One stock can't tell edge from luck.
At 55% accuracy, one name's noise swamps the signal. There isn't enough evidence in a single stock to know whether you have an edge at all.
Analysis is not enough.
Single-security signal platforms make it easy to evaluate and backtest ideas in isolation. The harder research problem is deciding whether noisy, regime-dependent signals still hold together in a broader portfolio context.
StrategyNet is software for systematic research and portfolio analysis. It ingests real-time data across US exchanges, futures, options, FX, crypto, indices, prediction markets, and financial statements, then helps users organize signal evidence into factors, compare candidate scenarios, and monitor exposures. Outputs are analytical inputs for review, not recommendations or instructions to trade.
Where research stacks break down.
Single-symbol tools make one idea easy to test. But signals don't work in isolation — portfolios do, and that is where correlation, crowding, and regime decide the outcome.
A real edge only emerges across many names.
A faint edge separates from noise across hundreds of uncorrelated positions, never on a single trade. Diversification is what turns 55% into a return.
Backtests reward data mining.
Search history for the strategy that fit best and you find noise dressed as edge — what wins a backtest rarely survives live.
One-symbol backtests miss the portfolio.
Correlation, crowding, and regime only appear once positions interact. A one-name backtest never sees them, so its results rarely hold up in a real book.
Regimes shift faster than you can recheck by hand.
Rechecking factor drift by hand after every macro surprise doesn't scale, and trading on stale conviction is costly.
Getting from idea to portfolio is mostly glue work.
Most teams stitch evaluation, optimization, and execution together with scripts and one-off spreadsheets. The result is slow, brittle, and hard to audit.
From idea to optimized, executable portfolio.
Every studio below maps to one stage of the same pipeline, so a raw idea turns into a reviewed, risk-adjusted allocation with an audit trail behind it.
- Compose ideas into factors with AI-assisted tooling, then evaluate whether they carry real information.
- Combine surviving factors into optimized baskets and stage them for review before anything reaches an execution API.
Workflow
01
Studio + Signal Designer
Create unique alpha from inputs such as earnings, news, prediction markets, and market data.
02
Signal Studio
Evaluate, compare, and rank signals that express an investment idea. Compare information content ratios, hit rates, and the spread between positions expected to benefit from the idea and those expected to lag if it plays out.
03
Strategy Studio
Assemble multiple ideas in one framework, then optimize baskets that turn idea factors into a single risk-adjusted portfolio plan.
04
Execution Blotter
Stage, execute, and monitor multiple strategies through an execution API. Alpaca is currently supported.
Step 01 — Idea to factor
Compose new factors from signal features with AI assistance.
AI Workbench helps transform source features, stacked factors, and optimizer output into reusable factor graphs for systematic research.
- Create composite factors from signal features and stacked factors.
- Optimize input weights with machine learning and compose graphs through the UI or Chat/API.
Live monitoring
Realtime Factors
Track live factor ranks, symbol projections, and intraday factor movement before sending a candidate signal into deeper evaluation.
- Monitor live factor ranks across symbols as market inputs update.
- Compare symbol projections and intraday factor trends before deeper signal evaluation.
Step 02 — Signal to factor evaluation
Evaluate whether a signal has usable information before it becomes a factor.
Signal Studio is the research surface for comparing candidate factors, reviewing evaluation runs, and checking whether an idea has enough statistical structure to justify portfolio construction.
- Rank signal runs by hit rate, information content, spread, and coverage.
- Filter factor families and inspect stability before portfolio construction.
Step 03 — Factor to portfolio
Compare optimizer scenarios before a portfolio moves toward execution.
Strategy Studio brings scenario generation, optimizer configuration, daily performance inspection, and factor attribution into one review surface.
- Compare optimizer scenarios, performance, drawdown, and rolling information ratios.
- Inspect factor contribution to isolate what is driving the strategy.
Plans
Start with Pro, move to Pro Plus as your workflow goes live and scheduled, or talk to us about a Team or Desk deployment.
