Aggregating Orderbook Depth to Create Liquidity Metrics

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Last updated 2 months ago

from os import environ import sys import pandas as pd import seaborn as sns import logging from datetime import date, datetime, timedelta from coinmetrics.api_client import CoinMetricsClient import json import logging from pytz import timezone as timezone_conv from datetime import timezone as timezone_info import matplotlib import matplotlib.dates as mdates import matplotlib.ticker as ticker from matplotlib.dates import MonthLocator, DateFormatter, YearLocator, AutoDateLocator from matplotlib.ticker import NullFormatter import matplotlib.pyplot as plt import numpy as np import plotly.express as px import matplotlib.ticker as mticker import matplotlib as mpl from matplotlib.offsetbox import OffsetImage, AnnotationBbox import matplotlib.image as mpimg %matplotlib inline

# 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)

['bittrex-btc-usdc-spot', 'bullish-btc-usdc-spot', 'bitfinex-btc-usd-spot', 'binance.us-btc-usdc-spot', 'ftx-btc-usd-spot', 'kucoin-btc-usdt-spot', 'bullish-btc-usd-spot', 'binance.us-btc-usdt-spot', 'cex.io-btc-usdt-spot', 'mexc-btc-busd-spot', 'coinbase-btc-usdc-spot', 'hitbtc-btc-usdc-spot', 'huobi-btc-usdt-spot', 'okex-btc-usdc-spot', 'binance-btc-busd-spot', 'poloniex-btc-usdt-spot', 'huobi-btc-usdc-spot', 'kraken-btc-usdc-spot', 'bitstamp-btc-usdt-spot', 'binance-btc-usdc-spot', 'coinbase-btc-usd-spot', 'hitbtc-btc-usdt-spot', 'kucoin-btc-usdc-spot', 'coinbase-btc-usdt-spot', 'mexc-btc-usdc-spot', 'mexc-btc-usdt-spot', 'kraken-btc-usdt-spot', 'kraken-btc-usd-spot', 'itbit-btc-usd-spot', 'bittrex-btc-usd-spot', 'crypto.com-btc-usd-spot', 'lmax-btc-usd-spot', 'bullish-btc-usdt-spot', 'bitflyer-btc-usd-spot', 'ftx-btc-usdt-spot', 'binance.us-btc-busd-spot', 'gemini-btc-usd-spot', 'liquid-btc-usd-spot', 'erisx-btc-usd-spot', 'ftx.us-btc-usd-spot', 'crypto.com-btc-usdt-spot', 'bybit-btc-usdc-spot', 'gate.io-btc-usdt-spot', 'liquid-btc-usdt-spot', 'okex-btc-usdt-spot', 'poloniex-btc-usdc-spot', 'binance.us-btc-usd-spot', 'ftx.us-btc-usdt-spot', 'binance-btc-usdt-spot', 'bittrex-btc-usdt-spot', 'bitfinex-btc-usdt-spot', 'gate.io-btc-usdc-spot', 'liquid-btc-usdc-spot', 'bybit-btc-usdt-spot', 'gemini-btc-usdt-spot', 'bitstamp-btc-usd-spot', 'gate.io-btc-usd-spot', 'cex.io-btc-usd-spot', 'bitstamp-btc-usdc-spot']

df['liquidity_depth_1_percent_ask_volume_usd'] = df['liquidity_depth_1_percent_ask_volume_usd'] * -1 df = df.rename(columns={"liquidity_depth_1_percent_ask_volume_usd": "ASKS", "liquidity_depth_1_percent_bid_volume_usd": "BIDS"})

time 2023-01-01 00:00:00+00:00 -51711674.3155 2023-01-01 01:00:00+00:00 -45829606.793167 2023-01-01 02:00:00+00:00 -45264924.078603 2023-01-01 03:00:00+00:00 -49672194.152268 2023-01-01 04:00:00+00:00 -45360291.558192 ... 2023-01-08 19:00:00+00:00 -48736064.951989 2023-01-08 20:00:00+00:00 -42514146.912984 2023-01-08 21:00:00+00:00 -48193752.138421 2023-01-08 22:00:00+00:00 -46457643.168556 2023-01-08 23:00:00+00:00 -43813017.641122 Name: ASKS, Length: 192, dtype: Float64

# Create the figure and axes plt.rcParams['font.family'] = 'arial' fig, ax = plt.subplots(figsize=(15, 9)) ax.set_facecolor('white') # # Add logo image # logo_path = './cm-logo.png' # logo_img = mpimg.imread(logo_path) # logo_offset = OffsetImage(logo_img, zoom=0.1) # logo_annotation = AnnotationBbox(logo_offset, xy=(0.1, 1.05), xycoords='axes fraction', # bboxprops={'facecolor': 'white', 'edgecolor': 'none'}) # ax.add_artist(logo_annotation) # Plot the area chart for BIDS (above x-axis) in green ax.fill_between(sum_bids.index, sum_bids.astype(float), color='green', alpha=0.5) # Plot the area chart for ASKS (below x-axis) in red ax.fill_between(sum_asks.index, sum_asks.astype(float), color='red', alpha=0.5) ax.set_xlabel('') ax.set_ylabel('ASKS BIDS\n',fontweight='bold',fontsize=16) ax.set_title(str(asset).upper() + ' Market Depth (\u00B11%)\n', fontsize=24) plt.suptitle(' USD & Stablecoin Pairs (USDC, USDT, BUSD)', fontsize=13.5) formatter = mticker.FuncFormatter(lambda x, pos: f'${x/1e6:.1f}M' if x >= 0 else f'-$ {abs(x)/1e6:.1f}M') ax.yaxis.set_major_formatter(formatter) ax.yaxis.grid(color='gray', linestyle='dashed', alpha=0.2) ax.xaxis.set_major_formatter(mdates.DateFormatter('%b %Y')) ax.xaxis.set_major_locator(mdates.MonthLocator(interval=1)) plt.xticks(rotation=0) ax.set_xlim(df['time'].min(), df['time'].max()) plt.subplots_adjust(top=0.95, bottom=0.1) plt.savefig('./' + str(asset).upper() + '-Market-Depth-1-Percent.png', dpi=300, bbox_inches='tight',pad_inches=0.5,facecolor='white') plt.show()

Aggregating Orderbook Depth to Create Liquidity Metrics

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