---
run_id: 17
date: "2026-03-11 10:01:44 UTC"
question: "multi-asset momentum extended validation, momentum statistical significance, regime-adaptive momentum, momentum with volatility overlay"
total_hypotheses: 21
confirmed: 0
rejected: 0
pending: 21
rounds: 10
---

# 研究迴圈報告 — Run #17

> 研究主題：multi-asset momentum extended validation, momentum statistical significance, regime-adaptive momentum, momentum with volatility overlay
> 產生時間：2026-03-11 10:01:44 UTC

## 執行摘要

本次研究迴圈共進行 **10** 輪，產生 **21** 個假說。
最高信心假說（confidence=0.9700）：
> At least one momentum variant has statistically significant positive returns after multiple testing correction

## 各輪摘要

| 輪次 | Agent 數 | 假說數 | 持續時間 | Token 用量 |
|------|----------|--------|----------|------------|
| R1 | 3 | 8 | — | — |
| R2 | 3 | 7 | — | — |
| R3 | 4 | 0 | — | — |
| R4 | 3 | 0 | — | — |
| R5 | 4 | 0 | — | — |
| R6 | 3 | 5 | — | — |
| R7 | 2 | 1 | — | — |
| R8 | 2 | 0 | — | — |
| R9 | 2 | 0 | — | — |
| R10 | 2 | 0 | — | — |

## 假說清單

### Round 1

- ⏳ **[statistical-power]** (confidence=0.9500)
  6-year data window has sufficient statistical power to detect realistic momentum Sharpe ratios
- ⏳ **[multiple-testing]** (confidence=0.9700)
  At least one momentum variant has statistically significant positive returns after multiple testing correction
- ⏳ **[regime-dependency]** (confidence=0.9300)
  Momentum strategy performance is consistent across market regimes
- ⏳ **[factor-attribution]** (confidence=0.9200)
  Momentum strategy generates genuine alpha beyond factor exposures
- ⏳ **[selection-bias]** (confidence=0.9500)
  The SPY/TLT/GLD asset universe was selected a priori, not because it performed best
- ⏳ **[bootstrap-validation]** (confidence=0.9000)
  Bootstrap confidence intervals for Sharpe ratio exclude zero
- ⏳ **[gold-bias]** (confidence=0.8800)
  The GLD-driven momentum edge is robust and not a period-specific artifact
- ⏳ **[parameter-sensitivity]** (confidence=0.9000)
  Lookback period sensitivity indicates overfitting

### Round 2

- ⏳ **[statistical-power-by-frequency]** (confidence=0.9700)
  Different strategy frequencies have dramatically different statistical power with our 6-year dataset
- ⏳ **[testability-ranking]** (confidence=0.9200)
  Some strategy classes are far more testable than others with our specific dataset
- ⏳ **[overfitting-risk]** (confidence=0.9500)
  Overfitting risk scales exponentially with parameter count relative to sample size
- ⏳ **[failure-analysis]** (confidence=0.9300)
  All prior research failures share common root causes that can be systematically avoided
- ⏳ **[research-direction]** (confidence=0.8800)
  0DTE premium selling is the optimal next research direction given our dataset and prior failures
- ⏳ **[research-direction]** (confidence=0.8500)
  Daily implied volatility mean reversion provides a complementary research direction with strong testability
- ⏳ **[process-improvement]** (confidence=0.9600)
  Enforcing quantitative guardrails will prevent repeating past failures

### Round 6

- ⏳ **[None]** (confidence=0.0000)
  VRP strategy variant: VRP_BASE
- ⏳ **[None]** (confidence=0.0000)
  VRP strategy variant: VRP_SPREAD
- ⏳ **[None]** (confidence=0.0000)
  VRP strategy variant: VRP_WEEKLY
- ⏳ **[None]** (confidence=0.0000)
  VRP strategy variant: ALWAYS_SELL
- ⏳ **[None]** (confidence=0.0000)
  VRP strategy variant: VRP_REGIME

### Round 7

- ⏳ **[None]** (confidence=0.0000)
  VRP_REGIME strategy with Sharpe 3.00

## 錯誤日誌摘要

- **backtest_crash**: 1 次

最近錯誤：

- [backtest_crash] Script ic_0dte_backtest.py timed out after 120s

## 方法評分

| Agent | 方法 | 成功率 | 提出數 | 確認數 | 樣本數 |
|-------|------|--------|--------|--------|--------|
| risk-auditor | statistical-power | 0.00% | 1 | 0 | 1 |
| risk-auditor | multiple-testing | 0.00% | 1 | 0 | 1 |
| risk-auditor | regime-dependency | 0.00% | 1 | 0 | 1 |
| risk-auditor | factor-attribution | 0.00% | 1 | 0 | 1 |
| risk-auditor | selection-bias | 0.00% | 1 | 0 | 1 |
| risk-auditor | bootstrap-validation | 0.00% | 1 | 0 | 1 |
| risk-auditor | gold-bias | 0.00% | 1 | 0 | 1 |
| risk-auditor | parameter-sensitivity | 0.00% | 1 | 0 | 1 |
| risk-auditor | statistical-power-by-frequency | 0.00% | 1 | 0 | 1 |
| risk-auditor | testability-ranking | 0.00% | 1 | 0 | 1 |
| risk-auditor | overfitting-risk | 0.00% | 1 | 0 | 1 |
| risk-auditor | failure-analysis | 0.00% | 1 | 0 | 1 |
| risk-auditor | research-direction | 0.00% | 2 | 0 | 2 |
| risk-auditor | process-improvement | 0.00% | 1 | 0 | 1 |
| optimizer | general | 0.00% | 5 | 0 | 5 |
| devil | general | 0.00% | 1 | 0 | 1 |

## 建議與後續行動

- 21 個假說仍待驗證，可增加輪次或手動檢視。
- 最常見錯誤類型為 **backtest_crash**（1 次），建議優先修復。