   74827 non-null  object
 3   base                   74827 non-null  object
 4   quote                  74827 non-null  object
 5   pair                   74827 non-null  object
 6   symbol                 74827 non-null  object
 7   size_asset             74827 non-null  object
 8   strike                 74827 non-null  object
 9   option_contract_type   74827 non-null  object
 10  is_european            74827 non-null  bool  
 11  contract_size          74827 non-null  object
 12  listing                74827 non-null  object
 13  expiration             74827 non-null  object
 14  settlement_price       74117 non-null  object
 15  status                 74827 non-null  object
 16  order_amount_min       74827 non-null  object
 17  order_price_increment  74827 non-null  object
 18  order_taker_fee        74827 non-null  object
 19  order_maker_fee        74827 non-null  object
 20  base_native            3558 non-null   object
 21  quote_native           3558 non-null   object
dtypes: bool(1), object(21)
memory usage: 12.1+ MB

df_asset_options['listing'] = pd.to_datetime(df_asset_options['listing'])
df_asset_options['expiration'] = pd.to_datetime(df_asset_options['expiration'])

df_asset_options = df_asset_options.loc[((df_asset_options.listing > start) & (df_asset_options.listing < end))]
df_asset_options

	market	exchange	type	base	quote	pair	symbol	size_asset	strike	option_contract_type	...	listing	expiration	settlement_price	status	order_amount_min	order_price_increment	order_taker_fee	order_maker_fee	base_native	quote_native
2384	deribit-ETH-10SEP24-1950-C-option	deribit	option	eth	usd	eth-usd	ETH-10SEP24-1950-C	eth	1950	call	...	2024-09-07 08:00:09+00:00	2024-09-10 08:00:00+00:00	2360.48	offline	1	0.0001	0.0003	0.0003	ETH	USD
2385	deribit-ETH-10SEP24-1950-P-option	deribit	option	eth	usd	eth-usd	ETH-10SEP24-1950-P	eth	1950	put	...	2024-09-07 08:00:09+00:00	2024-09-10 08:00:00+00:00	2360.48	offline	1	0.0001	0.0003	0.0003	ETH	USD
2386	deribit-ETH-10SEP24-2000-C-option	deribit	option	eth	usd	eth-usd	ETH-10SEP24-2000-C	eth	2000	call	...	2024-09-07 08:00:09+00:00	2024-09-10 08:00:00+00:00	2360.48	offline	1	0.0001	0.0003	0.0003	ETH	USD
2387	deribit-ETH-10SEP24-2000-P-option	deribit	option	eth	usd	eth-usd	ETH-10SEP24-2000-P	eth	2000	put	...	2024-09-07 08:00:09+00:00	2024-09-10 08:00:00+00:00	2360.48	offline	1	0.0001	0.0003	0.0003	ETH	USD
2388	deribit-ETH-10SEP24-2050-C-option	deribit	option	eth	usd	eth-usd	ETH-10SEP24-2050-C	eth	2050	call	...	2024-09-07 08:00:09+00:00	2024-09-10 08:00:00+00:00	2360.48	offline	1	0.0001	0.0003	0.0003	ETH	USD
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
74822	deribit-ETH-9SEP24-2800-P-option	deribit	option	eth	usd	eth-usd	ETH-9SEP24-2800-P	eth	2800	put	...	2024-09-06 08:00:10+00:00	2024-09-09 08:00:00+00:00	2311.75	offline	1	0.0001	0.0003	0.0003	ETH	USD
74823	deribit-ETH-9SEP24-2850-C-option	deribit	option	eth	usd	eth-usd	ETH-9SEP24-2850-C	eth	2850	call	...	2024-09-06 08:00:10+00:00	2024-09-09 08:00:00+00:00	2311.75	offline	1	0.0001	0.0003	0.0003	ETH	USD
74824	deribit-ETH-9SEP24-2850-P-option	deribit	option	eth	usd	eth-usd	ETH-9SEP24-2850-P	eth	2850	put	...	2024-09-06 08:00:10+00:00	2024-09-09 08:00:00+00:00	2311.75	offline	1	0.0001	0.0003	0.0003	ETH	USD
74825	deribit-ETH-9SEP24-2900-C-option	deribit	option	eth	usd	eth-usd	ETH-9SEP24-2900-C	eth	2900	call	...	2024-09-06 10:37:00+00:00	2024-09-09 08:00:00+00:00	2311.75	offline	1	0.0001	0.0003	0.0003	ETH	USD
74826	deribit-ETH-9SEP24-2900-P-option	deribit	option	eth	usd	eth-usd	ETH-9SEP24-2900-P	eth	2900	put	...	2024-09-06 10:37:00+00:00	2024-09-09 08:00:00+00:00	2311.75	offline	1	0.0001	0.0003	0.0003	ETH	USD

