Rename IBKR research modules to canonical strategy names

Author: Pigbibi

research/README_stock_alpha.md

@@ -4,8 +4,8 @@
 
 1. 复用 `russell_1000_multi_factor_defensive` 的现有真实数据代理回测结果。
 2. 公平比较它和两个高弹性 ETF 策略：
-   - `hybrid_growth_income`
-   - `semiconductor_rotation_income`
+   - `tqqq_growth_income`
+   - `soxl_soxx_trend_income`
 3. 研究一个新的 price-only 进攻型个股候选：`qqq_plus_stock_alpha_v1`。
 
 ## 代码位置

…ch_pullback_cash_buffer_daily_overlay.py …st_qqq_tech_enhancement_daily_overlay.pyresearch/backtest_tech_pullback_cash_buffer_daily_overlay.py renamed to research/backtest_qqq_tech_enhancement_daily_overlay.py research/backtest_tech_pullback_cash_buffer_daily_overlay.py renamed to research/backtest_qqq_tech_enhancement_daily_overlay.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Research-only daily overlay backtest for tech_pullback_cash_buffer."""
+"""Research-only daily overlay backtest for qqq_tech_enhancement."""
 
 from __future__ import annotations
 
@@ -107,7 +107,7 @@ def load_baseline_spec(path: Path) -> BaselineSpec:
     return BaselineSpec(
         config=config,
         risk_on_exposure=float(payload["exposures"]["risk_on"]),
-        name="tech_pullback_cash_buffer_monthly_baseline",
+        name="qqq_tech_enhancement_monthly_baseline",
         config_payload=payload,
     )
 
@@ -117,7 +117,7 @@ def build_baseline_candidate(spec: BaselineSpec) -> v12.GeometryCandidate:
         spec.name,
         spec.config,
         risk_on_exposure=spec.risk_on_exposure,
-        note="Monthly baseline from canonical tech_pullback_cash_buffer; month-start chooses names, non-rebalance days are no-op.",
+        note="Monthly baseline from canonical qqq_tech_enhancement; month-start chooses names, non-rebalance days are no-op.",
     )
 
 
@@ -901,7 +901,7 @@ def write_summary_markdown(
     best_name = family_scores.loc[family_scores["family"] == "daily_name_level_trim_overlay"].head(1)
     best_combo = family_scores.loc[family_scores["family"] == "daily_portfolio_plus_name_overlay"].head(1)
     lines = [
-        "# cash_buffer_branch daily overlay research",
+        "# qqq_tech_enhancement daily overlay research",
         "",
         "## Baseline",
         f"- strategy={baseline_payload['name']}",

research/backtest_stock_alpha_suite.py

@@ -2,8 +2,8 @@
 """
 Cross-strategy comparison for:
 - russell_1000_multi_factor_defensive
-- hybrid_growth_income
-- semiconductor_rotation_income
+- tqqq_growth_income
+- soxl_soxx_trend_income
 - qqq_plus_stock_alpha_v1 (research-only)
 
 The script keeps the defensive baseline frozen, compares it fairly against the
@@ -62,14 +62,14 @@
 
 
 SAFE_HAVEN = "BOXX"
-HYBRID_SAFE_CASH = "CASH"
+TQQQ_GROWTH_SAFE_CASH = "CASH"
 OFFENSIVE_NAME = "qqq_plus_stock_alpha_v1"
 
 DEFENSIVE_NAME = "russell_1000_multi_factor_defensive"
-HYBRID_FULL_NAME = "hybrid_growth_income"
-HYBRID_NORMALIZED_NAME = "hybrid_growth_income_no_income"
-SEMICONDUCTOR_FULL_NAME = "semiconductor_rotation_income"
-SEMICONDUCTOR_NORMALIZED_NAME = "semiconductor_rotation_income_no_income"
+TQQQ_GROWTH_FULL_NAME = "tqqq_growth_income"
+TQQQ_GROWTH_NORMALIZED_NAME = "tqqq_growth_income_no_income"
+SOXL_SOXX_TREND_FULL_NAME = "soxl_soxx_trend_income"
+SOXL_SOXX_TREND_NORMALIZED_NAME = "soxl_soxx_trend_income_no_income"
 
