Any AI can run a backtest. VARRD guarantees it was done right. Describe any trading idea — we test it with real data, real statistics, and the same guardrails that institutional quant firms enforce internally.
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Type any trading intuition in plain English. VARRD finds the pattern in decades of data, builds the formula, and tells you if the edge is real.
Most AI tools let the model do the math. We don't. Our engines calculate. The AI interprets. That distinction is everything.
| Capability | VARRD | ChatGPT (web) |
Claude Code (IDE) |
TradingView | QuantConnect | Composer | Robinhood Cortex |
Webull Vega |
|---|---|---|---|---|---|---|---|---|
| Natural language idea input | ✓ | ✓ | ✓ | ✗ | ✗ | ✓ | ✓ | ✓ |
| Real backtesting engine (not AI-generated stats) | ✓ | ✗ | ✓* | ✓ | ✓ | ✓ | ✗ | ✗ |
| Overfitting guardrails that account for research history | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Lookahead bias detection | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| One-shot OOS enforcement & slippage/commission modeling | ✓ | ✗ | ✗ | ✗ | ✓ | ✗ | ✗ | ✗ |
| Autonomous edge discovery AI researches, tests, and validates overnight |
✓ | ✗ | ✓* | ✗ | ✗ | ✗ | ✗ | ✗ |
| Saved edge library with live scan | ✓ | ✗ | ✗ | Alerts only | ✗ | Community library | ✗ | ✗ |
| Edge persistence and decay tracking | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Portfolio simulation & SL/TP optimization | ✓ | ✗ | ✓* | ✗ | ✓ | ✓ | ✗ | ✗ |
| No coding required | ✓ | ✓ | ✗ | ✗ | ✗ | ✓ | ✓ | ✓ |
* With significant limitations. · Based on publicly available product documentation as of March 2026.
Anyone can ask an AI to find a 4.0 Sharpe ratio setup. It'll happily oblige — with numbers it fabricated. The hard part isn't generating results. It's guaranteeing the results are honest. That's what we built.
Every trading idea can be tested. Describe what you're thinking, and VARRD handles the quantitative heavy lifting.
Say it however you think it. "What happens to gold when real yields drop?" or "Find every time the McRib came back and see if there's an edge to buy Bitcoin."
VARRD loads the data, builds indicators, explores correlations, and surfaces what the numbers show — before jumping to conclusions.
Statistical validation with anti-p-hacking guardrails, multiple comparison correction, and out-of-sample testing. No shortcuts.
If the edge is real, get entry rules, stop levels, and position sizing. If it's not — you know before risking capital.
Every answer is tied to a traceable test. No LLM guessing. No hallucinated statistics.
Any AI can produce a backtest. Our guardrails ensure the results actually mean something. They're enforced at the infrastructure level — not by prompting, not by suggestion. The AI physically cannot skip them. Here are a few.
Every test you run is counted. Try 50 variations? Your significance threshold rises accordingly. No free looks.
Multiple comparison penalty applied automatically. The more things you test, the higher the bar for significance. Based on the Dunn–Bonferroni method (1961).
Out-of-sample validation is sacred. One shot. Locked forever. No peeking, no re-running, no optimizing after the fact. Follows walk-forward validation methodology.
The system catches when a formula accidentally uses future data. Entry timing models account for when you'd actually get filled.
The AI never fabricates a number. Every statistic comes from computed results on real market data. Architecture enforces the separation.
You must see the pattern on a chart and approve it before any test runs. No skipping validation. No silent testing.
Every test is fingerprinted. Can't inflate results by running the same formula, market, and horizon combination twice.
Once out-of-sample validates, the parameters are locked permanently. No tweaking. No curve-fitting. The result is final.
These systems run whether the researcher is a human clicking buttons or an AI agent running autonomously at 3am. The infrastructure doesn't care who's asking — it enforces the same rigor every time.
Every validated setup lives in your personal library. See which edges are firing right now, with exact entry and exit levels.
Every edge you discover through VARRD — whether you found it yourself or your AI agent found it while you slept — gets saved to your personal hypothesis library with full statistical provenance.
When conditions align again, you'll know. Exact entry price, stop loss, take profit, and the statistical backing behind every level.
Trained on the research frameworks of elite systematic traders — generates institutional-quality hypotheses from decades of pattern recognition.
Your agent draws from 40 years of systematic trading frameworks to generate ideas that a senior researcher would recognize as worth testing.
Before testing, your agent profiles the asset like a senior portfolio manager — understanding regime, volatility structure, and where edges tend to live.
Every generated idea runs through VARRD's complete validation pipeline autonomously — event study, multi-market, backtest, optimization. No shortcuts.
This isn't a chatbot brainstorming session. Your agent uses VARRD like a quant researcher with decades of pattern recognition — generating, testing, and validating ideas while you sleep. Wake up to new edges in your library, fully backed by data.
Whether you're doing the research yourself, supervising an AI agent, or letting it run fully autonomous — same guardrails, same rigor.
Chat with VARRD directly. Describe your ideas, see charts, approve tests, get trade setups. The classic research experience.
Point your AI agent (Claude, GPT, or any model) at VARRD. It does the research, you review what it found. Best of both worlds.
Fully autonomous. Your agent self-authenticates via crypto wallet, pays with USDC, and researches while you sleep. Wake up to new edges.
For prop shops, quant desks, family offices, and hedge funds where the privacy of your edges is paramount.
Need special accommodations or have questions? Reach out any time.
VARRD was built by derivatives traders and engineers who spent years working alongside one of the most successful futures trading firms of the past 40 years — dissecting the research process that turned raw market intuition into systematic, repeatable edges.
VARRD is that process, rebuilt from the ground up with AI — so that anyone, not just quants with PhDs and Bloomberg terminals, can do the same caliber of research.
Co-Founder
Derivatives trader and lifelong entrepreneur with deep market intuition shaped by his father, one of the top macro derivatives traders globally. Has been building with AI models since 2018, making him one of the most knowledgeable engineers on the real-world capabilities of modern AI. His university has him review their AI curriculum every year.
Co-Founder
Derivatives trader with an Economics degree with a focus in quantitative finance from Princeton and D1 All-American honors, bringing both analytical precision and incredible discipline to the team. Has invested countless hours refining the backtesting engine, ensuring its outputs meet the highest standards of statistical rigor and real-market reliability.
Founding Member
Options trader with a Princeton Economics degree and D1 All-American honors, bringing both market knowledge and competitive intensity to the team. Leads the company's business and partnership efforts, aligning VARRD's development with the needs of enterprise clients.
VARRD is a research and decision-support tool. It does not execute trades, manage portfolios, or provide investment advice.