FinzData vs QuantConnect: your data, yours to keep

FinzData vs QuantConnect at a glance

A platform rents you access. FinzData gives you the archive. Here is the difference in one table.

* Plus $195 once for 5 years of the whole US market.

Get a free API key See the whole US market for $195

QuantConnect facts from quantconnect.com/terms (§2.6), quantconnect.com/pricing and its Dataset Market, checked 2026-10-17 to 2026-10-21.

The sentence

From QuantConnect's Terms of Service (§2.6), checked 2026-10-17:

"Data provided through QuantConnect may only be used inside the QuantConnect platform."

Export and extraction are prohibited by any means — the terms name the routes explicitly: including through logs, charts, Object Store downloads, network requests, the API, the MCP server, or AI agents. Read that last one again. The workflow this industry is moving to — an AI agent reading your research data in your own tools — is the workflow the terms single out.

Everything you build on that data inherits the confinement. Your backtests, your universes, your derived datasets: usable inside the platform, for as long as you subscribe, and nowhere else, ever.

A QuantConnect alternative you own: what you get with FinzData

• Ownership. Buy the years once and keep them. Bulk files and Parquet on your own machines, under a licence that lets you use them in any stack, any cloud and any future platform. Stop the updates and the history you bought stays yours.
• Breadth. 16,000+ US stocks with the delisted names still in them, 231 ETFs, 139 futures markets with 17,605 contracts, 18,000+ macro series, COT since 1986, 13F for every manager, options-market gamma, crypto since 2015 and point-in-time fundamentals, on one key.
• Depth. 26+ years of history at every resolution you backtest on: 1-minute, 5-minute, 15-minute, 30-minute, hourly and daily, with tick-level trades on the Institutional plan.
• Time, kept honest. Every row is stamped with the moment it became known. Macro arrives as first published, GEX as it stood after the close, COT on the day the CFTC released it.
• Signals no one else sells this way. Point-in-time dealer gamma exposure, the gamma flip and the walls, and the Quantitative Model's regime labels for growth, inflation, liquidity, credit and risk.
• Built for AI. A Python client that works like yfinance, an MCP server for Claude and ChatGPT, and an agent pricing tier, so your own agents read your data in your own tools.
• Value. The whole US market from $195 once plus $19.95 a month for daily updates, one ticker from $19, and no API call limit on any paid purchase.

Already building in LEAN? Our one-file integration (below) brings FinzData into QuantConnect Cloud and local LEAN, and the files stay yours outside it.

The industry's best value

The industry's best value. Start with exactly what your research needs, pay once, and own it:

The one-time price buys the history outright. Daily updates are $19.95 a month, and they are your choice: stop them at any time and every year you bought stays yours, so your cost stops at the one-time price.

Start free. A free key is $0: 1,000 calls a day and the last 12 months of every dataset, no card required. Every price is on the shop.

Use FinzData in QuantConnect and LEAN

One Python file carries FinzData into QuantConnect Cloud and local LEAN: survivorship-free prices, point-in-time GEX for single stocks, ETFs and the major indexes, macro as first published, regime labels, COT and continuous futures. Every row arrives only when the world could have seen it. And because you own what you buy, the same history works in every other tool you use.

Download finzdata_qc.py Example algorithm Get a free key

Set up FinzData in LEAN in three steps

1. Add the file. In your project, create finzdata_qc.py and paste in the module. With the LEAN CLI, drop it next to main.py.
2. Add your key as a parameter. Name it finzdata-api-key. With the LEAN CLI, put it under parameters in the project's config.json.
3. Subscribe to data. In initialize:

from finzdata_qc import FinzData, FinzDataGex, FinzDataMacro

FinzData.set_api_key(self.get_parameter("finzdata-api-key"))
self.gex = self.add_data(FinzDataGex, "SPY", Resolution.DAILY).symbol
self.unrate = self.add_data(FinzDataMacro, "UNRATE", Resolution.DAILY).symbol

Each point arrives in on_data like any other subscription. data[self.gex].value is the net GEX in billions, and every other column is there by name, such as data[self.gex]["flip"] or data[self.gex]["call_wall"].

What you can add

Columns you can read

Time, kept honest

Each class releases a row only when the world could have seen it. GEX arrives after our 17:00 ET compute. COT positions taken on a Tuesday arrive on the Friday the CFTC published them. Macro figures arrive at the close of the day they were published, with the period they describe kept in observation_date. Your backtest trades on what was known, and nothing more.

Example algorithm

Hold SPY while dealers are long gamma, step aside when they turn short gamma, and watch the unemployment rate as it was first published. It shows the mechanics; it is not a recommended strategy.

# FinzData x QuantConnect: example algorithm (Python).
# 1. Add finzdata_qc.py to your project (download: https://finzdata.com/quantconnect/finzdata_qc.py)
# 2. Add a project parameter named "finzdata-api-key" with your key (free key: https://api.finzdata.com)
# 3. Backtest. Free keys return the last 12 months; paid plans return full history.
from AlgorithmImports import *
from finzdata_qc import FinzData, FinzDataBars, FinzDataGex, FinzDataMacro


class FinzDataGammaExample(QCAlgorithm):
    """Hold SPY when dealers are long gamma (calmer markets), step aside when they are short gamma.
    An illustration of point-in-time GEX in LEAN, not a recommended strategy."""

    def initialize(self):
        self.set_start_date(2025, 11, 1)
        self.set_cash(100000)
        FinzData.set_api_key(self.get_parameter("finzdata-api-key"))
        self.spy = self.add_equity("SPY", Resolution.DAILY).symbol
        self.gex = self.add_data(FinzDataGex, "SPY", Resolution.DAILY).symbol           # dealer gamma, known at 17:00 ET
        self.unrate = self.add_data(FinzDataMacro, "UNRATE", Resolution.DAILY).symbol   # unemployment rate, as first published
        self.last_unrate = None

    def on_data(self, data: Slice):
        if data.contains_key(self.unrate):
            self.last_unrate = data[self.unrate].value
        if not data.contains_key(self.gex):
            return
        g = data[self.gex]
        self.plot("GEX", "net_gex_bn", g.value)
        self.plot("GEX", "flip", g["flip"])
        if g.value > 0 and not self.portfolio[self.spy].invested:
            self.set_holdings(self.spy, 1.0)
        elif g.value < 0 and self.portfolio[self.spy].invested:
            self.liquidate(self.spy)

Running locally with the LEAN CLI

pip install lean
lean init
lean project-create --language python "FinzData Gamma"
# copy finzdata_qc.py and the example into "FinzData Gamma", set finzdata-api-key in config.json
lean backtest "FinzData Gamma"

Who should choose FinzData

Choose FinzData if the data itself is the asset: you want survivorship-free, point-in-time history as files you own; you run or plan to run your own stack, your own cloud or AI agents over your data; you want dealer gamma, every macro vintage and regime labels beside your prices; or you simply refuse to let a terms-of-service sentence own your research archive.

Point it at whichever history your research stands on, starting with a free key.

Start with the whole market, for free

A free key gives you the last 12 months of every dataset, 1,000 calls a day, no card. When you are ready, the whole US market is $195 once, every paid purchase has no call limit, and everything you buy is yours to keep.

Get a free API key See prices

Sources and corrections

Prices and product terms checked 2026-10-17 against quantconnect.com/pricing, quantconnect.com/terms (§2.6) and finzdata.com. If any figure on this page is wrong, tell us and we will correct it with the date of the correction.

Frequently asked questions

Related

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• Point-in-time macro data
• Historical stock data with delisted names
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Get a free API key See pricing Download free samples