crates/aura-analysis/src/lib.rs

@@ -100,12 +100,15 @@ pub struct RMetrics {
     pub sqn_normalized: f64,
     pub net_expectancy_r: f64, // mean(R - cost_in_r) folded from the cost-model stream; == gross when empty
     pub conviction_terciles_r: [f64; 3], // E[R] by conviction_at_entry tercile (asc); <3 trades -> [0,0,0]
-    /// Realised R per closed trade, in trade order — an in-memory conduit for the
-    /// OOS R-series bootstrap. Excluded from serde (`skip`) so the C18 wire
-    /// shape is unchanged, and from `PartialEq` (below) so every existing
+    /// Cost-netted realised R per closed trade (`r − cost_in_r`), in trade
+    /// order — an in-memory conduit for the OOS R-series bootstrap. Equals
+    /// the gross series bit-for-bit when no cost model is bound (an empty
+    /// cost stream is the documented gross-R baseline: cost `0.0` per
+    /// trade). Excluded from serde (`skip`) so the C18 wire shape is
+    /// unchanged, and from `PartialEq` (below) so every existing
     /// `RMetrics`/`RunReport` equality assertion and round-trip stays green.
     #[serde(skip)]
-    pub trade_rs: Vec<f64>,
+    pub net_trade_rs: Vec<f64>,
 }
 
 impl PartialEq for RMetrics {
@@ -122,7 +125,7 @@ impl PartialEq for RMetrics {
             && self.sqn_normalized == o.sqn_normalized
             && self.net_expectancy_r == o.net_expectancy_r
             && self.conviction_terciles_r == o.conviction_terciles_r
-        // trade_rs deliberately excluded
+        // net_trade_rs deliberately excluded
     }
 }
 
@@ -229,7 +232,7 @@ pub fn summarize_r(
             sqn_normalized: 0.0,
             net_expectancy_r: 0.0,
             conviction_terciles_r: [0.0; 3],
-            trade_rs: Vec::new(),
+            net_trade_rs: Vec::new(),
         };
     }
     let rs: Vec<f64> = trades.iter().map(|t| t.r).collect();
@@ -277,6 +280,10 @@ pub fn summarize_r(
     // an empty stream is the gross-R baseline — every trade's cost is 0.0).
     let net_sum: f64 = trades.iter().map(|t| t.r - t.cost).sum();
     let net_expectancy_r = net_sum / n as f64;
+    // The per-trade net series the OOS bootstrap conduit carries (#259). A
+    // separate materialization, deliberately NOT factored through `net_sum`:
+    // that expression's tokens are byte-pinned (see the SQN note above).
+    let net_rs: Vec<f64> = trades.iter().map(|t| t.r - t.cost).collect();
     // conviction terciles: sort by conviction_at_entry ascending, split into three contiguous
     // near-equal-count buckets (floor boundaries i*n/3), E[R] per bucket. < 3 trades -> 0s.
     let conviction_terciles_r = if n < 3 {
@@ -311,7 +318,7 @@ pub fn summarize_r(
         sqn_normalized,
         net_expectancy_r,
         conviction_terciles_r,
-        trade_rs: rs,
+        net_trade_rs: net_rs,
     }
 }
 
@@ -324,7 +331,8 @@ pub fn summarize_r(
 /// `summarize_r_includes_open_trade_and_matches_r_metrics_from_rs` — touch one copy
 /// without the other and that test is the sole tripwire. The
 /// fields a flat R series cannot carry are set honestly: `n_open_at_end = 0`,
-/// `net_expectancy_r = expectancy_r` (exact under the cost = 0 invariant),
+/// `net_expectancy_r = expectancy_r` (exact: the input series is already
+/// cost-netted — the conduit carries `r − cost_in_r`),
 /// `conviction_terciles_r = [0,0,0]` (per-trade conviction is not pooled). Empty
 /// input -> a well-defined all-zero `RMetrics`.
 pub fn r_metrics_from_rs(rs: &[f64]) -> RMetrics {
@@ -334,7 +342,7 @@ pub fn r_metrics_from_rs(rs: &[f64]) -> RMetrics {
             expectancy_r: 0.0, n_trades: 0, win_rate: 0.0, avg_win_r: 0.0,
             avg_loss_r: 0.0, profit_factor: 0.0, max_r_drawdown: 0.0,
             n_open_at_end: 0, sqn: 0.0, sqn_normalized: 0.0, net_expectancy_r: 0.0,
-            conviction_terciles_r: [0.0; 3], trade_rs: Vec::new(),
+            conviction_terciles_r: [0.0; 3], net_trade_rs: Vec::new(),
         };
     }
     let sum: f64 = rs.iter().sum();
@@ -375,9 +383,9 @@ pub fn r_metrics_from_rs(rs: &[f64]) -> RMetrics {
         n_open_at_end: 0,
         sqn,
         sqn_normalized,
-        net_expectancy_r: mean, // cost = 0 -> net == gross (frictionless)
+        net_expectancy_r: mean, // input series is already net -> net == mean
         conviction_terciles_r: [0.0; 3],
-        trade_rs: Vec::new(),
+        net_trade_rs: Vec::new(),
     }
 }
 
@@ -832,6 +840,30 @@ mod tests {
         assert!((m.net_expectancy_r - 0.0).abs() < 1e-12);
     }
 
