Analytical features built for disciplined decision-making
Rivenhalls combines real-time data analysis, predictive modelling, and drawdown governance in one decision-support environment. Each feature is designed to clarify risk, structure review, and support consistent process.
Rivenhalls provides analytical software for decision support. It does not provide regulated financial advice or execution services.
Connected analysis, from data to decision record
Rivenhalls brings market data, analytical models, and risk rules together so review is structured rather than fragmented. Users can examine current conditions, test assumptions, and document rationale in a consistent workflow.
Features are modular: use real-time monitoring for situational awareness, modelling for forward-looking assessment, and governance tools to keep exposure within defined mandates.
Analytical workspace: monitor, model, and review within defined risk parameters.
Detailed feature descriptions and benefits
Six interconnected modules cover the full analytical cycle. Each includes transparent inputs, configurable rules, and exportable records for internal review.
Real-Time Data Analysis
Consolidate streaming market data into clear views of trend, volatility, and regime change. Filters and timeframes are adjustable to match your analytical focus.
- Configurable dashboards for price, volume, and volatility
- Alert logic based on your own thresholds
- Consistent data definitions across views
Predictive Modelling
Apply probabilistic models to assess potential paths and sensitivities. Outputs show ranges and key drivers, not single-point forecasts.
- Scenario conditioning by user-defined assumptions
- Driver attribution for model outputs
- Versioned assumptions for auditability
Drawdown Governance
Define drawdown limits, exposure rules, and review triggers before decisions are made. The system flags breaches for structured reassessment.
- User-set limits by strategy or portfolio view
- Automatic flagging when thresholds are approached
- Review log to document responses
Scenario & Stress Analysis
Examine how positions or hypotheses behave under alternative conditions, including volatility shifts and adverse moves.
- Historical and hypothetical scenario templates
- Side-by-side comparison of outcomes
- Clear display of assumptions and limitations
Data Integration
Bring together market feeds and internal datasets in a structured format for analysis, with field mapping and validation checks.
- Structured import for CSV and API sources
- Validation prompts for missing or inconsistent fields
- Consistent taxonomy for downstream analysis
Reporting & Decision Records
Export summaries that link insight to evidence: inputs used, rules applied, and rationale recorded at the time of review.
- Shareable summaries for internal stakeholders
- Traceable link between data, model, and note
- Printable and archivable formats
Fragmented review
Insights spread across tools, thresholds implicit, and rationale difficult to reconstruct after the fact.
Connected review
Data, models, limits, and notes reside in one workflow, making review repeatable and easier to oversee.
A consistent four-step workflow
Features are ordered to support process discipline: establish context, assess outlook, check against risk rules, then record the decision.
Connect inputs
Select data sources and define symbols, timeframes, and fields for analysis.
Analyse conditions
Review real-time structure and run models to explore ranges and drivers.
Check governance
Compare findings against drawdown limits and scenario tolerances.
Record & export
Document interpretation, save assumptions, and share a summary for oversight.
Applied to different analytical roles
The same feature set adapts to different responsibilities. Select a profile to see relevant applications.
Structured intraday and swing review
Use monitoring and governance together to keep short-term assessment aligned with pre-defined risk boundaries.
- Monitor volatility shifts without switching tools
- Test adverse moves before adjusting exposure
- Log rationale alongside limit status
Evidence-based research workflow
Combine modelling, scenario testing, and documentation to produce analysis that others can understand and challenge.
- Attribute model outputs to key drivers
- Compare base, upside, and stress assumptions
- Export methods and limitations with results
Oversight and consistency across teams
Standardise how analysis is prepared and reviewed, supporting internal control and knowledge sharing.
- Common definitions for metrics and limits
- Repeatable templates for review and reporting
- Archivable records for internal audit processes
CSV / API mapping with validation checks before analysis begins.Common questions
Practical points on configuration, interpretation, and limits. For methodology background, see the approach and governance pages.
Do I need technical skills to configure features?
No specialist development is required for standard use. Dashboards, thresholds, scenarios, and reports are configured through guided settings. Data mapping options are available for teams managing their own feeds.
How should predictive outputs be interpreted?
Outputs should be treated as conditional assessments based on the data and assumptions selected. Review the displayed drivers and ranges, test alternative assumptions, and compare results against your own risk mandate before any decision.
Can limits and alerts replace risk management?
No. Governance features support discipline by flagging threshold events and structuring review. They do not manage risk on your behalf. Users remain responsible for setting appropriate limits and for all decisions.
What can be exported for internal review?
Summaries can include charts, model assumptions, limit status, scenario results, and user notes, providing a traceable record of what was reviewed and when.
Review the features in context
Request access to discuss how the modules apply to your analytical process and risk framework. We will outline configuration options and documentation practices.