 FULL_COMPARISON_LAYER = "full_strategy"
 NORMALIZED_COMPARISON_LAYER = "normalized"
@@ -573,7 +573,7 @@ def build_period_summary_rows(
                     benchmark_returns,
                     start=start,
                     end=end,
-                    safe_haven_symbols=(SAFE_HAVEN, HYBRID_SAFE_CASH),
+                    safe_haven_symbols=(SAFE_HAVEN, TQQQ_GROWTH_SAFE_CASH),
                     full_returns_reference=net_returns,
                 )
                 rows.append(
@@ -620,7 +620,7 @@ def compute_rolling_36m_capm_alpha(strategy_returns: pd.Series, benchmark_return
     )
 
 
-def run_hybrid_growth_income_backtest(
+def run_tqqq_growth_income_backtest(
     qqq_ohlc: pd.DataFrame,
     asset_returns: pd.DataFrame,
     *,
@@ -643,12 +643,12 @@ def run_hybrid_growth_income_backtest(
     entry_line_floor: float,
     entry_line_cap: float,
 ) -> tuple[pd.Series, pd.DataFrame, pd.Series]:
-    strategy_symbols = ["TQQQ", SAFE_HAVEN, "SPYI", "QQQI", HYBRID_SAFE_CASH]
+    strategy_symbols = ["TQQQ", SAFE_HAVEN, "SPYI", "QQQI", TQQQ_GROWTH_SAFE_CASH]
     index = asset_returns.index.intersection(qqq_ohlc.index)
     qqq_history = qqq_ohlc.loc[index].copy()
     returns = asset_returns.reindex(index).fillna(0.0)
     weights_history = pd.DataFrame(0.0, index=index, columns=strategy_symbols)
-    portfolio_returns = pd.Series(0.0, index=index, name=HYBRID_FULL_NAME)
+    portfolio_returns = pd.Series(0.0, index=index, name=TQQQ_GROWTH_FULL_NAME)
     turnover_history = pd.Series(0.0, index=index, name="turnover")
 
     current_weights: dict[str, float] = {SAFE_HAVEN: 1.0}
@@ -712,15 +712,15 @@ def run_hybrid_growth_income_backtest(
             SAFE_HAVEN: target_boxx_value,
             "SPYI": target_spyi_value,
             "QQQI": target_qqqi_value,
-            HYBRID_SAFE_CASH: reserved,
+            TQQQ_GROWTH_SAFE_CASH: reserved,
         }
         target_weights = {
             symbol: value / current_equity
             for symbol, value in target_values.items()
             if value > 1e-12 and current_equity > 0
         }
         if not target_weights:
-            target_weights = {HYBRID_SAFE_CASH: 1.0}
+            target_weights = {TQQQ_GROWTH_SAFE_CASH: 1.0}
 
         threshold_weight = rebalance_threshold_ratio
         rebalance_needed = any(
@@ -738,7 +738,7 @@ def run_hybrid_growth_income_backtest(
         portfolio_returns.at[next_date] = sum(
             weight * float(next_returns.get(symbol, 0.0))
             for symbol, weight in current_weights.items()
-            if symbol != HYBRID_SAFE_CASH
+            if symbol != TQQQ_GROWTH_SAFE_CASH
         )
         current_equity *= 1.0 + float(portfolio_returns.at[next_date])
 
@@ -748,7 +748,7 @@ def run_hybrid_growth_income_backtest(
     return portfolio_returns, weights_history, turnover_history
 
 
-def run_semiconductor_rotation_income_backtest(
+def run_soxl_soxx_trend_income_backtest(
     soxl_prices: pd.Series,
     asset_returns: pd.DataFrame,
     *,
@@ -772,7 +772,7 @@ def run_semiconductor_rotation_income_backtest(
     soxl_series = soxl_prices.loc[index].copy()
     returns = asset_returns.reindex(index).fillna(0.0)
     weights_history = pd.DataFrame(0.0, index=index, columns=strategy_symbols)
-    portfolio_returns = pd.Series(0.0, index=index, name=SEMICONDUCTOR_FULL_NAME)
+    portfolio_returns = pd.Series(0.0, index=index, name=SOXL_SOXX_TREND_FULL_NAME)
     turnover_history = pd.Series(0.0, index=index, name="turnover")
 
     current_weights: dict[str, float] = {SAFE_HAVEN: 1.0}
@@ -1367,7 +1367,7 @@ def build_strategy_runs(
     ).reindex(master_index)
     soxl_close = etf_frames["close"]["SOXL"].reindex(master_index)
 