376 rows × 22 columns

TRADE VOLUME

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.

list_options_markets = list(df_asset_options.market.unique())

full_vol = pd.DataFrame()
batch_size = 420

for i in range(0, len(list_options_markets),batch_size):
    mkt_batch = list_options_markets[i:i+batch_size]
    print(str('Retrieving batch of trades for markets ' + str(i) + ' - ' + str(i+batch_size) + '...'))

    vol_batch = client.get_market_trades(
        markets=mkt_batch,
        start_time = start,
        end_time= end,
        page_size=10000
    ).to_dataframe()
    print('Retrieved batch of ' + str(len(vol_batch)) + ' trades')
    
    full_vol = pd.concat((full_vol, vol_batch), axis = 0, ignore_index=False)
    print('Total of ' + str(len(full_vol)) + ' trades\n')

full_vol = full_vol.reset_index(drop=True)

Retrieving batch of trades for markets 0 - 420...


Retrieved batch of 12012 trades
Total of 12012 trades

full_vol = full_vol[['market','time','amount']]
full_vol = full_vol[~(full_vol['time'] > end)]
full_vol.sort_values('time')

	market	time	amount
1071	deribit-ETH-3SEP24-2375-P-option	2024-09-01 06:55:13.947000+00:00	1
1072	deribit-ETH-3SEP24-2375-P-option	2024-09-01 08:04:42.145000+00:00	1
1073	deribit-ETH-3SEP24-2375-P-option	2024-09-01 08:07:41.254000+00:00	3
2429	deribit-ETH-4SEP24-2550-C-option	2024-09-01 08:33:21.911000+00:00	1
2805	deribit-ETH-4SEP24-2700-C-option	2024-09-01 08:47:26.803000+00:00	14
...	...	...	...
11208	deribit-ETH-9SEP24-2300-C-option	2024-09-07 23:54:16.170000+00:00	9
9225	deribit-ETH-8SEP24-2325-C-option	2024-09-07 23:54:52.991000+00:00	2
8166	deribit-ETH-8SEP24-2050-P-option	2024-09-07 23:57:33.509000+00:00	2
9650	deribit-ETH-8SEP24-2400-C-option	2024-09-07 23:58:04.697000+00:00	1
9651	deribit-ETH-8SEP24-2400-C-option	2024-09-07 23:58:53.038000+00:00	1

10824 rows × 3 columns

Retrieve 1-minute Reference Rate

df_refrate = client.get_asset_metrics(
    assets=asset,
    frequency='1m',
    metrics='ReferenceRateUSD',
    start_time=start,
    end_time=end
).to_dataframe()

df_refrate = df_refrate.set_index('time').sort_index().drop(columns=['asset'])
df_refrate

	ReferenceRateUSD
time
2024-09-01 00:00:00+00:00	2512.79
2024-09-01 00:01:00+00:00	2512.41
2024-09-01 00:02:00+00:00	2510.65
2024-09-01 00:03:00+00:00	2513.37
2024-09-01 00:04:00+00:00	2511.32
...	...
2024-09-08 23:55:00+00:00	2298.15
2024-09-08 23:56:00+00:00	2297.49
2024-09-08 23:57:00+00:00	2294.79
2024-09-08 23:58:00+00:00	2296.77
2024-09-08 23:59:00+00:00	2298.61

