Portfolio Signal Tearsheet — rank_day_20
Strategy: lagging_indecies
• This report maps realized portfolio contributions to the signal’s quantile buckets.
What is this?
How to read this page
This is an ex-post attribution page. It answers: given the actual realized weights,
constraints, execution and costs, which signal quantile buckets contributed to portfolio returns?
Use the Signal diagnostics page to see ex-ante predictiveness (IC / forward returns).
contrib_ret_ls: Realized portfolio contribution: (top bucket contrib − bottom bucket contrib).
contrib_ret_by_q: Realized portfolio contribution per quantile bucket in return space.
cost_pnl_by_q: Estimated costs per bucket (commission/fees + slippage proxy when available).
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Contribution by Quantile
Return space: w(t−1) × r(t)
Interpretation: if the signal is working and portfolio construction is aligned, higher quantiles
should contribute more (or at least L–S should be positive for long-top/short-bottom designs).
Summary
Totals by bucket
| total_contrib | avg_daily_contrib | |
|---|---|---|
| Q1 | 0.112688 | 0.000040 |
| Q2 | 0.029307 | 0.000010 |
| Q3 | 0.060467 | 0.000021 |
| Q4 | -0.007361 | -0.000003 |
| Q5 | 0.301453 | 0.000107 |
Costs by Quantile
Commission/fees + slippage proxy if available
| total_cost_drag | avg_daily_cost_drag | |
|---|---|---|
| Q1 | 0.002090 | 0.000001 |
| Q2 | 0.000081 | 0.000000 |
| Q3 | 0.000721 | 0.000000 |
| Q4 | 0.000071 | 0.000000 |
| Q5 | 0.002651 | 0.000001 |
Costs are shown in return space as
cost_pnl / equity (approx). For exact PnL attribution, extend the trade log with explicit slippage/borrow/financing components.
Generated by quantdsl_backtest • Portfolio tear sheet is ex-post: it reflects constraints, execution, and costs.