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Portfolio Strategy

SIGMA

Walk-forward

Signal-Integrated Global Macro Allocation

Rebalancing
Monthly
Universe
10 ETFs
As of
...

The Strategy

SIGMA (Signal-Integrated Global Macro Allocation) is a systematic strategy that allocates across 10 global asset-class ETFs spanning equities, fixed income, and commodities. Each month it decides, per asset class, whether to hold a long position or stand aside in cash.

The result is a long or flat allocation that adjusts monthly to changing conditions, aiming to stay invested in asset classes when the environment is supportive and reduce exposure when it is not. The model is fully rules-based with no discretionary input.

Walk-Forward Test Active Starting April 25, 2026, this strategy is being tested with market data in a walk-forward framework. All historical data before this date represents backtested performance. The vertical marker in the chart indicates the start of the walk-forward period.

How It Works

On the last trading day of each month, SIGMA re-evaluates every asset class with a quantitative model and sets the portfolio for the month ahead.

The model is built to avoid look-ahead bias so historical and live results stay comparable. The dashboard shows both backtested and out-of-sample performance. The shaded area marks April 25, 2026, the start of the walk-forward test. Data to the left is historical backtesting; data to the right is hypothetical out-of-sample performance.

10
ETF Universe
Binary
Long / Flat Signals
Monthly
Rebalancing

Simulation Settings

Set your start date and initial capital to configure your portfolio. SIGMA rebalances monthly across 10 global asset-class ETFs. Data is available from August 2002.

Model Performance

Drawdown

Peak-to-trough decline

Historical Allocation

Model Value
--
--
YTD Return
--
Benchmark SPY: -- (--)
Volatility (6M Lookback)
--
Sharpe Ratio
--
Excess return basis

Walk-Forward Performance

Since Apr 25, 2026
--
SIGMA Return
--
SPY B&H Return
--
Outperformance
--
Trading Days

Model Asset Class Allocation

Model ETF Allocation

Model Allocation

Hypothetical model weights for illustration only. Shown as of the latest data refresh. Model value: initial capital plus accumulated hypothetical returns.

Symbol Weight Price Shares Value
Loading holdings...

Performance Metrics

Sortino Ratio
--
Downside risk-adjusted
Max Drawdown
--
Peak to trough
Info Ratio
--
Active return
Beta
--
vs SPY
Calmar Ratio
--
Return/Max DD
VaR (95%)
--
Daily at risk
Downside Dev
--
Downside risk
Up Capture
--
Bull market
Down Capture
--
Bear market
Positive Months
--
Historical %

Walk-Forward Test Status

Walk-forward testing started April 25, 2026

Monthly rebalancing (next: --)

--
days to rebalance

Crisis Performance

Strategy behavior during major market downturns:

Crisis SIGMA SPY
2008 GFC---55%
2020 Covid---34%
2022 Bear---25%

SIGMA vs SPY Portfolio

Full backtest period comparison:

Metric SIGMA SPY
CAGR----
Volatility----
Sharpe Ratio----
Max Drawdown----

Strategy Health Monitor

Live drift detection and alpha decay tracking

Drift Detection

Detects structural shifts in performance

...
Drift level 0%
0% 50% watch 80% warn 100% alert

Alpha Decay Monitor

Risk-adjusted return, 12 vs 36 months

...
12M Sharpe
--
36M Sharpe
--
12M Alpha
--
Decay Slope
--

The left panel flags structural shifts in performance against expectations. The right panel compares recent risk-adjusted returns with the longer-run track record. A weakening trend points to a fading edge.

Statistical Validation

Before deployment, SIGMA was validated with a battery of standard statistical robustness tests. All tests used the fixed production strategy without post-hoc parameter tuning.

Permutation Test passed
p < 0.001

10,000 random allocation sequences tested. None matched the observed risk-adjusted return.

Bootstrap passed
CI: 1.21 – 2.21

10,000 bootstrap samples produce a 95% confidence interval for the Sharpe ratio entirely above zero.

Out-of-Sample passed
100% positive

Every out-of-sample split produced a positive Sharpe ratio, with a median of 1.60.

Noise Robustness passed
Monotonic

Performance degrades smoothly under added noise. The strategy retains a Sharpe above 1.3 even at 100% noise contamination.

Regime Stability passed
All regimes

Positive risk-adjusted returns across bull, bear, high-volatility, and low-volatility environments.

Benchmark Alpha passed
t > 5.8

Statistically significant alpha against all tested benchmarks: SPY, 60/40, equal-weight buy-and-hold, and SPY trend-following.

All tests conducted on the fixed production strategy. Past statistical performance does not guarantee future results.