-    hybrid_full_returns, hybrid_full_weights, hybrid_full_turnover = run_hybrid_growth_income_backtest(
+    hybrid_full_returns, hybrid_full_weights, hybrid_full_turnover = run_tqqq_growth_income_backtest(
         qqq_ohlc,
         etf_returns_matrix,
         starting_equity=full_account_equity,
@@ -1389,7 +1389,7 @@ def build_strategy_runs(
         entry_line_floor=1.02,
         entry_line_cap=1.08,
     )
-    hybrid_normalized_returns, hybrid_normalized_weights, hybrid_normalized_turnover = run_hybrid_growth_income_backtest(
+    hybrid_normalized_returns, hybrid_normalized_weights, hybrid_normalized_turnover = run_tqqq_growth_income_backtest(
         qqq_ohlc,
         etf_returns_matrix,
         starting_equity=normalized_account_equity,
@@ -1412,7 +1412,7 @@ def build_strategy_runs(
         entry_line_cap=1.08,
     )
 
-    semiconductor_full_returns, semiconductor_full_weights, semiconductor_full_turnover = run_semiconductor_rotation_income_backtest(
+    semiconductor_full_returns, semiconductor_full_weights, semiconductor_full_turnover = run_soxl_soxx_trend_income_backtest(
         soxl_close,
         etf_returns_matrix,
         starting_equity=full_account_equity,
@@ -1430,7 +1430,7 @@ def build_strategy_runs(
         income_layer_qqqi_weight=0.70,
         income_layer_spyi_weight=0.30,
     )
-    semiconductor_normalized_returns, semiconductor_normalized_weights, semiconductor_normalized_turnover = run_semiconductor_rotation_income_backtest(
+    semiconductor_normalized_returns, semiconductor_normalized_weights, semiconductor_normalized_turnover = run_soxl_soxx_trend_income_backtest(
         soxl_close,
         etf_returns_matrix,
         starting_equity=normalized_account_equity,
@@ -1524,17 +1524,17 @@ def build_strategy_runs(
     strategy_runs = [
         defensive_run,
         StrategyRun(
-            strategy_name=HYBRID_FULL_NAME,
-            display_name="hybrid_growth_income::full",
+            strategy_name=TQQQ_GROWTH_FULL_NAME,
+            display_name="tqqq_growth_income::full",
             comparison_layer=FULL_COMPARISON_LAYER,
             gross_returns=hybrid_full_returns,
             weights_history=hybrid_full_weights,
             turnover_history=hybrid_full_turnover,
             metadata={"research_group": "etf_full", "starting_equity": full_account_equity, "income_layer": "on"},
         ),
         StrategyRun(
-            strategy_name=SEMICONDUCTOR_FULL_NAME,
-            display_name="semiconductor_rotation_income::full",
+            strategy_name=SOXL_SOXX_TREND_FULL_NAME,
+            display_name="soxl_soxx_trend_income::full",
             comparison_layer=FULL_COMPARISON_LAYER,
             gross_returns=semiconductor_full_returns,
             weights_history=semiconductor_full_weights,
@@ -1552,17 +1552,17 @@ def build_strategy_runs(
             metadata={"research_group": "baseline", "group_normalization": "sector", "data_assumption": "official_monthly_v2_alias"},
         ),
         StrategyRun(
-            strategy_name=HYBRID_NORMALIZED_NAME,
-            display_name="hybrid_growth_income::no_income",
+            strategy_name=TQQQ_GROWTH_NORMALIZED_NAME,
+            display_name="tqqq_growth_income::no_income",
             comparison_layer=NORMALIZED_COMPARISON_LAYER,
             gross_returns=hybrid_normalized_returns,
             weights_history=hybrid_normalized_weights,
             turnover_history=hybrid_normalized_turnover,
             metadata={"research_group": "etf_normalized", "starting_equity": normalized_account_equity, "income_layer": "off"},
         ),
         StrategyRun(
-            strategy_name=SEMICONDUCTOR_NORMALIZED_NAME,
-            display_name="semiconductor_rotation_income::no_income",
+            strategy_name=SOXL_SOXX_TREND_NORMALIZED_NAME,
+            display_name="soxl_soxx_trend_income::no_income",
             comparison_layer=NORMALIZED_COMPARISON_LAYER,
             gross_returns=semiconductor_normalized_returns,
             weights_history=semiconductor_normalized_weights,

