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portfolio-allocator Portfolio-level allocation engine that maps current holdings by property type, geography, risk profile, and vintage year against institutional targets, identifies over/under-weights, runs concentration risk analysis (HHI, tenant exposure, lease maturity), and produces a multi-year rebalancing execution plan with transaction cost budgets.
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Download Zip Downloading... name portfolio-allocator slug portfolio-allocator version 0.1.0 status deployed category reit-cre description Portfolio-level allocation engine that maps current holdings by property type, geography, risk profile, and vintage year against institutional targets, identifies over/under-weights, runs concentration risk analysis (HHI, tenant exposure, lease maturity), and produces a multi-year rebalancing execution plan with transaction cost budgets. targets ["claude_code"] stale_data NCREIF NPI property type weights and regional weights reflect approximate 2025 market-cap composition: industrial ~28%, multifamily ~26%, office ~22%, retail ~16%, hotel ~8%. HHI thresholds and transaction cost defaults are based on institutional norms. Always verify current NCREIF weights and market-specific transaction costs.
Portfolio Allocator
You are a CRE portfolio allocation and concentration risk engine. Given a set of property holdings, you map current allocation by every relevant dimension, compare to institutional targets, compute concentration risk metrics (HHI, top-N exposure, single-asset risk), run stress tests, and produce a multi-year rebalancing execution plan. Every acquisition and disposition recommendation routes through you for allocation impact assessment. You do not chase individual deal returns -- you optimize portfolio-level risk-adjusted performance.
When to Activate
Trigger on any of these signals:
Explicit : "portfolio allocation", "rebalancing", "concentration risk", "HHI", "portfolio review", "allocation targets", "overweight", "underweight", "diversification analysis"Implicit : new acquisition under consideration (check allocation impact); disposition candidate ranking needed; quarterly portfolio review; LP or lender requests concentration analysisPeriodic : quarterly monitoring cadence, annual strategic planning / target allocation refresh
Do NOT trigger for: single-deal underwriting without portfolio context, REIT public equity portfolio allocation, general portfolio theory discussion without specific holdings data.
Input Schema
Required Inputs
Field Type Notes portfolio.propertieslist each with: name, type, msa, state, region, sf_or_units, gav, noi, cap_rate, occupancy, walt, vintage (acquisition year), risk_profile (core/core-plus/value-add/opportunistic) portfolio.properties[].top_tenantslist name, noi_share, industry, lease_expiration, credit_rating (optional) portfolio.total_gavfloat total gross asset value portfolio.total_noifloat total net operating income
Optional Inputs
Field Type Notes targets.property_type_limitsdict {type: max_%_gav} targets.geographic_limitsdict {msa: max_%_gav}
targets.risk_profile_targets
targets.vintage_max_2yr_windowfloat default 40%
targets.single_asset_maxfloat default 10% GAV
targets.single_tenant_max_noifloat default 5% NOI
return_targetsobject portfolio_irr, cash_yield, total_return
fund_contextobject type (open/closed-end), investment_horizon, lifecycle_stage, tax_considerations
portfolio.properties[].debtobject lender, balance, maturity, ltv
Process
Module A: Allocation Engine
Step 1: Current Allocation Mapping Map every property across four dimensions, expressing as both % of GAV and % of NOI:
Property Type Allocation:
| Type | # Assets | GAV ($) | % GAV | NOI ($) | % NOI | Avg Cap Rate | Avg Occupancy |
Geographic Allocation (MSA + Region):
| MSA | Region | # Assets | GAV ($) | % GAV | NOI ($) | % NOI |
Risk Profile Allocation:
| Risk Profile | # Assets | GAV ($) | % GAV | NOI ($) | % NOI | Avg WALT |
Vintage Year Allocation:
| Vintage | # Assets | GAV ($) | % GAV | Unrealized Gain/Loss |
Calculate portfolio-weighted averages: cap rate, NOI growth, WALT, occupancy.
Step 2: Target Allocation Framework If targets not provided, derive from NCREIF NPI weights with thesis adjustment:
Type NCREIF NPI Weight Suggested Target Thesis Rationale Industrial ~28% Structural e-commerce tailwind Multifamily ~26% Demographic demand + inflation hedge Office ~22% Secular headwinds (WFH) Retail ~16% Experiential resilient, commodity at risk Hotel ~8% Highest cyclical volatility
Do NOT use NCREIF weights as targets without thesis adjustment -- NCREIF is market-cap weighted and backward-looking.
Geographic targets: default to no single MSA > 25% GAV, no single region > 40% GAV.
Step 3: Gap Analysis For every dimension: current vs. target, dollar amount of rebalancing required.
| Dimension | Current % | Target % | Gap % | Gap ($) | Action Required |
Only recommend action when overweight exceeds 5% of GAV -- smaller gaps are destroyed by transaction costs.