+    /// Property (#259): the bootstrap conduit `net_trade_rs` carries the
+    /// COST-NETTED per-trade R (`r − cost_in_r`) in trade order — the same
+    /// per-trade values `net_expectancy_r` averages — while every gross
+    /// scalar stays cost-free. With an empty cost stream the conduit equals
+    /// the gross series bit-for-bit (cost 0.0 per trade), which is what
+    /// keeps uncosted campaigns byte-identical.
+    #[test]
+    fn summarize_r_net_trade_rs_is_the_cost_netted_series_in_trade_order() {
+        let c = 2.0_f64;
+        let record = vec![
+            (Timestamp(0), row14(true, 1.0, 100.0, 96.0, 1.0, false, 0.0)),
+            (Timestamp(1), row14(false, 0.0, 100.0, 98.0, 1.0, true, 0.5)),
+        ];
+        let cost = vec![
+            (Timestamp(0), vec![Scalar::f64(c / 4.0), Scalar::f64(c / 4.0), Scalar::f64(0.0)]),
+            (Timestamp(1), vec![Scalar::f64(0.0), Scalar::f64(c / 4.0), Scalar::f64(c / 2.0)]),
+        ];
+        let m = summarize_r(&record, &cost);
+        assert_eq!(m.net_trade_rs, vec![1.0 - 0.5, 0.5 - 1.0], "net conduit = r − cost, trade order");
+        assert!((m.expectancy_r - 0.75).abs() < 1e-12, "gross scalars stay cost-free");
+        let gross = summarize_r(&record, &[]);
+        assert_eq!(gross.net_trade_rs, vec![1.0, 0.5], "empty cost stream ⇒ conduit == gross series");
+    }
+
     // One PositionManagement dense record row for the derive tests: only the columns
     // derive_position_events reads (closed, direction, size, open) are set; the rest
     // default to 0. Distinct per-row timestamps (the derive keys events on the row's
@@ -949,7 +981,7 @@ mod tests {
                 sqn_normalized: 1.0,
                 net_expectancy_r: 0.4,
                 conviction_terciles_r: [-0.5, 0.5, 1.5],
-                trade_rs: Vec::new(),
+                net_trade_rs: Vec::new(),
             }),
         };
         let json = serde_json::to_string(&m).expect("serialize");
@@ -997,25 +1029,25 @@ mod tests {
     }
 
     #[test]
-    fn summarize_r_populates_trade_rs_in_trade_order() {
+    fn summarize_r_populates_net_trade_rs_in_trade_order() {
         // two closed trades (R = +2.0, then -1.0) over a minimal PositionManagement
-        // record; trade_rs must carry [2.0, -1.0] in trade order.
+        // record; net_trade_rs must carry [2.0, -1.0] in trade order.
         let rec = pm_record_two_closed_trades(); // helper below
         let m = summarize_r(&rec, &[]);
-        assert_eq!(m.trade_rs, vec![2.0, -1.0]);
+        assert_eq!(m.net_trade_rs, vec![2.0, -1.0]);
         assert_eq!(m.n_trades, 2);
     }
 
     #[test]
-    fn summarize_r_empty_record_has_empty_trade_rs() {
+    fn summarize_r_empty_record_has_empty_net_trade_rs() {
         let m = summarize_r(&[], &[]);
-        assert!(m.trade_rs.is_empty());
+        assert!(m.net_trade_rs.is_empty());
         assert_eq!(m.n_trades, 0);
     }
 
     /// Property: a position still open on the last row is folded into the trade
     /// ledger at its `unrealized_r` (a window-end trade), so `summarize_r`'s
-    /// `trade_rs` carries that synthetic open trade's R and `n_trades` counts it.
+    /// `net_trade_rs` carries that synthetic open trade's R and `n_trades` counts it.
     /// This is the one case where the two reducers' inputs differ in meaning — it
     /// is exactly the per-trade R series the OOS conduit hands `r_metrics_from_rs`,
     /// so the two must agree on the R-distribution arithmetic for an
@@ -1024,12 +1056,12 @@ mod tests {
     fn summarize_r_includes_open_trade_and_matches_r_metrics_from_rs() {
         let rec = pm_record_closed_then_open_at_end();
         let m = summarize_r(&rec, &[]);
-        assert_eq!(m.trade_rs, vec![2.0, 0.5]);
+        assert_eq!(m.net_trade_rs, vec![2.0, 0.5]);
         assert_eq!(m.n_trades, 2);
         assert_eq!(m.n_open_at_end, 1);
         // Feed the open-at-end pooled series through the flat reducer: the
         // R-distribution fields (the verbatim-copied arithmetic) must agree.
-        let pooled = r_metrics_from_rs(&m.trade_rs);
+        let pooled = r_metrics_from_rs(&m.net_trade_rs);
         assert_eq!(pooled.n_trades, m.n_trades);
         assert_eq!(pooled.expectancy_r, m.expectancy_r);
         assert_eq!(pooled.win_rate, m.win_rate);
@@ -1042,25 +1074,25 @@ mod tests {
     }
 