research/backtest_stock_alpha_v1_robustness.py

@@ -583,7 +583,7 @@ def evaluate_period_metrics(
         benchmark_returns,
         start=start,
         end=end,
-        safe_haven_symbols=(suite.SAFE_HAVEN, suite.HYBRID_SAFE_CASH),
+        safe_haven_symbols=(suite.SAFE_HAVEN, suite.TQQQ_GROWTH_SAFE_CASH),
         full_returns_reference=net_returns,
     )
     period_returns = slice_series_or_frame(net_returns, start, end).dropna()

…id_growth_continuous_scaling_followup.py …qq_growth_continuous_scaling_followup.pyresearch/backtest_hybrid_growth_continuous_scaling_followup.py renamed to research/backtest_tqqq_growth_continuous_scaling_followup.py research/backtest_hybrid_growth_continuous_scaling_followup.py renamed to research/backtest_tqqq_growth_continuous_scaling_followup.py

@@ -17,7 +17,7 @@
 if str(CURRENT_DIR) not in sys.path:
     sys.path.insert(0, str(CURRENT_DIR))
 
-import backtest_hybrid_growth_indicator_variants as base  # noqa: E402
+import backtest_tqqq_growth_indicator_variants as base  # noqa: E402
 import backtest_stock_alpha_suite as suite  # noqa: E402
 from us_equity_strategies.strategies.tqqq_growth_income import get_hybrid_allocation  # noqa: E402
 

…_hybrid_growth_idle_throttle_followup.py …st_tqqq_growth_idle_throttle_followup.pyresearch/backtest_hybrid_growth_idle_throttle_followup.py renamed to research/backtest_tqqq_growth_idle_throttle_followup.py research/backtest_hybrid_growth_idle_throttle_followup.py renamed to research/backtest_tqqq_growth_idle_throttle_followup.py

@@ -16,7 +16,7 @@
 if str(CURRENT_DIR) not in sys.path:
     sys.path.insert(0, str(CURRENT_DIR))
 
-import backtest_hybrid_growth_indicator_variants as base  # noqa: E402
+import backtest_tqqq_growth_indicator_variants as base  # noqa: E402
 import backtest_stock_alpha_suite as suite  # noqa: E402
 from us_equity_strategies.strategies.tqqq_growth_income import get_hybrid_allocation  # noqa: E402
 

…test_hybrid_growth_indicator_variants.py …cktest_tqqq_growth_indicator_variants.pyresearch/backtest_hybrid_growth_indicator_variants.py renamed to research/backtest_tqqq_growth_indicator_variants.py research/backtest_hybrid_growth_indicator_variants.py renamed to research/backtest_tqqq_growth_indicator_variants.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Research-only TQQQ / hybrid_growth_income indicator overlay study.
+"""Research-only TQQQ / tqqq_growth_income indicator overlay study.
 
 Goal:
 - keep the current hybrid growth attack logic as the baseline;
@@ -521,7 +521,7 @@ def build_summary_rows(strategy_runs: list[StrategyRun], benchmark_returns: pd.S
 
 
 def build_runtime_full_reference(qqq_ohlc: pd.DataFrame, asset_returns: pd.DataFrame) -> StrategyRun:
-    full_returns, full_weights, full_turnover = suite.run_hybrid_growth_income_backtest(
+    full_returns, full_weights, full_turnover = suite.run_tqqq_growth_income_backtest(
         qqq_ohlc,
         asset_returns,
         starting_equity=RUNTIME_FULL_STARTING_EQUITY,
@@ -545,8 +545,8 @@ def build_runtime_full_reference(qqq_ohlc: pd.DataFrame, asset_returns: pd.DataF
     )
     index = full_returns.index
     return StrategyRun(
-        strategy_name="hybrid_growth_income_runtime_full_reference",
-        display_name="hybrid_growth_income_runtime_full_reference",
+        strategy_name="tqqq_growth_income_runtime_full_reference",
+        display_name="tqqq_growth_income_runtime_full_reference",
         gross_returns=full_returns,
         weights_history=full_weights.reindex(index).fillna(0.0),
         turnover_history=full_turnover.reindex(index).fillna(0.0),
@@ -652,12 +652,12 @@ def build_markdown(summary: pd.DataFrame, recommendation: dict[str, object]) ->
     runtime_reference = focus.loc[focus["income_mode"] == "runtime_full_reference"].copy()
 
