While IRR projections are standard, they often ignore:
• Timing-based liquidity drag
• Sponsor execution bandwidth
• Macro volatility in emerging markets

At Bay Street Hospitality, we’ve replaced static underwriting models with a dynamic, risk-adjusted return engine—one that integrates real-time inputs across capital markets, brand operating risk, and public/private benchmarks.
This whitepaper outlines our framework for calculating realistic, defendable return projections using synthetic volatility, scenario-adjusted AHA (Adjusted Hospitality Alpha), and dispersion-informed Bay Score metrics.

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Framework Overview: Dynamic Return Modeling Components

Our risk-adjusted return engine incorporates 6 core modules:

• AHA (Adjusted Hospitality Alpha): Measures IRR net of benchmark and illiquidity premium

• BAS (Bay Adjusted Sharpe): Return per unit of volatility + exit dispersion

• BMRI (Bay Macro Risk Index): Downward IRR adjustment in fragile markets

• LSD (Liquidity Stress Delta): Exit risk penalty (modeled as % IRR drag)

• DISP Score: Market dispersion multiplier on volatility

• Synthetic Volatility Engine: Volatility estimate based on public REIT proxies

Together, these metrics refine how Bay Street prices risk, structures deals, and allocates capital.

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Return Recalibration in Action

Let’s assume the following underwriting baseline:
• Projected IRR: 18%
• Target geography: Mexico
• Deal type: Brand conversion
• Sponsor: Mid-cap, low co-investment

Using our engine:

• BMRI (Macro Risk Score): 67 → −1.5% IRR

• LSD (Exit Delay Stress): 3.2% → −1.2% IRR

• Sponsor Discount (Low Coinvest): N/A → −0.8% IRR

• Volatility Estimate (Dispersion-adjusted): 22% → Used for BAS calculation

Final Adjusted IRR = 14.5%
AHA = 6.2% (vs BSHI of 8.3%)
BAS = 0.66 (acceptable threshold >0.55)
Bay Score = 83 (Q2, Institutional Grade)

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Scenario Modeling: How Volatility and BMRI Impact Decisions

Sample scenarios comparing investment decisions:

• Portugal brand-led JV | IRR: 16% | BMRI: 41 | LSD: 2.5 | BAS: 0.78 | Bay Score: 92 → Prioritize

• India operator equity stake | IRR: 18% | BMRI: 58 | LSD: 3.6 | BAS: 0.62 | Bay Score: 76 → Accept with pref equity

• Philippines leasehold | IRR: 14% | BMRI: 73 | LSD: 5.1 | BAS: 0.47 | Bay Score: 61 → Restructure or pass

The engine flags low BAS and IRR drag when dispersion, volatility, or macro instability compounds.

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Technical Design: How the Engine Works

AHA Formula:
AHA = IRR_deal − Benchmark_BSHI − Illiquidity Premium

Where the illiquidity premium is modeled as a function of LSD, FX risk, and capital lockup duration.

BAS Formula:
BAS = AHA / σ_synthetic

Where σ = Synthetic volatility estimate based on public REIT comps, adjusted by regional dispersion and leverage.

BMRI reduces IRR based on macro fragility using a four-factor weighted model:

• Sovereign spread vs U.S. Treasuries

• FX volatility (90-day trailing)

• Tourism deviation vs 5-year average

• Government risk (OECD/WEF composite)

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Applications to Portfolio Design

• High BMRI + low BAS → Position as opportunistic; increase pref equity, reduce weight

• Low BMRI + high AHA → Prioritize for growth sleeve or early liquidity harvesting

• Low Sponsor Co-invest + high LSD → Reduce expected IRR via conservative exit assumptions

By simulating thousands of combinations, Bay Street optimizes both expected return and downside resilience.

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LP Implications: Why It Matters

Institutional allocators benefit directly:

• Transparent return expectation: No more inflated IRRs untied to market reality

• Defensible downside: Understand how exit drag and market stress impact outcomes

• Scenario-based structuring: Negotiate waterfall terms tied to score outputs

Whether allocating $10M to India or $100M across 5 markets, LPs can trust Bay Street’s numbers reflect probabilistic outcomes, not static base cases.

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Conclusion: Risk Isn’t a Black Box

Hospitality investing carries nuanced risks—brand cyclicality, policy shocks, operating leverage.

Rather than oversimplify, Bay Street models these risks directly into return expectations. With a dynamic engine grounded in volatility, dispersion, sponsor quality, and macro risk, we offer investors not just a projection—but a precision-calibrated return expectation.

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