Traditional cap-weighted or vintage-year methods miss the dynamic nature of hospitality. Bay Street Hospitality's platform optimizes across a globally diversified universe of REITs, developers, operators, and tech platforms—balancing alpha generation with liquidity management and macro risk sensitivity.

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The Streamlit-powered optimizer maximizes a composite utility function blending Bay Score, AHA, and BAS, subject to real-world fund constraints such as position size, regional caps, liquidity stress limits (LSD), and minimum ESG thresholds.

Key Data Inputs

- Projected IRR
- Adjusted Hospitality Alpha (AHA)
- Bay Adjusted Sharpe (BAS)
- Bay Score
- Volatility Estimate
- Region & Asset Classification

Constraints

- Max 10% per asset
- Max 30% per region
- Minimum Bay Score 70+
- Liquidity stress (LSD) thresholds

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• IC Memo Optimization: Tests pipeline impact on current allocations.
• Public Equity Construction: Optimized REIT/operator baskets.
• Private Deal Screening: Simulates risk contribution of private transactions.
• Macro Rebalancing: Adjusts weights dynamically during market shifts.
• Stress Testing: Runs drawdown and liquidity crisis simulations.

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Bay Street’s optimizer enables:
- Systematic alpha capture.
- Transparent allocation justifications.
- Liquidity-aware capital pacing.
- Dynamic public-private integration.
- Institutional-grade downside preparation.

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• Every IRR is liquidity and volatility adjusted.
• Every asset, public or private, is evaluated by the same scoring architecture.
• Portfolio construction, not selection, drives long-term alpha.

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Appendix: Metrics & Benchmarks

Bay Score: Weighted composite of IRR, AHA, BAS, ESG, co-investment strength, liquidity stress.

AHA = Return − Benchmark − Illiquidity Premium

BAS = AHA ÷ Volatility

Utility Function: Maximize Weighted Sum of (Bay Score + AHA - Liquidity Drag)

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The Bay Street Hospitality Index (BSHI) integrates STR, CoStar, NCREIF, FTSE Nareit, MSCI, and S&P data for private and public benchmarking. Dynamic illiquidity premiums (1–7.5%) modeled from liquidity stress factors ensure realistic return assumptions.

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Bay Street uses CoStar Method Tags for inferred data points, Forecast Confidence Scores for grading forecast robustness, and STR-conformant RevPAR modeling protocols.

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Copyright Notice and Legal Disclaimer

Materials by Bay Street Hospitality are for informational purposes only. Past performance is not indicative of future results. Reproduction or distribution without permission is prohibited. © 2025 Bay Street Hospitality Fund I GP LLC.

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