BigQuant

AI quant research platform for China's A-share market, Python-first

Business & Finance Freemium Has API
Researched · Published · Reviewed
RECATOOLS Score
6.6 / 10
Capability
7
Value for money
7
Ease of use
6
ASEAN readiness
3
API quality
5
Founded
HQ
Users
Launched
Developer

Overview

BigQuant gives retail and institutional quants in China a factor-mining and backtesting workbench -- petabyte market data, 2,000+ prebuilt factors, visual and Python workflows -- plus a PLUS membership for courses and community. No built-in brokerage; live trading needs a separate broker link.

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Pricing

Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.

Free
Free
Full research environment with base data, factor library and backtesting
  • 2,000+ built-in factors
  • Visual + Python strategy IDE
  • Backtesting and paper trading
  • Community wiki access
PLUS
Custom
Paid membership for courses, community and extra compute
  • 100+ quant/programming/AI courses
  • 10,000+ article knowledge base
  • BigQuant Club community + mentor sessions
  • Priority GPU/compute for factor mining

What you can produce with BigQuant

  • Petabyte-scale historical and real-time China market data
  • 2,000+ prebuilt factor library plus custom factor expression engine
  • Visual (no-code) and Python/Jupyter-style strategy IDE
  • Backtesting engine with paper trading
  • Live trading via connected third-party broker API (no in-house brokerage)
  • PLUS membership: 100+ courses, 10,000+ article knowledge base
  • BigAlpha annual competition with free compute credits
  • Open-source BigQuant Python SDK on GitHub (early stage)
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ASEAN Perspective

BigQuant in Southeast Asia

ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).

RECATOOLS Verdict

BigQuant has been a fixture of China's retail-quant scene since 2016, and it earns that status: a genuinely deep factor library, petabyte-scale historical data, and a workbench that lets you build strategies visually or drop into Python/Jupyter-style notebooks. The free tier is real, not a trial gate, and the annual BigAlpha competition hands out compute credits to active factor-miners.

Two things temper the score. First, BigQuant holds no brokerage license itself, so "live trading" means wiring up a separate broker's API -- a step new users often miss reading about upfront. Second, its marketed AI coding assistant reportedly struggles with anything beyond boilerplate strategy code and occasionally cites outdated API syntax, according to user complaints on Zhihu. It's a serious research tool for China's A-share market; treat the no-code framing skeptically.

Independent AI-assisted assessment by RECATOOLS.

What people say

BigQuant (formally Kuang Bang Technology, founded 2016 in Chengdu by Liang Ju) sits alongside JoinQuant and MiQuant as one of the three platforms Chinese quant hobbyists compare first, per recurring Zhihu comparison threads. Free registration gets you the core research environment -- over 2,000 built-in factors, a factor-expression engine for building derivatives, backtesting, and paper trading -- with a PLUS membership layered on top for courses, a 10,000-plus-article knowledge base, community access and priority compute for GPU-heavy factor mining or deep-learning strategies. Exact PLUS pricing isn't published; it runs through a recharge/credits system rather than a public price list.

The recurring complaint across user threads is that BigQuant has no brokerage license of its own, so "live trading" means routing orders through a separate connected broker -- described by one Zhihu commenter as the platform's biggest sticking point (最大的槽点) for anyone expecting an end-to-end pipeline. A second complaint cluster targets the AI assistant: users report it doesn't reliably know current API syntax and produces strategy code that fails to run once a strategy gets past boilerplate, calling repeated back-and-forth with it a waste of time. A third is that BigQuant markets itself as usable with "zero code," but real strategy work still demands solid programming skills, and documentation is described as hard to search.

On the plus side, nobody disputes the data depth or the factor library size, and the platform has enough of an install base to run its own open GitHub toolbox (BigQuant/bigquant, still in early active development with a handful of commits) alongside the hosted product. For readers in ASEAN markets, the practical limit is coverage: the platform, its documentation and its community are built around China's A-share market, with no indication of Southeast Asian exchange data or English-language support -- and no evidence the platform has ever been localized for a non-Chinese audience, in contrast to some rival quant platforms that at least offer partial English documentation.

Summary of public user & expert reviews, compiled by RECATOOLS.

About this listing

Researched on
Published on
Last reviewed

This entry was compiled from publicly available data including BigQuant's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with BigQuant unless explicitly stated.

Data accuracy

Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.

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