audit/tables.md

Table Provenance

For each paper table: data source plus the audit pass that re-derived each cell from the underlying run metrics. Audited 2026-04-28 against commit a4bf9e6.

tab:final_personality_performance — Cross-market 6M summary (Appendix~\ref{appendix:additional_results})

• Source: Experiment 1 (US 6M and CN 6M) via comparison bundles
• Cells verified: return, MDD, baseline gap (= return − own-market EqW return), rank
• Status: ✓ all 10 rows verified

Market	Mandate	Run ID	return (%)	MDD (%)	Baseline gap	Rank
China	Fundamental Value	mp_fundamental_value_20260413_163905_878961	-0.00	4.06	-6.50	4
China	Macro Tactical	mp_macro_tactical_20260413_163905_878979	4.02	4.55	-2.48	2
China	Behavioral Momentum	mp_behavioral_momentum_20260413_163905_878974	-2.52	5.28	-9.02	5
China	Low-Volatility	mp_smart_beta_passive_20260413_163905_878984	0.30	2.62	-6.20	3
China	EqW	mp_equal_weight_index_20260413_163905_878987	6.50	6.25	0.00	1
U.S.	Fundamental Value	mp_fundamental_value_20260409_165131_876468	-4.73	6.14	-14.15	5
U.S.	Macro Tactical	mp_macro_tactical_20260409_165131_876505	3.42	4.40	-6.00	2
U.S.	Behavioral Momentum	mp_behavioral_momentum_20260409_165131_876499	1.54	4.40	-7.88	3
U.S.	Low-Volatility	mp_smart_beta_passive_20260409_165131_876510	0.70	2.03	-8.72	4
U.S.	EqW	mp_equal_weight_index_20260409_165131_876514	9.42	4.83	0.00	1

tab:case_study_footprint — Behavior footprint (Appendix~\ref{appendix:additional_results})

• Source: Experiment 1 via comparison bundles
• Cells verified: trades, avg turnover (%), avg cash (%), avg exposure (%)
• Status: ✓ all 10 rows verified (turnover and cash/exposure stored as fractions, displayed as percent)

Market	Mandate	Trades	Turnover	Cash	Exposure
China	Fundamental Value	90	1.01%	38.92%	61.08%
China	Macro Tactical	1777	5.60%	11.39%	88.61%
China	Behavioral Momentum	666	12.46%	52.12%	47.88%
China	Low-Volatility	85	0.44%	69.55%	30.45%
China	EqW	84	0.56%	1.38%	98.62%
U.S.	Fundamental Value	123	1.72%	70.56%	29.44%
U.S.	Macro Tactical	1763	3.48%	36.24%	63.76%
U.S.	Behavioral Momentum	513	10.92%	69.38%	30.62%
U.S.	Low-Volatility	27	0.28%	83.76%	16.24%
U.S.	EqW	63	0.45%	2.40%	97.60%

tab:behavior_validity — Sharpe + holding days (Appendix~\ref{appendix:additional_results})

• Source: Experiment 1
• Cells verified: trades (CN/US), avg holding days (CN/US), MDD (CN/US), Sharpe (CN/US)
• Status: ✓ all 5 rows verified (paper rounds holding days to 1 decimal: 11.82→11.8, 96.79→96.8, etc.)

tab:reproducibility — Full-run reproducibility (Section~\ref{sec:results}, Q4)

• Source: Experiments 1 and 2 (US 6M, R1 vs R2)
• Cells verified: R1 return, R2 return, ΔReturn, R1 trades, R2 trades, ΔTrades
• Status: ✓ all 5 rows verified

Mandate	R1 ret	R2 ret	ΔRet	R1 trades	R2 trades	ΔTrades
Equal-Weight	9.42	9.42	0.00	63	63	0
Macro Tactical	3.42	2.78	-0.64	1763	1817	+54
Behavioral Momentum	1.54	0.50	-1.04	513	512	-1
Low-Volatility	0.70	0.70	0.00	27	27	0
Fundamental Value	-4.73	-10.29	-5.56	123	126	+3

