Examples and tutorials
Options
Equity options: Introduction
Options on futures: Introduction
All options with a given underlying
Join options with underlying prices
US equity options volume by venue
Resample US equity options NBBO
Estimate implied volatility
Get symbols for 0DTE options
Calculate daily statistics for equity options
Historical data
Request a large number of symbols
Programmatic batch downloads
Best bid, best offer, and midprice
Custom OHLCV bars from trades
Join schemas on instrument ID
Plot a candlestick chart
Calculate VWAP and RSI
End-of-day pricing and portfolio valuation
Benchmark portfolio performance
Market halts, volatility interrupts, and price bands
Resample OHLCV from 1-minute to 5-minute
Algorithmic trading
A high-frequency liquidity-taking strategy
Build prediction models with machine learning
Execution slippage and markouts
Matching engine latencies
Using messaging rates as a proxy for implied volatility
Mean reversion and portfolio optimization
Pairs trading based on cointegration
Build a real-time stock screener
Core concepts
Venues and datasets
CME Globex MDP 3.0
Cboe BYX Depth
Cboe BYZ Depth
Cboe EDGA Depth
Cboe EDGX Depth
Databento US Equities Basic
Databento US Equities Mini
Databento US Equities Summary
Eurex Exchange
European Energy Exchange
ICE Endex iMpact
ICE Europe Commodities iMpact
ICE Europe Financials iMpact
ICE Futures US iMpact
IEX TOPS
MEMX Memoir
MIAX Depth of Market
Nasdaq Basic with NLS Plus
Nasdaq TotalView-ITCH
NYSE American Integrated
NYSE Arca Integrated
NYSE Texas Integrated
NYSE National Trades and BBO
NYSE Integrated
OPRA Pillar
Corporate actions
Adjustment factors
Security master
API Reference
Resources
Release notes
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HTTP API
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Raw API
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Data
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Collapse all
Examples and tutorials
Historical data
End-of-day pricing and portfolio valuation
Overview
This example shows how to use the Historical client to calculate the end-of-day (EOD) value of a hypothetical portfolio. To do this we will request the closing price for each symbol on a given date and use this price to determine the value of our portfolio.
OHLCV-1d schema
We'll demonstrate this example using the OHLCV-1d schema.
The OHLCV family of schemas contain the opening, high, low and closing prices as well
as the aggregated volume of trades within a time interval. Since we are interested in
end-of-day evaluation, we'll use an interval of one day, which is specified by the
suffix -1d
.
Many users will prefer to use the official daily settlement prices found in the
statistics
schema for this purpose.
Example
import databento as db
# A hypothetical portfolio mapping symbols to a quantity of shares
portfolio = {
"AAPL": 200,
"AMZN": 200,
"GOOG": 100,
"META": 100,
"NFLX": 114,
}
# Create a historical client
client = db.Historical("YOUR_API_KEY")
# Request OHLCV-1d data
data = client.timeseries.get_range(
dataset="XNAS.ITCH",
start="2022-09-19",
symbols=list(portfolio.keys()),
stype_in="raw_symbol",
schema="ohlcv-1d",
)
# Convert to DataFrame
eod_data = data.to_df()
eod_data = eod_data.set_index("symbol")
# Sum the products of the close prices and portfolio quantities
eod_evaluation = sum(
eod_data.at[symbol, "close"] * quantity for symbol, quantity in portfolio.items()
)
print(f"${eod_evaluation:,.2f}")