Market Price API

REST API · For developers

Add Live Market Prices Using Market Price API

Retrieve current market prices together with daily performance, trading volume, market capitalization, bid/ask prices, pre-market and post-market data, and market status using a single API. Market Price API returns a structured snapshot for stocks, ETFs, and other supported assets.

It’s designed for dashboards, watchlists, portfolio applications, asset pages, automation workflows, and internal tools that need current market data without retrieving full historical datasets. A lightweight response keeps integrations fast while providing the key information most applications need.

Includes /market-price View Documentation
Candlestick price chart above a table listing seven trading days (2024-05-16 through 2024-05-24) with Open, High, Low, Close, and Volume columns, followed by a row of icons for trend, calendar, percentage, filters, and currency.

Market Price API


Description

Retrieve current market prices and essential trading information through a lightweight API. Market Price API returns the latest available price together with daily change, trading volume, market capitalization, bid and ask prices, pre-market and post-market prices, opening and previous close values, and current market status in a single response.

Use it to build watchlists, portfolio dashboards, asset pages, price widgets, automation workflows, and AI applications that require up-to-date market snapshots. The endpoint is optimized for fast integrations, low bandwidth usage, and applications that need current pricing without requesting larger market or historical datasets.


Interface Example

Interface example for Market Price API showing three overlapping UI cards: an AAPL price widget (Apple, Stock, NASDAQ, US) with previous close $314.86 and current price $329.10, up $1.60 (+0.49%), marked Pre-market; a Watchlist (ETFs) table listing SPY, QQQ, VTI, and VXUS with current price, change %, volume, and status columns (all marked PRE); and an NVDA session breakdown card comparing Pre-Market ($194.32, −1.11%), Regular Session ($196.51, −4.99%), and Post-Market ($196.14, −0.19%) prices.

Output Example


AAPL — Apple · Stock · US
$329.10 ▲ +$1.60 (+0.49%) · Pre-market
Market Cap $4.81T · Previous Close $314.86 · Volume 60.78M
Regular session closed at $327.50 (+4.01%) · Post-market $327.80 (+0.09%)

7203.T — Toyota Motor Corporation · Stock · Japan
¥3,008 ▲ +¥42.50 (+1.43%) · Regular session
Market Cap ¥35.62T ($18.36 USD) · Previous Close ¥2,965.50 · Volume 30.62M

VTSAX — Vanguard Total Stock Mkt Idx Adm · Mutual Fund · US
$177.75 ▲ +$0.18 (+0.10%) · Pre-market
Previous Close $177.57

How to Build this Workflow

This workflow is built using the following FinImpulse APIs

Resources


API Cost Examples

Scenario APIs Used Usage Example Estimated Monthly Cost
Portfolio Dashboard Market Price API 10,000 price requests ≈ $0.20
Market Price API = $0.00002
10,000 requests × $0.00002 = $0.20 / month
Watchlists Market Price API 100,000 price requests ≈ $2.00
Market Price API = $0.00002
100,000 requests × $0.00002 = $2.00 / month
Price Widgets Market Price API 500,000 price requests ≈ $10.00
Market Price API = $0.00002
500,000 requests × $0.00002 = $10.00 / month
Asset Pages Market Price API 1,000,000 price requests ≈ $20.00
Market Price API = $0.00002
1,000,000 requests × $0.00002 = $20.00 / month

Disclaimer. The pricing examples above are calculated using the APIs shown in this workflow and represent typical usage scenarios. Static data can be cached client-side to reduce actual costs below these estimates, and the Sandbox environment is available for development and testing separately from production usage. Actual costs depend on the endpoints, datasets, response size, request frequency, caching strategy, and additional data included in your application.

FinImpulse provides financial data and analytics APIs only. AI-generated responses depend on the application, prompts, and language model used. FinImpulse does not provide investment advice, trading recommendations, or guarantee the accuracy of AI-generated conclusions.

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