The 2pp doctrine-effect threshold quoted in the prose is derived from the ΔRet column above, not from any external benchmark.

tab:us_3m_backend_robustness — Default vs GPT-5.4 (Section~\ref{sec:results}, Q4)

• Source: Experiments 3 (default backend) and 4 (GPT-5.4) on US 3M
• Aggregator: derived/gpt54_robustness/backend_comparison.csv (also feeds fig:backend_robustness)
• Cells verified: return, MDD, trades, avg cash for each of 5 mandates × 2 backends
• Status: ✓ all 5 rows × 8 columns verified

Mandate	Default ret	GPT-5.4 ret	Default MDD	GPT-5.4 MDD	Default trades	GPT-5.4 trades	Default cash	GPT-5.4 cash
Fundamental Value	0.00	1.23	0.00	1.10	0	31	100.00%	95.21%
Behavioral Momentum	-0.90	4.77	1.08	1.40	513	621	91.06%	46.33%
Macro Tactical	-0.45	4.29	4.77	3.13	893	901	39.71%	17.31%
Low-Volatility	-2.44	-2.44	3.33	3.33	15	15	83.38%	83.38%
Equal-Weight	5.96	5.96	3.52	3.52	52	52	2.14%	2.14%

tab:us_3m_ablation_main / tab:us_3m_ablation — Mechanism ablation (Section~\ref{sec:results} + Appendix)

• Source: Experiment 3 (US 3M default backend; Full and Ablated variants per mandate)
• Cells verified: return, MDD, trades, avg cash for 8 variants
• Baseline gap: computed as return − 5.96 (EqW return on this window)
• Status: ✓ all 8 rows verified

Mandate / Variant	Run ID	Return	Baseline gap	MDD	Trades	Cash
Fundamental Value / Full	20260417_160942	0.00	-5.96	0.00	0	100.00%
Fundamental Value / No filter	20260417_191443	5.80	-0.16	2.10	611	20.72%
Behavioral Momentum / Full	20260417_220721	-0.90	-6.86	1.08	513	91.06%
Behavioral Momentum / No guardrails	20260418_004927	-0.75	-6.71	1.60	392	89.05%
Macro Tactical / Full	20260418_033940	-0.45	-6.41	4.77	893	39.71%
Macro Tactical / No tilt	20260418_072633	-0.33	-6.29	5.35	918	35.76%
Low-Volatility / Reference	20260418_110947	-2.44	-8.40	3.33	15	83.38%
Equal-Weight / Reference	20260418_111210	5.96	0.00	3.52	52	2.14%

tab:efficiency_ablation — Execution paths (Appendix)

• Source: Experiment 5 source doc docs/2026-03-23-cn-10tickers-6m-efficiency-ablation.md
• Cells verified: total runtime, speedup, LLM call count, total tokens, estimated cost (CNY), cache bundle counts, shared phase-one timing, phase-two mode
• Status: ✓ verified against source doc

tab:released_work_comparison — Related-work comparison (Section~\ref{sec:related})

• Source: Hand-coded from cited papers' reported scope (DeepFund, AMA, STOCKBENCH, InvestorBench, TradingAgents, FinMem, HedgeAgents)
• No backtest runs to verify against; the row for QuantArena (#assets=40, #days=226) is the sum of the two case-study universes (20 US + 20 CN tickers, 124 + 102 trading days).

tab:sector_style_universe — Universe matrix (Appendix)

• Source: universe/sector_style_universe.csv (40 rows: 20 US + 20 CN tickers, each tagged with sector and size-style cell)
• Status: the figure-generation scripts and the paper text both consume this same CSV, so the 5×4 grid in the table is by construction what the case studies trade.

tab:implementation_matrix — Implementation matrix (Appendix)

• Source: Hand-coded mapping of mandate → engine class / LLM role / signal sources / guardrails / diagnostics (no per-run artifact to verify).