Dashboards & Asset Exploration
Relevant source files
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The Dashboards & Asset Exploration module provides interactive interfaces for analyzing financial networks. It includes high-level network metrics, filterable asset lists, and detailed relationship explanations. This module translates raw graph data into actionable insights through visual cards, data tables, and interactive panels.
Sources: ARCHITECTURE.md:14-25, frontend/README.md:65-71
Metrics Dashboard
The Metrics Dashboard presents a summary of the asset relationship network. It uses visual cards to display key performance indicators and network health statistics. The dashboard updates dynamically when the underlying graph data changes.
Sources: frontend/app/components/MetricsDashboard.tsx:7-14, frontend/tests/components/MetricsDashboard.test.tsx:132-140
Key Performance Indicators
The dashboard tracks the following network metrics:
- Total Assets: The count of unique nodes in the network.
- Total Relationships: The count of edges connecting assets.
- Network Density: The ratio of actual relationships to possible relationships, expressed as a percentage.
- Degree Statistics: Includes the average and maximum number of connections per asset.
Sources: frontend/app/components/MetricsDashboard.tsx:28-60, frontend/tests/components/MetricsDashboard.test.tsx:20-25
The diagram shows how graph data flows into the dashboard to populate specific metric cards.
Asset Exploration and Filtering
The Asset Explorer provides a tabular interface for searching and inspecting individual financial instruments. It allows users to browse the full inventory of assets and apply filters based on metadata.
Sources: frontend/app/components/AssetList.tsx:1-10, frontend/README.md:67
Filtering Mechanisms
Users can refine the asset list using the following controls:
- Asset Class Filter: Filters assets by type (e.g., Equity, Bond, Commodity).
- Sector Filter: Filters assets based on industrial or economic sectors.
- Combined Search: Apply multiple filters simultaneously to isolate specific asset groups.
Sources: frontend/app/components/AssetList.tsx:15-35, frontend/tests/components/MetricsDashboard.test.tsx:112-120
Data Table Structure
| Field | Type | Description |
|---|---|---|
| ID / Symbol | String | Unique identifier or market ticker for the asset. |
| Name | String | Full descriptive name of the financial instrument. |
| Price | Decimal | Current market price or valuation. |
| Market Cap | Decimal | Total valuation for equities or relevant size metric. |
Sources: frontend/app/components/AssetList.tsx:40-60, frontend/tests/components/MetricsDashboard.test.tsx:81-90
Relationship Explanation
The Relationship Explanation Panel provides context for why two assets are connected. It identifies the nature of the link and the numerical strength of that connection.
Sources: frontend/app/components/RelationshipExplanationPanel.tsx:5-15, ARCHITECTURE.md:143-150
Connection Types
The system detects several relationship types between assets:
- Same Sector: Assets operating within the same industry category.
- Corporate Link: Direct relationships such as corporate bonds linked to an issuer's equity.
- Commodity Exposure: Sensitivity of an equity or bond to commodity price movements.
- Currency Risk: Exposure to foreign exchange fluctuations.
Sources: ARCHITECTURE.md:144-149, frontend/app/components/RelationshipExplanationPanel.tsx:20-30
The flowchart illustrates the logic used to categorize and display asset relationships in the UI.
Data Flow Architecture
The exploration components interact with the FastAPI backend to retrieve processed graph data. The frontend components use Axios to perform HTTP requests and render the returned JSON payloads.
Sources: ARCHITECTURE.md:55-75, frontend/README.md:74-78
Integration Sequence
This sequence shows the interaction between the dashboard and the backend services to retrieve metrics.
Sources: ARCHITECTURE.md:60-70, frontend/tests/components/MetricsDashboard.test.tsx:133-138
Conclusion
The Dashboards & Asset Exploration system provides the primary interface for users to interpret financial asset networks. By combining high-level metrics with granular asset tables and relationship explanations, the module enables comprehensive analysis of market interdependencies and network structures.