RAD-AA · A working paper in numbers

Regime-aware
dynamic asset
allocation.

A regime-aware strategy focused on the US market, investing through investable ETF exposures across U.S. equities, U.S. fixed income, U.S. real estate, commodities, gold, and cash. Walk-forward backtested across 2002–present after an initial 1970–2001 training/testing split.

This is a research portfolio project, not a live investment product: the goal is to demonstrate a full investment-research pipeline from data engineering and regime classification through portfolio construction, walk-forward testing, and risk controls.

Start here

In plain English: the model classifies five macro regimes, blends three portfolio construction engines, and de-risks when stress indicators become extreme.


As of 21 July 2026

Growth· day 410· panic -0.76σ · scalar 1.00

Model output from the research framework. Not a recommendation or managed portfolio.

Latest model allocation

  • IEF37.8%
  • SMH25.0%
  • IWD15.5%
  • SPY7.4%
  • DBC6.2%
  • GLD4.1%
  • IWF2.8%
  • IJR1.0%

Live-forward monitor · 2026 YTD

The framework was evaluated through 2025; 2026 results track model behaviour after the original evaluation window.

+17.32%

SPY: +14.46%+2.86 pts

CAGR

+8.43%

SPY: +9.47%-1.04 pts

Sharpe ratio

0.83

SPY: 0.58+0.25

Max drawdown

-23.47%

SPY: -59.22%+35.75 pts

§01Performance

What it returned, and at what cost.

Cumulative gross-of-tax, net-of-management-expense returns over the out-of-sample window. Drawdown shown alongside, because a return number without its loss-side companion is an incomplete picture.

Cumulative net return

Log-equivalent linear scale; benchmarks are gross (no fees). The Regime-Aware Ensemble nets a 50 bp/yr management expense.

Drawdown — underwater

Distance from each strategy’s running peak. The Regime-Aware Ensemble’s deepest drawdown was -23.5% versus the S&P's -59.2%.

Tear sheet · annualized

StrategyCAGRVolSharpeSortinoMax DDCalmarWin
Momentum Sleeve+13.80%26.21%0.620.88-48.81%0.2853.8%
HRP Risk-Balanced Sleeve+5.34%6.53%0.831.16-14.33%0.3754.7%
Entropy-Pooled MVO Sleeve+8.86%10.46%0.861.21-23.35%0.3854.9%
Regime-Aware Ensemble+8.43%10.40%0.831.17-23.47%0.3654.4%
SPY (gross)+9.47%18.79%0.580.81-59.22%0.1654.9%
60/40 (gross)+8.17%10.96%0.771.10-34.09%0.2455.3%

OOS · 6,091 business days · 2002-01-022026-07-21

§02Interpretation

What the evidence supports — and what it does not.

The historical results suggest that RAD-AA’s strongest contribution is not persistent raw return dominance, but improved risk-adjusted performance and drawdown control versus static equity exposure. The Regime-Aware Ensemble slightly trails SPY on CAGR over the full OOS window, while producing materially lower volatility, a higher Sharpe ratio, and a substantially smaller maximum drawdown.

The framework should therefore be interpreted as a regime-aware risk-allocation system rather than a pure return-maximization engine. Its value is in adapting exposures when macro conditions, stress indicators, and cross-asset relationships change.

The results do not prove persistent alpha, nor do they eliminate model risk. Backtests remain sensitive to design choices, asset availability, transaction assumptions, regime definitions, and the fact that future market regimes may differ from the historical sample. The purpose of the framework is to demonstrate a complete research process: regime classification, portfolio construction, risk overlays, walk-forward testing, and honest performance evaluation.

§03Risk discipline

How the strategy de-risks when the world goes wrong.

An aggregate panic Z-score over four EWMA-normalized stress components — equity vol, bond vol, equity-bond correlation breakdown, and curve-slope vol. When the score crosses +4σ, the strategy linearly de-levers; at +5.5σ it is fully in cash.

Panic Z-score · OOS

Solid line: aggregate panic. Amber: deleveraging threshold (+4σ). Terracotta: full-cash threshold (+5.5σ).


Crisis fingerprint

The five most extreme panic days in the OOS window all fall in one week — March 2020.

The crisis engine is deterministic and known in advance — no fitting, no ex-post tuning. The metric tracks what common sense would label as panic: through the week of 13–19 March 2020, the score sat above the full-cash threshold and the strategy held no risk assets.

Across 6,091 OOS days, the engine fully de-risked on 7 days and partially on 15.

Top 5 panic days

  1. 0119 March 20205.78σ
  2. 0212 March 20205.61σ
  3. 0326 March 20203.91σ
  4. 0419 September 20083.83σ
  5. 0514 April 20253.82σ
§04Composition

What it holds, and why it holds it.

The strategy is the regime-conditional blend of three portfolio construction sleeves. Each regime calls for a different mix; the table below states the weights.