11520 rows × 1 columns

full_vol['time'] = full_vol['time'].round('T')

# Merge trades data with 1s reference rate
full_vol = full_vol.merge(df_refrate.reset_index(),how='left', on='time')

Calculate USD value of trades

full_vol['USD Volume'] = full_vol['amount'] * full_vol['ReferenceRateUSD']

full_vol

	market	time	amount	ReferenceRateUSD	USD Volume
0	deribit-ETH-10SEP24-1950-P-option	2024-09-07 09:06:00+00:00	5	2293.8	11469.0
1	deribit-ETH-10SEP24-1950-P-option	2024-09-07 09:43:00+00:00	10	2279.45	22794.5
2	deribit-ETH-10SEP24-1950-P-option	2024-09-07 09:43:00+00:00	9	2279.45	20515.05
3	deribit-ETH-10SEP24-1950-P-option	2024-09-07 09:43:00+00:00	1	2279.45	2279.45
4	deribit-ETH-10SEP24-1950-P-option	2024-09-07 11:42:00+00:00	5	2285.0	11425.0
...	...	...	...	...	...
10819	deribit-ETH-9SEP24-2750-C-option	2024-09-06 17:38:00+00:00	1	2235.41	2235.41
10820	deribit-ETH-9SEP24-2750-C-option	2024-09-07 17:02:00+00:00	5	2288.46	11442.3
10821	deribit-ETH-9SEP24-2750-C-option	2024-09-07 18:21:00+00:00	45	2278.46	102530.7
10822	deribit-ETH-9SEP24-2750-C-option	2024-09-07 18:21:00+00:00	23	2278.46	52404.58
10823	deribit-ETH-9SEP24-2800-P-option	2024-09-06 17:37:00+00:00	1	2233.79	2233.79

10824 rows × 5 columns

vol_sum = full_vol.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True)).sum()

vol_sum.to_csv('./deribit_' + str(asset).upper() + '_options_vol_' + str(start) + '_to_' + str(end) + '.csv')

vol_sum[['USD Volume']]

	USD Volume
time
2024-09-01 00:00:00+00:00	5424658.14
2024-09-02 00:00:00+00:00	19562749.43
2024-09-03 00:00:00+00:00	40646881.35
2024-09-04 00:00:00+00:00	63609486.54
2024-09-05 00:00:00+00:00	44657679.33
2024-09-06 00:00:00+00:00	158263998.37
2024-09-07 00:00:00+00:00	44401580.5

v = vol_sum.plot.line(y='USD Volume')
v.set_xlabel("Date", fontsize = 15)
plt.setp(v.get_yticklabels(), fontsize=13)
plt.setp(v.get_xticklabels(), fontsize=13)
v.set_xlabel("")
plt.xlim([vol_sum.index[0], vol_sum.index[-1]])
v.set_ylabel("Daily Volume (USD)\n", fontsize = 15)
v.set_title(('\nDeribit ' + str(asset).upper() + ' Options Volume\n'),fontsize=23)
v.get_legend().remove()
v.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '${:,.1f}'.format(x/1000000) + 'M'))

OPEN INTEREST

Open interest represents the number of contracts that are currently outstanding and not settled for a specific derivatives market.

# Drop markets without open interest data
oi_cat = df_asset_options.loc[df_asset_options.listing < end, 'market'].tolist()
len(oi_cat)

376

full_oi = pd.DataFrame()
batch_size = 420

for i in range(0, len(oi_cat),batch_size):
    mkt_batch = oi_cat[i:i+batch_size]
    print(str('\nRetrieving EOD open interest for markets ' + str(i) + ' through ' + str(i+batch_size) + '...'))
    
    start_date = pd.to_datetime(start)
    end_date = pd.to_datetime(end)
    delta = timedelta(days=1)
    print(str(start_date) + '\n...')
    
    while start_date <= end_date:
        
        oi_batch = client.get_market_open_interest(
            markets=mkt_batch,
            start_time = start_date.strftime("%Y-%m-%d"),
            limit_per_market = 1,
            paging_from='start',
            timezone='America/New_York'
        ).to_dataframe()
        #print(oi_batch)
        full_oi = pd.concat((full_oi, oi_batch), axis = 0, ignore_index=False)
        start_date += delta
        
    print(start_date)

Retrieving EOD open interest for markets 0 through 420...
2024-09-01 00:00:00
...


