AI trading research: event studies, backtesting, statistical validation on stocks, futures, crypto.
AI trading research: event studies, backtesting, statistical validation on stocks, futures, crypto.
VARRD — AI Trading Research & Backtesting · v1.0.3
augiemazza
VARRD
Turn any trading idea into a statistically validated edge — or find out it doesn't work for $0.25.
pip install varrd
Ask it anything
varrd research "Does buying SPY after a 3-day losing streak actually work?"
varrd research "When VIX spikes above 30, is there a bounce in ES?"
varrd research "Is there a seasonal pattern in wheat before harvest?"
varrd research "What happens to gold when the dollar drops 3 days straight?"
varrd research "Does Bitcoin rally after the halving?"
varrd research "When crude oil drops 5% in a week, what happens next?"
Every question gets real data, a chart with signals marked, a statistical test, and a definitive answer.
What you get back
Edge found
STRONG EDGE — Statistically significant vs both zero and market baseline.
Direction: LONG
Win Rate: 62%
Sharpe: 1.45
Signals: 247
Trade Setup:
Entry: $5,150.25
Stop Loss: $5,122.00
Take Profit: $5,192.50
Risk/Reward: 1:1.5
No edge
NO EDGE — Neither test passed. No tradeable signal found.
You found out for 25 cents instead of $25,000 in live losses.
Both are valuable results.
How it works
Your idea (plain English)
↓
Load real market data — stocks, futures, crypto
↓
Chart the pattern — see actual signals on price history
↓
You approve — sanity check before spending statistical power
↓
Statistical test — event study with proper controls
↓
Verdict: STRONG EDGE / MARGINAL / NO EDGE
↓
Trade setup — exact entry, stop-loss, take-profit in dollars
A typical session is 3–5 turns and costs ~$0.25.
Quick start — Python
from varrd import VARRD
v = VARRD() # auto-creates free account, $2 in credits
# Research a trading idea
r = v.research("When RSI drops below 25 on ES, is there a bounce?")
r = v.research("test it", session_id=r.session_id)
print(r.context.edge_verdict) # "STRONG EDGE" / "NO EDGE"
# Get exact trade levels
r = v.research("show me the trade setup", session_id=r.session_id)
# What's firing right now across all your strategies?
signals = v.scan(only_firing=True)
for s in signals.results:
print(f"{s.name}: {s.direction} {s.market} @ ${s.entry_price}")
# Let VARRD discover edges autonomously
result = v.discover("mean reversion on futures")
print(result.edge_verdict, result.market, result.win_rate)
Quick start — CLI
# Full research workflow (auto-follows chart → test → trade setup)
varrd research "When wheat drops 3 days in a row, is there a snap-back?"
# What's firing right now?
varrd scan --only-firing
# Search saved strategies
varrd search "momentum on grains"
# Let VARRD discover edges on its own
varrd discover "mean reversion on futures"
Use with AI agents
Claude Desktop / Claude Code / Cursor
Add to your MCP config — no API key needed:
{
"mcpServers": {
"varrd": {
"transport": {
"type": "streamable-http",
"url": "https://app.varrd.com/mcp"
}
}
}
}
Then just ask: "Is there a pattern when gold spikes after a Fed rate decision?"
CrewAI
from crewai import Agent, Task, Crew
researcher = Agent(
role="Trading Researcher",
goal="Find statistically validated trading edges",
backstory="You are a quantitative researcher who tests trading ideas rigorously.",
mcps=[{"type": "streamable-http", "url": "https://app.varrd.com/mcp"}]
)
task = Task(
description="Research whether RSI oversold conditions on ES lead to a bounce within 5 days.",
agent=researcher,
expected_output="Edge verdict with trade setup if edge is found."
)
crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()
LangChain / LangGraph
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
model = ChatAnthropic(model="claude-sonnet-4-20250514")
async with MultiServerMCPClient({
"varrd": {"url": "https://app.varrd.com/mcp", "transport": "streamable_http"}
}) as client:
agent = create_react_agent(model, client.get_tools())
result = await agent.ainvoke({"messages": [
{"role": "user", "content": "Does gold rally when the dollar drops 3 days in a row?"}
]})
Raw MCP (any client)
# Any MCP-compatible client can connect to:
https://app.varrd.com/mcp
# Transport: Streamable HTTP | No auth required | $2 free credits
8 statistical guardrails (infrastructure-enforced)
Every test runs through these automatically. You can't skip them.
| Guardrail | What It Prevents |
|---|---|
| K-Tracking | Tests 50 variations of the same idea? Significance bar goes up automatically. |
| Bonferroni Correction | Multiple comparison penalty. No p-hacking. |
| OOS Lock | Out-of-sample is one shot. Can't re-run after seeing results. |
| Lookahead Detection | Catches formulas that accidentally use future data. |
| Tools Calculate, AI Interprets | Every number comes from real data. AI never fabricates stats. |
| Chart → Approve → Test | You see and approve the pattern before spending statistical power. |
| Fingerprint Dedup | Can't retest the same formula/market/horizon twice. |
| No Post-OOS Optimization | Parameters lock after out-of-sample validates. |
Data coverage
| Asset Class | Markets | Timeframes |
|---|---|---|
| Futures (CME) | ES, NQ, CL, GC, SI, ZW, ZC, ZS, ZB, TY, HG, NG + 20 more | 1h and above |
| Stocks / ETFs | Any US equity | Daily |
| Crypto (Binance) | BTC, ETH, SOL + more | 10min and above |
15,000+ instruments total.
MCP tools
| Tool | Cost | What It Does |
|---|---|---|
research |
~$0.25 | Multi-turn quant research. Orchestrates 15 internal tools. |
autonomous_research |
~$0.25 | AI discovers edges for you. Give it a topic, get validated results. |
scan |
Free | Scan strategies against live data. Fresh entry/stop/target prices. |
search |
Free | Find strategies by keyword or natural language. |
get_hypothesis |
Free | Full details on any strategy. |
check_balance |
Free | View credits and available packs. |
buy_credits |
Free | Buy credits with USDC on Base or Stripe. |
reset_session |
Free | Kill a broken session and start fresh. |
Pricing
- $2 free on signup — enough for 6–8 research sessions
- Research: ~$0.20–0.30 per idea tested
- Discovery (autonomous): ~$0.20–0.30
- ELROND council (8 expert investigators): ~$0.40–0.60
- Multi-market (3+ markets): ~$1
- Scan, search, balance: Always free
- Credit packs: $5 / $20 / $50 via Stripe
- Credits never expire
Examples
See examples/ for runnable scripts:
quick_start.py— 5 lines to scan all strategiesresearch_idea.py— Full multi-turn research workflowmulti_idea_loop.py— Test many ideas in a loopscan_portfolio.py— Portfolio scan with trade levelsmcp_config.json— MCP config for Claude Desktop / Cursor
For AI agent builders
See AGENTS.md for the complete integration guide — tool reference, response formats, authentication, and workflow patterns.
Links
- Web app: app.varrd.com
- Website: varrd.com
- MCP endpoint:
https://app.varrd.com/mcp - PyPI: pypi.org/project/varrd