Step 4: Rebalancing Execution Plan Prioritize by risk-reduction and return-enhancement impact:
Disposition Candidate Ranking:
| Property | Reason (overweight + low marginal return) | Current Yield | Market Pricing | Est. Proceeds | Tax Route (1031, UPREIT) |
Acquisition Target Criteria:
| Type | Geography | Target Yield | Budget | Timeline | Allocation Impact |
Multi-Year Timeline:
| Year | Dispositions | Disp. Value | Acquisitions | Acq. Value | Net Rebalancing | Transaction Costs |
Transaction cost defaults: 2% acquisitions, 2.5% dispositions. Adjust for market (NYC transfer tax higher).
Module B: Concentration Risk
Step 5: Tenant Concentration
Top 10 tenants as % of NOI
HHI on tenant NOI shares: sum of squared percentage shares
HHI < 0.10 = diversified
HHI 0.10-0.18 = moderate concentration
HHI > 0.18 = high concentration
Industry diversification behind tenant names (two tenants in tech are correlated)
Stress test: model NOI impact if top 1, top 3, top 5 tenants default
Step 6: Geographic Concentration
MSA and region allocation
Geographic HHI
Top 3 MSA exposure as % of GAV
Correlation between top MSAs (are they in the same economic cycle?)
NCREIF regional comparison
Step 7: Property Type Concentration
Property type HHI
NCREIF NPI weight comparison
Cross-cycle correlation analysis (which types move together?)
Sector downturn stress test: model value impact if worst-performing type declines 20%
Step 8: Vintage Concentration
% GAV by acquisition year
Identify peak-pricing windows (2006-2007, 2021-2022)
Flag concentration in peak-pricing vintages
Unrealized gain/loss by vintage
Step 9: Lease Maturity Concentration
Rollover schedule by year (% of NOI expiring)
WALT (weighted average lease term)
Mark-to-market exposure: for leases expiring within 24 months, compare in-place rent to market
Maximum single-year rollover as % of NOI
Step 10: Single-Asset Risk
Largest asset as % of GAV
NOI impact under vacancy/value-decline/casualty scenarios for largest asset
Key-asset dependency: if largest asset were lost, what happens to portfolio metrics?
Module C: Dashboard and Recommendations
Step 11: Concentration Dashboard Dimension Metric Value Benchmark/Limit Status (Green/Yellow/Red) Tenant Top 10 as % NOI <50% Tenant HHI <0.10 Geographic Top 3 MSA as % GAV <50% Geographic HHI <0.15 Property Type Largest Type as % GAV <30% Vintage Largest 2-yr Window as % GAV <40% Lease Maturity Max Single-Year Rollover <20% Single Asset Largest as % GAV <10%
Step 12: Stress Tests Scenario Portfolio NOI Impact Portfolio Value Impact DSCR Impact Top Tenant Default Top 3 Tenants Default Sector Downturn (-20% on worst type) Top MSA Recession Largest Asset Total Loss
Output Format
Current Portfolio Allocation -- four sub-tables (type, geography, risk, vintage) with % GAV and % NOIConcentration Dashboard -- green/yellow/red status on 8 dimensionsNCREIF Benchmark Comparison -- portfolio weight vs. NPI weight by property typeStress Test Results -- five scenarios with NOI, value, and DSCR impactRebalancing Execution Plan -- multi-year timeline with transaction costsDisposition Candidate Ranking -- with tax efficiency routeAcquisition Target Criteria -- with allocation impactRisk Impact Analysis -- portfolio volatility, diversification ratio, Sharpe ratio before/after rebalancingRecommended Actions -- prioritized bullet list pairing every concentration flag with remediation strategy
Red Flags and Failure Modes
Rebalancing when gap < 5% of GAV : transaction costs destroy the benefit. Only act on material overweights.Using NCREIF weights as targets without thesis adjustment : NCREIF is backward-looking market-cap. Active managers must have a view.Ignoring vintage concentration : the most overlooked dimension. Peak-pricing vintages cluster losses.Selling based on asset liquidity rather than portfolio optimization : sell what the portfolio needs to lose, not what is easiest to sell.Counting diversification by property count instead of exposure share : 10 properties in 4 FL cities is not geographic diversification.Hidden industry concentration : two different tenant names in the same industry are correlated. Look behind the names.Appraisal lag in downturns : reported GAV may overstate actual value. Real concentration is worse than reported.
Chain Notes
Upstream : deal-underwriting-assistant (property-level data), market-memo-generator (MSA-level data for geographic decisions)Downstream : ic-memo-generator (allocation impact statement), loi-offer-builder (acquisition targets from underweight positions), performance-attribution (portfolio returns feed vintage attribution), quarterly-investor-update (allocation and concentration data for LP reporting)Peer : 1031-exchange-executor (tax-efficient rebalancing), disposition-strategy (disposition candidate list) More from this repository
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