2024-09-09 00:00:00

full_oi.info()

<class 'pandas.core.frame.DataFrame'>
Index: 2534 entries, 0 to 193
Data columns (total 6 columns):
 #   Column          Non-Null Count  Dtype              
---  ------          --------------  -----              
 0   market          2534 non-null   string             
 1   time            2534 non-null   datetime64[ns, UTC]
 2   contract_count  2534 non-null   Int64              
 3   value_usd       2534 non-null   Float64            
 4   database_time   2534 non-null   datetime64[ns, UTC]
 5   exchange_time   2534 non-null   datetime64[ns, UTC]
dtypes: Float64(1), Int64(1), datetime64[ns, UTC](3), string(1)
memory usage: 143.5 KB

oi_sum = full_oi.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))['value_usd'].sum()

oi_sum.to_csv('./deribit_' + str(asset).upper() + '_options_oi_' + str(start) + '_to_' + str(end) + '.csv')
oi_sum

time
2024-09-01 00:00:00+00:00             0.0
2024-09-02 00:00:00+00:00      6467612.33
2024-09-03 00:00:00+00:00     24927750.02
2024-09-04 00:00:00+00:00     55323320.59
2024-09-05 00:00:00+00:00     59305999.71
2024-09-06 00:00:00+00:00      51922555.8
2024-09-07 00:00:00+00:00    144108764.26
2024-09-08 00:00:00+00:00    122269418.49
Freq: D, Name: value_usd, dtype: Float64

#p = sns.lineplot(data=vol_sum, x="time", y="USD Volume")
oi = oi_sum.plot.area(y='value_usd')
oi.set_xlabel("Date", fontsize = 15)
plt.setp(oi.get_yticklabels(), fontsize=13)
plt.setp(oi.get_xticklabels(), fontsize=13)
oi.set_xlabel("")
plt.xlim([oi_sum.index[0], oi_sum.index[-1]])
oi.set_ylabel("Daily Open Interest (USD)\n", fontsize = 15)
oi.set_title(('\nDeribit ' + str(asset).upper() + ' Options Open Interest\n'),fontsize=23)
# oi.get_legend().remove()
oi.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '${:,.2f}'.format(x/1_000_000) + 'M'))

Split into Calls/Puts

full_oi_split = full_oi.merge(df_asset_options[['market','option_contract_type']],how='left', on='market')

full_oi_split

	market	time	contract_count	value_usd	database_time	exchange_time	option_contract_type
0	deribit-ETH-10SEP24-1950-C-option	2024-09-07 08:00:00+00:00	0	0.0	2024-09-07 08:00:19.312717+00:00	2024-09-07 08:00:00+00:00	call
1	deribit-ETH-10SEP24-1950-P-option	2024-09-07 08:00:00+00:00	0	0.0	2024-09-07 08:00:18.188738+00:00	2024-09-07 08:00:00+00:00	put
2	deribit-ETH-10SEP24-2000-C-option	2024-09-07 08:00:00+00:00	0	0.0	2024-09-07 08:00:18.188738+00:00	2024-09-07 08:00:00+00:00	call
3	deribit-ETH-10SEP24-2000-P-option	2024-09-07 08:00:00+00:00	0	0.0	2024-09-07 08:00:18.708225+00:00	2024-09-07 08:00:00+00:00	put
4	deribit-ETH-10SEP24-2050-C-option	2024-09-07 08:00:00+00:00	0	0.0	2024-09-07 08:00:18.708225+00:00	2024-09-07 08:00:00+00:00	call
...	...	...	...	...	...	...	...
2529	deribit-ETH-9SEP24-2800-P-option	2024-09-08 04:00:00+00:00	1	2285.35	2024-09-08 04:00:06.461248+00:00	2024-09-08 04:00:00+00:00	put
2530	deribit-ETH-9SEP24-2850-C-option	2024-09-08 04:00:00+00:00	0	0.0	2024-09-08 04:00:01.855497+00:00	2024-09-08 04:00:00+00:00	call
2531	deribit-ETH-9SEP24-2850-P-option	2024-09-08 04:00:00+00:00	0	0.0	2024-09-08 04:00:03.353208+00:00	2024-09-08 04:00:00+00:00	put
2532	deribit-ETH-9SEP24-2900-C-option	2024-09-08 04:00:00+00:00	0	0.0	2024-09-08 04:00:04.393566+00:00	2024-09-08 04:00:00+00:00	call
2533	deribit-ETH-9SEP24-2900-P-option	2024-09-08 04:00:00+00:00	0	0.0	2024-09-08 04:00:02.869006+00:00	2024-09-08 04:00:00+00:00	put

