Investment Methodology

Last Updated: August 2026

Commitment to Clients

We build portfolios we’re comfortable holding ourselves. Every investment decision we make reflects the same care and discipline we would apply to our own capital. Our clients entrust us not only with the stewardship of their assets, but often with their aspirations for generational wealth, social impact, and financial resilience. We honor that trust by integrating rigorous investment practices with a broader mission: to pursue strong risk-adjusted returns while contributing meaningfully to a more inclusive and durable economic system.

Investment Methodology

SPG’s investment methodology is grounded in modern portfolio theory (MPT), passive implementation, and practical behavioral and tax considerations. Our evidence-based, top-down approach integrates long-term historical data, capital market assumptions, and structural constraints to construct portfolios that align with client goals while reinforcing our broader mission.

Evidence-Based Investing

Our allocation framework draws from decades of empirical research and is designed to optimize long-term, risk-adjusted returns.

Key elements include:

• Modern Portfolio Theory (MPT): We diversify across equities, fixed income, alternatives, and cash, pursuing the strongest available balance of return and risk. Because the estimated efficient frontier (the set of portfolios offering the best available return at each level of risk) shifts with every change in the forecasts behind it, we construct each portfolio from explicit constraints and downside-risk criteria designed to keep it efficient across many plausible market environments, not just at a single estimated point.
• Capital Market Assumptions (CMAs): Our forward-looking return and volatility inputs come from Horizon Actuarial’s annual Survey of Capital Market Assumptions, an independent aggregation of forecasts from more than 40 institutional investment firms. We use the survey’s 20-year (long-horizon) averages, because our clients’ plans run in decades. The survey states its expected returns geometrically (as compound annual rates) and gross of fees. Some asset classes we hold are not covered by the survey, notably municipal bonds, aggregate bond sleeves, U.S. Treasury maturity segments, and short-duration TIPS. For those, we use the current yield to maturity of the corresponding benchmark index, because today’s yield is the most reliable forward estimate for a bond sleeve. We check all of these assumptions against long-run history as a reasonableness test, but the survey governs; we do not blend forecasts with historical averages. History is the weaker guide here: the past four decades included a long decline in interest rates and a large rise in equity valuations, and neither can simply repeat.
• Correlation Assumptions: We rely solely on long-term historical correlation data, as we find no credible evidence that asset class correlations can be forecast with any reliable degree of accuracy. In our view, assumed changes in correlation structures often reflect noise, not signal.
• Classification Standards: We classify equity sectors using the Global Industry Classification Standard (GICS), the most widely used sector framework, so market segment exposure is measured consistently across accounts, models, and reports.

This disciplined methodology anchors our assumptions in empirical reality while incorporating current market conditions and consensus outlooks, providing a more robust foundation for long-term portfolio design.

Structural Constraints and Discipline

SPG’s portfolios are constructed with safeguards that reinforce consistency, reduce avoidable risks, and improve tax efficiency:

• Market Timing and Active vs. Passive Investing: We reject the premise of market timing and high-cost active management. The data is compelling: long-term studies show that passive strategies have often outperformed active management after fees and taxes. Additionally, markets are composed of millions of participants, each with their own incentives, emotions, and time horizons. That level of behavioral and informational chaos is inherently unpredictable, and we don’t pretend otherwise.
• Asymmetric Risk Awareness: We recognize that large drawdowns require disproportionately large gains to recover (for example, a 50% loss requires a 100% gain just to break even). This foundational principle drives our emphasis on diversification and downside risk management disciplines.
• Automated Rebalancing: Portfolios are rebalanced systematically (not subjectively) when holdings drift a set distance from their targets, avoiding emotional decision-making or arbitrary timing.

Global Diversification and Practical Constraints

We intentionally avoid excessive home-country bias and thus our model portfolios are globally diversified by default. U.S. equity exposure is implemented via direct indexing for tax efficiency and customization, while international equities and other asset classes are accessed through ETFs selected for low cost and tracking accuracy.

