Model Backtest is the tearsheet: select two or more models and see how each allocation would have performed. Read how the simulation works, then use the growth chart, drawdown track, monthly views, and a metrics table grouped into Return, Risk, Efficiency, and Consistency.
The comparison needs at least one model with a complete 100% allocation. If no model qualifies, the empty state distinguishes an empty library from incomplete saved models and offers Open Target Models. Finish an allocation there, then return to Model Backtest; the page remains available in Back history.
Getting a fair comparison
- Every curve is indexed from the latest common start date across the selected models, and runs to their earliest common end date, so no figure covers a period one of them lacks. The page names which model (and whether its price or weight history) pins the start. A model with young funds constrains everyone. Check the "Weights / Prices / Period" line under each column.
- Hiding a model with its legend chip only stops drawing that line. The window, and every number the table reports, follow the models you have selected. Untick one to widen the comparison.
- A model's version history is replayed exactly as you recorded it. Each dated version applies from its effective date, and a diamond marks every switch with the weights that changed.
- Extend back extrapolates early weights before a model's first version to lengthen the window. It is on by default at Max, and that stretch draws dashed; set it to Off to see recorded history only.
- The vs benchmark (a ticker or another model) draws as a dashed overlay and adds relative columns: excess CAGR, beta, tracking error, information ratio, up/down capture. Edit beside it opens whichever list feeds your current pick: your models on Target Models, or the comparison-ticker list in Settings → Charts.
Three ways to read the curve
The toggle above the chart switches what the y-axis measures. All three describe the same backtest over the same window.
- $: the growth of $10,000, the value the simulation actually tracks.
- %: cumulative return from the window start, which is the fair comparison when models start at different values.
- %/yr: annualized return so far, the per-year rate that compounds to the return at each date. It is the same figure the CAGR row reports, drawn as it settled, so a model that won on one early run shows its lead decaying rather than looking permanent.
Annualizing needs a year to mean anything. Three months of +8% is not +36%/yr. The %/yr curve therefore begins a year into the window, and the toggle is disabled outright on a window shorter than that. The drawdown track below is unaffected: it keeps measuring real declines from the true window start, including peaks set before the annualized curve begins.
Narrowing the comparison
Sleeve re-runs the backtest on one asset class of each model, renormalized to 100%. This lets you compare two models' bond sleeves head-to-head. Category does the same for one slice category, and combines with Sleeve. A model benchmark follows the same filter, so the comparison stays like-for-like. Explain outperformance decomposes the difference between two models by slice and ticker.
Reading the numbers
The Strengths / Trade-offs cards summarize, per model, which metrics it leads and where it trails the leader. This is the same best/worst ranking the table marks, in a sentence. Hover any metric there or in the table for its one-line definition, and see reading the backtest metrics for what each one is for and why two of them can disagree.
The performance and monthly-return tables are named keyboard regions. Tab to the table boundary and use Left/Right to scroll through model or month columns that do not fit at the current window width.
Underlines mark the best (and with 3+ models, worst) value per column; heat coloring is reserved for the risk-adjusted ratios.