The MissingInfo Pattern: How Modern Portfolio Systems Handle Incomplete Market Data

The Challenge: Incomplete Market Data in Portfolio Valuation

Your portfolio has 50 positions. 47 have prices. 3 don't.
What should your system show for total market value?

In real-world portfolio management, incomplete data is a daily reality. Market feeds have gaps, exotic instruments lack pricing, and FX rates for emerging currencies may not be available immediately.

The question becomes: how do you provide useful information to users while being transparent about what's incomplete?

Approach	System Behavior	User Experience
Block calculation	Report fails entirely	No visibility until data is complete
Exclude missing items	Calculate with available data only	Partial result, but gaps not visible
Track what's missing	Partial result + explicit gap list	Transparency and actionable next steps

The MissingInfo Approach Rather than hiding incomplete data or blocking calculations, the MissingInfo pattern makes missing information an explicit part of the result. This allows the UI to contextually expose data gaps to users, turning incomplete data into an operational workflow rather than a system limitation.

The Pattern: Results That Know What They Don't Know

The MissingInfo pattern wraps calculation results with context about what data was available and what was missing. Each result carries:

The computed value (when calculable with available data)
A list of missing instrument prices that would complete the calculation
A list of missing FX rates needed for currency conversions

This allows the system to provide partial results while making gaps explicit:

Standard Result

Value: 2,450,000

(Complete positions only)

MissingInfo Result

Value: 2,450,000
Missing Prices: SHELL @ 2024-03-15
Missing FX Rates: EUR/USD @ 2024-03-15

(Shows what's needed)

Two Categories of Missing Data

Missing Instrument Prices

Cause: Illiquid securities, delayed feeds, newly added instruments, exotic derivatives
What's captured: Date, Instrument identifier, Contract parameters (for derivatives)

Missing FX Rates

Cause: Exotic currency pairs, weekend/holiday gaps, emerging market currencies
What's captured: Date, Base currency, Counter currency

By separating these categories, operations teams can route issues to the right people - pricing teams for instruments, treasury for FX rates.

How Missing Information Propagates Through Calculations

The pattern's power comes from automatic propagation. When you combine two values, their missing data combines too.

graph TD P1["POSITION 1: Apple
Value: $500,000
Missing: None"] P2["POSITION 2: Shell
Value: Unknown
Missing: SHELL price @ Mar-15"] P3["POSITION 3: Nestle
Value: CHF 200,000
Missing: CHF/USD rate @ Mar-15"] PT["PORTFOLIO TOTAL
Partial Value: $500,000 + ???
Missing Price: SHELL @ Mar-15
Missing FX: CHF/USD @ Mar-15"] P1 --> PT P2 --> PT P3 --> PT style P1 fill:#d4edda,stroke:#28a745 style P2 fill:#fff3cd,stroke:#ffc107 style P3 fill:#fff3cd,stroke:#ffc107 style PT fill:#f8d7da,stroke:#dc3545

Key behaviors:

Missing information from any component bubbles up to the aggregate
Duplicates are automatically removed (same missing price only listed once)
Missing items are sorted by date for easy prioritization

The Valuation Chain: Where Missing Data Originates

Here's how data flows through a typical valuation:

graph TD EXT["EXTERNAL DATA SOURCES"] PF["Price Feeds"] FXF["FX Feeds"] PL["Price Lookup"] FXL["FX Rate Lookup"] PR["Price or MissingPrice"] FXR["Rate or MissingRate"] CALC["CALCULATION LAYER
• Market Value in Asset Currency
• Market Value in Reporting Currency
• Accrued Interest
• Unrealized Gains"] AGG["AGGREGATION LAYER
• Position Totals
• Portfolio Totals
• Client Totals"] EXT --> PF EXT --> FXF PF --> PL FXF --> FXL PL --> PR FXL --> FXR PR --> CALC FXR --> CALC CALC --> AGG style EXT fill:#e7f3ff,stroke:#0066cc style CALC fill:#fff3e0,stroke:#ff9800 style AGG fill:#f3e5f5,stroke:#9c27b0

At each calculation step:

If data is available → wrap the value
If data is missing → wrap the "missing" information instead
When combining → merge both values AND missing information

The User Experience: Contextual Exposure of Data Gaps

By including missing information as part of the calculation result, the UI can contextually expose data gaps exactly where they matter. The workflow becomes:

graph LR S1["STEP 1
Generate report
See partial total
with warning"] S2["STEP 2
Click warning
View missing data:
• SHELL @ Mar-15
• PE Fund III @ Mar-15
• EUR/USD @ Mar-15"] S3["STEP 3
Enter missing
values directly
Data saved"] S4["STEP 4
Refresh report
Complete
valuation"] S1 --> S2 S2 --> S3 S3 --> S4 style S1 fill:#fff3cd,stroke:#ffc107 style S2 fill:#cfe2ff,stroke:#0d6efd style S3 fill:#d1e7dd,stroke:#198754 style S4 fill:#d4edda,stroke:#28a745

The missing information travels with the calculation result, allowing the UI to show users exactly what's needed in context - not as an error, but as actionable next steps.

Deduplication: Clean, Actionable Lists

When a portfolio has 100 positions in Shell stock across 20 accounts, the missing price appears once, not 100 times.

graph TD RAW["RAW MISSING DATA
from 100 positions"] D1["SHELL @ Mar-15"] D2["SHELL @ Mar-15"] D3["SHELL @ Mar-15"] D4["... 97 more"] DEDUP["DEDUPLICATION
Unique by Date + Symbol"] RESULT["AFTER DEDUPLICATION
SHELL @ Mar-15"] RAW --> D1 RAW --> D2 RAW --> D3 RAW --> D4 D1 --> DEDUP D2 --> DEDUP D3 --> DEDUP D4 --> DEDUP DEDUP --> RESULT style RAW fill:#f8d7da,stroke:#dc3545 style DEDUP fill:#cfe2ff,stroke:#0d6efd style RESULT fill:#d4edda,stroke:#28a745

Deduplication rules:

Prices: Unique by (Date, Instrument Symbol)
FX Rates: Unique by (Date, Base Currency, Counter Currency)

This keeps the action list manageable, regardless of how many positions are affected.

Business Benefits

For Operations

No more hunting through reports to find data gaps
Missing data becomes a prioritized to-do list
Inline entry reduces context switching

For Compliance

Reports clearly indicate completeness
Audit trail shows what was missing and when it was fixed
No silent substitution of zeros that could mask issues

For Portfolio Managers

Partial valuations still provide directional insight
Clear visibility into data quality
Faster turnaround on complete reports

For Technology

Pattern is composable - works across any calculation
Type-safe - compiler enforces proper handling
Testable - missing scenarios are explicit, not edge cases

Requirements Checklist for Evaluating Systems

When evaluating portfolio management systems, consider these capabilities:

Does the system provide partial results when some data is unavailable?

Can users see which specific data points are missing from any calculation?

Does missing information propagate through aggregations automatically?

Are missing items deduplicated for clean action lists?

Can users enter missing data directly from reports?

Does the system track both missing prices AND missing FX rates separately?

Are missing items sorted/prioritized (e.g., by date)?

These features help systems handle the reality of incomplete data gracefully, providing transparency and enabling efficient operations workflows.

The Three Principles

Principle 1: Make Gaps Explicit

Include missing information as part of the result
Transparency enables informed decisions

Principle 2: Propagate Context

Missing information flows through calculations
Aggregates carry complete context from components

Principle 3: Enable Action

Contextual exposure of gaps in the UI
Users see what's needed, where it's needed

Conclusion

The MissingInfo pattern provides a structured approach to handling incomplete market data in portfolio systems.

By making missing information an explicit part of calculation results, systems can provide transparency while maintaining operational efficiency. The UI can contextually expose data gaps to users, turning incomplete data into clear, actionable next steps.

In wealth management, where data completeness directly impacts reporting accuracy and operational workflows, this pattern offers a practical solution to a common challenge.

What approaches have you seen for handling incomplete market data? We'd love to hear from others in the wealth management space.

Patterns

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