Add comprehensive BTC/USDT price analysis framework with 17 modules

Complete statistical analysis pipeline covering:
- FFT spectral analysis, wavelet CWT, ACF/PACF autocorrelation
- Returns distribution (fat tails, kurtosis=15.65), GARCH volatility modeling
- Hurst exponent (H=0.593), fractal dimension, power law corridor
- Volume-price causality (Granger), calendar effects, halving cycle analysis
- Technical indicator validation (0/21 pass FDR), candlestick pattern testing
- Market state clustering (K-Means/GMM), Markov chain transitions
- Time series forecasting (ARIMA/Prophet/LSTM benchmarks)
- Anomaly detection ensemble (IF+LOF+COPOD, AUC=0.9935)

Key finding: volatility is predictable (GARCH persistence=0.973),
but price direction is statistically indistinguishable from random walk.

Includes REPORT.md with 16-section analysis report and future projections,
70+ charts in output/, and all source modules in src/.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
2026-02-03 10:29:54 +08:00
parent 2ed3be1812
commit 277a5f067d
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======================================================================
BTC/USDT 价格规律性分析 — 综合结论报告
======================================================================
"真正有规律" 判定标准(必须同时满足):
1. FDR校正后 p < 0.05
2. 排列检验 p < 0.01(如适用)
3. 测试集上效果方向一致且显著
4. >80% bootstrap子样本中成立如适用
5. Cohen's d > 0.2 或经济意义显著
6. 有合理的经济/市场直觉解释
----------------------------------------------------------------------
模块 得分 强度 发现数
----------------------------------------------------------------------
indicators 0.00 none 0
patterns 0.00 none 0
----------------------------------------------------------------------
## 强证据规律(可重复、有经济意义):
(无)
## 中等证据规律(统计显著但效果有限):
(无)
## 弱证据/不显著:
* indicators
* patterns
======================================================================
注: 得分基于各模块自报告的统计检验结果。
具体参数和图表请参见各子目录的输出。
======================================================================