Pro
$200/month
Core research, factor construction, and portfolio testing.
- Integrates US Equities, ETF, Futures, Options, FX, Crypto, Prediction Markets as signal inputs
- Core suite of factors, AI Designer for custom factor creation, Signal Studio, Strategy Studio, Execution blotter.
- Daily factor tracking: provides as of T-1 factor values and performance metrics.
- Factor Cards and portfolio optimizer.
- Hedge universe management with backtest reports.
- Scenario analytics and alerting.
- Daily reports and limited analytics export.
Pro Plus
$400/month
Scheduled research, optimization, and integration workflows.
- Extended suite of factors, AI Designer for custom factor creation, Signal Studio, Strategy Studio, Execution blotter.
- Core suite of factors, AI Designer for custom factor creation, Signal Studio, Intraday Signal Studio, Strategy Studio, Intraday Strategy Studio, Execution blotter.
- Live factor tracking: monitor macro and market data, news, and prediction markets for factor drift and signal decay.
- Intraday and Daily strategies testing and monitoring.
- Scheduled optimizer and hedge workflows.
- Scheduled reports, webhooks, and API access for derived analytics.
- Expanded factor library and compute allocation.
Team / Desk
Talk to us
Institutional workflow layer.
- Multi-seat workflow, shared factor libraries, and shared hedge universes.
- Audit log and approval workflow.
- Data entitlement mapping and vendor or exchange-specific controls.
- Custom data integration and custom reporting.
- Permissioned BYOD data.
Built for professional systematic research workflows.
strategynet.xyz is a research system from a team of experienced quantitative engineers. It is designed to replicate professional workflows: extract signals, distill them into portable alpha or factors, use those factors to drive optimization, and connect the results to systematic analysis and portfolio monitoring.
One factor model, every asset class
Equities, ETFs, futures, options, FX, crypto, indices, and prediction markets feed the same factor and optimization framework instead of separate tools.
AI-assisted, human-reviewed
AI Workbench helps compose and weight factor graphs. You still review every scenario before it reaches an execution API.
Execution-linked, not just theoretical
Strategies that clear evaluation can be staged straight to a connected execution API, closing the loop between research and the blotter.
Security built in from Pro up
Authenticator-app two-factor authentication, scoped API keys, and session-based access controls ship with every paid tier.
Frequently asked questions
What teams evaluating StrategyNet ask us most often.
Is this investment advice or a recommendation to trade?
No. StrategyNet is research and portfolio-analysis software. It organizes signal evidence into factors and produces candidate scenarios for your own review. Outputs are analytical, not personalized investment advice, and you are responsible for your own investment decisions.
What data does it cover?
Real-time and historical data across US equities, ETFs, futures, options, FX, crypto, major indices, prediction markets, and financial statements, feeding one shared factor model.
Do I need to write code to use it?
No. Every studio is point-and-click. Teams that want programmatic control can also compose factors and automate workflows through the API and Chat interface.
How is my account and data protected?
Authenticator-app two-factor authentication, scoped API keys, and session-based access controls are available from the Pro tier up.
Which plan is right for my team?
Pro covers core research and daily factor tracking. Pro Plus adds live tracking, intraday strategies, and scheduled automation. Team/Desk adds multi-seat workflows, audit logs, and custom data integration — talk to us to scope it.
Does StrategyNet place trades for me?
No. StrategyNet can stage candidate strategies to a connected execution API such as Alpaca, but you review and control what is sent. StrategyNet does not take custody of assets or manage your account on a discretionary basis.
Turn your next idea into a tested, optimized portfolio.
Start on Pro today, or talk to us about a Team or Desk deployment scoped to your data and workflow.
StrategyNet can generate candidate trade scenarios based on selected factors, constraints, and portfolio data. These scenarios are model outputs for analysis only. They are not recommendations, investment advice, or instructions to trade. You are responsible for independently reviewing all outputs before taking any action.