We apply a number of practical constraints grounded in real-world considerations, for example (but not limited to):

• Risk-Return Tradeoffs: Our aggressive model holds 90% equities instead of 100%. In backtests spanning four decades, the return cost of the 10% reserve is small, roughly 0.3% annually, while the reserve provides a rebalancing reservoir deployable into equities during severe declines, and it helps guard against the far larger and permanent cost of abandoning an all-equity portfolio at the bottom. We accept a small, bounded reduction in expected return to shrink an unbounded behavioral risk. Backtested figures in this document are hypothetical, carry the limitations described in Appendix A, and do not represent any client account.
• Fixed Income Design: In taxable accounts, we cap municipal bond exposure at ~60%. Beyond that threshold, the marginal tax-adjusted benefit declines while diversification is compromised, so the remainder is allocated to traditional core fixed income. Where a model’s entire fixed income sleeve is too small to divide without creating positions too small to matter, as in the aggressive taxable model, the cap yields and a single municipal holding is used.
• Global Fixed Income Allocation: Hedged international bonds serve one purpose in our models: they are the only fixed income in the lineup not issued or backed by the U.S. government, in portfolios that otherwise lend most of their fixed income to that same government. We size this hedge at roughly 5-8% of the fixed income sleeve where that sleeve is large (conservative and moderate) and omit it where ballast is too small to divide (aggressive). The backtested cost of holding it is approximately zero; its benefit, a buffer in a U.S.-specific rate or fiscal event, is by nature absent from historical samples. Currency hedging is deliberate: it keeps this sleeve steady enough for conservative portfolios, and it means this sleeve responds to interest-rate differences abroad rather than to swings in the dollar.
• Asset Class Inclusion: Every position must have a defined function and be large enough to affect portfolio outcomes. High-yield bonds are excluded from all models: in calm markets they behave like bonds, but in a crisis they fall alongside stocks, failing as a diversifier exactly when one is needed. Standard volatility measures miss this, making them look safer than they are. In taxable accounts, tax-inefficient instruments such as TIPS, Treasuries, and commodities are retained only where their function cannot be replicated tax-efficiently, with the cost quantified and accepted explicitly.
• Market Weights and Eligibility: Equity sleeves hold global market-capitalization weights across an eligible universe rather than discretionary country tilts. Eligibility rests on a single criterion: we do not hold assets whose ownership claim a government can override at will, because that risk is uninsurable and diversification cannot fix confiscation. Under this criterion, China is excluded. Foreign claims on Chinese companies rest on structures the state has repeatedly subordinated to policy goals, from the contractual proxies used by offshore-listed firms to abrupt regulatory action against entire listed sectors. Russia sits outside the investable index universe. This is an eligibility rule, not a market forecast. Excluded markets are re-tested each June against structural criteria (enforceable foreign ownership and court-upheld minority protections), never against price action, and we expect this policy to look unrewarding during rallies in excluded markets. Emerging-market exposure in eligible countries is held at market weight in models whose scale and risk tolerance support it. Our U.S. and developed sleeves are all-cap. The emerging sleeve is large and mid cap, because no ex-China emerging fund covers small caps at a cost we would accept. Emerging small caps are roughly 1% of a model’s equities, and we revisit this each June.

Model Portfolios and Construction

We offer three core model portfolios (Conservative, Moderate, and Aggressive) with both taxable and tax-deferred variants.

Targeted top-level allocations are:

• Conservative: 20% equities / 80% fixed income, alternatives, and cash
• Moderate: 60% equities / 40% fixed income, alternatives, and cash
• Aggressive: 90% equities / 10% fixed income, alternatives, and cash

We find complexity offers diminishing returns and disproportionately increased overhead; these models account for the vast majority of investment-related financial planning needs.

Portfolio optimization inputs include:

• 20-year CMAs on expected returns and volatility
• Historical volatility and correlations
• Tax-efficiency and liquidity characteristics of each asset class
• Behavioral tolerance for volatility within each risk profile

We benchmark each asset class to an appropriate index so we can monitor how closely each holding follows it.

