Range is the research bench for serious day traders. 10 years of survivorship-bias-free US equity data. Realistic fill simulation. Walk-forward and probabilistic Sharpe scoring by default — so you ship strategies that survive contact with the market, not curve-fits that look pretty in TradingView.
Founding 100 lock in $9/mo for life (vs $29 retail). First access Q3 2026.
Every retail platform — TradingView, the marketplaces, the YouTube notebooks — ships with the same hidden defects. The strategies look profitable because the test was rigged. Not on purpose. By default.
"Today's Russell 3000" excludes every busted ticker that delisted. Your ORB backtest never sees the names that collapsed at 9:32 a.m. — only the survivors. Real expected returns are significantly lower than what most tools show.
Most platforms fill at the bar close. Day-trading breakouts move before the close. Skip slippage on a 1.5% breakout and a losing system can look profitable. Several major scanners openly admit they ignore the spread.
Tweak 12 parameters across 5 years. You'll find a "winner" by chance alone. Without walk-forward, Monte Carlo, or a probabilistic Sharpe ratio you're not finding edges — you're finding noise that flatters your priors.
Configure entries, exits, filters, sizing, and execution rules through a form-first builder. Behind the glass: an event-driven engine with realistic spread, queue position, and halt handling. The first no-code platform that doesn't quietly cheat.
Every backtest ships with a Robustness Score: walk-forward out-of-sample performance, probabilistic Sharpe ratio, parameter heatmaps, regime breakdowns, Monte Carlo simulations. Strategies below 60 carry a warning. Below 40, a refusal.
Reproduce strategies from real research — opening-range-breakout variants, gap-and-go studies, VWAP-reclaim setups — in one click. Compare your variants against the published baseline. Build on academic foundations instead of YouTube hot takes.
You've outgrown Pine. You want walk-forward, multi-symbol portfolios, and 10-year universe — without writing a backtester from scratch in Python.
Your audience deserves backtests that hold up under scrutiny. Range exports compliance-aware reports with hypothetical-performance disclosures by default.
Before you risk $500 on another evaluation, validate your strategy against 10 years of US equities — and find out whether it survives a 2022-style regime.
A small, intentionally limited beta. We're picking 100 traders, educators, and prop-prep candidates to use Range before public launch. In exchange for honest feedback, you get:
No — and we won't pretend otherwise. Multiple academic studies (Barber & Odean, Chague et al., FINRA 2020) put the real day-trader success rate well under 5%. Range will not change those base rates. What Range can do is dramatically shorten the time between "I have an idea" and "I know whether it survives serious statistical testing." If a strategy doesn't pass Range's robustness checks, it almost certainly won't make you money live. That alone is worth the subscription.
No. Range refuses to sell "AI-generated alpha." We do use language models for plain-English explanations of your backtest results and for natural-language editing of conditions — but the core engine is a deterministic event-driven simulator running on clean historical data. The differentiation is statistical rigor, not magical signals.
Not at all. Range is form-first. You configure rules through dropdowns, sliders, and conditional blocks. There's an "advanced" mode that exposes a logic tree for multi-condition entries, but you'll never touch a code editor.
Not in v1. We're shipping the research bench first. Paper-trading is on the roadmap for Q4 2026.
US equities only, with 10 years of delisted-aware history on 1-minute bars. Crypto, futures, options, forex are on the roadmap for Q4 2026.
Range is currently a solo project run by a software engineer with a background in systematic trading research. Building in public — beta members get the founder's direct line during the program.