     #[test]
-    fn rmetrics_partial_eq_ignores_trade_rs() {
-        // two RMetrics equal in every metric but differing in trade_rs compare EQUAL
-        // (trade_rs is an in-memory conduit, excluded from equality) — this is what
-        // keeps serialize->deserialize round-trips equal (trade_rs is serde-skipped,
+    fn rmetrics_partial_eq_ignores_net_trade_rs() {
+        // two RMetrics equal in every metric but differing in net_trade_rs compare EQUAL
+        // (net_trade_rs is an in-memory conduit, excluded from equality) — this is what
+        // keeps serialize->deserialize round-trips equal (net_trade_rs is serde-skipped,
         // so it deserializes empty).
         let a = summarize_r(&pm_record_two_closed_trades(), &[]);
         let mut b = a.clone();
-        b.trade_rs = Vec::new();
+        b.net_trade_rs = Vec::new();
         assert_eq!(a, b);
     }
 
     #[test]
-    fn populated_trade_rs_is_absent_from_serialized_json() {
-        // the in-memory conduit must never reach the wire: a populated trade_rs is
+    fn populated_net_trade_rs_is_absent_from_serialized_json() {
+        // the in-memory conduit must never reach the wire: a populated net_trade_rs is
         // dropped by #[serde(skip)], so the C18 on-disk shape is byte-unperturbed (#139).
         let m = summarize_r(&pm_record_two_closed_trades(), &[]);
-        assert_eq!(m.trade_rs, vec![2.0, -1.0], "precondition: trade_rs is populated");
+        assert_eq!(m.net_trade_rs, vec![2.0, -1.0], "precondition: net_trade_rs is populated");
         let json = serde_json::to_string(&m).expect("RMetrics serializes");
-        assert!(!json.contains("trade_rs"), "trade_rs must not reach the wire: {json}");
+        assert!(!json.contains("net_trade_rs"), "net_trade_rs must not reach the wire: {json}");
     }
 
     /// A minimal dense PositionManagement record with two closed trades at R = +2, -1.

crates/aura-campaign/src/exec.rs

@@ -407,7 +407,7 @@ fn run_cell(
                 let bootstrap =
                     match families.iter().rev().find(|f| f.block == "std::walk_forward") {
                         Some(fam) => StageBootstrap::PooledOos(r_bootstrap(
-                            &pooled_trade_rs(&fam.reports),
+                            &pooled_net_trade_rs(&fam.reports),
                             *resamples as usize,
                             *block_len as usize,
                             seed,
@@ -423,7 +423,7 @@ fn run_cell(
                                         .metrics
                                         .r
                                         .as_ref()
-                                        .map(|r| r.trade_rs.as_slice())
+                                        .map(|r| r.net_trade_rs.as_slice())
                                         .unwrap_or(&[]);
                                     (
                                         *ordinal,
@@ -627,15 +627,15 @@ fn scalar_point(space: &[ParamSpec], point: &[Cell]) -> Vec<Scalar> {
     space.iter().zip(point).map(|(ps, c)| Scalar::from_cell(ps.kind, *c)).collect()
 }
 
-/// The pooled walk-forward OOS trade-R series: the family reports' `trade_rs`
+/// The pooled walk-forward OOS trade-R series: the family reports' `net_trade_rs`
 /// concatenated in report order — which IS roll order (the wf stage builds its
 /// family via `walkforward_member_reports`, per-window OOS reports in roll
 /// order). Reports without an R block contribute nothing.
-fn pooled_trade_rs(reports: &[RunReport]) -> Vec<f64> {
+fn pooled_net_trade_rs(reports: &[RunReport]) -> Vec<f64> {
     let mut pooled = Vec::new();
     for report in reports {
         if let Some(r) = &report.metrics.r {
-            pooled.extend_from_slice(&r.trade_rs);
+            pooled.extend_from_slice(&r.net_trade_rs);
         }
     }
     pooled

crates/aura-campaign/src/lib.rs

@@ -365,7 +365,7 @@ mod tests {
                     sqn: 13.0,
                     net_expectancy_r: 14.0,
                     conviction_terciles_r: [0.0; 3],
-                    trade_rs: Vec::new(),
+                    net_trade_rs: Vec::new(),
                 }),
             },
         }

crates/aura-campaign/tests/execute.rs

@@ -41,9 +41,9 @@ fn param_i64(params: &[(String, Scalar)], name: &str) -> i64 {
 
 /// The deterministic 4-trade R series a planted report carries (matches
 /// `n_trades: 4`; non-constant so block resampling has structure). In-memory
-/// only: `trade_rs` is serde-skipped and excluded from `PartialEq`, so every
+/// only: `net_trade_rs` is serde-skipped and excluded from `PartialEq`, so every
 /// existing equality and round-trip assertion stays green.
-fn planted_trade_rs(net: f64) -> Vec<f64> {
+fn planted_net_trade_rs(net: f64) -> Vec<f64> {
     vec![net, -net, 2.0 * net, net]
 }
 
@@ -84,7 +84,7 @@ fn planted_report(cell: &CellSpec, params: &[(String, Scalar)], window_ms: (i64,
                 sqn_normalized: net,
                 net_expectancy_r: net,
                 conviction_terciles_r: [0.0, 0.0, 0.0],
-                trade_rs: planted_trade_rs(net),
+                net_trade_rs: planted_net_trade_rs(net),
             }),
         },
     }
@@ -483,11 +483,11 @@ fn execute_mc_after_gate_bootstraps_each_survivor() {
     assert_eq!(mc.selection, None);
 