Equity:

• Russell 3000 Index
• MSCI World ex USA IMI Index
• MSCI Emerging Markets ex China Index

Fixed Income:

• Bloomberg US Treasury 1–3 Year Index
• Bloomberg US Treasury 3–10 Year Index
• Bloomberg US Aggregate Bond Index
• S&P National AMT-Free Municipal Bond Index
• S&P Short Term National AMT-Free Municipal Bond Index
• Bloomberg Global Aggregate ex-USD Hedged Index
• Bloomberg US Treasury TIPS 0-5 Year Index
• Bloomberg US Treasury Inflation-Linked Bond Index (Series-L)

Alternatives:

• Bloomberg Commodity Index

Cash Equivalents:

• Bloomberg 1–3 Month U.S. Treasury Bill Index

Optimization and Implementation

Each June, SPG CMAs are updated and model portfolios are re-evaluated within our constraint-based framework; optimization tools inform, but do not override, the structural rules described in this document. The June review also re-tests our market-eligibility criteria, our watch list of jurisdictions with weak shareholder protections, and the current yields behind our derived assumptions. Optimization occurs within explicit constraints derived from what each portfolio must be able to withstand (maximum tolerable drawdown, income reserves, inflation protection, and rate-shock tolerance) and prioritizes downside-risk measures such as the Sortino ratio and conditional value-at-risk rather than the Sharpe ratio, which treats upside and downside volatility identically and systematically understates credit and tail risk. Our capital market assumptions are stated gross of fees; client-facing return projections (including the retirement planner) and reported performance are shown net of SPG’s 1.00% annual advisory fee and underlying fund expenses. For optimization and Monte Carlo simulation we use the arithmetic-mean equivalents of the geometric expected returns, consistent with standard practice. Our inflation assumption is the survey’s expected long-term inflation, currently about 2.4%.

U.S. Equity via Direct Indexing

U.S. equities are implemented through Altruist’s U.S. All-Cap Direct Index model, which holds the index’s individual stocks directly in client accounts rather than through a fund:

• Coverage: ~3,000 U.S. stocks (tracks the Russell 3000 Index)
• Fees: Up to 0.15% annually proportional to the account’s equity allocation, included in SPG’s fee
• Tax Sensitivity: Daily loss harvesting, lot-level control, and wash-sale monitoring across accounts held at Altruist
• Execution: Automated, fractional-share trading with real-time drift monitoring and no transaction fees

ETF Implementation for Non-U.S. Exposure

Non-U.S. equity, global fixed income, and alternatives are implemented using ETFs selected for:

• Low expense ratios
• Tight index tracking
• Issuer stability

Tax Management Overlay

Taxable portfolios incorporate:

• Automated tax-loss harvesting (via Altruist’s TaxIQ)
• Placing assets in the account types where they’re taxed least
• Municipal bond prioritization in fixed income

Liquidity as a Structural Requirement

SPG core portfolios exclude illiquid investments such as private equity, venture capital, private real estate, hedge funds, or interval funds. While these assets may offer appealing return profiles under certain circumstances, they are fundamentally incompatible with the transparent operational design of SPG and its structural generosity program.

Illiquid investments often carry higher fees, delayed reporting, and limited exit flexibility, all of which conflict with our core investment principles: transparency, cost-efficiency, and client-first alignment.

Liquidity is not merely a portfolio management preference: it is a structural requirement. Our model relies on a transparent, recurring, and scalable billing process to redirect a percentage of gross advisory revenue to public good. Illiquid or irregularly priced assets create valuation ambiguity and administrative friction that undermine both client experience and our philanthropic infrastructure.

By limiting our core portfolios to daily-liquid public market instruments, primarily ETFs and direct indexing, we preserve operational integrity so our charitable commitments can be met reliably.

Fiduciary Oversight

All portfolios are supported by comprehensive documentation:

• Quarterly statements for performance and tax efficiency
• Client-specific Investment Policy Statement (IPS) compliance
• Operational and audit readiness

Summary

SPG’s investment methodology integrates academic rigor, automation, and structural safeguards to build resilient, tax-aware portfolios that reflect our core principles: disciplined implementation, inclusive wealth-building, and a fairer economic system.

Our approach is built to pursue long-term success in real markets for real people.

Appendix A: Model Portfolio Composition and Historical Backtesting (Net of Fees)

The tables below present composition and backtested historical performance data for SPG’s three core model portfolios: Conservative, Moderate, and Aggressive, each in both taxable and tax-deferred configurations. Columns without a (Taxable) label show the tax-deferred versions.