Today · 2026-07-21

The blend in Growth regime.

  • IEF37.8%
  • SMH25.0%
  • IWD15.5%
  • SPY7.4%
  • DBC6.2%
  • GLD4.1%
  • IWF2.8%
  • IJR1.0%

Tight credit spreads, supportive curve. The strategy leans into risk via the HRP Risk-Balanced Sleeve (75%) and Momentum Sleeve (25%); the Entropy-Pooled MVO Sleeve stands down.

Regime-conditional ensemble

RegimeMomentum SleeveHRP Risk-Balanced SleeveEntropy-Pooled MVO Sleeve
Growth25%75%0%
Calm40%20%40%
Macro Stress10%20%70%
Inflation Shock25%35%40%
Crash0%0%100%

Regime classification · OOS

200420082012201620202024

Growth

32.6%

1,984 days

Calm

8.5%

518 days

Macro Stress

33.0%

2,012 days

Inflation Shock

9.4%

575 days

Crash

16.5%

1,002 days

§05Methodology

How it works.

The strategy is opinionated and short enough to describe end-to-end. Below, in six short sections, is the full pipeline.

05.01

Data foundation

Fifty-six years of daily total returns across fourteen tradable assets. Treasury proxies are constructed from FRED yields using par-bond duration and convexity. Gold is sourced from Stooq XAUUSD daily fixings with the GLD expense ratio deducted. Real estate uses NAREIT total-return history before VNQ's 2004 inception. Style and quality factors come from AQR's research data. All proxies are vol-scaled and mean-adjusted into the live ETFs once available, preserving cumulative return continuity across the splice.

05.02

Regime classification

A five-component Gaussian Mixture Model on z-scored macro features — real yield, curve slope, inflation pressure, credit spread, and lagged equity-stress measures. Components are labeled by their fitted centroid profile: Growth / Calm / Macro Stress / Inflation Shock / Crash. Inflation Shock separates inflation-and-rate pressure from broader macro stress; Crash is reserved for broad dislocation. The raw GMM classification is smoothed by a Continuous Statistical Jump Model overlay with a fixed transition penalty selected from the research diagnostics. Online Viterbi steps the regime forward each business day; full retrains happen only on a regime change.

05.03

Three portfolio sleeves

Momentum Sleeve — vol-conviction momentum across six sector ETFs (QQQ, SMH, XLE, XME, TLT, GLD), holding 100% in the asset with the strongest 126-day momentum gated by a 21-day-vol switching margin.
HRP Risk-Balanced Sleeve — top-N Hierarchical Risk Parity across nine assets, with a 50/50 blend of GJR-GARCH-shocked sample covariance and the regime prior, levered (or de-levered) to a regime-targeted volatility (12% / 10% / 8% / 7% / 6% in Growth/Calm/Macro Stress/Inflation Shock/Crash).
Entropy-Pooled MVO Sleeve — an eight-asset MVO sleeve using Meucci-style entropy pooling to separate return views from the historical covariance estimate, with regime-locked risk aversion and L2, a hard per-asset cap (35% per risky / 10% BIL), and an L1 turnover penalty against the prior day's drift.

05.04

Risk overlays

Two scalars sit between the optimizer and the executed allocation. The crisis scalar is a deterministic function of an aggregate panic Z-score (equity vol, bond vol, correlation breakdown, curve-slope vol; EWMA-normalized) — linear ramp from 1.0 at +4σ to 0.0 at +5.5σ. The LL-velocity mitigator blends the portfolio toward 1/N when the GMM's log-likelihood collapses, signalling that current macro is unprecedented relative to the training distribution.

05.05

Walk-forward, no look-ahead

At every point in the backtest, the model has access only to data published before that day. The macro engine retrains on every regime change using only the historical window up to the retrain date. No future information leaks into past allocations. Without walk-forward retraining, the backtest would be an over-fit illustration rather than a track record.

05.06

Pre-inception splicing

Five of the ten core ETFs list inside the OOS window: TLT and IEF (July 2002), VNQ (September 2004), GLD (November 2004), DBC (February 2006), and BIL (May 2007). Pre-listing returns for each are a synthetic proxy — FRED par-bond total return for bonds, Stooq XAUUSD for gold, NAREIT for real estate, T-Bill carry for cash — vol-scaled and mean-adjusted into the live ETF using a 756-day overlap window starting at inception. Because that calibration window sits after the listing date, the splice scaling is forward-looking from the proxy era's perspective. Roughly 5.5 of the 24 OOS years partly evaluate against spliced synthetic returns; from June 2007 onward, every asset is live. CPI is shifted forward 45 days to cover the BLS publication lag, and the four Momentum Sleeve sector extras (QQQ, SMH, XLE, XME) have no proxy and are excluded from the candidate universe before their respective inception dates.