Comparison
An Alpha Vantage alternative built for backtesting
If you are evaluating an Alpha Vantage alternative, the key question is what you need the data for. Alpha Vantage is known for a free API key and broad coverage of stocks, FX, crypto and technical indicators, with a daily request cap on the free tier. FinzData is built for research and backtesting: survivorship-free US equity history, point-in-time fundamentals, positioning data and bulk files, all through one key and a pandas-first Python client.
What Alpha Vantage is known for
Alpha Vantage is a popular market-data API known for offering a free API key, broad asset coverage (US and global stocks, foreign exchange, cryptocurrencies) and a large catalogue of technical indicators. The free tier carries a daily request cap, and paid plans raise throughput. For many hobby projects, dashboards and lightweight quote checks, that combination works well.
Researchers usually start looking for an Alpha Vantage alternative when a backtest needs things a quote API is not designed around: delisted names, fundamentals as they were known at the time, and bulk history that does not require tens of thousands of individual requests.
What FinzData includes
FinzData is a market-data API and Python client (pip install finzdata) that mirrors the yfinance interface and returns pandas DataFrames. The table below summarises what is included, so you can check each row against your current provider.
| Dataset | FinzData | Check with Alpha Vantage |
|---|---|---|
| Delisted stocks | Yes — 16,000+ US stocks since January 2000, including delisted names (survivorship-free) | See their docs |
| Point-in-time fundamentals | Yes — SEC XBRL company facts keyed by filing date | See their docs |
| COT positioning | Yes — legacy, disaggregated, TFF and supplemental reports, 950+ futures markets since 1986 | See their docs |
| 13F holdings | Yes — SEC 13F institutional holdings | See their docs |
| Short interest | Yes — FINRA short interest since 2017 | See their docs |
| Macro vintages | Yes — 11,000+ US series with every revision (FRED/ALFRED) | See their docs |
| Pandas client | Yes — mirrors yfinance: Ticker, history, download | See their docs |
| Bulk files | Yes — Parquet and bulk files on paid plans | See their docs |
Why delisted names and point-in-time data matter
A backtest run only on stocks that still exist today overstates returns, because the losers that were acquired or delisted are missing. FinzData keeps delisted names in the universe, so a screen run in 2008 sees the same constituents a trader would have seen then.
The same logic applies to fundamentals. FinzData stores SEC XBRL company facts point-in-time by filing date, so a value strategy uses the numbers that were public on each rebalance date, not restated figures published later. Daily point-in-time valuation ratios (P/E, P/B, P/S, EV/EBITDA, market cap, dividend yield) are available from 2009.
Migrating from Alpha Vantage
Migration is usually a small change because the FinzData client mirrors yfinance. Replace your price download calls with yf.Ticker(...).history(...) or the lower-level client, and keep the rest of your pandas pipeline unchanged. Prices are stored as traded; splits and dividends are published separately and applied on read via adjust='none'|'splits'|'all'.
Code: prices and point-in-time fundamentals
import finzdata as yf
# Daily bars, unadjusted, for a delisted or live ticker
df = yf.Ticker("AAPL").history(start="2005-01-01", interval="1d")
# Lower-level client for the rest of the datasets
c = yf.Client()
# Prices with explicit adjustment control
px = c.prices("AAPL", adjust="all")
# Fundamentals as known on a given filing date
pe = c.fundamentals(ticker="AAPL", concept="EarningsPerShareBasic", as_of="2015-06-30")
# Daily point-in-time valuation
val = c.valuation("AAPL", start="2010-01-01")
# COT positioning for a futures market
cot = c.cot(report="tff", market="E-MINI S&P 500")
When Alpha Vantage is the better choice
Alpha Vantage is a reasonable choice if you want a free API key for light usage, need FX or crypto quotes alongside equities, or want pre-computed technical indicators served from the same endpoint. If your work is a dashboard or a small script rather than a survivorship-free backtest, check their current pricing page and free tier — it may cover everything you need.
Pricing and trying it out
FinzData's free tier includes the last 12 months of every dataset and 1,000 API calls per day, no card required. Paid look-back bundles are $195 for the first 5 years of history and $95 for each further 5 years, plus $19.95/month for daily updates; institutional licensing is $975 once plus $59.95/month. You can inspect free 10-row samples, browse live charts, read the docs or see pricing.
Frequently asked questions
Is FinzData a drop-in Alpha Vantage alternative?
For Python users, close to it: the client mirrors yfinance, so yf.Ticker("AAPL").history(...) returns a pandas DataFrame. The REST API at https://api.finzdata.com returns JSON or CSV for non-Python stacks.
Does FinzData include delisted stocks?
Yes. Coverage is 16,000+ US stocks since January 2000 including delisted names, so backtests are survivorship-free.
Can I get fundamentals as they were known at the time?
Yes. SEC XBRL company facts are stored point-in-time by filing date, and daily point-in-time valuation ratios are available from 2009.
Does FinzData cover FX and crypto like Alpha Vantage?
FinzData focuses on US equities, ETFs, futures positioning, ownership and macro data. If FX and crypto quotes are central to your work, check Alpha Vantage's docs for their current coverage.
How do I avoid per-request limits when loading history?
Paid plans include Parquet and bulk files, so you can load full history in bulk instead of paging through REST requests.
Is there a free tier?
Yes: the last 12 months of every dataset and 1,000 API calls per day, with no card required.