     // each survivor's bootstrap == a hand-called r_bootstrap on its planted
-    // trade_rs, seeded from the campaign doc (the deflation convention)
+    // net_trade_rs, seeded from the campaign doc (the deflation convention)
     let net = |fast: i64, slow: i64| (fast * 10 + slow) as f64 / 100.0;
     let expected = StageBootstrap::PerSurvivor(vec![
-        (2, r_bootstrap(&planted_trade_rs(net(3, 6)), 200, 2, 7)),
-        (3, r_bootstrap(&planted_trade_rs(net(3, 9)), 200, 2, 7)),
+        (2, r_bootstrap(&planted_net_trade_rs(net(3, 6)), 200, 2, 7)),
+        (3, r_bootstrap(&planted_net_trade_rs(net(3, 9)), 200, 2, 7)),
     ]);
     assert_eq!(mc.bootstrap, Some(expected));
 
@@ -513,15 +513,15 @@ fn execute_mc_after_wf_pools_the_oos_series() {
     assert_eq!(wf.block, "std::walk_forward");
     assert_eq!(wf.reports.len(), 2);
 
-    // pooled input = the wf family reports' trade_rs concatenated in report
+    // pooled input = the wf family reports' net_trade_rs concatenated in report
     // order (roll order per walkforward_member_reports)
     let mut pooled: Vec<f64> = Vec::new();
     for report in &wf.reports {
-        pooled.extend_from_slice(&report.metrics.r.as_ref().expect("planted R block").trade_rs);
+        pooled.extend_from_slice(&report.metrics.r.as_ref().expect("planted R block").net_trade_rs);
     }
     let net = (3 * 10 + 9) as f64 / 100.0;
-    let mut expected_pool = planted_trade_rs(net);
-    expected_pool.extend(planted_trade_rs(net));
+    let mut expected_pool = planted_net_trade_rs(net);
+    expected_pool.extend(planted_net_trade_rs(net));
     assert_eq!(pooled, expected_pool);
 
     let mc = &out.record.cells[0].stages[2];
@@ -677,7 +677,7 @@ fn execute_generalize_only_after_sweep() {
 /// annotators compose in ONE pipeline without disturbing each other or the
 /// population stages' generalize-nominee. `std::monte_carlo` sits between
 /// `std::walk_forward` and `std::generalize` in the pipeline, yet its
-/// per-cell bootstrap still pools exactly the wf family's OOS `trade_rs`
+/// per-cell bootstrap still pools exactly the wf family's OOS `net_trade_rs`
 /// (unaffected by generalize running after it), and `std::generalize`'s
 /// campaign-scope nominee is still the wf stage's last-window winner
 /// (unaffected by mc having annotated the cell first). A regression that
@@ -706,13 +706,13 @@ fn execute_mc_and_generalize_compose_in_one_pipeline() {
         assert_eq!(cell.stages[3].block, "std::monte_carlo");
     }
 
-    // mc's bootstrap pools the wf family's OOS trade_rs exactly as it does
+    // mc's bootstrap pools the wf family's OOS net_trade_rs exactly as it does
     // with no generalize stage after it (execute_mc_after_wf_pools_the_oos_series)
     let wf = &out.cells[0].families[1];
     assert_eq!(wf.block, "std::walk_forward");
     let mut pooled: Vec<f64> = Vec::new();
     for report in &wf.reports {
-        pooled.extend_from_slice(&report.metrics.r.as_ref().expect("planted R block").trade_rs);
+        pooled.extend_from_slice(&report.metrics.r.as_ref().expect("planted R block").net_trade_rs);
     }
     let expected_mc = StageBootstrap::PooledOos(r_bootstrap(&pooled, 200, 2, 7));
     assert_eq!(out.record.cells[0].stages[3].bootstrap, Some(expected_mc));

crates/aura-campaign/tests/member_seam_e2e.rs

@@ -125,7 +125,7 @@ fn rankable_metrics_are_all_per_member_resolvable() {
                 sqn: 13.0,
                 net_expectancy_r: 14.0,
                 conviction_terciles_r: [0.0; 3],
-                trade_rs: Vec::new(),
+                net_trade_rs: Vec::new(),
             }),
         },
     };

crates/aura-cli/src/main.rs

@@ -875,11 +875,11 @@ fn select_winner(
 /// (window order, then within-window trade order). Windows with no `r` block
 /// contribute nothing. The single home of the pooling-in-roll-order semantics —
 /// both the walk-forward `oos_r` summary and the `mc` R-bootstrap reduce this.
-fn pooled_oos_trade_rs(result: &WalkForwardResult) -> Vec<f64> {
+fn pooled_oos_net_trade_rs(result: &WalkForwardResult) -> Vec<f64> {
     result
         .windows
         .iter()
-        .flat_map(|w| w.run.oos_report.metrics.r.as_ref().map(|r| r.trade_rs.clone()).unwrap_or_default())
+        .flat_map(|w| w.run.oos_report.metrics.r.as_ref().map(|r| r.net_trade_rs.clone()).unwrap_or_default())
         .collect()
 }
 