Model Portfolio Composition

Asset Class	Conservative	Conservative (Taxable)	Moderate	Moderate (Taxable)	Aggressive	Aggressive (Taxable)
US Equity (Direct Index)	14.0%	14.0%	39.0%	39.0%	58.5%	58.5%
International Developed	6.0%	6.0%	15.5%	15.5%	23.0%	23.0%
Emerging Markets (ex-China)	—	—	5.5%	5.5%	8.5%	8.5%
Short-Term Treasuries	5.0%	—	—	—	—	—
Intermediate Treasuries	37.0%	18.0%	16.0%	8.5%	6.0%	—
US Core Bonds	12.0%	—	8.0%	—	—	—
International Bonds (Hedged)	5.0%	5.0%	3.0%	—	—	—
Short-Term Municipal	—	11.0%	—	—	—	—
Intermediate Municipal	—	37.0%	—	21.5%	—	6.0%
Short-Term TIPS	6.0%	8.0%	3.0%	6.0%	—	—
Intermediate TIPS	14.0%	—	6.0%	—	—	—
Broad Commodities	—	—	3.0%	3.0%	3.0%	3.0%
Cash	1.0%	1.0%	1.0%	1.0%	1.0%	1.0%
Total	100.0%	100.0%	100.0%	100.0%	100.0%	100.0%

Model Descriptions:

• Conservative: Built for stability first: shorter horizons, a low tolerance for decline, or the portion of a plan that cannot afford a deep drawdown when the money is needed soon. The portfolio holds 20% equities and 80% fixed income organized by function: a reserve of roughly three years of withdrawals in short-duration holdings, a large U.S. Treasury allocation that has historically risen in equity crises, and inflation-protected securities guarding long-term purchasing power. In our backtest covering the 2007 to 2009 crash, this mix fell about 14% at its deepest point. In our 30-year simulations it supported a 3.3% annual withdrawal in 90% of outcomes. Stability has a price: over long horizons, the growth-oriented models have historically sustained higher spending, so this model’s job is steadiness when time or tolerance is short.
• Moderate: Built for investors who need growth and moderation together: multi-decade horizons with meaningful spending along the way, including many investors drawing on their portfolios, for whom continued growth matters as much as stability. This 60/40 portfolio pairs a market-capitalization equity engine with a fixed income sleeve organized by function: Treasuries for crisis rebalancing, inflation-protected securities for purchasing power, and commodities for environments in which stocks and bonds fall together. In our backtest covering the 2007 to 2009 crash, this mix fell about 34% at its deepest point. Recovery from declines that size has historically taken years, not months.
• Aggressive: This 90/10 portfolio is built for long horizons, whether accumulation years or a multi-decade retirement, and for investors who can stay invested through severe declines. In our backtest covering the 2007 to 2009 crash, this mix fell about 50% at its deepest point. The 10% reserve exists to be spent at the bottom: a Treasury allocation that has historically risen in equity crises funds rebalancing into depressed markets, and a small commodities sleeve addresses inflation-led environments.

The backtest below is intended to demonstrate the real-world behavior of each model over full market cycles. The full window deliberately includes the 2008 financial crisis and the 2022 bond bear market, the two hardest tests in modern market data.

Historical Backtesting (Net of Fees)

	Conservative	Conservative (Taxable)	Moderate	Moderate (Taxable)	Aggressive	Aggressive (Taxable)
CAGR, last 10 years (net of fees)	3.14%	3.40%	7.89%	7.99%	11.23%	11.29%
CAGR, full window (net of fees)	3.67%	3.61%	6.05%	6.02%	7.51%	7.48%
Standard Deviation (annualized)	4.93%	4.60%	10.15%	10.20%	14.67%	14.77%
Best Year	11.14%	11.16%	21.73%	22.79%	29.98%	30.70%
Worst Year	−12.07%	−9.40%	−22.90%	−24.17%	−36.21%	−37.01%
Maximum Drawdown	−14.47%	−12.66%	−33.86%	−34.45%	−49.81%	−50.30%