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Filter impact lenses

UPDATED 2026-07-25

Filter impact lenses are the three ways a screener backtest reports what a single filter contributed: On its own, Added in sequence, and If removed. They appear in the Which filters earn their place table — one row per filter, expandable into the full six-horizon breakdown. The three lenses answer three different questions and, critically, are not measured on the same scale: one is a return, two are differences. Reading one as if it were another is the single most common way to misjudge a filter.

What each of the three lenses measures

LensThe question it answersWhat the number is
On its own"How did this filter's own picks do?"an average annualized return — a level, shown as a percentage, with no other filter and no benchmark subtracted
Added in sequence"What did adding this filter change, at its place in the chain?"a difference — the change from the filters before it in the screener's order to the same set with it, in percentage points (pp)
If removed"What would dropping this filter cost?"a difference — the full filter set minus the same set with this one filter taken out, in percentage points (pp)

Why the three percentages are not comparable

On its own is a return; the other two are differences. A filter reading +14.2% on its own and +0.3 pp added in sequence is not contradicting itself: the first says its own picks averaged a 14.2% annualized return, the second says it moved the screener 0.3 points when stacked onto the filters above it. Subtracting, ratioing, or ranking across the two columns is meaningless.

The two differences use different baselines. Added in sequence is measured against the filters that come before it, so it depends on filter order — the same filter can look large in first position and near-zero in last, because whatever it excludes may already have been excluded. If removed is measured against the complete set, so it does not depend on order; it is the honest "what do I lose by deleting this" figure and it is the one the table leads with, under the header "Removing it would cost you…".

A negative If removed means removal would help. Because the lens is "full set minus set-without-it", a negative value says the screener performed better without that filter over the period. Those rows are tinted in the destructive (red) style so a filter that is actively costing you is visible without reading the number.

Defaults in Fincanva

  • The table's lead column is the If removed lens, drawn as a bar diverging from a centre line — right for positive, left for negative, widths scaled to the largest magnitude in the table.
  • One horizon at a time drives the lead column, chosen from the same six horizons; the selector opens on 12 months.
  • Expanding a filter's row reveals the full grid: six horizons × the three lenses, so a filter can be strong at one horizon and weak at another.
  • The On its own column carries the sub-label "raw return" precisely because it is not a delta.
  • A value that cannot be computed shows "—" rather than a zero.

Worked example

A screener holds three filters and the third one looks weak. Expanded at the 12-month horizon, its row reads: On its own +9.8%, Added in sequence +0.2 pp, If removed −1.1 pp.

Read across the row rather than down a column. On its own, the filter's picks averaged a 9.8% annualized return — respectable in isolation, and it says nothing about the screener. Added in sequence, it moved the screener by only 0.2 points once the two filters above it had already narrowed the field, so most of what it excludes was excluded already. If removed is negative: the full three-filter screener trailed the two-filter version by 1.1 annualized points, meaning this filter cost the screener rather than helping it, and its row is tinted red. Notice that the third figure — not the flattering first one — is the one about this screener.

These figures describe what a screener's matches would have done on historical data, not what they will do. Fincanva provides no financial advice — see Is this financial advice?.

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Fincanva provides no financial advice. Backtests show what would have happened — not what will.

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