     lines = [
-        "# TQQQ / hybrid_growth_income indicator overlay review",
+        "# TQQQ / tqqq_growth_income indicator overlay review",
         "",
         "## Setup",
         "- Baseline signal: current QQQ MA200 + ATR staged TQQQ logic.",
         "- Main research set: attack-only normalization (`income_threshold_usd = 1e9`) so the idle-asset choice is visible.",
-        "- Runtime reference: current full `hybrid_growth_income` with income layer on.",
+        "- Runtime reference: current full `tqqq_growth_income` with income layer on.",
         "- Idle asset candidates: `CASH`, `BOXX`, `QQQ`.",
         "- Extra indicator gates are nested from simple to complex to avoid blind indicator stuffing.",
         "",

…brid_growth_position_scaling_followup.py …tqqq_growth_position_scaling_followup.pyresearch/backtest_hybrid_growth_position_scaling_followup.py renamed to research/backtest_tqqq_growth_position_scaling_followup.py research/backtest_hybrid_growth_position_scaling_followup.py renamed to research/backtest_tqqq_growth_position_scaling_followup.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Focused TQQQ position-scaling study on top of the existing hybrid attack sleeve."""
+"""Focused TQQQ position-scaling study on top of the existing TQQQ growth sleeve."""
 
 from __future__ import annotations
 
@@ -17,7 +17,7 @@
 if str(CURRENT_DIR) not in sys.path:
     sys.path.insert(0, str(CURRENT_DIR))
 
-import backtest_hybrid_growth_indicator_variants as base  # noqa: E402
+import backtest_tqqq_growth_indicator_variants as base  # noqa: E402
 import backtest_stock_alpha_suite as suite  # noqa: E402
 from us_equity_strategies.strategies.tqqq_growth_income import get_hybrid_allocation  # noqa: E402
 

research/configs/growth_pullback_tech_pullback_cash_buffer.json

@@ -6,7 +6,7 @@
 
 
 def load_module():
-    path = Path(__file__).resolve().parents[1] / 'research' / 'backtest_tech_pullback_cash_buffer_daily_overlay.py'
+    path = Path(__file__).resolve().parents[1] / 'research' / 'backtest_qqq_tech_enhancement_daily_overlay.py'
     spec = importlib.util.spec_from_file_location('backtest_cash_buffer_branch_daily_overlay_test', path)
     module = importlib.util.module_from_spec(spec)
     sys.modules[spec.name] = module
@@ -71,7 +71,7 @@ def test_result_export_not_empty(tmp_path):
     module = load_module()
     summary_path = tmp_path / 'summary.md'
     baseline_payload = {
-        'name': 'tech_pullback_cash_buffer',
+        'name': 'qqq_tech_enhancement',
         'family': 'tech_heavy_pullback',
         'exposures': {'risk_on': 0.8, 'soft_defense': 0.6, 'hard_defense': 0.0},
         'holdings_count': 8,
@@ -81,7 +81,7 @@ def test_result_export_not_empty(tmp_path):
         'benchmark_symbol': 'QQQ',
     }
     baseline_row = pd.Series({
-        'strategy': 'tech_pullback_cash_buffer_monthly_baseline',
+        'strategy': 'qqq_tech_enhancement_monthly_baseline',
         'CAGR': 0.25,
         'Max Drawdown': -0.2,
         'Information Ratio vs QQQ': 0.8,
@@ -129,4 +129,4 @@ def test_result_export_not_empty(tmp_path):
     )
 
     assert summary_path.exists() and summary_path.stat().st_size > 0
-    assert 'cash_buffer_branch daily overlay research' in summary_path.read_text(encoding='utf-8')
+    assert 'qqq_tech_enhancement daily overlay research' in summary_path.read_text(encoding='utf-8')