Paper: arXiv 2603.03213

Authors: Ashwin Alankar, Allan Maymin, Philip Maymin, Myron Scholes, Sujiang Zhang

Abstract

The Total Portfolio Approach and Strategic Asset Allocation are widely viewed as competing frameworks for institutional portfolio management. We argue they differ in a single governance parameter: the tracking error constraint. Using U.S. equity and bond data from 2000 to 2026, with portfolio simulations spanning 2004 to 2026, we show that Sharpe ratios are statistically indistinguishable across the full constraint spectrum while the volatility of realized tracking error varies approximately 12-fold. The cost of constraints spikes during crises, when forward returns are richest and governance pressure to de-risk is strongest. Dynamic tracking error subsumes both approaches and provides boards with a more productive framework for investment governance.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 6.0/10 (capped from 7.5: transaction costs not modelled; no out-of-sample test; see penalty flags)
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a strong synthesis of institutional governance theory and empirical asset allocation using U.S. market data spanning 2000-2026. It formalizes theoretical propositions on dynamic tracking error while evaluating long-horizon portfolio simulations and crisis-period constraint costs.

Research Flowchart

  flowchart TD
    A[Research Goal: Evaluate TPA vs. SAA Governance Frameworks] --> B[Data Inputs: US Equities & Bonds 2000-2026]
    B --> C[Methodology: Simulate Portfolios across Tracking Error Constraints 2004-2026]
    C --> D[Analysis: Compare Sharpe Ratios & Realized Tracking Error Volatility]
    D --> E[Key Finding 1: Sharpe Ratios Indistinguishable; Tracking Error Vol Varies ~12x]
    D --> F[Key Finding 2: Constraint Costs Spike in Crises During High Forward Returns]
    E & F --> G[Outcome: Dynamic Tracking Error Subsumes TPA & SAA for Better Governance]