2534 rows × 7 columns

calls = full_oi_split.loc[(full_oi_split.option_contract_type == 'call')]
call_sum_split = calls.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))[['value_usd']].sum()
puts = full_oi_split.loc[(full_oi_split.option_contract_type == 'put')]
put_sum_split = puts.groupby(pd.Grouper(key='time', axis=0, freq='1D', sort=True))[['value_usd']].sum()

put_sum_split = put_sum_split.rename(columns={"value_usd": "Puts - USD Value", "contract_count": "Puts - Contract Count" })
call_sum_split = call_sum_split.rename(columns={"value_usd": "Calls - USD Value", "contract_count": "Calls - Contract Count" })

full_oi_split = call_sum_split.merge(put_sum_split,how='left', on='time')
full_oi_split

	Calls - USD Value	Puts - USD Value
time
2024-09-01 00:00:00+00:00	0.0	0.0
2024-09-02 00:00:00+00:00	4987937.59	1479674.74
2024-09-03 00:00:00+00:00	14177673.6	10750076.42
2024-09-04 00:00:00+00:00	30418324.31	24904996.28
2024-09-05 00:00:00+00:00	37814891.94	21491107.77
2024-09-06 00:00:00+00:00	24772293.7	27150262.1
2024-09-07 00:00:00+00:00	73624086.44	70484677.82
2024-09-08 00:00:00+00:00	61750871.09	60518547.4

full_oi_split['Put/Call Ratio'] = full_oi_split['Puts - USD Value'] / full_oi_split['Calls - USD Value']
full_oi_split[['Put/Call Ratio']]

	Put/Call Ratio
time
2024-09-01 00:00:00+00:00	NaN
2024-09-02 00:00:00+00:00	0.296651
2024-09-03 00:00:00+00:00	0.75824
2024-09-04 00:00:00+00:00	0.81875
2024-09-05 00:00:00+00:00	0.568324
2024-09-06 00:00:00+00:00	1.095993
2024-09-07 00:00:00+00:00	0.957359
2024-09-08 00:00:00+00:00	0.980044

full_oi_split.to_csv('./deribit_' + str(asset).upper() + '_options_oi_calls_puts_' + str(start) + '_to_' + str(end) + '.csv')

pc = sns.lineplot(data=full_oi_split[['Put/Call Ratio']], x="time", y="Put/Call Ratio")
pc.set_xlabel("Date", fontsize = 15)
plt.setp(pc.get_yticklabels(), fontsize=13)
plt.setp(pc.get_xticklabels(), fontsize=13)
pc.set_xlabel("")
plt.xlim([full_oi_split.index[0], full_oi_split.index[-1]])
pc.set_ylabel("Put/Call Ratio\n", fontsize = 15)
pc.set_title(('\nDeribit ' + str(asset).upper() + ' Options\nPut/Call Ratio\n'),fontsize=23)
pc.yaxis.set_major_formatter(mticker.FuncFormatter(lambda x, pos: '{:,.2f}'.format(x)))