Signals
Probabilities with context
Risk
Regime and drawdown
Exports
CSV and API options
Educational use only. Always validate with independent research and your policies.
Signal Engine
The signal engine evaluates each pair across multiple timeframes using a mix of pattern recognition, volatility features, and macro sensitivity proxies. Outputs are probabilities and bias labels that are easy to read in a meeting or a classroom. Every signal includes a description of the drivers that contributed most, a confidence band, and data freshness. This helps users debate the logic instead of reacting to a score in isolation. You can review historical snapshots to understand how views evolved when volatility changed, which is helpful for post mortems and process coaching. We focus on clarity and documentation so teams can apply their own judgment and house rules without guessing how the model works.
Signals do not instruct trades. They highlight tendencies observed in the data and the conditions that might weaken the view. This format supports independent decision making and reduces the chance of overconfidence. The engine is tuned to avoid frequent whipsaws by using regime filters and sample-size gates, which you can inspect in the platform. If a factor becomes less predictive, the interface will flag reduced influence so you can adjust weight in your notes.
Risk and Regime Analytics
Risk modules estimate potential drawdown ranges, regime shifts, and clustering behavior. Instead of blanket warnings, the interface shows which inputs are raising the flag and how long similar conditions persisted in the sample. Users can compare regime labels across timeframes to decide whether a short-term move aligns with the broader context or is likely to fade. Tail scenarios are presented as ranges with historical analogs so teams can plan responses rather than react under pressure. Reports include concise definitions and links to method notes so everyone shares the same terms.
Risk views are most helpful when combined with internal exposure rules. COR Analytics supports this by letting you export metrics in a standard format. You can add thresholds in your spreadsheet or BI tool and attach internal commentary. The goal is to make oversight repeatable without forcing a specific framework. We avoid prescriptive alerts and focus on transparency so you can calibrate to your tolerance and governance policies.
Coverage and Refresh
Coverage includes major and widely followed cross pairs. Data pipelines include validations to reduce gaps and label questionable prints for review. Refresh windows are scheduled to align with market hours and typical reporting cycles. On the dashboard, each tile shows last refresh time and sample depth so you can assess whether a view is stale. Historical snapshots help you compare model output before and after releases or volatility spikes. This reduces hindsight bias and improves the quality of internal debate.
Your workflow determines how often you pull data. Some teams refresh once per day for a structured morning review. Others use intraday windows during busy periods and revert to a slower cadence when markets are quiet. The platform avoids forced notifications, which keeps attention on planned reviews. We do not execute orders or connect to brokerage accounts. The output is designed to support discussion, note taking, and consistent documentation.
Transparency and Controls
Every view in COR Analytics includes a trail you can audit. Inputs are listed, feature importance is summarized, and confidence intervals are visible. You can open a panel to see what would reduce conviction and which conditions previously led to false positives. This is useful during team reviews because it encourages questions about evidence, not personalities. Users can add notes next to a snapshot, tag a watchlist item, and export the full context to a shared folder or spreadsheet. That consistency helps teams build better habits and makes it easier to explain why a view changed.
Permissions are simple. Viewers can read dashboards and exports. Editors can create watchlists and notes. Admins can manage integrations and retention settings. We keep roles minimal to reduce friction while still protecting sensitive commentary. There are no dark patterns or surprise pop ups. What you see is what our crawler sees, and content is the same for all users. This approach supports compliance reviews and keeps expectations aligned.
Security and Privacy
Security focuses on practical controls that support research work without adding unnecessary complexity. Access is role based and session handling follows industry recommendations. We collect only what is needed to operate the service, such as account details and usage telemetry that helps improve performance. Where analytics are enabled, they are documented in our privacy materials and can be controlled through the cookie banner. We do not sell personal data and we honor unsubscribe and data deletion requests.
If your policies require specific handling of exports, you can keep reports in your own storage and disable optional features. We publish retention windows for form submissions, analytics, and account data. Users can request access or correction through the contact details in the footer. Review our policy for lawful bases, processor categories, and transfer safeguards. These controls support compliance reviews and give teams confidence when sharing insights within their organization.
Exports and Integrations
Reports can be exported as CSV for spreadsheets or pulled via API for automation. The formats are documented and include version tags, which makes it easier to update your workflows safely. Watchlists, notes, and regime flags are available to help you mirror the interface in your internal tools. Many teams combine CSV exports for quick checks with an automated API pull that updates a dashboard before a weekly meeting. This hybrid approach keeps your stack flexible and avoids lock-in.
If a connector is not listed, you can still import the standard files. We publish examples so your team can get started quickly without custom support. Scheduling lets you prepare packets before market open or align updates with your calendar. The goal is a simple handoff that respects your governance and record-keeping rules. Visit the integrations page for details and sample code.
Getting Started
You can explore COR Analytics without creating an account by visiting the demo. The demo includes a rotating sample of pairs, recent snapshots, and a tour of the key panels. When you are ready, choose a plan that matches your review cadence and collaboration needs. All plans share the same core models and transparency features, and you can change tiers at any time. If your organization requires a review of privacy, security, or export handling, our materials are available in the policy pages and can be requested by email.
Educational and research support only. Past conditions do not guarantee similar outcomes in the future.