@@ -888,14 +888,14 @@ fn pooled_oos_trade_rs(result: &WalkForwardResult) -> Vec<f64> {
 /// (C14).
 fn walkforward_summary_json(result: &WalkForwardResult) -> String {
     let total = result.stitched_oos_equity.last().map(|&(_, v)| v).unwrap_or(0.0);
-    let pooled_rs = pooled_oos_trade_rs(result);
+    let pooled_rs = pooled_oos_net_trade_rs(result);
     let mut obj = serde_json::json!({
         "windows": result.windows.len(),
         "stitched_total_pips": total,
         "param_stability": param_stability(result),
     });
     if result.windows.iter().any(|w| w.run.oos_report.metrics.r.is_some()) {
-        // RMetrics serializes its scalar fields (trade_rs is serde-skipped, so the
+        // RMetrics serializes its scalar fields (net_trade_rs is serde-skipped, so the
         // oos_r block is the clean R-metric summary of the pooled series).
         obj["oos_r"] = serde_json::to_value(r_metrics_from_rs(&pooled_rs))
             .expect("RMetrics serializes");
@@ -914,7 +914,7 @@ fn walkforward_summary_json(result: &WalkForwardResult) -> String {
 /// (e.g. `sma_signal.fast.length`) by the strategy's own param space, while
 /// `stop_length`/`stop_k` ride the risk regime unwrapped, so an exact-name match
 /// would miss the wrapped ones) through the same `MetricStats::from_values`; the
-/// `oos_r` block pools the per-window `trade_rs` through `r_metrics_from_rs`.
+/// `oos_r` block pools the per-window `net_trade_rs` through `r_metrics_from_rs`.
 /// Canonical JSON (C14).
 ///
 /// `axes` carries the invocation's raw axis names in argv order, followed by the
@@ -954,7 +954,7 @@ fn walkforward_summary_json_from_reports(reports: &[RunReport], axes: &[String])
         .collect();
     let pooled_rs: Vec<f64> = reports
         .iter()
-        .flat_map(|r| r.metrics.r.as_ref().map(|m| m.trade_rs.clone()).unwrap_or_default())
+        .flat_map(|r| r.metrics.r.as_ref().map(|m| m.net_trade_rs.clone()).unwrap_or_default())
         .collect();
     let mut obj = serde_json::json!({
         "windows": reports.len(),

crates/aura-cli/tests/research_docs.rs

@@ -5,7 +5,7 @@
 use std::path::{Path, PathBuf};
 
 mod common;
-use common::{ScratchGuard, ScratchPath, fresh_project};
+use common::{ScratchGuard, ScratchPath, fresh_project, fresh_project_with_data};
 
 /// A fresh, unique working directory for a process test that persists
 /// content-addressed documents under `./runs/` (so `aura process register`
@@ -1010,7 +1010,10 @@ fn register_process_doc(dir: &Path, file: &str, doc: &str) -> String {
 /// the RAW `param_space` names (`fast.length` / `slow.length` — see the
 /// naming note in the referential test above). `persist_taps`/`emit` are
 /// spliced verbatim (pass `""` for empty, `"\"family_table\""` etc.).
-fn campaign_doc_json(
+/// [`campaign_doc_json`] with the instrument spliced — the synthetic-archive
+/// e2e targets `SYMA` (tests/common/mod.rs) instead of the hardcoded GER40.
+fn campaign_doc_json_for(
+    instrument: &str,
     bp_id: &str,
     proc_id: &str,
     window: (i64, i64),
@@ -1022,7 +1025,7 @@ fn campaign_doc_json(
   "format_version": 1,
   "kind": "campaign",
   "name": "run-seam",
-  "data": {{ "instruments": ["GER40"], "windows": [ {{ "from_ms": {from}, "to_ms": {to} }} ] }},
+  "data": {{ "instruments": ["{instrument}"], "windows": [ {{ "from_ms": {from}, "to_ms": {to} }} ] }},
   "strategies": [ {{ "ref": {{ "content_id": "{bp_id}" }},
                     "axes": {{ "fast.length": {{ "kind": "I64", "values": [2, 4] }},
                               "slow.length": {{ "kind": "I64", "values": [8, 16] }} }} }} ],
@@ -1035,6 +1038,16 @@ fn campaign_doc_json(
     )
 }
 
+fn campaign_doc_json(
+    bp_id: &str,
+    proc_id: &str,
+    window: (i64, i64),
+    persist_taps: &str,
+    emit: &str,
+) -> String {
+    campaign_doc_json_for("GER40", bp_id, proc_id, window, persist_taps, emit)
+}
+
 /// An mc-bearing process: intrinsically valid AND (since the v2 executor) an
 /// executable pipeline shape — `sweep -> monte_carlo` annotates each sweep
 /// survivor. The two addressing-mode tests below run it over the [1, 2] 1970
@@ -1990,6 +2003,163 @@ fn campaign_run_real_e2e_sweep_gate_walkforward() {
     );
 }
 
