This paper introduces Veripath’s proprietary global farmland allocation model, designed to help institutional investors evaluate and construct diversified farmland portfolios using a systematic, factor-based approach.
The model screens farmland markets across 18 jurisdictions using more than 20 quantitative and qualitative inputs, including historical returns, volatility, inflation sensitivity, governance risk, and market liquidity. These factors are translated into portfolio allocations through a weighted scoring system, with outputs stress-tested under multiple macroeconomic scenarios such as inflation, stagflation, and deflation.
A key differentiator is the use of productivity-adjusted pricing, which evaluates farmland based on cost per unit of output rather than price per acre. This framework identifies relative value across regions and captures a long-term convergence effect, generating incremental return potential as pricing gaps normalize over time.
The model also incorporates Monte Carlo simulation to assess the full distribution of potential outcomes, allowing investors to evaluate downside risk, return variability, and portfolio resilience under different economic regimes. This approach reflects the non-linear and regime-dependent nature of farmland returns, which differ meaningfully across inflationary and deflationary environments.
By combining factor-based scoring, scenario analysis, and productivity benchmarking, the framework provides a transparent and repeatable method for allocating capital across global farmland markets. The result is a portfolio construction approach that prioritizes capital preservation, inflation alignment, and risk-adjusted returns in an asset class that remains structurally under-allocated by institutional investors.