Using Economic Regimes to Inform a Rules-Based ETF Allocation

How much of a macro-regime allocation's return comes from its growth and inflation "season" scores, and how much from the price-based risk controls applied to them? This paper decomposes an economic-season allocation system that the author designed and introduced to a graduate student-managed investment fund at a US university. The evaluated account is a standalone managed sleeve backtest, separate from the live fund. The scores blend four baskets of exchange-traded funds (ETFs), and price rules set the holdings. Over April 2019-September 2026, which is out of sample for the season-basket coefficients, the selected-equity sleeve earned 21.57% a year net of modeled costs with a 16.23% maximum drawdown. At matched forecast risk over April 2017-September 2026 it led a risk-managed global equity account by 8.38 points a year. Most of this edge comes from the price-based layer. PV (price controls plus a volatility cap) holds the four baskets in equal shares under the same price-based controls. At equal forecast risk over April 2019-September 2026, the full system leads PV by 0.63 percentage points a year with selected equities and 0.20 with broad equities (95% intervals [-0.286, 1.739] and [-0.399, 0.984]), a lead concentrated in 2020-2022. For allocators, the price-based layer is the part to build first, and a matched-risk test against a price-based comparator built from the same baskets measures a macro overlay; here it caps the macro increment at about 1.7 points a year. The 2019-2026 record was studied during development, so the evidence is a historical reconstruction.