+/// Property (#259): a campaign's cost block reaches the walk-forward →
+/// monte-carlo evidence chain — the pooled-OOS bootstrap resamples the
+/// COST-NETTED per-trade series, so the same matrix run with and without a
+/// cost block records DIFFERENT `pooled_oos` stats (today's bug: identical to
+/// every digit). Hostless: runs over the synthetic SYMA archive, no
+/// data-mount skip-guard.
+#[test]
+fn campaign_run_synthetic_e2e_cost_block_nets_the_pooled_oos_bootstrap() {
+    let (dir, _fixture) = fresh_project_with_data();
+    let runs_dir = dir.join("runs");
+    std::fs::remove_dir_all(&runs_dir).ok();
+    let _cleanup = ScratchGuard(vec![
+        ScratchPath::Dir(runs_dir.clone()),
+        ScratchPath::File(dir.join("netmc.process.json")),
+        ScratchPath::File(dir.join("gross.campaign.json")),
+        ScratchPath::File(dir.join("net.campaign.json")),
+    ]);
+    let bp_id = seed_blueprint(&dir, "campaign-run-netmc-seed");
+    let proc_id = register_process_doc(&dir, "netmc.process.json", WF_PROCESS_DOC);
+    // SYMA's synthetic archive spans 2024-01..08; Mar-01..Jun-30 (~17 weeks)
+    // gives the (14d, 7d, 7d) roller a comfortable tiling.
+    let base = campaign_doc_json_for(
+        "SYMA",
+        &bp_id,
+        &proc_id,
+        (1709251200000, 1719791999999),
+        "",
+        "",
+    );
+    // The costed twin: the SAME document plus a constant cost block — the
+    // only difference (the replacen pattern of the cost e2e siblings).
+    let with_cost = base.replacen(
+        "\"seed\": 7,",
+        "\"seed\": 7,\n  \"cost\": [ { \"constant\": { \"cost_per_trade\": 0.5 } } ],",
+        1,
+    );
+    assert_ne!(with_cost, base, "replacen must actually match the seed field");
+    write_doc(&dir, "gross.campaign.json", &base);
+    write_doc(&dir, "net.campaign.json", &with_cost);
+
+    // Both runs share the store (the cost-e2e sibling pattern) — the record
+    // line is read from each run's own stdout, so no isolation is needed.
+    let pooled = |doc: &str| -> serde_json::Value {
+        let (out, code) = run_code_in(&dir, &["campaign", "run", doc]);
+        assert_eq!(code, Some(0), "campaign run failed: {out}");
+        let line = out
+            .lines()
+            .find(|l| l.starts_with("{\"campaign_run\":"))
+            .expect("the always-on final campaign_run line");
+        let v: serde_json::Value = serde_json::from_str(line).expect("record parses");
+        v["campaign_run"]["cells"][0]["stages"][3]["bootstrap"]["pooled_oos"].clone()
+    };
+    let gross = pooled("gross.campaign.json");
+    let net = pooled("net.campaign.json");
+
+    let n_gross = gross["n_trades"].as_u64().expect("gross n_trades");
+    let n_net = net["n_trades"].as_u64().expect("net n_trades");
+    assert!(n_gross > 0, "the synthetic window must produce OOS trades: {gross}");
+    assert_eq!(
+        n_gross, n_net,
+        "cost is a feed-forward subtraction — it must not change the trade population"
+    );
+    let mean_gross = gross["e_r"]["mean"].as_f64().expect("gross mean");
+    let mean_net = net["e_r"]["mean"].as_f64().expect("net mean");
+    assert!(
+        mean_net < mean_gross,
+        "the costed bootstrap must resample the NET series (#259): gross {mean_gross} vs net {mean_net}"
+    );
+    let p_gross = gross["prob_le_zero"].as_f64().expect("gross prob_le_zero");
+    let p_net = net["prob_le_zero"].as_f64().expect("net prob_le_zero");
+    assert!(
+        p_net >= p_gross,
+        "a strictly-lower resample mean cannot lower prob_le_zero: gross {p_gross} vs net {p_net}"
+    );
+}
+
+/// Property (#259), the OTHER mc bootstrap input shape: with no
+/// `walk_forward` in the pipeline (`sweep -> monte_carlo`), each surviving
+/// sweep member gets its OWN bootstrap (`PerSurvivor`, keyed by ordinal) —
+/// a distinct code path from `PooledOos` above (`member_net_trade_rs` /
+/// `SweepPoint` in aura-registry, not the wf-family pooling in
+/// aura-campaign). That path must resample the same cost-netted
+/// `net_trade_rs` conduit: a cost block must shift EVERY surviving member's
+/// resampled mean down, never leave any member's bootstrap gross-identical.
+/// Hostless: runs over the synthetic SYMA archive, no data-mount skip-guard.
+/// The gated real-data sibling (`campaign_run_real_e2e_sweep_monte_carlo_per_survivor`)
+/// exercises this shape but never with a cost block, so it cannot pin this property.
+#[test]
+fn campaign_run_synthetic_e2e_cost_block_nets_the_per_survivor_bootstrap() {
+    let (dir, _fixture) = fresh_project_with_data();
+    let runs_dir = dir.join("runs");
+    std::fs::remove_dir_all(&runs_dir).ok();
+    let _cleanup = ScratchGuard(vec![
+        ScratchPath::Dir(runs_dir.clone()),
+        ScratchPath::File(dir.join("persurvivor.process.json")),
+        ScratchPath::File(dir.join("gross_ps.campaign.json")),
+        ScratchPath::File(dir.join("net_ps.campaign.json")),
+    ]);
+    let bp_id = seed_blueprint(&dir, "campaign-run-persurvivor-seed");
+    let proc_id = register_process_doc(&dir, "persurvivor.process.json", MC_PROCESS_DOC);
+    // Same SYMA window as the pooled-OOS sibling above — known to produce
+    // trades over the synthetic archive.
+    let base = campaign_doc_json_for(
+        "SYMA",
+        &bp_id,
+        &proc_id,
+        (1709251200000, 1719791999999),
+        "",
+        "",
+    );
+    let with_cost = base.replacen(
+        "\"seed\": 7,",
+        "\"seed\": 7,\n  \"cost\": [ { \"constant\": { \"cost_per_trade\": 0.5 } } ],",
+        1,
+    );
+    assert_ne!(with_cost, base, "replacen must actually match the seed field");
+    write_doc(&dir, "gross_ps.campaign.json", &base);
+    write_doc(&dir, "net_ps.campaign.json", &with_cost);
+
+    let per_survivor = |doc: &str| -> Vec<(u64, serde_json::Value)> {
+        let (out, code) = run_code_in(&dir, &["campaign", "run", doc]);
+        assert_eq!(code, Some(0), "campaign run failed: {out}");
+        let line = out
+            .lines()
+            .find(|l| l.starts_with("{\"campaign_run\":"))
+            .expect("the always-on final campaign_run line");
+        let v: serde_json::Value = serde_json::from_str(line).expect("record parses");
+        v["campaign_run"]["cells"][0]["stages"][1]["bootstrap"]["per_survivor"]
+            .as_array()
+            .expect("no walk_forward precedes: the PerSurvivor arm, not pooled_oos")
+            .iter()
+            .map(|pair| (pair[0].as_u64().expect("ordinal"), pair[1].clone()))
+            .collect()
+    };
+    let gross = per_survivor("gross_ps.campaign.json");
+    let net = per_survivor("net_ps.campaign.json");
+
+    assert_eq!(gross.len(), 4, "2x2 axes -> four surviving members: {gross:?}");
+    assert_eq!(gross.len(), net.len(), "cost must not change the surviving-member population");
+    for ((g_ord, g), (n_ord, n)) in gross.iter().zip(net.iter()) {
+        assert_eq!(g_ord, n_ord, "the two runs must enumerate members in the same ordinal order");
+        let n_trades_g = g["n_trades"].as_u64().expect("gross n_trades");
+        let n_trades_n = n["n_trades"].as_u64().expect("net n_trades");
+        assert!(n_trades_g > 0, "member {g_ord} must have produced trades: {g}");
+        assert_eq!(
+            n_trades_g, n_trades_n,
+            "member {g_ord}: cost is a feed-forward subtraction — it must not change the trade population"
+        );
+        let mean_g = g["e_r"]["mean"].as_f64().expect("gross mean");
+        let mean_n = n["e_r"]["mean"].as_f64().expect("net mean");
+        assert!(
+            mean_n < mean_g,
+            "member {g_ord}: the costed PerSurvivor bootstrap must resample the NET series (#259): gross {mean_g} vs net {mean_n}"
+        );
+    }
+}
+
 /// The campaign `data.bindings` override end to end (#231, 6b): the same
 /// seeded strategy, window, and seed run twice — bare (price<-close default)
 /// and with `price` rebound to the open column. Both exit 0; the realized

