research: clean up closed Tier-1 scaffolding from branch

Drop intermediate history-depth reports, sector-residual runners/map/code hooks
(evidence stays in final reports + docs), and slim MacBook helper to ssl/earnings/
prod-book-matrix only. SSL bootstrap and archived research conclusions retained.

tests/unit/test_backtest_service.py

@@ -100,75 +100,6 @@ def test_residual_momentum_removes_market_beta_but_keeps_specific_drift():
     assert drift["mom_12_1_resid"] > pure["mom_12_1_resid"] + 0.12
 
 
-def test_sector_residual_momentum_two_factor():
-    """Pure market+sector beta stock → sector resid ~0; idiosyncratic drift kept."""
-    dates, pure_beta, highs, benchmark = _signal_test_series(extra_return=0.0)
-    # Sector ETF = leveraged market (collinear-ish but not identical).
-    sector = {d: benchmark[d] * 1.02 + 0.5 for d in dates}
-    # Stock with pure exposure to market + sector, no alpha.
-    closes = [100.0]
-    for i in range(1, len(dates)):
-        m_prev = benchmark[dates[i - 1]]
-        m_cur = benchmark[dates[i]]
-        s_prev = sector[dates[i - 1]]
-        s_cur = sector[dates[i]]
-        m_ret = m_cur / m_prev - 1.0
-        s_ret = s_cur / s_prev - 1.0
-        closes.append(closes[-1] * (1.0 + 0.7 * m_ret + 0.5 * s_ret))
-    highs_p = [c * 1.01 for c in closes]
-
-    pure = bt._signal_values(
-        dates, closes, highs_p, 260, benchmark, sector_etf_closes=sector
-    )
-    assert "mom_12_1_sector_resid" in pure
-    assert pure["mom_12_1_sector_resid"] == pytest.approx(0.0, abs=0.05)
-
-    # Add idiosyncratic drift — sector residual should keep it.
-    drift_closes = [100.0]
-    for i in range(1, len(dates)):
-        m_prev = benchmark[dates[i - 1]]
-        m_cur = benchmark[dates[i]]
-        s_prev = sector[dates[i - 1]]
-        s_cur = sector[dates[i]]
-        m_ret = m_cur / m_prev - 1.0
-        s_ret = s_cur / s_prev - 1.0
-        drift_closes.append(
-            drift_closes[-1] * (1.0 + 0.7 * m_ret + 0.5 * s_ret + 0.0008)
-        )
-    drift_highs = [c * 1.01 for c in drift_closes]
-    drift = bt._signal_values(
-        dates, drift_closes, drift_highs, 260, benchmark, sector_etf_closes=sector
-    )
-    assert drift["mom_12_1_sector_resid"] > pure["mom_12_1_sector_resid"] + 0.10
-
-
-def test_inject_sector_demeaned_momentum():
-    collected = {
-        "mom_12_1": {
-            (2024, 1): [
-                {"val": 0.20, "fwd": 0.01, "symbol": "AAA"},
-                {"val": 0.10, "fwd": 0.02, "symbol": "BBB"},
-                {"val": 0.40, "fwd": -0.01, "symbol": "CCC"},
-                {"val": 0.00, "fwd": 0.03, "symbol": "DDD"},
-            ]
-        }
-    }
-    symbol_to_sector = {
-        "AAA": "Information Technology",
-        "BBB": "Information Technology",
-        "CCC": "Energy",
-        "DDD": "Energy",
-    }
-    bt._inject_sector_demeaned_momentum(collected, symbol_to_sector)
-    dem = collected["mom_12_1_sector_demeaned"][(2024, 1)]
-    by_sym = {r["symbol"]: r["val"] for r in dem}
-    # IT mean = 0.15 → AAA +0.05, BBB -0.05; Energy mean = 0.20 → CCC +0.20, DDD -0.20
-    assert by_sym["AAA"] == pytest.approx(0.05)
-    assert by_sym["BBB"] == pytest.approx(-0.05)
-    assert by_sym["CCC"] == pytest.approx(0.20)
-    assert by_sym["DDD"] == pytest.approx(-0.20)
-
-
 def test_assigns_raw_and_residual_percentiles_independently():
     cands = [
         {"iso_week": (2026, 1), "momentum": 0.10, "residual_momentum": 0.30},