Build and test strategiesat the speed of thought

The AI IDE for quantitative trading — extensive market data and cloud compute built in, with an agent that builds and backtests strategies alongside you.

Get StartedView Pricing
Interactive preview of the QuantPad project workspace: a prompt types into the message field, then you press Send to watch short assistant lines, web search, file creation, and execution play once in the editor and chat.
AAPL implied-vol surface

Market data coverage includes major U.S. futures and equities venues.

Institutional market data, built in

Included with every subscription

Futures, the full US equity universe, and complete options chains — on equities and futures alike — from monthly bars down to the order book, are preloaded in every workspace. No separate data vendor, no API keys, no egress fees. Just import quantpad_data and start researching.

  • 40+
    Futures markets

    Index, rates, metals, energy, FX, grains & crypto

  • 8,000+
    US equities

    The entire listed US stock universe

  • Full
    Options chains

    OPRA equity options + CME options on futures

  • 1s → 1mo
    Bar resolutions

    Plus tick trades, L1 quotes & L2 depth

  • OHLCV bars

    1s · 1m · 1h · 1d base, resampled to any timeframe through monthly

    Illustration only — QuantPad serves historical data, not live feeds.

    Futures
    16 years
    US Equities
    8 years
    Equity Options
    13 years
    Futures Options
    16 years
  • Trades

    Every tick-by-tick print with size, side & venue flags

    Futures
    16 years
    US Equities
    12 months
    Equity Options
    3 years
    Futures Options
    16 years
  • Top-of-book quotes (L1)

    Best bid/offer, sizes & consolidated BBO snapshots

    Futures
    16 years
    US Equities
    12 months
    Equity Options
    3 years
    Futures Options
    16 years
  • Order-book depth (L2)

    10-level market-by-price book for microstructure work

    Futures
    30 days
    US Equities
    30 days
    Equity Options
    —
    Futures Options
    30 days

History columns show plan-included lookback. Futures are served as back-adjusted continuous contracts; the current in-progress session is excluded.

Futures across every major sector

  • Equity index
  • Treasuries
  • Metals
  • Energy
  • FX
  • Grains
  • Crypto
  • Volatility

Full-size and micro contracts — ES, NQ, CL, GC, 6E, ZN, BTC and more — each routed to the right exchange calendar automatically, now with full options chains on the major roots.

Macro & fundamentals, same workspace

FRED economic data
The full St. Louis Fed database — GDP, CPI, rates, employment and thousands more series.
SEC EDGAR filings
Company submissions, XBRL financial facts and full-text filing search.

Your data, in full market context

Manual or systematic, ask a question about your trades and the agent pulls the real market data around every entry — volatility, trend, regime — so the answer reflects what the market was actually doing.

Animated preview: upload a trade log, the agent reads it, writes analysis code, runs it, shows a regime chart, and suggests next steps.
ES pullback analysis
Ask QuantPad to refine the analysis…

Production-grade DSL coding

Build indicators and strategies in the languages your venues use. Skills, retrieval, and linters are integrated end-to-end.

  • Multi-DSL

    PineScript, NinjaScript, PowerLanguage, EasyLanguage — one agent, consistent workflow across venues.

Pine strategy draft
Build a PineScript v6 strategy for ES: ATR trailing stop with controlled pyramiding. Load the Pine skill, search the example library for similar patterns, draft the script, and run it through the linter.
pinescript-v6
ATR-based trailing stop with pyramiding
strategyrisk-managementatr
// @version=6
strategy("ATR Pyramid", overlay=true, pyramiding=3)
atrLen = input.int(14, "ATR Length")
atrMult = input.float(1.5, "Trail Multiplier")

The linter flagged two issues — ATR length must be a compile-time simple int, and the entry condition reads cleaner with an explicit boolean. Patching both now.

atrVal = ta.atr(atrLen)
atrVal = ta.atr(14)
@@
if ta.crossover(close, ta.sma(close, 50))
bool longSignal = ta.crossover(close, ta.sma(close, 50))

That revision passes the linter. You can paste it into TradingView or keep refining the risk and pyramid rules here.

Follow up on this strategy…

Stop paying to fail prop challenges

Upload your trade log and QuantPad runs thousands of Monte Carlo simulations against the real rules of Topstep, Apex, Take Profit Trader and more. Know your pass probability and expected payout before you pay for an evaluation.

Preview of the prop firm Monte Carlo simulator: use Challenge or Funded to switch the equity path chart; metrics show both phases. Pass, fail, and payout statistics come from a sample trade log.
Net EV (mean)

$579

Payout probability

66.80%

Mean payout

$2,703

Days to 1st payout

10.4 days

Net EV, 5th pct

-$998

Net EV, 95th pct

$4,881

Challenge equity paths
Trading day 1 / 39Median $49.8K
Median P&L$-221
p5 – p95$-595 to $1.1K
59% losing

Monthly usage included, top up any time

Every paid plan includes a monthly usage allowance that refreshes each month. Push it hard and you can top up anytime — additional usage goes straight to model-provider costs, with no markup from us.

  • Your allowance refreshes every month
  • Top up only if you need more
  • Pass-through pricing — zero markup
Included usageActive
58%
0%Refreshes monthly100%
Additional balance

Top up at provider cost — no markup. Auto-recharge optional.

Build on the community's research

Share, like, favorite, comment on, and clone projects — Python research, papers, and indicators or strategies in Pine and other DSLs. Included with every subscription.

  • Volatility Term Structure
    Official

    Volatility Term Structure

    Compares realized volatility across intraday horizons to read whether near-term vol is calm, elevated, front- or back-loaded.

    Clone-ready
  • Directional Imbalance Map
    Official

    Directional Imbalance Map

    Measures candle acceptance versus rejection to separate clean, persistent directional pressure from mean-reversion risk.

    Clone-ready
  • Trend Quality vs. Mean Reversion
    Official

    Trend Quality vs. Mean Reversion

    Scores when a market is trending cleanly versus chopping, and adapts the playbook.

    Clone-ready
  • Explore the full libraryBrowse every published strategy in the app

Clone in one click

Every file lands in a fresh project — code, notebooks and all — ready to run and make your own.

Publish your own

Share a strategy when you're ready and build a following — or keep exploring what the community ships.

One plan. The full quant stack.

Lock in the launch price now — it stays fixed for as long as your subscription stays active.