crates/aura-registry/src/lib.rs

@@ -505,8 +505,8 @@ fn closed_neighbourhood(i: usize, axis_lens: &[usize]) -> Vec<usize> {
     out
 }
 
-fn member_trade_rs(rep: &RunReport) -> &[f64] {
-    rep.metrics.r.as_ref().map(|r| r.trade_rs.as_slice()).unwrap_or(&[])
+fn member_net_trade_rs(rep: &RunReport) -> &[f64] {
+    rep.metrics.r.as_ref().map(|r| r.net_trade_rs.as_slice()).unwrap_or(&[])
 }
 
 /// Recompute the selected R metric from a trade-R slice (reuses the engine's
@@ -522,13 +522,13 @@ fn member_metric_from_rs(rs: &[f64], m: Metric) -> f64 {
     }
 }
 
-/// The centred best-of-K null-max distribution: each member's `trade_rs` is
+/// The centred best-of-K null-max distribution: each member's `net_trade_rs` is
 /// mean-subtracted (the no-edge null), then for each resample every member is
 /// moving-block-resampled (in odometer order, from a per-iteration seed) and the
 /// max recomputed metric across members is taken. Deterministic given `seed` (C1).
 fn null_best_of_k(family: &SweepFamily, m: Metric, n_resamples: usize, block_len: usize, seed: u64) -> Vec<f64> {
     let centred: Vec<Vec<f64>> = family.points.iter().map(|p| {
-        let rs = member_trade_rs(&p.report);
+        let rs = member_net_trade_rs(&p.report);
         if rs.is_empty() { return Vec::new(); }
         let mean = rs.iter().sum::<f64>() / rs.len() as f64;
         rs.iter().map(|x| x - mean).collect()
@@ -657,8 +657,8 @@ pub fn optimize_deflated(
         let null_max = null_best_of_k(family, m, n_resamples, block_len, seed);
         // Keep only the finite best-of-K draws. The null is *not computable* in two
         // degenerate cases: zero resamples (`null_max` empty), or no member carries
-        // `trade_rs` (every member's centred series is empty, so each iteration's
-        // best-of-K folds to `NEG_INFINITY`). The latter is reachable — `trade_rs`
+        // `net_trade_rs` (every member's centred series is empty, so each iteration's
+        // best-of-K folds to `NEG_INFINITY`). The latter is reachable — `net_trade_rs`
         // is `#[serde(skip)]`, so a family loaded back from the registry has empty
         // conduits even when its `r` block (hence `raw`) is finite. Filtering to
         // finite values collapses both into one "no usable null" branch, instead of
@@ -847,7 +847,7 @@ mod tests {
             sqn_normalized: sqn, // mirror sqn: only the rank-key wiring is under test here
             net_expectancy_r,
             conviction_terciles_r: [0.0, 0.0, 0.0],
-            trade_rs: Vec::new(),
+            net_trade_rs: Vec::new(),
         });
         rep
     }
@@ -1174,16 +1174,16 @@ mod tests {
         assert_eq!(ranked[0].metrics.total_pips, 3.0); // best-first within the family
     }
 
-    fn member(total_pips: f64, trade_rs: Vec<f64>) -> SweepPoint {
+    fn member(total_pips: f64, net_trade_rs: Vec<f64>) -> SweepPoint {
         // Every RMetrics field is derived from the R slice by `r_metrics_from_rs`
         // (the same arithmetic production members carry), then the per-trade
-        // `trade_rs` conduit is restored: `r_metrics_from_rs` empties it
-        // (`trade_rs: Vec::new()`), whereas a production member is built by
+        // `net_trade_rs` conduit is restored: `r_metrics_from_rs` empties it
+        // (`net_trade_rs: Vec::new()`), whereas a production member is built by
         // `summarize_r`, which RETAINS it — and `optimize_deflated`'s R arm
         // resamples exactly that conduit, so a fixture without it cannot reach
         // the R-arm path under test.
-        let mut r = aura_engine::r_metrics_from_rs(&trade_rs);
-        r.trade_rs = trade_rs;
+        let mut r = aura_engine::r_metrics_from_rs(&net_trade_rs);
+        r.net_trade_rs = net_trade_rs;
         SweepPoint {
             params: vec![],
             report: RunReport {
@@ -1219,7 +1219,7 @@ mod tests {
 
     #[test]
     fn optimize_deflated_winner_is_byte_identical_to_optimize() {
-        let fam = fixture_family_with_r(); // helper: ≥3 members, varied sqn_normalized + trade_rs
+        let fam = fixture_family_with_r(); // helper: ≥3 members, varied sqn_normalized + net_trade_rs
         for metric in ["total_pips", "sqn_normalized", "expectancy_r"] {
             let plain = optimize(&fam, metric).unwrap();
             let (defl, _) = optimize_deflated(&fam, metric, 200, 3, 7).unwrap();
@@ -1259,18 +1259,18 @@ mod tests {
         assert_eq!(sel.overfit_probability, Some(1.0), "(0+1)/(0+1) Laplace floor");
     }
 
-    /// Regression: a family whose members carry an `r` block but NO `trade_rs` —
+    /// Regression: a family whose members carry an `r` block but NO `net_trade_rs` —
     /// the serde-skipped state of a family `load`ed back from the registry — must
     /// NOT yield a `+inf` deflated score on the R arm with positive resamples. With
     /// no member contributing a centred series, every best-of-K draw is
     /// `NEG_INFINITY`; the finite-filter collapses this to the same degenerate floor
     /// as zero-resamples (`deflated_score == raw`, `overfit_probability == 1.0`).
     #[test]
-    fn optimize_deflated_no_trade_rs_floors_instead_of_infinity() {
+    fn optimize_deflated_no_net_trade_rs_floors_instead_of_infinity() {
         let mut fam = fixture_family_with_r();
         for p in &mut fam.points {
             if let Some(r) = p.report.metrics.r.as_mut() {
-                r.trade_rs.clear(); // mimic a serde-loaded member (trade_rs is #[serde(skip)])
+                r.net_trade_rs.clear(); // mimic a serde-loaded member (net_trade_rs is #[serde(skip)])
             }
         }
         let sel = optimize_deflated(&fam, "expectancy_r", 500, 3, 1).unwrap().1;

docs/design/INDEX.md

@@ -1564,11 +1564,13 @@ boundary is test-pinned on both sides), plus three new static guards
 (unanimous #200 triage): nothing flows out of them; filtering stays the gate's monopoly.
 `std::monte_carlo` bootstraps the stage's *incoming R-evidence* with one semantics,
 input-shaped by position — after a walk_forward, ONE `r_bootstrap` over the wf family's
-pooled per-window OOS `trade_rs` in roll order (`PooledOos`); after sweep/gates, one
-`r_bootstrap` per surviving member's fresh in-memory series (`PerSurvivor`, ordinals into
-the population family; a zero-trade member records the engine's defined all-zero
-degenerate) — seeded from the campaign doc's `seed` (C1; `trade_rs` is `#[serde(skip)]`,
-so annotators run in-executor or not at all). `std::generalize` executes at **campaign
+pooled per-window OOS `net_trade_rs` in roll order (`PooledOos`; #259 materialized this
+conduit as the cost-netted per-trade series `r − cost_in_r`, equal to the gross series
+bit-for-bit when no cost model is bound); after sweep/gates, one `r_bootstrap` per
+surviving member's fresh in-memory series (`PerSurvivor`, ordinals into the population
+family; a zero-trade member records the engine's defined all-zero degenerate) — seeded
+from the campaign doc's `seed` (C1; `net_trade_rs` is `#[serde(skip)]`, so annotators run
+in-executor or not at all). `std::generalize` executes at **campaign
 scope**: after all cells, per (strategy, window) the per-cell *nominees* (last wf
 window's OOS report, else the sweep winner; none on gate truncation) across instruments
 feed the shipped `generalization()` when ≥ 2 exist — divergent per-instrument winners